Fusarium Head Blight Epidemics in Soft Red Winter Wheat Fields in Georgia from 2018 to 2019

2021 ◽  
Author(s):  
Bikash Ghimire ◽  
James Buck ◽  
Mohamed Mergoum ◽  
Alfredo D. Martinez-Espinoza
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Integrated Management ◽  
Management Strategies ◽  
The United States ◽  
Kernel Weight ◽  
Head Blight ◽  
Weather Variables ◽  
Soft Red Winter Wheat ◽  
Red Winter Wheat

Fusarium head blight (FHB) epidemics on wheat have caused significant yield and economic penalties in the United States since the early 1990s. This report documents FHB epidemics on soft red winter wheat in Georgia in 2018 and 2019. Forty-four wheat fields across 23 counties were assessed for FHB incidence (2019 only), Fusarium-damaged kernel, deoxynivalenol (DON) contamination, and thousand kernel weight. Higher levels of FHB were observed in 2019 compared to 2018. A significant correlation was observed between DON and 7-day pre-anthesis weather variables in 2019. FHB parameters were significantly correlated to post-anthesis weather variables at 10-day in both years and at 20 and 30-day in 2018 suggesting that post-anthesis rather than pre-anthesis weather had a greater impact on FHB in our study. The combination of hours of conducive temperature and relative humidity post-anthesis was consistently correlated with all FHB parameters in both years and could be the best predictor of FHB epidemics. FHB has emerged as the leading threat for soft red winter wheat production in Georgia. Planting moderately resistant wheat cultivars along with in-season management including proper fungicide application, by closely monitoring the national FHB forecasting system, would be the best integrated management strategies for Georgian wheat growers.

scholarly journals Meta-Analysis of the Effects of Triazole-Based Fungicides on Wheat Yield and Test Weight as Influenced by Fusarium Head Blight Intensity

2010 ◽  
Vol 100 (2) ◽  
pp. 160-171 ◽  
Author(s):  
P. A. Paul ◽  
M. P. McMullen ◽  
D. E. Hershman ◽  
L. V. Madden
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Wheat Yield ◽  
Test Weight ◽  
Response To Treatment ◽  
Yield Response ◽  
Head Blight ◽  
Yield Increase ◽  
Soft Red Winter Wheat ◽  
Red Winter Wheat

Multivariate random-effects meta-analyses were conducted on 12 years of data from 14 U.S. states to determine the mean yield and test-weight responses of wheat to treatment with propiconazole, prothioconazole, tebuconazole, metconazole, and prothioconazole+tebuconazole. All fungicides led to a significant increase in mean yield and test weight relative to the check (D; P < 0.001). Metconazole resulted in the highest overall yield increase, with a D of 450 kg/ha, followed by prothioconazole+tebuconazole (444.5 kg/ha), prothioconazole (419.1 kg/ha), tebuconazole (272.6 kg/ha), and propiconazole (199.6 kg/ha). Metconazole, prothioconazole+tebuconazole, and prothioconazole also resulted in the highest increases in test weight, with D values of 17.4 to 19.4 kg/m3, respectively. On a relative scale, the best three fungicides resulted in an overall 13.8 to 15.0% increase in yield but only a 2.5 to 2.8% increase in test weight. Except for prothioconazole+tebuconazole, wheat type significantly affected the yield response to treatment; depending on the fungicide, D was 110.0 to 163.7 kg/ha higher in spring than in soft-red winter wheat. Fusarium head blight (FHB) disease index (field or plot-level severity) in the untreated check plots, a measure of the risk of disease development in a study, had a significant effect on the yield response to treatment, in that D increased with increasing FHB index. The probability was estimated that fungicide treatment in a randomly selected study will result in a positive yield increase (p+) and increases of at least 250 and 500 kg/ha (p250 and p500, respectively). For the three most effective fungicide treatments (metconazole, prothioconazole+tebuconazole, and prothioconazole) at the higher selected FHB index, p+ was very large (e.g., ≥0.99 for both wheat types) but p500 was considerably lower (e.g., 0.78 to 0.92 for spring and 0.54 to 0.68 for soft-red winter wheat); at the lower FHB index, p500 for the same three fungicides was 0.34 to 0.36 for spring and only 0.09 to 0.23 for soft-red winter wheat.

