Summary
Soybean Glycine max (L.) Merr. is an economically important crop that is grown worldwide. Sudden death syndrome (SDS), caused by Fusarium virguliforme, is one of the top yield‐limiting ...diseases in soybean. However, the genetic basis of SDS resistance, especially with respect to epistatic interactions, is still unclear. To better understand the genetic architecture of soybean SDS resistance, genome‐wide association and epistasis studies were performed using a population of 214 germplasm accessions and 31 914 SNPs from the SoySNP50K Illumina Infinium BeadChip. Twelve loci and 12 SNP–SNP interactions associated with SDS resistance were identified at various time points after inoculation. These additive and epistatic loci together explained 24–52% of the phenotypic variance. Disease‐resistant, pathogenesis‐related and chitin‐ and wound‐responsive genes were identified in the proximity of peak SNPs, including stress‐induced receptor‐like kinase gene 1 (SIK1), which is pinpointed by a trait‐associated SNP and encodes a leucine‐rich repeat‐containing protein. We report that the proportion of phenotypic variance explained by identified loci may be considerably improved by taking epistatic effects into account. This study shows the necessity of considering epistatic effects in soybean SDS resistance breeding using marker‐assisted and genomic selection approaches. Based on our findings, we propose a model for soybean root defense against the SDS pathogen. Our results facilitate identification of the molecular mechanism underlying SDS resistance in soybean, and provide a genetic basis for improvement of soybean SDS resistance through breeding strategies based on additive and epistatic effects.
Significance Statement
We report 12 additive effect loci and 12 epistatic interactions associated with resistance to sudden death syndrome in soybean; and pinpoint a trait‐associated single nucleotide polymorphism in SIK1, encoding a leucine‐rich receptor kinase.
In field trials in Iowa, we investigated the association of a fungicide applied at early pod set to the diversity and composition of foliar endophytic fungi in presenescent soybeans. The main purpose ...of our study was to determine whether fungicides affect the microbiome of soybean plants during the pod-fill reproductive stage. In a replicated experiment focused on the impact of a fungicide application including a quinone outside inhibitor (QoI) and a pyrazole-carboxamide spanning two growing seasons, healthy stems and leaves near the tops of soybean were sampled for endophytic fungi. The survey yielded 1,791 isolates belonging to 17 putative species, identified by morphology and sequence analysis of the ribosomal DNA internal transcribed spacer region. Taxa were grouped by genus into operational taxonomic units:
,
, and
were the dominant genera isolated. Plant parts were analyzed separately using a multivariate community analysis of isolate counts per plant. The 14.3% fluxapyroxad and 28.6% pyraclostrobin fungicide spray significantly increased the proportion of
isolates over no-spray controls, whereas the inverse occurred for foliar
isolates. In addition, seed harvested from fields with shorter-season varieties and sprayed with fungicide showed higher percentages of
isolates than fields with no fungicide spray. In conclusion, soybean farmers may want to consider that the application of a QoI fungicide in the absence of disease pressure might adversely impact seed quality.
Foliar fungicide applications to corn (Zea mays L.) occur at one or more application timings ranging from early vegetative growth stages to mid-reproductive stages. Previous studies indicated that ...fungicide applications are profitable under high disease pressure when applied during the tasseling to silking growth stages. Few comprehensive studies in corn have examined the impact of fungicide applications at an early vegetative growth stage (V6) compared to late application timings (VT) for yield response and return on fungicide investment (ROI) across multiple locations.
Compare yield response of fungicide application timing across multiple fungicide classes and calculate the probability of positive ROI.
Data were collected specifically for this analysis using a uniform protocol conducted in 13 states in the United States and one province in Canada from 2014-2015. Data were subjected to a primary mixed-model analysis of variance. Subsequent univariate meta-analyses, with and without moderator variables, were performed using standard meta-analytic procedures. Follow-up power and prediction analyses were performed to aid interpretation and development of management recommendations.
