Abstract : In order to vertify the feasibility of the near-infrared to detect the veterinary drug in honey, studying the impact of different background correction methods for linear modeling and nonlinear modeling. Use PLSR to establish the linear model between near-infrared spectroscopy and to be measured, and LSSVR to establish the nonlinear model between near-infrared spectroscopy and to be measured. At the same time, we used Wavelet transform, Multiplicative Scatter Correction, Standard Normalized Variate, First derivative transform, Second derivative transform, Orthogonal Signal Correction and other background correction methods to improve the feasibility of the near-infrared detection.
Daoliang Li; Yingyi Chen. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. Springer, IFIP Advances in Information and Communication Technology, AICT-392 (Part I), pp.150-156, 2013, Computer and Computing Technologies in Agriculture VI. 〈10.1007/978-3-642-36124-1_19〉
https://hal.inria.fr/hal-01348093
Contributeur : Hal Ifip
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Soumis le : vendredi 22 juillet 2016 - 13:56:42
Dernière modification le : vendredi 22 juillet 2016 - 14:11:20
Document(s) archivé(s) le : dimanche 23 octobre 2016 - 12:06:41
Hongqian Chen, Zhenhua Tu, Zhaoshen Qing, Xiaobin Qiu, Chaoying Meng. Feasibility Study of Veterinary Drug Residues in Honey by NIR Detection. Daoliang Li; Yingyi Chen. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. Springer, IFIP Advances in Information and Communication Technology, AICT-392 (Part I), pp.150-156, 2013, Computer and Computing Technologies in Agriculture VI. 〈10.1007/978-3-642-36124-1_19〉. 〈hal-01348093〉
