Effect of different raw materials on aroma fingerprints of ‘boza’ using an e-nose and sensory analysis

Main Article Content

K. Kemahlıoğlu
P. Kendirci
P. Kadiroğlu
U. Yücel
F. Korel

Keywords

e-nose, boza, cereals, flavour profile analysis, rheology

Abstract

Boza is a Turkish traditional beverage produced by fermentation of maize, rice, wheat, millet, cracked wheat, and durum clear flour. The aim of this study was to determine the effect of different raw material combinations on the aroma fingerprints of boza samples using an electronic nose equipped with surface acoustic wave detector in combination with sensory analysis. According to flavour profile analysis of boza samples, significant differences were obtained among the samples. Hierarchical clustering analysis of e-nose and sensory analyses indicated that boza samples were clustered based on their aroma profiles, odour and taste properties revealing the effect of different cereals as raw materials. Rheological analysis showed that all boza samples exhibited pseudoplastic flow behaviour as the apparent viscosity decreased with increasing shear rate. This revealed that differences in raw materials did not change flow behaviour of boza samples. The results indicated that e-nose could be used as a fast and non-destructive method to assess the influence of raw material formulation on aroma profiles of boza samples in correlation with sensory analysis

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References

Akpinar-Bayizit, A., Yilmaz-Ersan, L. and Ozcan, T., 2010. Determination of boza’s organic acid composition as it is affected by raw material and fermentation. International Journal of Food Properties13: 648-656.
Alpaslan, M. and Hayta, M., 2007. Effect of soymilk substitution on the rheological and sensory properties of salep, a traditional Turkish milk beverage. International Journal of Food Properties10: 413-420.
Altay, F., Karbancioglu-Guler, F., Daskaya-Dikmen, C. and Heperkan, D., 2013. A review on traditional Turkish fermented non-alcoholic beverages: microbiota, fermentation process and quality characteristics. International Journal of Food Microbiology 167: 44-56.
Altug, T. and Elmaci, Y., 2011. G?dalarda duyusal de?erlendirme. Sidas Media, ?zmir, Turkey, 134 pp.
Anonymous, 1992. TS 9778, Boza Standard. Turkish Standards Institution, Ankara, Turkey.
Arici, M., Ersöz Tatlisu, N.B., Toke, Ö.S., Yilmaz, M.T., Cankurt, H., Durak, M.Z. and Sagdic, O., 2014. Microbiological, steady, and dynamic rheological characterization of boza samples: temperature sweep tests and applicability of the Cox-Merz rule. Turkish Journal of Agriculture and Forestry 38: 377-387.
Buratti, S., Ballabio, D., Benedetti, S. and Cosio, M.S., 2007. Prediction of Italian red wine sensorial descriptors from electronic nose, electronic tongue and spectrophotometric measurements by means of Genetic Algorithm regression models. Food Chemistry 100: 211-218.
Chen, Q., Song, J., Bi, J., Meng, X. and Wu, X., 2018. Characterization of volatile profile from ten different varieties of Chinese jujubes by HS-SPME/GC-MS coupled with e-nose. Food Research International 105: 605-615.
Coskun, F. and Cakir, E., 2014. Effect of the addition of different spices on some characteristics of boza during storage. Bulgarian Journal of Agricultural Science 20: 1079-1084.
Fischer, P. and Windham, E.J., 2011. Rheology of food materials. Current Opinion in Colloid & Interface Science 16: 36-40.
Genc, M., Zorba, M. and Ova, G., 2002. Determination of rheological properties of boza by using physical and sensory analysis. Journal of Food Engineering 52: 95-98.
Gotcheva, V., Pandiella, S.S., Angelov, A., Roshkova, Z. and Webb, C., 2001. Monitoring the fermentation of the traditional Bulgarian beverage boza. International Journal of Food Science and Technology 36: 129-134.
Guohua, H., Jiaojiao, J., Deng, S., Xiao, Y., Mengtian, Z., Minmin, W. and Dandan, Y., 2015. Winter jujube (Zizyphus jujuba Mill.) quality forecasting method based on electronic nose. Food Chemistry 170: 484-491.
Hayta, M., Alpaslan, M. and Köse, E., 2001.The effect of fermentation on viscosity and protein solubility of Boza, a traditional cereal-based fermented Turkish beverage. European Food Research and Technology 213: 335-337.
Jian, L., Feixiang, Z., Jinghao, J., Han, L. and Guohua, H., 2015. Chinese bayberry (Myrica rubra Sieb. et Zucc.) quality determination based on an electronic nose and non-linear dynamic model. Analytical Methods 7: 9928-9939.
Jiang, J., Li, J., Zheng, F., Lin, H. and Hui, G., 2016. Rapid freshness analysis of mantis shrimps (Oratosquilla oratoria) by using electronic nose. Journal of Food Measurement and Characterization 10: 48-55.
