Search Results (4)

Soybean is a high oil and protein-rich legume with several production constraints. Globally, several fungi, viruses, nematodes, and bacteria cause significant yield losses in soybean. Coniothyrium glycines (CG), the causal pathogen for red leaf blotch disease, is the least researched and causes severe damage to soybean. The identification of resistant soybean genotypes and mapping of genomic regions associated with resistance to CG is critical for developing improved cultivars for sustainable soybean production. This study used single nucleotide polymorphism (SNP) markers generated from a Diversity Arrays Technology (DArT) platform to conduct a genome-wide association (GWAS) analysis of resistance to CG using 279 soybean genotypes grown in three environments. A total of 6395 SNPs was used to perform the GWAS applying a multilocus model Fixed and random model Circulating Probability Unification (FarmCPU) with correction of the population structure and a statistical test p-value threshold of 5%. A total of 19 significant marker–trait associations for resistance to CG were identified on chromosomes 1, 5, 6, 9, 10, 12, 13, 15, 16, 17, 19, and 20. Approximately 113 putative genes associated with significant markers for resistance to red leaf blotch disease were identified across soybean genome. Positional candidate genes associated with significant SNP loci-encoding proteins involved in plant defense responses and that could be associated with soybean defenses against CG infection were identified. The results of this study provide valuable insight for further dissection of the genetic architecture of resistance to CG in soybean. They also highlight SNP variants and genes useful for genomics-informed selection decisions in the breeding process for improving resistance traits in soybean. Full article

Red leaf blotch (RLB) of almond, caused by Polystigma amygdalinum, is an important foliar disease of this nut tree in the Mediterranean basin and especially in Spain. In recent years, the control of this disease has become a key factor in the management of Spanish almond orchards. The management of RLB is not easy due to intrinsic factors of the disease (e.g., long infection and latency periods) and the low number of registered fungicides in this country. From 2015 to 2019, different field trials were conducted in the Lleida region, NE Spain, to evaluate the efficacy of several fungicide products and of application strategies to control this disease. Systemic fungicides, which included fluopyram, trifloxystrobin, and mixtures of fluopyram + trifloxystrobin and pyraclostrobin + boscalid, performed better than contact and penetrant products and showed up to 90% control against RLB. However, the efficacy of the tested fungicides varied depending on the year. In terms of application strategies, when fungicide applications were conducted following specific meteorological conditions (after 15 days from >15 mm rainfalls with ≈10–15 °C as the minimum average temperature), their efficacy was comparable to that of calendar-based treatments (every 14, 21, or 31 days from petal fall) but with fewer applications (depending on the year, 2–4 applications as compared with 5–9 for calendar treatments). Full article

Red leaf blotch is one of the major fungal foliar diseases affecting almond orchards. High-resolution thermal and hyperspectral airborne imagery was acquired from two flights and compared with concurrent field visual evaluations for disease incidence and severity. Canopy temperature and vegetation indices were calculated from thermal and hyperspectral imagery and analyzed for their ability to detect the disease at early stages. The classification methods linear discriminant analysis and support vector machine, using linear and radial basis kernels, were applied to a combination of these vegetation indices in order to quantify and discriminate between red leaf blotch severity levels. Chlorophyll and carotenoid indices and chlorophyll fluorescence were effective in detecting red leaf blotch at the early stages of disease development. Linear models showed higher power to separate between asymptomatic trees and those affected by advanced stages of disease development while the non-linear model was better in discriminating asymptomatic plants from those at early stages of red leaf blotch development. Leaf-level measurements of stomatal conductance, chlorophyll content, chlorophyll fluorescence, photochemical reflectance index, and spectral reflectance showed no significant differences between healthy leaves and the green areas of symptomatic leaves. This study demonstrated the feasibility of early detecting and quantifying red leaf blotch using high-resolution hyperspectral imagery. Full article