Spectroscopy can be used for detecting crop characteristics.A goal of crop spectrum analysis is to extract effective features from spectral data for establishing a detection model.An ideal spectral feature set should have high sensitivity to target parameters but low information redundancy among features.However,feature-selection methods that satisfy both requirements are lacking.To address this issue,in this study,a novel method,the continuous wavelet projections algorithm(CWPA),was developed,which has advantages of both continuous wavelet analysis(CWA)and the successive projections algo-rithm(SPA)for generating optimal spectral feature set for crop detection.Three datasets collected for crop stress detection and retrieval of biochemical properties were used to validate the CWPA under both classification and regression scenarios.The CWPA generated a feature set with fewer features yet achiev-ing accuracy comparable to or even higher than those of CWA and SPA.With only two to three features identified by CWPA,an overall accuracy of 98％in classifying tea plant stresses was achieved,and high coefficients of determination were obtained in retrieving corn leaf chlorophyll content(R2=0.8521)and equivalent water thickness(R2=0.9508).The mechanism of the CWPA ensures that the novel algo-rithm discovers the most sensitive features while retaining complementarity among features.Its ability to reduce the data dimension suggests its potential for crop monitoring and phenotyping with hyperspec-tral data.

Xiaohu Zhao;Jingcheng Zhang;Ruiliang Pu;Zaifa Shu;Weizhong He;Kaihua Wu

College of Artificial Intelligence,Hangzhou Dianzi University,Hangzhou 310018,Zhejiang,China;School of Geosciences,University of South Florida,Tampa,FL 33620,USA;Lishui Institute of Agriculture and Forestry Sciences,Lishui 323000,Zhejiang,China

作物学报（英文版）

[1]Xiaohu Zhao;Jingcheng Zhang;Ruiliang Pu;Zaifa Shu;Weizhong He;Kaihua Wu-.The continuous wavelet projections algorithm:A practical spectral-feature-mining approach for crop detection)[J].作物学报（英文版）,2022(05):1264-1273

CWPA,discovers,hyperspec

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