Modeling Yield Losses and Fungicide Profitability for Managing Fusarium Head Blight in Brazilian Spring Wheat

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 (β0) and slope (β1). 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.

Foliar Fungicides Containing FRAC 11 Mitigate Phomopsis Stem Canker in Sunflower (Helianthus annuus)

Phomopsis stem canker reduces yield of sunflower (Helianthus annuus L.) up to or exceeding 40%; however, management recommendations have not been developed for U.S. farmers. Between 2009 and 2020, foliar fungicide trials were conducted in Minnesota, Nebraska, North Dakota, and South Dakota for a total of 49 location-years. Random effects meta-analyses were performed on the disease severity index (DSI) and yield data collected from the foliar fungicide trials to determine the overall and individual effectiveness of the tested fungicides. Effect sizes, Cohen's f or Hedges' g, were calculated as the difference in DSI or yield between the fungicide treatment and nontreated control (NTC) divided by the pooled SD. The pooled Cohen's f for DSI and yield was 0.40 (95% CI = [0.29, 0.42]), indicating a large effect size and that fungicide treatments had a significant effect on DSI and yield (P < 0.0001). Among the fungicide groups, quinone outside inhibitor (QoI) (DSI [k = 45; g = -0.47] and yield [k = 46; g = 0.41]) is moderately effective and premixes of demethylation inhibitors (DMI), succinate dehydrogenase inhibitors (SDHI), and QoI (DMI + SDHI + QoI) (DSI [k = 3; g = -0.79] and yield [k = 3; g = 0.94]) are largely effective in comparison with NTC. Upon performing prediction analyses, the probability of not recovering the fungicide application cost (P_loss) associated with QoI (pyraclostrobin) was <0.35 for a range of sunflower grain prices suggesting a greater probability of return on investment from a single application of fungicide. Overall, our study suggests that the use of QoI fungicides is likely to be profitable in the presence of Phomopsis stem canker (DSI > 5%).

Fusarium graminearum Species Complex: A Bibliographic Analysis and Web-Accessible Database for Global Mapping of Species and Trichothecene Toxin Chemotypes

Fusarium graminearum is ranked among the five most destructive fungal pathogens that affect agroecosystems. It causes floral diseases in small grain cereals including wheat, barley, and oats, as well as maize and rice. We conducted a systematic review of peer-reviewed studies reporting species within the F. graminearum species complex (FGSC) and created two main data tables. The first contained summarized data from the articles including bibliographic, geographic, methodological (ID methods), host of origin and species, while the second data table contains information about the described strains such as publication, isolate code(s), host/substrate, year of isolation, geographical coordinates, species and trichothecene genotype. Analyses of the bibliographic data obtained from 123 publications from 2000 to 2021 by 498 unique authors and published in 40 journals are summarized. We describe the frequency of species and chemotypes for 16,274 strains for which geographical information was available, either provided as raw data or extracted from the publications, and sampled across six continents and 32 countries. The database and interactive interface are publicly available, allowing for searches, summarization, and mapping of strains according to several criteria including article, country, host, species and trichothecene genotype. The database will be updated as new articles are published and should be useful for guiding future surveys and exploring factors associated with species distribution such as climate and land use. Authors are encouraged to submit data at the strain level to the database, which is accessible at https://fgsc.netlify.app.

Aggressiveness and Mycotoxin Production by Fusarium meridionale Compared with F. graminearum on Maize Ears and Stalks in the Field

Fusarium meridionale and F. graminearum both cause Gibberella ear rot (GER) and Gibberella stalk rot (GSR) of maize in Brazil, but the former is much more common. Recent work with two isolates of each from maize suggested this dominance could be caused by greater aggressiveness and competitiveness of F. meridionale on maize. We evaluated pathogenicity and toxigenicity of 16 isolates of F. graminearum and 24 isolates of F. meridionale recovered from both wheat and maize. Strains were individually inoculated into ears of four maize hybrids in field trials. GER severity varied significantly between isolates within each species. Although ranges overlapped, the average GER severity induced by F. meridionale (25.2%) was two times as high overall as that induced by F. graminearum (12.8%) for isolates obtained from maize but was similar for those isolated from wheat (19.9 and 21.4%, respectively). In contrast, severity of GSR was slightly higher for F. graminearum (22.2%) than for F. meridionale (19.8%), with no effect of the host of origin. Deoxynivalenol and its acetylated form 15ADON were the main mycotoxins produced by F. graminearum (7/16 strains), and nivalenol toxin was produced by F. meridionale (17/24 strains). Six isolates of F. graminearum and three of F. meridionale also produced zearalenone. Results confirmed that F. meridionale from maize is, on average, more aggressive on maize but also suggested greater complexity related to diversity among the isolates within each species and their interactions with different hybrids. Further studies involving other components of the disease cycle are needed to more fully explain observed patterns of host dominance.

