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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.

Key message Eight soybean genomic regions, including six never before reported, were found to be associated with resistance to soybean rust (Phakopsora pachyrhizi) in the southeastern USA. Abstract Soybean rust caused by Phakopsora pachyrhizi is one of the most important foliar diseases of soybean [Glycine max (L.) Merr.]. Although seven Rpp resistance gene loci have been reported, extensive pathotype variation in and among fungal populations increases the importance of identifying additional genes and loci associated with rust resistance. One hundred and ninety-one soybean plant introductions from Japan, Indonesia and Vietnam, and 65 plant introductions from other countries were screened for resistance to P. pachyrhizi under field conditions in the southeastern USA between 2008 and 2015. The results indicated that 84, 69, and 49% of the accessions from southern Japan, Vietnam or central Indonesia, respectively, had negative BLUP values, indicating less disease than the panel mean. A genome-wide association analysis using SoySNP50K Infinium BeadChip data identified eight genomic regions on seven chromosomes associated with SBR resistance, including previously unreported regions of Chromosomes 1, 4, 6, 9, 13, and 15, in addition to the locations of the Rpp3 and Rpp6 loci. The six unreported genomic regions might contain novel Rpp loci. The identification of additional sources of rust resistance and associated genomic regions will further efforts to develop soybean cultivars with broad and durable resistance to soybean rust in the southern USA.

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Soybean accounts for over a quarter of the world's oilseed consumption and over 70% of the world's protein meal consumption. The separate development of high oleic, low linolenic acid (HOLL) soybean and high‐protein (HP) soybean means that no soybean cultivar on the market has an optimal fatty acid profile and increased protein. The objective of this study was to develop and evaluate high protein, high oleic acid, and low linolenic acid (HP‐HOLL) soybean. A five‐gene stack was created using a two‐phase forward breeding scheme and marker‐assisted selection method. Forty‐six HP‐HOLL lines from three genetic backgrounds were grown in six environments in the Southeast United States. Although genotype‐by‐environment interaction was significant for seed composition traits, lines met the >75% and <3% cutoffs for oleic acid and linolenic acid, respectively, and met or exceeded the protein concentration of the HP parent. No negative interaction could be detected between the HP and HOLL traits. Additionally, yield testing in four environments indicated yield parity for some lines, suggesting HP and HOLL soybean cultivars with high yield could be selected.