Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia
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Star Yanxin Gao | Y. Beyene | A. Rathore | R. Varshney | S. Mccouch | K. Dreher | P. Pérez-Rodríguez | J. Crossa | Manish Roorkiwal | Xuecai Zhang | M. Gowda | P. Gaur | M. Olsen | E. Jones | C. Bharadwaj | N. Santantonio | K. Robbins | Sikiru Adeniyi Atanda | C. Ayala-Hernández | S. McCouch | Nicholas Santantonio
[1] A. Melchinger,et al. Genomic prediction with multiple biparental families , 2019, Theoretical and Applied Genetics.
[2] Star Yanxin Gao,et al. Empirical Comparison of Tropical Maize Hybrids Selected Through Genomic and Phenotypic Selections , 2019, Front. Plant Sci..
[3] J. Ribaut,et al. Modernising breeding for orphan crops: tools, methodologies, and beyond , 2019, Planta.
[4] Uwe Scholz,et al. BrAPI—an application programming interface for plant breeding applications , 2019, Bioinform..
[5] J. Cobb,et al. Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the breeder’s equation , 2019, Theoretical and Applied Genetics.
[6] Valentin Guignon,et al. Benchmarking database systems for Genomic Selection implementation , 2019, bioRxiv.
[7] J. Rutkoski. A practical guide to genetic gain , 2019, Advances in Agronomy.
[8] Yusheng Zhao,et al. Reciprocal recurrent genomic selection: an attractive tool to leverage hybrid wheat breeding , 2018, Theoretical and Applied Genetics.
[9] Hannah Ritchie,et al. Beyond Calories: A Holistic Assessment of the Global Food System , 2018, Front. Sustain. Food Syst..
[10] Jose Crossa,et al. Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea , 2018, Scientific Reports.
[11] M. Reynolds,et al. Genomic‐enabled Prediction Accuracies Increased by Modeling Genotype × Environment Interaction in Durum Wheat , 2018, The plant genome.
[12] J. Hickey,et al. Optimal cross selection for long-term genetic gain in two-part programs with rapid recurrent genomic selection , 2017, Theoretical and Applied Genetics.
[13] D. Wyse,et al. Uncovering the Genetic Architecture of Seed Weight and Size in Intermediate Wheatgrass through Linkage and Association Mapping , 2017, The plant genome.
[14] G. de los Campos,et al. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives. , 2017, Trends in plant science.
[15] A. Melchinger,et al. Genomic Prediction Within and Across Biparental Families: Means and Variances of Prediction Accuracy and Usefulness of Deterministic Equations , 2017, G3: Genes, Genomes, Genetics.
[16] A. Bentley,et al. A Two‐Part Strategy for Using Genomic Selection to Develop Inbred Lines , 2017 .
[17] Jose Crossa,et al. Increasing Genomic‐Enabled Prediction Accuracy by Modeling Genotype × Environment Interactions in Kansas Wheat , 2017, The plant genome.
[18] Shiori Yabe,et al. A Simple Package to Script and Simulate Breeding Schemes: The Breeding Scheme Language , 2017 .
[19] J. Poland,et al. Genomic Selection for Small Grain Improvement , 2017 .
[20] R. Varshney,et al. Genomic Selection for Crop Improvement , 2017, Springer International Publishing.
[21] M. Gore,et al. rAmpSeq: Using repetitive sequences for robust genotyping , 2016, bioRxiv.
[22] S. Mccouch,et al. When more is better: how data sharing would accelerate genomic selection of crop plants. , 2016, The New phytologist.
[23] Rajeev K. Varshney,et al. Genome-Enabled Prediction Models for Yield Related Traits in Chickpea , 2016, Front. Plant Sci..
[24] Gregor Gorjanc,et al. AlphaSim: Software for Breeding Program Simulation , 2016, The plant genome.
[25] José Crossa,et al. Genetic Gains in Grain Yield Through Genomic Selection in Eight Bi-parental Maize Populations under Drought Stress , 2015 .
[26] Lukas A. Mueller,et al. solGS: a web-based tool for genomic selection , 2014, BMC Bioinformatics.
[27] Ignacy Misztal,et al. Single Step, a general approach for genomic selection , 2014 .
[28] Ky L. Mathews,et al. Evaluation of genomic selection training population designs and genotyping strategies in plant breeding programs using simulation , 2014 .
[29] L. Totir,et al. Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction , 2014, Crop and Pasture Science.
[30] R. Bernardo,et al. General Combining Ability Model for Genomewide Selection in a Biparental Cross , 2014 .
[31] Jean-Luc Jannink,et al. Genomic selection in plant breeding. , 2014, Methods in molecular biology.
[32] J. Bruinsma,et al. World agriculture towards 2030/2050: the 2012 revision , 2012 .
[33] M. Goddard,et al. Using the genomic relationship matrix to predict the accuracy of genomic selection. , 2011, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.
[34] José Crossa,et al. Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers , 2010, Genetics.
[35] J. Woolliams,et al. The Impact of Genetic Architecture on Genome-Wide Evaluation Methods , 2010, Genetics.
[36] S. Robinson,et al. Food Security: The Challenge of Feeding 9 Billion People , 2010, Science.
[37] M. Goddard. Genomic selection: prediction of accuracy and maximisation of long term response , 2009, Genetica.
[38] P. VanRaden,et al. Efficient methods to compute genomic predictions. , 2008, Journal of dairy science.
[39] R. Bernardo,et al. Prospects for genomewide selection for quantitative traits in maize , 2007 .
[40] M. Goddard,et al. Prediction of total genetic value using genome-wide dense marker maps. , 2001, Genetics.
[41] A. Gilmour. ASREML for testing fixed effects and estimating multiple trait variance components. , 1997 .
[42] Robin Thompson,et al. Average information REML: An efficient algorithm for variance parameter estimation in linear mixed models , 1995 .
[43] F. Loew. Genetics and Animal Breeding , 1969 .
[44] J. Lush. GENETICS AND ANIMAL BREEDING , 1936 .