Feasibility study of pheasant meat ripening by means of NIR spectroscopy and electronic nose methods

Transcription

1 IZVORNI ZNANSTVENI RAD Feasibility study of pheasant meat ripening by means of NIR spectroscopy and electronic nose methods Endre Drégelyi Kiss, Gabriella Andrássy-Baka, Lászlñ Locsmándi, András Szabñ, Rñbert Romvári Kaposvár University, Faculty of Animal Science, Laboratory of Animal Product Qualification, 7400, Kaposvár, Guba S. u. 40., Hungary Abstract Thirty female pheasant carcasses were aged in a refrigerator. Pectoralis muscle samples (n=5 x 6) were taken at days 0, 4, 6, 8 and 12 of ripening for further analysis. First the fresh samples were measured with near infrared spectroscopy and electronic nose (EN) techniques, than the ripened raw and heat treated (cooked, roasted and grilled) samples with EN techniques. Thereafter, discriminant analysis was performed on the spectral and sensory data to classify the sample groups according to the ripening period. Both methods were capable to discriminate within the fresh and aged samples perfectly. The NIR based classification result reached the 97% within the raw samples originated from the four ripening period. The cross validation results of the EN response signal based classification were 75, 45 and 49% in case of cooked, roasted and grilled samples, respectively. Key words: pheasant, NIR spectroscopy, electronic nose, heat treated meat Introduction Newly emerging trend is the reviving of the small game and venison as a meat source for the modern consumer. The wild pheasant is gamy and tender, which inspires fantasies in the kitchen for a long time past (David, 1950). Relatively low number of scientific papers deal with the pheasant meat quality on an experimental basis. The effect of slaughter age of pheasant carcass traits was described by Sarica et al. (1999). According to the results of Adamski and. Kuźniacka (2006), there are no sex depending differences on most psychical traits and also on chemical composition of pheasant meat, therefore both male and female have the same nutritive value and culinary usefulness. Very little scientific information is available from the sensory properties of pheasant. The raw pheasant meat contains relatively low level of aroma, which can increase with ripening typically in refrigerator for a given time. This flavour development is usually attributed to autolytic changes of the musculature but bacterial metabolism in gut also plays part in the process (Griffiths, 1975). Barnes et al. (1973) studied the effect of storage time and temperature on gamy character. The delicious flavour of cooked meat mainly derived from volatile compounds that developed during heating. In poultry more than 450 volatile components have been identified yet (Keeton and Eddy, 2004). From the viewpoint of meat aroma development three temperature intervals have outstanding importance. At 55 ºC the heat treated meat volatile characteristics are similar that of the raw meat. Around ºC the odor has a socalled boiled meat character as a result of lipid autoxidation and the aroma precursors existing in the raw meat. Over 110 ºC the Maillard reaction is dominant in flavour development resulting the typical cooked meat aroma. In studies dealing with the heat effects of meat the term Warmed-Over Flavour (WOF, off-flavour component s development of heat treated meat stored for hours in refrigerator) is generally used. Conventionally the volatile compounds characterization is based on natural sensing of panel testers. The basic shortcoming of the classical approach is the low repeatability and 45. hrvatski i 5. međunarodni simpozij agronoma 963

