Accuracy of within- and among-family genomic prediction for Fusarium head blight and Septoria tritici blotch in winter wheat

2018 ◽  
Vol 132 (4) ◽  
pp. 1121-1135 ◽  
Author(s):  
Cathérine Pauline Herter ◽  
Erhard Ebmeyer ◽  
Sonja Kollers ◽  
Viktor Korzun ◽  
Tobias Würschum ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Genomic Prediction ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Head Blight

scholarly journals Genetic architecture is more complex for resistance to Septoria tritici blotch than to Fusarium head blight in Central European winter wheat

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Vilson Mirdita ◽  
Guozheng Liu ◽  
Yusheng Zhao ◽  
Thomas Miedaner ◽  
C. Friedrich H. Longin ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Genetic Architecture ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Head Blight ◽  
Central European ◽  
European Winter Wheat

An experimental approach for estimating the genomic selection advantage for Fusarium head blight and Septoria tritici blotch in winter wheat

2019 ◽  
Vol 132 (8) ◽  
pp. 2425-2437 ◽  
Author(s):  
Cathérine Pauline Herter ◽  
Erhard Ebmeyer ◽  
Sonja Kollers ◽  
Viktor Korzun ◽  
Thomas Miedaner
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Genomic Selection ◽  
Experimental Approach ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Head Blight

scholarly journals A Microbial Fermentation Mixture Reduces Fusarium Head Blight and Promotes Grain Weight but does not impact Septoria tritici blotch

2021 ◽  
Author(s):  
Tony Twamley ◽  
Mark Gaffney ◽  
Angela Feechan
Keyword(s):  
Fusarium Head Blight ◽  
Fungal Pathogens ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Microbial Fermentation ◽  
In Planta ◽  
Head Blight ◽  
Zymoseptoria Tritici ◽  
The Impact

AbstractFusarium graminearum and Zymoseptoria tritici cause economically important diseases of wheat. F. graminearum is one of the primary causal agents of Fusarium head blight (FHB) and Z. tritici is the causal agent of Septoria tritici blotch (STB). Alternative control methods are required in the face of fungicide resistance and EU legislation which seek to cut pesticide use by 2030. Both fungal pathogens have been described as either hemibiotrophs or necrotrophs. A microbial fermentation-based product (MFP) was previously demonstrated to control the biotrophic pathogen powdery mildew, on wheat. Here we investigated if MFP would be effective against the non-biotrophic fungal pathogens of wheat, F. graminearum and Z. tritici. We assessed the impact of MFP on fungal growth, disease control and also evaluated the individual constituent parts of MFP. Antifungal activity towards both pathogens was found in vitro but MFP only significantly decreased disease symptoms of FHB in planta. In addition, MFP was found to improve the grain number and weight, of uninfected and F. graminearum infected wheat heads.

scholarly journals GWAS-Assisted Genomic Prediction to Predict Resistance to Septoria Tritici Blotch in Nordic Winter Wheat at Seedling Stage

2019 ◽  
Vol 10 ◽  
Author(s):  
Firuz Odilbekov ◽  
Rita Armoniené ◽  
Alexander Koc ◽  
Jan Svensson ◽  
Aakash Chawade
Keyword(s):  
Winter Wheat ◽  
Genomic Prediction ◽  
Seedling Stage ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici

scholarly journals Genome-Wide Association Analysis and Genomic Prediction for Adult-Plant Resistance to Septoria Tritici Blotch and Powdery Mildew in Winter Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Admas Alemu ◽  
Gintaras Brazauskas ◽  
David S. Gaikpa ◽  
Tina Henriksson ◽  
Bulat Islamov ◽  
...  
Keyword(s):  
Powdery Mildew ◽  
Winter Wheat ◽  
Plant Resistance ◽  
Genomic Prediction ◽  
Adult Plant Resistance ◽  
Genome Wide Association ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Adult Plant ◽  
Genome Wide

Septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici and powdery mildew (PM) caused by Blumeria graminis f.sp tritici (Bgt) are among the forefront foliar diseases of wheat that lead to a significant loss of grain yield and quality. Resistance breeding aimed at developing varieties with inherent resistance to STB and PM diseases has been the most sustainable and environment-friendly approach. In this study, 175 winter wheat landraces and historical cultivars originated from the Nordic region were evaluated for adult-plant resistance (APR) to STB and PM in Denmark, Estonia, Lithuania, and Sweden. Genome-wide association study (GWAS) and genomic prediction (GP) were performed based on the adult-plant response to STB and PM in field conditions using 7,401 single-nucleotide polymorphism (SNP) markers generated by 20K SNP chip. Genotype-by-environment interaction was significant for both disease scores. GWAS detected stable and environment-specific quantitative trait locis (QTLs) on chromosomes 1A, 1B, 1D, 2B, 3B, 4A, 5A, 6A, and 6B for STB and 2A, 2D, 3A, 4B, 5A, 6B, 7A, and 7B for PM adult-plant disease resistance. GP accuracy was improved when assisted with QTL from GWAS as a fixed effect. The GWAS-assisted GP accuracy ranged within 0.53–0.75 and 0.36–0.83 for STB and PM, respectively, across the tested environments. This study highlights that landraces and historical cultivars are a valuable source of APR to STB and PM. Such germplasm could be used to identify and introgress novel resistance genes to modern breeding lines.

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.

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