Quantification of the relationship between the environment and Fusarium head blight, Fusarium pathogen density, and mycotoxins in winter wheat in Europe

2012 ◽  
Vol 133 (4) ◽  
pp. 975-993 ◽  
Author(s):  
Alissa B. Kriss ◽  
Pierce A. Paul ◽  
Xiangming Xu ◽  
Paul Nicholson ◽  
Fiona M. Doohan ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Head Blight ◽  
The Relationship

scholarly journals Meta-Analysis of Regression Coefficients for the Relationship Between Fusarium Head Blight and Deoxynivalenol Content of Wheat

2006 ◽  
Vol 96 (9) ◽  
pp. 951-961 ◽  
Author(s):  
P. A. Paul ◽  
P. E. Lipps ◽  
L. V. Madden
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Spring Wheat ◽  
Meta Analysis ◽  
Regression Coefficients ◽  
Wheat Cultivars ◽  
Head Blight ◽  
Regression Slope ◽  
Winter Wheat Cultivars ◽  
The Relationship

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.

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

2022 ◽  
Vol 79 (3) ◽  
Author(s):  
Radivoje Jevtić ◽  
Nina Skenderović ◽  
Vesna Župunski ◽  
Mirjana Lalošević ◽  
Branka Orbović ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Kernel Weight ◽  
Head Blight ◽  
Thousand Kernel Weight ◽  
The Relationship

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

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.

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.

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

2008 ◽  
Vol 88 (6) ◽  
pp. 1087-1089 ◽  
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

Mapping of quantitative trait loci for field resistance to Fusarium head blight in an European winter wheat

2002 ◽  
Vol 106 (6) ◽  
pp. 961-970 ◽  
Author(s):  
L. Gervais ◽  
F. Dedryver ◽  
J.-Y. Morlais ◽  
V. Bodusseau ◽  
S. Negre ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Quantitative Trait ◽  
Field Resistance ◽  
Head Blight ◽  
Trait Loci ◽  
European Winter Wheat

scholarly journals Disease Risk, Spatial Patterns, and Incidence-Severity Relationships of Fusarium Head Blight in No-till Spring Wheat Following Maize or Soybean

Plant Disease ◽  
2015 ◽  
Vol 99 (10) ◽  
pp. 1360-1366 ◽  
Author(s):  
Pierri Spolti ◽  
Denis A. Shah ◽  
José Maurício C. Fernandes ◽  
Gary C. Bergstrom ◽  
Emerson M. Del Ponte
Keyword(s):  
Fusarium Head Blight ◽  
Large Scale ◽  
Disease Risk ◽  
Random Pattern ◽  
Southern Brazil ◽  
Head Blight ◽  
Previous Crop ◽  
Regional Sources ◽  
Epidemiological Surveys ◽  
The Relationship

The first large-scale survey of Fusarium head blight (FHB) in commercial wheat fields in southern Brazil was conducted over three years (2009 to 2011). The objectives were to: (i) evaluate whether increased FHB risk is associated with within-field maize residue; (ii) determine the spatial pattern of FHB incidence; and (iii) quantify the relationship between FHB incidence and severity. FHB was assessed in a total of 160 fields between early milk and dough. Incidence ranged from 1.0 to 89.9% (median = 25%) and severity from 0.02 to 18.6% (median = 1.3%). FHB risk was neither lower nor higher in wheat following maize than in wheat following soybean. Only 18% of fields were classified as having aggregated patterns of FHB-symptomatic spikes. A binary power law description of the variances was consistent with an overall random pattern of the disease. These results conform with the hypothesis that FHB epidemics in southern Brazil are driven by sufficient atmospherically-transported inoculum from regional sources. The incidence-severity relationship was coherent across growing season, growth stage, and previous crop; one common fitted curve described the relationship across all observations. Estimating severity from incidence may be useful in reducing the workload in epidemiological surveys.

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