Management of Soybean Cyst Nematode and Sudden Death Syndrome with Nematode-Protectant Seed Treatments Across Multiple Environments in Soybean.

As soybean (Glycine max) production continues to expand in the United States and Canada, so do pathogens and pests that directly threaten soybean yield potential and economic returns for farmers. One such pathogen is the soybean cyst nematode (SCN; Heterodera glycines). SCN has traditionally been managed using SCN-resistant cultivars and rotation with nonhost crops, but the interaction of SCN with sudden death syndrome (SDS; caused by Fusarium virguliforme) in the field makes management more difficult. Nematode-protectant seed treatments have become options for SCN and SDS management. The objectives of this study were to evaluate nematode-protectant seed treatments for their effects on (i) early and full season SCN reproduction, (ii) foliar symptoms and root-rot caused by SDS, and (iii) soybean yield across environments accounting for the above factors. Using a standard protocol, field trials were implemented in 13 states and one Canadian province from 2019 to 2021 constituting 51 site-years. Six nematode-protectant seed treatment products were compared with a fungicide + insecticide base treatment and a nontreated check. Initial (at soybean planting) and final (at soybean harvest) SCN egg populations were enumerated, and SCN females were extracted from roots and counted at 30 to 35 days postplanting. Foliar disease index (FDX) and root rot caused by the SDS pathogen were evaluated, and yield data were collected for each plot. No seed treatment offered significant nematode control versus the nontreated check for in-season and full-season nematode response, no matter the initial SCN population or FDX level. Of all treatments, ILEVO (fluopyram) and Saltro (pydiflumetofen) provided more consistent increases in yield over the nontreated check in a broader range of SCN environments, even when FDX level was high.

Impact of Foliar Fungicide Application on the Culturable Fungal Endophyte Community of Soybean Seed in the Midwest United States.

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 Alternaria, Diaporthe, and Fusarium. The study showed that the fungicide treatment reduced the incidence of Fusarium in Wisconsin seed, increased the incidence of Diaporthe in seed from all states, and had no impact on the incidence of Alternaria. 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.

Influence of Integrated Management Strategies on Soybean Sudden Death Syndrome (SDS) Root Infection, Foliar Symptoms, Yield and Net Returns.

Three soybean field trials were conducted in Indiana to evaluate the integration of seed treatment, cultivar selection, and seeding rate on sudden death syndrome (SDS) root rot, pathogen load in the root, foliar symptoms, yield, and net return. Two soybean cultivars, one moderately resistant and one susceptible to SDS, were planted at three seeding rates (272,277 seeds/ha, 346,535 seeds/ha, and 420,792 seeds/ha). Fluopyram and pydiflumetofen seed treatments were applied to both cultivars, and the cultivars were then compared with a control. Low foliar SDS disease pressure was observed in our study. Seed treatment with either fluopyram or pydiflumetofen and the use of a moderately resistant cultivar decreased Fusarium virguliforme DNA concentration in the root relative to the control and the use of a susceptible cultivar. Fluopyram significantly reduced visual root rot severity by 8.8% and increased yield by 105 kg/ha relative to the control but was not different from pydiflumetofen. However, pydiflumetofen performed the same as the control with respect to root rot severity and yield. Findings from this study support the use of a seed treatment to protect roots from infection and the use of a moderately resistant cultivar planted at a seeding rate of 346,535 seeds/ha to protect yield and maximize net returns when a field has low foliar SDS pressure.

A transformer-based approach for early prediction of soybean yield using time-series images.

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.

Efficacy and Profitability of Fungicides for Managing Frogeye Leaf Spot on Soybean in the United States: A 10-Year Quantitative Summary.

Frogeye leaf spot (FLS), caused by Cercospora sojina, is an economically important disease of soybean in the United States. Data from 66 uniform fungicide trials (UFTs) conducted from 2012 to 2021 across eight states (Alabama, Arkansas, Illinois, Iowa, Kentucky, Louisiana, Mississippi, and Tennessee) were gathered and analyzed to determine the efficacy and profitability of the following fungicides applied at the beginning pod developmental stage (R3): azoxystrobin + difenoconazole (AZOX + DIFE), difenoconazole + pydiflumetofen (DIFE + PYDI), pyraclostrobin (PYRA), pyraclostrobin + fluxapyroxad + propiconazole (PYRA + FLUX + PROP), tetraconazole (TTRA), thiophanate-methyl (TMET), thiophanate-methyl + tebuconazole (TMET + TEBU), and trifloxystrobin + prothioconazole (TFLX + PROT). A network meta-analytic model was fitted to the log of the means of FLS severity data and to the nontransformed mean yield for each treatment, including the nontreated. The percent reduction in disease severity (%) and the yield response (kg/ha) relative to the nontreated was the lowest for PYRA (11%; 136 kg/ha) and the greatest for DIFE + PYDI (57%; 441 kg/ha). A significant decline in efficacy over time was detected for PYRA (18 percentage points [p.p.]), TTRA (27 p.p.), AZOX + DIFE (18 p.p.), and TMET + TEBU (19 p.p.) by using year as a continuous covariate in the model. Finally, probabilities of breaking even were the greatest (>65%) for the most effective fungicide DIFE + PYDI and the lowest (<55%) for PYRA. Results of this meta-analysis may be useful to support decisions when planning fungicide programs.

