Fast Verification of Buffalo’s Milk Authenticity by Mid-Infrared Spectroscopy, Analytical Measurements and Multivariate Calibration

Mid-infrared spectroscopy (MID), chemical composition and physicochemical characteristics associated with chemometrics were used to rapidly detect and quantify the amount of cow’s milk added in buffalo’s milk. A total of 165 samples, divided into buffalo’s milk, buffalo’s milk added with cow’s milk (10 to 90%) and cow’s milk were evaluated to obtain fat, protein, lactose, total and defatted solids, urea, pH, acidity, cryoscopic index and band absorbances in the spectra associated with principal component analysis (PCA), multiple linear regression (MLR) and partial least squares regression (PLS). The treatments were separated into groups by PCA, allowing the classification of samples. MLR and PLS models were able to predict cow’s milk contents in buffalo’s milk. MID and results of the analytical measures studied when associated with chemometrics are efficient in the rapid quantitative detection of adulteration in buffalo’s milk.

本研究借助结合化学计量学（chemometrics）的中红外光谱（Mid-infrared spectroscopy, MID）技术、化学成分与理化特性指标，实现水牛乳中掺加牛乳含量的快速检测与定量分析。共计制备165份样品，分为纯水牛乳、掺加10%~90%牛乳的水牛乳以及纯牛乳三个组别。对所有样品的脂肪、蛋白质、乳糖、总固形物与脱脂固形物、尿素含量、pH值、酸度、冰点指数以及光谱波段吸光度进行测定，并结合主成分分析（principal component analysis, PCA）、多元线性回归（multiple linear regression, MLR）与偏最小二乘回归（partial least squares regression, PLS）开展数据分析。主成分分析可将不同处理组的样品进行聚类分离，实现样品的有效分类。多元线性回归与偏最小二乘回归模型均可精准预测水牛乳中牛乳的掺加含量。综上，结合化学计量学的中红外光谱技术与本研究所采用的分析检测结果，可高效实现水牛乳掺假行为的快速定量检测。