STABILITY ANALYSIS IN ROSELLE (Hibiscus sabdariffa L.) S.JYOTHSNA

Transcription

1 STABILITY ANALYSIS IN ROSELLE (Hibiscus sabdariffa L.) S.JYOTHSNA B.Sc. (Ag.) MASTER OF SCIENCE IN ARICULTURE (ENETICS AND LANT BREEDIN) 2014

2 STABILITY ANALYSIS IN ROSELLE (Hibiscus sabdariffa L.) BY S.JYOTHSNA B.Sc. (Ag.) THESIS SUBMITTED TO THE ACHARYA N.. RANA ARICULTURAL UNIVERSITY IN ARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEREE OF MASTER OF SCIENCE IN ARICULTURE (ENETICS AND LANT BREEDIN) CHAIRERSON: Dr. A. AALA SWAMY DEARTMENT OF ENETICS AND LANT BREEDIN ARICULTURAL COLLEE, NAIRA ACHARYA N.. RANA ARICULTURAL UNIVERSITY 2014

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4 CERTIFICATE This is to certify that the thesis entitled STABILITY ANALYSIS IN ROSELLE (Hibiscus sabdariffa L.) submitted in partial fulfilment of the requirements for the degree of Master of Science in Agriculture of the Acharya N.. Ranga Agricultural University, Hyderabad, is a record of the bonafied original research work carried out by Ms. S. JYOTHSNA under our guidance and supervision. No part of the thesis has been submitted by the student for any other degree or diploma. The published part and all assistance received during the course of the investigations have been duly acknowledged by the author of the thesis. (To be signed at the time of Final Viva-voce) Thesis approved by the Student Advisory Committee Chairperson : Dr. A. AALA SWAMY Senior Scientist (lant Breeding) & Head Agricultural Research Station, Amadalavalasa Member : Dr. LAL AHAMED M. Assistant rofessor Department of enetics and lant Breeding Agricultural College, Bapatla Member : Dr. N. VENKATA LAKSHMI Assistant rofessor Department of Agronomy Agricultural College, Bapatla Date of Final Viva-voce:

5 CERTIFICATE Ms. S. JYOTHSNA has satisfactorily prosecuted the course of research and that the thesis entitled STABILITY ANALYSIS IN ROSELLE (Hibiscus sabdariffa L.) submitted is the result of original research work and is of sufficiently high standard to warrant its presentation to the examination. I also certify that the thesis or part thereof has not been previously submitted by her for a degree of any university. Date: lace: (Dr. A. AALASWAMY) Chairperson Senior Scientist (lant Breeding) & Head Agricultural Research Station Amadalavalasa

6 DECLARATION I, Ms. S. JYOTHSNA, hereby declare that the thesis entitled STABILITY ANALYSIS IN ROSELLE (Hibiscus sabdariffa L.), submitted to Acharya N.. Ranga Agricultural University for the degree of Master of Science in Agriculture in the major field of enetics and lant Breeding is the result of original research work done by me. I also declare that no material contained in the thesis has been published earlier in any manner. lace: Date: (S.JYOTHSNA) I.D. No.: NAM

7 ACKNOWLEDEMENTS It is by grace of Almighty, omnipotent blessings of my teachers and parents that I could accomplish and bring to light this humble piece of work. I humbly place on record my respect and profound sense of gratitude to the esteemed Chairman of my advisory committee, Dr. A. Appala Swamy, Senior Scientist (lant Breeding) and Head, Agricultural Research Station, Amadalavalasa, Chairman of my Advisory committee for his keen interest, scholarly counsel, constructive suggestions, boundless help and indefatigable guidance which provided me commendable encouragement and shaped my efforts into a successful research work. I cordially offer my unboundful gratitude to Dr. Lal Ahamed. M, Assistant rofessor (lant Breeding), Agricultural College, Bapatla, member of my Advisory committee for his encouragement in conducting research, valuable comments and meticulous reasoning to refine the dissertation and reckon with set standards during the course of investigation and preparation of the thesis. With a deep sense of reverence, I wish to express my sincere gratitude to Dr. N. Venakata Lakshmi, Assistant rofessor (Agronomy), Agricultural College, Bapatla, member of my Advisory committee for sparing her precious time and giving pragmatic suggestions during the course of my research work, which helped a lot in bringing the thesis to the present format. With a deep sense of reverence, I wish to express my sincere gratitude to Dr. M. Venku Naidu, Associate Dean, Agricultural College, Naira for his cooperation and valuable guidance throughout my research work. I deem it a great privilege to express my gratitude to Dr. J.S.V. Samba Murthy, Retired rofessor, Department of enetics and lant Breeding, Agricultural College, Bapatla for his unstinted attention, constant encouragement, valuable suggestions and generous help during my post graduation study and research work. I sincerely thank Dr. M. Reddi Sekhar, rofessor and Head, Dept. of enetics and lant Breeding, Agricultural College, Naira and Dr.. V. Rama kumar, rofessor and Head, Dept. of enetics and lant Breeding, Agricultural College, Bapatla, for their valuable suggestions and help rendered during my research work. I sincerely extend my profound gratitude to Dr. D. Rathna Babu, Assistant rofessor (lant Breeding), Agricultural College, Bapatla and Dr. K. Madhu Kumar, Scientist (lant Breeding), Agricultural Research Station, Amadalavalasa, for their sustained encouragement, constant support and valuable suggestions offered during research work.

8 I am also very much thankful to Agricultural Extension Officer Srinivas Rao for his help during my farm operations by providing sufficient labourers. From my mere existence on earth to present situation, my every step of life is moulded by my mother Smt. S. Rambai and father Sri S. ovinda Ramana. I will forever remain indebted to them. Their parenting brings every time the best in every effort of my venture. No words can express my immense gratitude to my grand mother S. Seethamma, for her love and affection and valuable efforts during my studies. I express my immense grattitude for my sister avani, brother in-law Suresh Kumar and my brother Leela raveen for their love and affection. Single para would not justify my deep affection towards my friends ushpa, Sowmya Lakshmi, ayathri, Divya Sree, Sujala, rathyusha, Divya Bharathi, Janaki, Divya, Sandhya, Bhagyashree, Menaka, Neerisha, oorna Teja and Revathi for providing a helping hand whenever needed, always being there beside me in difficult times during my course of study and giving constant motivation and made my life really enjoyable. A Hearty thanks to my seniors Venkateshwara Rao, Hari Ram Kumar, Bhargavi, Haritha, admavathi, Sri Lakshmi, Anitha, Rajitha and Anusha for the much needed moral support and help during the course of my study. I acknowledge and appreciate my classmate friends rasanna Kumar, Revathi, Triveni, Vanaja, Rani Jadhav, Sudheer, B. S. atil, Vijay, Eswar Rao and Vinay Kumar for their support extended to boost up my morale in carrying out this thesis research work. I am grateful to Acharya N.. Ranga Agricultural University for providing financial help in the form of stipend during my course of study. I am very much thankful to Record Assistant, Sri Bhaskara Rao & attender, Smt. Siva arvathi, Ramulamma and rasanna Kumar for their help during my. rogramme in the Department. While travelling on this part of education, many hands pushed me forth, learned hearts put me on the right track. I ever rest THANKS to all of them. Any omission in this brief acknowledgements doesn t mean lack of gratitude. lace: Naira Date: (S. JYOTHSNA)

9 LIST OF CONTENTS Chapter No Title age No. I INTRODUCTION II REVIEW OF LITERATURE III MATERIAL AND METHODS IV RESULTS AND DISCUSSION V SUMMARY AND CONCLUSIONS LITERATURE CITED AENDIX

10 LIST OF LATES late No. Title age No. 3.1 Experimental field with label indicating all the details of the experimental site LIST OF AENDIX Appendix No. Title age No. A. Meterological data during the cropping period kharif, 2013 ( to )

11 LIST OF ILLUSTRATIONS Fig. No. Title age No. 4.1 enetic parameters of roselle in Environment I 4.2 enetic parameters of roselle in Environment II 4.3 enetic parameters of roselle in Environment III 4.4 henotypic path diagram showing cause-effect relationship of yield components with fibre yield per plant of roselle in Environment I 4.5 henotypic path diagram showing cause-effect relationship of yield components with fibre yield per plant of roselle in Environment II 4.6 henotypic path diagram showing cause-effect relationship of yield components with fibre yield per plant of roselle in Environment III 4.7 henotypic path diagram showing cause-effect relationship of yield components with fibre yield per plant of roselle pooled over Environments 4.8 Biplot (AMMI 1) for days to 50% flowering in roselle 4.9 Interaction Biplot (AMMI 2) for days to 50% flowering in roselle 4.10 Biplot (AMMI 1) for plant height in roselle 4.11 Interaction Biplot (AMMI 2) for plant height in roselle 4.12 Biplot (AMMI 1) for basal stem diameter in roselle 4.13 Interaction Biplot (AMMI 2) for basal stem diameter in roselle 4.14 Biplot (AMMI 1) for bark thickness in roselle 4.15 Interaction Biplot (AMMI 2) for plant height in roselle 4.16 Biplot (AMMI 1) for number of nodes per plant in roselle 4.17 Interaction Biplot (AMMI 2) for number of nodes per plant in roselle 4.18 Biplot (AMMI 1) for internodal length per plant in roselle 4.19 Interaction Biplot (AMMI 2) for internodal length per plant in roselle 4.20 Biplot (AMMI 1) for green plant weight in roselle 4.21 Interaction Biplot (AMMI 2) for green plant weight in roselle

12 4.22 Biplot (AMMI 1) for fibre length per plant in roselle 4.23 Interaction Biplot (AMMI 2) for fibre length per plant in roselle 4.24 Biplot (AMMI 1) for fibre wood ratio in roselle 4.25 Interaction Biplot (AMMI 2) for fibre wood ratio in roselle 4.26 Biplot (AMMI 1) for fibre yield per plant in roselle 4.27 Interaction Biplot (AMMI 2) for fibre yield per plant in roselle

13 LIST OF SYMBOLS AND ABBREVIATIONS & : And % : er cent / : er 0 C : Degree centigrade AINJAF : All India Network roject on Jute and Allied Fibres AMMI : Additive Main effects and Multiplicative Interaction ANOVA : Analysis of Variance ASV : AMMI s stability value CD : Critical difference cm : Centimeter CV : Coefficient of variation d -1 : er day d.f : Degrees of freedom et al., : and coworkers g : ram A : enetic advance AM : enetic advance as per cent of mean CV : enotypic coefficient of variation h 2 (b) : Heritability in broad sense ICA : Interaction principal component axis K : Selection differential kg ha -1 : Kilograms per hectare Max : Maximum Min : Minimum mm : Millimeter No. : Number NS : Non-significant CV : henotypic coefficient of variation CA : rincipal Component Analysis per se : As such with mean RBD : Randomized block design S : Significant SE(µ) : Standard error of mean SEd : Standard error of difference SS : Sum of squares via viz., : : Through Namely X : rand mean

14 LIST OF TABLES Table Title No. 2.1 Review of literature on genetic variability studies in roselle 2.2 Review of literature on heritability, h 2 (b) and genetic advance (A) studies in roselle 2.3 Review of literature on association of component characters with fibre yield in roselle 2.4 Review of literature on association among yield component characters in roselle 2.5 Review of literature on direct effect of component characters on fibre yield in roselle 2.6 Review of literature on indirect effects among component characters with fibre yield in roselle 3.1 Source of origin employed in the study and morphological characters of roselle 3.2 Analysis of variance of stability model (as per Eberhart and Russell, 1966) 3.3 Analysis of variance of stability model (as per laisted and eterson, 1959) Analysis of variance (mean sum of squares) for ten quantitative 4.1 characters in three different environments (dates of sowing) for 30 genotypes of roselle 4.2 Mean performance for ten quantitative characters in 30 genotypes of roselle in three different environments (dates of sowing) 4.3 Estimates of genetic variability parameters of yield component attributes in three different environments (dates of sowing) of roselle 4.4 henotypic and enotypic correlation coefficient in 30 genotypes of roselle in Environment I 4.5 henotypic and enotypic correlation coefficient in 30 genotypes of roselle in Environment II 4.6 henotypic and enotypic correlation coefficient in 30 genotypes of roselle in Environment III 4.7 henotypic and enotypic correlation coefficient in 30 genotypes of roselle pooled over Environments 4.8 ath coefficients of yield and yield components of roselle in Environment I 4.9 ath coefficients of yield and yield components of roselle in Environment II 4.10 ath coefficients of yield and yield components of roselle in Environment III 4.11 ath coefficients of yield and yield components of roselle in pooled over Environments 4.12 Bartlett s 2 values and Environmental index values (I j ) for different characters in roselle 4.13 ooled analysis of variance (mean sum of squares) for stability performance (Eberhart and Russell (1966) model) for ten characters of roselle over three environments age No.

15 Stability parameters in respect of days to 50% flowering and plant height for 30 genotypes of roselle Stability parameters in respect of basal stem diameter and bark thickness for 30 genotypes of roselle Stability parameters in respect of number of nodes per plant and internodal length per plant for 30 genotypes of roselle Stability parameters in respect of green plant weight and fibre length per plant for 30 genotypes of roselle Stability parameters in respect of fibre wood ratio and fibre yield per plant for 30 genotypes of roselle enotypes classified into different groups according to Eberhart and Russell (1966) stability parameters in rosellee Analysis of variance of AMMI model for the quantitative characters in roselle AMMI stability values (ASV) for ten quantitative characters of 30 genotypes of roselle More and less stable genotypes according to AMMI s stability values (ASV) in roselle Ranking of genotypes based on different stability parameters for days to 50% flowering in roselle Ranking of genotypes based on different stability parameters for plant height in roselle Ranking of genotypes based on different stability parameters for basal stem diameter in roselle Ranking of genotypes based on different stability parameters for bark thickness in roselle Ranking of genotypes based on different stability parameters for number of nodes per plant in roselle Ranking of genotypes based on different stability parameters for internodal length per plant in roselle Ranking of genotypes based on different stability parameters for green plant weight in roselle Ranking of genotypes based on different stability parameters for fibre length per plant in rosellee Ranking of genotypes based on different stability parameters for fibre wood ratio in roselle Ranking of genotypes based on different stability parameters for fibre yield per plant in roselle Mean of ranks of ten stability parameters for ten quantitative characters of 30 genotypes of roselle 4.34 Stable genotypes based on different stability parameters in roselle

16 ABSTRACT Name of the Author : S. JYOTHSNA Title of the thesis : STABILITY ANALYSIS IN ROSELLE (Hibiscus sabdariffa L.) Faculty : ARICULTURE Major Field of study : ENETICS AND LANT BREEDIN Major Advisor : Dr. A. AALA SWAMY University : ACHARYA N.. RANA ARICULTURAL UNIVERSITY Year of Submission : 2014 The present investigation was carried out during kharif 2013 in three environments [(different dates of sowing i.e., Environment 1 (E 1 ) = ; Environment 2 (E 2 ) = ; Environment 3 (E 3 ) = )] at the Agricultural Research Station Farm, Amadalavalasa, Andhra radesh with 30 genotypes of roselle (Hibiscus sabdariffa L.) in order to study the variability, heritability, genetic advance as per cent of mean, character association, magnitude of direct and indirect effects and stability. The data were recorded on days to 50% flowering, plant height (cm), basal stem diameter (mm), bark thickness (mm), number of nodes per plant, internodal length per plant (cm), green plant weight (g), fibre length per plant (cm), fibre wood ratio and fibre yield per plant (g). The analysis of variance revealed significant differences among the genotypes for all the characters in all three environments indicating the presence of genetic variability in the studied material. The genotypic coefficients of variation for all the characters studied were lesser than the phenotypic coefficients of variation indicating the interaction of genotypes with environment. High heritability coupled with high genetic advance was observed for fibre wood ratio (in environment IIΙ) and fibre yield per plant (in environment II), indicating the importance of additive gene action in governing the inheritance of these traits. Hence, direct phenotypic selection is useful with respect to above traits. Character association and path coefficient analysis studies revealed that, basal stem diameter, bark thickness, green plant weight and fibre length per plant showed significant positive association coupled with positive direct effects on fibre yield per plant in all the environments indicating the use of these attributes in selection to evolve high fibre yielding genotypes.

17 In pooled analysis of variance for stability, the genotypes, environments, environment (linear) and pooled deviations showed significant differences for most of the characters studied, indicating divergent environments and the importance of non-linear component in the genotype-environment interaction. According to Eberhart and Russell (1966) stability model (mean, regression and deviation from regression), the genotypes, AS (for days to 50% flowering and green plant weight); ER-1 (for plant height and basal stem diameter), AHS-161 (for bark thickness), AMV-4 (plant height, number of nodes per plant and fibre length per plant), AHS-152 (for fibre wood ratio); ER-58 (for internodal length per plant) and HS (fibre length per plant and fibre yield per plant) were found to be stable for average environmental conditions. In AMMI analysis, the mean squares were significant for genotypes and environments for all the quantitative characters indicating significant differences among genotypes and environments. Among the environments, environment-i was found to be most suitable for all the characters except internodal length per plant as indicated by high mean value of ICA 1 and low value of ICA 2. The genotypes viz., AR-12, CRIJAFR-2, AS-80-29, AS-80-19, AMV-4 and HS-4288 recorded high mean but low interaction effects and found to be adaptable for all environments for most of the characters. According to AMMI s stability values (ASV), the genotype HS-4288 was found to be stable for plant height, green plant weight, fibre length per plant and fibre yield per plant. The genotype AHS-152 was found to be stable for days to 50% flowering and fibre wood ratio. The genotype ER-58 was found to be stable for basal stem diameter and internodal length per plant. While the genotype AMV-4 was found to be stable for bark thickness, number of nodes per plant and fibre yield per plant. Based on the mean of ranks of stability parameters for all the quantitative characters, the genotype HS-4288 was found to be most stable for green plant weight, fibre wood ratio and fibre yield per plant whereas the genotype AHS-152 was found to be most stable for days to 50% flowering, CRIJAFR-8 was found to be stable for plant height, AR-12 was found to be stable for basal stem diameter, AHS-162 was found to be stable for bark thickness, AMV-4 was found to be stable for number of nodes per plant, ER-38 was found to be stable for intermodal length per plant and ER-10 was found to be stable for fibre wood ratio. The genotypes AR-12, AMV-4, CRIJAFR-2, HS-4288 and ER-1 were found to be stable based on overall rank of stability parameters for ten quantitative characters. Based on the comparative studies of the Eberhart and Russell (1966) stability model, AMMI s stability values (ASV) and mean of ranks of different stability parameters for all the quantitative characters, the genotypes AS (for days to 50% flowering, days to maturity and green plant weight); AMV-4 and HS-4288 (plant height, internodal length per plant, green plant weight, fibre length per plant and fibre yield per plant) ER-1 (basal stem diameter and bark thickness) and AHS-152 (for fibre wood ratio) were found to be most stable over environments. In the present investigation the genotypes, ER-1, AS-80-29, AS-80-19, JRR-9, AR-12, AR-71, AMV-4 and HS-4288 were found most promising by comparative study of stability models and stability parameters, and may serve as potential parental genotypes for future breeding programmes to develop desirable stable segregants for roselle crop improvement programmes.

18 Chapter I INTRODUCTION Roselle (Hibiscus sabdariffa L.) is a diploid species (2n = 72), a member of the family Malvaceae. It is originally from India, Sudan and Malaysia and has been introduced to eastern Africa and Central America. It is an important fibre yielding crop next to jute. Besides fibre, it also provides forage and paper pulp which in turn broadened the agricultural diversity of resources to reduce pressure on forest resources. In recent years, Mesta (roselle and kenaf) is even attracting the attention of food and beverage manufacturers and pharmaceutical concerns as a natural food product and as a colorant to replace synthetic dyes (Appalaswamy et al., 2013). As it is a short day plant and sensitive to photoperiod, temperature and prolonged moisture stress, the fibre yield of roselle is not stable and varies widely. In India, Mesta (roselle and kenaf) is cultivated in about 910 thousand hectares, with an annual production of about million bales of fibres (1 bale = 180 kg) and productivity of 2283 kg ha -1 ( ). Andhra radesh has 30 thousand hectares and produces 0.20 million bales with the productivity of 1398 kg ha -1 (Anon, 2012). All India compound growth rates (per cent per annum) of mesta for area (-47.64), production (-41.05) and productivity (0.017) from to (Directorate of Economics and Statistics, Department of Agriculture and Cooperation), clearly indicated drastic decline in area and production, thus highlighting the great need for increasing the yield by developing improved varieties with resistance to biotic and abiotic stresses. The variability in environment, namely location effect, seasonal fluctuations and their interaction highly influence the performance of genotypes in relation to yield potential. So, the quantum jump in yield can be realized by breeding the genotypes performing the best over the environments. Fibre yield being a complex quantitative character is highly influenced by the environment. Breeding varieties for different regions of predictable environmental conditions or identifying stable varieties over environments are the solutions to get yield jump by exploiting the genotype x environment interaction (Verma and Jay Lal Mahto, 1994). enotype x Environment interactions are known to interfere with the evaluation of genotype and reduces the progress of selection in plant breeding programmes as the genetic nature of a genotype

19 is masked (Comstock and Moll, 1963) and as such, these interactions are of considerable importance in developing improved varieties and rationalization of procedure for future genetic improvement in crop plants. Thus, the study of genotype x environment interaction using suitable biometrical techniques would lead to successful identification of stable genotypes which would either be released for commercial cultivation or to be used in future breeding programme. The existence of heritable variability and favorable correlation among various characters is critical for launching of any breeding programme (Swarup and Chaungle, 1962). Heritability, genetic advance and creation and quantification of genetic variability, and associated response of fibre yield parameters among the prevailing genotypes is vital for achieving the desired results (ulli Bai et al., 2005a). Further, path coefficient analysis helps to determine direct and indirect relations among the traits, as it is important in order to determine the plant selection criteria (Dewey and Lu, 1959). Thus, the correlation in combination with path analysis over environments can provide a better insight into the cause and effect relationship among the quantitative characters. Keeping in view the above aspects, the present investigation was taken up with 30 genotypes of roselle (Hibiscus sabdariffa L.) in three environments (dates of sowing) with the following objectives: OBJECTIVES OF INVESTIATION 1. To study the extent of genetic variability, heritability (broad sense) and genetic advance of quantitative characters along with yield over environments. 2. To ascertain the association between the yield and its component characters and among themselves over environments. 3. To assess the magnitude of direct and indirect effects of component characters on fibre yield through path coefficient analysis over environments. 4. To evaluate the stability of genotypes over environments through stability analysis studies (Eberhart and Russell model and AMMI model).

20 Chapter II REVIEW OF LITERATURE Roselle (Hibiscus sabdariffa L.) is a fibre yielding plant in which the fibre is obtained from the bast region of stem. Hence other bast fibre yielding crops kenaf and jute were also considered in reviewing the literature. Literature with respect to variability, heritability (broad sense), genetic advance, character association, path analysis and stability analysis by Eberhart and Rusell model and AMMI model are reviewed here under: 2.1 VARIABILITY Knowledge on the nature and magnitude of genotypic and phenotypic variability present in any crop species plays a vital role in formulating a successful breeding programme for evolving superior cultivars. Estimation of genetic variability does not gives a clear indication of the possible improvement that can be achieved through selection and it should be used in conjunction with heritability and genetic advance. The magnitude of heritable variation more particularly its genetic component is the most important aspect of the genetic constitution of the breeding material which has a close bearing on its response to selection (anse, 1957). The available literature on variability studies in roselle and some other fibre crops (kenaf and jute) are summarized in Table HERITABILITY, ENETIC ADVANCE AND ENETIC ADVANCE AS ER CENT OF MEAN Heritability is the measure of transmission of characters from generation to generations. The consistency of the performance of selection in succeeding generations depends on the magnitude of heritable variation present in relation to the observed variation. Heritability measures the relative amount of the heritable portion of variability, while the genetic advance helps to measure the amount of

21 progress that could be expected with selection in a character. High trait heritability is not always an indication of high genetic gain, however, direct selection brings about improvement (aul, 1978). The available literature on heritability, genetic advance and genetic advance as per cent of mean in roselle and other fibre crops (kenaf and jute) are presented in Table CHARACTER ASSOCIATION Correlation coefficient is a measure of the degree of closeness and the linear relationship between two variables. The study of correlations between different characters may help the plant breeder to know how the improvement of one character will bring simultaneous changes in other characters. The yield of a plant is polygenically inherited and highly influenced by the environment. Its expression depends upon a number of component traits. Hence, direct selection for yield may not be effective. Further the component characters may be simply inherited and less subjected to environmental variations. To effect selection of these component characters, it is essential to have the knowledge of genetic correlations among the factors contributing to the yield that leads to most effective method of selection by the use of favorable contributions of characters and to minimize the retarding effect of antagonistic correlations (Singh and Bains, 1967). Correlation studies indicate the magnitude of association between pairs of characters and are useful for selecting genotypes with desirable contributions of characters thereby aiding the plant breeder in crop improvement. The available literature on character association studies in roselle and other fibre crops (kenaf and jute) are summarized and presented in Tables 2.3 and ATH ANALYSIS STUDIES ath coefficient analysis provides a means of measuring the direct and indirect effects of a variable through other variables on the end products. Yield being a complex and polygenically controlled character, direct selection for yield

22 may not be a reliable approach because it is highly influenced by environmental factors. Therefore, it becomes essential to identify the component characters through which yield improvement can be obtained. Though, correlation gives information about the components of complex character like yield, it will not provide an exact picture of relative importance of the direct and indirect contributions of the component characters on yield. Hence, path analysis is an important tool to partition the correlation coefficients into direct and indirect effects of independent variable and dependent variable. Thus, correlation studies coupled with path analysis would give a better insight into cause and effect relationship between different pairs of characters. The available literature on path analysis studies in roselle and other fibre crops (kenaf and jute) are presented in the Tables 2.5 and 2.6.

23 Table.2.1. Review of literature on genetic variability studies in Roselle (Hibiscus sabdariffa L.) S.No. Character Crop Wider genetic variability Narrow genetic variability 1. Days to Roselle - Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. 50% (2005), Rama Kumar (2000), Krishnaveni and Krishna Murthy flowering (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), Aruna et al. (1989), admaja (1989) Kenaf - Mostofa et al. (2002), Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991), Madhavi Rani (1990) 2. lant height 3. Basal stem diameter Jute - Bhattacharya et al. (2007), Shukla and Singh (1967) Roselle Kenaf Jute Hari Ram Kumar (2012), Ibrahim and Hussein (2006), Aliyu et al. (2005), ulli Bai et al. (2005), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), Aruna et al. (1989) Bhattacharya et al. (2007a), hosh Dastidar and Bhaduri (1983), Shukla and Singh (1967) Roselle Hari Ram Kumar (2012), ulli Bai et al. (2005), Rama Kumar (2000), uptaji and Subramanyam (1997), uptaji (1993) - Rani et al. (2006), Ibrahim and Hussein (2006), Krishnaveni and Krishna Murthy (2000b), admaja (1989) Echekwu and Showemimo (2004), Mostofa et al. (2002), Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991), Madhavi Rani (1990) Nasima Ali and Sasmal (2011), Bhattacharya et al. (2007a), Chaudhury et al. (1985), Josy Joseph (1975), Singh (1970) Krishnaveni and Krishna Murthy (2000b), Kameswara Rao (1996), Aruna et al. (1989), admaja (1989) Kenaf Echekwu and Showemimo (2004) Mostofa et al. (2002), Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991), Madhavi Rani (1990) Table 2.1 (Cont.)

24 S.No. Character Crop Wider genetic variability Narrow genetic variability 3. Basal stem diameter Jute hosh Dastidar and Bhaduri (1983) Nasima Ali and Sasmal (2011), Chaudhury et al. (1985), Josy Joseph (1975), Singh (1970), Shukla and Singh (1967) 4. Bark thickness 5. Number of nodes per plant 6. Internodal length per plant 7. reen plant weight Roselle Rani et al. (2006), ulli Bai et al. (2005), admaja (1989) Roselle Hari Ram Kumar (2012), ulli Bai et al. (2005), Rama Kumar (2000), Kameswara Rao (1996), Aruna et al. (1989), admaja (1989) Rani et al. (2006), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), uptaji (1993) Kenaf - Mostofa et al. (2002), Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991), Madhavi Rani (1990) Jute - Nasima Ali and Sasmal (2011), Chaudhury et al. (1985), hosh Dastidar and Bhaduri (1983), Josy Joseph (1975) Roselle uptaji and Subramanyam (1997), uptaji (1993) Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000), Kameswara Rao (1996) Kenaf Efrayimu (1993) Mostofa et al. (2002), Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992), Madhavi Rani (1990) Jute - Chaudhury et al. (1985) Roselle Hari Ram Kumar (2012), Rama Kumar (2000), Krishnaveni and Krishna murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), admaja (1989) - - Table 2.1 (Cont.)

25 S.No. Character Crop Wider genetic variability Narrow genetic variability 7. reen Kenaf Mostofa et al. (2002), Subramanyam et al. (1995), Kantilal (1991) plant Appala Swamy (1994), Mohan Rao (1994), weight Adilakshmi (1992), Madhavi Rani (1990) 8. Fibre length per plant 9. Fibre wood ratio 10. Fibre yield per plant Jute Nasima Ali and Sasmal (2011), Josy Joseph (1975), Shukla and Singh (1967) Roselle Hari Ram Kumar (2012), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) Kenaf Roselle Hari Ram Kumar (2012), ulli Bai et al. (2005), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), admaja (1989) Kenaf Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992) Roselle Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), admaja (1989) Kenaf Mostofa et al. (2002), Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Madhavi Rani (1990) Jute hosh Dastidar and Bhaduri (1983), Josy Joseph (1975), Singh (1970), Shukla and Singh (1967) - - ulli Bai et al. (2005), Krishnaveni and Krishna Murthy (2000b), admaja (1989) Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991), Madhavi Rani (1990) Subramanyam et al. (1995), Efrayimu (1993), Kantilal (1991), Madhavi Rani (1990) Krishnaveni and Krishna Murthy (2000b) Kantilal (1991) Chaudhury et al. (1985) -

26

27 Table 2.2. Review of literature on heritability, h 2 (b), and genetic advance (A) studies S. No Character Crop High heritability and High heritability and Low heritability and Low heritability and high genetic advance low genetic advance high genetic advance low genetic advance 1. Days to 50% flowering Roselle Aruna et al. (1989) Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Anuradha and Venkateswara Rao (1993) Kumar (2000), Krishnaveni - and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao(1996) uptaji (1993), admaja(1989) Kenaf Mostofa et al. (2002) Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) - Adilakshmi (1992) - Madhavi Rani (1990) Jute Bhattacharya et al. (2007a) Bhattacharya et al. (2007a) Shukla and Singh (1967) lant height Roselle Hari Ram Kumar (2012), Rani et al. (2006), Ibrahim and Hussein (2006), Rama Kumar (2000), Krishnaveni and Krishna Murthy ulli Bai et al. (2005), (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996),Anuradha and Venkateswara Rao (1993), uptaji (1993), Aruna et al. (1989), admaja (1989) - - Table 2.2 (Cont.)