Meta-Analytic Modeling of the Severity-Yield Relationships in Soybean Frogeye Leaf Spot Epidemics.

Frogeye leaf spot (FLS), caused by Cercospora sojina, is an important foliar disease affecting soybean in the United States. A meta-analytic approach including 39 fungicide trials conducted from 2012 to 2021 across eight states (Alabama, Arkansas, Illinois, Iowa, Kentucky, Louisiana, Mississippi, Tennessee) was used to assess the relationship between FLS severity and soybean yield. Correlation and regression analyses were performed separately to determine Fisher's transformation of correlation coefficients (Zr), intercept (ß0) and slope (ß1). Disease pressure (low severity, ≤34.5; high severity, >34.5%) and yield class (low, ≤3,352; high, >3,352 kg/ha) were included as categorical moderators. Pearson's [Formula: see text], obtained from back-transforming the [Formula: see text]r estimated by an overall random-effects model, showed a significant negative linear relationship between FLS severity and yield ([Formula: see text] = -0.60). The [Formula: see text]r was affected by disease pressure (P = 0.0003) but not by yield class (P = 0.8141). A random-coefficient model estimated a slope of -19 kg/ha for each percent severity for a mean attainable yield of 3,719.9 kg/ha. Based on the overall mean (95% CI) of the intercept and slope estimated by the random-coefficients model, the estimated overall relative damage coefficient was 0.51% (0.36 to 0.69), indicating that a percent increase in FLS severity reduced yield by 0.51%. The best model included yield class as a covariate, and population-average intercepts differed significantly between low (3,455.1 kg/ha) and high (3,842.7 kg/ha) yield classes. This highlights the potential impact of FLS on soybean yield if not managed and may help in disease management decisions.

Fungicide Sensitivity of Sclerotinia sclerotiorum from U.S. Soybean and Dry Bean, Compared to Different Regions and Climates.

Fungicide use is integral to reduce yield loss from Sclerotinia sclerotiorum on dry bean and soybean. Increasing fungicide use against this fungus may lead to resistance to the most common fungicides. Resistance has been reported in Brazil (Glycine max) and China (Brassica napus subsp. napus), however, few studies have investigated fungicide sensitivity of S. sclerotiorum in the United States. This work was conducted to determine if there was a difference in fungicide sensitivity of S. sclerotiorum isolates in the United States from: (i) dry bean versus soybean and (ii) fields with different frequencies of fungicide application. We further hypothesized that isolates with fungicide applications of a single active ingredient from tropical Brazil and subtropical Mexico were less sensitive than temperate U.S. isolates due to different management practices and climates. The EC50(D) fungicide sensitivity of 512 S. sclerotiorum isolates from the United States (443), Brazil (36), and Mexico (33) was determined using a discriminatory concentration (DC) previously identified for tetraconazole (2.0 ppm; EC50(D) range of 0.197 to 2.27 ppm), boscalid (0.2; 0.042 to 0.222), picoxystrobin (0.01; 0.006 to 0.027), and thiophanate-methyl, which had a qualitative DC of 10 ppm. Among the 10 least sensitive isolates to boscalid and picoxystrobin, 2 presented mutations known to confer resistance in the SdhB (qualitative) and SdhC (quantitative) genes; however, no strong resistance was found. This study established novel DCs that can be used for further resistance monitoring and baseline sensitivity of S. sclerotiorum to tetraconazole worldwide plus baseline sensitivity to boscalid in the United States.

Field and Greenhouse Assessment of Seed Treatment Fungicides for Management of Sudden Death Syndrome and Yield Response of Soybean.

