Identification of Adulterated Milk Based on Two-Dimensional Correlation Near-Infrared Spectra Parameterization and BP Neural Network
MIAO Jing1, CAO Yu-zhen1*, YANG Ren-jie2, 3, LIU Rong2, SUN Hui-li4, XU Ke-xin2
1. College of Precision Instrument and Opto-electronics Engineering，Tianjin University，Tianjin 300072，China 2. State Key Laboratory of Precision Measuring Technology and Instruments，Tianjin University，Tianjin 300072，China 3. Department of Electromechanical Engineering，Tianjin Agricultural University，Tianjin 300384，China 4. Tianjin Medical Devices Quality Supervision and Testing Center，Tianjin 300191，China
Abstract：Discriminant models of adulterated milk and pure milk were established using BP neural network combined with two-dimensional (2D) correlation near-infrared spectra parameterization. Forty pure milk samples，40 adulterated milk samples with urea (1～20 g·L-1) and 40 adulterated milk samples with melamine (0.01～3 g·L-1) were prepared respectively. Based on the characteristics of 2D correlation near-infrared spectra of pure milk and adulterated milk，5 apparent statistic parameters were calculated based on the parameterization theory. Using 5 characteristic parameters，discriminant models of urea adulterated milk，melamine adulterated milk and two types of adulterated milk were built by BP neural network. The prediction rate of unknown samples were 95%，100% and 96.7%，respectively. The results show that this method can extract effectively feature information of adulterant，reduce the input dimensions of BP neural network，and better realize qualitative analysis of adulterant in milk.
苗 静1，曹玉珍1*，杨仁杰2, 3，刘 蓉2，孙惠丽4，徐可欣2 . 基于二维相关近红外谱参数化及BP神经网络的掺杂牛奶鉴别 [J]. 光谱学与光谱分析, 2013, 33(11): 3032-3035.
MIAO Jing1, CAO Yu-zhen1*, YANG Ren-jie2, 3, LIU Rong2, SUN Hui-li4, XU Ke-xin2 . Identification of Adulterated Milk Based on Two-Dimensional Correlation Near-Infrared Spectra Parameterization and BP Neural Network . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(11): 3032-3035.
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