近红外光谱法快速检测婴儿配方奶粉中的脂肪酸含量

采用傅里叶近红外光谱结合偏最小二乘法(PLS)法建立了测定婴儿配方奶粉中的总脂肪酸、饱和脂肪酸和不饱和脂肪酸含量的近红外数学模型,并通过交互验证和外部检验两种方式考察了近红外数学模型的可靠性。通过选择不同的波长范围,采用平滑、矢量归一化、一阶求导、二阶求导和散射校正对近红外光谱进行处理,总脂肪酸、饱和脂肪酸和不饱和脂肪酸的校正模型相关系数(R2)分别为0.9337、0.9374、0.9020,RPD分别为3.63、3.65、2.90。结果表明近红外数学模型具有良好的预测性能。采用建立的模型对验证集中的20个婴儿配方奶粉样品进行预测,总脂肪酸含量、饱和脂肪酸和不饱和脂肪酸的预测值与化学测定值之间经配对t检验分析,与常规化学方法得到的检验结果无显著差异。

Rapid Determination of Total Fatty Acids, Saturated Fatty Acids, and Unsaturated Fatty Acids in Infant Formula using Near-infrared Spectroscopy

A near-infrared mathematical model for the detection of the total fatty acid (TFA), saturated fatty acid (SFA), and unsaturated fatty acid (UFA) contents in infant formula was established using Fourier near-infrared (NIR) spectroscopy combined with partial least squares (PLS) regression prediction. The reliability of the model was verified by cross-validation and external validation. Different wavelengths and different correction algorithms, including smoothing, vector normalization, first derivative, second derivative, and multiple scatter correction (MSC), were used to process the NIR spectra. The correction model correlation coefficients (R2) for TFA, SFA, and UFA contents were 0.9337, 0.9374, and 0.9020, respectively. The coefficient residual predictive deviations (RPDs) were 3.63, 3.65, and 2.90, respectively. These data demonstrated that this NIR mathematical model had good predictive performance. Twenty collected infant formula samples were predicted using the established model. Paired sample t test analysis showed that the chemically measured and predicted values of TFAs, SFAs, and UFAs had no distinct statistical differences.