Near infrared spectroscopy coupled to chemometrics for the authentication of donkey milk

被引:6
|
作者
Di Donato, Francesca [1 ]
Biancolillo, Alessandra [1 ]
Ferretti, Alessandra [2 ]
D'Antonio, Angelo Antonio [1 ]
Marini, Federico [2 ]
机构
[1] Univ Aquila, Dept Phys & Chem Sci, Via Vetoio, I-67100 Laquila, Italy
[2] Univ Roma La Sapienza, Dept Chem, Piazzale Aldo Moro 5, I-00185 Rome, Italy
关键词
Donkey milk; Near Infrared (NIR) spectroscopy; Authentication; Partial LeastSquare-Discriminant Analysis  (PLS-DA); Variable Sorting for Normalization (VSN); ANOVA-Simultaneous Component Analysis  (ASCA); ADULTERATION; REGRESSION; MODELS; ASCA; TOOL;
D O I
10.1016/j.jfca.2022.105017
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Donkey milk (DM) is an emerging foodstuff, gaining increasing attention due to its nutritional properties. As a high value-added product, it can be subjected to adulteration with cheaper milks, e.g., cow milk. The present work addresses the possibility of developing a fast and economic method for the authentication of pure DM using Near Infrared (NIR) Spectroscopy. For this purpose, 147 samples (67 pure DM and 80 mixtures) were analyzed fresh; additionally, all samples underwent successive freezing-thawing cycles. Partial Least Squares-Discriminant Analysis (PLS-DA) was used to differentiate pure and adulterated samples. PLS-DA model built on the fresh milk correctly classified all training and test samples (100% accuracy). When model was applied to the freeze-thawed individuals, it showed high accuracy (79.7% after 3 cycles), suggesting that the spectroscopic signature of adulteration prevails on that of freezing-thawing, though the impact of the latter was proved to be significant by ANOVA-Simultaneous Component Analysis (ASCA).
引用
收藏
页数:8
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