scholarly journals Efficacy of Fungicide Applications During and After Anthesis Against Fusarium Head Blight and Deoxynivalenol in Soft Red Winter Wheat

Plant Disease ◽  
2014 ◽  
Vol 98 (10) ◽  
pp. 1387-1397 ◽  
Author(s):  
D. L. D'Angelo ◽  
C. A. Bradley ◽  
K. A. Ames ◽  
K. T. Willyerd ◽  
L. V. Madden ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Field Experiments ◽  
The Other ◽  
Square Root ◽  
Head Blight ◽  
Soft Red Winter Wheat ◽  
Untreated Check ◽  
Red Winter Wheat ◽  
Days After Anthesis

Seven field experiments were conducted in Ohio and Illinois between 2011 and 2013 to evaluate postanthesis applications of prothioconazole + tebuconazole and metconazole for Fusarium head blight and deoxynivalenol (DON) control in soft red winter wheat. Treatments consisted of an untreated check and fungicide applications made at early anthesis (A), 2 (A+2), 4 (A+4), 5 (A+5), or 6 (A+6) days after anthesis. Six of the seven experiments were augmented with artificial Fusarium graminearum inoculum, and the other was naturally infected. FHB index (IND), Fusarium damaged kernels (FDK), and DON concentration of grain were quantified. All application timings led to significantly lower mean arcsine-square-root-transformed IND and FDK (arcIND and arcFDK) and log-transformed (logDON) than in the untreated check; however, arcIND, arcFDK, and logDON for the postanthesis applications were generally not significantly different from those for the anthesis applications. Relative to the check, A+2 resulted in the highest percent control for both IND and DON, 69 and 54%, respectively, followed by A+4 (62 and 52%), A+6 (62 and 48%), and A (56 and 50%). A+2 and A+6 significantly reduced IND by 30 and 14%, respectively, relative to the anthesis application. Postanthesis applications did not, however, reduce DON relative to the anthesis application. These results suggest that applications made up to 6 days following anthesis may be just as effective as, and sometimes more effective than, anthesis applications at reducing FHB and DON.

Genome‐wide analysis and prediction of Fusarium head blight resistance in soft red winter wheat

Crop Science ◽  
2020 ◽  
Vol 60 (6) ◽  
pp. 2882-2900 ◽  
Author(s):  
Dylan L. Larkin ◽  
Amanda L. Holder ◽  
R. Esten Mason ◽  
David E. Moon ◽  
Gina Brown‐Guedira ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Fusarium Head Blight Resistance ◽  
Blight Resistance ◽  
Head Blight ◽  
Genome Wide Analysis ◽  
Soft Red Winter Wheat ◽  
Genome Wide ◽  
Red Winter Wheat

scholarly journals Quantifying the Effects of Fusarium Head Blight on Grain Yield and Test Weight in Soft Red Winter Wheat

2015 ◽  
Vol 105 (3) ◽  
pp. 295-306 ◽  
Author(s):  
Jorge David Salgado ◽  
Laurence V. Madden ◽  
Pierce A. Paul
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Fusarium Head Blight ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Test Weight ◽  
Head Blight ◽  
Soft Red Winter Wheat ◽  
Red Winter Wheat

