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논문 기본 정보

자료유형
학술저널
저자정보
Anna Antonella Spina (Department of Health Science Magna Græcia University) Carlotta Ceniti (Department of Health Science Magna Græcia University) Cristian Piras (Department of Health Science Magna Græcia University) Bruno Tilocca (Department of Health Science Magna Græcia University) Domenico Britti (Department of Health Science Magna Græcia University) Valeria Maria Morittu (Department of Health Science Magna Græcia University)
저널정보
한국축산학회(구 한국동물자원과학회) 한국축산학회지 한국축산학회지 제64권 제3호
발행연도
2022.5
수록면
531 - 538 (8page)

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In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo- cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R2 ≥ 0.99 (R2cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R2val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow’s milk at no additional cost.

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