Fungicide application resulted in a range of yield responses from -2,683.0 to 3,230.9 kg/ha relative to the non-treated control, with 68.2% of these responses being positive. Evidence suggests that all three moderator variables tested (application timing, fungicide class, and disease base level), had some effect (α = 0.05) on the absolute difference in yield between fungicide treated and non-treated plots (Formula: see text). Application timing influenced Formula: see text, with V6 + VT and the VT application timings resulting in greater yield responses than the V6 application timing alone. Fungicide formulations that combined demethylation inhibitor and quinone outside inhibitor fungicides significantly increased yield response.
Foliar fungicide applications can increase corn grain yield. To ensure the likelihood of a positive ROI, farmers should focus on applications at VT and use fungicides that include a mix of demethylation inhibitor and quinone outside inhibitor active ingredients.
Neonicotinoids are the most widely used insecticides worldwide and are typically deployed as seed treatments (hereafter NST) in many grain and oilseed crops, including soybeans. However, there is a ...surprising dearth of information regarding NST effectiveness in increasing soybean seed yield, and most published data suggest weak, or inconsistent yield benefit. The US is the key soybean-producing nation worldwide and this work includes soybean yield data from 194 randomized and replicated field studies conducted specifically to evaluate the effect of NSTs on soybean seed yield at sites within 14 states from 2006 through 2017. Here we show that across the principal soybean-growing region of the country, there are negligible and management-specific yield benefits attributed to NSTs. Across the entire region, the maximum observed yield benefits due to fungicide (FST = fungicide seed treatment) + neonicotinoid use (FST + NST) reached 0.13 Mg/ha. Across the entire region, combinations of management practices affected the effectiveness of FST + NST to increase yield but benefits were minimal ranging between 0.01 to 0.22 Mg/ha. Despite widespread use, this practice appears to have little benefit for most of soybean producers; across the entire region, a partial economic analysis further showed inconsistent evidence of a break-even cost of FST or FST + NST. These results demonstrate that the current widespread prophylactic use of NST in the key soybean-producing areas of the US should be re-evaluated by producers and regulators alike.
Genome-wide association (GWAS) and epistatic (GWES) studies along with expression studies in soybean Glycine max (L.) Merr. were leveraged to dissect the genetics of Sclerotinia stem rot (SSR) caused ...by Sclerotinia sclerotiorum (Lib.) de Bary, a significant fungal disease causing yield and quality losses. A large association panel of 466 diverse plant introduction accessions were phenotyped in multiple field and controlled environments to: (1) discover sources of resistance, (2) identify SNPs associated with resistance, and (3) determine putative candidate genes to elucidate the mode of resistance. We report 58 significant main effect loci and 24 significant epistatic interactions associated with SSR resistance, with candidate genes involved in a wide range of processes including cell wall structure, hormone signaling, and sugar allocation related to plant immunity, revealing the complex nature of SSR resistance. Putative candidate genes for example, PHYTOALEXIN DEFFICIENT 4 (PAD4), ETHYLENE-INSENSITIVE 3-LIKE 1 (EIL3), and ETHYLENE RESPONSE FACTOR 1 (ERF1) clustered into salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) pathways suggest the involvement of a complex hormonal network typically activated by both necrotrophic (ET/JA) and biotrophic (SA) pathogens supporting that S. sclerotiorum is a hemibiotrophic plant pathogen.
Crop yield prediction which provides critical information for management decision-making is of significant importance in precision agriculture. Traditional manual inspection and calculation are often ...laborious and time-consuming. For yield prediction using high-resolution images, existing methods, e.g., convolutional neural network, are challenging to model long range multi-level dependencies across image regions. This paper proposes a transformer-based approach for yield prediction using early-stage images and seed information. First, each original image is segmented into plant and soil categories. Two vision transformer (ViT) modules are designed to extract features from each category. Then a transformer module is established to deal with the time-series features. Finally, the image features and seed features are combined to estimate the yield. A case study has been conducted using a dataset that was collected during the 2020 soybean-growing seasons in Canadian fields. Compared with other baseline models, the proposed method can reduce the prediction error by more than 40%. The impact of seed information on predictions is studied both between models and within a single model. The results show that the influence of seed information varies among different plots but it is particularly important for the prediction of low yields.
