Application of Non-Destructive Technology in Plant Disease Detection: Review

Yanping Wang, Jun Sun (), Zhaoqi Wu, Yilin Jia and Chunxia Dai
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Yanping Wang: School of Electrical and Information Engineering, Jiangsu University, Zheniiang 212013, China
Jun Sun: School of Electrical and Information Engineering, Jiangsu University, Zheniiang 212013, China
Zhaoqi Wu: School of Electrical and Information Engineering, Jiangsu University, Zheniiang 212013, China
Yilin Jia: School of Electrical and Information Engineering, Jiangsu University, Zheniiang 212013, China
Chunxia Dai: School of Electrical and Information Engineering, Jiangsu University, Zheniiang 212013, China

Agriculture, 2025, vol. 15, issue 15, 1-27

Abstract: In recent years, research on plant disease detection has combined artificial intelligence, hyperspectral imaging, unmanned aerial vehicle remote sensing, and other technologies, promoting the transformation of pest and disease control in smart agriculture towards digitalization and artificial intelligence. This review systematically elaborates on the research status of non-destructive detection techniques used for plant disease identification and detection, mainly introducing the following two types of methods: spectral technology and imaging technology. It also elaborates, in detail, on the principles and application examples of each technology and summarizes the advantages and disadvantages of these technologies. This review clearly indicates that non-destructive detection techniques can achieve plant disease and pest detection quickly, accurately, and without damage. In the future, integrating multiple non-destructive detection technologies, developing portable detection devices, and combining more efficient data processing methods will become the core development directions of this field.

Keywords: plant disease detection; non-destructive detection; spectrum technology; imaging technology (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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