Seed treatments for the management of sudden death syndrome (SDS) caused by Fusarium virguliforme are available in the United States and Canada; however, side-by-side comparisons of these seed treatments are lacking. Sixteen field experiments were established in Illinois, Indiana, Iowa, Michigan, and Wisconsin, United States, and Ontario, Canada, in 2019 and 2020 to evaluate seed treatment combinations. Treatments included a nontreated check (NTC), fungicide and insecticide base seed treatments (base), fluopyram, base + fluopyram, base + saponin extracts from Chenopodium quinoa, base + fluopyram + heat-killed Burkholderia rinojenses, base + pydiflumetofen, base + thiabendazole + heat-killed B. rinojenses, and base + thiabendazole + C. quinoa extracts + heat-killed B. rinojenses. Treatments were tested on SDS moderately resistant and susceptible soybean cultivars at each location. Overall, NTC and base had the most root rot, most foliar disease index (FDX), and lowest yield. Base + fluopyram and base + pydiflumetofen were most effective for managing SDS. Moderately resistant cultivars reduced FDX in both years but visual root rot was greater on the moderately resistant than the susceptible cultivars in 2020. Yield response to cultivar was also inconsistent between the 2 years. In 2020, the susceptible cultivar provided significantly more yield than the moderately resistant cultivar. Treatment effect for root rot and FDX was similar in field and greenhouse evaluations. These results reinforce the need to include root rot evaluations in addition to foliar disease evaluations in the breeding process for resistance to F. virguliforme and highlights the importance of an integrated SDS management plan because not a single management tactic alone provides adequate control of the disease.

Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean.

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.

Detection and discovery of plant viruses in soybean by metagenomic sequencing.

BACKGROUND: Viruses negatively impact soybean production by causing diseases that affect yield and seed quality. Newly emerging or re-emerging viruses can also threaten soybean production because current control measures may not be effective against them. Furthermore, detection and characterization of new plant viruses requires major efforts when no sequence or antibody-based resources are available. METHODS: In this study, soybean fields were scouted for virus-like disease symptoms during the 2016-2019 growing seasons. Total RNA was extracted from symptomatic soybean parts, cDNA libraries were prepared, and RNA sequencing was performed using high-throughput sequencing (HTS). A custom bioinformatic workflow was used to identify and assemble known and unknown virus genomes. RESULTS: Several viruses were identified in single or mixed infections. Full- or nearly full-length genomes were generated for tobacco streak virus (TSV), alfalfa mosaic virus (AMV), tobacco ringspot virus (TRSV), soybean dwarf virus (SbDV), bean pod mottle virus (BPMV), soybean vein necrosis virus (SVNV), clover yellow vein virus (ClYVV), and a novel virus named soybean ilarvirus 1 (SIlV1). Two distinct ClYVV isolates were recovered, and their biological properties were investigated in Nicotiana benthamiana, broad bean, and soybean. In addition to infections by individual viruses, we also found that mixed viral infections in various combinations were quite common. CONCLUSIONS: Taken together, the results of this study showed that HTS-based technology is a valuable diagnostic tool for the identification of several viruses in field-grown soybean and can provide rapid information about expected viruses as well as viruses that were previously not detected in soybean.

Identification of Septoria glycines Isolates from Soybean with Resistance to Quinone Outside Inhibitor Fungicides.

Brown spot, caused by Septoria glycines, is a common foliar disease of soybean (Glycine max). Applications of fungicide products that contain quinone outside inhibitor (QoI) active ingredients to soybean fields have contributed to the selection and development of QoI-resistant populations of S. glycines. We investigated the molecular mechanisms of QoI-resistance in these populations through targeted analysis of the cytochrome b gene. Isolates of S. glycines collected from several soybean fields over different seasons varied in sensitivity to QoI fungicides. Characterization of the cytochrome b gene revealed a mutation that changed an amino acid from glycine to alanine at codon 143 - one that is generally associated with QoI fungicide resistances. A PCR assay was developed that allowed successful discrimination of QoI-sensitive and -resistant isolates based on the G143A mutation. Results of this study demonstrated that 47.5% of S. glycines isolates tested were resistant to QoI fungicides. Accurate monitoring of this mutation will help slow the spread of QoI resistance and will be important for fungicide resistant management in this pathosystem.

Integration of Row Spacing, Seeding Rates, and Fungicide Applications for Control of Sclerotinia Stem Rot in Glycine max.