2 Fisheries, Game Management and Beekeeping reproducibility connected to the sensoric susceptibility of the estimating persons (Plutowska and Wardencki, 2007). To overcome the subjectivity of this method, electronic noses (EN) were developed. A review of the applications of EN to the evaluation of quality of foods was given by Di Natale et al. (2003). However, no artificial sensor based volatile compounds measurement to be found in the literature about pheasant meat. One of the most impressive technique in food qualification is the NIR spectroscopy which is a rapid ad non destructive method requiring little or no sample preparation. Contrary to wet chemistry, no reagents are required and no waste is produced (Pla et al., 2007). The application of NIR reflectance spectroscopy in the prediction of meat and meat products was reviewed by Prieto et al. (2009). The aim of our study was to test the applicability of NIR and EN methods following the ripening process of pheasant meat. Materials and methods Thirty female pheasants were used for the ripening study (liveweight = 1154, SD = 150 g). The eviscerated carcasses were hanged up in a refrigerator at 4 ºC. One quarter from each pectoralis superficialis muscle was taken at the 0, 4, 6, 8 and 12 days of storage. Three different heat treatment protocols (cooked at 85 ºC for 47 min., roasted at 200 ºC for 20 min. and grilled on a contact grill for 3 minutes) were performed. NIRS analyses The homogenized fresh and freeze-dried meat samples were measured by a Foss NIRSystems 6500 monochromator (Foss NIRSystems INC., Silver Spring, MD, USA) equipped with a sample transport module and a small ring cup cuvette. Reflectance spectra were taken from 400 to 2500 nm region and recorded as log 1/R at 2 nm intervals. The WinISI II spectral analytical software (InfraSoft International, Port Matilda, PS, USA) was utilized for the operation of the scanner and for the development of analytical procedures. All the samples were scanned twice and average spectra were saved. In order to separate the meat sample groups discriminate equations were developed using a partial least square (PLS) regression procedure. E-nose measurement The flavour characteristics measurement was performed by a Cyranose 320 e-nose equipment with semi-conducting polymer sensors using headspace sampling method. First the raw, then the heat treated samples (5 grams of each) were measured. The so-called fresh flavour was tested after the heat cooled back at 42 ºC, the WOF was measured after a 24 hour cooling storage of the heated samples at 7 ºC. All measurements were carried out in four repetitions. Finally principal components (PC) were extracted and used for discriminant analysis to classify the meat samples according to their ripening time (SPSS 10.0 for Windows). Results and discussion Figure 1 shows the mean of the visible/near infrared spectra of the raw, and heat treated samples at the beginning of the experiment and after 12 days of ripening. Before the discrimination analysis different mathematical treatments were applied on the spectral data. Finally, a gap and a smoothing segment of 8 data points proved to be the best without the use of scattering process. Thereafter first the fresh (0 day) and than the pooled aged raw samples (4, 6, 8, 12 day) were discriminated based on 12 PLS term. As a result of the remarkable structural and compositional differences between the samples during meat conversion (approx. two hours after slaughter) and the samples under aging only two misclassified samples were found. With the same discriminating method the ripening samples were classified acceptably, with the misclassification of 2, 1, 1 and 3 samples at th Croatian & 5 th International Symposium on Agriculture

3 the aging days 4, 6, 8 and 12, respectively. On Figure 2 the 3D representation of the sample distribution can bee seen. Figure 1. Average visible/nir reflectsnce spectra of the raw, and heat treated samples (1-raw meat, 2-grilled meat, 3-cooked meat, 4-roasted meat) Figure 2. 3D representation of the aged sample distribution Figure 3. Plot of the first two canonical discrimination functions obtained for WOF samples The EN response signals derived from the 32 sensors after correction and normalization for baseline signal. Similarly with the NIR evaluation the discriminant analysis of the fresh (0 day) and the pooled aged raw/untreated pheasant meat samples (day 4, 6, 8 and 12 day) were successful. Consequently attention was focused on the differentiability of the ripened samples. Based on the first two PCs (principal component), the discrimination possibility of the cooked meat samples was 100%. However, the correctly classified cross-validated cases were only 45.8%. While the two outside groups (day 4 and 12) were separated well, the central groups (day 6 and 8) were overlapped. The discrimination possibility of WOF samples was remarkably higher. Using the first two PCs (explaining the total variance of 92.4%), the results obtained from the cross validation was 75%. The complete separation of WOF samples (day 4, 6, 8 and 12) are illustrated in Figure 3. The perfect separation was due to the off-flavour component of WOF meat which is mainly attributable of lipid 45. hrvatski i 5. međunarodni simpozij agronoma 965

