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Research on the Quantitative Determination of Lime in Wheat Flour by Near-Infrared Spectroscopy

文献类型： 外文期刊

作者： Wang Dong 1 ; Ma Zhi-hong 1 ; Pan Li-gang 1 ; Han Ping 1 ; Zhao Liu 1 ; Wang Ji-hua 1 ;

作者机构： 1.Beijing Res Ctr Agrifood Testing & Farmland Monit, Beijing 100097, Peoples R China

2.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

3.China Agr Univ, Coll Food Sci & Nutr Engn, Beijing 100083, Peoples R China

关键词： Near-infrared spectroscopy;Partial least square;Wheat flour;Lime;Calcium carbonoxide

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2013 年 33 卷 1 期

页码：

收录情况： SCI

摘要： The safety of wheat flour is always focused by all quarters of society. Based on comparing the feature of NIR spectra of calcium oxide, calcium hydroxide and calcium carbonate in this research, the diffuse reflection NIR spectra of the wheat flour samples with different content of calcium oxide, calcium hydroxide and calcium carbonate mixed in were collected. The calibration models of lime and calcium carbonate were developed by partial least square algorithm, with the validation method of cross validation. The result indicated that the determination coefficients (R-2) of lime and calcium carbonate are 99.80% and 96.98% respectively, the root mean square errors of calibration set are 0.19 and 0.34 respectively; the root mean square errors of cross Validation set are 0.26 and 0.75 respectively; the root mean square errors of prediction set are 0.63 and 0.44 respectively; the ratio performance deviations (RPD) are 8.57 and 5.24 respectively, which indicated that the calibration models were precise enough to adapt to the on-site rapid determination of lime in wheat flour. The result of F-test indicated that a very remarkable correlation exists between the estimated and specified values of the calibration sets and the external validation sets. This research, to some extent, will provide some reference methods for the rapid determination of wheat flour for quality safety, which is important for the quality control of wheat flour.

  • 相关文献

[1]Research on Detection of Lime in Wheat Flour by NIR Micro-Imaging. Wang, Dong,Wang, Jihua,Wang, Dong,Ma, Zhihong,Han, Ping,Zhao, Liu,Pan, Ligang,Li, Xiaoting,Wang, Jihua,Wang, Dong.

[2]The Application of Classical Least Square Algorithm in the Quantitative Analysis of Lime in Wheat Flour by ATR-MIR Spectroscopy. Wang, Dong,Wang, Jihua,Wang, Dong,Han, Donghai,Wang, Dong,Ma, Zhihong,Pan, Ligang,Zhao, Liu,Han, Ping,Wang, Jihua. 2012

[3]The Application of CLS Algorithm in the Quantitative Analysis of Lime in Wheat Flour by NIR Spectroscopy. Wang, Dong,Ma, Zhihong,Pan, Ligang,Zhao, Liu,Han, Ping,Wang, Jihua. 2012

[4]Research on the Quantitative Determination of Lime in Wheat Flour by Short-Wavelength Near-Infrared Spectroscopy. Wang, Dong,Wang, Jihua,Wang, Dong,Ma, Zhihong,Pan, Ligang,Han, Ping,Zhao, Liu,Wang, Jihua,Wang, Dong,Han, Donghai.

[5]Application research on enhancing near-infrared micro-imaging quality by 2nd derivative. Wang Dong,Ma Zhi-hong,Zhao Liu,Wang Bei-hong,Han Ping,Pan Li-gang,Wang Ji-hua. 2013

[6]Quantitative Analysis of the Content of Deltamethrin in Agrochemicals by Near-Infrared, Attenuated Total Reflectance Infrared and Raman Spectroscopy. Xiong Yan-mei,Tang Guo,Duan Jia,Li Chun-zi,Min Shun-geng,Wang Dong. 2010

[7]Study on the Near Infrared Model Development of Mixed Liquid Samples by the Algorithm of OSC-PLS. Wang, Dong,Ye, Shengfeng,Min, Shungeng,Wang, Dong,Ma, Zhihong. 2011

[8]Comparative Research on Estimating the Severity of Yellow Rust in Winter Wheat. Wang Jing,Jing Yuan-shu,Zhao Juan,Wang Jing,Huang Wen-jiang,Zhang Qing,Wang Li,Zhang Jing-cheng. 2015

[9]Application of Long-Wave Near Infrared Hyperspectral Imaging for Measurement of Soluble Solid Content (SSC) in Pear. Li, Jiangbo,Tian, Xi,Huang, Wenqian,Zhang, Baohua,Fan, Shuxiang,Li, Jiangbo,Tian, Xi,Huang, Wenqian,Zhang, Baohua,Fan, Shuxiang,Li, Jiangbo,Huang, Wenqian,Li, Jiangbo,Huang, Wenqian.

[10]Preliminary Research on the Adaptability of NIR Quantitative Calibration Models for Metal Elements in Soil. Pan Li-gang. 2017

[11]The Characteristic Spectral Selection Method Based on Forward and Backward Interval Partial Least Squares. Qu Fang-fang,Ren Dong,Hou Jin-jian,Zhang Zhong,Wang Ji-hua,Hou Jin-jian,Lu An-xiang,Wang Ji-hua,Xu Hong-lei. 2016

[12]Assessment of Influence Detective Position Variability on Precision of Near Infrared Models for Soluble Solid Content of Watermelon. Qian Man,Fan Shu-xiang,Chen Li-ping,Qian Man,Huang Wen-qian,Wang Qing-yan,Fan Shu-xiang,Zhang Bao-hua,Chen Li-ping,Qian Man,Huang Wen-qian,Wang Qing-yan,Fan Shu-xiang,Zhang Bao-hua,Chen Li-ping,Qian Man,Huang Wen-qian,Wang Qing-yan,Fan Shu-xiang,Zhang Bao-hua,Chen Li-ping. 2016

[13]Simultaneous Determination of Instant Coffee, Plant Fat and Sugar Content in Liquid Coffee Beverage by Diffuse Reflectance Near-Infrared Spectroscopy. Wang Dong,Min Shun-geng,Duan Jia,Xiong Yan-mei,Li Qian-qian,Wang Dong,Wang Dong. 2012

[14]Penetration Depth of Near-Infrared Light in Small, Thin-Skin Watermelon. Qian, Man,Chen, Liping,Fan, Shuxiang,Qian, Man,Wang, Qingyan,Chen, Liping,Huang, Wenqian,Fan, Shuxiang,Zhang, Baohua,Qian, Man,Wang, Qingyan,Chen, Liping,Huang, Wenqian,Fan, Shuxiang,Zhang, Baohua,Qian, Man,Wang, Qingyan,Chen, Liping,Huang, Wenqian,Fan, Shuxiang,Zhang, Baohua,Qian, Man,Wang, Qingyan,Chen, Liping,Huang, Wenqian,Fan, Shuxiang,Zhang, Baohua. 2016

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