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Near‐infrared reflectance spectroscopy phenomic prediction can perform similarly to genomic prediction of maize agronomic traits across environments.
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- Plant Genome, 2024, v. 17, n. 2, p. 1, doi. 10.1002/tpg2.20454
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- Article
Genome‐wide scanning to identify and validate single nucleotide polymorphism markers associated with drought tolerance in spring wheat seedlings.
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- Plant Genome, 2024, v. 17, n. 2, p. 1, doi. 10.1002/tpg2.20444
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- Article
Utilizing genomic prediction to boost hybrid performance in a sweet corn breeding program.
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- Frontiers in Plant Science, 2024, p. 1, doi. 10.3389/fpls.2024.1293307
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- Article
Simulations of multiple breeding strategy scenarios in common bean for assessing genomic selection accuracy and model updating.
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- Plant Genome, 2024, v. 17, n. 1, p. 1, doi. 10.1002/tpg2.20388
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- Article
Assessing the Genotype-by-Environment G×E Interaction in Desi Chickpea via the Bayesian Additive Main Effects and Multiplicative Interaction Model.
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- Agriculture; Basel, 2024, v. 14, n. 2, p. 215, doi. 10.3390/agriculture14020215
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- Article
Improving predictive ability in sparse testing designs in soybean populations.
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- Frontiers in Genetics, 2023, p. 1, doi. 10.3389/fgene.2023.1269255
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- Article
Genetic architecture of soybean tolerance to off-target dicamba.
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- Frontiers in Plant Science, 2023, p. 1, doi. 10.3389/fpls.2023.1230068
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- Article
Phenomic data-driven biological prediction of maize through field-based high-throughput phenotyping integration with genomic data.
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- Journal of Experimental Botany, 2023, v. 74, n. 17, p. 5307, doi. 10.1093/jxb/erad216
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CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for maize phenotype predictability in the United States and Canada.
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- Earth System Science Data, 2023, v. 15, n. 9, p. 3963, doi. 10.5194/essd-15-3963-2023
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- Article
Genomic prediction for complex traits across multiples harvests in alfalfa (Medicago sativa L.) is enhanced by enviromics.
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- Plant Genome, 2023, v. 16, n. 2, p. 1, doi. 10.1002/tpg2.20306
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- Article
Branch angle and leaflet shape are associated with canopy coverage in soybean.
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- Plant Genome, 2023, v. 16, n. 2, p. 1, doi. 10.1002/tpg2.20304
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Integrating and optimizing genomic, weather, and secondary trait data for multiclass classification.
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- Frontiers in Genetics, 2023, v. 14, p. 1, doi. 10.3389/fgene.2022.1032691
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- Article
Genomic selection performs as effectively as phenotypic selection for increasing seed yield in soybean.
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- Plant Genome, 2023, v. 16, n. 1, p. 1, doi. 10.1002/tpg2.20285
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Comparing artificial‐intelligence techniques with state‐of‐the‐art parametric prediction models for predicting soybean traits.
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- Plant Genome, 2023, v. 16, n. 1, p. 1, doi. 10.1002/tpg2.20263
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- Article
CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for Maize phenotype predictability in the U.S. and Canada.
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- Earth System Science Data Discussions, 2023, p. 1, doi. 10.5194/essd-2023-11
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- Article
Simulations of rate of genetic gain in dry bean breeding programs.
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- Theoretical & Applied Genetics, 2023, v. 136, n. 1, p. 1, doi. 10.1007/s00122-023-04244-x
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Erratum to: Relative utility of agronomic, phenological, and morphological traits for assessing genotype‐by‐environment interaction in maize inbreds.
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- Crop Science, 2022, v. 62, n. 6, p. 2568, doi. 10.1002/csc2.20860
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- Article
Identification of Disease Resistance Parents and Genome-Wide Association Mapping of Resistance in Spring Wheat.
