您好，欢迎访问安徽省农业科学院 机构知识库！

Integration of spectroscopy and image for identifying fusarium damage in wheat kernels

文献类型： 外文期刊

作者： Zhang, Dongyan 1 ; Chen, Gao 1 ; Zhang, Huihui 2 ; Jin, Ning 1 ; Gu, Chunyan 4 ; Weng, Shizhuang 1 ; Wang, Qian 1 ; Chen, 1 ;

作者机构： 1.Anhui Univ, Natl Engn Res Ctr Agroecol Big Data Anal & Applic, Hefei 230601, Peoples R China

2.USDA ARS, Water Management & Syst Res Unit, Ft Collins, CO 80526 USA

3.Shanxi Inst Energy, Dept Resources & Environm, Jinzhong 030600, Peoples R China

4.Anhui Acad Agr Sci, Inst Plant Protect & Agroprod Safety, Hefei 230031, Peoples R China

关键词： Hyperspectral imaging; Spectral and image features; Classification model; Wheat kernel; Fusarium head blight

期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：4.098； 五年影响因子：3.464 ）

ISSN： 1386-1425

年卷期： 2020 年 236 卷

页码：

收录情况： SCI

摘要： Hyperspectral imaging (HSI) was studied for the detection of varying degrees of damage in wheat kernels caused by Fusarium head blight (Gibberella zeae), a major disease in wheat worldwide. A total of 810 wheat kernel samples were collected from a field trial with the three levels of Fusarium infection, healthy, moderate, and severe. Hyperspectral image of the wheat kernels was acquired over a wavelength range of 400-1000 nm. The raw spectral data were pre-processed, and then the optimal wavelengths were selected using principal component analysis (PCA), successive projection algorithm (SPA) and random forest (RF). The image features were extracted based on the optimal wavelengths, and then the spectral features and image features were combined as fusion features. Support vector machine (SVM), random forest (RF) and naive Bayes (NB) were employed to build the classification models to identify the degrees of Fuasrium damage based on spectral and fusion features. The best performance was obtained by using the SPA-RF method to select the optimal wavelengths and corresponding image features, with a classification accuracy of 96.44%. The method developed from this study can provide a more effective way to identify the degrees of Fusarium damage in wheat kernels. (C) 2020 Elsevier B.V. All rights reserved.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：安徽省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台