The relationship between Fusarium head blight traits, thousand-kernel weight, and yield in winter wheat

A total of 126 field studies reporting deoxynivalenol (DON; ppm) content of harvested wheat grain and Fusarium head blight index (IND; field or plot-level disease severity) were analyzed to determine the overall mean regression slope and intercept for the relationship between DON and IND, and the influence of study-specific variables on the slope and intercept. A separate linear regression analysis was performed to determine the slope and intercept for each study followed by a meta-analysis of the regression coefficients from all studies. Between-study variances were significantly (P < 0.05) greater than 0, indicating substantial variation in the relationship between the variables. Regression slopes and intercepts were between -0.27 and 1.48 ppm per unit IND and -10.55 to 32.75 ppm, respectively. The overall mean regression slope and intercept, 0.22 ppm per unit IND and 2.94 ppm, respectively, were significantly different from zero (P < 0.001), and the width of the 95% confidence interval was 0.07 ppm per unit IND for slope and 1.44 ppm for intercept. Both slope and intercept were significantly affected by wheat type (P < 0.05); the overall mean intercept was significantly higher in studies conducted using winter wheat cultivars than in studies conducted using spring wheat cultivars, whereas the overall mean slope was significantly higher in studies conducted using spring wheat cultivars than in winter wheat cultivars. Study location had a significant effect on the intercept (P < 0.05), with studies from U.S. winter wheat-growing region having the highest overall mean intercept followed by studies from Canadian wheat-growing regions and U.S. spring wheat-growing regions. The study-wide magnitude of DON and IND had significant effects on one or both of the regression coefficients, resulting in considerable reduction in between-study variances. This indicates that, at least indirectly, environment affected the relationship between DON and IND.

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

Plant Health Progress ◽

10.1094/php-08-21-0111-rs ◽

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.

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Field resistance of Martonvásár winter wheat cultivars against Fusarium head blight

Acta Agronomica Hungarica ◽

10.1556/aagr.52.2004.4.4 ◽

2005 ◽

Vol 52 (4) ◽

pp. 351-359 ◽

Cited By ~ 2

Author(s):

K. Puskás ◽

G. Vida ◽

J. Komáromi ◽

O. Veisz ◽

Z. Bedő

Keyword(s):

Winter Wheat ◽

Fusarium Head Blight ◽

Yield Components ◽

Kernel Weight ◽

Field Resistance ◽

Test Weight ◽

Wheat Cultivars ◽

Head Blight ◽

Winter Wheat Cultivars ◽

Fhb Resistance

Fifty Triticum aestivum genotypes, including winter wheat cultivars from Martonvásár, were tested for fusarium head blight (FHB) resistance under artificially inoculated conditions. Field resistance, kernel infection, and the relative yield components (test weight, thousand kernel weight and kernel weight/heads) were examined following infection with Fusarium graminearum and F. culmorum isolates. Using data from two years, a number of Martonvásár varieties with above-average resistance to FHB were identified. On the basis of field infection, AUDPC values close to those of resistance sources were calculated for the variety Mv Emese, while 67.5% of the varieties tested had values which did not differ significantly from those of the control variety Arina. The yield components examined were modified substantially by artificial FHB infection. The thousand kernel weight and test weight of the variety exhibiting the greatest degree of infection were only 21.14% and 25.58%, respectively, of the untreated control. In one case the decline in the kernel weight/head was more than 90%. The results of multivariable statistical analysis indicated that among the Hungarian wheat genotypes, Bánkúti 1201, B9086-95 (a line derived from Bánkúti 1201), Mv Emese, Martonvásári4 and Mv Táltos could be grouped with the best sources of resistance. The experimental data revealed wide genetic variability for FHB resistance in the Martonvásár breeding stock.

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Improvement of Resistance of Wheat Cultivars to Fusarium Head Blight in the Yellow-Huai Rivers Valley Winter Wheat Zone with Functional Marker Selection of Fhb1 Gene

ACTA AGRONOMICA SINICA ◽

10.3724/sp.j.1006.2018.00505 ◽

2018 ◽

Vol 44 (4) ◽

pp. 505 ◽

Cited By ~ 5

Author(s):

Hong-Jun ZHANG ◽

Zhen-Qi SU ◽

Gui-Hua BAI ◽

Xu ZHANG ◽

Hong-Xiang MA ◽

...

