A novel method based on lesion expansion to assess plant disease severity
IntroductionSeverity is a key indicator utilized in plant disease monitoring and pathogen-plant interaction phenotyping.MethodsA plant disease severity assessment method based on lesion expansion was proposed in this study to more accurately and quickly assess the severity of plant diseases for whic...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2025.1510663/full |
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| _version_ | 1850231169547763712 |
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| author | Feng Qin Haiguang Wang Qian Jiang Hongli Wang |
| author_facet | Feng Qin Haiguang Wang Qian Jiang Hongli Wang |
| author_sort | Feng Qin |
| collection | DOAJ |
| description | IntroductionSeverity is a key indicator utilized in plant disease monitoring and pathogen-plant interaction phenotyping.MethodsA plant disease severity assessment method based on lesion expansion was proposed in this study to more accurately and quickly assess the severity of plant diseases for which the lesion area ratio of an investigated plant unit at each severity class in the corresponding severity grading standard is not the actual ratio of the lesion area to the area of the whole investigated plant unit. By taking wheat stripe rust caused by Puccinia striiformis f. sp. tritici as an example, after image segmentation operations of single diseased wheat leaves with wheat stripe rust, lesion expansion processing was carried out using nine method combinations of three proposed lesion expansion methods and three proposed lesion expansion coefficient determination methods, and then the severity assessments of single diseased wheat leaves were conducted.ResultsThe results showed that the accuracy of severity assessments of single diseased wheat leaves in each severity class was in the range of 78.00% to 100.00%. No matter which method was used to determine the lesion expansion coefficient/coefficients, the performance of the severity assessments of the single diseased leaves achieved after lesion expansion using lesion expansion method 3 (the lesion expansion method based on an image scaling algorithm) outperformed that achieved after lesion expansion using the other two lesion expansion methods. The performance of the method combination of lesion expansion method 3 and lesion expansion coefficient determination method 1 with a lesion expansion coefficient of 2.74, achieving an accuracy of 96.16% for severity assessments of all the single diseased wheat leaves, was the optimal method among the nine method combinations.DiscussionThe results demonstrated that satisfactory severity assessment results could be achieved using the proposed method based on lesion expansion. The results indicated that the lesion-expansion-based plant disease severity assessment method is feasible, and can be used to solve the severity assessment problem described above. This study provided a new idea and method for accurate severity assessment of plant diseases and provided support for the automatic and intelligent assessment of plant disease severity. |
| format | Article |
| id | doaj-art-ce449f5aeb34415b93258cf494c6f708 |
| institution | OA Journals |
| issn | 1664-462X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj-art-ce449f5aeb34415b93258cf494c6f7082025-08-20T02:03:38ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2025-02-011610.3389/fpls.2025.15106631510663A novel method based on lesion expansion to assess plant disease severityFeng QinHaiguang WangQian JiangHongli WangIntroductionSeverity is a key indicator utilized in plant disease monitoring and pathogen-plant interaction phenotyping.MethodsA plant disease severity assessment method based on lesion expansion was proposed in this study to more accurately and quickly assess the severity of plant diseases for which the lesion area ratio of an investigated plant unit at each severity class in the corresponding severity grading standard is not the actual ratio of the lesion area to the area of the whole investigated plant unit. By taking wheat stripe rust caused by Puccinia striiformis f. sp. tritici as an example, after image segmentation operations of single diseased wheat leaves with wheat stripe rust, lesion expansion processing was carried out using nine method combinations of three proposed lesion expansion methods and three proposed lesion expansion coefficient determination methods, and then the severity assessments of single diseased wheat leaves were conducted.ResultsThe results showed that the accuracy of severity assessments of single diseased wheat leaves in each severity class was in the range of 78.00% to 100.00%. No matter which method was used to determine the lesion expansion coefficient/coefficients, the performance of the severity assessments of the single diseased leaves achieved after lesion expansion using lesion expansion method 3 (the lesion expansion method based on an image scaling algorithm) outperformed that achieved after lesion expansion using the other two lesion expansion methods. The performance of the method combination of lesion expansion method 3 and lesion expansion coefficient determination method 1 with a lesion expansion coefficient of 2.74, achieving an accuracy of 96.16% for severity assessments of all the single diseased wheat leaves, was the optimal method among the nine method combinations.DiscussionThe results demonstrated that satisfactory severity assessment results could be achieved using the proposed method based on lesion expansion. The results indicated that the lesion-expansion-based plant disease severity assessment method is feasible, and can be used to solve the severity assessment problem described above. This study provided a new idea and method for accurate severity assessment of plant diseases and provided support for the automatic and intelligent assessment of plant disease severity.https://www.frontiersin.org/articles/10.3389/fpls.2025.1510663/fullplant diseaseseveritydisease assessmentimage processinglesion expansionexpansion coefficient |
| spellingShingle | Feng Qin Haiguang Wang Qian Jiang Hongli Wang A novel method based on lesion expansion to assess plant disease severity Frontiers in Plant Science plant disease severity disease assessment image processing lesion expansion expansion coefficient |
| title | A novel method based on lesion expansion to assess plant disease severity |
| title_full | A novel method based on lesion expansion to assess plant disease severity |
| title_fullStr | A novel method based on lesion expansion to assess plant disease severity |
| title_full_unstemmed | A novel method based on lesion expansion to assess plant disease severity |
| title_short | A novel method based on lesion expansion to assess plant disease severity |
| title_sort | novel method based on lesion expansion to assess plant disease severity |
| topic | plant disease severity disease assessment image processing lesion expansion expansion coefficient |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2025.1510663/full |
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