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- Plants (2223-7747), 2022, v. 11, n. 21, p. 2905, doi. 10.3390/plants11212905
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Evaluating dimensionality reduction for genomic prediction.
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- Frontiers in Genetics, 2022, v. 13, p. 1, doi. 10.3389/fgene.2022.958780
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Optimizing predictions in IRRI's rice drought breeding program by leveraging 17 years of historical data and pedigree information.
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- Frontiers in Plant Science, 2022, v. 13, p. 1, doi. 10.3389/fpls.2022.983818
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- Article
Incorporation of Soil-Derived Covariates in Progeny Testing and Line Selection to Enhance Genomic Prediction Accuracy in Soybean Breeding.
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- Frontiers in Genetics, 2022, v. 13, p. 1, doi. 10.3389/fgene.2022.905824
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Climate and genetic data enhancement using deep learning analytics to improve maize yield predictability.
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- Journal of Experimental Botany, 2022, v. 73, n. 15, p. 5336, doi. 10.1093/jxb/erac146
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- Article
Identification of Spring Wheat with Superior Agronomic Performance under Contrasting Nitrogen Managements Using Linear Phenotypic Selection Indices.
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- Plants (2223-7747), 2022, v. 11, n. 14, p. N.PAG, doi. 10.3390/plants11141887
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- Article
Differential responses of soybean genotypes to off‐target dicamba damage.
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- Crop Science, 2022, v. 62, n. 4, p. 1472, doi. 10.1002/csc2.20757
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- Article
Genomic Prediction Accuracy of Stripe Rust in Six Spring Wheat Populations by Modeling Genotype by Environment Interaction.
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- Plants (2223-7747), 2022, v. 11, n. 13, p. 1736, doi. 10.3390/plants11131736
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- Article
Enhancing Genomic Prediction Models for Forecasting Days to Maturity in Soybean Genotypes Using Site-Specific and Cumulative Photoperiod Data.
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- Agriculture; Basel, 2022, v. 12, n. 4, p. N.PAG, doi. 10.3390/agriculture12040545
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- Article
Genomic Predictions for Common Bunt, FHB, Stripe Rust, Leaf Rust, and Leaf Spotting Resistance in Spring Wheat.
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- Genes, 2022, v. 13, n. 4, p. 565, doi. 10.3390/genes13040565
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- Article
Differentiate Soybean Response to Off-Target Dicamba Damage Based on UAV Imagery and Machine Learning.
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- Remote Sensing, 2022, v. 14, n. 7, p. 1618, doi. 10.3390/rs14071618
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- Article
Genome-based prediction of agronomic traits in spring wheat under conventional and organic management systems.
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- Theoretical & Applied Genetics, 2022, v. 135, n. 2, p. 537, doi. 10.1007/s00122-021-03982-0
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- Article
Genome‐enabled prediction for sparse testing in multi‐environmental wheat trials.
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- Plant Genome, 2021, v. 14, n. 3, p. 1, doi. 10.1002/tpg2.20151
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- Article
Development of a Genomic Prediction Pipeline for Maintaining Comparable Sample Sizes in Training and Testing Sets across Prediction Schemes Accounting for the Genotype-by-Environment Interaction.
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- Agriculture; Basel, 2021, v. 11, n. 10, p. 932, doi. 10.3390/agriculture11100932
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- Article
An Assessment of the Factors Influencing the Prediction Accuracy of Genomic Prediction Models Across Multiple Environments.
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- Frontiers in Genetics, 2021, v. 12, p. 1, doi. 10.3389/fgene.2021.689319
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- Article
Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield Within the Genomes to Fields Maize Project.
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- Frontiers in Genetics, 2021, v. 11, p. N.PAG, doi. 10.3389/fgene.2020.592769
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- Article
Modeling spatial trends and enhancing genetic selection: An approach to soybean seed composition breeding.
