Rapid spectral analysis of agro-products using an optimal strategy: dynamic backward interval PLS–competitive adaptive reweighted sampling

A novel strategy of variable selection approach named dynamic backward interval partial least squares–competitive adaptive reweighted sampling (DBiPLS-CARS) was proposed in this study. Near-infrared data sets of three different agro-products, namely corn, crop processing lamina, and plant leaf sampl...

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Veröffentlicht in:	Analytical and bioanalytical chemistry Jg. 412; H. 12; S. 2795 - 2804
Hauptverfasser:	Song, Xiangzhong, Du, Guorong, Li, Qianqian, Tang, Guo, Huang, Yue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2020 Springer Springer Nature B.V
Schlagworte:	Adaptive sampling Algorithms Analytical Chemistry Biochemistry Business competition Cereal crops Characterization and Evaluation of Materials Chemistry Chemistry and Materials Science corn crop residues Crops, Agricultural - chemistry data collection Food Science Laboratory Medicine leaves Monitoring/Environmental Analysis Monte Carlo Method Plant Leaves - chemistry prediction processing residues rapid methods Regression analysis Research Paper Sampling Spectral analysis Spectroscopy, Near-Infrared - methods Spectrum analysis Zea mays - chemistry China Monte Carlo uninformative variable elimination (MCUVE) Dynamic backward interval partial least squares (DBiPLS) Competitive adaptive reweighted sampling (CARS) Variable selection Agro-products
ISSN:	1618-2642, 1618-2650, 1618-2650
Online-Zugang:	Volltext
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