College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil (Wuhan Polytechnic University), Ministry of Education, College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Hubei Key Laboratory for Processing and Transformation of Agricultural Products (Wuhan Polytechnic University), College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China.
College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2021 Feb 5;246:118973. doi: 10.1016/j.saa.2020.118973. Epub 2020 Sep 23.
Geographical discrimination and adulteration analysis play significant roles in edible oil analysis. A novel method for discrimination and adulteration analysis of edible oils were proposed in this study. The two-dimensional correlation spectra of edible oils were obtained by solvents perturbation and the convolutional neural networks (CNNs) were constructed to analyze the synchronous and asynchronous correlation spectra of the edible oils. The differences for geographical origins of oils or oil types could be amplificated through the networks. For different networks, the layer sequences and the filter number of convolutional layers may affect the analysis results. A group of sesame oils from different geographical origins and a group of olive oils adulterated by other vegetable oils were adopted to evaluate the proposed method. The results show that the proposed method may provide an alternative method for edible oil discrimination and adulteration analysis in practical applications. For the two datasets, the prediction accuracy could be 97.3% and 88.5%, respectively.
地理歧视和掺假分析在食用油分析中起着重要作用。本研究提出了一种用于鉴别和分析食用油掺假的新方法。通过溶剂扰动获得食用油的二维相关光谱，构建卷积神经网络（CNNs）来分析食用油的同步和异步相关光谱。通过网络可以放大油或油类型的地理来源差异。对于不同的网络，卷积层的层序列和滤波器数量可能会影响分析结果。采用来自不同地理来源的一组芝麻油和一组用其他植物油掺假的橄榄油来评估所提出的方法。结果表明，该方法可为实际应用中的食用油鉴别和掺假分析提供一种替代方法。对于这两个数据集，预测准确率分别可达 97.3%和 88.5%。