Adapting to the projected epidemics of Fusarium head blight of wheat in Korea under climate change scenarios

Fusarium head blight (FHB) of wheat, mainly caused by Fusarium graminearum Schwabe, is an emerging threat to wheat production in Korea under a changing climate. The disease occurrence and accumulation of associated trichothecene mycotoxins in wheat kernels strongly coincide with warm and wet environments during flowering. Recently, the International Panel for Climate Change released the 6th Coupled Model Intercomparison Project (CMIP6) climate change scenarios with shared socioeconomic pathways (SSPs). In this study, we adopted GIBSIM, an existing mechanistic model developed in Brazil to estimate the risk infection index of wheat FHB, to simulate the potential FHB epidemics in Korea using the SSP245 and SSP585 scenarios of CMIP6. The GIBSIM model simulates FHB infection risk from airborne inoculum density and infection frequency using temperature, precipitation, and relative humidity during the flowering period. First, wheat heading dates, during which GIBSIM runs, were predicted over suitable areas of winter wheat cultivation using a crop development rate model for wheat phenology and downscaled SSP scenarios. Second, an integrated model combining all results of wheat suitability, heading dates, and FHB infection risks from the SSP scenarios showed a gradual increase in FHB epidemics towards 2100, with different temporal and spatial patterns of varying magnitudes depending on the scenarios. These results indicate that proactive management strategies need to be seriously considered in the near future to minimize the potential impacts of the FHB epidemic under climate change in Korea. Therefore, available wheat cultivars with early or late heading dates were used in the model simulations as a realistic adaptation measure. As a result, wheat cultivars with early heading dates showed significant decreases in FHB epidemics in future periods, emphasizing the importance of effective adaptation measures against the projected increase in FHB epidemics in Korea under climate change.

Sequential Post-Heading Applications for Controlling Wheat Blast: A 9-Year Summary of Fungicide Performance in Brazil

Wheat blast, caused by Pyricularia oryzae Triticum lineage, is a major constraint to wheat production, mainly in the tropics of Brazil, where severe epidemics have been more frequent. We analyzed disease and wheat yield data from 42 uniform field trials conducted over 9 years (2012 to 2020) to assess whether the percent control and yield response were influenced by fungicide type, region (tropical or subtropical), and year. Six treatments were selected, all evaluated in at least 19 trials. Two fungicides were applied as solo active ingredients (MANCozeb, and TEBUconazole), and four were premixes (AZOXystrobin plus TEBU, TriFLoXystrobin plus PROThioconazole, TFLX plus TEBU, and PYRAclostrobin plus EPOXiconazole). Percent control, calculated from back-transforming estimates by a meta-analysis network model fitted to the log of the means, ranged from 43 to 58%, with all but PYRA plus EPOX showing efficacy >52% on average, not differing among them. The variation in both efficacy and yield response was explained by region, and all but TEBU performed better in the subtropics than in the tropics. Yield response from using three sequential sprays was approximately two times greater in the subtropics (319 to 532 kg/ha) than in the tropics (149 to 241.3 kg/ha). No significant decline in fungicide efficacy or yield response was observed in 9 years of study for any of the fungicides. These results reinforce the need to improve control by adopting an integrated management approach in the tropics given poorer performance and lower profitability, especially for the premixes, than in the subtropics.

Are Demethylation Inhibitor Plus Quinone Outside Inhibitor Fungicide Premixes During Flowering Worthwhile for Fusarium Head Blight Control in Wheat? A Meta-Analysis

Fusarium head blight (FHB), caused mainly by Fusarium graminearum, is best controlled with demethylation inhibitor (DMI) fungicides during flowering. However, the use of premixes of DMI and quinone outside inhibitor (QoI) fungicides to control FHB has increased in Brazil. Data on FHB severity and wheat yields measured in field experiments conducted in Brazil were gathered from both peer- and nonpeer-reviewed sources published from 2000 to 2018. After selection criteria were applied, 73 field trials from 35 bibliographic sources were identified, among which 50% of the data were obtained from cooperative network trials conducted after 2011. To be included in the analysis, DMI plus QoI premixes or tebuconazole were tested in at least 14 trials and 3 years. Four premixes met the criteria. Estimates of percent control (and respective 95% confidence intervals) by a network model fitted to the log of the treatment means ranged from 44.1% (pyraclostrobin plus metconazole applied once; 32.4 to 53.7) to 64.3% (pyraclostrobin plus metconazole; 58.4 to 69.3); the latter did not differ from tebuconazole (59.9%; 53.6 to 65.3). Yield response was statistically similar for pyraclostrobin plus metconazole (532.1 kg/ha; 441 to 623) and trifloxystrobin plus prothioconazole (494.9 kg/ha; 385 to 551), and both differed statistically from a group composed of tebuconazole (448.2 kg/ha; 342 to 554), trifloxystrobin plus tebuconazole (468.2 kg/ha; 385 to 551), azoxystrobin plus tebuconazole (462.4 kg/ha; 366 to 558), and pyraclostrobin plus metconazole applied once (413.7 kg/ha; 308 to 518). The two categories of FHB index (7% cutoff) and yield (3,000 kg/ha cutoff), both in the nontreated check, did not explain the heterogeneity in the estimates. Considering only the fungicide effects on yield, two sequential sprays of tebuconazole or one spray of pyraclostrobin plus metconazole as management choices are likely more profitable than DMI plus QoI premixes sprayed twice during flowering.