Enhancing fusarium head blight detection in wheat crops using hyperspectral indices and machine learning classifiers

Author:

Mustafa GhulamORCID,Zheng Hengbiao,Khan Imran Haider,Zhu Jie,Yang Tao,Wang Aiguo,Xue Bowen,He Can,Jia Haiyan,Li Guoqiang,Cheng Tao,Cao Weixing,Zhu Yan,Yao Xia

Funder

Jiangsu Provincial Agricultural Science and Technology Innovation Fund

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Ministry of Agriculture of the People's Republic of China

National Key Research and Development Program of China

Jiangsu Collaborative Innovation Center for Modern Crop Production

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference57 articles.

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2. Hyperspectral quantification of wheat resistance to Fusarium head blight: Comparison of two Fusarium species;Alisaac;Eur. J. Plant Pathol.,2018

3. Fusarium head blight: Effect of infection timing on spread of fusarium graminearum and spatial distribution of deoxynivalenol within wheat spikes;Alisaac;Microorganisms,2021

4. Spectral-texture approach to hyperspectral image analysis for plant classification with SVMs;AlSuwaidi;IEEE,2017

5. Combining spectral and texture features in hyperspectral image analysis for plant monitoring;AlSuwaidi;Meas. Sci. Technol.,2018

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