4 Fisheries, Game Management and Beekeeping oxidation (Pegg and Shahidi, 2004). These results are in good agreement with the findings of O Sullivan et al. (2003) who successfully tested the WOF based classification capability of different muscle types by the EN method. The aging-time dependent classification of the grilled samples was unsuccessful since the applied heating temperature of 200 ºC caused a hard cortex layer on the sample surface. In this case irrespectively of the sample s actual ripening phase the volatile products of the Maillard reaction are dominant (Mottram, 1998) suppressing the effect of aging specific components. Furthermore, an attempt was done to describe the effect of the different heating treatments on the volatile component development. The result achieved on the pooled samples (cooked, roasted and grilled) can be seen on Figure 4. The 91.7 % correctly classified cross-validated grouped cases refer to the remarkable effect of the applied heat procedure compared to the influence of aging time. Figure 4. PCA plot of the heat treated meat sample Conclusion The results obtained from this research suggest that both the NIR and the EN methods are suitable to follow the ripening process of pheasant meat. References Adamski M., Kuźniacka J. (2006). The effect of age and sex on slaughter traits of pheasants (Phasianus colchicus L.). Animal Science Papers and Reports. 24 (2): Barnes E. M., Mead G. C., Griffiths N. M. (1973). The microbiology and sensory evaluation of pheasants hung at 5, 10 and 15 C. British Poultry Science. 14 (3): Di Natale C, Paolesse R., D Amico A. (2003). Food and Beverage Quality Assurance In Handbook of machine olfaction: electronic nose technology, Pearce T. C. (ed.), Schiffman S.S. (ed.), Nagel H. T. (ed.), Gardner J. W. (ed.), Weinheim, Germany: WILEY- VCH GmbH & Co. David E. (1950). A Book of Mediterranean Food. London, UK: John Lehmann Ltd. Griffiths N. M. (1975). Sensory evaluation of pheasants hung at 10 g for up to 15 days. British Poultry Science. 16 (1): th Croatian & 5 th International Symposium on Agriculture

5 Keeton J. T.,Eddy S. (2004) Chemical and physical characteristics of meat - Chemical Composition In Encyclopedia of meat sciences, Jensen W. K. (ed.), Devine C.E. (ed.), Dikeman M. (ed.), Oxford, UK: Elsevier Ltd. Mottram D. S. (1998). Flavour formation in meat and meat products. Food Chemistry. 62 (4): O Sullivan M. G., Byrne D. V., Jensen M. T., Andersen H. J., Vestergaard J. (2003). A comparison of warmed-over flavour in pork by sensory analysis, GC/MS and the electronic nose. Meat Science. 65 (3): Pegg R. B., Shahidi F. (2004). Heat Effects on meat - Warmed-Over Flavour In Handbook of machine olfaction: electronic nose technology, Pearce T. C. (ed.), Schiffman S. S. (ed.), Nagel H. T. (ed.), Gardner J. W. (ed.), Weinheim, Germany: WILEY-VCH GmbH & Co. Pla M., Hernandez P., Arino B., Ramirez J. A., Diaz I. (2007). Prediction of fatty acid content in rabbit meat and discrimination between conventional and organic production systems by NIRS methodology. Food Chemistry. 100 (1): Plutowska B., Wardencki W. (2007). Aromagrams - Aromatic profiles in the appreciation of food quality. Food Chemistry. 101 (2): Prieto N., Roehe R., Lavìn P., Batten G., Andrés S. (2009). Application of near infrared reflectance spectroscopy to predict meat and meat products quality: A review. Meat Science. 83 (2): Sarica M., Karacay N., Camci Ő. (1999). Slaughter age and carcass traits of pheasants. Archiv fűr Geflügelkunde. 63 (4): SPSS for Windows Version 10.0, Copyright SPSS Inc. Chicago, IL. 45. hrvatski i 5. međunarodni simpozij agronoma 967