您好，欢迎访问江苏省农业科学院 机构知识库！
江苏省农业科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Spectral Quantitative Analysis and Research of Fusarium Head Blight Infection Degree in Wheat Canopy Visible Areas

文献类型： 外文期刊

作者： Chen, Yanyu 1 ; Wang, Xiaochan 1 ; Zhang, Xiaolei 1 ; Sun, Ye 2 ; Sun, Haiyan 3 ; Wang, Dezhi 1 ; Xu, Xin 1 ;

作者机构： 1.Nanjing Agr Univ, Coll Engn, Nanjing 210031, Peoples R China

2.Nanjing Tech Univ, Coll Food Sci & Light Ind, Nanjing 210009, Peoples R China

3.Jiangsu Acad Agr Sci, Inst Plant Protect, Nanjing 210014, Peoples R China

关键词： in situ wheat canopy; fusarium head blight; spectrum; infection degree; visible areas

期刊名称：AGRONOMY-BASEL （ 影响因子：3.7； 五年影响因子：4.0 ）

ISSN：

年卷期： 2023 年 13 卷 3 期

页码：

收录情况： SCI

摘要： Obtaining complete and consistent spectral images of wheat ears in the visible areas of in situ wheat canopies poses a significant challenge due to the varying growth posture of wheat. Nevertheless, detecting the presence and degree of wheat Fusarium head blight (FHB) in situ is critical for formulating measures that ensure stable grain production and supply while promoting green development in agriculture. In this study, a spectral quantitative analysis model was developed to evaluate the infection degree of FHB in an in situ wheat canopy's visible areas. To achieve this, a spectral acquisition method was used to evaluate the infection degree of FHB in a wheat canopy's visible areas. Hyperspectral images were utilized to obtain spectral data from healthy and mildly, moderately, and severely infected wheat ear canopies. The spectral data were preprocessed, and characteristic wavelengths were extracted using twelve types of spectral preprocessing methods and four types of characteristic wavelength extraction methods. Subsequently, sixty-five spectral quantitative prediction models for the infection degree of FHB in the in situ wheat canopy visible areas were established using the PLSR method, based on the original spectral data, preprocessed spectral data, original spectral characteristic wavelengths extracted data, and preprocessed spectral characteristic wavelengths extracted data. Comparative analysis of the models indicated that the MMS + CARS + PLSR model exhibited the best prediction effect and could serve as the spectral quantitative analysis model for the evaluation of the infection degree of FHB in an in situ wheat canopy's visible areas. The model extracted thirty-five characteristic wavelengths, with a modeling set coefficient of determination (R-2) of 0.9490 and a root-mean-square error (RMSE) of 0.2384. The testing set of the coefficient of determination (R-2) was 0.9312, with a root-mean-square error (RMSE) of 0.2588. The model can facilitate the spectral quantitative analysis of the infection degree of FHB in the in situ wheat canopy visible areas, thereby aiding in the implementation of China's targeted poverty alleviation and agricultural power strategy.

  • 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：江苏省农业科学院

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