28 S. No. Character Crop 2. lant height 3. Basal stem diameter High heritability and high genetic advance Kenaf Appala Swamy (1994) Mohan Rao (1994), Adilakshmi (1992) Jute Roselle hosh Dastidar and Bhaduri (1983), Shukla and Singh (1967) Hari Ram Kumar (2012), Rama Kumar (2000), Anuradha and Venkateswara Rao (1993) High heritability and low genetic advance Mostofa et al. (2002) Nasima Ali and Sasmal (2011), Bhattacharya et al. (2007a), Chaudhury et al. (1985), Josy Joseph (1975), Singh (1970) ulli Bai et al. (2005), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), Aruna et al. (1989) Low heritability and high genetic advance - admaja (1989) Low heritability and low genetic advance Subramanyam et al. (1995) Madhavi Rani (1990) Kenaf Subramanyam et al. (1995), Madhavi Rani (1990) Mostofa et al. (2002), Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992) - - Jute hosh Dastidar and Bhaduri (1983), Singh (1970), Shukla and Singh (1967) - - Nasima Ali and Sasmal (2011), Chaudhury et al. (1985), Josy Joseph (1975) Table 2.2 (Cont.)

29 S.No. Character Crop 4. Bark thickness 5. Number of nodes per plant Roselle Roselle Kenaf High heritability and high genetic advance High heritability and low genetic advance Low heritability and high genetic advance Rani et al. (2006), ulli Bai et al. (2005) - - Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al (2005), Rama Kumar (2000), Aruna et al. (1989) Subramanyam et al. (1995), Mohan Rao (1994), Madhavi Rani (1990) Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996) uptaji (1993), admaja (1989) Appala Swamy (1994) Low heritability and low genetic advance admaja (1989) Mostofa et al. (2002), Adilakshmi (1992) 6. Internodal length per plant Jute hosh Dastidar and Bhaduri (1983), Josy Joseph (1975) Roselle Rani et al. (2006), Rama Kumar (2000), admaja (1989) Kenaf Jute Chaudhury et al. (1985) - Nasima Ali and Sasmal (2011) - Hari Ram Kumar (2012), ulli Bai et al. (2005), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), Aruna et al. (1989) Mostofa et al. (2002), Appala Swamy (1994), Mohan Rao (1994) Chaudhury et al.(1985) Subramanyam et al. (1995), Adilakshmi (1992), Madhavi Rani (1990) Table 2.2 (Cont.)

30 S.No. Character 7. reen plant weight 8. Fibre length per plant Crop High heritability and high genetic advance Roselle Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), Anuradha and Venkateswara Rao (1993), uptaji (1993), admaja (1989) Kenaf Mostofa et al. (2002), Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992), Madhavi Rani (1990) Jute Nasima Ali and Sasmal (2011), Josy Joseph (1975), Shukla and Singh (1967) Roselle Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) High heritability and low genetic advance Low heritability and high genetic advance Low heritability and low genetic advance ulli Bai et al. (2005), admaja (1989) Krishnaveni and Krishna Murthy (2000b) Table 2.2 (Cont.)

31 S.No. Character 8. Fibre length per plant 9. Fibre wood ratio 10. Fibre yield per plant Crop High heritability and high genetic advance Kenaf Subramanyam et al. (1995), Appala Swamy (1994), Mohan Rao (1994), Madhavi Rani (1990) Roselle Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000), Kenaf Roselle Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000), Kenaf Subramanyam et al. (1995), Adilakshmi (1992), Madhavi Rani (1990) Jute Chaudhury et al. (1985), hosh Dastidar and Bhaduri (1983), Josy Joseph (1975), Singh (1970), Shukla and Singh (1967) - High heritability and low genetic advance Adilakshmi (1992) uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) Subramanyam et al. (1995), Appala Swamy (1994), Adilakshmi (1992), Madhavi Rani (1990) Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), Anuradha and Venkateswara Rao (1993), uptaji (1993) Mostofa et al. (2002), Appala Swamy (1994), Mohan Rao (1994) Low heritability and high genetic advance Low heritability and low genetic advance admaja (1989) Mohan Rao (1994) admaja (1989)

32

33 Table 2.3. Review of literature on association of component characters with fibre yield S. No. Character Crop Association S/NS / Reference 1. Days to 50% flowering Roselle ositive S Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) NS Bhajantri et al. (2007) Rani et al. (2006) ulli Bai et al. (2005b) Rama Kumar (2000), 2. lant height Negative S admaja (1989) NS Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Krishnaveni (2000) Kameswara Rao (1996) Kenaf ositive S Appala Swamy (1994) NS Appala Swamy (1994) Sasmal and Chakraborty (1978) Negative NS Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Efrayimu (1993) Madhavi Rani (1990) Jute ositive NS Shukla and Singh (1967) Roselle ositive S Hari Ram Kumar (2012), Bhajantri et al. (2007) Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Krishnaveni (2000) Kameswara Rao (1996) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Negative NS Rama Kumar (2000). Kenaf ositive S NS Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) Adamson and Bagby (1975) Sasmal and Chakraborty (1978) Appala Swamy (1994) Efrayimu (1993) Table 2.3 (Cont.)

34 S. No Character Crop Association S/NS / Reference 2. lant Jute ositive height S Basudev Roy (1966) 3. Basal stem diameter 4. Bark thickness NS Roselle ositive S Roy and hosh Dastidar (2004) Islam et al. (2001) Chaudhury et al. (1981) upta and Das (1977) Maiti et al. (1983) Josy Joseph (1975) Singh (1970) Shukla and Singh (1967) Maiti et al. (1983) Ahmed (1972) Bhajantri et al. (2007b) Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005a) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Krishnaveni (2000) Rama Kumar (2000), Kameswara Rao (1996) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) NS Bhajantri et al. (2007) Kenaf ositive S Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) Adamson and Bagby (1975) Sasmal and Chakraborty (1978) NS Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Negative NS Appala Swamy (1994) Jute ositive S Roselle ositive S Roy and hosh Dastidar (2004) Islam et al. (2001) Chaudhury et al. (1981) upta and Das (1977) Maiti et al. (1983) Josy Joseph (1975) Singh (1970) Shukla and Singh (1967) Rani et al. (2006) ulli Bai et al. (2005a) Table 2.3 (Cont.)

35 S. No. Character Crop Association S/NS / Reference 5. Number of nodes per plant Roselle ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) Kameswara Rao (1996) admaja (1989) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) NS Anuradha and Suriyakumari (2002) Krishnaveni et al. (2000a) Negative NS Rama Kumar (2000), 6. Internodal length per plant 7. reen plant weight Kenaf ositive S NS Jute ositive S Roselle ositive S Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Efrayimu (1993) Madhavi Rani (1990) Sasmal and Chakraborty (1978) Appala Swamy (1994) Adilakshmi (1992) Efrayimu (1993) Chaudhary et al. (1981) Josy Joseph (1975) NS Chaudhary et al. (1981) Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Kameswara Rao (1996) Aruna et al. (1988) NS Rama Kumar (2000), Negative S Rani et al. (2006) ulli Bai et al. (2005b) Kenaf Negative NS Appala Swamy (1994) Subramanyam et al. (1995) Efrayimu (1993) Madhavi Rani (1990) Jute ositive S Chaudhary et al. (1981) Roselle ositive S Hari Kam Kumar et al. (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Krishnaveni et al. (2000a) Rama Kumar (2000), Kameswara Rao (1996) admaja (1989) Anuradha and Venkateswara Rao(1993) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Table 2.3 (Cont.)

36 S. No. S/ NS / Kenaf ositive S Character Crop Association 7. reen plant weight 8. Fibre length per plant 9. Fibre wood ratio 10. Fibre yield per plant Jute ositive S Roselle ositive S Reference Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Efrayimu (1993) Madhavi Rani (1990) NS Efrayimu (1993) Islam et al. (2001) Maiti et al. (1983) Josy Joseph (1975) Shukla and Singh (1967) Hari Ram Kumar (2012) Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Kameswara Rao (1996) admaja (1989) Negative NS Rama Kumar (2000) Kenaf ositive S NS Roselle ositive S Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Efrayimu (1993) Madhavi Rani (1990) Appala Swamy (1994) Efrayimu (1993) Rama Kumar (2000), admaja (1989) Aruna et al. (1988) : henotypic S: Significant : enotypic NS: Non-significant NS Negative S Kenaf ositive S Negative NS Hari Ram Kumar (2012), Kameswara Rao (2002) Kameswara Rao (1996) Rani et al. (2006) ulli Bai et al. (2005b) Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) NS Appala Swamy (1994) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Roselle ositive S Bhajantri et al. (2007) Rani et al. (2006) Kenaf ositive S Adilakshmi (1992)

37 Table 2.4. Review of literature on association among yield component characters S. Charact No. er Crop Association S/NS / Reference I Association of days to 50% flowering with 1. lant Roselle ositive S Aruna et al. (1988) height NS Rani et al. (2006) Kameswara Rao (2002) Anuradha and Venkateswara Rao (1993) 2. Basal stem diameter Negative S Rama Kumar (2000), NS admaja (1989) Kenaf ositive NS Hari Ram Kumar (2012), ulli Bai et al. (2005b) Anuradha and Suriyakumari (2002) Appala Swamy (1994) Efrayimu (1993) Sasmal and Chakraborty (1978) Basu and Chakravarty (1971) Negative S Basu and Chakravarty (1971) NS Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) Sasmal and Chakraborty (1978) Jute ositive NS Shukla and Singh (1967) Negative S Bhattacharya et al. (2007b) Basudev Roy (1966) NS Bhajantri et al. (2007) Bhattacharya et al. (2007b) Roselle ositive S Aruna etal. (1988) NS Anuradha and Venkateswara Rao(1993) Negative S Rama Kumar (2000), admaja (1989) NS Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Kameswara Rao (1996) Kenaf ositive NS Adilakshmi (1992) Sasmal and Chakraborty (1978) Negative NS Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Madhavi Rani (1990) Jute ositive NS Shukla and Singh (1967)

38 S.No. Character Crop Association S/NS / Reference I Association of days to 50% flowering with 3. Bark thickness Roselle Negative NS Rani et al. (2006) ulli Bai et al. (2005b) 4. Number of Roselle ositive S Aruna et al. (1988) nodes per plant NS Hari Ram Kumar (2012), Kameswara Rao (2002) Negative S admaja (1989) NS Rani et al. (2006) Anuradha and Suriyakumari (2002) Rama Kumar (2000) 5. Internodal length per plant 6. reen plant weight Kenaf ositive S Adilakshmi (1992) NS Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1992) Negative NS Sasmal and Chakraborty (1978) Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) Roselle ositive S ulli Bai et al. (2005b) Aruna et al. (1988) NS Kameswara Rao (2002) Negative NS Hari Ram Kumar (2012), Rani et al. (2006) Anuradha and Suriyakumari (2002) Rama Kumar (2000) Kenaf ositive S Efrayimu (1993) NS Appala Swamy (1994) Negative S Mohan Rao (1994) NS Subramanyam et al. (1995) Adilakshmi (1994) Madhavi Rani (1990) Roselle ositive S Anuradha and Venkateswara Rao (1993) NS Rama Kumar (2000), Negative S NS Kenaf ositive NS Negative NS Hari Ram Kumar (2012), admaja (1989) Aruna et al. (1988) Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari(2002) Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1989) Jute ositive NS Shukla and Singh (1967) Negative S Rama Kumar (2000) Table 2.4 (Cont.)

39 S. No. Character Crop Association S/NS / Reference I Association of days to 50% flowering with 7. Fibre length Roselle ositive NS Rani et al. (2006) per plant Negative S Rama Kumar (2000), 8. Fibre wood ratio 9. Fibre yield per plant NS Hari Ram Kumar (2012), ulli Bai et al. (2005b) Kameswara Rao (2002) admaja (1989) Kenaf ositive S Efrayimu (1993) NS Appala Swamy(1995) Adilakshmi (1992) Kenaf Negative NS Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) Roselle ositive S Aruna et al. (1988) NS Negative NS Kenaf ositive NS Rani et al. (2006) ulli Bai et al. (2005b) Rama Kumar (2000), admaja (1989) Hari Ram Kumar (2012), Kameswara Rao (2002) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1989) Negative S Mohan Rao (1994) NS Roselle ositive S Subramanyam et al. (1995) Madhavi Rani (1990) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) NS ulli Bai (2005b) Rama Kumar (2000) Negative S admaja (1989) NS Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Kenaf ositive S Appala Swamy (1994) NS Appala Swamy (1994) Sasmal and Chakraborty (1978) Negative NS Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1989) Madhavi Rani (1990) Jute ositive S Singh (1970) NS Shukla and Singh (1967) Table 2.4 (Cont.)

40 S. No. Character Crop Association S/NS / Reference II Association of lant height with 1. Basal stem diameter Roselle ositive S Sinha et al. (1986) 2. Bark thickness 3. Number of nodes per plant NS Kenaf ositive S NS Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Sanoussi et al. (2011) Rama Kumar (2000), Banerjee et al. (1988) Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) Adamson and Bagby (1975) Echekwu and Showemino (2004) Appala Swamy (1994) Efrayimu (1993) Sasmal and Chakraborty (1978) Negative NS Adilakshmi (1992) Jute ositive S NS Maiti et al. (1983) Roselle ositive S Rani et al. (2006) Roselle ositive S Roy and hosh Dastidar (2004) Islam et al. (2001) Chaudhary et al. (1981) Maiti et al. (1983) Josy Joseph (1975) Jitendra Mohan and yan rakash (1971) Singh (1970) Shukla and Singh (1967) Hari Ram Kumar (2012), Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) admaja (1989) Aruna et al. (1988) Sinha et al. (1986) NS Anuradha and Suriyakumari (2002) Negative S Rani et al. (2006) NS Banerjee et al. (1988) Table 2.4 (Cont.)

41 S. No. Character Crop Association S/NS / Reference II Association of lant height with 3. Number of nodes per plant Kenaf ositive S Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Madhavi Rani (1990) NS Adilakshmi (1992) Sasmal and Chakraborty (1978) Jute ositive S Josy Joseph (1975) 4. Internodal length per plant 5. reen plant weight 6. Fibre length per plant Roselle ositive S NS Islam et al. (2001) Hari Ram Kumar (2012), Rani et al. (2006) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Aruna et al. (1988) Sinha et al. (1986) NS Rama Kumar (2000) Negative S ulli Bai et al.(2005b) NS ulli Bai et al.(2005b) Kenaf ositive S NS Roselle ositive S Appala Swamy (1994) Mohan Rao (1994) Appala Swamy (1994) Subramanyam et al. (1995) Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) Kameswara Rao (2002) Anuradha and Venkateswara Rao (1993) admaja (1989) Banerjee et al (1988) Sinha et al. (1986) NS Rama Kumar (2000) Negative NS Aruna et al. (1988) Kenaf ositive S NS Jute ositive S Roselle ositive S Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1992) Islam et al. (2001) Maiti et al. (1983) Josy Joseph (1975) NS Maiti et al. (1983) Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) admaja (1989) Table 2.4 (Cont.)

42 S.No. Character Crop Association S/NS / Reference II Association of lant height with 6. Fibre Roselle ositive NS Rama Kumar (2000) length per plant Kenaf ositive S Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) 7. Fibre wood ratio 8. Fibre yield per plant Jute ositive S Chaudhary et al. (1981) Roselle ositive S Rani et al. (2006) Aruna et al. (1998) NS Hari Ram Kumar (2012), Kameswara Rao (2002) Negative S ulli Bai et al. (2005b) admaja (1989) NS Rama Kumar (2000) Kenaf ositive S Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) NS Mohan Rao (1994) Adilakshmi (1992) Negative NS Appala Swamy (1994) Efrayimu (1993) Roselle ositive S Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Negative NS Rama Kumar (2000), Kenaf ositive S Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) Sasmal and Chakraborty (1978) NS Appala Swamy (1994) Jute ositive S NS Efrayimu (1993) Roy and hosh Dastidar (2004) Islam et al. (2001) Chaudhary et al. (1981) Maiti et al. (1983) upta and Das (1977) Maiti et al. (1983) Ahmed et al. (1972) Table 2.4 (Cont.)

43 S. No. Character Crop Association S/NS / Reference III Association of Basal stem diameter with 1. Bark Roselle ositive S Rani et al. (2006) thickness 2. Number of nodes per plant Roselle ositive S Hari Ram Kumar (2012), admaja (1989) Aruna et al. (1988) 3. Internodal length per plant 4. reen plant weight NS Kenaf ositive S NS Banerjee et al. (1988) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Rama Kumar (2000) Sinha et al. (1986) Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Sasmal and Chakraborty (1978) Negative NS Efrayimu (1993) Jute ositive S Josy Joseph (1975) NS Islam et al. (2001) Roselle ositive S NS Hari Ram Kumar (2012), Aruna et al. (1988) Kameswara Rao (2002) Rama Kumar (2000), Sinha et al. (1986) Negative S ulli Bai et al. (2005b) Kenaf ositive NS Negative NS Roselle ositive S NS Anuradha and Suriyakumari (2002) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Appala Swamy (1994) Subramanyam et al. (1995) Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Rama Kumar (2000), admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Sinha et al. (1986 NS Banerjee et al. (1988) Table 2.4 (Cont.)

44 S. No. Character Crop Association S/NS / Reference III Association of Basal stem diameter with 4. reen plant weight Kenaf ositive S Appala Swamy (1994) Subramanyam et al. (1995) Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) NS Appala Swamy (1994) 5. Fibre length per plant 6. Fibre wood ratio 7. Fibre yield per plant Jute ositive S Roselle ositive S Kenaf ositive S Mohan Rao (1994) Islam et al. (2001) Maiti et al. (1983) Josy Joseph (1975) Shukla and Singh (1967) Hari Ram Kumar (2012), ulli Bai et al. (2005) Kameswara Rao (2002) admaja (1989) NS Rama Kumar (2000), Subramanyam et al. (1995) Efrayimu (1993) Madhavi Rani (1990) NS Appala Swamy (1994) Adilakshmi (1992) Negative NS Efrayimu (1993) Adilakshmi (1992) Jute ositive S Chaudhary et al. (1981) NS Chaudhary et al. (1981) Roselle ositive S Rama Kumar (2000), Aruna et al. (1988) Negative S ulli Bai et al. (2005b) admaja (1989) NS Kameswara Rao (2002) Kenaf ositive S Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) NS Negative NS Roselle ositive S Mohan Rao (1994) Adilakshmi (1992) Appala Swamy (1994) Efrayimu (1993) Hari Ram Kumar (2012), ulli Bai et al. (2005b) Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Rama Kumar (2000), admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Table 2.4 (Cont.)

45 S. No. III Character Crop Association S/NS / Reference Association of Basal stem diameter with Kenaf ositive S NS Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) Sasmal and Chakraborty (1978) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Sasmal and Chakraborty (1978) Negative NS Appala Swamy (1994) Jute ositive S IV Association of bark thickness with 1. Number of Roselle ositive S Rani et al. (2006) nodes per plant 2. Internodal Roselle Negative S Rani et al. (2006) length per ulli Bai et al. (2005b) plant 3. Fibre length per plant Roy and hosh Dastidar (2004) Islam et al. (2001) Maiti et al. (1983) Chaudhary et al. (1981) upta and Das (1977) Josy Joseph (1975) Singh (1970) Shukla and Singh (1967) Roselle ositive S Rani et al. (2006) ulli Bai et al. (2005b) 4. Fibre-wood Roselle Negative S Rani et al. (2006) ratio NS ulli Bai et al. (2005b) 5. Fibre yield per plant Roselle ositive S Rani et al. (2006) ulli Bai et al. (2005b) V Association of number of nodes per plant with 1. Internodal length per plant Roselle ositive NS Hari Ram Kumar (2012) Rama Kumar (2000) Aruna et al. (1988) Negative S Kameswara Rao (2002) Sinha et al. (1986) NS Anuradha and Suriyakumari (2002) Kenaf ositive S NS Negative NS Mohan Rao (1994) Adilakshmi (1992) Mohan Rao (1994) Adilakshmi (1992) Appala Swamy (1994) Subramanyam et al. (1995) Efrayimu (1993) Madhavi Rani (1990) Table 2.4 (Cont.)

46 S. No. Character Crop Association S/NS / Reference V Association of number of nodes per plant with 2. reen plant weight Roselle ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) admaja (1989) 3. Fibre length per plant 4. Fibre wood ratio 5. Fibre yield per plant NS Negative NS Kenaf ositive S Sinha et al. (1986) Anuradha and Suriyakumari (2002) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Rama Kumar (2000), Aruna et al. (1988) Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) NS Efrayimu (1993) Adilakshmi (1992) Jute ositive S Josy Joseph (1975) NS Islam et al. (2001) Roselle ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) Rama Kumar (2000), admaja (1989) Kenaf ositive S Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Madhavi Rani (1990) NS Appala Swamy (1994) Adilakshmi (1992) Jute Negative S Chaudhary et al. (1981) Roselle ositive NS Hari Ram Kumar (2012), Aruna et al. (1988) Negative S Rama Kumar (2000), NS Kameswara Rao (2002) admaja (1989) Kenaf ositive S Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) NS Mohan Rao (1994) Efrayimu (1993) Negative NS Appala Swamy (1994) Efrayimu (1993) Roselle ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) admaja (1989) Aruna et al. (1988) Sinha et al. (1986) Table 2.4 (Cont.)

47 S. No. Character Crop Association S/NS / Reference V Association of number of nodes per plant with 5. Fibre yield Roselle ositive NS Anuradha and Suriyakumari (2002) per plant Banerjee et al. (1988) Sinha et al. (1986) Negative NS Rama Kumar (2000), Kenaf ositive S Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) Sasmal and Chakraborty (1978) NS Appala Swamy (1994) Adilakshmi (1992) Sasmal and Chakraborty (1978) Jute ositive S Chaudhary et al. (1981) NS Association of Internodal length per plant with Roselle ositive S VI 1. reen plant weight 2. Fibre length per plant 3. Fibre wood ratio Josy Joseph (1975) Islam et al. (2001) Chaudhary et al. (1981) Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Sinha et al. (1986) NS Rama Kumar (2000) Negative S Aruna et al. (1988) Kenaf ositive S Mohan Rao (1994) Adilakshmi (1992) NS Adilakshmi (1992) Negative NS Madhavi Rani (1990) Appala Swamy (1994) Subramanyam et al. (1995) Efrayimu (1993) Roselle ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) NS Rama Kumar (2000) Negative S Rani et al. (2006) ulli Bai et al. (2005b) Kenaf ositive S Mohan Rao (1994) NS Appala Swamy (1994) Subramanyam et al. (1995) Negative NS Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) Roselle ositive S Hari Ram Kumar (2012), ulli Bai et al. (2005) Aruna et al. (1988) Table 2.4 (Cont.)

48 S. No. Character Crop Association S/NS / Reference VI Association of Internodal length per plant with 3. Fibre wood ratio Roselle ositive NS Kameswara Rao (2002) Rama Kumar (2000), Negative S Rani et al. (2006) Kenaf ositive S Mohan Rao (1994) NS Appala Swamy (1994) Adilakshmi (1992) Negative S Subramanyam et al. (1995) Madhavi Rani (1990) NS Efrayimu (1993) 4. Fibre yield per plant VII 1. Fibre length per plant Roselle ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Aruna et al. (1988) Sinha et al. (1986) NS Rama Kumar (2000), Negative S Rani et al. (2006) ulli Bai et al. (2005b) Kenaf ositive S Mohan Rao (1994) Adilakshmi (1992) NS Adilakshmi (1992) Negative NS Appala Swamy (1994) Subramanyam et al. (1995) Efrayimu (1993) Madhavi Rani (1990) Jute ositive S Chaudhary et al. (1981) Association of reen plant weight per plant with Roselle ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) admaja (1989) 2. Fibre wood ratio Kenaf ositive S NS Roselle ositive S NS NS Rama Kumar (2000) Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1992) Rama Kumar (2000), Aruna et al. (1988) Hari Ram Kumar (2012), Kameswara Rao (2002) Negative S admaja (1989) NS Hari Ram Kumar (2012), Table 2.4 (Cont.)

49 S. No. Character Crop Association S/NS / Reference VII Association of reen plant weight per plant with 2. Fibre wood Kenaf ositive S Subramanyam et al. (1995) ratio Mohan Rao (1994) Madhavi Rani (1990) NS Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Negative S Appala Swamy (1994) 3. Fibre yield per plant Roselle ositive S Kenaf ositive S Jute ositive S Hari Ram Kumar (2012), Kameswara Rao (2002) Anuradha and Suriyakumari (2002) Rama Kumar (2000), admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Appala Swamy (1994) Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) Islam et al. (2001) Maiti et al. (1983) Josy Joseph (1975) Shukla and Singh (1967) VIII Association of fibre length per plant with 1. Fibre wood Roselle ositive S Kameswara Rao (2002) ratio NS Hari Ram Kumar (2012), Negative S Rani et al. (2006) ulli Bai et al. (2005) Rama Kumar (2000), admaja (1989) 2. Fibre yield per plant Kenaf ositive S Subramanyam et al. (1995) Mohan Rao (1994) Madhavi Rani (1990) NS Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Negative NS Appala Swamy (1994) Roselle ositive S Hari Ram Kumar (2012), ulli Bai et al. (2005b) Kameswara Rao (2002) admaja (1989) Negative S Rani et al. (2006) Rama Kumar (2000), NS Rama Kumar (2000), Table 2.4 (Cont.)

50 S.No. Character Crop Association S/NS / Reference VIII Association of fibre length per plant with 2. Fibre yield per plant Kenaf ositive S Subramanyam et al. (1995) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Madhavi Rani (1990) NS Appala Swamy (1994) IX Association of fibre wood ratio with 1. Fibre yield Roselle ositive S Rama Kumar (2000), admaja (1989) Aruna et al. (1988) NS Hari Ram Kumar (2012), Kameswara Rao (2002) Rama Kumar (2000), Negative S NS admaja (1989) Kenaf ositive S NS Negative NS Rani et al. (2006) ulli Bai et al. (2005b) Subramanyam et al. (1995) Mohan Rao (1994) Adilakshmi (1992) Madhavi Rani (1990) Sasmal and Chakraborty (1978) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Appala Swamy (1994) Efrayimu (1993) : henotypic S: Significant : enotypic NS: Non-significant

51 Table.2.5. Review of literature on direct effect of component characters on yield S.No Character Crop 1. Days to 50% flowering Roselle ositive direct effect Negative direct effect henotypic enotypic henotypic enotypic ulli Bai et al. (2005b) Rani et al. (2006) Hari Ram Kumar (2012), Kameswara Rao (2002), Krishnaveni and Krishna Rani et al. (2006) Rama Kumar (2000), Murthy (2000a) Aruna et al. (1988) Anuradha and Venkateswara admaja (1989) admaja (1989) Rao (1993) Sasmal and Chakraborty (1978) Hemalatha (1990) Hari Ram Kumar (2012), ulli Bai et al. (2005b), Kameswara Rao (2002), Anuradha and Suriyakumari (2002), Rama Kumar (2000), Aruna et al. (1988) Kameswara Rao (1996) Hemalatha (1990) Kenaf Mohan Rao (1994) Efrayimu (1993) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Jute - Abdelatif Ahmed Sulaiman et al. (2009) 2. lant height Roselle Hari Ram Kumar (2012), ulli Hari Ram Kumar (2012), Bai et al. (2005b), Anuradha Rani et al. (2005) and Suriyakumari (2002) ulli Bai et al. (2005b), Krishnaveni and Krishna Rama Kumar (2000), Murthy (2000a), Rama Kumar Anuradha and Venkateswara (2000), Rao (1993) Aruna et al. (1988) Banerjee et Aruna et al. (1988) al. (1988) Sinha et al.(1986) Hemalatha (1990) Hemalatha (1990) Rani et al. (2005) Kameswara Rao (2002) Kameswara Rao (1996) admaja (1989) Kameswara Rao (2002) Kameswara Rao (1996) admaja (1989) Kenaf Efrayimu (1993) Kantilal (1991) Jute Roy and hosh Dastidar (2004) Islam et al. (2001) Chaudhary et al. (1981) hosh Dastidar and Bhaduri (1983) Sasmal and Chakraborty (1978), Mohan Rao (1994) Efrayimu (1993) Chaudhary et al. (1981) hosh Dastidar and Bhaduri (1983) Appala Swamy (1994) Mohan Rao (1994) Adilakshmi (1992) - - Table 2.5 (Cont.)

