Phytophthora root and stem rot of soybean

Phytophthora sojae is a soil borne pathogen that in the past has caused very large economic losses. During the late 1970s, 300,000 soybean acres (approximately 10% of total soybean production in Ohio) were lost due to P. sojae. This disease has since been effectively managed predominately through the incorporation of single-gene mediated resistance but quantitative or partial resistance has been used as well. In fact, today, we can repeat 100% loss by planting soybean cultivars that were popular during earlier epidemics. Without high levels of resistance to this pathogen, many soybean acres would be lost each year to this disease. Phytophthora doesn’t forget and it doesn’t go away

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

Re-emergence of Tobacco streak virus Infecting Soybean in the United States and Canada

Tobacco streak virus (TSV), an Ilarvirus, was first confirmed as a viral pathogen of tobacco in 1936 (Johnson 1936) and first reported in North American soybean in 1969 (Fagbenle and Ford 1970). TSV has a wide host range with strains able to infect at least 140 different plant genera, including crop, ornamental, and wild species (Fulton 1948). Due to its extensive host range and strain adaptations, TSV is found in commercial crops worldwide. Since 1969, however, TSV has not been a problem on soybean or commonly reported until the 2013 season, when it was found in fields throughout Iowa. A similar situation is found throughout the Midwest, with TSV being reported in recent years in Illinois, Kansas, and Wisconsin, as well as Ontario, Canada

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

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

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 (). Application timing influenced , 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

Ecology and diversity of culturable fungal species associated with soybean seedling diseases in the Midwestern United States

Aims: To isolate and characterize fungi associated with diseased soybean seedlings in Midwestern soybean production fields and to determine the influence of environmental and edaphic factors on their incidence. Methods and Results: Seedlings were collected from fields with seedling disease history in 2012 and 2013 for fungal isolation. Environmental and edaphic data associated with each field was collected. 3036 fungal isolates were obtained and assigned to 76 species. The most abundant genera recovered were Fusarium (73%) and Trichoderma (11.2%). Other genera included Mortierella, Clonostachys, Rhizoctonia, Alternaria, Mucor, Phoma, Macrophomina and Phomopsis. Most recovered species are known soybean pathogens. However, non-pathogenic organisms were also isolated. Crop history, soil density, water source, precipitation and temperature were the main factors influencing the abundance of fungal species. Conclusion: Key fungal species associated with soybean seedling diseases occurring in several US production regions were characterized. This work also identified major environment and edaphic factors affecting the abundance and occurrence of these species. Significance and Impact of the Study: The identification and characterization of the main pathogens associated with seedling diseases across major soybean-producing areas could help manage those pathogens, and devise more effective and sustainable practices to reduce the damage they cause

Population Genomics Provide Insights into the Global Genetic Structure of \u3ci\u3eColletotrichum graminicola\u3c/i\u3e, the Causal Agent of Maize Anthracnose

Understanding the genetic diversity and mechanisms underlying genetic variation in pathogen populations is crucial to the development of effective control strategies. We investigated the genetic diversity and reproductive biology of Colletotrichum graminicola isolates which infect maize by sequencing the genomes of 108 isolates collected from 14 countries using restriction site-associated DNA sequencing (RAD-seq) and wholegenome sequencing (WGS). Clustering analyses based on single-nucleotide polymorphisms revealed three genetic groups delimited by continental origin, compatible with short-dispersal of the pathogen and geographic subdivision. Intra- and intercontinental migration was observed between Europe and South America, likely associated with the movement of contaminated germplasm. Low clonality, evidence of genetic recombination, and high phenotypic diversity were detected. We show evidence that, although it is rare (possibly due to losses of sexual reproduction- and meiosis-associated genes) C. graminicola can undergo sexual recombination. Our results support the hypotheses that intra- and intercontinental pathogen migration and genetic recombination have great impacts on the C. graminicola population structure