Soybean (Glycine max) farmers in the Upper Midwest region of the United States often experience severe yield losses due to Sclerotinia stem rot (SSR). Previous studies have revealed benefits of individual management practices for SSR. This study examined the integration of multiple control practices on the development of SSR, yield, and the economic implications of these practices. Combinations of row spacings, seeding rates, and fungicide applications were examined in multisite field trials across the Upper Midwest from 2017 to 2019. These trials revealed that wide row spacing and low seeding rates individually reduced SSR levels but also reduced yields. Yields were similar across the three highest seeding rates examined. However, site-years where SSR developed showed the highest partial profits at the intermediate seeding rates. This finding indicates that partial profits in diseased fields were reduced by high seeding rates, but this trend was not observed when SSR did not develop. Fungicides strongly reduced the development of SSR while also increasing yields. However, there was a reduction in partial profits due to their use at a low soybean sale price, but at higher sale prices fungicide use was similar to not treating. Additionally, the production of new inoculum was predicted from disease incidence, serving as an indicator of increased risk for SSR development in future years. Overall, this study suggests using wide rows and low seeding rates in fields with a history of SSR while reserving narrow rows and higher seeding rates for fields without a history of SSR.

Influence of Fusarium virguliforme Temporal Colonization of Corn, Tillage, and Residue Management on Soybean Sudden Death Syndrome and Soybean Yield.

The asymptomatic host range of Fusarium virguliforme includes corn, a common crop rotated with soybean that we hypothesize may alter F. virguliforme population dynamics and disease management. A field-based approach explored the temporal dynamics of F. virguliforme colonization of corn and soybean roots under different tillage and residue managements. Experiments were conducted in Iowa, Indiana, Michigan, and Wisconsin, United States and Ontario, Canada from 2016 to 2018. Corn and soybean roots were sampled at consecutive timepoints between 1 and 16 weeks after planting. DNA was extracted from all roots and analyzed by real-time quantitative PCR for F. virguliforme quantification. Trials were rotated between corn and soybean, containing a two-by-two factorial of tillage (no-tilled or tilled) and corn residue (with or without) in several experimental designs. In 2016, low amounts (approximately 100 fg per 10 mg of root tissue) of F. virguliforme were detected in the inoculated Iowa, Indiana, and Michigan locations and noninoculated Wisconsin corn fields. However, in 2017, greater levels of F. virguliforme DNA were detected in Iowa, Indiana, and Michigan across sampling timepoints. Tillage practices showed inconsistent effects on F. virguliforme root colonization and sudden death syndrome (SDS) foliar symptoms among trials and locations. However, residue management did not alter root colonization of corn or soybean by F. virguliforme. Plots with corn residue had greater SDS foliar disease index in Iowa in 2016. However, this trend was not observed across the site-years, indicating that corn residue may occasionally increase SDS foliar symptoms depending on the disease level and soil and weather factors.

Identification of Soybean (Glycine max) Check Lines for Evaluating Genetic Resistance to Sclerotinia Stem Rot.

Soybean production in the upper midwestern United States is affected by Sclerotinia stem rot (SSR) caused by the fungal pathogen Sclerotinia sclerotiorum. Genetic resistance is an important management strategy for this disease; however, assessing genetic resistance to S. sclerotiorum is challenging because a standardized method of examining resistance across genotypes is lacking. Using a panel of nine diverse S. sclerotiorum isolates, four soybean lines were assessed for reproducible responses to S. sclerotiorum infection. Significant differences in SSR severity were found across isolates (P < 0.01) and soybean lines (P < 0.01), including one susceptible, two moderately resistant, and one highly resistant line. These four validated lines were used to screen 11 other soybean genotypes to evaluate their resistance levels, and significant differences were found across genotypes (P < 0.01). Among these 11 genotypes, five commercial and public cultivars displayed high resistance and were assessed during field studies across the upper midwestern United States growing region to determine their response to SSR and yield. These five cultivars resulted in low disease levels (P < 0.01) in the field that were consistent with greenhouse experiment results. The yields were significantly different in fields with disease present (P < 0.01) and disease absent (P < 0.01), and the order of cultivar performance was consistent between environments where disease was present or absent, suggesting that resistance prevented yield loss to disease. This study suggests that the use of a soybean check panel can accurately assess SSR resistance in soybean germplasm and aid in breeding and commercial soybean development.

Diaporthe Seed Decay of Soybean [Glycine max (L.) Merr.] Is Endemic in the United States, But New Fungi Are Involved.