52 S.No Character Crop 3. Basal stem diameter Roselle Kenaf Jute ositive direct effect Negative direct effect henotypic enotypic henotypic enotypic ulli Bai et al. (2005b),Kameswara Rao (2002), Anuradha and Suriyakumari (2002), Krishnaveni and Krishna Murthy (2000a),Kameswara Rao (1996) Hemalatha (1990), admaja (1989) Banerjee et al. (1988) Mohan Rao (1994), Efrayimu (1993) Adilakshmi (1992), Kantilal (1991) Roy and hosh Dastidar (2004) Islam et al. (2001) Chaudhary et al. (1981) hosh Dastidar and Bhaduri (1983) 4. Bark thickness Roselle Rani et al. (2006), ulli Bai et al. (2005b) 5. Number of nodes per plant Roselle Kameswara Rao (2002), Anuradha and Suriyakumari (2002), Kameswara Rao (1996), Hemalatha (1990),admaja (1989),Aruna et al. (1988). ulli Bai et al. (2005b), Kameswara Rao (2002), Anuradha and Venkateswara Rao (1993), Kameswara Rao (1996), admaja (1989), Sinha et al. (1986) Sasmal and Chakraborty (1978), Mohan Rao (1994) Efrayimu (1993) hosh Dastidar and Bhaduri (1983) - - Appala Swamy (1994) Adilakshmi (1992) - Chaudhary et al. (1981) ulli Bai et al. (2005b) - Rani et al. (2006) Kameswara Rao (2002), Kameswara Rao (1996), Hemalatha (1990), Aruna et al. (1988) Krishnaveni and Krishna Murthy (2000a) Sinha et al. (1986), admaja (1989) Table 2.5 (Cont.)

53 S.No Character Crop 5. Number of nodes per plant 6. Internodal length per plant 7. reen plant weight ositive direct effect Negative direct effect henotypic enotypic henotypic enotypic Sasmal and Chakraborty Mohan Rao (1994) Mohan Rao (1994) (1978), Adilakshmi (1992) Kantilal (1991) Efrayimu (1993) Kenaf Appala Swamy (1994) Efrayimu (1993),Adilakshmi(1992) Jute Chaudhary et al. (1981) - hosh Dastidar and Bhaduri (1983) Chaudhary et al. (1981), hosh Dastidar and Bhaduri (1983) Mohan Rao (1994) Efrayimu (1992) Kenaf Mohan Rao (1994) Efrayimu (1992) Adilakshmi (1992) Appala Swamy (1994), Adilakshmi (1992) Jute Chaudhary et al. (1981) - - Chaudhary et al. (1981) Roselle Hari Ram Kumar (2012), Kameswara Rao (2002), - Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Aruna et al. (1988), Anuradha and Anuradha and Hemalatha (1990) Suriyakumari (2002), Venkateswara Rao (1993) admaja (1989) Krishnaveni and Krishna Sinha et al. (1986) Murthy (2000a), Rama Kameswara Rao (1996) Kumar(2000), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Aruna et al. (1988) Banerjee (1988) Kenaf Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Kantilal (1989) - Adilakshmi (1992) Jute - - Islam et al. (2001) - Table 2.5 (Cont.)

54 S.No Character Crop 8. Fibre length Roselle Hari Ram Kumar (2012), ulli Bai et al. (2005b), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a) Kameswara Rao (1996) Hemalatha (1990) admaja (1989) 9. Fibre wood ratio 10. Fibre yield per plant Kenaf Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) ositive direct effect Negative direct effect henotypic enotypic henotypic enotypic ulli Bai et al. (2005b) ulli Bai et al. (2005b), Hari Ram Kumar (2012), Kameswara Rao (2002) Rama Kumar (2000), Rani et al. (2006), Rama Kameswara Rao (1996) Kumar (2000), Roselle Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) admaja (1989) Kenaf Mohan Rao (1994) Efrayimu (1993) Kantilal (1991) Roselle Rani et al. (2006) Aruna et al. (1988) Adilakshmi (1992) Adilakshmi (1992) - - Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989) Mohan Rao (1994) Adilakshmi (1992) Rani et al. (2006) Aruna et al. (1988) Adilakshmi (1992) Aruna et al. (1988) Aruna et al. (1988) Appala Swamy (1994), Adilakshmi (1992) Efrayimu (1993) - -

55 Table.2.6. Review of literature on indirect effects among component characters with yield S.No. Character Through Crop Effect / Reference 1. Days to 50% flowering lant height Basal stem diameter Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Hemalatha (1990) admaja (1989) Anuradha and Venkateswara Rao (1993) Hari Ram Kumar (2012), Rani et al. (2006) Rama Kumar (2000), Kameswara Rao (1996) Aruna et al. (1988) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Appala Swamy (1994) Mohan Rao (1994) Adilakshmi (1992) Sasmal and Chakraborty. (1978) Hari Ram Kumar (2012), ulli Bai et al. (2005b) Anuradha and Suriyakumari (2002) Krishnaveni and Krishna Murthy (2000a) Hemalatha (1990) Anuradha and Venkateswara Rao (1993) Hari Ram Kumar (2012), Rani et al. (2006) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Table 2.6 (Cont.)

56 S. No. Character Through Crop Effect / Reference 1. Days to 50% flowering Basal stem diameter Bark thickness Number of nodes per plant Internodal length per plant Kenaf ositive Negative Appala Swamy (1994) Adilakshmi (1992) Sasmal and Chakraborty. (1978) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Roselle ositive Rani et al. (2006) Negative ulli Bai et al. (2005b) Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), admaja (1989) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Sasmal and Chakraborty. (1978) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Kameswara Rao (2002) Aruna et al. (1988) ulli Bai et al. (2005b) Rama Kumar (2000), Table 2.6 (Cont.)

57 S. No. Character Through Crop Effect / Reference 1. Days to 50% Internodal length per Kenaf ositive Mohan Rao (1994) Efrayimu (1993) flowering plant Negative Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) reen plant weight Fibre length per plant Roselle ositive Negative Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002) Rama Kumar (2000), Hemalatha (1990) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Kenaf ositive Mohan Rao (1994) Negative Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Roselle ositive Negative Kenaf ositive Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Krishnaveni and Krishna Murthy (2000a) Hemalatha (1990) admaja (1989) Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) Kameswara Rao (2002) Rama Kumar (2000), admaja (1989) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Table 2.6 (Cont.)

58 S. No Character Through Crop Effect / Reference 1. Days to 50% Fibre length per Kenaf Negative Mohan Rao (1994) Efrayimu (1993) flowering plant Fibre wood ratio 2. lant height Fibre yield per plant Days to 50% flowering Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005) Rama Kumar (2000), admaja (1989) Hari Ram Kumar (2012), Kameswara Rao (2002) Kameswara Rao (2002) Aruna et al. (1988) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1992) Rani et al. (2006) Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), Hemalatha (1990) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Kameswara Rao (1996) admaja (1989) Appala Swamy (1994) Adilakshmi (1992) Sasmal and Chakraborty. (1978) Mohan Rao (1994) Efrayimu (1993) Kantilal (1991) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Table 2.6 (Cont.)

59 S. No Chara -cter Through Crop Effect / Reference Basal stem diameter Negative Kenaf ositive Negative Roselle ositive Roselle ositive Sinha et al. (1986) Negative Aruna et al. (1988) Kenaf ositive Negative Hari Ram Kumar (2012), ulli Bai et al. (2005b) Rani et al. (2006) Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Sasmal and Chakraborty. (1978) Hari Ram Kumar (2012), Rani et al. (2006) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Krishnaveni and Krishna Murthy(2000a) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Anuradha and Venkateswara Rao(1993) Aruna et al. (1988) Banerjee et al. (1988) Hari Ram Kumar (2012), ulli Bai et al. (2005) Hemalatha (1990) Mohan Rao (1994) Efrayimu (1993) Kantilal (1991) Sasmal and Chakraborty. (1978) Echekwu and Showemimo (2004) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1992) Table 2.6 (Cont.)

60 S.No. Character Through Crop Effect / Reference Bark thickness Number of nodes per plant 2. lant height Internodal length per plant Jute ositive Roselle ositive Roy and osh Dastidar (2004) Islam et al. (2001) osh Dastidar and Bhaduri (1983) Chaudhary et al. (1981) Rani et al. (2006) ulli Bai et al. (2005b) Negative Rani et al. (2006) Roselle ositive Negative Kenaf ositive Negative Jute Negative Roselle ositive Negative Kenaf ositive Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a) admaja (1989) Appala Swamy (1994) Efrayimu (1993) Sasmal and Chakraborty. (1978) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) osh Dastidar and Bhaduri (1983) Chaudhary et al. (1981) Rani et al. (2006) ulli Bai et al. (2005b) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Aruna et al. (1988) Sinha et al. (1986) Hari Ram Kumar (2012), ulli Bai et al. (2005b) Mohan Rao (1994) Efrayimu (1993) Table 2.6 (Cont.)

61 S.No. Character 2. lant height Through Crop Effect / Reference reen plant weight Fibre length per plant Fibre length per plant Negative Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Jute ositive Chaudhary et al. (1981) Roselle ositive Negative Kenaf ositive Negative Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Banerjee et al. (1988) Sinha et al. (1986) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Adilakshmi (1992) Kantilal (1991) Jute Negative Islam et al. (2001) Roselle ositive Rani et al. (2006) ulli Bai et al. (2005a) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) Roselle ositive admaja (1989) Negative Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Table 2.6 (Cont.)

62 S.No. Character Through Crop Effect / Reference Fibre wood ratio Fibre yield per plant Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Mohan Rao (1994) Efrayimu (1993) Hari Ram Kumar (2012), Rani et al. (2006) Kameswara Rao (2002) Kameswara Rao (1996) ulli Bai et al. (2005b) Rama Kumar (2000), admaja (1989) Aruna et al (1988) Appala Swamy (1994) Efrayimu (1993) Kantilal (1991) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Hari Ram Kumar (2012), Rani et al. (2006) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Sinha et al. (1986) Rani et al. (2006) Rama Kumar (2000), Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Sasmal and Chakraborty. (1978) Table 2.6 (Cont.)

63 S. Charact No. er 2. lant height 3. Basal stem diameter Through Crop Effect / Reference Fibre yield per plant Days to 50% flowering lant height Jute ositive Roselle ositive Negative Kenaf ositive Negative Islam et al (2002) osh Dastidar and Bhaduri (1983) Hari Ram Kumar (2012), Rani et al. (2006) Anuradha and Suriyakumari (2002) Hemalatha (1990) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Hari Ram Kumar (2012), ulli Bai et al. (2005a) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), Kameswara Rao (1996) Aruna et al. (1988) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Sasmal and Chakraborty. (1978) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1992) Jute ositive Roy and hosh Dastidar (2004) Roselle ositive Negative Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005) Anuradha and Suriyakumari (2002) Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), Hemalatha (1990) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Banerjee et al. (1988) Rani et al. (2006) Kameswara Rao (2002) Kameswara Rao (1996) admaja (1989) Aruna et al. (1988) Table 2.6 (Cont.)

64

65 S.No. Character Through Crop Effect / Reference 3. Basal stem diameter lant height Bark thickness Number of nodes per plant Internodal length per plant Kenaf ositive Negative Jute ositive Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Sasmal and Chakraborty. (1978) Echekwu and Showemimo (2004) Appala Swamy (1994) Mohan Rao (1994) Islam et al. (2001) osh Dastidar and Bhaduri (1983) Negative Chaudhary et al. (1981) Roselle ositive Rani et al. (2006) ulli Bai et al. (2005b) Negative Rani et al. (2006) Roselle ositive Sinha et al. (1986) Negative Kenaf ositive Negative Jute Negative Roselle ositive Rani et al. (2006) ulli Bai et al. (2005b) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a) admaja (1989) Banerjee et al. (1988) Appala Swamy (1994) Efrayimu (1993) Sasmal and Chakraborty. (1978) Mohan Rao (1994) Adilakshmi (1992) Kantilal (1991) osh Dastidar and Bhaduri (1983) Chaudhary et al. (1981) Rani et al. (2006) ulli Bai et al. (2005b) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Aruna et al. (1988) Table 2.6 (Cont.)

66 S.No. Character Through Crop Effect / Reference 3. Basal stem diameter Internodal length per plant reen plant weight per plant Fibre length per plant Negative Hari Ram Kumar (2012), ulli Bai et al. (2005b) Kenaf ositive Appala Swamy (1994) Mohan Rao (1994) Negative Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Jute Negative Chaudhary et al. (1981) Roselle ositive Banerjee et al. (1988) Negative Kenaf ositive Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) admaja (1989) Anuradha and Venkateswara Rao (1993) Aruna et al. (1988) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Sinha et al. (1986) Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Negative Adilakshmi (1992) Jute Negative Islam et al. (2001) Roselle ositive admaja (1989) Negative Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) Hari Ram Kumar (2012), Rani et al. (2006) ulli Bai et al. (2005b) Table 2.6 (Cont.)

67 S.No. Character Through Crop Effect / Reference 3. Basal stem diameter Fibre length per plant Fibre wood ratio Fibre yield per plant Fibre yield per plant Kenaf ositive Kenaf Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Roselle ositive Appala Swamy (1994) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1989) Kantilal (1991) Efrayimu (1993) Adilakshmi (1989) Hari Ram Kumar (2012), Rani et al. (2006) Rama Kumar (2000), admaja (1989) Hari Ram Kumar (2012), ulli Bai et al. (2005b) Kameswara Rao (2002) Kameswara Rao (1996) admaja (1989) Aruna et al. (1988) Appala Swamy (1994) Efrayimu (1993) Adilakshmi (1989) Kantilal (1991) Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1989) Hari Ram Kumar (2012), Rani et al. (2006) Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a) Rama Kumar (2000), Kameswara Rao (1996) Anuradha and Venkateswara Rao (1993) Hemalatha (1990) admaja (1989) Aruna et al. (1988) Negative Sinha et al. (1986) Kenaf ositive Mohan Rao (1994) Efrayimu (1993) Adilakshmi (1992) Kantilal (1991) Sasmal and Chakarborthy (1978) Negative Appala Swamy (1994) Jute ositive osh Dastidar and Bhaduri (1983) Table 2.6 (Cont.)

68 S.No. Character Through Crop Effect / Reference 4. Bark thickness Days to 50% flowering lant height Basal stem diameter Number of nodes per plant Negative Islam et al (2001) Roselle ositive Rani et al. (2006) Negative ulli Bai et al. (2005b) Roselle ositive Rani et al. (2006) ulli Bai et al. (2005b) Negative Rani et al. (2006) Roselle ositive Rani et al. (2006) ulli Bai et al. (2005b) Roselle ositive ulli Bai et al. (2005b) Negative Rani et al. (2006) 5. Number of nodes per plant Internodal length per plant Fibre length per plant Fibre wood ratio Fibre yield per plant Days to 50% flowering Roselle ositive Rani et al. (2006) Negative ulli Bai et al. (2005b) Roselle ositive Rani et al. (2006) ulli Bai et al. (2005b) Negative Rani et al. (2006) Roselle ositive Rani et al. (2006) Negative ulli Bai et al. (2005b) Roselle ositive Roselle ositive Rani et al. (2006) ulli Bai et al. (2005b) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002) Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996) Hemalatha (1990) Table 2.6 (Cont.)

69 S.No. Character Through Crop Effect / Reference 5. Number of nodes per plant lant height Basal stem diameter Basal stem diameter Negative Kenaf ositive Negative Roselle ositive Negative Kenaf Negative ositive Negative Hari Ram Kumar (2012), Kameswara Rao (2002) Krishnaveni and Krishna Murthy (2000a), Rama Kumar (2000), Kameswara Rao (1996), Aruna et al. (1988) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Sasmal and Chakraborty. (1978) Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Krishnaveni and Krishna Murthy (2000a), Hemalatha (1990), Aruna et al. (1988) Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989) Banerjee et al. (1988), Sinha et al. (1986) Mohan Rao (1994), Efrayimu (1993), Kantilal (1991), Sasmal and Chakraborty. (1978) Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992) Jute ositive osh Dastidar and Bhaduri (1983) Negative Chaudhary et al. (1981) Roselle ositive Roselle ositive Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Hemalatha (1990), admaja (1989) Banerjee et al. (1988), Sinha et al. (1986) Table 2.6 (Cont.)

70 S.No. Character Through Crop Effect / Reference Negative Hari Ram Kumar (2012), Rama Kumar (2000), Kameswara Rao (1996), Hemalatha (1990), Aruna et al. (1988) Bark thickness Internodal length per plant reen plant weight Kenaf ositive Mohan Rao (1994), Adilakshmi (1992), Kantilal (1991), Sasmal and Chakraborty. (1978) Negative Appala Swamy (1994), Adilakshmi (1992) Jute ositive osh Dastidar and Bhaduri (1983), Chaudhary et al. (1981) Roselle ositive Rani et al. (2006), ulli Bai et al. (2005b) Negative Rani et al. (2006) Roselle ositive Anuradha and Suriyakumari (2002) Aruna et al. (1988) Negative Hari Ram Kumar (2012), Kameswara Rao (2002) Rama Kumar (2000), Kameswara Rao (1996), Sinha et al. (1986) Kenaf ositive Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Negative Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Jute ositive Chaudhary et al. (1981) Roselle ositive Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Aruna et al. (1988), Banerjee et al. (1988), Sinha et al. (1986) Table 2.6 (Cont.)

71 S. No. Characte r 5. Number of nodes per plant Through Crop Effect / Reference reen plant weight Fibre length per plant Fibre wood ratio Fibre yield per plant Negative Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a), Hemalatha (1990), admaja (1989) Kenaf ositive Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993) Kenaf ositive Adilakshmi (1992), Kantilal (1991) Negative Adilakshmi (1992) Roselle ositive Negative Kenaf Negative Hari Ram Kumar (2012), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) Hari Ram Kumar (2012), Rama Kumar (2000), Mohan Rao (1994), Efrayimu (1993) Roselle ositive Rama Kumar (2000), Negative Hari Ram Kumar (2012), Kameswara Rao (2002), Kameswara Rao (1996), admaja (1989), Aruna et al. (1988) Kenaf ositive Negative Roselle ositive Appala Swamy (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Adilakshmi (1992), Mohan Rao (1994) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002) Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Aruna et al. (1988), Sinha et al. (1986) Negative Rama Kumar (2000), Table 2.6 (Cont.)

72 S. No. Character Through Crop Effect / Reference 6. Internodal length per plant 6. Internodal length per plant Days to 50% flowering Days to 50% flowering lant height Basal stem diameter Kenaf ositive Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991), Sasmal and Chakraborty. (1978) Jute Negative osh Dastidar and Bhaduri (1983) Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) Roselle ositive Aruna et al. (1988) Negative Hari Ram Kumar (2012), Aruna et al. (1988) Kenaf ositive Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993) Negative Roselle ositive Negative Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), Rani et al. (2006), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Sinha et al. (1986) Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (1996), Aruna et al. (1988) Kenaf ositive Mohan Rao (1994), Efrayimu (1993) Negative Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992) Jute Negative Chaudhary et al. (1981) Roselle ositive Hari Ram Kumar (2012), ulli Bai et al. (2005b), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Kameswara Rao (1996) Table 2.6 (Cont.)

73

74 S. No. Character Through Crop Effect / Reference 6. Internodal length per plant Negative Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), Aruna et al. (1988), Sinha et al. (1986) Kenaf ositive Mohan Rao (1994) Negative Appala Swamy (1994), Efrayimu (1993), Adilakshmi (1992) Bark thickness Number of nodes per plant Number of nodes per plant reen plant weight Fibre length per plant Jute Negative Chaudhary et al. (1981) Roselle ositive Rani et al. (2006) Negative Rani et al. (2006), ulli Bai et al. (2005b) Roselle ositive Sinha et al. (1986) Negative Anuradha and Suriyakumari (2002), Aruna et al. (1988), Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) Kenaf ositive Mohan Rao (1994), Efrayimu (1993) Negative Appala Swamy (1994), Adilakshmi (1992), Efrayimu (1993) Jute ositive Chaudhary et al. (1981) Roselle ositive Negative Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Kameswara Rao (1996), Aruna et al. (1988), Sinha et al. (1986) Hari Ram Kumar (2012), Rama Kumar (2000), Aruna et al. (1988) Kenaf ositive Mohan Rao (1994) Negative Appala Swamy (1994), Efrayimu (1993), Adilakshmi (1992) Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Kameswara Rao (1996), Table 2.6 (Cont.)

75 S.N o. Character Through Crop Effect / Reference 6. Internodal length per plant 7. reen plant weight Fibre wood ratio Fibre yield per plant Fibre yield per plant Days to 50% flowering Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Roselle Negative Kenaf ositive Negative Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Rama Kumar (2000), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), ulli Bai et al. (2005b), Kameswara Rao (2002), Kameswara Rao (1996) Rani et al. (2006), Rama Kumar (2000), Aruna et al. (1988) Efrayimu (1993), Adilakshmi (1992) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Kameswara Rao (1996), Aruna et al. (1988) Rani et al. (2006), Rama Kumar (2000), Sinha et al. (1986) Mohan Rao (1994), Adilakshmi (1992) Appala Swamy (1994), Efrayimu (1993) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Rama Kumar (2000), Hemalatha (1990), admaja (1989), Anuradha and Venkateswara Rao (1993), Aruna et al. (1988) Table 2.6 (Cont.)

76 S.No. Charact er 7. reen plant weight Through Crop Effect / Reference lant height Basal stem diameter Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Hari Ram Kumar (2012), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), Aruna et al. (1988) Efrayimu (1993), Kantilal (1991) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Rama Kumar (2000), Hemalatha (1990), Anuradha and Venkateswara Rao (1993), Aruna et al. (1988), Banerjee et al. (1988), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), admaja (1989) Mohan Rao (1994), Efrayimu (1993) Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992), Kantilal (1991) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Anuradha and Venkateswara Rao (1993), Banerjee et al. (1988) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a), Hemalatha (1990), Aruna et al. (1988) Mohan Rao (1994), Efrayimu (1993), Kantilal (1991) Table 2.6 (Cont.)

77 S. No. Character 7. reen plant weight Through Crop Effect / Reference Number of nodes per plant Internod al length per plant Internoda l length per plant Fibre length per plant Negative Appala Swamy (1994), Adilakshmi (1992), Efrayimu (1993) Jute ositive Islam et al. (2001) Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) Hari Ram Kumar (2012), Rama Kumar (2000), admaja (1989), Aruna et al. (1988), Banerjee et al. (1988), Sinha et al. (1986) Appala Swamy (1994), Efrayimu (1993) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) Hari Ram Kumar (2012), Aruna et al. (1988), Sinha et al. (1986) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a), Table 2.6 (Cont.)

78 S. No. Character 7. reen plant weight 8. Fibre length per plant Through Crop Effect / Reference Fibre wood ratio Fibre yield per plant Fibre yield per plant Days to 50% flowerin g Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Kenaf ositive Jute ositive Islam et al. (2001) Roselle ositive Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Kantilal (1991) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) Hari Ram Kumar (2012), admaja (1989), Aruna et al. (1988) Appala Swamy (1994), Efrayimu (1993), Adilakshmi (1992) Mohan Rao (1994), Efrayimu (1993), Kantilal (1991) Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Rama Kumar (2000), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Anuradha and Venkateswara Rao (1993), Aruna et al. (1988), Sinha et al. (1986) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Hari Ram Kumar (2012), Rama Kumar (2000), Hemalatha (1990), admaja (1989) Table 2.6 (Cont.)

79 S.No. Character Through Crop Effect / Reference lant height Basal stem diameter Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993) Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Hari Ram Kumar (2012), Rani et al. (2006), Krishnaveni and Krishna Murthy (2000a), Hemalatha (1990) Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989) Mohan Rao (1994), Efrayimu (1993), Kantilal (1991) Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992) Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) Hari Ram Kumar (2012), ulli Bai et al. (2005b), Rama Kumar (2000), Hemalatha (1990) Table 2.6 (Cont.)

80 S.No. Character Through Crop Effect / Reference 7. Fibre length per plant Basal stem diameter Bark thickness Number of nodes per plant Internodal length per plant reen plant weight Kenaf ositive Negative Roselle ositive, Mohan Rao (1994), Efrayimu (1993), Kantilal (1991) Appala Swamy (1994), Efrayimu (1993), Adilakshmi (1992) Rani et al. (2006), ulli Bai et al. (2005b) Negative Rani et al. (2006), Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Kameswara Rao (2002), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a), Rama Kumar (2000), admaja (1989) Appala Swamy (1994), Efrayimu (1993) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) ulli Bai et al. (2005b), Kameswara Rao (2002), Kameswara Rao (1996) Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Rama Kumar (2000) Mohan Rao (1994), Efrayimu (1993) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), Kameswara Rao (2002), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) Table 2.6 (Cont.)

81 S.No. Character Through Crop Effect / Reference Negative 8. Fibre length per plant 9. Fibre wood ratio Fibre wood ratio Fibre yield per plant Days to 50% flowering Kenaf ositive Hari Ram Kumar (2012), Krishnaveni and Krishna Murthy (2000a), Rama Kumar (2000), Hemalatha (1990), admaja (1989) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Kantilal (1991) Negative Adilakshmi (1992) Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) ulli Bai et al. (2005b), admaja (1989) Appala Swamy (1994), Efrayimu (1993), Kantilal (1991) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Rama Kumar (2000), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) Rani et al. (2006), ulli Bai et al. (2005b) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Rama Kumar (2000), Table (Cont.)

82 S. No. Character Through Crop Effect / Reference 9. Fibre wood ratio lant height lant height Basal stem diameter Bark thickness Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Hari Ram Kumar (2012), Kameswara Rao (2002), Kameswara Rao (1996), admaja (1989), Aruna et al. (1988) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993) Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (1996), admaja (1989) Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Aruna et al. (1988) Appala Swamy (1994), Mohan Rao (1994), Kantilal (1991) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Hari Ram Kumar (2012), ulli Bai et al. (2005b), Rama Kumar (2000), admaja (1989) Rani et al. (2006), Kameswara Rao (2002), Kameswara Rao (1996), admaja (1989), Aruna et al. (1988) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Kantilal (1991) Negative Efrayimu (1993), Adilakshmi (1992) Roselle ositive Rani et al. (2006), Negative Rani et al. (2006), ulli Bai et al. (2005b) Table 2.6 (Cont.)

83 S. No. Character Through Crop Effect / Reference 9. Fibre wood ratio Number of nodes per plant Internod al length per plant reen plant weight Roselle ositive Negative Hari Ram Kumar (2012), admaja (1989), Aruna et al. (1988) Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989) Kenaf ositive Efrayimu (1993) Negative Kantilal (1991) Roselle ositive Appala Swamy (1994), Mohan Rao (1994), Adilakshmi (1992), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), Aruna et al. (1988) Negative ulli Bai et al. (2005b) Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Negative Mohan Rao (1994), Efrayimu (1993) Hari Ram Kumar (2012), Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992) Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989), Aruna et al. (1988) Hari Ram Kumar (2012), admaja (1989), Aruna et al. (1988) Mohan Rao (1994), Efrayimu (1993) Appala Swamy (1994), Adilakshmi (1992), Kantilal (1991) Table 2.6 (Cont.)

84 S. No. Character Through Crop Effect / Reference 10. Fibre yield per plant Fibre length per plant Fibre yield per plant Days to 50% flowering lant height Basal stem diameter Roselle ositive Negative Kenaf ositive Negative Roselle ositive Negative Kenaf ositive Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Kameswara Rao (1996), admaja (1989) Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Rama Kumar (2000), admaja (1989) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Appala Swamy (1994), Mohan Rao (1994), Efrayimu (1993) Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989), Aruna et al. (1988) Rani et al. (2006), admaja (1989) Mohan Rao (1994), Efrayimu (1993), Adilakshmi (1992), Kantilal (1991) Negative Appala Swamy (1994), Efrayimu (1993) Roselle ositive ulli Bai et al. (2005b), Negative Hari Ram Kumar(2012), Rani et al. (2006) Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b) Negative Rani et al. (2006) Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b) Table 2.6 (Cont.)

85 S. No. Character Through Crop Effect / Reference Bark thickness Number of nodes per plant Internod al length per plant reen plant weight Fibre length per plant Fibre wood ratio Roselle ositive Rani et al. (2006) Negative Rani et al. (2006) Roselle ositive Hari Ram Kumar (2012), Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006) Negative ulli Bai et al. (2005b) Roselle ositive Hari Ram Kumar (2012), Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006) Negative Rani et al. (2006), ulli Bai et al. (2005b) Roselle ositive Hari Ram Kumar (2012), Rani et al. (2006) Negative ulli Bai et al. (2005b) : henotypic : enotypic

86 Chapter III MATERIAL AND METHODS 3.1 MATERIAL The experimental material for the stability analysis consisted of 30 genotypes of roselle derived from various breeding programmes developed under All India Network roject on Jute and Allied Fibres (AINJAF). The material was made available for study by Agricultural Research Station, Amadalavalasa (Andhra radesh). The source of origin and the important morphological characters of the genotypes are furnished in Table METHODS Field study was conducted at Agricultural Research Station Farm, Amadalavalasa located between 18 o 20' and 19º10' North latitude and 83º50' and 84 o 50' East longitude at an altitude of 10 m above mean sea level, during kharif The meteorological data pertaining to the investigation period are presented in appendix A. Thirty genotypes of roselle were sown in three dates of sowing with 21 days intervals i.e., 18 th June, 10 th July and 31 th July, 2013 thus providing three environments for the study. The experiment was laid out in a randomized block design replicated thrice. Each genotype was sown in three rows of three meter length with a spacing of 30cm between the rows and 10cm within the row. Recommended package of practices and need based plant protection measures were followed to raise a healthy crop. Experimental field with different dates of sowing is shown in late 3.1. Observations were recorded on five randomly selected plants in each treatment and in each replication. The plants were selected from the middle of the row excluding the border plants. The crop was harvested at 50 % flowering stage on plot basis. The fibre was extracted by adopting standard process of retting.

87 Table 3.1. Source of origin of genotypes employed in the study and morphological characters of the genotypes of roselle (Hibiscus sabdariffa L.) S.No enotype Origin Morphological characters 1 ER-1 Exotic collection 2 ER-10 Exotic collection 3 ER-38 Exotic collection 4 ER-58 Exotic collection 5 ER-63 Exotic collection 6 AR-12 Indigenous local collection 7 AR-71 Indigenous local collection 8 AR-72 Indigenous local collection Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent dark pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. 9 R-28 Indigenous local collection Rough and bristled pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. 10 R-93 Indigenous local collection Rough and bristled pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Table 3.1 (Cont.)

