Abstract
Abstract
Background
Frogeye leaf spot is a disease of soybean, and there are limited sources of crop genetic resistance. Accurate quantification of resistance is necessary for the discovery of novel resistance sources, which can be accelerated by using a low-cost and easy-to-use image analysis system to phenotype the disease. The objective herein was to develop an automated image analysis phenotyping pipeline to measure and count frogeye leaf spot lesions on soybean leaves with high precision and resolution while ensuring data integrity.
Results
The image analysis program developed measures two traits: the percent of diseased leaf area and the number of lesions on a leaf. Percent of diseased leaf area is calculated by dividing the number of diseased pixels by the total number of leaf pixels, which are segmented through a series of color space transformations and pixel value thresholding. Lesion number is determined by counting the number of objects remaining in the image when the lesions are segmented. Automated measurement of the percent of diseased leaf area deviates from the manually measured value by less than 0.05% on average. Automatic lesion counting deviates by an average of 1.6 lesions from the manually counted value. The proposed method is highly correlated with a conventional method using a 1–5 ordinal scale based on a standard area diagram. Input image compression was optimal at a resolution of 1500 × 1000 pixels. At this resolution, the image analysis method proposed can process an image in less than 10 s and is highly concordant with uncompressed images.
Conclusion
Image analysis provides improved resolution over conventional methods of frogeye leaf spot disease phenotyping. This method can improve the precision and resolution of phenotyping frogeye leaf spot, which can be used in genetic mapping to identify QTLs for crop genetic resistance and in breeding efforts for resistance to the disease.
Funder
University of Georgia Research Foundation
Georgia Agricultural Commodity Commission for Soybeans
Georgia Seed Development
Publisher
Springer Science and Business Media LLC
Subject
Plant Science,Genetics,Biotechnology
Reference31 articles.
1. Mian MAR, Boerma HR, Weaver DB. Performance of frogeye leaf spot-resistant and-susceptible near-isolines of soybean. Plant Dis. 1998;82:1017–21.
2. Athow KL, Probst AH. The inheritance of resistance to frog-eye leaf spot on Soybeans. Phytopathology. 1952;42:660–2.
3. Allen TW, Bradley CA, Sisson AJ, Byamukama E, Chilvers MI, Coker CM, et al. Soybean yield loss estimates due to diseases in the United States and Ontario, Canada, from 2010 to 2014. Plant Health Prog. 2017. https://doi.org/10.1094/PHP-RS-16-0066.
4. Mian MAR, Missaoui AM, Walker DR, Phillips DV, Boerma HR. Frogeye leaf spot of soybean: a review and proposed race designations for isolates of Cercospora sojina Hara. Crop Sci. 2008. https://doi.org/10.2135/cropsci2007.08.0432.
5. Wise KA, Newman ME. Frogeye leaf spot. In: Hartman GL, Rupe JC, Sikora EJ, Domier LL, Davis JA, Steffey KL, editors. Compendium of soybean diseases. 5th ed. St. Paul: The American Phytopathological Society; 2015. p. 43–5.
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