Abstract
The present study was undertaken to develop a protocol for acquisition and analysis of images of ghee samples to derive mathematical parameters related to adulteration of cow ghee with vegetable fat and to develop a model to predict the adulteration levels. The images acquired using a flatbed scanner were quantified in terms of their pixel intensity, colour, morphological, textural and skeleton parameters using ImageJ software. The selected parameters were measured for images of pure cow ghee and compared with that obtained for ghee adulterated with 5%, 10%, 15% and 20% vegetable fat. The parameters were assessed for their ability to detect the fixed adulteration levels on a discrete scale was assessed using discriminant analysis and the adulteration levels of the samples were correctly classified to the extent of 92.2%. An equation for predicting adulteration levels on a continuous scale using regression analysis (adjusted R2 value 0.94) was developed, tested and further validated using a fresh data set including a commercially popular market sample of ghee giving a good fit (R2 value of 0.85).
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References
Brosnan T, Sun DW (2004) Improving quality inspection of food products by computer vision—a review. J Food Eng 61:3–16
Caccamo M, Melilli C, Barbano DM, Portelll G, Marino G, Licitra G (2004a) Measurement of holes and mechanical openness in cheese by image analysis. J Dairy Sci 87:739–748
Caccamo M, Melilli CMBD, Portelli G, Marino G, Licitra G (2004b) Characterization of bread breakdown during mastication by image texture analysis. J Food Eng 113:615–622
Davidson VJ, Ryks J, Chu T (2001) Fuzzy models to predict consumer ratings for biscuits based on digital features. IEEE Trans Fuzzy Syst 9(1):62–67
De S (2010) Outlines of dairy technology. Oxford University Press, New Delhi
Field A (2013) Following up MANOVA with discriminant analysis. In: Discovering statistics using SPSS, 4th edn. Sage Publications Ltd., New Delhi, pp 1889–1907
Gandhi K, Kumar A, Lal D (2015) Iodine value integrated with solvent fractionation technique as tool for detecting palm olein and sheep body fat adulteration in ghee (clarified milk fat). Indian J Dairy Sci 68(4):347–351
Gunasekaran S (1996) Computer vision technology for food quality assurance. Trends Food SciTechnol 7:245–256
Impoco G, Carrato S, CaccamoM Tuminello L, Licitra G (2007) Quantitative analysis of cheese microstructure using SEM imagery. Commun SIMAI Congr. https://doi.org/10.1685/csc06096
Joshi CH, Vyas SH (1976) Studies on buffalo ghee: II various conditions affecting the granulation of ghee. Indian J Dairy Sci 29:13–19
Liang B, Jason LS, Yuping S, Hartel RW, Perepezko JH (2006) Approaches to quantification of microstructure for model lipid systems. J Am Oil ChemSoc 85(5):389–399
Marchal PC, Gila DM, Garcia JG, Ortega GJ (2013) Expert system based on computer vision to estimate the content of impurities in olive oil samples. J Food Engi 119:220–228
Metin S, Hartel RW (2005) Crystallization of fats and oils. In: Shahidi F (ed) Bailey’s industrial oil and fat products. Wiley, London, pp 45–76
Parveen S, Portier KM, Robinson K, Edmiston L, Tamplin M (1999) Discriminate analysis of ribotype profiles of Escherichia coli for differentiating human and nonhuman sources of fecal pollution. Appl Environ Microbiol 65(7):3142–3147
Pathare PB, Opara UL, Al-Said FA (2013) Colour measurement and analysis in fresh and processed foods, a review. Food Bio Technol 6:36–60
Rachana CR, Nath BS (2008) Crystallization of milk fat and its importance in the texture of dairy products-a review. Indian J Dairy Sci 61(6):408–422
Rachana CR, Nath BS, Reshma MV, Armughan C (2013) Variation in grainy texture of commercial ghee in relation to laboratory ghee and its blends. Int J Dairy Technol 66(1):90–97
Ropadi AI, Pavlidi DE, Mohareb F, Panagou EZ, Nychas GJE (2015) Multispectral image analysis approach to detect adulteration of beef and pork in raw meats. Food Res Int 67:12–18
Sano EE, Assad ED, Cunha SAR, Correa TBS, Rodrigues HR (2003) Quantifying adulteration in roast coffee powders by digital image processing. J Food Qual 26:123–134
Serrano S, Villarejo M, Espejo R, Jodral M (2004) Chemical and physical parameters of Andalusian honey: classification of Citrus and Eucalyptus honeys by discriminant analysis. Food Chem 87:619–625
Singh N (2016) FMCGs taste ghee success as Patanjali spreads awareness. https://timesofindia.indiatimes.com/business/india-business/FMCGs-taste-ghee-success-as-Patanjali-spreads-awareness/articleshow/51886560.cms. Accessed 19 April 2016
Snedecor GW, Cochran WG (1994) Statistical methods, 8th edn. Affiliated East-West Press, New Delhi
Wasnik PG, Menon RR, Surendra Nath B, Balasubramanyam BV, Manjunatha M, Sivaram M (2017a) Application of particle analysis and colour parameters for detection of adulteration of cow ghee with vanaspati derived from image analysis. Indian J Dairy Sci 70(2):200–208
Wasnik PG, Menon RR, Surendra Nath B, Balasubramanyam BV, Manjunatha M, Sivaram M (2017b) Application of pixel intensity, fractal dimension and skeleton parameters for detection of adulteration of cow ghee with vanaspati derived from image analysis. Indian J Dairy Sci 70(3):331–337
Wuensch KL (2007) Multivariate data analysis with SPSS. East Carolina University, Greenville, pp 27–42
Yam KL, Papadakis S (2004) A simple digital imaging method for measuring and analyzing colour of food surfaces. J Food Eng 61(1):137–142
Acknowledgements
The work was done at Southern Regional Station, ICAR-National Dairy Research Institute, Bengaluru. The support of Maharashtra Animal and Fishery Sciences University, Nagpur to first author is gratefully acknowledged.
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Wasnik, P.G., Menon, R.R., Sivaram, M. et al. Development of mathematical model for prediction of adulteration levels of cow ghee with vegetable fat using image analysis. J Food Sci Technol 56, 2320–2325 (2019). https://doi.org/10.1007/s13197-019-03677-x
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DOI: https://doi.org/10.1007/s13197-019-03677-x