Achievements of the Zagreb Bc Institute in Winter Wheat Breeding for Resistance to Fusarium Head Blight (FHB) in Croatia

1997 ◽  
Vol 25 (3) ◽  
pp. 823-824 ◽  
Author(s):  
Slobodan Tomasovic
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Wheat Breeding ◽  
Head Blight ◽  
Breeding For Resistance

scholarly journals Identification of a Novel Genomic Region Associated With Resistance to Fusarium Head Blight in Chinese Winter Wheat

2021 ◽  
Author(s):  
Yunzhe Zhao ◽  
Xinying Zhao ◽  
Mengqi Ji ◽  
Wenqi Fang ◽  
Hong Guo ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Genome Wide Association Study ◽  
Wheat Breeding ◽  
Scab Resistance ◽  
Yield Reduction ◽  
Transferase Activity ◽  
Head Blight ◽  
A Genome ◽  
Fhb Resistance

Abstract Background: Fusarium head blight (FHB) is a disease affecting wheat spikes caused by Fusarium species, which leads to cases of severe yield reduction and seed contamination. Therefore, identifying resistance genes from various sources is always of importance to wheat breeders. In this study, a genome-wide association study (GWAS) focusing on FHB using a high-density genetic map constructed with 90K single nucleotide polymorphism (SNP) arrays in a panel of 205 elite winter wheat accessions, was conducted in 3 environments. Results: Sixty-six significant marker–trait associations (MTAs) were identified (P<0.001) on fifteen chromosomes explaining 5.4–11.2% of the phenotypic variation therein. Some important new genomic regions involving FHB resistance were found on chromosomes 2A, 3B, 5B, 6A, and 7B. On chromosome 7B, 6 MTAs at 92 genetic positions were found in 2 environments. Moreover, there were 11 MTAs consistently associated with diseased spikelet rate and diseased rachis rate as pleiotropic effect loci. Eight new candidate genes of FHB resistance were predicated in wheat. Of which, three genes: TraesCS5D01G006700, TraesCS6A02G013600, and TraesCS7B02G370700 on chromosome 5DS, 6AS, and 7BL, respectively, were important in defending against FHB by regulating chitinase activity, calcium ion binding, intramolecular transferase activity, and UDP-glycosyltransferase activity in wheat. In addition, a total of six excellent alleles associated with wheat scab resistance were discovered. Conclusion: These results provide important genes/loci for enhancing FHB resistance in wheat breeding populations by marker-assisted selection.

scholarly journals Fusarium ratings in Ontario winter wheat performance trial (OWWPT) using an index that combines Fusarium head blight symptoms and deoxynivalenol levels

2011 ◽  
Vol 47 (Special Issue) ◽  
pp. S115-S122 ◽  
Author(s):  
L. Tamburic-Ilincic ◽  
D. Falk ◽  
A. Schaafsma
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Triticum Aestivum L ◽  
Wheat Breeding ◽  
Head Blight ◽  
Sources Of Resistance ◽  
Selection Decisions ◽  
Grain Yield And Quality ◽  
Moderately Resistant ◽  
Performance Trial

Fusarium head blight (FHB) is one of the most serious diseases of wheat (Triticum aestivum L.). FHB&nbsp;reduces grain yield and quality, and the fungus produces mycotoxins, such as deoxynivalenol (DON). The most practical way to control FHB is through the development of resistant cultivars. In addition to exotic sources of resistance (such as cultivars Sumai 3 and Frontana), native sources of resistance are commonly used in winter wheat breeding programs in North America. In 1996, 2000, and 2004 severe epidemics of FHB cost the winter wheat industry in Ontario, Canada combined over $200 million. All wheat grown in Ontario is entered in the Ontario Winter Wheat Performance Trial (OWWPT) and tested every year for Fusarium resistance and DON&nbsp;level in three inoculated FHB nurseries. The objective of this study is to explain how the index that accounts for FHB&nbsp;symptoms and DON level jointly was developed, and how stable the performance of the cultivars grouped to susceptibility classes has been over a number of years. The index is related to Fusarium susceptibility classes (moderately resistant &ndash; MR, moderately susceptible &ndash; MS, susceptible &ndash; S and highly susceptible &ndash; HS), robust, stable, open-ended (old cultivars out, new cultivars in) and useful to farmers in making cultivars selection decisions. This information is available to growers and industry through the website www.gocereals.ca.

Genetic trends in Fusarium head blight resistance due to 20 years of winter wheat breeding and cooperative testing in the Northern US.

