Detection and Quantification of Adulteration in Honey through Near Infrared Spectroscopy

Transcription

1 Proceedings of the 2014 International Conference of Food Properties (ICFP 2014) Kuala Lumpur, Malaysia, January 24-26, 2014 Detection and Quantification of Adulteration in Honey through Near Infrared Spectroscopy C. Kumaravelu, a,b A. Gopal a a CSIR - Central Electronics Engineering Research Institute- Chennai Centre, CSIR Madras Complex, Chennai , India b Research Scholar, Sathyabama University, Chennai, , India. Abstract Honey is one of the important traditional medicines since ancient times. In this paper, a case study was carried out using Near Infrared (NIR) spectroscopy techniques with Chemometrics to detect the Jaggery adulterants in the honey. This component used to prepare adulterant solution of different proportionate by manually and mixed with four types of different honey samples. Totally 160 spectra were collected by the XDS TM Optiprobe analyzer reflection mode and built a calibration model using Partial Least Square (PLS) regression and predict the honey adulteration statistically with the calibration error and coefficient of determination R 2 of Keywords: Near Infra-red Spectroscopy, Chemometric Analysis, Honey Adulteration and Partial Least Squares. 1. Introduction Honey is a naturally sweet and viscous product produced by Apis Mellifera bees from the nectar of flowers, from secretions of living parts of the plants, or excretions of plant-sucking insects on the living part of plants that the honey bees collect, transform and combine with specific substances of their own, deposit, dehydrate, store and leave in the honey combs to ripen and mature [1]. Honey is produced primarily from floral nectars, and fructose and glucose are the major components. Over all, the chemical composition of honey varies depending on plant source, season, production methods, and storage conditions. The average composition of honey is fructose (38.19%), glucose (31.28%), maltose (7.97%), sucrose (4.5%), higher sugars (0.86%), water (17.2%) and some trace minerals. Honey is adulterated with cheaper sweeteners such as refined cane sugar, beet sugar, Jaggery and corn syrup. In India, commonly used adulterants are cane sugar, i.e. sucrose extracted from sugarcane and Jaggery, which is a traditional concentrated product of sugarcane, representing the stage of sugar production prior to centrifuging and separation of crystals and molasses. Jaggery contains about 50% sucrose, 20% invert sugars, 20% moisture and other insoluble matter, such as wood ash, proteins and bagasse fibres. It is consumed in Asia, Africa and South America [2]. According to the international honey standards, honey shall not have added any food ingredients to it nor any particular constituent be removed from it. The detection of adulteration is a technical problem and such adulterations with inexpensive sweeteners such as corn syrups, high fructose corn syrups, invert syrups or high fructose inulin syrups. The adulteration of honey with invert sugar or syrup may not readily be detected by direct sugar analysis because its constituents are the major natural components of honey and the adulterated product would also have similar physical properties to natural honey [3]. Gas Chromatography (GC) and Liquid Chromatography (LC) have been used simultaneously to analyze sugars in honey. Additions of exogenous sugars could be detected as the appropriate fingerprints of adulteration. This method may be considered as a replacement of isotopic analysis, which has some limitations. In another work, Gas Chromatography Mass Spectrometry (GC-MS) method has been developed for the detection of honey adulteration with high fructose Inulin syrups [4,5]. Fourier Transform Infrared (FTIR) spectroscopy in combination with multivariate statistical techniques makes possible to obtain specific information about different parameters simultaneously in a direct, reliable and rapid way. In contrast to the time-consuming carbon isotope ratio analysis techniques, these FTIR spectroscopic procedures can be performed in very short time. By the use of Attenuated Total Reflectance (ATR) mid infrared Fourier transform spectroscopy it has been possible to successfully quantify the content of adulterants such as corn syrup, High Fructose Corn Syrup (HFCS) and inverted sugar in honeys [6].

2 When honey from one country is sold in another country to increase its sales it can have an effect on the sales of other honeys in that country. To prevent this detection of the honey origin and adulterants are to be determined by scientific ways, hence this NIR techniques and methods were adopted for findings of adulterants presented in the honey. Near infrared spectroscopy is a useful technique to evaluate adulteration of honey samples and it is a rapid, non-destructive which may be suitable as a screening technique in the quality control of honey. It is quite possible to detect adulteration by calibrating enough honey samples and analyzed them using Principal Component Analysis (PCA) and Partial Least Square (PLS) techniques. 2. Materials and Methods Four varieties of honey samples were purchased from the local market. Three adulterated mixtures of 150 ml honey were prepared with the successively increasing amount of Jaggery and water solutions as is presented in the Table 1. This method has been repeated for the sample preparation of other honey samples. Out of 16 samples, 160 spectra were collected for the analysis. Table 1: Concentration of adulterated solution in honey sample I and their adulterated level Honey Sample I (ml) 2.1. NIR Measurement system All the honey samples with adulterant content were used directly for experimental purpose to get NIR spectral signatures. XDS TM Optiprobe analyzer from FOSS NIR system was used under reflectance mode to get NIR spectra in the range of 400nm nm. This instrument utilized to get the spectra sample to samples, composition to compositions to detect and quantify the content of adulteration in honey samples Spectral data analysis The NIR spectra of any samples are influenced by its physiochemical properties and pose some problems in evaluating the important aspects of the samples. In view of this, spectral pretreatment could be used to minimize the irrelevant information in order to develop a simple and robust model. Some of the more frequent pre-processing for NIR spectra includes baseline correction, Multiplicative Signal Correction (MSC), Savitzky - Golay 2 nd order derivative, Savitzky - Golay Smoothing, Detrend and Standard Normal Variate (SNV). PCA and PLS were also performed using Unscrambler software to find the correlation between the samples and build a model to predict the adulteration of Jaggery in unknown honey samples. The adulterated honey was not validated with standard chemical analysis. 3. Results and Discussion Content for Adulteration (Jaggery solution) Concentration of Jaggery solution (w/v) in percent Level of Adulteration 150 Nil Nil Nil - (H) 150 5g + 10ml Low (A) g+ 20ml Medium (B) g + 30ml High (C) 3.1 Quality and quantity analysis on one sample (Honey-1) Figure 1 shows the absorption spectra of honey-1 sample and adulterated honey-1 by adding the Jaggery solution with different concentration as mentioned in the Table-1. The wavelength corresponding to the C-H, N-H first overtone, N-H stretch, C-H stretch, Cellulose and C=O bonds at 1440nm, 1460nm, 1580nm, 1660nm, 1780nm and 1900nm [2] respectively. PCA was applied to these absorption data in the wavelength range of 1100nm 2200nm and all these spectral data were pre-treated with suitable pre-processing techniques like baseline correction, Savitzky - Golay Smoothing followed by SNV with five principal components (PC) and observed PC-1 to correspond 78% and PC-2 to correspond 16% of their total variance. It can be seen in the Figure 2 that concentration of Jaggery solution is ascending trend in the PC-1 axis from left to right.