88 S.No enotypes Origin Morphological characters 11 R-78 Indigenous local collection 12 R-134 Indigenous local collection 13 R-200 Indigenous local collection 14 R-83 Indigenous local collection 15 AS Indigenous local collection 16 AS Indigenous local collection 17 AS Indigenous local collection 18 CRIJAFR-2 CRIJAF, Barrackpore (W.B.) 19 CRIJAFR-8 CRIJAF, Barrackpore (W.B.) Rough and bristled pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Smooth non-pubescent green stem, entire leaf and light yellow flower with yellow in inner lobe. Non-pubescent smooth green stem, lobed leaf and light yellow flower with yellow in inner lobe. Smooth non-pubescent dark pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough and bristled pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough and bristled pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent light pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough and bristled dark pink stem, lobed leaf and light yellow flower with deep red in inner lobe. 20 JRR-9 Odisha Rough pubescent nodal pink with light pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Table 3.1 (Cont.)

89 S. No enotypes Origin Morphological characters 21 JRRM-9-1 Odisha Rough and bristled pubescent nodal pink with light pink stem, lobed leaf and light yellow flower with deep red in inner lobe. 22 AHS-160 ARS, Amadalavalasa (A..) 23 AHS-161 ARS, Amadalavalasa (A..) 24 AHS-152 ARS, Amadalavalasa (A..) 25 AHS-162 ARS, Amadalavalasa (A..) 26 AHS-172 ARS, Amadalavalasa (A..) 27 AHS-179 ARS, Amadalavalasa (A..) 28 AMV-4 ARS, Amadalavalasa (A..) 29 AMV-5 ARS, Amadalavalasa (A..) 30 HS-4288 CRIJAF, Barrackpore (W.B.) CRIJAF Central Research Institute on Jute and Allied Fibres ARS Agricultural Research Station A.. Andhra radesh W.B. West Bengal Rough pubescent dark pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent dark pink, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent dark pink, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent dark pink, lobed leaf and light yellow flower with deep red in inner lobe. Rough and bristled pubescent dark pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough and bristled pubescent dark pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent dark pink green stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent light pink stem, lobed leaf and light yellow flower with deep red in inner lobe. Rough pubescent nodal pink green stem, lobed leaf and light yellow flower with deep red in inner lobe.

90 3. 1. EXERIMENTAL FIELD OF ROSELLE WITH DIFFERENT DATES OF SOWIN

91 3.3 COLLECTION OF DATA The following observations were recorded Days to 50 % flowering: The number of days interval from sowing of the crop to the flowering of 50 % of plants in each replication lant height (cm): lant height was measured from base of the stem to the tip of the plant at the time of harvest Basal stem diameter (mm): Basal stem diameter in milliimeters was calibrated with the help of electronic vernier calipers Bark thickness (mm): Bark thickness in milliimeters was calibrated with the help of electronic vernier calipers. This was obtained by deducting the value of basal wood diameter from basal stem diameter Number of nodes per plant: The number of nodes on the main stem was counted at the time of harvest Internodal length (cm): The length of five internodes on the main stem in the middle region was measured and the average of these was taken as mean internodal length of the stem reen plant weight (g): The green plant weight of individual plant in grams was recorded at the time of harvest Fibre length (cm): After extraction of fibre, the length of the fibre of the individual plant was measured in centimeters using calibrated meter scale Fibre wood ratio: The ratio was obtained by dividing the weight of the fibre by the weight of the wood, after extraction of fibre Fibre yield per plant (g): After extraction of fibre, the fibre yield per plant was recorded in grams. 3.4 STATISTICAL METHODS The data recorded on the sampled plants for various characters were averaged replication-wise and mean values were subjected to the following statistical analysis. 1. Analysis of variance 2. Estimation of genetic parameters 3. Character association 4. ath coefficient analysis 5. Stability analysis

92 3.4.1 Analysis of variance The analysis of variance for each character was done as per the standard statistical procedure given by Cochran and Cox (1950) for randomized block design. Where, Y ij = µ + r i + t j + e ij Y ij = erformance of the j th genotype in the i th block. µ = general mean r i = effect of i th replication t j = effect of j th genotype e ij = random error associated with i th replication and j th genotype Analysis of variance (ANOVA) table for randomized block design Source of variation D.f. M.S.S. F ratio Replication r-1 M r M r / M e enotypes t-1 M g M g / M e Error (r-1)(t-1) M e Where, D.f. = Degrees of freedom M.S.S. = Mean sum of squares M r M g M e r g = Mean sum of squares due to replications = Mean sum of squares due to genotypes = Mean sum of squares due to error = Replication = enotypes The test of significance was carried out using F table values given by Fisher and Yates (1963) Estimation of genetic parameters The genotypic and phenotypic variances were calculated as per Burton and Devane (1953). enotypic variance (σ 2 g ) = (M g M e ) / r henotypic variance (σ 2 p ) = (σ 2 2 g ) + (σ e )

93 Where, M g = Mean sum of squares due to genotypes r = Number of replications M e = Mean sum of squares due to error σ e 2 = Error variance Coefficients of variation henotypic and genotypic coefficients of variation (CV and CV) were computed according to Burton (1952). CV (%) = CV (%) = x 100 x 100 Categorization of the range of variation was followed by Sivasubramanian and Madhava Menon (1973). Low = less than 10% Moderate = 10% - 20% High = More than 20% Heritability in broad sense [(h 2 (b)] Heritability in broad sense was estimated as per Allard (1960). h 2 (b) = ( ) () x 100 The range of heritability in broad sense [(h 2 (b)] was categorized, as proposed by Johnson et al. (1955). Low = less than 30% Moderate = 30% - 60% High = More than 60% enetic advance (A) This was estimated as per the formula proposed by Lush (1949) and Johnson et al. (1955). A = k x σ p x h 2 (b)

94 Where, k = Selection differential at 5 % selection intensity which accounts to a constant value of h 2 (b) = Heritability in broad sense σ p = henotypic standard deviation enetic advance as per cent of mean (AM) AM = (A/rand mean) x 100 The range of genetic advance as per cent of mean was classified as suggested by Robinson (1966) and Johnson et al. (1955). Low = less than 10 % Moderate = % High = more than 20 % CHARACTER ASSOCIATION henotypic and genotypic correlations were worked out by adopting the formulae suggested by Falconer (1964). henotypic coefficient of correlation (r p ) = r X X p cov( X X ) p / v( X ) p. v( X ) p i j i Where, r(x i,x j ) p = henotypic correlation between i th and j th characters Cov(X i,x j ) p = henotypic covariance between i th and j th characters V(X i ) p = henotypic variance of i th character V(X j ) p = henotypic variance of j th character j i j enotypic coefficient of correlation (r g ) = r X X g Cov.( X X ) g / v( X ) g. v( X g i j i j i j ) Where, r(x i,x j ) g Cov(X i,x j ) g V(X i ) g V(X j ) g = enotypic correlation between i th and j th characters = enotypic covariance between i th and j th characters = enotypic variance of i th character = enotypic variance of j th character

95 Significance of correlation coefficients were tested by comparing phenotypic and genotypic correlation coefficients with the table values (Fisher and Yates, 1963) at (n-2) degree of freedom at 5% and 1% level where n denotes the number of paired observations tested in the calculations ATH COEFFICIENT ANALYSIS ath coefficient analysis suggested by Wright (1921) and elaborated by Dewey and Lu (1959), was used to calculate the direct and indirect contribution of various traits towards fibre yield. For estimation of various direct and indirect effects, a set of simultaneous equations were formed: r 1y = 1y + r 12 2y + r 13 3y +.+ r 1k ky r 2y = r 21 1y + 2y + r 23 3y +.+ r 2k ky r iy = r i1 1y + r i2 2y + r i3 3y +.+ r ik ky r ky = r k1 1y + r k2 2y + r k3 3y +.+ r kk ky Where, r 1y to r ky = Coefficient of correlations between causal factors 1 to K and dependent character Y r 12 to r k-1,k =Coefficient of correlations among causal factors 1y to ky = Direct effects of characters 1 to k on character Y The above equations were written in a matrix form as under: A C B iy Y Y i i i i iy Y Y r r r r r r r r r then B = [C] -1 A Where, ii i i i i i C C C C C C C C C C C C C ] [

96 The direct effects were calculated as follows 1 Y k i 1 C 1 i r iy 2 Y k i 1 C 2 i r iy p iy k i 1 c 1 i r iy Residual effect In plant breeding, it is very difficult to have complete knowledge of all components traits of yield. The residual effect permits precise explanation about the pattern of interaction of other possible components of yield. In other words, residual effect measures a role of other possible independent variables which were not included in the study on the dependent variable. The residual effect was estimated with the help of direct effects and simple correlation coefficients. Where, I = 2 R y + Σ iy r iy 2 R y is the square of the residual effect Stability analysis studies Analysis of variance of genotype means was computed for each agronomic variable in each location. The data were pooled over environments as the coefficient of variation values in each environment were generally low, though the Bartlett s Chi-square values showed significance in case of certain characters (omez and omez, 1984). Bartlett s test of homogeneity (Bartlett, 1937) as quoted by anse and Sukhatme (1961). S 2 1 n n I S 2 r 2 K( nlogs 2 n I logs 2 r )

97 Where, n 1 C 1 3nk n = Number of environments 2 S = Error mean squares of locations or environments r K = Error degrees of freedom 2 2 (18 d.f) = C If calculated 2 is non-significant, the experimental errors of trials may be regarded as being homogeneous Eberhart and Russell s (1966) model Stability parameters were computed as given by Eberhart and Russell (1966). The model is Y ij I i j S ij i varies from 1 to 30 genotypes j varies from 1 to 3 environments Where, Y Mean of i th genotype in j th environment ij = Mean of all genotypes over all environments = Regression coefficient of i th genotype on the environmental index i which measures the response of this genotype to varying environments I = The environmental index which is defined as the deviation of the j mean of all the genotypes in an environment from the overall mean

98 S = The deviation from regression of the i th genotype at j th environment ij Analysis of variance for stability The analysis of variance as proposed by Eberhart and Russell (1966) is given in given table 3.2. Table 3.2. Analysis of variance as proposed by Eberhart and Russell (1966) Source d.f Sum of squares Mean squares Total (ge-1) 2 C. F 2 enotypes (g-1) 1/ e Y C. F MS 1 Environment+ (enotype x Environment) g(e-1) i Y j ij i Y 1/ g Y. j i j 2 ij i. Y Environment (Linear) 1 2 enotype x Environment (Linear) ooled deviations Deviation due to genotype 1 ooled error (g-1) g(e-2) (e-2) e(r-1)(g-1) Y j 2 ij Y j S j j I j i 2 2 i. / e I 2 2 ( Y I ) I ij j j - j j j Environment (linear) ss 2 ij 2 ij 2 Y / e I j i. 2 i j 2 ij j j MS 2 S MS 3 / I g = enotype e = Environment r = Replication D.f. = Degrees of freedom Estimation of stability parameters The regression coefficient (b) and the deviation from the line of regression (S 2 d) were estimated as follows: a) Regression coefficient: j 2 j

99 b Y j ij I j / I j 2 j Where, Y I j j ij j 2 j = The sum of products of environmental index (I j ) with corresponding mean of that genotype at each environment (Y ij ) I = The sum of squares of the environmental index (I j ) b) Mean square deviations (S 2 d) from linear regression: S 2 d 2 S 2 ij S j e ( e 2) r Where, S j 2 ij Y j 2 ij 2 Y I Y ij j i. j 2 g I j j 2 Where, S = Variance due to deviation from regression for a genotype j 2 ij 2 Y i. Y 2 = Variance due to dependent variable j ij g ( Y I ) 2 / I = Variance due to regression j ij j j 2 j 2 S e = The estimate of pooled error e g r = Number of environments = Number of genotypes = Number of replications The various computational steps involved in the estimation are as follows:

100 Computation of environmental index (I j ) I j Y i g ij Y i j ge ij with I = 0 j j Computation of regression coefficient (b) for each genotype Y I j ij b I j 2 j j a) For each value of regression coefficient, I is common. j 2 j b) Y I for each genotype is the sum of products of environmental index ij j j (I j ) with the corresponding mean (X ) of that genotype in each environment. These values may be obtained in the following manner Where X. I Y I S j j ij X = Matrix of means j j I = Vector for environmental index and S = Vector for sum of products, i.e., Y I ij j Computation of S 2 d In a regression analysis, it is possible to partition the variance of the dependent variable (Y) into two parts, the one which explains the linearity j

101 between dependent and independent variables (variance due to regression) and the other which explains the variance due to deviations from linearity. 2 Y 2 2 regression + deviation from the regression The variance of mean over different locations with regard to individual genotype may be obtained in the following way. 2 g i Y j 2 ij ( Y 2 i. / g) The variance due to deviations from regression 2 S for a genotype being ij j Where, S j 2 ij Y j 2 ij 2 Y I Y ij j i. j 2 g I j j 2 2 Y i. Y 2 = Variance due to dependent variable and j ij g ( Y I ) 2 / I = The variance due to regression j ij j j 2 j Y I Y I Y I j ij j j ij j j ij j because, 2 2 I I j j 2 j j = b Y I j ij j From follows: S Values, the stability parameters S 2 d for each variety is computed as j 2 ij 2 S d S j 2 ij /( e 2) S 2 e / r Deviation from regression Mean square = - deviation Degrees of freedom for environment ooled error Number of replications

102 The variance due to genotypes, environments and the pooled error were the same as those calculated in the pooled analysis of data, except that the total sum of squares was mainly partitioned into 3 main components namely (1) sum of squares due to genotypes (2) sum of squares due to environments + (genotype x environment) and (3) pooled error. Again sum of squares due to genotype x environment was further partitioned into 2 parts namely (a) sum of squares due to genotype x environment (linear) which is in fact sum of squares due to regression and (b) sum of squares due to deviations from linearity of response (i.e., sum of squares due to deviation). Sum of squares due to environment + enotype x environment = Y 2 Y 2 / ij i e i j j. Sum of squares due to environment (linear) 1 = 2 Y I / I. j j j g j j 2 Sum of squares due to genotype x environment (linear) 2 = 2 Y I / I - SS environment (linear) j ij j j j j Where, 2 Y I I by I j ij j 2 / j j for each genotype j ij j Tests of significance The following tests of significance were carried out : 1. To test the significance of the differences among genotype means namely, H o the F test used was Mean square due to genotypes MS 1 F = =

103 Mean square due to pooled deviation MS 3 2. To test that the genotypes did not differ due to regression on environmental index, i.e., H 0 b 1 b 2... b 10, the F test used was Mean square due to genotype x environment (linear) MS 2 F = = Mean square due to pooled deviation MS 3 3. Individual deviation from linear regression was tested as follows: 2 F S / e 2 j ij / pooled error mean sum of squares t value at (g-2) d.f at =0.05 and 0.01 levels. 4. The hypothesis that any regression coefficient does not differ from unity or from zero was tested by the appropriate t test, i.e., 1 b t SE( b) SE( b) S j 2 ij /( e 2) / I j 2 j t value at (g-2) d.f at p = 0.05 and 0.01 levels Additive Main effects and Multiplicative Interaction (AMMI) model (auch, 1988) AMMI model is a useful technique to capture non-linear interaction, when traditional stability model techniques fail to perceive important effects in studies of E interaction. Even a single rincipal Component Analysis (CA) axis can capture much large amount of E interaction when compared to the variation captured by the linear component of the traditional stability models. Due to the above salient features, for the present study, AMMI modeling methodology was employed for the identification of elite genotypes.

104 Additive model The model of yield response of the i th variety in the j th environment is Y ij g e i j d ij Where, = Overall mean yield g = Deviation of the mean of genotype i from i e = Deviation of environment j from j d = Residual deviation not explained by the components, g ij i and e j Y = Yield response of i th variety in the j th environment. ij d partitioned as ij d ij C (1) ij ij Where, C ij = Random variable representing interaction between the n genotypes and the environments with zero means and variance 2 e 2 = Residual errors with zero mean and variance ij The expectation of the variety by environments mean squares ( x EMS) is a linear combination of these two parameters: 2 2 E( EMS) e / r The percentage of structural variability in the deviations from the additive model, d ij, is estimated by 100 ( EMS EMS / r) EMS Multiplicative interactions

105 In principal component analysis (CA), the elements in a matrix D, say d, D [ d ] are decomposed as a sum of multiplicative terms. ij ij d ij q k 1 V k ik jk Where, q = Rank of the matrix D,,... q = Decreasing sequence of singular values of D. 1 2 ik = i th component of the k th left singular vector of D V jk = j th component of the k th right singular vector of D. The decomposition in above equation is exact & complete, so the problem of finding a partition of d ij like equation (1) is to choose a value m less than q such that d ij m k1 V k ik jk ij Where the some of products is e ij of equation (1) which should account for a large part of the structural variability in D. The combination of all above equations has become known as the Additive Main Effects and Multiplicative Interaction model of order m (AMMI) which can be written as Y ij g i e j m k 1 V k ik jk ij Where, Y ij = Mean yield of the i th genotype in the j th environment = rand mean g i = i th genotype

106 e j = j th environment k = Number of CA axes retained in the model k = Singular value for the CA axis, k u ik = i th genotype CA score for the axis, k v jk = j th environment CA score for the axis, k ij = Residual Other stability parameters The following stability parameters (other than mean, regression coefficient, deviation from the linear regression and ASV) were computed as follows : Variance of mean over environments: The variance of mean of values over 3 environments of each genotype was computed. The genotype with least variance or maximum information was considered stable to environmental fluctuations and vice versa Lewis (1954) stability factor: Lewis (1954) suggested a measure of phenotypic stability which he termed stability factor expressed as: Stability factor (SF) = X H. E X L. E Where, X = Mean value H.E. = High yielding environment L.E. = Low yielding environment (S.F. = 1 indicates maximum phenotypic stability The greater the stability factor deviates from unity, the less stable is the phenotype) laisted and eterson s (1959) model of variance over E interaction ( 2 ge):

107 laisted and eterson (1959) described a procedure to characterize the stability of the performance of several varieties. A combined analysis of variance at all locations was computed for each pair of varieties, g(g-1)/2 pairs for g varieties and an estimate 2 2 of ge was obtained for each pair and for each genotype (mean of ge for a particular genotype). The genotype with the smallest mean value was considered to be the most stable. This technique becomes cumbersome with an increase in the number of varieties. Table 3.3: Structure of pair wise ANOVA Source d.f. M.S. E.M.S. Total Environments (egr-1) (e-1) Replications /environment e(r-1) Varieties (g-1) Varieties x Environments (g-1) (e-1) ge Error e(r-1) (g-1) 2 Where, Mean e = Number of environments g = Number of genotypes r = Number of replications ge( MS ) error 2 ge1 2 MS 3 2 ge for genotype 1 = ge Wricke s (1962) Ecovalence method Wricke (1962 and 1966) developed a method to estimate the ecological valence or in short, ecovalence (Wi) of genotypes (g) grown under several environments (n) to measure the stability of performance. Ecovalence (W i ) is the contribution of each genotype to the genotype-environment interaction sum of squares and is expressed as percentage. 9 Y W Y i j ij n Where, W i = The ecovalence of i th genotype i. Y g. j Y.. gn 2

108 Y ij = The basic observation for the mean performance of i th genotype in j th environment. The lower the ecovalence of a genotype, the smaller its fluctuations from the experimental mean under different environments and thus a smaller share in the interaction sum of squares. (Accordingly, the genotype with the least ecovalence can be considered as more stable and the genotypes with a high ecovalence have a poor stability) enotypic stability (D 2 i) by Hanson (1970) Hanson proposed a statistic, which combines the information from equivalence and regression into a simple useful measure of yield stability. This measure which includes that part of the variance of environmental effects which could be reduced by breeding and selection was termed as genotypic stability (D 2 (i)), suppose the differences between regression coefficients are completely amenable to breeding procedures and denote the observed minimum of b by b min, then a stable genotype is one which does not deviate from the straight line, Y = Y i. + b min e The genotypic stability j. statistic therefore becomes D 2 ( i) i ( X X i. b X b X ij min j min Environmental variance, ecovalence and deviation mean squares are special cases of genotypic stability; when b min = 0, [D 2 (i)/(s-1)] = S 2 yi, when b min = 1, D 2 (i) = W i and for b min = b i D 2 (i)/(s-2) = S 2 di. (The genotype with least variance over environments was considered to be stable to environmental fluctuations and was ranked 1 st and vice versa)...) Shukla s (1972) stability variance ( 2 i) It is a measure of unbiased partitioning of the total variation due to genotype environment interaction into components assignable to individual cultivars. It indicated that the cultivars with significant mean squares were suggested to be unstable i.e., nonsignificance showed stability. It is the estimate of variance of g ij + e ij in terms of the residuals in a two-way classification and is a useful indicator of the stability of the i th genotype. i 2 2 ( X X X X ) / ( p 2)( q 1) ij i.. j.. SS ( E)/ ( 1)( 2)( q 1)

109 Ranking of genotypes based on different stability parameters Mean (µ): The genotype with greater mean performance was ranked first and least was ranked 30 th Mean of variance over environments ( 2 v): The genotype with least variance over environments was considered to be stable to environmental fluctuations and was ranked 1 st and vice versa Lewis stability factor (SF): Stability factor of unity value indicates maximum stability. The stability factor values were ranked such that least deviation from unity ranked 1 st and larger deviation was ranked 30 th laisted and eterson s ( 2 ge) value: The genotype with the smallest mean value of 2 ge was considered to be the most stable and ranked 1 st Wricke s Ecovalence: The genotype with the least ecovalence can be considered as more stable and ranked 1 st. The genotype with high ecovalence have a poor stability and ranked 30 th Regression coefficient (b i ) of Eberhart and Russell (1966) model: The deviations of bi values from unity (b i =1.00) was ranked such that least deviation was ranked first and larger deviation was ranked 30 th Deviation from regression (s 2 di) values of Eberhart and Russell (1966) model: The genotype with least s 2 di (greater stability) was ranked first whereas the genotype with maximum s 2 di (least stability) was ranked as 30 th Hanson enotypic stability (D 2 i): The genotype with least variance over environments was considered to be stable to environmental fluctuations and was ranked 1 st and vice versa Shukla s stability variance ( 2 i): The genotype with least stability variance ( 2 i) was ranked 1 st (greater stability) where as the genotype with maximum stability variance (least stability) was ranked as 30 th AMMI stability value (ASV): The genotype with least ASV value was considered to be stable to environmental fluctuations and was ranked 1 st and vice versa.

110 Chapter IV RESULTS AND DISCUSSION The data collected in the present investigation entitled Stability analysis in Roselle (Hibiscus sabdariffa L.) on 30 genotypes pertaining to 10 quantitative characters viz., days to 50% flowering, plant height (cm), basal stem diameter (mm), bark thickness (mm), number of nodes per plant, internodal length per plant (cm), green plant weight (g), fibre length per plant (cm), fibre wood ratio and fibre yield per plant (g) over three environments (dates of sowing viz., E 1 : , E 2 : and E 3 : ) at Agricultural Research Station Farm, Amadalavalasa was subjected to statistical analysis and the results thus obtained are presented character-wise here under: 4.1 Analysis of variance 4.2 Mean, genetic variability, heritability and genetic advance as per cent of mean 4.3 Character association 4.4 ath coefficient analysis 4.5 Stability analysis 4.1 ANALYSIS OF VARIANCE The ANOVA of three individual environments pertaining to ten quantitative characters revealed the presence of significant differences among the genotypes for all the characters, indicating considerable variation among the genotypes (Table 4.1). 4.2 MEAN, ENETIC VARIABILITY, HERITABILITY AND ENETIC ADVANCE AS ER CENT OF MEAN The success of any crop improvement programme essentially depends on the nature and magnitude of variability present in the crop. Knowledge on nature and magnitude of genetic variability is of immense value for planning effective breeding programme to improve the yield potential of genotypes. Besides genetic variability, knowledge on heritability and genetic advance plays a predictive role in breeding

111 through the expression of phenotypic reliability which serves as a guide to its breeding value. Estimates of heritability alone will not be of much value for selection on phenotypic performance hence it was suggested that genetic gain should be considered in conjuction with heritability (Johnson et al., 1955). Burton (1952) and Swarup and Chaungle (1962) indicated that genetic variability with heritability estimates would give a better idea on the amount of genetic advance expected through selection. In the present investigation, estimates of mean, range, phenotypic coefficient of variation (CV), genotypic coefficient of variation (CV), heritability in broad sense [h 2 (b)] and genetic advance as per cent of mean (AM) for 30 roselle genotypes over three environments were computed and presented in Tables 4.2 and 4.3. The graphical representation of CV, CV, ECV, h 2 (b) and AM over three environments are presented in Fig. 4.1 to Days to 50% flowering The estimates of CV and CV were low in all the three environments, indicating narrow genetic variability. Similar results were reported by Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993), Aruna et al. (1989) and admaja (1989). High heritability coupled with low genetic advance as per cent of mean was recorded in all three environments indicating the preponderance of non-additive gene action attributed to high influence of environment. Hence, simple selection for such trait may not be effective. Similar results were reported by Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al (2005), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) and admaja (1989). Among all the three environments, environment III recorded early flowering followed by environment II, while it was late in environment I. Among 30 genotypes, AHS-172 (89.00) recorded least number of days to 50% flowering while R-134 (148.00) recorded maximum number of days to 50% flowering.

112 4.2.2 lant height (cm) The estimates of CV and CV were low in all the three environments, indicating narrow genetic variability. Similar findings were reported by Rani et al. (2006), Ibrahim and Hussein (2006), Krishnaveni and Krishna Murthy (2000b) and admaja (1989). Moderate heritability coupled with low genetic advance as per cent of mean was recorded in environment I indicating non additive gene action, hence improvement in stable characters is possible through hybridization followed by selection. Similar result was reported by ulli Bai et al. (2005). Moderate heritability coupled with moderate genetic advance as per cent of mean was observed in environment II indicating both additive and non-additive gene action involved in the expression of the trait, hence, heterosis breeding may be useful. these results are in confirmity with Hari Ram Kumar (2012), Rani et al. (2006), Ibrahim and Hussein (2006), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996) Anuradha and Venkateswara Rao (1993) and uptaji (1993). Low heritability coupled with low genetic advance as per cent of mean was observed in environment III, indicating non-additive gene action and simple selection of this trait may not be effective for improvement. Similar results were reported by Subramanyam et al. (1995), Madhavi Rani (1990) in kenaf and aramjit Singh and Buttar (2013) in cotton. Among all the environments, environment I was favourable for plant height while environment IIΙ was least favourable on the basis of mean performance. Out of 30 genotypes evaluated, AHS-172 (364.47) was the tallest while AS (202.93) was the dwarf stature genotype Basal stem diameter The estimates of CV and CV were low in all the three environments, indicating narrow genetic variability. These results were in accordance with Krishnaveni and Krishna Murthy (2000b), Kameswara Rao (1996), Aruna et al. (1989) and admaja (1989). Low heritability coupled with low genetic advance as per cent of mean was observed in environment Ι and III, indicating non-additive gene action and simple

113 selection of this trait may not be effective. These results are in agreement with Nasima Ali and Sasmal (2011) and Chaudhury et al. (1985) in jute. Medium heritability coupled with low genetic advance as per cent of mean was recorded in environment IΙ indicating non additive gene action, hence hybridization followed by selection is more desirable. Similar results were observed by ulli Bai et al (2005), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) and Aruna et al. (1989) Among all the environments, environment I was favourable for basal stem diameter, while environment IIΙ was least favourable on the basis of mean performance. Among the 30 genotypes, AHS-172 (24.10) recorded maximum basal stem diameter, while, R-200 (10.91) recorded minimum basal stem diameter Bark thickness The estimates of CV and CV were low in environment Ι and ΙΙΙ indicating narrow genetic variability. The estimates of CV and CV were moderate in environment ΙΙ indicating wider genetic variability. Similar results were reported by Rani et al. (2006), ulli Bai et al. (2005) and admaja (1989) in roselle. Low heritability coupled with moderate genetic advance as per cent of mean was observed in environment I and ΙΙ. Low heritability couple with low genetic advance as per cent of mean was observed in environment III, indicating non-additive gene action and simple selection of this trait may not be effective. Similar results are reported by admaja (1989). Among all the environments, environment I was favourable for bark thickness, while environment IIΙ was least favourable on the basis of mean performance. Out of 30 genotypes evaluated, JRR-9 (4.82) had thick bark, while, AMV-5 (1.75) had thin bark Number of nodes per plant The estimates of CV and CV were low in all the three environments indicating narrow genetic variability. These results are in agreement with Rani et al. (2006), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997) and uptaji (1993).

114 Medium heritability coupled with low genetic advance as per cent of mean was recorded in environment I indicating non additive gene action, hence hybridization followed by selection is more desirable. These results are in harmony with the reports of Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) and admaja (1989). Low heritability couple with low genetic advance as percent mean was observed in environment II and ΙΙΙ, indicating non-additive gene action and selection of this trait may not be effective. Similar results are reported by Mostofa et al. (2002), Adilakshmi (1992) in kenaf and Chaudhury et al. (1985) in jute. Among all the environments, environment I was favourable for number of nodes, while environment IIΙ was least favourable on the basis of mean nodes performance. Among the 30 genotypes, R-83 (77.30) had maximum number of nodes where as, AR-72 (36.06) had minimum number of nodes Internodal length per plant The estimates of CV and CV were low in all the three environments, indicating narrow genetic variability. Similar results were reported by Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al (2005), Rama Kumar (2000) and Kameswara Rao (1996). Medium heritability coupled with low genetic advance as per cent of mean was recorded in environment I and ΙΙ indicating non additive gene action, hence hybridization followed by selection is more desirable for the improvement of the trait. Similar results are reported by Hari Ram Kumar (2012), ulli Bai et al. (2005), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) and Aruna et al. (1989). Low heritability coupled with low genetic advance as per cent of mean was observed in environment IIΙ, indicating non-additive gene action and selection of this trait may not be effective. Similar findings are reported by Subramanyam et al. (1995), Adilakshmi (1992) and Madhavi Rani (1990) in kenaf. Among all the environments, environment IΙΙ was favourable for intermodal length where as environment IΙ was least favourable on the basis of mean internodal length performance. Among the 30 genotypes, R-93 (4.47) had maximum internodal length, while, AS-80-29(6.85) had minimum internodal length.