Plant Disease ◽  
2021 ◽  
Author(s):  
Rupesh Gaire ◽  
Clay Sneller ◽  
Gina Brown-Guedira ◽  
David A. Van Sanford ◽  
Mohsen Mohammadi ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Mixed Model ◽  
Fusarium Head Blight Resistance ◽  
Wheat Breeding ◽  
Vital Role ◽  
Head Blight ◽  
Genetic Progress ◽  
Fhb Resistance ◽  
Genetic Trends

Fusarium head blight (FHB) is a devastating disease of wheat and barley. In the US, a significant long-term investment in breeding FHB resistant cultivars began after the 1990s. However, to this date, no study has been performed to understand and monitor the rate of genetic progress in FHB resistance as a result of this investment. Using 20 years of data (1998 to 2018) from the Northern Uniform (NU) and Preliminarily Northern Uniform (PNU) winter wheat scab nurseries which consisted of 1068 genotypes originating from 9 different institutions, we studied the genetic trends in FHB resistance within the northern soft red winter wheat growing region using mixed model analyses. For the FHB resistance traits incidence, severity, Fusarium damaged kernels (FDK), and deoxynivalenol content, the rate of genetic gain in disease resistance was estimated to be 0.30 ± 0.1, 0.60 ± 0.09, 0.37 ± 0.11 points per year, and 0.11 ± 0.05 ppm per year, respectively. Among the five FHB resistance QTL assayed for test entries from 2012 to 2018, the frequencies of favorable alleles from Fhb 2DL Wuhan1 W14, Fhb Ernie 3Bc, and Fhb 5A Ning7840 was close to zero across the years. The frequency of the favorable at Fhb1 and Fhb 5A Ernie ranged from 0.08 to 0.33 and 0.06 to 0.20 respectively across years, and there was no trend in changes in allele frequencies over years. Overall, this study showed that substantial genetic progress has been made towards improving resistance to FHB. It is apparent that the current investment in public wheat breeding for FHB resistance is achieving results and will continue to play a vital role in reducing FHB levels in growers’ fields.

Marker-based introduction of three quantitative-trait loci conferring resistance to Fusarium head blight into an independent elite winter wheat breeding population

2008 ◽  
Vol 117 (1) ◽  
pp. 29-35 ◽  
Author(s):  
F. Wilde ◽  
C. C. Schön ◽  
V. Korzun ◽  
E. Ebmeyer ◽  
M. Schmolke ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Quantitative Trait ◽  
Breeding Population ◽  
Wheat Breeding ◽  
Head Blight ◽  
Trait Loci

Molecular Characterization of Resistance to Fusarium Head Blight in U.S. Soft Red Winter Wheat Breeding Line VA00W-38

Crop Science ◽  
2012 ◽  
Vol 52 (5) ◽  
pp. 2283-2292 ◽  
Author(s):  
Shuyu Liu ◽  
Mark D. Christopher ◽  
Carl A. Griffey ◽  
Marla D. Hall ◽  
Patty G. Gundrum ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Molecular Characterization ◽  
Wheat Breeding ◽  
Breeding Line ◽  
Head Blight ◽  
Soft Red Winter Wheat ◽  
Red Winter Wheat

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

2018 ◽  
Vol 44 (4) ◽  
pp. 505 ◽  
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

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 Automatic Evaluation of Wheat Resistance to Fusarium Head Blight Using Dual Mask-RCNN Deep Learning Frameworks in Computer Vision

2020 ◽  
Vol 13 (1) ◽  
pp. 26
Author(s):  
Wen-Hao Su ◽  
Jiajing Zhang ◽  
Ce Yang ◽  
Rae Page ◽  
Tamas Szinyei ◽  
...  
Keyword(s):  
Fusarium Head Blight ◽  
Ground Truth ◽  
Wheat Breeding ◽  
Head Blight ◽  
Detection Rates ◽  
Ground Truth Data ◽  
Resistant Cultivars ◽  
Feature Pyramid ◽  
Rater Error ◽  
Wheat Lines

In many regions of the world, wheat is vulnerable to severe yield and quality losses from the fungus disease of Fusarium head blight (FHB). The development of resistant cultivars is one means of ameliorating the devastating effects of this disease, but the breeding process requires the evaluation of hundreds of lines each year for reaction to the disease. These field evaluations are laborious, expensive, time-consuming, and are prone to rater error. A phenotyping cart that can quickly capture images of the spikes of wheat lines and their level of FHB infection would greatly benefit wheat breeding programs. In this study, mask region convolutional neural network (Mask-RCNN) allowed for reliable identification of the symptom location and the disease severity of wheat spikes. Within a wheat line planted in the field, color images of individual wheat spikes and their corresponding diseased areas were labeled and segmented into sub-images. Images with annotated spikes and sub-images of individual spikes with labeled diseased areas were used as ground truth data to train Mask-RCNN models for automatic image segmentation of wheat spikes and FHB diseased areas, respectively. The feature pyramid network (FPN) based on ResNet-101 network was used as the backbone of Mask-RCNN for constructing the feature pyramid and extracting features. After generating mask images of wheat spikes from full-size images, Mask-RCNN was performed to predict diseased areas on each individual spike. This protocol enabled the rapid recognition of wheat spikes and diseased areas with the detection rates of 77.76% and 98.81%, respectively. The prediction accuracy of 77.19% was achieved by calculating the ratio of the wheat FHB severity value of prediction over ground truth. This study demonstrates the feasibility of rapidly determining levels of FHB in wheat spikes, which will greatly facilitate the breeding of resistant cultivars.

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

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