Keyword(s):

Winter Wheat ◽

Fusarium Head Blight ◽

Functional Marker ◽

Wheat Cultivars ◽

Head Blight ◽

Marker Selection ◽

Selection Of

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Using UAV-Based Hyperspectral Imagery to Detect Winter Wheat Fusarium Head Blight

Remote Sensing ◽

10.3390/rs13153024 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3024

Author(s):

Huiqin Ma ◽

Wenjiang Huang ◽

Yingying Dong ◽

Linyi Liu ◽

Anting Guo

Keyword(s):

Winter Wheat ◽

Fusarium Head Blight ◽

Hyperspectral Imagery ◽

Spectral Feature ◽

Support Vector ◽

Detection Accuracy ◽

Feature Combination ◽

Field Scale ◽

Head Blight ◽

Detection Model

Fusarium head blight (FHB) is a major winter wheat disease in China. The accurate and timely detection of wheat FHB is vital to scientific field management. By combining three types of spectral features, namely, spectral bands (SBs), vegetation indices (VIs), and wavelet features (WFs), in this study, we explore the potential of using hyperspectral imagery obtained from an unmanned aerial vehicle (UAV), to detect wheat FHB. First, during the wheat filling period, two UAV-based hyperspectral images were acquired. SBs, VIs, and WFs that were sensitive to wheat FHB were extracted and optimized from the two images. Subsequently, a field-scale wheat FHB detection model was formulated, based on the optimal spectral feature combination of SBs, VIs, and WFs (SBs + VIs + WFs), using a support vector machine. Two commonly used data normalization algorithms were utilized before the construction of the model. The single WFs, and the spectral feature combination of optimal SBs and VIs (SBs + VIs), were respectively used to formulate models for comparison and testing. The results showed that the detection model based on the normalized SBs + VIs + WFs, using min–max normalization algorithm, achieved the highest R2 of 0.88 and the lowest RMSE of 2.68% among the three models. Our results suggest that UAV-based hyperspectral imaging technology is promising for the field-scale detection of wheat FHB. Combining traditional SBs and VIs with WFs can improve the detection accuracy of wheat FHB effectively.

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

Phytopathology ◽

10.1094/phyto-100-2-0160 ◽

2010 ◽

Vol 100 (2) ◽

pp. 160-171 ◽

Cited By ~ 69

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.

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Near-infrared versus visual sorting of Fusarium-damaged kernels in winter wheat

Canadian Journal of Plant Science ◽

10.4141/cjps08053 ◽

2008 ◽

Vol 88 (6) ◽

pp. 1087-1089 ◽

Cited By ~ 14

Author(s):

Stephen N Wegulo ◽

Floyd E Dowell

Keyword(s):

Quality Assurance ◽

Winter Wheat ◽

Fusarium Head Blight ◽

Key Words ◽

Fusarium Graminearum ◽

Near Infrared ◽

Strongly Correlated ◽

Head Blight ◽

Rater Reliability ◽

Key Words Wheat

Fusarium head blight (scab) of wheat, caused by Fusarium graminearum, often results in shriveled and/or discolored kernels, which are referred to as Fusarium-damaged kernels (FDK). FDK is a major grain grading factor and therefore is routinely determined for purposes of quality assurance. Measurement of FDK is usually done visually. Visual sorting can be laborious and is subject to inconsistencies resulting from variability in intra-rater repeatability and/or inter-rater reliability. The ability of a single-kernel near-infrared (SKNIR) system to detect FDK was evaluated by comparing FDK sorted by the system to FDK sorted visually. Visual sorting was strongly correlated with sorting by the SKNIR system (0.89 ≤ r ≤ 0.91); however, the SKNIR system had a wider range of FDK detection and was more consistent. Compared with the SKNIR system, visual raters overestimated FDK in samples with a low percentage of Fusarium-damaged grain and underestimated FDK in samples with a high percentage of Fusarium-damaged grain. Key words: Wheat, Fusarium head blight, Fusarium-damaged kernels, single-kernel near-infrared

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