115 4.2.7 reen plant weight per plant The estimates of CV and CV were moderate in all the three environments, indicating wider genetic variability. These results are in harmony with the reports of Hari Ram Kumar (2012), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) and admaja (1989). Medium heritability coupled with moderate genetic advance as per cent of mean was observed in environment I and ΙΙΙ indicating both additive and non-additive gene action and hence, heterosis breeding may be useful. Moderate heritability coupled with high genetic advance as per cent of mean was noted in environment IΙ indicating additive gene effects and hence, selection may be effective. Similar results are observed by Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000b), uptaji and Subramanyam (1997), Kameswara Rao (1996), Anuradha and Venkateswara Rao (1993), uptaji (1993) and admaja (1989). Among all the environments, environment I was favourable for green plant weight, while environment IΙΙ was least favourable on the basis of mean performance over three environments. Out of 30 genotypes evaluated, AR-72 (117.11) recorded maximum green plant weight, while, CRIJAFR-8 (607.92) noted minimum green plant weight Fibre length per plant The estimates of CV and CV were low in all the three environments indicating the existence of narrow genetic variability. Similar results are reported by ulli Bai et al. (2005), Krishnaveni and Krishna Murthy (2000b) and admaja (1989). Medium heritability coupled with moderate genetic advance as per cent of mean was observed in environment I indicating both additive and non-additive gene action and hence, heterosis breeding may be useful. The findings are in accordance with Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996) and uptaji (1993). Low heritability coupled with low genetic advance as per cent of mean was observed in environment ΙΙ and IIΙ indicating non-additive gene action and selection of this trait may not be effective. Similar results are reported by Krishnaveni and Krishna Murthy (2000b).

116 Among the environments, environment I was favourable for fibre length per plant, while environment IΙΙ was least favourable on the basis of mean fibre length performance. Among the 30 genotypes, R-200 (190.67) recorded maximum fibre length per plant, while, AHS-172 (412.41) showed minimum fibre length per plant Fibre wood ratio The estimates of CV and CV were low in environment Ι indicating narrow genetic variability. Similar results are observed by Subramanyam et al. (1995), Efrayimu (1993), Kantilal (1991), Madhavi Rani (1990) in kenaf. The estimates of CV and CV were moderate in environment ΙΙ and high in environment ΙΙΙ indicating wider genetic variability. These results are in harmony with the findings of Hari Ram Kumar (2012), ulli Bai et al. (2005), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) and admaja (1989). Low heritability coupled with low genetic advance as per cent of mean was observed in environment Ι indicating non-additive gene action and selection of this trait may not be effective. Similar result was reported by admaja (1989). Moderate heritability coupled with high genetic advance as per cent of mean was noted in environment IΙ indicating additive gene effects and hence, selection may be effective. High heritability coupled with high genetic advance as per cent of mean was observed in environment IIΙ indicating additive gene effects and hence, selection may be effective. Similar results are reported by Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000), Among all the environments, environment IΙΙ was favourable for fibre wood ratio, while environment I was least favourable on the basis of mean fibre wood ratio. Out of 30 genotypes evaluated, R-200 (0.79) recorded maximum fibre wood ratio where as, R-28 (0.25) and AS (0.25) noted minimum fibre wood ratio Fibre yield per plant The estimates of CV and CV were high in environment Ι and moderate in environment ΙΙ and ΙΙΙ indicating wider genetic variability. Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000), uptaji and Subramanyam (1997), Kameswara Rao (1996), uptaji (1993) and admaja (1989) also reported similar results for this trait.

117 Moderate heritability coupled with high genetic advance as per cent of mean was observed in environment I indicating additive gene effects and hence, simple selection may be effective. High heritability coupled with high genetic advance as per cent of mean was observed in environment II. Indicated the predominance of additive gene action governing the inheritance of this character and offers the scope for improvement through simple selection procedures. Moderate heritability coupled with moderate genetic advance as per cent of mean was observed in environment IΙΙ indicating both additive and non-additive gene action and hence, heterosis breeding may be useful. These results are in agreement with Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005) and Rama Kumar (2000). Among all the environments, environment I was favourable for fibre yield per plant, while environment IΙΙ was least favourable on the basis of mean yield performance. Among the 30 genotypes, AHS-160 (40.54) recorded maximum fibre yield per plant while, ER-38 (7.08) had minimum fibre yield per plant. 4.3 CHARACTER ASSOCIATION Yield is a complex quantitative trait and considerably affected by environment. Therefore, selection of genotypes based on yield is not effective. enetic correlation measures the magnitude of relationship between various plant characters that determines the component characters on which selection can be made for improvement in yield (Johnson et al., 1955). enotypic correlation is the inherent association between two variables. It may be either due to pleiotropic action of genes or linkage. If the correlation between fibre yield in roselle and a character is due to the direct effect of the character, it reflects a true relationship between them and selection can be practised for such characters in order to improve yield. However, if the correlation is mainly due to indirect effect of the character through other component traits, the breeder has to select for the trait through which the indirect effect is expected. Thus, correlation coefficients are useful if indirect selection of a secondary trait is to be used for improving the primary trait of interest. A great yield response is obtained when the character for which indirect selection is practiced has a high heritability and a positive correlation with yield. Thus, correlation is an important tool helping in deciding the breeding procedure for genetic improvement of fibre yield in roselle.

118 In the present investigation, phenotypic and genotypic correlation coefficients between fibre yield and other related component characters, among themselves in roselle were estimated and presented in Tables 4.4 to Days to 50% flowering In environment I, this trait showed negative significant association with basal stem diameter (-0.329*; **), fibre length per plant (-0.388**, **) and fibre yield per plant (-0.383**, **) both at phenotypic and genotypic levels while with number of nodes per plant (-0.484**), green plant weight (-0.432**) and fibre wood ratio (-0.324*) only at genotypic level. These results are in accordance with Hari Ram Kumar (2012), Rama Kumar (2000) and admaja (1989). The association with other component characters viz., plant height ( ; ), bark thickness (-0.027; ) both at phenotypic and genotypic levels and number of nodes per plant (-0.283), green plant weight (-0.268) and fibre wood ratio (-0.136) at phenotypic level showed negative non-significant association. These results are in conformity with the findings of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Anuradha and Suriyakumari (2002), Kameswara Rao (2002) and admaja (1989). Internodal length per plant (0.454**; 0.645**) it showed positive significant association both at phenotypic and genotypic level with days to 50% flowering. These results are in conformity with the findings of ulli Bai et al. (2005b) and Aruna et al. (1988). In environment II, this trait exhibited positive significant association with basal stem diameter (0.420**; 0.696**) and bark thickness (0.335*, 0.662**) both at phenotypic and genotypic levels and plant height (0.316**), number of nodes per plant (0.401**), internodal length per plant (0.339*) at genotypic level. Similar results are reported by the ulli Bai et al. (2005b) and Aruna et al. (1988). It showed positive non significant association with green plant weight (0.157; 0.213), fibre length per plant (0.118; 0.221) and fibre yield per plant (0.179; 0.221) at both phenotypic and genotypic levels and plant height (0.245), number of nodes per plant (0.212), internodal length per plant (0.200) at phenotypic level. Days to 50% flowering had negative significant association with fibre wood ratio (-0.422**; **) at both phenotypic and genotypic levels. Similar results are observed for Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai (2005b), Kameswara Rao (2002), Rama Kumar (2000) and Mohan Rao (1994).

119 In environment III, this trait expressed positive significant association with fibre wood ratio (0.519**; 0.563**) at both phenotypic and genotypic levels and with bark thickness (0.338*), fibre yield per plant (0.544**) at genotypic level. Similar results were observed by Anuradha and Venkateswara Rao (1993) and Aruna et al. (1988). It showed positive non-significant association with basal stem diameter (0.009; 0.020), internodal length per plant (0.027; 0.022) at both phenotypic and genotypic levels while with bark thickness (0.172), fibre yield per plant (0.285) at phenotypic level. These results are in agreement with ulli Bai et al. (2005b), Kameswara Rao (2002), Anuradha and Venkateswara Rao (1993) and Aruna et al. (1988). While, it had negative non-significant association with plant height (-0.095; ), green plant weight (-0.120; ) and fibre length per plant (-0.059; ) at both phenotypic and genotypic levels. These results are in accordance with Hari Ram Kumar (2012), ulli Bai et al. (2005b), Anuradha and Suriyakumari (2002), Kameswara Rao (2002) and admaja (1989). It shows negative significant association with number of nodes per plant (-0.329*; **). Similar results are found with the findings of Rani et al. (2006), Anuradha and Suriyakumari (2002) and Rama Kumar (2000). In pooled environments, days to 50% flowering exhibited positive significant association with bark thickness (0.721**), internodal length per plant (0.541**) and fibre wood ratio (0.318**) at genotypic level, while, with bark thickness (0.121), internodal length per plant (0.231) and fibre wood ratio (0.075) and fibre length per plant (0.158**) at phenotypic level. These results are in accordance with ulli Bai et al. (2005b) and Aruna et al. (1988). It showed negative non-significant association with plant height (-0.011, ), basal stem diameter (-0.051, ) at both phenotypic and genotypic levels while number of nodes per plant (-0.150), green plant weight ( ), and fibre yield per plant (-0.174) at phenotypic level. These results are similar to Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Anuradha and Suriyakumari (2002), Kameswara Rao (1996), Adilakshmi (1992) and admaja (1989). It showed negative significant association with number of nodes per plant (-1.129**), green plant weight (-0.486**), fibre length per plant ( **) and fibre yield per plant (-0.365*) only at genotypic level. These results are in accordance with Anuradha and Suriyakumari (2002). This trait recorded negative significant association with fibre yield per plant in environment Ι and pooled environments and with basal stem diameter, number of nodes per plant, green plant weight, fibre length per plant. This indicates days to 50%

120 flowering has less importance in influencing fibre yield per plant or any other traits that contribute to fibre yield. These results are in conformity with reports of Appala Swamy (1994) and admaja (1989) lant height (cm) In environment I, this trait showed positive significant association with basal stem diameter (0.428**; 0.941**), number of nodes per plant (0.595**; 0.966**), green plant weight (0.438**; 0.635**), fibre length per plant (0.518**; 0.876**) and fibre yield per plant (0.423**; 0.401**) at both phenotypic and genotypic levels. But, bark thickness (0.492**) at genotypic level. It showed positive non-significant association with bark thickness (0.285), internodal length per plant (0.072) and fibre wood ratio (0.109) at phenotypic level. While, it had significant negative association with fibre wood ratio (-0.391**) at genotypic level, negative non-significant association with internodal length per plant (-0.023) at genotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Anuradha and Venkateswara Rao (1993) and Sinha et al. (1986). In environment II, this trait expressed positive significant association with basal stem diameter (0.503**;0.327**), number of nodes per plant (0.747**; 0.981**), green plant weight (0.508**; 0.717**), fibre length per plant (0.621**; 0.764**) and fibre yield per plant (0.490**; 0.633**) at both phenotypic and genotypic levels and with bark thickness (0.217; 0.032) and internodal length per plant (0.099; 0.286) it expressed positive non-significant association. These results are in accordance with Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002) and Sinha et al. (1986). While it had negative non-significant association with fibre wood ratio (-0.149; ) at both phenotypic and genotypic levels. Similar result was reported by Rama Kumar (2000). In environment III, this character exhibited positive significant association with number of nodes per plant (0.515**; 0.709**) at both phenotypic and genotypic levels. While, it had positive significant association with basal stem diameter (0.487**), green plant weight (0.423*) at phenotypic level and fibre length per plant (0.981**) at genotypic level. It shows positive non-significant association with bark thickness (0.175; 0.076), fibre yield per plant (0.276; 0.233) at both phenotypic and genotypic

121 levels and intermodal length per plant (0.151), green plant weight (0.237) at genotypic level and fibre length per plant (0.109) at phenotypic level. These results are in conformity with findings of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002) and Sinha et al. (1986). However, it had significant negative association with fibre wood ratio (-0.374**) only at genotypic level and negative non-significant association with basal stem diameter (-0.160) at genotypic level, internodal length (-0.028) and fibre wood ratio (-0.229) at phenotypic level. Similar results are reported by ulli Bai et al. (2005b) and Rama Kumar (2000). In pooled environments, plant height showed positive significant association with basal stem diameter (0.463**; 1.007**), number of nodes per plant (0.634**; 0.331*) and fibre length per plant (0.557**; 0.821**) at both phenotypic and genotypic levels, with internodal length per plant (0.398**) at genotypic level and green plant weight (0.447**), fibre yield per plant (0.394*) at phenotypic level. It shows positive non-significant association with bark thickness (0.240), internodal length per plant (0.047). These results are in agreement with works of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002) and Sinha et al. (1986). The trait plant height shows significant negative association with bark thickness (-0.752**) at genotypic level only. It shows negative non-significant association with fibre wood ratio (-0.091; ) at both phenotypic and genotypic levels, with green plant weight (-0.212) at genotypic level only. These results are in conformity with works of Rama Kumar (2000) and Aruna et al. (1988). This trait had significant positive association with fibre yield per plant in environment Ι and ΙΙ and with basal stem diameter, number of nodes per plant, green plant weight and fibre length per plant. These results indicated that increase in plant height would simultaneously increase the basal stem diameter, number of nodes per plant, green plant weight and fibre length per plant which would bring about an increase in fibre yield per plant. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Rama Kumar (2000) and Sinha et al. (1986).

122 4.3.3 Basal stem diameter In environment I, this trait showed positive significant association with bark thickness (0.372**; 0.939**), number of nodes per plant (0.712**; 1.045**), green plant weight (0.709**; 1.024**), fibre length per plant (0.610**; 0.985**) and fibre yield per plant (0.452**; 1.202**) at both phenotypic and genotypic levels. It shows positive non-significant association with fibre wood ratio (0.096) at genotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Rama Kumar (2000) and Sinha et al. (1986). While, it had significant negative association with internodal length per plant (-0.445**; **) at both phenotypic and genotypic levels. It shows negative non-significant association with fibre wood ratio (-0.121) at phenotypic level. These results are in conformity with reports of ulli Bai et al. (2005b) and Kameswara Rao (2002). In environment ΙI, this trait showed positive significant association with bark thickness (0.713**; 1.016**), number of nodes per plant (0.638**; 0.401**), green plant weight (0.572**; 0.775**) and fibre yield per plant (0.400**; 0.696**) at both phenotypic and genotypic levels. But with fibre wood ratio (0.488**) at genotypic level only. It shows positive non-significant association with internodal length per plant (0.184) at genotypic level and fibre length per plant (0.276) at phenotypic level. These results are in harmony with reports of Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Rama Kumar (2000) and Sinha et al. (1986). While, it had significant negative association with fibre wood ratio (-0.362*) at phenotypic level. Similar results were observed by ulli Bai et al. (2005b) and admaja (1989). It shows negative non-significant association with internodal length per plant (-0.101) at phenotypic level and fibre length per plant (-0.145) at genotypic level. These results are in conformity with reports of Anuradha and Suriyakumari (2002). In environment IΙΙ, this trait showed positive significant association with bark thickness (0.581**; 0.888**), number of nodes per plant (0.446**; 0.348*), green plant weight (0.739**; 1.221**), fibre length per plant (0.519**; 1.169**) and fibre yield per plant (0.356*; 0.329*) at both phenotypic and genotypic levels. But, with internodal length per plant (0.077) at genotypic level it shows positive non-significant association. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Rama Kumar (2000) and Sinha et al. (1986). While, it had significant negative association with fibre wood ratio (-0.646**) at genotypic level

123 and negative non-significant association with internodal length per plant (-0.051) and fibre wood ratio (-0.136) at phenotypic level. Similar results are reported by ulli Bai et al. (2005b) and Anuradha and Suriyakumari (2002). In pooled environments, this trait showed positive significant association with bark thickness (0.524**; 0.378**), number of nodes per plant (0.648**; 0.613**), green plant weight (0.667**; 0.334**), fibre length per plant (0.470**; 0.803**) at both phenotypic and genotypic levels and with fibre yield per plant (0.413**) at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Rama Kumar (2000) and Sinha et al. (1986). While, it had significant negative association with fibre wood ratio (-0.355*) and fibre yield per plant (-0.333*) at genotypic level. Basal stem diameter shows negative non-significant association with internodal length per plant (-0.210; ) at both phenotypic and genotypic levels and with fibre wood ratio (-0.162) at phenotypic level. These results are in harmony with reports of ulli Bai et al. (2005b) and Anuradha and Suriyakumari (2002). This trait had significant positive association with fibre yield per plant in all the three and pooled environments and with bark thickness, number of nodes per plant, green plant weight and fibre length per plant. These results indicated that increase in basal stem diameter would simultaneously increase the bark thickness, number of nodes per plant, green plant weight and fibre length per plant which would bring about an increase in fibre yield per plant. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), Kameswara Rao (2002), Rama Kumar (2000) and Sinha et al. (1986) Bark thickness In environment I, this trait showed positive significant association with green plant weight (0.408**; 0.626**) at both phenotypic and genotypic levels and number of nodes per plant (0.437**), fibre length per plant (0.935**) and fibre yield per plant (0.410**) at genotypic level. It shows positive non-significant association with number of nodes per plant (0.208), fibre length per plant (0.235) and fibre yield per plant (0.182) at phenotypic level. While, it had significant negative association with fibre wood ratio (-0.921**) at genotypic level. Bark thickness shows negative nonsignificant association with internodal length per plant (-0.096; ) at both

124 phenotypic and genotypic levels and with fibre wood ratio (-0.056) at phenotypic level. These results are in accordance with reports of Rani et al. (2006) and ulli Bai et al. (2005b). In environment IΙ, this trait showed positive significant association with number of nodes per plant (0.310*; 0.379**), green plant weight (0.365*; 0.594**) and fibre yield per plant (0.301*; 0.642**) at both phenotypic and genotypic levels. But, with internodal length per plant (0.034; 0.287) at both phenotypic and genotypic levels and fibre length per plant (0.149) at phenotypic level it shows positive non-significant association. While, it had significant negative association with fibre length per plant ( **), fibre wood ratio (-0.393**) at genotypic level. Bark thickness shows negative non-significant association with fibre wood ratio (-0.215) at phenotypic level. These results are in conformity with reports of Rani et al. (2006) and ulli Bai et al. (2005b). In environment IΙΙ, this trait showed positive significant association with green plant weight (0.535**; 0.682**), fibre yield per plant (0.296*; 0.347*) at both phenotypic and genotypic levels and fibre length per plant (0.599**) at genotypic level. While, it had significant negative association with internodal length per plant ( **) at genotypic level. It shows positive non-significant association with number of nodes per plant (0.139; 0.189) at both phenotypic and genotypic levels, fibre length per plant (0.164) at phenotypic level and fibre wood ratio (0.042) at genotypic level. Bark thickness shows negative non-significant association with internodal length per plant (-0.128) and fibre wood ratio (-0.021) at phenotypic level. These results are in conformity with reports of Rani et al. (2006) and ulli Bai et al. (2005b). In pooled environments, this trait showed positive significant association with green plant weight (0.404**) at phenotypic level, fibre wood ratio (0.987**) and fibre yield per plant (0.312**) at genotypic level. It shows positive non-significant association with number of nodes per plant (0.232), fibre length per plant (0.190) and fibre yield per plant (0.213) at phenotypic level and with internodal length per plant (0.146) at genotypic level, While, it had significant negative association with number of nodes per plant (-0.894**), green plant weight (-0.631**) and fibre length per plant ( **) at genotypic level. Bark thickness shows negative non-significant association with internodal length per plant (-0.060) and fibre wood ratio (-0.076) at phenotypic level. These results are in conformity with reports of Rani et al. (2006) and ulli Bai et al. (2005b).

125 This trait had significant positive association with fibre yield per plant in all three and pooled environments and with number of nodes per plant, green plant weight, fibre length per plant. These results indicated that increase in bark thickness would simultaneously increase the number of nodes per plant, green plant weight and fibre length per plant which would bring about an increase in fibre yield per plant. These results are in conformity with reports of Rani et al. (2006) and ulli Bai et al. (2005b) Number of nodes per plant In environment I, this trait showed positive significant association with green plant weight (0.578**; 0.763**), fibre length per plant (0.643**; 0.730**) and fibre yield per plant (0.478**; 0.794**) at both phenotypic and genotypic levels. But, with fibre wood ratio (0.300*) at genotypic level only. While, it had significant negative association with internodal length per plant (-0.334*; *) at both phenotypic and genotypic levels. Number of nodes per plant shows negative non-significant association with fibre wood ratio (-0.063) at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), admaja (1989) and Sinha et al. (1986). In environment ΙI, this trait showed positive significant association with green plant weight (0.504**; 0.812**), fibre length per plant (0.627**; 0.730**) and fibre yield per plant (0.489**; 0.970**) at both phenotypic and genotypic levels. But, with internodal length per plant (0.093) at genotypic level it shows positive non-significant association. Number of nodes per plant shows negative non-significant association with fibre wood ratio (-0.214; ) at both phenotypic and genotypic levels. But, with internodal length per plant (-0.186) at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Subramanyam et al. (1995), Madhavi Rani (1990), admaja (1989) and Aruna et al. (1988). In environment ΙIΙ, this trait showed positive significant association with green plant weight (0.361**; 1.305**) and fibre length per plant (0.509**; 0.474**) at both phenotypic and genotypic levels, But, with fibre wood ratio (0.306**) at phenotypic level only. It shows positive non-significant association with fibre yield per plant (0.246; 0.169) at both phenotypic and genotypic levels. Number of nodes per plant shows negative significant association with internodal length per plant (-0.518**) and

126 fibre wood ratio (-1.115**) at genotypic level. Where as, with internodal length per plant (-0.209) this trait showed negative non-significant association at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Anuradha and Suriyakumari (2002), Banerjee et al. (1988) and Sinha et al. (1986). In pooled environments, this trait showed positive significant association with green plant weight (0.525**; 0.923**), fibre length per plant (0.612**; 0.716**) and fibre yield per plant (0.437**; 1.071**) at both phenotypic and genotypic levels. It also recorded positive non-significant association with fibre wood ratio (0.213) and negative significant association with internodal length per plant (-0.753**) at genotypic level. But, with internodal length per plant (-0.235) and fibre wood ratio (-0.168) it shows negative non-significant correlation at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Anuradha and Suriyakumari (2002), Banerjee et al. (1988) and Sinha et al. (1986). This trait exhibited significant positive association with fibre yield per plant in environment Ι, ΙΙ and pooled and with green plant weight, fibre length per plant. These results indicated that increase in number of nodes would simultaneously increase the green plant weight and fibre length per plant which would bring about an increase in fibre yield per plant. These results are in conformity with reports of Hari Ram Kumar (2012), Kameswara Rao (2002), Rama Kumar (2000), Anuradha and Suriyakumari (2002), Banerjee et al. (1988) and Sinha et al. (1986) Internodal length per plant In environment Ι, this trait showed positive significant association with fibre wood ratio (0.426**) at genotypic level and positive non significant association (0.120) at phenotypic level. These results were in accordance with the reports of Hari Ram Kumar (2012), Appala Swamy (1994) and Adilakshmi (1992). Internodal length shows negative significant association with fibre length per plant (-0.347*; **) and fibre yield per plant (-0.385**; **) at both phenotypic and genotypic levels. But, with green plant weight (-0.348*) at genotypic level only. These results are in conformity with reports of Rani et al. (2006), ulli Bai et al. (2005b). This trait shows negative non-significant association with green plant weight (-0.282) at phenotypic level only. Similar results are reported by Subramanyam et al. (1995) and Madhavi Rani (1990).

127 In environment ΙΙ, this character recorded positive significant association with fibre length per plant (0.407**) at genotypic level. These results are in conformity with reports of Hari Ram Kumar (2012) and Kameswara Rao (2002). It also showed positive non-significant association with fibre wood ratio (0.049; 0.151) at both phenotypic and genotypic levels and for fibre length per plant (0.141) at phenotypic level. These results are in harmony with the reports of Kameswara Rao (2002) and Rama Kumar (2000). Internodal length shows negative non-significant association with green plant weight ( ; ), fibre yield per plant (-0.019, ) at both phenotypic and genotypic levels. These results are in conformity with reports of Appala Swamy (1994) and Efrayimu (1993). In environment ΙΙΙ, this trait showed positive significant association with fibre length per plant (0.966**) at genotypic level only. These results are in conformity with reports of Hari Ram Kumar (2012) and Kameswara Rao (2002). It shows positive nonsignificant association with fibre wood ratio (0.023; 0.162) at both phenotypic and genotypic levels. These results are in similarity with reports of Kameswara Rao (2002) and Rama Kumar (2000). Internodal length shows negative significant association with green plant weight (-0.687**) at genotypic level. This trait shows negative nonsignificant association with fibre yield per plant (-0.126, ) at both phenotypic and genotypic levels and with green plant weight (-0.205) and fibre length per plant ( ) at phenotypic level only. These results are in conformity with reports of Appala Swamy (1994), Efrayimu (1993) and Adilakshmi (1992). In pooled environments, this trait showed positive significant association with fibre length per plant (0.349*) and fibre wood ratio (0.320*) at genotypic level and positive non-significant association with fibre wood ratio (0.047) at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012) and Kameswara Rao (2002). It also recorded negative significant association with green plant weight (-0.628**) at genotypic level. This trait also recorded negative nonsignificant association with fibre yield per plant (-0.207, ) at both phenotypic and genotypic levels and with green plant weight (-0.189) and fibre length per plant ( ) at phenotypic level only. These results are in conformity with reports of Appala Swamy (1994) and Efrayimu (1993).

128 This trait recorded negative non-significant association with fibre yield per plant in environment Ι, ΙΙ and pooled with green plant weight, fibre length per plant and fibre wood ratio. This indicated that internodal length has less importance in influencing fibre yield per plant or any other traits that contribute to fibre yield. These results are in conformity with reports of Appala Swamy (1994) and Efrayimu (1993) reen plant weight In environment Ι, this trait showed positive significant association with fibre length per plant (0.141**; 0.407**) and fibre yield per plant (0.523**; 0.669**) at both phenotypic and genotypic levels. It showed positive non-significant association with fibre wood ratio (0.039) at phenotypic level. It also recorded negative non-significant association with fibre wood ratio (-0.189) at genotypic level. These results are in accordance with reports of Hari Ram Kumar (2012), Kameswara Rao (2002) and Rama Kumar (2000). In environment ΙΙ, this trait showed positive significant association with fibre yield per plant (0.498**; 0.826**) at both phenotypic and genotypic levels and fibre length per plant (0.442**) at genotypic level. It shows positive non-significant association with fibre length per plant (0.211) at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Kameswara Rao (2002) and Rama Kumar (2000). reen plant weight shows negative significant association with fibre wood ratio (-0.316*) at genotypic level and negative non-significant association with fibre wood ratio (-0.233) at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012) and Appala Swamy (1994). In environment ΙΙΙ, this trait showed positive significant association with fibre length per plant (0.379**; 0.896**) at both phenotypic and genotypic levels, with fibre yield per plant (0.380*) at phenotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), Kameswara Rao (2002) and Rama Kumar (2000). It showed positive non-signficant association with fibre yield per plant (0.281) at genotypic level. reen plant weight shows negative significant association with fibre wood ratio (-0.322*; **) at both phenotypic and genotypic levels. These result was in conformity with reports of admaja (1989).

129 In pooled environments, this trait showed positive significant association with fibre length per plant (0.411**) and fibre yield per plant (0.500**) at phenotypic level. These results are in conformity with reports of admaja (1989), Aruna et al. (1988) and Banerjee et al. (1988). It showed positive non-significant association with fibre length per plant (0.056) and fibre yield per plant (0.099) at genotypic level. reen plant weight shows negative significant association with fibre wood ratio (-0.512**) at genotypic level and negative non-significant association (-0.122) at phenotypic level. These result was in conformity with reports of Appala Swamy (1994). This trait had significant positive association with fibre yield per plant in three and pooled environments and with fibre length per plant. These results indicated that increase in green plant weight would simultaneously increase the fibre length per plant which would bring about an increase in fibre yield per plant. These results are in conformity with reports of admaja (1989), Aruna et al. (1988) and Banerjee et al. (1988) Fibre length per plant In environment Ι, this trait showed positive significant association with fibre yield per plant (0.556**; 0.844**) at both phenotypic and genotypic level. These results are in conformity with reports of Hari Ram Kumar (2012), ulli Bai et al. (2005b) and Kameswara Rao (2002). It recorded negative significant association with fibre wood ratio (-0.364*) at genotypic level and negative non-significant association with fibre wood ratio (-0.186) at phenotypic level. These results are in conformity with reports of Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000) and Appala Swamy (1994). In environment ΙΙ, this trait showed positive significant association with fibre yield per plant (0.418**; 0.613**) at both phenotypic and genotypic levels. It shows positive non-significant association with fibre wood ratio (0.226) at genotypic level only. These results are in conformity with reports of Hari Ram Kumar (2012), ulli Bai et al. (2005b) and Kameswara Rao (2002). It shows negative non-significant association with fibre wood ratio (-0.035) at phenotypic level. This result was in conformity with reports of Appala Swamy (1994).