Diaporthe seed decay can compromise seed quality in soybean [Glycine max (L.) Merr.] in the warm and humid production areas of the United States during crop maturation. In the current study, 45 isolates of Diaporthe were recovered from seed sampled from soybean fields affected by Diaporthe-associated diseases in eight U.S. states in 2017. The isolates obtained belonged to 10 species of Diaporthe based on morphology and phylogenetic analyses of the internal transcribed spacer, partial translation elongation factor 1-α, and ß-tubulin gene sequences. The associated species included D. aspalathi, D. caulivora, D. kongii, D. longicolla, D. sojae, D. ueckerae, D. unshiuensis, and three novel fungi, D. bacilloides, D. flavescens, and D. insulistroma. One isolate each of the 10 species was examined for pathogenicity on seed of cultivar Sava under controlled conditions. Seven days postinoculation, significant differences in the percentages of decayed seeds and seedling necrosis were observed among the isolates and the noninoculated control (P < 0.0001). While the isolates of D. bacilloides, D. longicolla, and D. ueckerae caused a significantly greater percentage of decayed seeds (P < 0.0001), the isolate of D. aspalathi caused the greatest seedling necrosis (P < 0.0001). The observation of new fungi causing Diaporthe seed decay suggests the need for a more comprehensive survey in U.S. soybean producing areas since members of the genus Diaporthe appear to form a complex that causes seed decay.

Meta-Analysis of Soybean Yield Response to Foliar Fungicides Evaluated from 2005 to 2018 in the United States and Canada.

Random-effect meta-analyses were performed on data from 240 field trials conducted between 2005 and 2018 across nine U.S. states and Ontario, Canada, to quantify the yield response of soybean after application of foliar fungicides at beginning pod (R3) stage. Meta-analysis showed that the overall mean yield response when fungicide was used compared with not applying a fungicide was 2.7% (110 kg/ha). Moderator variables were also investigated and included fungicide group, growing season, planting date, and base yield, which all significantly influenced the yield response. There was also evidence that precipitation from the time of planting to the R3 growth stage influenced yield when fungicide was used (P = 0.059). Fungicides containing a premix of active ingredients from multiple groups (either two or three ingredients) increased the yield by 3.0% over not applying a fungicide. The highest and lowest yield responses were observed in 2005 and 2007, respectively. Better yield response to fungicides (a 3.0% increase) occurred when soybean crops were planted not later than 21 May and when total precipitation between planting and the R3 application date was above historic averages. Temperatures during the season did not influence the yield response. Yield response to fungicide was higher (a 4.7% increase) in average yield category (no spray control yield 2,878 to 3,758 kg/ha) and then gradually decreased with increasing base yield. Partial economic analyses indicated that use of foliar fungicides is less likely to be profitable when foliar diseases are absent or at low levels.

Relationship Between Sudden Death Syndrome caused by Fusarium virguliforme and Soybean Yield: A Meta-Analysis.

In total, 52 uniform field experiments were conducted in Illinois, Indiana, Iowa, Michigan, South Dakota, and Wisconsin in the United States and Ontario, Canada from 2013 to 2017 comparing crop protection products against sudden death syndrome (SDS) of soybean. Data were analyzed using meta-analytic models to summarize the relationship between foliar disease index (FDX) and yield. For each study, correlation and regression analyses were performed separately to determine three effect sizes: Fisher's transformation of correlation coefficients (Z r ), intercept (ß0), and slope (ß1). Random- and mixed-effect meta-analyses were used to summarize the effect sizes. Study- and location-specific moderator variables FDX (low < 10% and high ≥ 10%), date of planting (early = prior to 7 May, conventional = 7 to 21 May, and late = after 21 May) cultivar (susceptible and partially resistant to SDS), study location, and growing season were used as fixed effects. The overall mean effect sizes of transformed correlation coefficient [Formula: see text] r was -0.41 and different from zero (P < 0.001), indicating that yield was negatively correlated with FDX. The [Formula: see text] r was affected by disease level (P < 0.01) and cultivar (P = 0.02), with a greater effect at higher disease levels and with susceptible cultivars. The mean [Formula: see text] 0 was 4,121 kg/ha and mean [Formula: see text] 1 was -21 kg/ha/% FDX and were different from zero (P < 0.01). Results from these data indicate that, for every unit of FDX increase, yield was decreased by 0.5%. Study locations and year affected the [Formula: see text] 0 , whereas none of the moderator variables significantly affected [Formula: see text] 1.

Soybean Fungal Endophytes Alternaria and Diaporthe spp. are Differentially Impacted by Fungicide Application.

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: Alternaria, Colletotrichum, and Diaporthe 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 Diaporthe isolates over no-spray controls, whereas the inverse occurred for foliar Alternaria isolates. In addition, seed harvested from fields with shorter-season varieties and sprayed with fungicide showed higher percentages of Diaporthe 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.

Neonicotinoid seed treatments of soybean provide negligible benefits to US farmers.

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.

Meta-analysis of yield response of foliar fungicide-treated hybrid corn in the United States and Ontario, Canada.

BACKGROUND: 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. OBJECTIVE: Compare yield response of fungicide application timing across multiple fungicide classes and calculate the probability of positive ROI. METHODS: 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. RESULTS: 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. CONCLUSION: 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.