about
Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.DHOEM: a statistical simulation software for simulating new markers in real SNP marker data.Genome-wide association analysis for heat tolerance at flowering detected a large set of genes involved in adaptation to thermal and other stresses.Genome-wide association mapping of root traits in a japonica rice panel.Editorial: Natural diversity in the new millennium.The roots of future rice harvests.Association mapping of resistance to rice blast in upland field conditions.The promoter of a metallothionein-like gene from the tropical tree Casuarina glauca is active in both annual dicotyledonous and monocotyledonous plants.A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice.Genome-wide association mapping for root cone angle in rice.Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations.Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations.Rice diversity panel provides accurate genomic predictions for complex traits in the progenies of biparental crosses involving members of the panel.Tolerance to mild salinity stress in japonica rice: A genome-wide association mapping study highlights calcium signaling and metabolism genes.Genomic Prediction Accounting for Genotype by Environment Interaction Offers an Effective Framework for Breeding Simultaneously for Adaptation to an Abiotic Stress and Performance Under Normal Cropping Conditions in Rice.Genetic Analysis of Water Use Efficiency in Rice (Oryza sativa L.) at the Leaf LevelSelection of trait-specific markers and multi-environment models improve genomic predictive ability in riceTargeted association analysis identified japonica rice varieties achieving Na(+)/K (+) homeostasis without the allelic make-up of the salt tolerant indica variety Nona BokraGenomic prediction offers the most effective marker assisted breeding approach for ability to prevent arsenic accumulation in rice grains
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description
Frans onderzoeker
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researcher ORCID ID = 0000-0003-0072-6285
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Nourollah Ahmadi
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Nourollah Ahmadi
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Nourollah Ahmadi
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Nourollah Ahmadi
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Nourollah AHMADI
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Nourollah Ahmadi
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Nourollah Ahmadi
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0000-0003-0072-6285
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nourollah-ahmadi-8b130789