This article reviews the recent progress of research on fusarium head blight (FHB) of wheat. It addresses the broad areas of strategies for disease management, biological control, the pathogen (Fusarium graminearum (teleomorph Gibberella zeae)), mycotoxins, the effects of dwarfing genes on FHB severity, quantitative trait loci (QTLs) and new perspectives. Where there are recent reviews on this subject, we have deliberately examined the subsequent literature to provide an update on research. With few resistant cultivars available even now, the main tools to manage the disease remain rotation, varietal selection, disease forecasting and fungicides. A few biocontrol organisms are being considered for commercial application. The pathogen's sexual life cycle has been investigated in depth, and with its complete genome sequence known, the pathways and genes controlling the sexual development and ascospore release of F. graminearum are being explored. The 3-acetyldeoxynivalenol chemotype of F. graminear...

Overview of some recent research developments in fusarium head blight of wheat

Fusarium head blight (FHB), or scab, for its devastating nature to wheat production and food security, has stimulated worldwide attention. Multidisciplinary efforts have been made to fight against FHB for a long time, but the great progress has been achieved only in the genomics era of the past 20 years, particularly in the areas of resistance gene/QTL discovery, resistance mechanism elucidation and molecular breeding for better resistance. This review includes the following nine main sections, (1) FHB incidence, epidemic and impact, (2) causal Fusarium species, distribution and virulence, (3) types of host resistance to FHB, (4) germplasm exploitation for FHB resistance, (5) genetic control of FHB resistance, (6) fine mapping of Fhb1, Fhb2, Fhb4 and Fhb5, (7) cloning of Fhb1, (8) omics-based gene discovery and resistance mechanism study and (9) breeding for better FHB resistance. The advancements that have been made are outstanding and exciting; however, judged by the complicated nature of resistance to hemi-biotrophic pathogens like Fusarium species and lack of immune germplasm, it is still a long way to go to overcome FHB.

https://link.springer.com/content/pdf/10.1007/s00122-019-03525-8.pdf

Germplasms, genetics and genomics for better control of disastrous wheat Fusarium head blight.

In the soft red winter wheat (Triticum aestivum L.) regions of the US, Fusarium head blight (FHB, caused by Fusarium spp.) resistance derived from locally adapted germplasm has been used predominantly. Two soft red winter wheat cultivars, Massey and Ernie, have moderate resistance to FHB. Mapping populations derived from Becker/Massey (B/M) and Ernie/MO 94-317 (E/MO) were evaluated for FHB resistance and other traits in multiple environments. Eight QTL in B/M and five QTL in E/MO were associated with FHB variables including incidence, severity (SEV), index (IND), Fusarium damaged kernels (FDK), deoxynivalenol (DON), and morphological traits flowering time and plant height. Four QTL were common to both populations. Three of them were located at or near known genes: Ppd-D1 on chromosome 2DS, Rht-B1 on 4BS, and Rht-D1 on 4DS. Alleles for dwarf plant height (Rht-B1b and Rht-D1b) and photoperiod insensitivity (Ppd-D1a) had pleiotropic effects in reducing height and increasing FHB susceptibility. The other QTL detected for FHB variables were on 3BL in both populations, 1AS, 1DS, 2BL, and 4DL in B/M, and 5AL (B1) and 6AL in E/MO. The additive effects of FHB variables ranged from 0.4 mg kg−1 of DON to 6.2 % for greenhouse (GH) SEV in B/M and ranged from 0.3 mg kg−1 of DON to 8.3 % for GH SEV in E/MO. The 4DS QTL had epistasis with Ppd-D1, Qdon.umc-6AL, and Qht.umc-4BS, and additive × additive × environment interactions with the 4BS QTL for SEV, IND, and FDK in E/MO. Marker-assisted selection might be used to enhance FHB resistance through selection of favorable alleles of significant QTL, taking into account genotypes at Rht-B1b, Rht-D1a and Ppd-D1a.

Electronic supplementary material
The online version of this article (doi:10.1007/s00122-013-2149-y) contains supplementary material, which is available to authorized users.

