Authentication and preference mapping of ham
Keywords:ham, consumer preference, sensory, DNA, animal species
Effective connection between the food industry and consumer demands are specific needs of consumers whitch were monitored in this study by using a preferential mapping method. Preference mapping is based on Principal Component Analysis (PCA), which is performed on preferences ratings given for each product and preferences of each consumer through an online questionnaire. Key features for the consumer choice were colour, odour, consistency, total flavour and overall appearance. We verified the composition and mapped the preferences of 10 hams purchased in Slovakia. In view of the persistence of identified cases of food counterfeiting and meat fraud, intensive monitoring and scrutiny is required through effective and accurate analytical methods, which are crucial for maintaining consumer confidence and ensuring compliance with local legislation and labeling. The reference approach for identifying animal species in food is the PCR method, which is however limited to several animal species, meat types. The use of microarray technology enables the identification of a wider range of animal species and greater user comfort, especially the speed of obtaining the results. It allows 24 animal species to be identified in one analysis in 8 samples at a time. Detection was performed using Chipron LCD Aarray Kit Meat 5.0. In all analyzed samples, components of animal origin were identified in accordance on the packaging of the products. The Meat 5.0 LCD chip, which was used for analysis, has detected the presence of other animal species.
Azuka, I., Ingrid, H., Georg, H., Andreas, M., Ulrich, B. 2011. Biochip technology for the detection of animal species in meat products. Food Analytical Methods, vol. 4, no. 3, p. 389-398. https://doi.org/10.1007/s12161-010-9178-9 DOI: https://doi.org/10.1007/s12161-010-9178-9
Barai, B. K., Nazak, R. R., Singhal, R. S., Kulkarni, P. R. 1992. Approaches to the detection of meat adulteration. Trends in Food Science & Technology, vol. 3, p. 69-72. https://doi.org/10.1016/0924-2244(92)90133-H DOI: https://doi.org/10.1016/0924-2244(92)90133-H
Bertolini, F., Ghionda, M. C., D’Alessandro, D., Geraci, C., Chiofalo, V., Fontanesi, L. 2015. A Next Generation Semiconductor Based Sequencing Approach for the Identification of Meat Species in DNA Mixtures. PLoS One, vol. 10, no. 4, p. e0121701. https://doi.org/10.1371/journal.pone.0121701 DOI: https://doi.org/10.1371/journal.pone.0121701
Bonany, J., Brugger, C., Buehler, A., Carb´o, J., Codarin, S., Donati, F., Schoorl, F. 2014. Preference mapping of apple varieties in Europe. Food Quality and Preference, vol. 32, p. 317-329. https://doi.org/10.1016/j.foodqual.2013.09.010 DOI: https://doi.org/10.1016/j.foodqual.2013.09.010
Bottero, M. T., Dalmasso, A. 2010. Animal species identification in food products: Evolution of biomolecular methods. Veterinary Journal, vol. 190, no. 1, p. 34-38. https://doi.org/10.1016/j.tvjl.2010.09.024 DOI: https://doi.org/10.1016/j.tvjl.2010.09.024
Cadena, R. S., Cruz, A. G., Faria, J. A. F., Bolini, H. M. A. 2012. Reduced fat and sugar vanilla ice creams: Sensory profiling and external preference mapping. J. Diary. Sci., vol. 95, p. 4842-4850. https://doi.org/10.3168/jds.2012-5526 DOI: https://doi.org/10.3168/jds.2012-5526
Carbonell, L., Izquierdo, L., Carbonell, I., Costell, E. 2008. Segmentation of food consumers according to their correlations with sensory attributes projected on preference spaces. Food Quality and Preference, vol. 19, no. 1, p. 71-78. https://doi.org/10.1016/j.foodqual.2007.06.006 DOI: https://doi.org/10.1016/j.foodqual.2007.06.006
Cravero, D. Cerutti, F., Maniaci, M. G., Barzanti, P., Scaramagli, S., Riina, M. V., Ingravalle, F., Acutis, P. L., Peletto, S. 2019. Evaluation of DNA isolation procedures from meat-based foods and development of a DNA quality score. LWT, vol. 106, p. 64-71. https://doi.org/10.1016/j.lwt.2019.02.028 DOI: https://doi.org/10.1016/j.lwt.2019.02.028
Engel, E., Nicklaus, S., Septier, C., Salles, C., Le Quéré, J. L. 2001. Evolution of the taste of a bitter Camembert cheese during ripening: characterization of a matrix effect. J. Agric. Food Chem., vol. 49, no. 6, p. 2930-2939. https://doi.org/10.1021/jf000967m DOI: https://doi.org/10.1021/jf000967m
European Commission. 2013. Recommendation 2013/99/EU on a coordinated control plan with a view to establish the prevalence of fraudulent practices in the marketing of certain foods. Available at : http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32013H0099&qid=1429713190676&from=EN.