130 In environment ΙΙΙ, this trait showed positive non-significant association with fibre yield per plant (0.267; 0.069) at both phenotypic and genotypic levels. This result was in conformity with report of Hari Ram Kumar (2012). It shows negative significant association with fibre wood ratio (-0.776**) at genotypic level and negative nonsignificant association with fibre wood ratio (-0.233) at phenotypic level. These results are in accordance with reports of Rani et al. (2006), ulli Bai et al. (2005), Rama Kumar (2000) and Appala Swamy (1994). In pooled environments, this trait showed positive significant association with fibre yield per plant (0.450**; 0.479**) at both phenotypic and genotypic levels. These results are in conformity with reports of Hari Ram Kumar (2012), ulli Bai et al. (2005b) and Kameswara Rao (2002). It recorded negative non-significant association with fibre wood ratio (-0.134; ) at both phenotypic and genotypic levels. This result was in conformity with reports of Appala Swamy (1994). This trait had significant positive association with fibre yield per plant in environment Ι, ΙΙ and pooled environments. These results indicated that increase in fibre length per plant would bring an increase in fibre yield per plant. These results are in conformity with reports of Hari Ram Kumar (2012), ulli Bai et al. (2005b) and Kameswara Rao (2002) Fibre wood ratio In environment Ι, this trait showed positive non-significant association with fibre yield per plant (0.219) at phenotypic level. This result was in conformity with reports of Rama Kumar (2000) and it recorded negative non-significant association with fibre yield per plant (-0.052) at genotypic level. This result was in conformity with reports of admaja (1989). In environment ΙΙ, this trait showed negative significant association with fibre yield per plant (-0.355*) at genotypic level and shows negative non-significant association with fibre yield per plant (-0.081) at phenotypic level. These results are in conformity with reports of Appala Swamy (1994), Mohan Rao (1994) and Efrayimu (1993).

131 In environment ΙΙΙ, this trait showed positive significant association with fibre yield per plant (0.314*; 0.591**) at both phenotypic and genotypic levels. These results are in conformity with reports of Rama Kumar (2000), admaja (1989), Aruna et al. (1988) and Adilakshmi (1992). In pooled environments, this trait showed positive significant association with fibre yield per plant (0.361*) at genotypic level. It shows positive non-significant association with fibre yield per plant (0.135) at phenotypic level. These results are in conformity with reports of Rama Kumar (2000). This trait had significant positive association with fibre yield per plant in environment ΙΙΙ. These results indicated that increase in fibre wood ratio would bring an increase in fibre yield per plant. This result was in conformity with reports of Rama Kumar (2000). The study of environment wise character association revealed that the characters viz., basal stem diameter, bark thickness and green plant weight showed significant positive association with fibre yield per plant in all three environments. Therefore, simultaneous improvement of fibre yield is possible through selection of these characters. 4.4 ATH COEFFICIENT ANALYSIS The information on the extent of association between the yield and other factors is important to bring the simultaneous improvement in correlated traits. Although, knowledge of phenotypic correlation of agronomic characters with fibre yield in roselle is indispensable in the characterization of component influences on manifesting the characters, these associations yet do not provide explicit information on the relative importance of direct and indirect effects of each component character on roselle fibre yield. With an increase in number of variables, it becomes imperative to measure the contribution of each variable towards the observed correlation. Therefore, partitioning the observed correlation coefficients into unidirectional pathways and alternate pathways facilitate the characterization of more complex traits devised by Wright (1921) and utilized by Dewey and Lu (1959) in selection programmes. In light of the above inferences, path coefficient analysis splits the correlation coefficients and

132 provides precise information on the direct and indirect effects in order to perceive the most influencing characters to be utilized as selection criteria in roselle breeding programme. Sometimes correlation coefficients may be negative, but the direct effect positive and high. Under these conditions, a restricted simultaneous selection model has to be followed i.e., restrictions are to be imposed to nullify the undesirable indirect effects, in order to make use of the direct effect (Singh and Chaudhary, 1977). As per the guidelines for the interpretation of path analysis results, the following broad points are kept in view (Singh and Chaudhary, 1977). If the correlation coefficient between a causal factor and the effect is almost equal to its direct effect, then correlation explains the true relationship and a direct selection through this trait will be effective. If the correlation coefficient is positive, but the direct effect is negative or negligible, the indirect effects seem to be the cause of positive correlation. In such situations, the indirect causal factors are to be considered simultaneously for selection. Correlation coefficient may be negative but the direct effect is positive and high. Under these circumstances, a restricted simultaneous selection model is to be followed i.e., restrictions are to be imposed to nullify the undesirable indirect effects in order to make use of the direct effect. If both correlation coefficient is negative and direct effects are also negative, then we have to drop the selection based on that character. The residual effect determines how best the causal factors account for the variability of the dependent factor. If the residual effect is high, some other factors which had not been considered in the study, need to be included in the analysis to account fully for the variation in yield. Hence, in the present study, direct and indirect effects of different yield component traits on roselle fibre yield per plant were estimated through path analysis at phenotypic and genotypic levels and are presented in Tables 4.8 to The phenotypic and genotypic path diagrams are given in Fig. 4.4 to 4.7, respectively.

133 4.4.1 Days to 50% flowering In environment I, it had negative direct effect ( ; ) and significant negative correlation with fibre yield per plant ( **; **) at both phenotypic and genotypic levels. The indirect effects via plant height (0.0049; ), basal stem diameter (0.0112; ), bark thickness (0.0009; ), number of nodes per plant (0.0096; ), green plant weight (0.0091; ), fibre length per plant (0.0132; ) and fibre wood ratio (0.0046; ) were low and positive. Where as, internodal length per plant ( ; ) was low and negative. Negative direct effects and significant negative association indicated that selection for this trait would not be realized in increased fibre yield per plant. These results are in accordance with reports of Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Hemalatha (1990), admaja (1989) and Aruna et al. (1988). In environment IΙ, it exhibited positive direct effect (0.0833; ) and positive non-significant correlation with fibre yield per plant (0.1799; ) at both phenotypic and genotypic levels. The indirect effects via plant height (0.0204; ), basal stem diameter (0.0350; ), bark thickness (0.0279; ), number of nodes per plant (0.0177; ), internodal length per plant (0.0167; ), green plant weight (0.0131; ) and fibre length per plant (0.0099; ) were low and positive. While, fibre wood ratio ( ; ) was low and negative. These results suggest that indirect casual factors are to be considered for improvement of yield. These results are in agreement with the findings of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Hemalatha (1990), admaja (1989) and Aruna et al. (1988). In environment III, it expressed positive direct effects (0.1881, ) both at phenotypic and genotypic levels and positive significant correlation (0.2853, **) with fibre yield per plant only at genotypic level. The positive indirect effects were mainly through basal stem diameter (0.0116), bark thickness (0.1881), internodal length (0.0125) and fibre wood ratio (0.3130) at genotypic levels. Thus, this trait showed significant positive correlation at genotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors are to be considered for simultaneous selection. These results are in accordance with Rani et al. (2006), ulli Bai et al. (2005b), Anuradha and Venkateswara Rao (1993) and Adilakshmi (1992).

134 In pooled environments, it had negative direct effects ( ; ) and negative correlation ( , *) with fibre yield per plant but significant only at genotypic level. Negative direct effects and significant negative association indicated that selection for this trait would not be realized in increased fibre yield per plant. These results are in conformity with reports of Rani et al. (2006) and admaja (1989) lant height (cm) In environment I, this trait expressed positive direct effect (0.1708) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.4233**, **) with fibre yield per plant both at phenotypic and genotypic levels. Thus, it exhibited positive significant association at both the levels and positive direct effect at phenotypic level, while negative direct effect at genotypic level. Significant positive association and low direct effect indicates that selection for this trait will be rewarding for improvement of fibre yield. These results are in agreement with works of Hari Ram Kumar (2012), ulli Bai et al. (2005b), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Krishnaveni and Krishna Murthy (2000a), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989), Aruna et al. (1988) and Banerjee et al. (1988). In environment II, this character recorded positive direct effect (0.1223) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.4902**, **) with fibre yield per plant both at phenotypic and genotypic levels. Thus, it exhibited positive significant association at both the levels and positive direct effect at phenotypic level, while negative direct effect at genotypic level. Significant positive association and low direct effect indicates that selection for this trait will be rewarding for improvement of fibre yield. These results are in agreement with works of Hari Ram Kumar (2012), Rani et al. (2005), ulli Bai et al. (2005b), Anuradha and Suriyakumari (2002), Kameswara Rao (2002), Krishna veni and Krishna murthy (2000a), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989), Aruna et al. (1988) and Banerjee et al. (1988). In environment III, it had positive direct effect (0.0862; ) and positive non-significant correlation with fibre yield per plant (0.2760; ) at both phenotypic and genotypic levels. Thus, it expressed positive association and positive direct effects at both the levels. It reveals true relationship between them and direct

135 selection for this trait will be rewarding for improvement of fibre yield. These results are in accordance with Hari Ram Kumar (2012), ulli Bai et al. (2005b), Rama Kumar (2000), Aruna et al. (1988) and Hemalatha (1990). In pooled environments, this trait exhibited positive direct effects (0.1094, ) and positive significant correlation (0.3943**) at phenotypic level, negative non-significant correlation ( ) at genotypic level with fibre yield per plant. The positive indirect effects were mainly through basal stem diameter (0.0507), bark thickness (0.0263), number of nodes per plant (0.0694), internodal length per plant (0.0052), green plant weight (0.0489) and fibre length per plant (0.3130) at phenotypic levels. Thus, this trait showed significant positive correlation at phenotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in accordance with Hari Ram Kumar (2012), ulli Bai et al. (2005b), Rama Kumar (2000), Aruna et al. (1988) and Hemalatha (1990) Basal stem diameter In environment I, this trait expressed negative direct effect ( ) at phenotypic level, positive direct effect (0.3054) at genotypic level and significant positive association (0.4523**, **) with fibre yield per plant both at phenotypic and genotypic levels. Thus, this trait showed significant positive correlation at genotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results were in accordance with Anuradha and Venkateswara Rao (1993), Sinha et al. (1986) and Sasmal and Chakraborty (1978). In environment IΙ, it had negative direct effects ( ; ) and significant positive correlation with fibre yield per plant (0.4003**; **) at both phenotypic and genotypic levels. Thus, it showed positive correlation and negative direct effect both at phenotypic and genotypic levels. This indicates that indirect effects seem to be the cause of positive correlation. In such a situation, the indirect causal factors are to be considered for simultaneous selection.

136 In environment IΙΙ, it showed negative direct effects ( ; ) and significant positive correlation with fibre yield per plant (0.3569*; *) at both phenotypic and genotypic levels. Thus, it reported significant positive correlation and negative direct effect both at phenotypic and genotypic levels. This indicates that indirect effects seem to be the cause of positive correlation. In such a situation, the indirect causal factors are to be considered for simultaneous selection. In pooled environments, it had positive direct effects (0.0168; ) and significant positive correlation (0.4136**) at phenotypic level and significant negative association ( *) at genotypic level with fibre yield per plant. The positive indirect effects were mainly through bark thickness (0.0088), number of nodes per plant (0.0109), green plant weight (0.0112) and fibre length per plant (0.0079) at phenotypic levels. Thus, this trait showed significant positive correlation at phenotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in accordance with ulli Bai et al. (2005b), Kameswara Rao (2002), Anuradha and Suriyakumari (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), Hemalatha (1990), admaja (1989) and Banerjee et al. (1988) Bark thickness In environment I, this character expressed negative direct effect ( ) at phenotypic level, positive direct effect (1.2748) at genotypic level and positive correlation (0.1828, **) with fibre yield per plant but significant only at genotypic level. The positive indirect effects were mainly through number of nodes per plant (0.5574), green plant weight (0.7980) and fibre length per plant (1.1928) at genotypic levels. Thus, this trait showed significant positive correlation at genotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in accordance with ulli Bai et al. (2005b). In environment II, this trait exhibited positive direct effects (0.1434, ) and significant positive association (0.3012*, **) with fibre yield per plant both at phenotypic and genotypic levels. These results revealed true relationship between them and direct selection for this trait will be rewarding for improvement of fibre yield. These results are in agreement with findings of Rani et al. (2006) and ulli Bai et al. (2005b).

137 In environment IΙΙ, this trait expressed positive direct effect (0.0500) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.2961*, *) with fibre yield per plant both at phenotypic and genotypic levels. Thus, it showed low and negative direct effects and significant positive correlation both at phenotypic and genotypic levels. This indicates that indirect effects seem to be cause of positive correlation. In such a situation, indirect causal factors were to be considered for simultaneous selection. These results are in accordance with Rani et al. (2006) and ulli Bai et al. (2005b). In pooled environments, this trait exhibited positive direct effects (0.0193, ) and positive correlation (0.2134, *) with fibre yield per plant but significant only at genotypic level. The positive indirect effects were mainly through internodal length per plant (0.1849) and fibre wood ratio (1.2460) at genotypic levels. Thus, this trait showed significant positive correlation at genotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in accordance with Rani et al. (2006) and ulli Bai et al. (2005b) Number of nodes per plant In environment I, it showed positive direct effect (0.0157; ) and significant positive correlation with fibre yield per plant (0.4788**; **) at both phenotypic and genotypic levels. These results revealed true relationship between them and direct selection for this trait will be rewarding for improvement of seed yield. These results are in agreement with findings of Kameswara Rao (2002), Hemalatha (1990) and Aruna et al. (1988). In environment II, this trait exhibited positive direct effects (0.0971, ) and significant positive association (0.4896**, **) with fibre yield per plant both at phenotypic and genotypic levels. These results revealed true relationship between them and direct selection for this trait will be rewarding for improvement of seed yield. These results are in agreement with findings of Kameswara Rao (2002), Hemalatha (1990) and Aruna et al. (1988). In environment IΙΙ, this trait expressed positive direct effect (0.2506) at phenotypic level, negative direct effect ( ) at genotypic level and positive association (0.2463; ) with fibre yield per plant at both phenotypic and genotypic

138 levels. Thus, the non-significant positive association with low and negative direct effects indicates that selection for this trait may not be effective for improvement of yield. These results are in agreement with Kameswara Rao (2002), Anuradha and Suriyakumari (2002), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Aruna et al. (1988) and Sinha et al. (1986). In pooled environments, this trait expressed positive direct effect (0.0515) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.4371**; **) with fibre yield per plant at both phenotypic and genotypic levels. The positive indirect effects were mainly through internodal length per plant (0.1849) at genotypic level and green plant weight (0.0270), fibre length per plant (0.0315) at phenotypic level. Thus, the significant positive association with negative direct effects indicates that selection for this trait may not be effective for improvement of yield. In this situation, indirect effects seem to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in agreement with Kameswara Rao (2002), Anuradha and Suriyakumari (2002), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Aruna et al. (1988) and Sinha et al. (1986) Internodal length per plant In environment I, it had negative direct effect ( ; ) and significant negative correlation with fibre yield per plant ( **; **) at both phenotypic and genotypic levels. Negative direct effects and significant negative association indicated that selection for this trait would not be realized in increased seed yield per plant. These results are in conformity with reports of Hari Ram Kumar (2012) and Rama Kumar (2000). In environment IΙ, this trait expressed negative direct effect ( ) at phenotypic level, positive direct effect (0.0904) at genotypic level and negative association ( ; ) with fibre yield per plant at both phenotypic and genotypic levels. Low and negative direct effects and non-significant negative correlation indicates that selection for this trait would not be realized in increased seed yield per plant. Similar results are in conformity with Rani et al. (2006), Kameswara Rao (2002), Kameswara Rao (1996) and Aruna et al. (1988).

139 In environment IΙΙ, this trait expressed positive direct effect (0.0148) at phenotypic level, negative direct effect ( ) at genotypic level and negative correlation ( ; ) with fibre yield per plant at both phenotypic and genotypic levels. Low and negative direct effects and non-significant negative correlation indicates that selection for this trait would not be realized in increased seed yield per plant. Similar results are in conformity with ulli Bai et al. (2005b) and Sinha et al. (1986). In pooled environments, this trait expressed negative direct effect ( ) at phenotypic level, positive direct effect (5.9083) at genotypic level and negative association ( ; ) with fibre yield per plant at both phenotypic and genotypic levels. Low and negative direct effects and non-significant negative correlation indicates that selection for this trait would not be realized in increased seed yield per plant. Similar results are in conformity with Rani et al. (2006), Kameswara Rao (2002), Kameswara Rao (1996) and Aruna et al. (1988) reen plant weight In environment I, this trait expressed positive direct effect (0.2285) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.5235**; **) with fibre yield per plant at both phenotypic and genotypic levels. The positive indirect effects were mainly through fibre length per plant (0.1279) at phenotypic level, fibre wood ratio (0.0090; ) both at phenotypic and genotypic levels. Thus, the significant positive association with low and negative direct effects indicates that selection for this trait may not be effective for improvement of yield. In this situation, indirect effects seem to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in agreement with Hari Ram Kumar (2012), Anuradha and Suriyakumari (2002), Krishnaveni and Krishna Murthy (2000a), Kameswara Rao (1996), Hemalatha (1990), admaja (1989), Aruna et al. (1988) and Banerjee (1988). In environment IΙ, it showed positive direct effects (0.3434; ) and significant positive correlation with fibre yield per plant (0.4981**; **) at both phenotypic and genotypic levels. These results revealed true relationship between them and direct selection for this trait will be rewarding for improvement of seed yield. These results are in agreement with findings of Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) and Anuradha and Venkateswara Rao (1993).

140 In environment III, it expressed positive direct effects (0.5113; ) both at phenotypic and genotypic levels and positive correlation (0.3807**, ) with fibre yield per plant but significant only at phenotypic level. The positive indirect effects were mainly through fibre length per plant (0.1938; ) both at phenotypic and genotypic levels. Thus, this trait showed significant positive correlation at phenotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in accordance with Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) and Anuradha and Venkateswara Rao (1993). In pooled environments, it expressed positive direct effects (0.3076, ) both at phenotypic and genotypic levels and positive correlation (0.5004**, ) with fibre yield per plant but significant only at phenotypic level. The positive indirect effects were mainly through fibre length per plant (0.1266; ) at phenotypic levels. Thus, this trait showed significant positive correlation at phenotypic level, indicating indirect effects seems to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in accordance with Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) and Anuradha and Venkateswara Rao (1993) Fibre length per plant In environment I, this trait expressed positive direct effect (0.3310) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.5562**; **) with fibre yield per plant at both phenotypic and genotypic levels. The positive indirect effects were mainly through fibre wood ratio (0.4455) at genotypic level. Thus, the significant positive association with low and negative direct effects indicates that selection for this trait may not be effective for improvement of yield. In this situation, indirect effects seem to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in agreement with Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000a), Hemalatha (1990) and admaja (1989).

141 In environment IΙ, this trait expressed positive direct effect (0.2118) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.4183**; **) with fibre yield per plant at both phenotypic and genotypic levels. Thus, the significant positive association with low and negative direct effects indicates that selection for this trait may not be effective for improvement of yield. In this situation, indirect effects seem to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in agreement with Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), Krishna veni and Krishna murthy (2000a), Hemalatha (1990) and admaja (1989). In environment IΙΙ, it had positive direct effects (0.1228; ) and positive correlation with fibre yield per plant (0.2673; ) at both phenotypic and genotypic levels. The indirect effects via fibre wood ratio ( ; ) was low and negative. These results suggest that indirect casual factors are to be considered for improvement of yield. Similar results are in agreement with findings of ulli Bai et al. (2005b), Kameswara Rao (2002) and Kameswara Rao (1996). In pooled environments, this trait expressed positive direct effect (0.2303) at phenotypic level, negative direct effect ( ) at genotypic level and significant positive association (0.4504**; **) with fibre yield per plant at both phenotypic and genotypic levels. The positive indirect effects were mainly through fibre wood ratio (0.7013) at genotypic level. Thus, the significant positive association with low and negative direct effects indicates that selection for this trait may not be effective for improvement of yield. In this situation, indirect effects seem to be the cause of positive association. Hence, indirect causal factors were to be considered for simultaneous selection. These results are in agreement with Hari Ram Kumar (2012), Rani et al. (2006), Rama Kumar (2000), Krishnaveni and Krishna Murthy (2000a), Hemalatha (1990) and admaja (1989) Fibre wood ratio In environment I, this trait expressed positive direct effects (0.2706, ) both at phenotypic and genotypic levels and positive correlation (0.2194) at phenotypic level and negative correlation ( ) at genotypic level with fibre yield per plant. Low direct effects and non-significant negative association indicated that selection for this

142 trait would not be realized in increased fibre yield per plant. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) and admaja (1989). In environment II, this trait showed negative direct effects ( ) and negative correlation ( ) with fibre yield per plant at phenotypic level. At genotypic level, It exhibits positive direct effect (0.0560) and significant negative correlation ( *) with fibre yield per plant. Low and negative direct effects and negative association significant at genotypic level indicated that selection for this trait would not be realized in increased fibre yield per plant. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996), admaja (1989) and Aruna et al. (1988). In environment III, this trait exhibited positive direct effects (0.4803, ) and significant positive correlation (0.3146*, **) with fibre yield per plant both at phenotypic and genotypic levels. These results revealed true relationship between them and direct selection for this trait will be rewarding for improvement of fibre yield. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) and admaja (1989). In pooled environments, this trait showed positive direct effects (0.2379; ) both at phenotypic and genotypic levels and positive correlation (0.1354; *) with significance only at genotypic level. These results revealed true relationship between them and direct selection for this trait will be rewarding for improvement of fibre yield. These results are in conformity with reports of Hari Ram Kumar (2012), Rani et al. (2006), ulli Bai et al. (2005b), Kameswara Rao (2002), Rama Kumar (2000), Kameswara Rao (1996) and admaja (1989). The study of environment wise path coefficient analysis indicated that bark thickness, number of nodes per plant, green plant weight and fibre length per plant had positive direct effects coupled with positive significant correlation with fibre yield per plant in all the three environments. Therefore, simultaneous improvement of fibre yield is possible through selection of these characters.

143 4.5 Stability analysis studies The interaction between genetic and non-genetic effects reduces the correlation between the genotype and phenotype, which in turn reduces the accuracy with which the environmental data can be interpreted. The variability in environment and their interaction highly influence the performance of genotypes in relation to yield. Knowledge on the genotype environment interaction is the basic requirement to a plant breeder for successful crop improvement (Shantha Kumar, 2000). Stability performance is one of the most desirable properties of a genotype to be released as a variety for wide cultivation (or) for use as a parent in crop improvement programmes Eberhart and Russell s (1966) stability model ooled analysis of variance for stability performance The Bartlett s 2 values showed non-significance for all the characters allowing pooling of variances over environments for further analysis (Table 4.12). The pooled analysis of variance of Eberhart and Russell model for stability was presented in Table The pooled analysis of variance for stability revealed mean squares due to genotypes were significant for days to 50% flowering, internodal length per plant and fibre yield per plant indicating sufficient variability among genotypes. The environments showed significant differences for all the characters. The genotype environment interaction component showed significance for the characters viz., days to 50% flowering, fibre wood ratio and fibre yield per plant and non-significance for remaining characters. Significance of environment (linear) component for all the characters confirms the observations of widely differing environments, in the analysis of variance. The genotype environment (linear) interaction component exhibited non-significance for all the characters except for days to 50% flowering, internodal length per plant, fibre wood ratio and fibre yield per plant. ooled deviation component was highly significant for days to 50% flowering, plant height, basal stem diameter, bark thickness, number of nodes per plant, green plant weight, fibre length per plant and fibre wood ratio indicating the importance of non-linear component in the genotype-environment interaction.

144 Environmental index reveals the suitability of an environment (Table 4.12). Based on the positive values of environmental index, environment I (sowing on ) was found to be the most suitable for all the characters except for internodal length per plant and fibre wood ratio. Environment II (sowing on ) was found to be the most suitable for plant height (0.667) while delayed sowing was found to be the most suitable for internodal length per plant (0.298) and fibre wood ratio (0.095). Earlier, Finlay and Wilkinson (1963) considered the linear regression (b i ) as a measure of stability, but later, Eberhart and Russell (1966) emphasized the need of both b i and s 2 d i in judging the stability of a genotype. According to Eberhart and Russell (1966) model, a genotype having unit regression coefficient (b i =1) and non-significant deviation from regression (s 2 d i = 0) with high mean was considered as stable. A genotype with high mean performance with near to unity regression and least deviation from regression could perform well under average environmental conditions. If a genotype exhibited high mean with greater than unity regression was considered to be stable for favourable environmental condition. However, if a genotype possessed high mean with less than unity regression, the genotype should be suitable for poor environmental conditions Stability parameters The data pertaining to stability parameters was presented in Tables Days to 50% flowering The variation exhibited for this trait ranged from days (AHS-172) to days (JRR-9) with a mean value of The regression coefficient values were non-significant. The deviations from regression value were significant for seventeen genotypes. For this trait, the genotypes, AR-12 (119.00), R-93 (118.80), CRIJAFR-8 (119.80), AHS-162 (116.80), AHS-172 (111.70), AMV-4 (115.70), AMV-5 (118.90), HS-4288 (116.70) recorded low mean values. The genotypes, AR-72 (1.007), AS (1.007), JRR-9 (1.007), AR-12 (1.024), ER-63 (1.041) and AS (0.964) showed non-significant regression coefficients nearing unity while the genotypes, AR-12 ( ), ER-63 (0.059), R-28 (0.052), AS (0.177), JRR-9 (0.072) and JRRM-9-1

145 (0.032) showed low, non-significant deviation from the regression values. The genotype, AR-12 had low mean value (119.00), non-significant regression co-efficient nearing unity (1.024) with low, non-significant deviation from regression (-0.073). The genotypes, JRR-9, AR-72, AS and AR-12, could perform well under average environmental conditions as they exhibited low mean performance with near to unity regression and least deviation from regression. The genotypes, ER-63, AS-80-19, CRIJAFR-2 and JRRM-9-1, were considered to be stable for favourable environmental condition as they exhibited low means with greater than unity regression, whereas the genotypes, R-200, AS and AHS-152, showed low means with less than unity regression, could perform well under poor environmental conditions. These results are in accordance with Appala Swamy (1994) in kenaf and upthaji (1993) in roselle lant height (cm) The variation exhibited for this trait ranged from (R-134) to (AHS-152) with a mean value of The regression coefficient values were significant for two genotypes. The deviations from regression values were significant for seven genotypes. For this trait, the genotypes AHS-152 (311.70), ER-1 (303.30), AHS-161 (296.80), HS-4288 (291.30) and AS (288.30) recorded high mean values. The genotypes ER-1 (0.967) and AMV-4 (1.066) showed non-significant regression coefficients nearing unity and none of the genotypes showed low, non-significant deviation from the regression values. The genotypes, ER-1, CRIJAFR-8 and AMV-4 could perform well under average environmental conditions as it exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, AS-80-19, AHS- 162 and R-78, were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotypes, AHS-152, HS-4288 and R-28, showed high means with less than unity regression, could perform well under poor environmental conditions. These results are in harmony with the reports of Appala Swamy (1994) in kenaf and upthaji (1993) in roselle.

146 Basal stem diameter (mm) The variation exhibited for this trait ranged from (AHS-179) to (R-134) with a mean value of The regression coefficient values were nonsignificant. The deviations from regression values were significant for six genotypes. For this trait, the genotypes, R-134 (17.75), R-93 (17.704), AS (17.59), ER-1 (17.38) and AHS-160 (17.27), recorded high mean values. The genotypes, ER-1 (1.07), ER-58 (1.03), JRRM-9-1 (0.97) and AS (0.96), showed non-significant regression coefficients nearing unity. The genotypes, AS (17.60) and R-93 (17.70), had high mean value, non-significant regression co-efficient nearing unity (0.96) and (1.08) with low, non-significant deviation from regression (0.512). The genotypes, ER-1 and R-93, could perform well under average environmental conditions as they exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, R-78, CRIJAFR-8, JRR- 9 and AMV-4, were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotypes, AR-12, AS and JRRM-9-1, showed high means with less than unity regression, could perform well under poor environmental conditions Bark thickness (mm) The variation exhibited for this trait ranged from (AMV-5) to (JRR-9) with a mean value of The regression coefficient values were significant for four genotypes. The deviations from regression values were significant for six genotypes. For this trait, the genotypes, JRR-9 (3.434), R-93 (17.704), ER-63 (3.233) and AHS-160 (3.153), recorded high mean values. The genotypes, ER-38 (0.99), ER-63 (0.97), R-28 (1.012) and AR-12 (1.041), showed non-significant regression coefficients nearing unity. The genotype, R-93, had high mean value (3.13), non-significant regression co-efficient nearing unity (1.124) with low, non-significant deviation from regression (0.061). The genotypes, AR-71, R-28, R-78 and AHS-161, could perform well under average environmental conditions as they exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, ER-1 and R-93,

147 were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotypes, AR-71 and R- 83, showed high means with less than unity regression, could perform well under poor environmental conditions Number of nodes per plant The variation exhibited for this trait ranged from (AHS-179) to (R-78) with a mean value of The regression coefficient values were nonsignificant for all the lines and the deviations from regression values were significant for six genotypes. For this trait, the genotypes, R-78 (56.800), R-93 (56.522), ER-1 (54.267) and AHS-160 (56.222), recorded high mean values. The genotypes, ER-1 (0.98), AR-71 (1.03), CRIJAFR-2 (1.06) and ER-63 (1.08), showed non-significant regression coefficients nearing unity. The genotype, AR-12, had high mean value (54.00), nonsignificant regression co-efficient nearing unity (0.919) with low, non-significant deviation from regression (-9.086). The genotypes, AR-12, AS and AMV-4, could perform well under average environmental conditions as they exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, R-200, AS and CRIJAFR-2, were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotypes, ER-1, AR-12, CRIJAFR-8 and AMV-4, showed high means with less than unity regression, could perform well under poor environmental conditions. These results are in accordance with Appala Swamy (1994) in kenaf and upthaji (1993) in roselle Internodal length per plant (cm) The variation exhibited for this trait ranged from (R-93) to (AHS-152) with a mean value of The regression coefficient values were significant for three genotypes. The deviations from regression values were significant for only one genotype.