3 H A B C Absorbance Wavelength(nm) Figure 1: NIR absorption spectra of Honey-1 and adulterated Honey-1 samples. Figure 2: Score plot of Honey-1 and adulterated Honey-1 Analysing the loading plot of adulterated honey-1, it was found the wavelengths correspond to the higher concentration of fructose content been shifted [2] in comparison with its pure honey-1. This wavelength shift can be seen in the loading plot shown in Figure 3 and the wavelengths corresponding to high absorption for both higher level adulterated honey-1 and its pure honey-1 were tabulated in Table 2. Table 2: Peak wavelength for adulterated and unadulterated honey-1 sample Wavelength in (nm) corresponding to high absorption for Pure Honey-1 Shift in wavelength (nm) for higher level adulterated Honey

4 Figure 3: Plot for X-loading weights and variables for first principle component. PLS calibrated model was built with 24 samples on honey-1 (spectral signature of pure honey and adulterated content) to predict the quantity of adulteration in it and validated the model for the unknown sample. This model has been shown in Figure 4 and used to determine the adulterated honey with standard error of calibration (SEC) and coefficient of determination (R 2 ) are and The standard deviation error to predict on high level adulteration in honey-1 sample is ± All the results Figure 4: Plot for reference and predicted adulterated content in honey-1 sample 3.2 Quality analysis on pure and adulterated samples. PCA analysis was continued for other samples. Totally 29 spectral signatures have been prepared for pure honeys and 36 spectral signatures for adulterated samples. The adulterated samples were categorised with alphabets a, b, c for honey-1, x, y, z for honey-2, p, q, r for honey-3 and honey-4 as u, v, w. Figure 5 shows the score plot of all pure honey samples and Figure 6 shows the samples spread for adulterated honeys.

5 Figure 5: PCA score plot for all pure honey samples. Figure 6: PCA score plot for all adulterated honey samples. 4. Conclusion NIR spectroscopy techniques with Chemometrics used to detect the adulterants of honey with various level of Jaggery solution both in qualitatively and quantitatively. PCA and PLS techniques were used to analyse these spectra and built a calibration model to estimate Jaggery concentration in honey-1 statistically with an accuracy in RMSEP of The developed model can predict the Jaggery concentrations by qualitatively as well as classify the various brands of honey samples. Further these techniques may be used for batch to batch honey quality monitoring in terms of adulteration and quantity estimation of honey contents by correlating with chemical analysis. Now this is a viable option to ensure better quality control in the Indian honey industry. Acknowledgments The authors wish to thank the Director, CSIR-CEERI, Pilani and Scientist In-charge, CSIR-CEERI, Chennai for their encouragement and support to present this paper in the international Conference on Food Properties (icfp ). References 1. M. Kartheek, A. Anton smith, A. Kottai Muthu and R.Manavalan, 2011, Determination of Adulterants in food: A Review, Journal of Chemical and Pharmaceutical Research, 3(2): Sunita Mishra, Uma Kamboj, HarpreetKaur & PawanKapur; 2010, Detection of jaggery syrup in honey using near-infrared Spectroscopy, Central Scientific Instruments Organization, Council of Scientific and Industrial Research, Chandigarh, India, 61(3):

6 3. Laleh mehryar, Mohsen Esmaiili, Honey and Honey Adultration Detection, A Review, Department of food science and Technology, University of Urmia, Iran. 4. Ruiz-Matute A.I., Rodríguez-Sánchez S., Sanz M.L. & Martínez-Castro I, 2010, Detection of adulterations of honey with high fructose syrups from inulin by GC analysis, Journal of Food Composition and Analysis 23, Kelly J.D., Petisco C. & Downey G., 2006, Potential of near infrared transflectance spectroscopy to detect adulteration of Irish honey by beet invert syrup and high fructose corn syrup, Near Infrared Spectroscopy, 14, Gallardo-Velázquez T., Osorio-Revilla G., Zuñiga-de Loa M. & Rivera-Espinoza Y, 2009, Application of FTIRHATR spectroscopy and multivariate analysis to the quantification of adulterants in Mexican honeys, Food Research International, 42,