Aphanomyces root rot (ARR) is a devastating disease in field pea (Pisum sativum L.) that can cause up to 100% crop failure. Assessment of ARR resistance can be a rigorous, costly, time-demanding activity that is relatively low-throughput and prone to human errors. These limits the ability to effectively and efficiently phenotype the disease symptoms arising from ARR infection, which remains a perennial bottleneck to the successful evaluation and incorporation of disease resistance into new cultivars. In this study, we developed a greenhouse-based high throughput phenotyping (HTP) platform that moves along the rails above the greenhouse benches and captures the visual symptoms caused by Aphanomyces euteiches in field pea. We pilot tested this platform alongside with conventional visual scoring in five experimental trials under greenhouse conditions, assaying over 12,600 single plants. Precision estimated through broad-sense heritability (H2) was consistently higher for the HTP-indices (H2 Exg =0.86) than the traditional visual scores (H2 DSI=0.59), potentially increasing the power of genetic mapping. We genetically dissected variation for ARR resistance using the HTP-indices, and identified a total of 260 associated single nucleotide polymorphism (SNP) through genome-wide association (GWA) mapping. The number of associated SNP for HTP-indices was consistently higher with some SNP overlapped to the associated SNP identified using the visual scores. We identified numerous small-effect QTLs, with the most significant SNP explaining about 5 to 9% of the phenotypic variance per index, and identified previously mapped genes known to be involved in the biological pathways that trigger immunity against ARR, including Psat5g280480, Psat5g282800, Psat5g282880, and Psat2g167800. We also identified a few novel QTLs with small-effect sizes that may be worthy of validation in the future. The newly identified QTLs and underlying genes, along with genotypes with promising resistance identified in this study, can be useful for improving a long-term, durable resistance to ARR. Keywords: High-throughput phenotyping, Genome-wide association mapping, Aphanomyces root rot, Aphanomyces euteiches, Field pea
Aphanomyces root rot (ARR) is a devastating disease in field pea (Pisum sativum L.) that can cause up to 100% crop failure. Assessment of ARR resistance can be a rigorous, costly, time‐demanding activity that is relatively low‐throughput and prone to human errors. These limits the ability to effectively and efficiently phenotype the disease symptoms arising from ARR infection which remains a perennial bottleneck to the successful evaluation and incorporation of disease resistance into new cultivars. In this study, we developed a greenhouse‐based high‐throughput phenotyping (HTP) platform that moves along the rails above the greenhouse benches and captures the visual symptoms caused by Aphanomyces euteiches in field pea. We pilot tested this platform alongside with conventional visual scoring in five experimental trials under greenhouse conditions, assaying over 12,600 single plants of advanced breeding lines developed by the North Dakota State University Pulse Breeding Program. Precision estimated through broad‐sense heritability (H2) was consistently higher for RGB‐derived indices (H2, Exg = 0.86) than the conventional visual scores (H2, disease severity index = 0.59). Prediction of disease severity using a random forest modeling of RGB‐derived indices achieved 0.69 accuracy on the test sets, with inaccurate classification partly attributed to the presence of tolerant lines (displaying root rot but no foliar symptoms) and within‐line genetic heterogeneity. We genetically dissected variation for ARR resistance from the population using RGB‐derived indices and visual scores through genome‐wide association mapping and identified a total of 260 associated single nucleotide polymorphism (SNP). The number of associated SNP for RGB‐derived indices was consistently higher than the number of associated SNP identified using visual scores, with the most significant SNP explaining about 5%–9% of variance per index. We identified previously mapped genes known to be involved in the biological pathways that trigger immunity against ARR and a few novel QTLs with small‐effect sizes that may be worthy of validation in the future. The newly identified QTLs and underlying genes, along with genotypes with promising resistance identified in this study, can be useful for improving a long‐term and durable resistance to ARR.
In the semi-arid regions of North Dakota and Montana, low annual precipitation favors production of high-quality durum wheat (Triticum turgidum L. ssp. durum). However, conducive weather conditions for disease epidemics have occurred more frequently in recent years. Modification of planting date can reduce disease risk by decreasing the timeframe a susceptible crop overlaps with conducive disease conditions. The effect of planting date on fungal leaf spotting diseases (leaf spot), ergot, Fusarium head blight (FHB), and yield of durum was evaluated in eleven experiments across four sites in eastern Montana and western North Dakota. Six durum cultivars with differing levels of susceptibility to leaf spot and FHB were planted at three planting dates from 2017 to 2019. Early planting maximized yield and influenced ergot incidence. While there was no effect of planting date, reduced susceptibility to leaf spot and FHB was associated with a reduction in leaf spotting disease severity and deoxynivalenol (DON) respectively in the harvested grain. Growers in the semi-arid regions of these states should prioritize the selection of disease resistant cultivars to help manage sporadic disease outbreaks and continue to plant early to maximize yield.
Worldwide, Ascochyta blight is caused by a complex of host-specific fungal pathogens, including Ascochyta pisi, Didymella pinodes, and Didymella pinodella. The application of foliar fungicides is often necessary for disease management, but a better understanding of pathogen prevalence, aggressiveness, and fungicide sensitivity is needed to optimize control. Leaf and stem samples were obtained from 56 field pea production fields in 14 counties in North Dakota from 2017 to 2020 and isolates were collected from lesions characteristic of Ascochyta blight. Based on fungal characteristics and sequencing the ITS1-5.8S-ITS2 region, 73% of isolates were confirmed to be D. pinodes (n = 177) and 27% were A. pisi (n = 65). Across pathogens, aggressiveness was similar among some isolates in greenhouse assays. The in vitro pyraclostrobin sensitivity of all D. pinodes isolates collected from 2017 to 2020 was lower than that of the three baseline isolates. Sensitivity of 91% of A. pisi isolates collected in 2019 and 2020 was lower than the sensitivity of two known sensitive isolates. Resistance factors (Rf) from mean EC50 values of pyraclostrobin baseline/known sensitive isolates to isolates collected from 2017 to 2020 ranged from 2 to 1,429 for D. pinodes and 1 to 209 for A. pisi. In vitro prothioconazole sensitivity of 91% of D. pinodes isolates collected from 2017 to 2020 was lower than the sensitivity of the baseline isolates and 98% of A. pisi isolates collected from 2019 to 2020 was lower than the sensitivity of the known sensitive isolates. Prothioconazole Rf ranged from 1 to 338 for D. pinodes and 1 to 127 for A. pisi. Based on in vitro results, 92% of D. pinodes and 98% of A. pisi isolates collected displayed reduced-sensitivity/resistance to both fungicides when compared to baseline/known sensitive isolates. Disease control under greenhouse conditions of both pathogens provided by both fungicides was significantly lower in isolates determined to be reduced-sensitive or resistant in in vitro assays when compared to sensitive. Results reported here reinforce growers desperate need of alternative fungicides and/or management tools to fight Ascochyta blight in North Dakota and neighboring regions.
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