Stripe rust, induced by Puccinia striiformis f. sp. tritici, is the most harmful and prevalent disease in temperate regions worldwide, affecting wheat production areas globally. An effective strategy for controlling the disease involves enhancing genetic resistance against stripe rust, achieved through Egyptian breeding efforts not previously conducted on wheat genotypes. The resistance level to stripe rust in thirty-eight wheat genotypes was assessed using marker-assisted selection methods. The investigation suggests that wheat breeding programs can utilize slow-rusting Yr genes, which are effective resistance genes, to develop novel genotypes with stripe rust resistance through marker-assisted breeding. Based on the four disease responses of the wheat genotypes under investigation, the results categorized the genotypes into three groups. The first group included resistant genotypes, the second group exhibited a slow-rusting character with the lowest disease symptom rates, and the last group displayed the highest disease characteristics rates throughout the three seasons, comprising fast-rusting genotypes. The rust-resistant genes identified were Yr5, Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr29, Yr30, and Yr36. Genes Yr26, Yr30, and Yr36 were present in all genotypes. Genotypes Misr3, Misr4, Giza168, Giza167, Giza170, Giza171, Gemmeiza9, and Gemmeiza10 carried the Yr9 gene. Only one genotype, Sids13, was found to have the Yr17 gene. Genes Yr18 and Yr29 were identified in Sids14, Giza168, Giza170, Gemmeiza9, and Gemmeiza10. However, none of the wheat genotypes showed the presence of Yr5, Yr10, or Yr15. Several backcrossing generations were conducted to introduce the Yr5 and Yr10 genes into susceptible genotypes (Misr1, Misr2, and Gemmeiza11). These genotypes are cultivated globally and are known for producing high-quality flour, making them of great importance to farmers. The study demonstrates significant potential for enhancing wheat genotypes for stripe rust resistance and increased production.
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http://dx.doi.org/10.1186/s12870-024-05470-1 | DOI Listing |
J Agric Food Chem
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State Key Laboratory of Rice Biology and Breeding, Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Institute of Biotechnology, Zhejiang University, Hangzhou 310058, China.
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Section of Intensive Plant Food Systems, Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.
Multi-environmental trials (MET) with temporal and spatial variance are crucial for understanding genotype-environment-management (GxExM) interactions in crops. Here, we present a MET dataset for winter wheat in Germany. The dataset encompasses MET spanning six years (2015-2020), six locations and nine crop management scenarios (consisting of combinations for three treatments, unbalanced in each location and year) comparing 228 cultivars released between 1963 and 2016, amounting to a total of 526,751 data points covering 24 traits.
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January 2025
Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
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Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1432 Ås, Norway.
Unlabelled: Genomic selection-based breeding programs offer significant advantages over conventional phenotypic selection, particularly in accelerating genetic gains in plant breeding, as demonstrated by simulations focused on combating Fusarium head blight (FHB) in wheat. FHB resistance, a crucial trait, is challenging to breed for due to its quantitative inheritance and environmental influence, leading to slow progress using conventional breeding methods. Stochastic simulations in our study compared various breeding schemes, incorporating genomic selection (GS) and combining it with speed breeding, against conventional phenotypic selection.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
MOE Key Laboratory of Environment Remediation and Ecological Health, College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address:
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