Gaze, L. V., Oliveira, B. R., Ferrao, L. L., Granato, D., Cavalcanti, R. N., Conte J´unior, C. A., Freitas, M. Q. 2015. Preference mapping of dulce de leche commercialized in Brazilian markets. Journal of Dairy Science, vol. 98, p. 1443-1454. https://doi.org/10.3168/jds.2014-8470 DOI: https://doi.org/10.3168/jds.2014-8470
Greenhoff, K, MacFie, H. J. H. 1994. Preference Mapping in practice. In MacFie, H. J. H., Thomson, D. M. H. (eds) Measurement of food preferences. Boston, Maryland : Springer, p. 137-166. ISBN 978-1-4613-5908-1. https://doi.org/10.1007/978-1-4615-2171-6_6 DOI: https://doi.org/10.1007/978-1-4615-2171-6_6
Günssen, U., Aydin, A., Ovali, B. Coskun, Y. 2006. Cig et ve ısıl islem görmüs set ürünlerinde ELISA teknigi ile farklı et türlerinin tespiti (Determination of different types of meat by using ELISA technique in cig meat and heat treated set products). Istanbul Üniv Vet Fak Derg., vol. 32, p. 45-52. (in Turkish)
Hsieh, Y. H. P. 2006. Meat species identification. Handbook of Food Science. Technology, and Engineering, vol. 1, p. 6. https://doi.org/10.1201/b15995-33 DOI: https://doi.org/10.1201/b15995-33
İlhak, O. I., Arslan, A. 2007. Identification of Meat Species by Polymerase Chain Reaction (PCR) Technique. Turkish Journal of Veterinary and Animal Sciences, vol. 31, no. 3, p. 159-163. Available at: https://dergipark.org.tr/en/download/article-file/132512
ISO 8589, 2007. Sensory analysis — General guidance for the design of test rooms. International Standard Organisation.
Jolliffe, I. T., Cadima, J. 2016. Principal component analysis: a review and recent developments. In Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, vol. 374, no. 2065, p. 2015-2020. https://doi.org/10.1098/rsta.2015.0202 DOI: https://doi.org/10.1098/rsta.2015.0202
Kostrzynska, M., Bachand, A. 2006. Application of DNA microarray technology for detection, identification, and characterization of food-borne pathogens. Canadian Journal of Microbiology, vol. 52, no. 1, p. 1-8. https://doi.org/10.1139/w05-105 DOI: https://doi.org/10.1139/w05-105
MacFie, H. 2007. Preference mapping and food product development. Consumerled Food Product Development, 2007, p. 551-592. https://doi.org/10.1533/9781845693381.3.551 DOI: https://doi.org/10.1533/9781845693381.3.551
Mansoor, B., Mohamad, J., Heena, Para, Parveez, A. B., Syed, G., Subha B., Asif, W., Rajesh, Q. 2015. Fraudulent Adulteration Substitution of Meat. Journal of Recent Research and Applied Studies, vol. 2, p. 22-33.
