Rapid and non-destructive decay detection of Yali pears using hyperspectral imaging coupled with 2D correlation spectroscopy  

作　　者：Yufan Zhang Wenxiu Wang Fan Zhang Qianyun Ma Shuang Gao Jie Wang Jianfeng Sun Yuanyuan Liu 

机构地区：[1]College of Food Science and Technology,Hebei Agricultural University,Baoding 071000,Hebei,China [2]Agricultural Engineering Key Laboratory at Universities of Education Department of

出　　处：《International Journal of Agricultural and Biological Engineering》2022年第5期236-244,共9页国际农业与生物工程学报（英文）

基　　金：financially supported by Hebei Province Key Research and Development Project(Grant No.20327111D);Basic Scientific Research Funds of Hebei Provincial Universities(Grant No.KY202002);Key Laboratory of Modern Agricultural Engineering,Tarim University(Grant No.TDNG2020102);the National Natural Science Foundation of China(Grant No.31960498).

摘　　要：The black spot disease caused by Alternaria alternata on Yali pears is a great concern as it compromises their edible quality and commercial value.To realize rapid and non-destructive classification of this disease,hyperspectral imaging(HSI)technology was combined with two-dimensional correlation spectroscopy(2DCOS)analysis.A total of 150 pear samples at different decay grades were prepared.After obtaining the HSI images,the whole sample was demarcated as the region of interest,and the spectral information was extracted.Seven preprocessing methods were applied and compared to build the classification models.Thereafter,using the inoculation day as an external perturbation,2DCOS was used to select the feature-related wavebands for black spot disease identification,and the result was compared to those obtained using competitive adaptive reweighting sampling and the successive projections algorithm.Results demonstrated that the simplified least squares support vector model based on 2DCOS-identified feature wavebands yielded the best performance with the identification accuracy,precision,sensitivity,and specificity of 97.30%,94.60%,96.16%,and 98.21%,respectively.Therefore,2DCOS can effectively interpret the feature-related wavebands,and its combination with HSI is an effective tool to predict black spot disease on Yali pears.

关 键 词：hyperspectral imaging technology black spot disease two-dimensional correlation spectroscopy Yali pear 

分 类 号：S436.6[农业科学—农业昆虫与害虫防治]