148 For this trait, the genotypes, AHS-152 (6.023), R-28 (6.017), AS (6.013), and AS (5.899), recorded high mean values. While the genotype, ER-58, had high mean value (5.55), non-significant regression co-efficient nearing unity (0.911) with low, non-significant deviation from regression (-0.065). The genotype, ER-58, could perform well under average environmental conditions as it exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, AR-12, AHS-152 and AS-80-29, were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotypes, CRIJAR-2 and ER- 38, showed high means with less than unity regression, could perform well under poor environmental conditions reen plant weight per plant The variation exhibited for this trait ranged from (AHS-179) to (AHS-172) with a mean value of The regression coefficient values were non-significant. The deviations from regression values were significant for nine genotypes. For this trait, the genotypes, AHS-172 ( ), ER-1 ( ), AHS-160 ( ), CRIJAFR-8 ( ) and AHS-160 ( ), recorded high mean values. The genotypes, AS (1.00), AMV-4 (0.97), AS (1.03), AS (1.03) and JRRM-9-1 (1.09), showed non-significant regression coefficients nearing unity and none of the genotypes showed low, non-significant deviation from the regression values. The genotypes, AS and AS-80-19, could perform well under average environmental conditions as they exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, ER-1, AR-71, R-78 and JRRM-9-1, were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotypes, AMV- 4, HS-4288 and R-83, showed high means with less than unity regression and could perform well under poor environmental conditions.

149 Fibre length per plant The variation exhibited for this trait ranged from (R-200) to (ER-1) with a mean value of The regression coefficient values were nonsignificant. The deviations from regression values were significant for four genotypes. For this trait, the genotypes, ER-1 (298.40), AHS-152 (298.00), AHS-172 (296.70) and AHS-161 (296.50), recorded high mean values. The genotypes, AMV-4 (1.03), AMV-5 (1.03), AHS-161 (1.04) and AS (1.05), showed non-significant regression coefficients nearing unity and none of the genotypes showed low, nonsignificant deviation from the regression values. The genotypes, AS-80-31, AMV-4 and HS-4288, could perform well under average environmental conditions as they exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, R-28, R-78 and AS-80-29, were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotypes, ER-10 and AHS-152, showed high means with less than unity regression, could perform well under poor environmental conditions. These results are in confirmity with the reports of Appala Swamy (1994) in kenaf and upthaji (1993) in roselle Fibre wood ratio The variation exhibited for this trait ranged from (CRIJAFR-2) to (R-28) with a mean value of The regression coefficient value was significant for only one genotype. The deviations from regression values were significant for three genotypes. For this trait, the genotypes, R-28 (0.481), R-200 (0.480), AR-72 (0.450) and JRRM-9-1 (0.444), recorded high mean values. The genotype, AHS-152 (0.96), showed non-significant regression coefficients nearing unity. The genotype, AHS-152, had high mean value (0.393), non-significant regression co-efficient nearing unity (0.96) with low, non-significant deviation from regression (0.00). The genotype, AHS-152, could perform well under average environmental conditions as it exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, AR-71, AR-72, R-78 and AS-80-29, were considered to be stable for favourable environmental condition as they exhibited

150 high means with greater than unity regression, whereas the genotypes, ER-10, showed high means with less than unity regression, could perform well even under poor environmental conditions Fibre yield per plant The variation exhibited for this trait ranged from (ER-38) to (AHS-160) with a mean value of The regression coefficient values were significant for four genotypes. The deviations from regression values were significant for two genotypes. For this trait, the genotypes, AHS-160 (22.136), R-78 (18.777), R-83 (17.370) and AHS-172 (17.432), recorded high mean values. The genotypes, AMV-4 (1.00), ER-58 (1.01) and HS-4288 (0.97), showed non-significant regression coefficients nearing unity and none of the genotypes showed low, non-significant deviation from the regression values. The genotype, HS-4288, had high mean value (17.11), nonsignificant regression co-efficient nearing unity (0.97) with low, non-significant deviation from regression (-2.60). The genotype, HS-4288, could perform well under average environmental conditions as it exhibited high mean performance with near to unity regression and least deviation from regression. The genotypes, R-78, R-83 and AHS-162, were considered to be stable for favourable environmental condition as they exhibited high means with greater than unity regression, whereas the genotype, ER-10 showed high means with less than unity regression, could perform well under poor environmental conditions. These results are in accordance with Appala Swamy (1994) in kenaf and upthaji (1993) in roselle Stable genotypes for various environmental conditions as per Eberhart and Russell (1966) stability parameters. Based on the stability parameters viz., (i) high mean(x), (ii) non-significant b i and (iii) non-significant deviation from regression by consideration of all the quantitative characters, the genotypes are grouped into three groups roup-i: Stable genotype for average environmental conditions

151 regression. enotypes with high mean, near to unity regression and least deviation from roup II: Stable genotypes for favourable environmental conditions enotypes with high mean, greater than unity regression and least deviation from regression. roup III: Stable genotypes for poor environmental conditions enotypes with high mean, less than unity regression and least deviation from regression. The genotypes are classified into the above groups character-wise and presented in the Table The genotypes, AS (for days to 50% flowering and green plant weight); ER-1 (for plant height and basal stem diameter), AHS-161 (for bark thickness), AMV-4 (plant height, number of nodes per plant and fibre length per plant), AHS-152 (for fibre wood ratio); ER-58 (for intermodal length per plant) and HS-4288 (fibre length per plant and fibre yield per plant) are found to be stable for average environmental conditions. The genotypes, AS (for days to 50% flowering, plant height and number of nodes per plant); R-78 (for plant height, basal stem diameter, green plant weight, fibre length per plant, fibre wood ratio and fibre yield per plant); ER-1 (for bark thickness and green plant weight); AR-71 (for green plant weight and fibre wood ratio) and AHS-152 stable for internodal length per plant are found to be stable for favourable environmental conditions. The genotypes, AHS-152 (for days to 50% flowering, plant height and fibre length per plant); HS-4288 (for plant height, green plant weight), AR-12 (for basal stem diameter, number of nodes per plant and fibre length per plant); R-83 (for bark thickness and green plant weight) and ER-10 (fibre length per plant and fibre yield per plant) are found to be stable for poor environmental conditions.

152 4.5.2 Additive Main Effects and Multiplicative Interaction Model (auch, 1988) The AMMI statistical model is a hybrid model. It makes use of standard ANOVA procedures to separate the additive variance from the multiplicative variance (genotype x environment interaction) and then uses a multiplicative procedure (rincipal component analysis CA) to extract the pattern from the E portion of the ANOVA analysis. The result is the least square analysis which with further graphical representation of the numerical results (Biplot analysis), often allows a straight forward interpretation of the underlying causes of E. The AMMI biplot is developed by placing both genotype and environment values on the X-axis and the respective CA axis eigen vector on the Y-axis. According to AMMI model, when a genotype and an environment had the same sign on the CA axis the interaction was positive; if different, their interaction was negative. If a genotype or an environment had a CA score of nearly zero, it had a small interaction effect and are considered as stable over wide range of environment. However, the genotypes with high mean performance with large CA scores are considered as having specific adaptability to the environments. The ICA scores of a genotype in the analysis are an indication of the stability of a genotype over environments. The combined analysis of variance (ANOVA) of 30 genotypes over three environments pertaining to AMMI model for fibre yield per plant and its components is presented in Table Days to 50% flowering AMMI analysis for days to 50% flowering showed that genotypes and environments were significant. The genotype, environment and genotype environment interaction accounted for 4.71%, 93.64% and 1.63% of the total variation, respectively. The ANOVA table indicated that only the ICA 1 axis was significant and explained 92.16% of the total x E interaction sum of squares percentage. The ICA 2 and ICA 3 were non-significant and explained 7.83% and 0.00% of the total x E interaction sum of squares. According to AMMI 1 biplot (Fig 4.9), the genotypes, 24 (AHS-152), 20 (JRR- 9), 6 (AR-12) and 15 (AS-80-29), were identified as stable. In AMMI 2 biplot (Fig 4.10), the genotypes, 8 (AR-72) and 5 (ER-63), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA 2.

153 lant height (cm) AMMI analysis for plant height showed that only environments were significant. The genotype, environment and genotype environment interaction accounted for 10.82%, 69.38% and 19.79% of the total variation, respectively. The ANOVA table indicated that the ICA 1, ICA 2 and ICA 3 were non-significant and explained %, 19.97% and 0.00% of the total x E interaction sum of squares. According to AMMI 1 biplot (Fig 4.11), genotypes, 19 (CRIJAFR-8), 9 (R-28), 17 (AS-80-19), 18 (CRIJAFR-2) and 30 (HS-4288), were identified as stable genotypes. In AMMI 2 biplot (Fig 4.12), the genotypes, 19 (CRIJAFR-8), 23 (AHS- 161) and 30 (HS-4288), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA Basal stem diameter (mm) AMMI analysis for basal stem diameter showed that only environments were significant. The genotype, environment and genotype environment interaction accounted for 3.69%, 82.34% and 13.93% of the total variation, respectively. The ANOVA table indicated that the ICA 1, ICA 2 and ICA 3 were non-significant and explained 77.34%, 22.65% and 0.00% of the total E interaction sum of squares. According to AMMI 1 biplot (Fig 4.13), genotypes, 21 (JRRM-9-1), 4 (ER-58), 6 (AR-12), 18 (CRIJAFR-2) and 13 (R-200), were identified as stable. In AMMI 2 biplot (Fig 4.14), the genotypes, 1 (ER-1), 6 (AR-12) and 21 (JRRM-9-1), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA Bark thickness (mm) AMMI analysis for bark thickness showed that only environments were significant. The genotype, environment and genotype environment interaction accounted for 10.76%, 65.41% and 23.52% of the total variation, respectively. The ANOVA table indicated that the ICA 1, ICA 2 and ICA 3 were non-significant and explained 15.42%, 35.18% and 0.00% of the total E interaction sum of squares.

154 According to AMMI 1 biplot (Fig 4.15), genotypes, 23 (AHS-161) and 13 (R- 200), were identified as stable. In AMMI 2 biplot (Fig 4.16), the genotypes, 23 (AHS- 161), 14 (R-83) and 11 (R-78), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA Number of nodes per plant AMMI analysis for number of nodes per plant showed that only environments were significant. The genotype, environment and genotype environment interaction accounted for 3.87%, 84.29% and 11.82% of the total variation, respectively. The ANOVA table indicated that the ICA 1, ICA 2 and ICA 3 were non-significant and explained 10.16%, 1.66% and 0.00% of the total E interaction sum of squares. According to AMMI 1 biplot (Fig 4.17), genotypes, 28 (AMV-4) and 22 (AHS- 160), were identified as stable. In AMMI 2 biplot (Fig 4.18), the genotypes, 7 (AR-71), and 20 (JRR-9), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA Internodal length per plant (cm) AMMI analysis for intermodal length per plant showed that genotypes and environments were significant. The genotype, environment and genotype environment interaction accounted for 33.97%, 27.41% and 38.62% of the total variation, respectively. The ANOVA table indicated that the ICA 1, ICA 2 and ICA 3 were non-significant and explained 68.11%, 31.87% and 0.00% of the total E interaction sum of squares. According to AMMI 1 biplot (Fig 4.17), genotypes, 4 (ER-58), 18 (CRIJAFR- 2) and 25 (AHS-162), were identified as stable genotypes. In AMMI 2 biplot (Fig 4.18), the genotypes, 6 (AR-12), 14 (R-83), 4 (ER-58) and 11 (R-78), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment II is most suitable as indicated by high mean value of ICA 1 and low value of ICA 2.

155 reen plant weight (g) AMMI analysis for green plant weight per capsule showed that environments were significant. The genotype, environment and genotype environment interaction accounted for 3.86%, 83.01% and 13.12% of the total variation, respectively. The ANOVA table indicated that ICA 1, ICA 2 and ICA 3 were non-significant and explained %, 18.19% and 0.00% of the total E interaction sum of squares. According to AMMI 1 biplot (Fig 4.19), genotypes, 11 (R-78), 17 (AS-80-19) and 30 (HS-4288), were identified as stable genotypes. According to AMMI 2 biplot (Fig. 4.20), genotypes, 4 (ER-58), 6 (AR-12) and 17 (AS-80-19), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA Fibre length per plant (cm) AMMI analysis for fibre length per plant showed that environments were significant. The genotype, environment and genotype environment interaction accounted for 12.11%, 68.32% and 19.55% of the total variation, respectively. The ANOVA table indicated that the ICA 1, ICA 2 and ICA 3 were non-significant and explained 83.30%, 16.69% and 0.001% of the total E interaction sum of squares. According to AMMI 1 biplot (Fig 4.21), genotypes, 28 (AMV-4) and 30 (HS- 4288), were identified as stable genotypes. In AMMI 2 biplot (Fig 4.22), the genotypes, 28 (AMV-4) and 16 (AS-80-31), were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA Fibre wood ratio AMMI analysis for fibre wood ratio showed that environments were significant. The genotype, environment and genotype environment interaction accounted for 13.81%, 33.49% and 52.53% of the total variation, respectively. The ANOVA table indicated that ICA 1, ICA 2 and ICA 3 were explained 85.16%, 14.83% and 0.00 % of the total E interaction and were non-significant.

156 According to AMMI 1 biplot (Fig 4.23), the genotypes, 2 (ER-10) and 22 (AHS-160) were identified as stable genotypes. In AMMI 2 biplot (Fig 4.24), genotypes, 8 (AR-72), 11 (R-78) and 30 (HS-4288) were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA Fibre yield per plant (g) AMMI analysis for fibre yield per plant showed that genotypes and environments were significant. The genotype, environment and genotype environment interaction accounted for 7.72%, 75.93% and 16.34% of the total variation, respectively. The ANOVA table indicated that only the ICA 1 axis was significant and explained 14.68% of the total E interaction sum of squares percentage. The ICA 2 and ICA 3 were non-significant and explained 1.65% and 0.00% of the total x E interaction sum of squares. According to AMMI 1 biplot (Fig 4.25), genotype, 30 (HS-4288), was identified as stable genotype. In AMMI 2 biplot (Fig 4.26), the genotypes, 18 (CRIJAFR-2), 28 (AMV-4) and 30 (HS-4288) were nearer to ICA origin, hence these genotypes were stable over environments. Among the environments, environment I is most suitable as indicated by high mean value of ICA 1 and low value of ICA AMMI s stability values (ASV) Quantitative stability measure is essential in order to quantify and rank genotypes according to their yield stability. However, the AMMI model does not provide measure for a quantitative stability. For this, AMMI s stability value (ASV) was proposed by urchase et al. (1997). The genotype with low ASV values is considered as stable genotype. The data pertaining to AMMI s stability value (ASV) were presented in Table 4.21 and the results are discussed here under. For days to 50% flowering, the ASV values ranged from to The genotypes, AHS-152 (0.095), JRR-9 (0.221), AR-72 (0.624) and AS (0.624) were found to be most stable, while AHS-160 (13.134), AHS-172 (16.832), R-78 (23.860) and AHS-162 (26.982) were less stable. Whereasfor plant height, the ASV values ranged from to The genotypes, CRIJAFR-8 (0.700), ER-63

157 (1.192), HS-4288 (1.843) and R-28 (1.941) were considered to be most stable, while AHS-172 (19.450), ER-38 (19.890), R-83 (20.073) and AHS-179 (20.395) were less stable genotypes. For basal stem diameter, the ASV values ranged from to The genotypes, JRRM-9-1 (0.170), ER-58 (0.254), AR-12 (0.274) and ER-1 (0.480) were considered to be most stable, while AHS-162 (3.782), AHS-152(3.786), AHS-179 (4.155) and AHS-172 (4.968) were less stable genotypes. Whereasfor bark thickness, the ASV values ranged from to The genotypes, AHS-161 (0.067), AMV-4 (0.165), AR-12 (0.168) and R-78 (0.173) were found to be most stable, while AHS-152 (0.917), AHS-179 (1.057), AHS-172 (1.098) and AHS-162 (1.175) were less stable genotypes. For number of nodes per plant, the ASV values ranged from 0.43 to The genotypes, CRIJAFR-2 (0.43), CRIJAFR-8 (0.58), AMV-4 (0.69) and AS (0.69) were considered to be most stable, while AHS-172 (9.22), AMV-5 (9.66), R-83 (15.09) and AHS-179 (19.05) were less stable genotypes. Whereasfor internodal length per plant, the ASV values ranged from 0.08 to The genotypes, ER-58 (0.08), AHS- 162 (0.16), R-83 (0.16) and R-78 (0.19) were found to be most stable, while AS (0.82), AMV-5 (0.87), AHS-160 (1.00) and AS (2.03) were less stable genotypes. For green plant weight, the ASV values ranged from 2.14 to The genotypes, AS (2.14), HS-4288 (2.32), R-78 (2.38) and AS (2.86) were considered to be more stable, while AHS-172 (27.84), ER-38 (28.08), CRIJAFR-8 (32.10) and AHS-179 (32.46) were less stable genotypes. Whereasfor fibre length per plant, the ASV values ranged from 0.61 to The genotypes, AMV-4 (0.61), HS (1.67), AS (1.99) and ER-38 (2.83) were found to be most stable, while AHS-152 (16.80), R-200 (16.90), AHS-179 (26.109) and AHS-172 (32.51) were less stable genotypes. For fibre wood ratio, the ASV values ranged from 0.08 to The genotypes, AHS-152 (0.08), ER-10 (0.09), AHS-160 (0.11) and R-134 (0.19) were found to be most stable, while AS (1.42), JRRM-9-1 (1.70), R-200 (1.74) and JRR-9 (1.87) were less stable genotypes. Whereasfor fibre yield per plant, the ASV values ranged from 0.42 to The genotypes, HS-4288 (0.42), AMV-4 (0.45), CRIJAFR-2 (1.03) and R-200 (1.14) were considered to be most stable, while AS (12.90), R-83 (17.79), AHS-172 (18.53) and AHS-160 (20.42) were less stable genotypes.

158 Selection of stable genotypes based on AMMI s Stability Values (ASV) An attempt was made in the present investigation to select the stable genotypes based on the ASVs by considering all the 10 quantitative characters. The data pertaining to ASVs were presented in Table 4.22 and the results are discussed here under. The genotype, HS-4288 was found to be stable for plant height, green plant weight, fibre length per plant and fibre yield per plant. The genotype, AHS-152 was found to be stable for days to 50% flowering and fibre wood ratio. The genotype, ER- 58 was found to be stable for basal stem diameter and internodal length per plant. While the genotype, AMV-4 was found to be stable for bark thickness, number of nodes per plant and fibre yield per plant Ranking of genotypes based on different stability parameters The data pertaining to ranking of genotypes based on different stability parameters are presented in Tables 4.23 to The results are discussed stability parameter wise here under Mean of ranks over environments of different characters for roselle genotypes The genotypes, AHS-172 (111.70) and AMV-4 (115.70) for days to 50% flowering showed desirable mean performance with low mean values. Whereas the genotypes, AHS-152 (311.70) and ER-1 (303.30) for plant height; R-134 (17.75) and R-93 (17.70) for basal stem diameter; JRR-9 (3.43) and ER-63 (3.23) for bark thickness; R-78 (56.80) and HS-4288 (55.56) for number of nodes per plant; R-28 (6.02) and AHS-152 (6.02) for internodal length per plant; AHS-172 (351.10) and ER-1 (349.20) for green plant weight; ER-1 (298.40) and AHS-152 (298.00) for fibre length per plant; R-28 (0.48) and R-200 (0.48) for fibre wood ratio and AHS-160 (22.14) and AS (19.60) for fibre yield per plant showed desirable mean performance with high mean values.

159 Mean of variance over environments for different characters in roselle genotypes The genotypes, AHS-162 (334.70) and R-78 (366.70) for days to 50% flowering; AHS-179 ( ) and R-200 ( ) for plant height; AHS-179 (5.43) and ER-10 (9.10) for basal stem diameter; ER-10 (0.06) and AHS-179 (0.12) for bark thickness; AHS-179 (85.51) and ER-10 (137.35) for number of nodes per plant; JRRM- 9-1 (0.002) and AR-71 (0.02) for internodal length per plant; AHS-179 ( ) and ER-17 ( ) for green plant weight; AHS-179 (672.80) and AHS-152 ( ) for fibre length per plant; AR-12 (0.000) and R-93 (0.000) for fibre wood ratio and AS (11.46) and AHS-161 (33.70) for fibre yield per plant showed low variance of rank values compared to other genotypes thus indicating the less fluctuations to changing environments Lewis stability factor (SF) values for different characters in roselle genotypes The genotypes, AHS-162 (1.25) and R-78 (1.26) for days to 50% flowering; AHS-179 (1.17) and ER-10 (1.22) for plant height; AHS-179 (1.24) and ER-10 (1.30) for basal stem diameter; ER-10 (1.12) and AHS-179 (1.18) for bark thickness; AHS- 179 (1.28) and ER-10 (1.36) for number of nodes per plant; JRRM-9-1 (1.01) and AR- 71 (1.04) for internodal length per plant; AHS-179 (1.55) and R-134 (1.90) for green plant weight; AHS-179 (1.13) and AHS-152 (1.18) for fibre length per plant; AR-12 (1.04) and R-93 (1.06) for fibre wood ratio and AS (1.45) and AHS-161 (1.74) for fibre yield per plant showed stable performance as indicated by low stability factor values Mean genotype-environment interaction variance values (as per laisted and eterson, 1959) for different characters in roselle genotypes The genotypes, AHS-152 (3.50), AR-72 (3.52) and IS-112-B (0.81) for days to 50% flowering; CRIJAFR-8 (297.97) and ER-63 (303.27) for plant height; AR-12 (1.27), JRRM-9-1 (1.27) and ER-58 (1.29) for basal stem diameter; AR-12 (0.10), R-78 (0.10), R-83 (0.10) and AHS-161 (0.10) for bark thickness; AR-28 (11.28) and CRIJAFR-2 (11.39) for number of nodes per plant; ER-58 (0.06), ER-38 (0.07), AR-12 (0.07), R-78 (0.07) and R-83 (0.07) for internodal length per plant; AS ( ) and AS ( ) for green plant weight; AMV-4 (329.47) and AS-80-31

160 (330.87) for fibre length per plant; ER-10 (0.006), R-134 (0.006), CRIJAFR-2 (0.006), AHS-160 (0.006), AHS-152 (0.006), HS-4288 (0.006) and ER-1 (0.007), ER-38 (0.007), AHS-179 (0.007) for fibre wood ratio and ER-1 (0.01), ER-10 (0.01), ER-38 (0.01), ER-58 (0.01), ER-63 (0.01), AR-12 (0.01), AR-72 (0.01), R-93 (0.01), R-78 (0.01), R-134 (0.01), R-83 (0.01), AS (0.01), AS (0.01), CRIJAFR-2 (0.01), CRIJAFR-8 (0.01), AHS-160 (0.01), AHS-161 (0.01), AHS-152 (0.01), AHS- 162 (0.01), AHS-172 (0.01), AHS-179 (0.01), AMV-5 (0.01), HS-4288 (0.01) and R-28 (0.02), R-200 (0.02), AS (0.02), JRRM-9-1 (0.02), AMV-4 (0.02), for fibre yield per plant showed stable performance as indicated by low stability factor values Wricke s Ecovalence value for different characters in roselle genotypes The genotypes, AHS-152 (0.002) and AR-72 (0.06), AS (0.06) for days to 50% flowering; CRIJAFR-8 (11.47) and ER-63 (31.97) for plant height; AR-12 (0.09) and JRRM-9-1 (0.11) for basal stem diameter; AHS-161 (0.01), R-78 (0.03) and R-83 (0.03) for bark thickness; AR-71 (1.13) and CRIJAFR-2 (1.56) for number of nodes per plant; ER-58 (0.01) and R-83 (0.02) for internodal length per plant; AS (389.87) and AS (558.77) for green plant weight; AMV-4 (23.35) and AS (28.79) for fibre length per plant; R-134 (0.001), AHS-160 (0.001), ER-10 (0.002), CRIJAFR-2 (0.002), AHS-152 (0.002) and HS-4288 (0.002) for fibre wood ratio and HS-4288 (0.26) and AMV-4 (0.32) for fibre yield per plant showed desirable performance with less contribution to genotype-environment interaction as evidenced from low ecovalence values Regression coefficients (b i ) (as per Eberhart and Russell, 1966) for different characters in roselle genotypes The genotypes, AHS-152 (1.00) and JRR-9 (1.01) for days to 50% flowering; CRIJAFR-8 (0.99) and ER-63 (1.02) for plant height; ER-58 (1.03) and JRRM-9-1 (0.97) for basal stem diameter; ER-38 (0.99) and R-28 (1.01) for bark thickness; ER-1 (0.98) and AR-71 (1.03) for number of nodes per plant; AHS-162 (0.91) and ER-58 (0.91) for internodal length per plant; AS (1.00) and AMV-4 (0.98) for green plant weight; AMV-5 (1.03) and AMV-4 (1.04) for fibre length per plant; AHS-152 (0.96) and ER-10 (0.90) for fibre wood ratio and AMV-4 (1.01) and ER-58 (1.01) for fibre yield per plant showed consistence performance as evidenced by close to unit regression values.

161 Deviation from regression values (s 2 di) (as per Eberhart and Russell, 1966) of different characters for roselle genotypes The genotypes, CRIJAFR-2 (-0.01) and R-200 (0.01) for days to 50% flowering; CRIJAFR-2 (4.15) and R-28 (-36.62) for plant height; ER-10 (0.07) and AMV-4 (0.11) for basal stem diameter; AHS-179 (0.02) and CRIJAFR-8 (-0.02) for bark thickness; R-78 (-0.10) and AHS-160 (-0.56) for number of nodes per plant; AHS- 152 (-0.003) and AMV-4 (0.01) for internodal length per plant; JRRM-9-1 (-33.35) and AMV-4 ( ) for green plant weight; R-78 (14.33) and AS (64.31) for fibre length per plant; ER-63 (0.000) and AHS-179 (0.000) for fibre wood ratio and AHS- 152 (0.11) and AHS-161 (0.56) for fibre yield per plant showed desirable performance with less fluctuations as s 2 d i values were low compared to other genotypes AMMI s stability values (ASV) of different characters for roselle genotypes The genotypes, AHS-152 (0.09) and JRR-9 (0.22) for days to 50% flowering; CRIJAFR-8 (0.70) and ER-63 (1.19) for plant height; JRRM-9-1 (0.17) and ER-58 (0.25) for basal stem diameter; AHS-161 (0.07) and AMV-4 (0.17) for bark thickness; CRIJAFR-2 (0.43) and CRIJAFR-8 (0.59) for number of nodes per plant; ER-58 (0.09) and AHS-162 (0.16) for internodal length per plant; AS (2.15) and HS-4288 (2.32) for green plant weight; AMV-4 (0.61) and HS-4288 (1.67) for fibre length per plant; AHS-152 (0.09) and ER-10 (0.09) for fibre wood ratio and HS-4288 (0.31) and AMV-4 (1.33) for fibre yield per plant showed stable performance as indicated by low ASV values Hanson s genotypic stability values (D 2 i) of different characters for roselle genotypes The genotypes, R-78 (2.10) and AHS-162 (2.67) for days to 50% flowering; AHS-179 (32.04) and R-200 (36.04) for plant height; ER-10 (1.74) and AHS-179 (1.82) for basal stem diameter; ER-10 (0.16) and AHS-179 (0.33) for bark thickness; AHS-179 (9.18) and ER-10 (10.71) for number of nodes per plant; R-134 (0.80) and JRRM-9-1 (0.84) for internodal length per plant; AHS-179 (52.75) and ER-10 (89.15) for green plant weight; AHS-179 (25.87) and AHS-152 (37.57) for fibre length per plant; R-83 (0.06), AHS-172 (0.06), AMV-5 (0.06), ER-58 (0.09) and AR-12 (0.09) for fibre wood ratio and AS (0.59) and AHS-161 (2.84) for fibre yield per plant showed desirable performance and stability as evidenced from their low variance values.

162 Shukla s stability variance values for different characters in roselle genotypes The genotypes, AHS-152 (-0.250), AR-12 (-0.219) and AS (-0.219) for days to 50% flowering; CRIJAFR-8 ( ) and ER-63 (-3.943) for plant height; AR- 12 (-0.039) and JRRM-9-1 (-0.030) for basal stem diameter; AHS-161 (-0.003) and R- 83 (0.008) for bark thickness; AR-71 (-0.180) and CRIJAFR-2 (0.050) for number of nodes per plant; ER-58 (0.001) and R-83 (0.008) for internodal length per plant; AS (82.811) and AS ( ) for green plant weight; AMV-4 ( ) and AS (-7.680) for fibre length per plant; ER-10 (0.00), R-134 (0.00), AHS-160 (0.00), AHS-152 (0.00), CRIJAFR-2 (0.001) and HS-4288 (0.001) for fibre wood ratio and HS-4288 (-0.336) and AMV-4 (-0.305) for fibre yield per plant showed consistent performance as evidenced by lower stability variance Selection of stable genotypes based on mean of ranks of different stability parameters for ten quantitative characters. An attempt was made in the present investigation to select the stable genotypes based on the mean of ranks of different stability parameters [mean, mean of variance over environments, Lewis stability factor, variance due to x E, Wricke s ecovalence, regression coefficient, deviation from regression, Hanson s genotypic stability, Shukla s stability variance, AMMI s stability values (ASV)] for 10 quantitative characters. The data pertaining to mean of ranks of different stability parameters for ten quantitative characters are presented in Table 4.33 and the results are discussed here under: Based on the mean of all the different stability parameters, the genotypes, HS-4288, was found to be the most stable for green plant weight, fibre wood ratio and fibre yield per plant whereas the genotype, AHS-152, was found to be most stable for days to 50% flowering; CRIJAFR-8, was found to be stable for plant height, AR-12, was found to be stable for basal stem diameter; AHS-162, was found to be stable for bark thickness; AMV-4, was found to be stable for number of nodes per plant, ER-38, was found to be stable for internodal length per plant; and ER-10, was found to be stable for fibre wood ratio.