Meullenet, J. F., Xiong. R., Findlay, C. 2007. Multivariate and probabilistic analyses of sensory science problems. Ames, IA : IFT Press. Blackwell Publishing, 256 p. ISBN 978-0-813-80178-0.
Miller, M. B., Tang, Y. W. 2009. Basic concepts of mikroarrays and potential applications in clinical microbiology. Clin. Microbiol. Rev., vol. 22, no. 4, p. 611-633. https://doi.org/10.1128/CMR.00019-09 DOI: https://doi.org/10.1128/CMR.00019-09
Montowska, M., Rao, W., Alexander, M. R., Tucker, G. A., Barett, D. A. 2014. Tryptic digestion coupled with ambient desorption electrospray ionization and liquid extraction surface analysis mass spectrometry enabling identification of skeletal muscle proteins in mixtures and distinguishing between beef, pork, horse, chicken, and Turkey meat. Analytical Chemistry, vol. 6, p. 4479-4487. https://doi.org/10.1021/ac5003432 DOI: https://doi.org/10.1021/ac5003432
Myers, M. J., Farrell, D. E., Deaver, C. M., Mason, J., Swaim, H. L., Yancy, H. F. 2010 Detection of rendered meat and bone meals by PCR is dependent on animal species of origin and DNA extraction method. J. Food Prot., vol. 73, no. 6, p. 1090-1096. https://doi.org/10.4315/0362-028x-73.6.1090 DOI: https://doi.org/10.4315/0362-028X-73.6.1090
Oltman, A. E., Yates, M. D., Drake, M. A. 2016. Preference mapping of fresh tomatoes across 3 stages of consumption. Journal of Food Science, vol. 81, p. 1495-1505. https://doi.org/10.1111/1750-3841.13306 DOI: https://doi.org/10.1111/1750-3841.13306
Özpinar, H. Tezmen, G., Gökçe I., Tekiner, I. H. 2013. Detection of Animal Species in Some Meat and Meat Products by Comparatively Using DNA Microarray and Real Time PCR Methods. Kafkas Üniversitesi Veteriner Fakültesi Dergisi, vol. 19, no. 2, p. 245-252. https://doi.org/10.9775/kvfd.2012.7616 DOI: https://doi.org/10.9775/kvfd.2012.7616
Pereira, F., Carneiro, J., Amorim, A. 2008. Identification of species with DNAbased technology: current progress and challenges. Recent Pat. DNA Gene. Seq., vol. 2, no. 3, p. 187-199. https://doi.org/10.2174/187221508786241738 DOI: https://doi.org/10.2174/187221508786241738
Şakalar, E., Abasiyanik, M. F., Bektik, E., Tayyrov, A. 2012. Effect of heat processing on DNA quantification of meat species. Journal of Food Science, vol. 77, no. 9, p. N40-N44. https://doi.org/10.1111/j.1750-3841.2012.02853.x DOI: https://doi.org/10.1111/j.1750-3841.2012.02853.x
Santillo, A., Albenzio, M. 2015. Sensory Profile and Consumers’ Liking of Functional Ovine Cheese. Foods, vol. 4, no. 4, p. 665-677. https://doi.org/10.3390/foods4040665 DOI: https://doi.org/10.3390/foods4040665
Supeková, S. 2008. Kvalita potravín a "značka kvality SK" z pohľadu spotrebiteľa (Food quality and "SK quality label" from the consumer perspective.). Trendy v potravinárstve, vol. 15, no. 2, p. 5-6.
Villamor, R. R., Daniels, C. H., Moore, P. P., Ross, C. F. 2013. Preference mapping of frozen and fresh raspberries. Journal of Food Science, 78, p. 911-919. https://doi.org/10.1111/1750-3841.12125 DOI: https://doi.org/10.1111/1750-3841.12125
Yosef, T. A. 2014. Food Forensics: Using DNA-Based Technology for the Detection of Animal Species in Meat Products. Nature and Science, vol. 12, p. 82-90.
How to Cite
This license permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.