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Vanika Garg Rutwik Barmukh Manish Roorkiwal Chris Ojiewo Abhishek Bohra MAHENDAR THUDI Vikas Kumar Singh Himabindu Kudapa Reyaz Mir Chellapilla Bharadwaj Xin Liu Manish Pandey (2024, [Artículo])
Agricultural Biotechnology Crop Genomics Genome Sequencing CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOTECHNOLOGY CROPS GENOMICS PLANT BREEDING AGRICULTURE GENETIC IMPROVEMENT
Genomic prediction of hybrid crops accounting for non additive genetic effects
David González-Diéguez (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION HYBRIDS MAIZE GENOMES GENETICS GENETIC VARIANCE CROPS
Genome-based predictions of sub-genome genetic interactions effects in wheat populations
David González-Diéguez (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOMES WHEAT GENETICS MARKER-ASSISTED SELECTION GENETIC VARIANCE HYBRIDS
Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])
Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to
the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding
Alison Bentley Charles Chen Nunzio D'Agostino (2022, [Artículo])
Allele Mining High-Throughput Phenotyping Genomic Estimated Breeding Value CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP IMPROVEMENT DNA CHROMOSOME MAPPING GENETIC LINKAGE GENOMES GENOTYPING GERMINATION HEAT STRESS QUALITY CONTROL SINGLE NUCLEOTIDE POLYMORPHISM TRITICUM AESTIVUM GENETIC DIVERSITY (AS RESOURCE) HIGH-THROUGHPUT SEQUENCING
Abdelfattah DABABAT Yong Suk Chung (2023, [Artículo])
Biological Indexing Sequencing Analysis Citrus Orchards CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PHYLOGENETIC ANALYSIS CITRUS RNA DNA
Applications of in vitro tissue culture technologies in breeding and genetic improvement of wheat
Akila Wijerathna-Yapa BHOJA BASNET (2022, [Artículo])
Wheat Biotechnology Genome Editing Cas9 CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CRISPR GENE EDITING TISSUE CULTURE WHEAT BIOTECHNOLOGY
Shailendra Sharma deepmala sehgal Apekshita Singh Shailendra Goel SoomNath Raina (2022, [Artículo])
Corona Viruses Genome Structure Novel Mutations Resistance to Vaccines SARS-CoV-2 CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA COVID-19 ANTIBODY FORMATION LIFE CYCLE VACCINATION VACCINES LINEAGE
Wheat seed demand assessment assisted by genotyping in Ethiopia
Moti Jaleta Kindie Tesfaye Olaf Erenstein (2023, [Artículo])
This study examines the extent to which wheat varieties supplied by the formal seed system align with the varieties demanded and used by farmers in Ethiopia. The framework of stated and revealed preferences drawn from the consumer preference theory is used to analyze farmer demand for different wheat varieties. We used official data from the formal seed sector and representative survey data from wheat farm households in Ethiopia. The survey data allow to contrast the farmer reported varietal use with genotyping by sequencing (also known as DNA fingerprinting). Farmers' reliance on informal seed sources and own saved seed, among others, contributes to the misidentification of the varieties they grow. Consequently, farmers are likely to misinform the formal seed demand assessment leading to either an over- or underestimation of actual seed demand for specific wheat varieties. Genotyping by sequencing, as opposed to farmer reports, established the persistence of old varieties. This also implies vulnerability of wheat production to disease dynamics depending on the longevity of disease resistance by the variety in use. Apart from narrowing the gap between the actual and stated demand and ensuring timely replacement of wheat varieties, genotyping-assisted estimates can save seed carry-over cost. Genotyping by sequencing is increasingly used as the new benchmark and gold standard for identifying and tracking the adoption of crop varieties. The technique has potential to enhance the performance of the seed sector through effective planning that can optimize resource commitments and accelerate the rate of varietal replacement.
Seed Demand Varietal Replacement CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPING-BY-SEQUENCING SEEDS WHEAT