› eQTLs are key players in the integration of genomic and transcriptomic data for phenotype prediction - Vincent Segura
10:00-10:15 (15min)
› Integration of DNA methylation and transcriptome data im-proves complex trait prediction in Hordeum vulgare - Pernille Bjarup Hansen, Center for Quantitative Genetics and Genomics, Aarhus University, 4200 Slagelse
10:15-10:30 (15min)
› Phenomic Selection in a structured hybrid rapeseed population using near-infrared reflectance spectroscopy - Lennard Ehrig, Department of Plant Breeding, Justus Liebig University Giessen
10:30-10:45 (15min)
› Beyond QTL effects in quantitative genetics: comparative genomics and machine learning techniques for prediction across populations - Guillaume Ramstein, Aarhus University
10:45-11:00 (15min)
› Genomic selection using information on multiple phenotypic traits and multiple growing environments - Jon BANCIC, The Roslin Institute
14:15-14:30 (15min)
› Analysis of longitudinal, image-based canopy cover estimates as a quality indicator in wheat variety trials - Jip Ramakers, Wageningen University and Research
14:30-14:45 (15min)
› Illuminating and enhancing wheat breeders' eyes based decisions with drone-based phenomic predictions - Lukas Roth, ETH Zurich, Institute of Agricultural Sciences
14:45-15:00 (15min)
› Genetic Factor-Analytic BLUP for Improved Genomic Prediction with High-Dimensional Secondary Traits - Jonathan Kunst, Biometris, Wageningen University and Research
15:00-15:15 (15min)
› Quantifying the Drivers of Genetic Change in Plant Breeding - Thiago Oliveira, The University of Edinburgh
16:30-16:45 (15min)
› Comparison of genomic enabled cross selection criteria for the improvement of inbred line populations - Alice Danguy des Déserts, Syngenta
16:45-17:00 (15min)
› Improving the use of plant genetic resources to sustain breeding programs efficiency - Dimitri SANCHEZ, Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale), LIDEA
17:00-17:15 (15min)
› Artificial intelligence guided allele stacking to develop high yielding, highly resistant varieties - Kai Voss-Fels, Geisenheim University, University of Queensland
17:15-17:30 (15min)
› IBD-based mixed model approaches for genetic studies in multi-parent populations (MPPs): additive, epistatic, and QTL-by-environment effects - Wenhao Li, Wageningen University & Research
09:15-09:30 (15min)
› Defining the causes and consequences of phantom epistasis in heterotic hybrids -
09:30-09:45 (15min)
› GENOME-BASED PREDICTION OF SUB-GENOME GENETIC INTERACTION EFFECTS IN WHEAT POPULATIONS -
09:45-10:00 (15min)
› Uncovering directional epistasis in bi-parental populations using genomic data -
10:00-10:15 (15min)
› Effects of systematic data reduction on trend estimation from German registration trials -
10:45-11:00 (15min)
› A comprehensive review of fast algorithms for large-scale genome-wide association studies based on linear mixed models -
11:00-11:15 (15min)
› Empirical comparison of times series models and tensor product penalised splines for modelling spatial dependence in plant breeding field trials. - Bev Gogel, University of Wollongong
11:15-11:30 (15min)
› Understanding the recombination landscape of breeding lines in wheat and barley -
11:30-11:45 (15min)
Gene-by-Environment interaction and Crop Growth Modeling
Chairman: Carlota Vaz Patto
› A framework based on differential equations for the dynamic modelling of crop growth for sets of genotypes - George Van Voorn, Wageningen University & Research
09:45-10:00 (15min)
› Functional–Structural Plant Modeling Highlights How Diversity in Leaf Dimensions and Tillering Capability Could Promote the Efficiency of Wheat Cultivar Mixtures - Pierre Barbillon
10:00-10:15 (15min)
Gene-by-Environment interaction and Crop Growth Modeling
Chairman: Dietrich Borchardt
› Quantifying genetic drivers of yield variability of UK cereal crops - Joanna Raymond, University of East Anglia
11:45-12:00 (15min)
› Resource allocation optimization for multi-environment trials in cereals breeding - Lucia Gutierrez, University of Wisconsin Madison
12:00-12:15 (15min)
› Design of a CIMMYT Australian ICARDA Germplasm Evaluation (CAIGE) experiment using an Incomplete multi-environment trial (IMET) design approach incorporating genetic relatedness - LU WANG, Centre for Biometrics and Data Science for Sustainable Primary Industries
12:15-12:30 (15min)
Gene-by-Environment interaction and Crop Growth Modeling
Chairman: Hans-Peter Piepho
› Meta-analysis of GWAS for studying GxE interactions - Annaïg De Walsche, MIA Paris, INRAE GQE - Le Moulon
14:00-14:15 (15min)
› Genomic selection using random regressions on known and latent environmental covariates - Daniel Tolhurst, The Roslin Institute
14:15-14:30 (15min)
› learnMET: an R package to apply nonlinear algorithms for genomic prediction using multi-environment trial data - Cathy Westhues, Division of Plant Breeding Methodology, Center for Integrated Breeding Research (CiBreed), University of Göttingen, Computomics
14:30-14:45 (15min)
› Revisiting superiority and stability measures in multi-environment trials using genomic data - Humberto Fanelli Carvalho, Centro de Biotecnología y Genómica de Plantas (CBGP-INIA), Universidad Politécnica de Madrid (UPM) – Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) Campus Montegancedo-UPM
14:45-15:00 (15min)
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https://eucarpiabiom22.sciencesconf.org/data/program/Abstract.pdf
https://eucarpiabiom22.sciencesconf.org/data/program/Abstract_EucarpiaBiometrics_AndreasHund_ETH.docx
https://eucarpiabiom22.sciencesconf.org/data/program/00.Zulma_Vitezica.pptx