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum, is known to negatively affect wheat grain yield (YLD) and test weight (TW). However, very little emphasis has been placed on formally quantifying FHB–YLD and FHB–TW relationships. Field plots of three soft red winter wheat cultivars—‘Cooper’ (susceptible to FHB), ‘Hopewell’ (susceptible), and ‘Truman’ (moderately resistant)—were grown during the 2009, 2010, 2011, and 2012 seasons, and spray inoculated with spore suspensions of F. graminearum and Parastagonospora nodorum to generate a range of FHB and Stagonospora leaf blotch (SLB) levels. FHB index (IND) and SLB were quantified as percent diseased spike and flag leaf area, respectively, and YLD (kg ha−1) and TW (kg m−3) data were collected. Using IND as a continuous covariate and cultivar (CV) and SLB as categorical fixed effects, linear mixed-model regression analyses (LMMR) were used to model the IND–YLD and IND–TW relationship and to determine whether these relationships were influenced by CV and SLB. The final models fitted to the data were of the generic form y = a + b (IND), where a (intercept) or b (slope) could also depend on other factors. LMMR analyses were also used to estimate a and b by combining the studies from these 4 years with an additional 16 experiments conducted from 2003 to 2013, and bivariate random-effects meta-analysis was used to estimate population mean b ([Formula: see text]) and a (ā) for the IND–YLD relationship. YLD and TW decreased as IND increased, with b ranging from −3.2 to −2.3 kg m−3 %−1 for TW. For the IND–YLD relationship, [Formula: see text] was −51.7 kg ha−1 %IND−1 and ā was 4,426.7 kg ha−1. Neither cultivar nor SLB affected the IND–YLD relationship but SLB affected a of the IND–TW regression lines, whereas cultivar affected b. Plots with the highest levels of SLB (based on ordinal categories for SLB) had the lowest a and Hopewell had the highest b. The level of IND at which a 50-kg m−3 reduction in TW was predicted to occur was 19, 16, and 22% for Cooper, Hopewell, and Truman, respectively. A yield loss of 1 MT ha−1 was predicted to occur at 19% IND. The rate of reduction in relative TW or YLD per unit increase in IND was between −0.39 and −0.32%−1 for TW and −1.17%−1 for YLD. Results from this study could be integrated into more general models to evaluate the economics of FHB management strategies.

GWAS for Fusarium Head Blight Traits in a Soft Red Winter Wheat Mapping Panel

Crop Science ◽  
2019 ◽  
Vol 59 (5) ◽  
pp. 1823-1837 ◽  
Author(s):  
Elisane W. Tessmann ◽  
Yanhong Dong ◽  
David A. Van Sanford
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Head Blight ◽  
Soft Red Winter Wheat ◽  
Mapping Panel ◽  
Red Winter Wheat

Registration of the Soft Red Winter Wheat Germplasm MD01W233-06-1 Resistant to Fusarium Head Blight

2010 ◽  
Vol 4 (3) ◽  
pp. 255-260 ◽  
Author(s):  
José M. Costa ◽  
Harold E. Bockelman ◽  
Gina Brown-Guedira ◽  
Sue E. Cambron ◽  
Xianming Chen ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Head Blight ◽  
Wheat Germplasm ◽  
Soft Red Winter Wheat ◽  
Red Winter Wheat

Quantitative trait loci analysis of four components of Fusarium head blight resistance in the soft red winter wheat cultivar Truman

2012 ◽  
Author(s):  
◽  
Md Sariful Islam
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Head Blight ◽  
Phenotypic Data ◽  
University Of Missouri ◽  
Components Of Resistance ◽  
Soft Red Winter Wheat ◽  
Fhb Resistance ◽  
The University ◽  
Red Winter Wheat

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Fusarium head blight (FHB) mainly caused by Fusarium graminearum Schwabe [telomorph: Gibberella zeae Schw. (Petch)] causes devastating losses in wheat globally. Host-plant resistance provides the best hope for reducing economic losses but sources of resistance are limited. "Truman" soft red winter wheat, developed and released by the University of Missouri has excellent broad-based FHB resistance. This research was conducted to identify QTL associated with five components of resistance in Truman. Two years (2 replications per year) of phenotypic data were collected on these components of resistance on a set of 167 F9 recombinant inbred lines developed from the cross Truman/MO 94-317. Genetic linkage maps were constructed using 160 single sequence repeat and 530 diversity array technology polymorphic markers. Across years, QTL for type II resistance were identified on chromosomes 1BSc, 2BL, 2DS and 3BSc; for disease incidence on 2ASc, 2DS, and 3DS; for disease severity on 2DS, and 3BSc; for Fusarium damage kernels (FDK) on 2ASc, 2DS, and 3BLc; and for low DON on 2ASc, 2DS, and 3BLc. Additional QTL for FDK were identified on 1BLc, 2ASc, and 3BLc; and for DON on 2ASc, 2DS, and 6ALc were identified from phenotypic data collected in Kentucky. The effects of identified QTL ranged from 5.0 to 30.7 % of the total phenotypic variation. Several of these QTL appear to be potentially novel and therefore should enhance FHB resistance in programs attempting to pyramid unique FHB resistance genes through marker-assisted-selection.

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