Defining optimal soybean seeding rates and associated risk across North America

Soybean [Glycine max (L.) Merr.] seeding rate research across North America is typically conducted in small geo-political regions where environmental effects on the seeding rate × yield relationship are minimized. Data from 211 individual field studies (∼21,000 data points, 2007–2017) were combined from across North America ranging in yield from 1,000– 7,500 kg ha−1. Cluster analysis was used to stratify each individual field study into similar environmental (soil × climate) clusters and into high (HYL), medium (MYL), and low (LYL) yield levels. Agronomically optimal seeding rates (AOSR) were calculated and Monte Carlo risk analysis was implemented. Within the two northern most clusters the AOSR was higher in the LYL followed by the MYL and then HYL. Within the farthest south cluster, a relatively small (±15,000 seeds ha−1) change in seeding rate from the MYL was required to reach the AOSR of the LYL and HYL, respectively. The increase in seeding rate to reach the LYL AOSR was relatively greater (5x) than the decrease to reach the HYL AOSR within the northern most cluster. Regardless, seeding rates below the AOSR presented substantial risk and potential yield loss, while seeding rates above provided slight risk reduction and yield increases. Specific to LYLs and MYLs, establishing and maintaining an adequate plant stand until harvest maximized yield regardless of the seeding rate, while maximizing seed number was important with lower seeding rates. These findings will help growers manage their soybean seed investment by adjusting seeding rates based upon the productivity of the environment.Fil: Gaspar, Adam P.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Mourtzinis, Spyridon. University of Wisconsin; Estados UnidosFil: Kyle, Don. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Galdi, Eric. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Lindsey, Laura E.. Ohio State University; Estados UnidosFil: Hamman, William P.. Ohio State University; Estados UnidosFil: Matcham, Emma G. University of Wisconsin; Estados UnidosFil: Kandel, Hans J.. North Dakota State University; Estados UnidosFil: Schmitz, Peder. North Dakota State University; Estados UnidosFil: Stanley, Jordan D.. North Dakota State University; Estados UnidosFil: Schmidt, John P.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Mueller, Daren S.. University of Iowa; Estados UnidosFil: Nafziger, Emerson D.. University of Illinois; Estados UnidosFil: Ross, Jeremy. University of Arkansas for Medical Sciences; Estados UnidosFil: Carter, Paul R.. Dow Agrosciences Argentina Sociedad de Responsabilidad Limitada.; ArgentinaFil: Varenhorst, Adam J.. University of South Dakota; Estados UnidosFil: Wise, Kiersten A.. University of Kentucky; Estados UnidosFil: Ciampitti, Ignacio Antonio. Kansas State University; Estados UnidosFil: Carciochi, Walter Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina. Kansas State University; Estados UnidosFil: Chilvers, Martin I.. Michigan State University; Estados UnidosFil: Hauswedell, Brady. University of South Dakota; Estados UnidosFil: Tenuta, Albert U.. University of Guelph; CanadáFil: Conley, Shawn P.. University of Wisconsin; Estados Unido

Population Genomics Provide Insights into the Global Genetic Structure of Colletotrichum graminicola, the Causal Agent of Maize Anthracnose

Understanding the genetic diversity and mechanisms underlying genetic variation in pathogen populations is crucial to the development of effective control strategies. We investigated the genetic diversity and reproductive biology of Colletotrichum graminicola isolates which infect maize by sequencing the genomes of 108 isolates collected from 14 countries using restriction site-associated DNA sequencing (RAD-seq) and whole-genome sequencing (WGS). Clustering analyses based on single-nucleotide polymorphisms revealed three genetic groups delimited by continental origin, compatible with short-dispersal of the pathogen and geographic subdivision. Intra- and intercontinental migration was observed between Europe and South America, likely associated with the movement of contaminated germplasm. Low clonality, evidence of genetic recombination, and high phenotypic diversity were detected. We show evidence that, although it is rare (possibly due to losses of sexual reproduction- and meiosis-associated genes) C. graminicola can undergo sexual recombination. Our results support the hypotheses that intra- and intercontinental pathogen migration and genetic recombination have great impacts on the C. graminicola population structure. IMPORTANCE Plant pathogens cause significant reductions in yield and crop quality and cause enormous economic losses worldwide. Reducing these losses provides an obvious strategy to increase food production without further degrading natural ecosystems; however, this requires knowledge of the biology and evolution of the pathogens in agroecosystems. We employed a population genomics approach to investigate the genetic diversity and reproductive biology of the maize anthracnose pathogen (Colletotrichum graminicola) in 14 countries. We found that the populations are correlated with their geographical origin and that migration between countries is ongoing, possibly caused by the movement of infected plant material. This result has direct implications for disease management because migration can cause the movement of more virulent and/or fungicide-resistant genotypes. We conclude that genetic recombination is frequent (in contrast to the traditional view of C. graminicola being mainly asexual), which strongly impacts control measures and breeding programs aimed at controlling this disease.This research was supported by grants AGL2015-66362-R, RTI2018-093611-B-100, and PID2021-125349NB-100, funded by the Ministry of Science and Innovation (MCIN) of Spain AEI/10.13039/501100011033; and by grant SA165U13 funded by the Junta de Castilla y Léon. F.R. was supported by grant FJC2020-043351-I financed by MCIN/AEI /10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. R.B. was supported by the postdoctoral program of USAL (Program II). F.B.C.-F. was supported by grant BES-2016-078373, funded by MCIN/AEI/10.13039/501100011033. S.B. was supported by a fellowship program from the regional government of Castilla y León. W.B. was supported by a productivity fellowship from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq 307855/2019-8). Genome sequencing was funded by the UNC Microbiome Core, which is funded in part by the Center for Gastrointestinal Biology and Disease (CGIBD P30 DK034987) and the UNC Nutrition Obesity Research Center (NORC P30 DK056350). P.D.E. was partially supported by the USDA National Institute of Food and Federal Appropriations under Project PEN04660 and accession no. 1016474.Peer reviewe

Phytophthora root and stem rot of soybean

Phytophthora sojae is a soil borne pathogen that in the past has caused very large economic losses. During the late 1970s, 300,000 soybean acres (approximately 10% of total soybean production in Ohio) were lost due to P. sojae. This disease has since been effectively managed predominately through the incorporation of single-gene mediated resistance but quantitative or partial resistance has been used as well. In fact, today, we can repeat 100% loss by planting soybean cultivars that were popular during earlier epidemics. Without high levels of resistance to this pathogen, many soybean acres would be lost each year to this disease. Phytophthora doesn’t forget and it doesn’t go away!This is an article from The Plant Health Instructor (2007): 1, doi:10.1094/PHI-I-2007-0830-07. Posted with permission.</p