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Prediction of crude protein content in rice grain with canopy spectral reflectance

文献类型: 外文期刊

作者: Zhang, H. 1 ; Song, T. Q. 1 ; Wang, K. L. 1 ; Wang, G. X. 3 ; Hu, H. 4 ; Zeng, F. P. 1 ;

作者机构: 1.Chinese Acad Sci, Inst Subtrop Agr, Key Lab Agroecol Proc Subtrop Reg, Changsha, Hunan, Peoples R China

2.Chinese Acad Sci, Huanjiang Observat & Res Stn Karst Ecosyst, Huanjiang, Peoples R China

3.Zhejiang Univ, Inst Agr Ecol Res, Coll Life Sci, Hangzhou 310003, Zhejiang, Peoples R China

4.Zhejiang Acad Agr Sci, Key Lab Digital Agr, Inst Digital Agr Res, Hangzhou, Zhejiang, Peoples R China

关键词: biofortification;forage;antioxidant enzymes;root anatomy;Brachiaria brizantha

期刊名称:PLANT SOIL AND ENVIRONMENT ( 影响因子:1.799; 五年影响因子:2.169 )

ISSN:

年卷期:

页码:

收录情况: SCI

摘要: Non-destructive and rapid monitoring methods for crude protein content (CPC) in rice grain are of significance in nitrogen diagnosis and grain quality monitoring, and in enhancing nutritional management and use efficiency. In this study, CPC and canopy spectra in rice were measured based on rice field experiment. Key spectral bands were selected by principal component analysis (PCA) method, and the predicted models were built by multiple linear regressions (MLR), artificial neural network (ANN) and partial least squares regression (PLSR). The results showed that there is a significant correlation between CPC content and key spectral bands. The results of prediction for the three models were in order of PLSR > ANN > MLR with correlation values of 0.96, 0.92 and 0.90, respectively, for the validation data. Therefore, it is implied that CPC in rice (grain quality) could be estimated by canopy spectral data.

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