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research area of

• BURGUEÑO FERREIRA, Juan Andres, Senior Biometrician / Head of BSU, CIMMYT, CIMMYT
• DREISIGACKER, Susanne, Wheat Molecular Breeding, CIMMYT, CIMMYT
• Fritsche Neto, Roberto, University of Sao Paulo
• JULIANA, Philomin, Associate Scientist - Bread Wheat Breeder, CIMMYT, CIMMYT
• PEREZ RODRIGUEZ, Paulino, Consultant, CIMMYT, CIMMYT
• RIBAUT, Jean-Marcel, Program Director, Integrated Breeding Platform, CIMMYT, CIMMYT
• van Etten, Jacob, Lever Director, The Alliance of Bioversity International and CIAT, The Alliance of Bioversity and CIAT
• You, Liangzhi, Senior Research Fellow, IFPRI, IFPRI

subject area of

• A Benchmarking Between Deep Learning, Support Vector Machine and Bayesian Threshold Best Linear Unbiased Prediction for Predicting Ordinal Traits in Plant Breeding.
• A Genomic Selection Index Applied to Simulated and Real Data
• A Hierarchical Bayesian Estimation Model for Multienvironment Plant Breeding Trials in Successive Years
• A Minimum Set of Soil Indicators for the Semi-Arid Rangeland Productivity Assessment
• A Proposal to Estimate the Variable Importance Measures in Predictive Models Using Results from a Wrapper
• A REVIEW OF ROADS DATA DEVELOPMENT METHODOLOGIES
• A Selection Index Method Based on Eigenanalysis
• A method for combining molecular markers and phenotypic attributes for classifying plant genotypes
• Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat
• An imputation platform to enhance integration of rice genetic resources.
• Analysis and Interpretation of Interactions in Agricultural Research
• Analysis of multi-temporal SPOT NDVI images for small-scale land-use mapping
• Approximate Genome-Based Kernel Models for Large Data Sets Including Main Effects and Interactions.
• Bayesian Genomic-Enabled Prediction as an Inverse Problem
• Bayesian Markov Chain Random Field Cosimulation for Improving Land Cover Classification Accuracy
• Classifying genetic resources by categorical and continuous variables
• Comparative Map and Trait Viewer (CMTV): an integrated bioinformatic tool to construct consensus maps and compare QTL and functional genomics data across genomes and experiments
• Cropland for sub-Saharan Africa: A synergistic approach using five land cover data sets
• Current Status and Future Prospects of Next-Generation Data Management and Analytical Decision Support Tools for Enhancing Genetic Gains in Crops
• Deep Kernel and Deep Learning for Genome-Based Prediction of Single Traits in Multienvironment Breeding Trials.
• Deep Kernel for Genomic and Near Infrared Predictions in Multi-environment Breeding Trials.
• Distribution and asymptotic behavior of the phylogenetic transfer distance
• Ecosystem analysis-based methodology for technology extrapolation
• Ensemble species distribution modelling with transformed suitability values
• Evaluation and Interpretation of Interactions
• From global to local: Testing the potential of cross-scaling in global data sets
• Generalizing the sites regression model to three-way interaction including multi-attributes.
• Genome-based prediction of multiple wheat quality traits in multiple years.
• Genomic Prediction in Animals and Plants: Simulation of Data, Validation, Reporting and Benchmarking
• Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models
• Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials.
• Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.
• Genomic-enabled prediction with classification algorithms.
• Genotype phasing in populations of closely related individuals.
• Geography of international water conflict and cooperation: Data sets and applications
• Improving Gene Regulatory Network Inference by Incorporating Rates of Transcriptional Changes.
• Incorporating regional knowledge into global data sets: Some ideas for rice in Asia
• Incorporating the Rate of Transcriptional Change Improves Construction of Gene Regulatory Networks
• Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.
• Land Use Change with Spatially Explicit Data: A Dynamic Approach
• Mapping rice areas of South Asia using MODIS multitemporal data
• Mixed model with spatial variance-covariance structure for accommodating of local stationary trend and its influence on multi-environmental crop variety trial assessment
• Modelling rankings in R: the PlackettLuce package
• Modelling rankings in R: the PlackettLuce package
• Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture.
• Multi-temporal yield pattern analysis method for deriving yield zones in crop production systems
• Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits
• Multimodel ensembles improve predictions of crop-environment-management interactions.
• Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials.
• Pre-treatment of soil X-ray powder diffraction data for cluster analysis
• Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems.
• Regression‐Based Evaluation of Ecophysiological Models
• The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0)
• The Modified Location Model for Classifying Genetic Resources
• Using Factor Analytic Models for Joining Environments and Genotypes without Crossover Genotype × Environment Interaction