/pdf/molecular-characterization-of-field-resistance-to-fusarium-4apgdg2cr0.pdf

Molecular characterization of field resistance to Fusarium head blight in two US soft red winter wheat cultivars

Genomic selection has the potential to increase genetic gains by using molecular markers as predictors of breeding values of individuals. This study evaluated the accuracy of predictions for grain yield, heading date, plant height, and yield components in soft red winter wheat under different prediction scenarios. Response to selection for grain yield was also compared across different selection strategies- phenotypic, marker-based, genomic, combination of phenotypic and genomic, and random selections. Genomic selection was implemented through a ridge regression best linear unbiased prediction model in two scenarios- cross-validations and independent predictions. Accuracy for cross-validations was assessed using a diverse panel under different marker number, training population size, relatedness between training and validation populations, and inclusion of fixed effect in the model. The population in the first scenario was then trained and used to predict grain yield of biparental populations for independent validations. Using subsets of significant markers from association mapping increased accuracy by 64–70% for grain yield but resulted in lower accuracy for traits with high heritability such as plant height. Increasing size of training population resulted in an increase in accuracy, with maximum values reached when ~ 60% of the lines were used as a training panel. Predictions using related subpopulations also resulted in higher accuracies. Inclusion of major growth habit genes as fixed effect in the model caused increase in grain yield accuracy under a cross-validation procedure. Independent predictions resulted in accuracy ranging between − 0.14 and 0.43, dependent on the grouping of site-year data for the training and validation populations. Genomic selection was “superior” to marker-based selection in terms of response to selection for yield. Supplementing phenotypic with genomic selection resulted in approximately 10% gain in response compared to using phenotypic selection alone. Our results showed the effects of different factors on accuracy for yield and agronomic traits. Among the factors studied, training population size and relatedness between training and validation population had the greatest impact on accuracy. Ultimately, combining phenotypic with genomic selection would be relevant for accelerating genetic gains for yield in winter wheat.

/pdf/accuracy-of-genomic-selection-for-grain-yield-and-agronomic-3vtnf5g07r.pdf

Accuracy of genomic selection for grain yield and agronomic traits in soft red winter wheat

In agricultural commodities, the occurrence of deoxynivalenol (DON) has been reported all over the world, with levels varying among grain types and years of production. The grain supply chain, including growers, buyers, and end users, have effectively managed DON with strategies to control this issue systematically. The safety of consumers is ensured through use of these management strategies. This is observed in this review of the North American systems. This article describes the occurrence and management of DON in North America, which is accomplished by 1) a review of the toxicological effects of DON; 2) a review of publically available data and introduction of new information regarding the occurrence of DON in wheat, maize, and barley in North America, including variability due to growing regions, grain varieties, and year of production; 3) an overview of industry practices to reduce DON contamination from field through milling when necessary; 4) a review of how all in the value chain, including growe...

http://mycored.eu/download/2209/cfw-60-1-0032-ep.pdf

DON Occurrence in Grains: A North American Perspective

Registration of 'Truman' wheat

Journal of Plant Registrations, Vol 1, May–June 2007 21 Uses of Axcella 2 will include overseeding of warm-season turfgrass, home lawns, sports fi elds, and on some golf courses for fairways and rough areas. Axcella 2 will also be useful to reduce erosion during the cool-season on seeded lawns before the establishment of warm-season turf. It is projected that Axcella 2 will also have advantages over forage-type annual ryegrass in road-side erosion control because of less mowing requirement and less competition (canopy height) with wild fl owers. Range of adaptation for cool-season planting will be in the lower south of the USA or possibly as a temporary ground cover or nurse grass during the summer in the northern USA. Seed production will be in Oregon. Breeder seed of Axcella 2 will be maintained by TAES. DLFInternational Seeds has an exclusive license for production of a licensed cultivar as Foundation Class Seed Stock and to produce and sell Axcella 2 as a licensed product. U.S. Plant Variety Protection will be fi led for Axcella 2. All seed requests should be sent to the corresponding author during the period of Protection by the Plant Variety Protection Certifi cate. Seed of this release is deposited in the National Plant Germplasm System where it will be available after the expiry of the Plant Variety Protection for research purposes, including development and commercialization of new cultivars. It is requested that appropriate recognition be made if the germplasm contributes to the development of new germplasm or cultivars.

Registration of ‘Bess’ Wheat

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

R. L. Wright

Author Tools

Chat about Author

Papers

Registration of 'Truman' wheat

Registration of ‘Bess’ Wheat