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Stage-gate advancement process in maize breeding
Berhanu Tadesse Ertiro (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT BREEDING MAIZE TESTING
E. African spring wheat breeding pipeline and Network (CIMMYT-KALRO)
sridhar bhavani (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PLANT BREEDING RESEARCH NETWORKS
Principles of field experimentation
Berhanu Tadesse Ertiro (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FIELD EXPERIMENTATION EXPERIMENTAL DESIGN RANDOMIZED BLOCK DESIGN LATTICE DESIGN PLANT BREEDING
Efficacy of plant breeding using genomic information
Osval Antonio Montesinos-Lopez Alison Bentley Carolina Saint Pierre Leonardo Abdiel Crespo Herrera Morten Lillemo Jose Crossa (2023, [Artículo])
Genomic Selection Genomic Prediction Genomic Best Linear Unbiased Predictor CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT BREEDING GENOMICS MARKER-ASSISTED SELECTION ENVIRONMENT
Visualising the pattern of long-term genotype performance by leveraging a genomic prediction model
Vivi Arief Ian Delacy Thomas Payne Kaye Basford (2022, [Artículo])
Factor Analytic Genotype-By-Year Historical Data Relationship Matrix CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPES PLANT BREEDING SPRING WHEAT RESEARCH
Francisco Pinto Matthew Paul Reynolds Robert Furbank (2024, [Artículo])
Deep Learning Object-Based Image Analysis Optical Imagery CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE IMAGE ANALYSIS PLANT BREEDING REMOTE SENSING MACHINE LEARNING
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
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
Sowing the wheat seeds of Afghanistan's future
Nigel Poole Rajiv Sharma Orzala Nemat Jason Donovan Alison Bentley (2022, [Artículo])
Humanitarian Intervention CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FOOD SECURITY IRRIGATION NUTRITION PLANT BREEDING SEED SYSTEMS
The generation challenge programme platform: Semantic standards and workbench for crop science
Richard Bruskiewich Guy Davenport Mathieu Rouard Reinhard Simon Samart Wanchana Trushar Shah Victor Jun Ulat Andrew Farmer Pankaj Jaiswal Mark Wilkinson David Marshall Alyssa Collins (2008, [Artículo])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP IMPROVEMENT GENETIC RESOURCES PLANT BREEDING BIODIVERSITY COMPUTER APPLICATIONS DIGITAL TECHNOLOGY DATA PROCESSING