Abstract: To address the increasingly severe issue of water adulteration in the non-bovine milks market, this study proposed a rapid, non-destructive method for identifying multiple types of adulterated non-bovine milks based on portable nearinfrared spectroscopy combined with convolutional neural networks (CNN). Spectral data were collected for four types of non-bovine milks, camel, horse, donkey, and yak milks, as well as samples of these milks diluted with water at varying concentrations (2%–80%, V/V). We compared the effects of standard normal variate transformation (SNV) and Savitzky- Golay filter smoothing preprocessing on the performance of partial least squares discriminant analysis (PLS-DA) and CNN models. The results showed that non-bovine milks exhibited significant characteristic absorption of moisture at 6 882 and 10 200 cm–1. The CNN model with SNV preprocessing achieved the best performance, with a classification accuracy of 98.71% on the test set, and its precision and recall were superior to those of traditional PLS-DA model. This model not only accurately distinguished between milks from different species but also exhibited high sensitivity in detecting water adulteration as low as 2%. The present study demonstrates that the discrimination system based on a portable near-infrared spectrometer and CNN can effectively reduce matrix interference in minor species milks.

Key words: near-infrared spectroscopy; non-bovine milks; water adulteration identification; convolutional neural network

摘要： 针对特种乳市场日益严重的掺水欺诈问题，本研究提出一种基于便携式近红外光谱结合卷积神经网络 （convolutional neural network，CNN）的多种类特种乳掺假快速、无损鉴别方法。采集驼乳、马乳、驴乳及牦牛乳 4 种典型特种乳及其梯度掺水（2%～80%，V/V）样本的光谱数据，对比研究标准正态变量变换（standard normal variate transformation，SNV）、Savitzky-Golay滤波平滑（Savitzky-Golay filter smoothing，SG）预处理对偏最小 二乘判别分析（partial least squares discriminant analysis，PLS-DA）与CNN模型性能的影响。结果表明，特种乳在 6 882 cm－1及10 200 cm－1波段的水分特征吸收显著。经SNV预处理的CNN模型表现最优，其在测试集上的分类准确 率达98.71%，精确率与召回率均优于传统PLS-DA模型。该模型能精准区分物种来源，对低至2%的掺水比例表现出 良好识别潜力。研究表明，基于便携式近红外光谱仪与CNN深度学习算法构建的鉴别体系能够有效降低特种乳物 种间的基质干扰。

关键词: 近红外光谱；特种乳；掺水鉴别；卷积神经网络