163 Based on overall rank of all the different stability parameters for ten quantitative characters, the genotypes AR-12, AMV-4, CRIJAFR-2, HS-4288 and ER-1 were found to be stable Selection of most stable genotypes An attempt was made in the present investigation to select the most stable genotypes based on the Eberhart and Russell (1966), stability parameters, AMMI s stability values (ASV) and mean of ranks of different stability parameters for ten quantitative characters. The data pertaining to the most stable genotypes for ten quantitative characters are presented in Table 4.34 and the results are discussed here under: The genotypes, AS (for days to 50% flowering and green plant weight); AMV-4, HS-4288 (plant height, internodal length per plant, green plant weight, fibre length per plant and fibre yield per plant) ER-1 (basal stem diameter and bark thickness) and AHS-152 (for fibre wood ratio) were found to be stable over environments. In the present investigation, the genotypes, ER-1, AS-80-29, AS-80-19, JRR-9, AR-12, AR-71, R-78, AMV-4 and HS-4288 are found to be most promising by comparative study of stability models and stability parameters and may serve as potential parental genotypes for future breeding programmes to develop desirable stable seggregants in roselle improvement.

164 Chapter V SUMMARY AND CONCLUSIONS The present investigation was carried out during late kharif, 2013 in three different dates of sowing [Environment 1 (E 1 ) = ; Environment 2 (E 2 ) = ; Environment 3 (E 3 ) = )] at the Agricultural Research Station Farm, Amadalavalasa, Andhra radesh with 30 genotypes of roselle (Hibiscus sabdariffa L.) to study the mean, genetic variability, heritability, genetic advance as per cent of mean, character association, the magnitude of direct and indirect effects of yield component traits on fibre yield, using stability analysis (Eberhart and Russell s (1966), Additive Main effects and Multiplicative Interaction (AMMI) model and different stability parameters i.e., mean, mean of variance over environments, Lewis stability factor, variance due to E, Wricke s ecovalence, regression coefficient, deviation from regression, Hanson s genotypic stability, Shukla s stability variance and AMMI s stability value (ASV). Observations were recorded on randomly selected plants for ten quantitative characters viz., days to 50% flowering, plant height (cm), basal stem diameter (mm), bark thickness (mm), number of nodes per plant, internodal length per plant (cm), green plant weight (g), fibre length per plant, fibre wood ratio and fibre yield per plant (g). The analysis of variance revealed significant differences among the genotypes for all the characters in all the environments indicating the presence of sufficient genetic variability in the studied material. The genotypic coefficients of variation for all the characters studied were lesser than the phenotypic coefficients of variation indicating the interaction of genotypes with environment. High heritability coupled with high genetic advance as per cent of mean was observed for fibre wood ratio (in environment IIΙ) and fibre yield per plant (in environment II) indicating the importance of additive gene action in governing the inheritance of these traits. Hence, direct phenotypic selection is useful with respect to these traits.

165 The study of environment-wise character association revealed that the characters viz., basal stem diameter, bark thickness and green plant weight showed significant positive association with fibre yield per plant in all the environments. Therefore, simultaneous improvement of fibre yield is possible through selection of these characters. The study of environment-wise path coefficient analysis indicated that bark thickness, number of nodes per plant, green plant weight and fibre length per plant had positive direct effects coupled with positive significant correlation with fibre yield per plant in all the three environments. Therefore, simultaneous improvement of fibre yield is possible through selection of these characters. ooled analysis of variance for stability showed significant differences among the genotypes for days to 50% flowering, internodal length per plant and fibre yield per plant indicating sufficient variability among the genotypes. Environments and environment (linear) components were significant for all the characters indicating that environments were divergent. The genotype environment (linear) interaction showed significance for days to 50% flowering, internodal length per plant, fibre wood ratio and fibre yield per plant and non-significance for remaining characters. ooled deviation component was highly significant for days to 50% flowering, plant height, basal stem diameter, bark thickness, number of nodes per plant, green plant weight, fibre length per plant and fibre wood ratio indicating the importance of non-linear component in the genotype-environment interaction. As per Eberhart and Russell stability analysis, the genotypes AS (for days to 50% flowering and green plant weight); ER-1 (for plant height and basal stem diameter), AHS-161 (for bark thickness), AMV-4 (plant height, number of nodes per plant and fibre length per plant), AHS-152 (for fibre wood ratio); ER-58 (for intermodal length per plant) and HS-4288 (fibre length per plant and fibre yield per plant) were found to be stable for average environmental conditions. The genotypes, AS (for days to 50% flowering, plant height and number of nodes per plant); R- 78 (for plant height, basal stem diameter, green plant weight, fibre length per plant, fibre wood ratio and fibre yield per plant); ER-1 (for bark thickness and green plant weight); AR-71 (for green plant weight and fibre wood ratio) and AHS-152 (for internodal length per plant) were found to be stable for favourable environmental conditions. The genotypes, AHS-152 (for days to 50% flowering, plant height and fibre

166 length per plant); HS-4288 (for plant height, green plant weight), AR-12 (for basal stem diameter, number of nodes per plant and fibre length per plant); R-83 (for bark thickness and green plant weight) and ER-10 (fibre length per plant and fibre yield per plant) were found to be stable for poor environmental conditions In AMMI analysis, the mean squares were significant for genotypes and environments for all the quantitative characters indicating significant differences among the genotypes and environments. Among the environments, sowing on third week of June (environment-i) was found to be most suitable for all the characters except for internodal length per plant as indicated by high mean value of ICA 1 and low value of ICA 2. The genotypes viz., AR-12, CRIJAFR-2, AS-80-29, AS-80-19, AMV-4 and HS-4288 which recorded high mean values with low interaction effects were found to be adaptable over environments for most of the characters. According to AMMI s stability values (ASV), the genotype HS-4288 was found to be stable for plant height, green plant weight, fibre length per plant and fibre yield per plant. The genotype AHS-152, was found to be stable for days to 50% flowering and fibre wood ratio. The genotype ER-58 was found to be stable for basal stem diameter and internodal length per plant. While the genotype, AMV-4, was found to be stable for bark thickness, number of nodes per plant and fibre yield per plant. Based on the mean of ranks of all the different stability parameters (mean, mean of variance over environments, Lewis stability factor, variance due to x E, Wricke s Ecovalence, Regression Coefficient, deviation from regression, Hanson s genotypic stability, Shukla s stability variance, AMMI s stability value (ASV)), the genotypes HS-4288 was found to be the most stable for green plant weight, fibre wood ratio and fibre yield per plant while the genotype AHS-152 was found to be the most stable for days to 50% flowering, CRIJAFR-8 was found to be stable for plant height, AR-12 was found to be stable for basal stem diameter, AHS-162 was found to be stable for bark thickness, AMV-4 was found to be stable for number of nodes per plant, ER-38 was found to be stable for internodal length per plant, and ER-10 was found to be stable for fibre wood ratio. The genotypes, AR-12, AMV-4, CRIJAFR-2, HS-4288 and ER-1, were found to be stable based on overall rank of all the different stability parameters for 10 quantitative characters.

167 Among different stability parameters, the variance of means over environments showed positive significant association with Hanson s genotypic stability for days to 50% flowering, plant height, basal stem diameter, bark thickness, number of nodes per plant, green plant weight, fibre length per plant, fibre wood ratio and fibre yield per plant. Variance due to E, Wrickes ecovalence and Shukla s variance showed significant positive association for most of the characters. The ranks of ASV showed positive correlation with all the stability parameters indicating that selection of stable genotypes based on the ranks of ASV will be most appropriate. The most stable genotypes were selected by the comparative studies of the Eberhart and Russell (1966) stability parameters, AMMI s stability values (ASV) and mean of ranks of different stability parameters for 10 quantitative characters. The genotypes AS (for days to 50% flowering, days to maturity and green plant weight); AMV-4, HS-4288 (plant height, internodal length per plant, green plant weight, fibre length per plant and fibre yield per plant); ER-1 (basal stem diameter and bark thickness) and AHS-152 (for fibre wood ratio) were found to be most stable. In the present investigation, the genotypes ER-1, AS-80-29, AS-80-19, JRR-9, AR-12, AR-71, R-78, AMV-4 and HS-4288 were found to be most promising by comparative study of stability models and stability parameters and may serve as potential parental genotypes for future breeding programmes to develop desirable stable seggregants for roselle improvement.

168 LITERATURE CITED Abdelatif Ahmed., Sulaiman Ahmed., Mohammed Kheir Abdelrahman and Elhag hassan Abuelgasim Some genotypic and phenotypic traits of roselle (Hibiscus sabdariffa var. sabdariffa) and their practical implications. Journal of Science and Technology. 10 (2): Adamson, W.C and Bagby, M.O Woody core fibre length, percentage and yield components of kenaf. Agronomy Journal. 67 (1): Adilakshmi, D Selection indices in kenaf (Hibiscus sabdariffa L.). M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Ahmed, S.U Effect of height on fibre yield in jute (Corchorus capsularis L.). Crop Science. 12: Allard, R.W rinciples of lant Breeding. John Wiley and Sons Inc., New York Allard, R.W and Bradshaw, A.D Implications of genotype-environmental interactions in applied plant breeding. Crop Science 4: Aliyu, L., Kuchinda, K. C., Lawal, A.B and Muhammad, A.A Evaluation of the agronomic potential, genetic variability and heritability in roselle (Hibiscus sabdariffa L.) at sumaru, Nigeria. Crop Research. 30 (30): Anuradha, T enetic divergence in roselle (Hibiscus sabdariffa L.). Journal of Research ANRAU. 31 (2): Anuradha, T and Suriyakumari, S Correlation and path coefficient analysis studies in F 2 generation in mesta. Madras Agriculture Journal. 89 (7-9): Anuradha, T and Venkateswara Rao, M Heritability and genetic advance of yield and yield attributes in mesta (Hibiscus sabdariffa L.). The Andhra Agricultural Journal. 40 (1&4): Anon Inventaire national du patrimoine naturel.

169 Appala Swamy, A Stability analysis in kenaf (Hibiscus cannabinus L.). M.Sc.(Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Appala Swamy, A., Madhu Kumar, K., Jagannadham, J and Amara Jyothi, Diversified eco-safe products of mesta. Book of abstracts, National Seminar onjjute and Allied Fibres in Changing Times Issues and Strategies. 3-5 Jan,2013. National Institute Of Research On Jute And Allied Fibre Technology Organised By The Indian Natural Fibre Society,12,Regent ark,kolkata Aruna, C., Subramanyam, D., Rama Kumar,.V and Satyanaryana, Correlation and path analysis in roselle (Hibiscus sabdariffa L.). Journal of Research AAU. 17 (1): Aruna, Ch., Subramanyam, D., Rama Kumar,.V and Satyanaryana, Variability, heritability and genetic advance in roselle (Hibiscus sabdariffa L.). Journal of Research AAU. XVII (2): Banerjee, R., Sinha, M.K., uha Roy, M.K and Banerjee, S Correlation and path analysis of yield components in Hibiscus sabdariffa L. Jute Development Journal. 8 (4): Bartlett, M.S Some examples of statistical methods of research in agriculture and applied biology. Supplement to Journal of Royal Statistical Society. 4: Basudev Roy Correlation between plant height and flowering time in jute (Corchorus olitorius L.). Indian Agriculturist. 10 (1): Basu, N. C and Chakravarthy, K A study on growth and flowering in mesta (Hibiscus cannabinus L.). Indian Agriculturist. 15 (1&2): Bhajantri, C.M., Mummigatti, U.V and Doddamani, M.B Correlation studies in mesta genotypes. Karnataka Journal of Agricultural Science. 20 (2): Bhangoo, M. S., Tehran, H.S and Henderson, J Effect of planting date, nitrogen levels, row spacing and plant population of kenaf performance in the San Joaquin Valley. Agronomy Journal (USA). 78 (4): Bhattacharya, C., Karmakar, K. S and Bakshi, A. 2007a. Study on genetic variability in capsularis jute at different population levels: A comparative study. Journal of Interacademica. 11 (4);

170 Bhattacharya, C., Karmakar, K. S and Bakshi, A. 2007b. A comparative study on association of characters with seed yield in genotypic and phenotypic level in two cultivated species of jute growth under red and lateriate one of west Bengal. Journal of Interacademica. 11 (4): Bhattacharya, C., Sarkar, and atra,.k. 2007c. Correlation studies in different root characters of jute (Corchrous capsularis L.) at 11 weeks growth stage. Journal of Interacademica. 11 (25): Burton.W Quantitative inheritance in grass. roceedings of 6 th International rass Land Congress. 1: Burton,.W and Devane, E.W Estimating heritability in tall fescue (Festuca arundinaceae) from replicated clone material. Agronomy Journal. 45: Campbell, T.A and White,. A opulation density and planting date effects on kenaf performance. Agronomy Journal (USA) 74 (1): Chaudhury, S.K., uha Roy, M.K and Sinha, M.K enetic variability and heritability studies in tossa jute germplasm. Jute Development Journal. 5 (1): Chaudhury, S.K., Sinha, M.K and Singh, D ath analysis in tossa jute. Indian Journal of Agricultural Science. 51 (11): Chaudhury, S.K and Haque, M.N Stability performance of some greengram varieties. Indian Journal of Agricultural Science. 47: Cochran,.W and Cox, M Experimental Designs. John Wiley and Sons Inc., New York Comstock, R.E and Moll, R.H enotype-environment interactions. Symposium on Statistical enetics and lant Breeding. National Academy of Sciences, National Research Council ub. 982, Desai, K.D., atel, R.M., Tikka, S.B.S and Kukadia, M.V henotypic stability of some promising genotypes of grain sorghum. Indian Journal of Agricultural Science. 53 (7): Dewey, D.R and Lu, K.H A correlation and path coefficient analysis of components of crested wheat grass seed production. Agronomy Journal. 51 (9):

171 Echekwu, C.A and Showemimo, F. A enetic, phenotypic and environmental variances and character associations in kenaf. African Crop Science Journal. 12 (4): Efrayimu, B enetic divergence in kenaf (Hibiscus sabdariffa L.). M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Eberhart, S.A and Russell, W.A Stability parameters for comparing varieties. Crop Science. 6: Falconer, D.S An Introduction to Quantitative enetics. Oliver and Boyd, Edinburgh, London Farshadfar E., Mahmodi N and Anitha Y AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). Australian Journal of Agricultural Research. 5 (13): Finlay, K.W and Wilkinson,.N Analysis of adaptation in a plant breeding programme. Australian Journal of Agricultural Research. 14: Fisher, R.A and Mackenzie, W.A Studies in crop variation. The manorial response of different potato varieties. Journal of Agricultural Sciences, cambridge. 13: Fisher, R.A and Yates, F Statistical Tables for Biological, Agricultural and Medical Research. Oliver and Boyd, Edinburgh, London Freeman,.H and erkins, J.M Environmental and genotype environmental components of variability VIII. Relation between genotypes grown in different environments and measures of these environments. Heredity. 27: Fripp, Y.J enotype Environmental interactions in Schizophyllum commne. Heredity. 28: auch, M Model selection and validation for yield traits with interaction. Biometrics. 44: hosh Dastidar, K.K and Bhaduri,.N enetic variability and association of different doses of nitrogen and sowing dates in capsularis jute. Indian Journal of enetics and lant Breeding. 43 (2):

172 omez, K.W. and omez, A.A Statistical rocedures for Agricultural Research. John Wiley & Sons Inc. New York. p: upta, S.K and Das, A.D Correlation and regression between fibre yield and its components in white jute. Indian Journal of Agricultural Science. 47 (7): uptaji, K.N.V.S. and Subramanyam, D enetic variability studies in mesta (Hibiscus sabdariffa L.). Andhra Agricultural Journal. 44 (1&2): uptaji, N.V.S.B.K Stability analysis in roselle (Hibiscus sabdariffa L.). M.Sc.(Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Hanson, W.D enotypic stability. Theoretical and Applied enetics. 40: Hari Ram Kumar B enetic Divergence studies in roselle (Hibiscus sabdariffa L.) M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Hassan Zali., Ezatollah Farshadfar., Hosein Sabaghpour, S and Rahmatollah Karimizadeh Evaluation of genotype environment interaction in chickpea using measures of stability from AMMI model. Annals of Biological Research. 3 (7): Hemalatha,.V enetic studies on intervarietal crosses of roselle (Hibiscus sabdariffa L.). M.Sc.(Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Hill, J enotype X environment interaction a challenge for plant breeding. Journal of Agricultural Science, Cambridge. 85: Ibrahim, M.M and Hussein, R.M Variability, heritability and genetic advance in some genotypes of roselle (Hibiscus sabdariffa L.). World Journal of Agricultural Science. 2 (3): Immer, F.R., Hays, H.K and owers, L Statistical determination of barley varietal adaptation. Journal of American Society of Agronomy. 26: Islam, S. Md., Uddin, M.N., Haque, M.M and Islam, M.N ath coefficient analysis for yield related traits in white jute (Corchorus capsularis L.). akistan Journal of Biological Sciences. 4 (1):

173 Jackson, J.E A User s uide to rincipal Components. John Wiley and Sons Inc., New York. Jha, S. K., Singh, N. K., Arun Kumar, R., Agarwal,. K., Bhatt, J. C., uleria, S. K., Lone, A. A., Sudan, R. S., Singh, K. and Mahajan, V Additive Main effects and Multiplicative Interaction analysis for grain yield of short duration maize hybrids in North-Western Himalayas. Indian Journal of enetics. 73 (1): Jindla L.N., Singh T. H., Allah Rang and Bansal M.L Stability for fibre yield and its components in jute. Research and Development Reporter. 4 (2): Johnson, H.W., Robinson, H.F and Comstock, R.E Estimates of genetic and environmental variability in soybean. Agronomy Journal. 47: Jowett, D Yield stability parameters for sorghum in East Africa. Crop Science. 12: Josy Joseph enetic parameters in a segregating population of Corchorus capsularis L. Indian Journal of enetics and lant Breeding. 35 (1): Kameswara Rao, K Correlation and path coefficient studies in fourty five genotypes of roselle (Hibiscus sabdariffa L.). The Andhra Agricultural Journal. 49 (3&4): Kameswara Rao, K Study of metro glyph analysis in roselle (Hibiscus sabdariffa L.). M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Kantilal, D enetic studies in F 2 progeny of sixteen kenaf crosses (Hibiscus sabdariffa L.). M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Kavithamani D., Amala Balu and Rajarathinam S Stability Analysis of seed cotton and its components of ossypium barbadense enotypes. Madras Agricultural Journal. 98 (10-12): Krishnaveni, B and Krishna Murthy, B. 2000a. ath analysis studies in F 2 and F 3 generation of roselle (Hibiscus sabdariffa L.). Journal of Research ANRAU. 28 (1&2):

174 Krishnaveni, B and Krishna Murthy, B. 2000b. Studies on variability, heritability and genetic advance in inter-varietal progenies of roselle (Hibiscus sabdariffa L.). Journal of Research ANRAU. 28 (1&2): Lewis, D enotype environment interaction. A relationship between dominance, heterosis, phenotypic stability and variability. Heredity. 8: Lush, J.L Heritability of quantitative character in farm animals. roceedings of 8 th Congress enetics. Heriditas. 35: Madhavi Rani, A Studies on heterosis and combining ability in kenaf (Hibiscus sabdariffa L.). M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Mahajan, R.K and Rao, A.V Note on regression analysis of genotype x environment interaction in rice. Indian Journal of Agricultural Sciences. 52: Maiti S. N., Datta,., Dikshit, U. N., Dua, D. B., Srivastava, S. K., hosh, K. L., Jha, K. C., Datta, A. N and Mukerjee, N Stability in five varieties of Tossa jute showing resistance to early flowering. Indian Journal of Agricultural Science. 51: Maiti, S. N., Biswas, S. R and Sen, S A cumulative study of selection indices in jute (Corchrous Spp). Mysore Journal of Agricultural Science. 11: Mohan Rao, Combining ability and heterosis in kenaf (Hibiscus cannabinus L.). M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Mostofa, M.., Islam, M.R., Morshed Alam, A.T.M., Mahbub Ali, S.M and Mollah, M.A.F enetic variability, heritability and correlation studies in kenaf (Hibiscus sabdariffa L.). Online Journal of Biological Sciences. 2 (6): Nasim Ali, Md and Sasmal, B A note on heritability and genetic advance from F2 to F3 generations in tossa jute. Indian Agriculturist. 55 (1&2): Ottai M. E. S., Aboud, K. A., Mahmoud, I. M and E-Harira, D. M Stability analysis of roselle cultivars (Hibiscus sabdariffa L.) in different nitrogen fertilizer conditions. World Journal of Agricultural Science. 2(3) :

175 admaja, Heterosis studies on roselle (Hibiscus sabdariffa L.). M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. anse, V enetics of quantitative characters in relation to plant breeding. Indian Journal of enetics. 17: anse, V. and Sukhatme,.V Statistical Methods for Agricultural Workers. Indian Council of Agricultural Research, New Delhi aramajit Singh and Buttar,. S Study of heritability, correlation and path coefficient analysis among yield components in Bt cotton hybrids (ossypium hirsutum L.). Cotton Research Journal, Jan-June: aul, N.K enetic architecture of yield and components of yield in mustard (Brassica juncea L.) Theoretical and Applied enetics. 53: erkins, M.J and Jinks, J.L Environmental and genotype environment components of variability. Multiple lines and crosses. Heredity. 23: laisted, R. L and eterson, L.C A technique for evaluating the ability of selection to yield consistently in different seasons or locations. American otato Journal. 36: ulli Bai,., Razia Sultana, anduranga Rao, C and Srinivasa Rao, V. 2005a. Multivariate analysis in roselle hemp (Hibiscus sabdariffa L.). The Andhra Agricultural Journal. 52 (1&2): ulli Bai,., Razia Sultana, anduranga Rao, C and Srinivasa Rao, V. 2005b. Character association and path analysis in roselle hemp (Hibiscus sabdariffa L.). The Andhra Agricultural Journal. 52 (3&4): urchase, J.L arametric analysis to describe x E interaction and yield stability in winter wheat. h.d Dissertation. Department of Agronomy, Faculty of Agriculture, University of the Free state, Bloemfontein, South Africa. p: 148. Qi, J.M., Zheng Y. Y and Wang Y. J An investigation on the high yielding ability and stability of jute cultivas in the three southern provinces of China and analytical methods. Journal of Fujian Agricultural College. 13 (4):

176 Rama Kumar,. V enetic analysis of fibre yield and yield components in roselle (Hibiscus sabdariffa L.) h.d. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Rani, Ch., Rama Kumar,.V., anduranga Rao, C and Srinivasa Rao, V Character association, path analysis and selection indices in roselle (Hibiscus sabdariffa L.). The Andhra Agricultural Journal. 53 (3&4): Riaz, M., Naveed, M., Farooq, J., Mahmood, A., Rafiq, Ch., Nadeem, M and Sadiq, A AMMI analysis for stability, adaptability and E interaction studies in cotton (ossypium hirsutum L.). The Journal of Animal and lant sciences. 23 (3): Robinson, H.H Quantitative genetics in relation to breeding on the centennial of medalism. Indian Journal of enetics. 26: Roy, S and hosh Dastidar, K.K Association of leaf characters with fibre yield, plant height and basal diameter in tossa jute (Corchorus olitorius L.). Indian Journal of enetics and lant Breeding. 64 (3): Salih, F.A Effect of variety, sowing date and Nitrogen on kenaf yields in kennana area of Sudan EL- Damer Suan- Acta Agronomica (Hungary) 31 (2) : Salih, Effect of sowing date and row width on he kenaf dry ribbon production in Central Sudan. Khartoum Sudan- Beitrage. Zur tropischen Landwirtschaft und Veterindramedizin (erman DR). 22 (4): Salman, S.C Analysis of variance and long term variety test of wheat. Agronomy Journal. 43: Sanoussi Atta, Hadiara Hassane Seyni, Yacoubous Bakasso, Benoit Sarr, Saka Lona and Mahamane Saadou Yield character variability in roselle (Hibiscus sabdariffa L.). African Journal of Agricultural Research. 6 (6): Sardhana, S., hosh, A. K and Borthakur, D. N Adaptability of romising roselle varieties to the uplands of Tripura. Indian Journal of Agricultural Sciences. 54 (8): Sasmal, B. C and Chakraborty, K Correlation and path coefficient analysis of yield component in mesta (Hibiscus sabdariffa L.). Indian journal of Heredity. 10 (2):

177 Sharma, S.M., Jain, K.K., Rai, R.C and Neelam Singh Evaluation of yield and stability performance of some green gram varieties. Indian Journal of Agricultural Sciences. 47: Shukla,.K and Singh, D Studies on heritability, correlation and discriminate function selection in jute. Indian Journal of enetics and lant Breeding. 27 (2): Shukla,.K Some statistical aspects of partitioning genotype environment components of variability. Heredity. 29: Singh, R.K and Bains, S.S enetic divergence for ginning outturn and its components in upland cotton. Indian Journal of enetics and lant Breeding. 28: Singh, D Estimates of correlation, heritability and discriminate function in jute (Corchorus olitorius L.). Indian Journal of Heredity. 2 (1): Singh, R.K and Chaudhary, B.D Biometrical Methods in Quantitative enetic Analysis. Kalyani ublishers, New Delhi Singh, A., anguly, D. M and Basak, S. L Effects of spacings and sowing dates on jute seed yield. Seed Research (India). 12 (2): Singh, and Narayanan, S.S Heterosis and Inbreeding depression. In. Singh and S.S. Narayanan (eds). In Biometrical techniques in plant breeding Kalyani ublishers, Ludhiana, India Sinha, M.K., uha Roy, K and Chaudhury, S.K Correlation and path-coefficient analysis in mesta. Indian journal of Agricultural Sciences. 56 (2): Sivasubramanian, S and Menon, M enotypic and henotypic variability in rice. Madras Agricultural Journal. 60: Subramanyam, D., Rama Kumar,.V., Krishnamurthy, B and Ismail, S Heritability and correlation studies in kenaf (Hibiscus cannabinus L.). Indian Journal of enetics. 53 (3): Swarup and Chaungle, B.S Studies on genetic variability in sorghum; phenotypic variation and heritable component in some quantitative characters contributing towards yield. Indian Journal of enetics. 22:

178 Turesson Cote The species and the variety as ecological unit. Heredity. 3: Venkateswara Rao, K Stability analysis studies on sesamum (Sesamum indicum L.) M.Sc. (Ag) Thesis. Acharya N Ranga Agricultural University, Rajendranagar, Hyderabad, India. Verma, A.K and Jay Lal Mahto Stability for yield and yield attributing characters in sesame under rainfed conditions. Journal of Oilseeds Research. 11 (2): Wricke, O Uber eine Methode zur Erfassung derkologischen strenb reite in Feldversuchen. Z flanzenxaxht. 47: Wricke, O Uber eine Biometrics che Methode zur Erfassung derokologischen Anpassung. Acta. Agri. Scand. Suppl. 16: Wright, S Systems of mating. enetics. 6: Wright, S Correlation and causation. Journal of Agricultural Research. 20: Yan, W and Hunt, L.A enotype by environment interaction and crop yield. lant Breeding Reviews. 16: Yates, F and Cochran, W The analysis of groups of experiments. Journal of Agricultural Sciences. 28: Yiguo Liu Diallel and stability analysis of kenaf (Hibiscus cannabinus L.) in South Africa. M.Sc. (Ag) Thesis. University of Free States, Bloemfontein, South Africa. Zobel, R.W., Wright, M.J and auch, M Statistical analysis of a yield trial. Agronomy Journal. 80: Note : The pattern of Literature Cited presented above is in accordance with the guidelines for thesis presentation, Acharya N.. Ranga Agricultural University, Hyderabad.

179 Fig Biplot (AMMI 1) for days to 50% flowering in roselle Fig Interaction Biplot (AMMI 2) for days to 50% flowering in roselle enotypes ICA 1 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :

180 Fig Biplot (AMMI 1) for plant height in roselle Fig Interaction Biplot (AMMI 2) for plant height in roselle enotypes ICA 1 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :

181 Fig Biplot (AMMI 1) for basal stem diameter in roselle Fig Interaction Biplot (AMMI 2) for basal stem diameter in roselle ICA 1 enotypes 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :

182 Fig Biplot (AMMI 1) for bark thickness in roselle Fig Interaction Biplot (AMMI 2) for bark thickness in roselle enotypes ICA 1 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :

183 Fig Biplot (AMMI 1) for number of nodes per plant in roselle Fig Interaction Biplot (AMMI 2) for number of nodes per plant in roselle ICA 1 enotypes 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :

184 Fig Biplot (AMMI 1) for internodal length per plant in roselle Fig Interaction Biplot (AMMI 2) for internodal length per plant in roselle enotypes ICA 1 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :

185 Fig Biplot (AMMI 1) for green plant weight in roselle Fig Interaction Biplot (AMMI 2) for green plant weight in roselle enotypes ICA 1 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :

186 Fig Biplot (AMMI 1) for fibre length per plant in roselle Fig Interaction Biplot (AMMI 2) for fibre length per plant in roselle ICA 1 enotypes 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R-200 ER-1 2.ER R-833.ER AS ER AS ER-63 6.AR AS AR CRIJAFR-2 8.AR CRIJAFR-8 9.R R JRR-9 11.R R JRRM R AHS R AHS AS AHS AS AHS AS AHS CRIJAFR-2 27.AHS CRIJAFR-8 28.AMV-420.JRR-9 29.AMV-5 21.JRRM HS AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) Environments (Dates of sowing) E I : ; E II : ; E III :

187 Fig Biplot (AMMI 1) for fibre wood ratio in roselle Fig Interaction Biplot (AMMI 2) for fibre wood ratio in roselle enotypes ICA 1 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III : Fig Biplot (AMMI 1) for seed yield per plant in sesame

188 Fig Biplot (AMMI 1) for fibre yield per plant in roselle Fig Interaction Biplot (AMMI 2) for fibre yield per plant in roselle enotypes ICA 1 1. ER-1 2.ER-10 3.ER ER-58 5.ER-63 6.AR-12 7.AR-71 8.AR-72 9.R R R R R R AS AS AS CRIJAFR-2 19.CRIJAFR-8 20.JRR-9 21.JRRM AHS AHS AHS AHS AHS AHS AMV-4 29.AMV-5 30.HS-4288 Environments (Dates of sowing) E I : ; E II : ; E III :