Variety classification and identification of maize seeds based on hyperspectral imaging method  

作　　者：XUE Hang XU Xiping MENG Xiang 

机构地区：[1]College of Optoelectronic Engineering,Changchun University of Science and Technology,Changchun 130022,China [2]College of Electronic and Information Engineering,Beihua University,Jilin 132021,China

出　　处：《Optoelectronics Letters》2025年第4期234-241,共8页光电子快报(英文版)

基　　金：supported by the Science and Technology Development Plan Project of Jilin Provincial Department of Science and Technology (No.20220203112S);the Jilin Provincial Department of Education Science and Technology Research Project (No.JJKH20210039KJ)。

摘　　要：In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.

关 键 词：feature extraction extract feature wavelengthsclassification models variety classification hyperspectral imaging combined preprocessing competitive adaptive reweighted sampling cars successive projections algorithm spa PREPROCESSING maize seeds 

分 类 号：S513[农业科学—作物学]