Kadiroglu, P. and Korel, F., 2015. Chemometric studies on zNose™ and machine vision technologies for discrimination of commercial extra virgin olive oils. Journal of the American Oil Chemists’ Society 92: 1235-1242.
Kadiroglu, P., Korel, F. and Tokatli, F., 2011. Classification of Turkish extra virgin olive oils by a SAW detector electronic nose. Journal of the American Oil Chemists’ Society 88: 639-645.
Korel, F. and Balaban, M.Ö., 2008. Electronic nose technology in food analysis, In: Ötle? S. (eds.) Handbook of food analysis instruments. CRC Press Taylor and Francis Group, Boca Raton, FL, USA, pp. 365-378.
Kose, E. and Yucel, U., 2003. Chemical composition of boza. Journal of Food Technology 1: 191-193.
Lee, W.-H., Choi, S., Oh, I.-N., Shim, J.-Y., Lee, K.-S., An, G. and Park, J.-T., 2017. Multivariate classification of the geographic origin of Chinese cabbage using an electronic nose-mass spectrometry. Food Science and Biotechnology 26: 603-609.
Li, J., Feng, H., Liu, W., Gao, Y. and Hui, G., 2016. Design of a portable electronic nose system and application in k value prediction for large yellow croaker (Pseudosciaena crocea). Food Analytical Methods 9: 2943-2951.
Lihuan, S., Liu, W., Xiaohong, Z., Guohua, H. and Zhidong, Z., 2017. Fabrication of electronic nose system and exploration on its applications in mango fruit (M. indica cv. Datainong) quality rapid determination. Journal of Food Measurement and Characterization 11(4): 1969-1977.
López de Lerma, M.N., Bellincontro, A., García-Martínez, T., Mencarelli, F. and Moreno, J.J., 2013. Feasibility of an electronic nose to differentiate commercial Spanish wines elaborated from the same grape variety. Food Research International 51: 790-796.
Oates, M.J., Fox, P., Sanchez-Rodriguez, L., Carbonell-Barrachina, Á.A. and Ruiz-Canales, A., 2018. DFT based classification of olive oil type using a sinusoidally heated, low cost electronic nose. Computers and Electronics in Agriculture 155: 348-358.
Pacioni, G., Cerretani, L., Procida, G. and Cichelli, A., 2014. Composition of commercial truffle flavored oils with GC-MS analysis and discrimination with an electronic nose. Food Chemistry 146: 30-35.
Peris, M. and Escuder-Gilabert, L., 2016. Electronic noses and tongues to assess food authenticity and adulteration. Trends in Food Science & Technology 58: 40-54.
Qin, Z., Pang, X., Chen, D., Cheng, H., Hu, X. and Wu, J., 2013. Evaluation of Chinese tea by the electronic nose and gas chromatography-mass spectrometry: correlation with sensory properties and classification according to grade level. Food Research International 53: 864-874.
Qiu, S. and Wang, J., 2015. Application of sensory evaluation, HS-SPME GC-MS, e-nose, and e-tongue for quality detection in citrus fruits. Journal of Food Science 80(10): 296-304.
Ren, Y., Ramaswamy, H.S., Li, Y., Yuan, C. and Ren, X., 2018. Classification of impact injury of apples using electronic nose coupled with multivariate statistical analyses. Journal of Food Process Engineering 41(5): e12698. DOI: https://doi.org/10.1111/jfpe.12698
Rodriguez-Mendez, M.L., Apetrei, C., Gay, M., Medina-Plaza, C., De Saja, J.A., Vidal, S., Aagaard, O., Ugliano, M., Wirth, J. and Cheynier, V., 2014. Evaluation of oxygen exposure levels and polyphenolic content of red wines using an electronic panel formed by an electronic nose and an electronic tongue. Food Chemistry 155: 91-97.
Steinkraus, K.H., 1994. Nutritional significance of fermented foods. Food Research International 27: 259-267.
Yang, C.J., Ding, W., Ma, L.J. and Jia, R., 2015. Discrimination and characterization of different intensities of goaty flavour in goat milk by means of an electronic nose. Journal of Dairy Science 98: 55-67.
Ying, X., Liu, W. and Hui, G., 2015. Litchi freshness rapid non-destructive evaluating method using electronic nose and non-linear dynamics stochastic resonance model. Bioengineered 6(4): 218-221.
Zheng, L., Gao, Y., Zhang, J., Li, J., Yu, Y. and Hui, G., 2016. Chinese quince (Cydonia oblonga Miller) freshness rapid determination method using surface acoustic wave resonator combined with electronic nose. International Journal of Food Properties 19: 2623-2634.
Zorba, M., Hancioglu, O., Genc, M., Aslan, A., Ova, G. and Karapinar, M., 1999. The choice of starter culture combination for the boza production by using sensory evaluation and determination of the chemical and rheological properties, In: Toldra, F., Ramon, D. and Navarro, J.L. (eds.) Proceedings of the international congress: improved traditional foods for the next century. October 28-29, 1999. Valencia, Spain, pp. 79-83.
Zorba, M., Hancioglu, O., Genc, M., Karapinar, M. and Ova, G., 2003. The use of starter cultures in the fermentation of boza, a traditional Turkish beverage. Process Biochemistry 38: 1405-1411.