Application of Visible/Near-Infrared Spectroscopy in the Prediction of Azodicarbonamide in Wheat Flour
文献类型: 外文期刊
作者: Che, Wenkai 1 ; Sun, Laijun 1 ; Zhang, Qian 1 ; Zhang, Dan 1 ; Ye, Dandan 1 ; Tan, Wenyi 1 ; Wang, Lekai 2 ; Dai, Changju 1 ;
作者机构: 1.Heilongjiang Univ, Key Lab Elect Engn, Coll Heilongjiang Prov, Harbin 150080, Heilongjiang, Peoples R China
2.Heilongjiang Acad Agr Sci, Qual & Safety Inst Agr Prod, Harbin, Heilongjiang, Peoples R China
关键词: azodicarbonamide;flour;near-infrared reflectance spectroscopy;noninvasive detection;prediction model
期刊名称:JOURNAL OF FOOD SCIENCE ( 影响因子:3.167; 五年影响因子:3.376 )
ISSN: 0022-1147
年卷期: 2017 年 82 卷 10 期
页码:
收录情况: SCI
摘要: Azodicarbonamide is wildly used in flour industry as a flour gluten fortifier in many countries, but it was proved by some researches to be dangerous or unhealthy for people and not suitable to be added in flour. Applying a rapid, convenient, and noninvasive technique in food analytical procedure for the safety inspection has become an urgent need. This paper used Vis/NIR reflectance spectroscopy analysis technology, which is based on the physical property analysis to predict the concentration of azodicarbonamide in flour. Spectral data in range from 400 to 2498nm were obtained by scanning 101 samples which were prepared using the stepwise dilution method. Furthermore, the combination of leave-one-out cross-validation and Mahalanobis distance method was used to eliminate abnormal spectral data, and correlation coefficient method was used to choose characteristic wavebands. Partial least squares, back propagation neural network, and radial basis function were used to establish prediction model separately. By comparing the prediction results between 3 models, the radial basis function model has the best prediction results whose correlation coefficients (R), root mean square error of prediction (RMSEP), and ratio of performance to deviation (RPD) reached 0.99996, 0.5467, and 116.5858, respectively.
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