Arifah Mitsalina Fildzah, Nisa Khoirun, Windarsih Anjar, Rohman Abdul
Center of Excellence, Institute for Halal Industry and Systems, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
Int J Food Sci. 2022 Feb 22;2022:7643959. doi: 10.1155/2022/7643959. eCollection 2022.
Expensive milk such as horse's milk (HM) may be the target of adulteration by other milk such as goat's milk (GM) and cow's milk (CM). FTIR spectroscopy in combination with chemometrics of linear discriminant analysis (LDA) and multivariate calibrations of partial least square regression (PLSR) and principal component regression (PCR) was used for authentication of HM from GM and CM. Milk was directly subjected to attenuated total reflectance (ATR) spectral measurement at midinfrared regions (4000-650 cm). Results showed that LDA could make clear discrimination between HM and HM adulterated with CM and GM without any misclassification observed. PLSR using 2 derivative spectra at 3200-2800 and 1300-1000 cm provided the best model for the relationship between actual values of GM and FTIR predicted values than PCR. At this condition, values for calibration and validation models obtained were 0.9995 and 0.9612 with RMSEC and RMSEP values of 0.0093 and 0.0794. PLSR using normal FTIR spectra at 3800-3000 and 1500-1000 cm offered for the relationship between actual values of CM and FTIR predicted values of >0.99 in calibration and validation models with low errors of RMSEC of 0.0164 and RMSEP of 0.0336 during authentication of HM from CM. Therefore, FTIR spectroscopy in combination with LDA and PLSR is an effective method for authentication of HM from GM and CM.
昂贵的奶类，如马奶（HM），可能会成为被其他奶类，如羊奶（GM）和牛奶（CM）掺假的目标。傅里叶变换红外光谱（FTIR）结合线性判别分析（LDA）化学计量学以及偏最小二乘回归（PLSR）和主成分回归（PCR）的多变量校准，用于鉴别马奶与羊奶和牛奶。牛奶直接在中红外区域（4000 - 650 cm）进行衰减全反射（ATR）光谱测量。结果表明，LDA能够清晰地区分马奶与掺有牛奶和羊奶的马奶，未观察到任何误判。与PCR相比，使用3200 - 2800和1300 - 1000 cm处的二阶导数光谱的PLSR为羊奶实际值与FTIR预测值之间的关系提供了最佳模型。在此条件下，校准模型和验证模型的R值分别为0.9995和0.9612，RMSEC和RMSEP值分别为0.0093和0.0794。在从牛奶中鉴别马奶的过程中，使用3800 - 3000和1500 - 1000 cm处的常规FTIR光谱的PLSR在校准模型和验证模型中为牛奶实际值与FTIR预测值之间的关系提供的R值>0.99，RMSEC误差较低，为0.0164，RMSEP为0.0336。因此，FTIR光谱结合LDA和PLSR是鉴别马奶与羊奶和牛奶的有效方法。
