Research on maize component measurement of wavelength selection based on SiPLS and SPA

doi:10.13382/j.jemi.2017.12.012

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Research on maize component measurement of wavelength selection based on SiPLS and SPA
DOI:
                        10.13382/j.jemi.2017.12.012
                    
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Author:
                        Jiang Weiwei1Jiang Weiwei
School of Computer and Information, Hefei University of Technology, Hefei 230009, China
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Lu ChanghuaLu Changhua
1. School of Computer and Information, Hefei University of Technology, Hefei 230009, China; 2. Anhui Institute of Optics Fine Mechanics, Chinese Academy of Sciences, Hefei 230031,China
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Zhang Yujun2Zhang Yujun
Anhui Institute of Optics Fine Mechanics, Chinese Academy of Sciences, Hefei 230031,China
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Wang JizhouWang Jizhou
1. School of Computer and Information, Hefei University of Technology, Hefei 230009, China; 3. Hefei University, Hefei 230061, China
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Ju Wei1Ju Wei
School of Computer and Information, Hefei University of Technology, Hefei 230009, China
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Xiao Mingxia1Xiao Mingxia
School of Computer and Information, Hefei University of Technology, Hefei 230009, China
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Affiliation:1. School of Computer and Information, Hefei University of Technology, Hefei 230009, China; 2. Anhui Institute of Optics Fine Mechanics, Chinese Academy of Sciences, Hefei 230031,China; 3. Hefei University, Hefei 230061, China
Clc Number:O657.3； TN911.7
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Abstract:

After pretreatment of 80 samples of maize, interval partial least square (iPLS), combination of interval partial least squares (SiPLS) and successive projections algorithm (SPA) is respectively used to optimize the best wavelength of moisture components, and the correction model is established. The results show that iPLS, SiPLS and SPA method reduces the modeling variables from 700 to 70, 140 and 2, respectively, which occupies 10%, 20% and 0.29% of the whole spectrum. And, the modeling accuracy is even better than that of the 700 full spectral variables. The modeling accuracy of SiPLS and SPA is matched. But the SPA method reduces variables from 700 to 2. The complexity is minimized, and the precision of the model is kept, which show that the SPA method is an effective feature extraction method of wavelength. This research method can be extended to the application of fat, protein and starch components detection of corn.

Key words:interval partial least squares; combined interval partial least squares; continuous projection algorithm; quantitative analysis

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Online: January 24,2018
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