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- Crop Science, 2021, v. 61, n. 2, p. 976, doi. 10.1002/csc2.20364
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Genome-Wide Association Mapping and Genomic Prediction of Anther Extrusion in CIMMYT Hybrid Wheat Breeding Program via Modeling Pedigree, Genomic Relationship, and Interaction With the Environment.
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- Frontiers in Genetics, 2020, v. 11, p. N.PAG, doi. 10.3389/fgene.2020.586687
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Genome-based trait prediction in multi- environment breeding trials in groundnut.
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- Theoretical & Applied Genetics, 2020, v. 133, n. 11, p. 3101, doi. 10.1007/s00122-020-03658-1
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Coupling day length data and genomic prediction tools for predicting time-related traits under complex scenarios.
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- Scientific Reports, 2020, v. 10, n. 1, p. 1, doi. 10.1038/s41598-020-70267-9
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- Article
Prediction Strategies for Leveraging Information of Associated Traits under Single- and Multi-Trait Approaches in Soybeans.
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- Agriculture; Basel, 2020, v. 10, n. 8, p. 308, doi. 10.3390/agriculture10080308
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- Article
Genomic Prediction Enhanced Sparse Testing for Multi-environment Trials.
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- G3: Genes | Genomes | Genetics, 2020, v. 10, n. 8, p. 2725, doi. 10.1534/g3.120.401349
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- Article
Variance heterogeneity genome‐wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions.
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- Plant Genome, 2020, v. 13, n. 1, p. 1, doi. 10.1002/tpg2.20011
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- Article
Maize genomes to fields (G2F): 2014–2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets.
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- BMC Research Notes, 2020, v. 13, n. 1, p. 1, doi. 10.1186/s13104-020-4922-8
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- Article
Enhancing Hybrid Prediction in Pearl Millet Using Genomic and/or Multi-Environment Phenotypic Information of Inbreds.
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- Frontiers in Genetics, 2020, v. 10, p. 1, doi. 10.3389/fgene.2019.01294
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- Article
Relative utility of agronomic, phenological, and morphological traits for assessing genotype‐by‐environment interaction in maize inbreds.
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- Crop Science, 2020, v. 60, n. 1, p. 62, doi. 10.1002/csc2.20035
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- Publication type:
- Article
Comparison of array‐ and sequencing‐based markers for genome‐wide association mapping and genomic prediction in spring wheat.
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- Crop Science, 2020, v. 60, n. 1, p. 211, doi. 10.1002/csc2.20098
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- Article
Deep Kernel and Deep Learning for Genome-Based Prediction of Single Traits in Multienvironment Breeding Trials.
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- Frontiers in Genetics, 2019, v. 10, p. 1, doi. 10.3389/fgene.2019.01168
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- Article
Genome-Wide Association and Gene Co-expression Network Analyses Reveal Complex Genetics of Resistance to Goss's Wilt of Maize.
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- G3: Genes | Genomes | Genetics, 2019, v. 9, n. 10, p. 3139, doi. 10.1534/g3.119.400347
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- Article
Joint Use of Genome, Pedigree, and Their Interaction with Environment for Predicting the Performance of Wheat Lines in New Environments.
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- G3: Genes | Genomes | Genetics, 2019, v. 9, n. 9, p. 2925, doi. 10.1534/g3.119.400508
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- Article
Genomic Prediction Using Canopy Coverage Image and Genotypic Information in Soybean via a Hybrid Model.
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- Evolutionary Bioinformatics, 2019, v. 15, p. N.PAG, doi. 10.1177/1176934319840026
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- Article
Response Surface Analysis of Genomic Prediction Accuracy Values Using Quality Control Covariates in Soybean.
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- Evolutionary Bioinformatics, 2019, v. 15, p. N.PAG, doi. 10.1177/1176934319831307
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- Article
Genomic Prediction Using Canopy Coverage Image and Genotypic Information in Soybean via a Hybrid Model.
- Published in:
- Evolutionary Bioinformatics, 2019, p. 1, doi. 10.1177/1176934319840026
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- Publication type:
- Article