Charcoal rot (CR) disease caused by
is responsible for significant yield losses in soybean production. Among the methods available for controlling this disease, breeding for resistance is the most ...promising. Progress in breeding efforts has been slow due to the insufficient information available on the genetic mechanisms related to resistance. Genome-wide association studies (GWAS) enable unraveling the genetic architecture of resistance and identification of causal genes. The aims of this study were to identify new sources of resistance to CR in a collection of 459 diverse plant introductions from the USDA Soybean Germplasm Core Collection using field and greenhouse screenings, and to conduct GWAS to identify candidate genes and associated molecular markers. New sources for CR resistance were identified from both field and greenhouse screening from maturity groups I, II, and III. Five significant single nucleotide polymorphism (SNP) and putative candidate genes related to abiotic and biotic stress responses are reported from the field screening; while greenhouse screening revealed eight loci associated with eight candidate gene families, all associated with functions controlling plant defense response. No overlap of markers or genes was observed between field and greenhouse screenings suggesting a complex molecular mechanism underlying resistance to CR in soybean with varied response to different environments; but our findings provide useful information for advancing breeding for CR resistance as well as the genetic mechanism of resistance.
Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease ...resistant cultivars. Genome-wide association studies (GWAS) involve phenotyping large numbers of accessions, and have been used for a myriad of traits. In field studies, genetic accessions are phenotyped across multiple environments and replications, which takes a significant amount of labor and resources. Deep Learning (DL) techniques can be effective for analyzing image-based tasks; thus DL methods are becoming more routine for phenotyping traits to save time and effort. This research aims to conduct GWAS on sudden death syndrome (SDS) of soybean
Glycine max
L. (Merr.) using disease severity from both visual field ratings and DL-based (using images) severity ratings collected from 473 accessions. Images were processed through a DL framework that identified soybean leaflets with SDS symptoms, and then quantified the disease severity on those leaflets into a few classes with mean Average Precision of 0.34 on unseen test data. Both visual field ratings and image-based ratings identified significant single nucleotide polymorphism (SNP) markers associated with disease resistance. These significant SNP markers are either in the proximity of previously reported candidate genes for SDS or near potentially novel candidate genes. Four previously reported SDS QTL were identified that contained a significant SNPs, from this study, from both a visual field rating and an image-based rating. The results of this study provide an exciting avenue of using DL to capture complex phenotypic traits from images to get comparable or more insightful results compared to subjective visual field phenotyping of traits for disease symptoms.
The purpose of our study was to determine whether the application of quinone outside inhibitor (QoI) and pyrazole-carboxamide fungicides as a tank mix would impact the endophyte community of soybean ...seed. Field trials during 2018 in Iowa, South Dakota, and Wisconsin, U.S.A., investigated the impact of a single combination fungicide spray at early pod set in soybeans. The composition of culturable endophytic fungi in mature soybean seed was assessed on three cultivars per state, with maturity groups (MGs) ranging from 1.1 to 4.7. An unusually wet 2018 season delayed harvest, which led to a high level of fungal growth in grain. The survey included 1,080 asymptomatic seeds that were disinfested and individually placed on 5-cm-diameter Petri plates of acidified water agar. The survey yielded 721 fungal isolates belonging to 24 putative species in seven genera; taxa were grouped into genera based on a combination of morphological and molecular evidence. The dominant genera encountered in the survey were
,
, and
. The study showed that the fungicide treatment reduced the incidence of
in Wisconsin seed, increased the incidence of
in seed from all states, and had no impact on the incidence of
. This is one of the first attempts to characterize the diversity of seed endophytes in soybean and the first to characterize the impacts of fungicide spraying on these endophyte communities across three states. Our study provides evidence that the impact of a fungicide spray on soybean seed endophyte communities may be influenced by site, weather, and cultivar maturity group.
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