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Date |
Time |
Session |
Starting time |
Title |
Speaker |
30-Oct |
9:00-10:30 |
Introduction |
9:00 |
GxExM past, present, future |
Fred van Eeuwijk |
9:22 |
GxExM at WUR-PSG |
Richard Harrison |
9:34 |
GxExM within the CGIAR |
Martin Kropff |
9:56 |
Mixed models for incorporating environmental covariates |
Hans Peter Piepho |
10:18 |
GxExM as a topic within G3 |
Lauren McIntyre |
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10:30-11:00 |
Coffee/tea break |
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11:00-12:30 |
Statistics |
11:00 |
New methods for modelling and disentangling GxE interaction using known and latent environmental covariates |
Daniel Tolhurst |
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11:22 |
Modelling GxExM: Pitfalls to Avoid and Strategies to Adopt |
Salvador Gezan |
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11:39 |
Investigation of ensemble approach for genomic prediction in crop breeding |
Shunichiro Tomura |
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11:56 |
Mixed model analysis of historical VCU trials across Europe: precision and genetic gain |
Jip Ramakers |
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12:13 |
Evaluation of the trialling efficiency of Australia's National Variety Trial Main Wheat Season among the Three Growing Regions |
Vivi Arief |
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12:30-12:45 |
Poster flash talks |
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12:45-13:45 |
Lunch |
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13:45-15:15 |
Phenotyping |
13:45 |
Predicting GxE from Trait Dynamics: Utilizing Stay Green and Multiple Physiological Traits for Enhanced Wheat Adaptation to Contrasting Drought Conditions |
Daniela Bustos-Korts |
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14:07 |
Modelling and prediction of height-related traits in dependence on environmental covariates |
Olivia Zumsteg |
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14:24 |
Complementing genomics with platform omics help decipher the genetic architecture of in-field productivity in the presence of genotype by environment interactions |
Baber Ali |
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14:41 |
High-throughput field phenotyping to facilitate the prediction of crop performance for new environments and new genotypes in breeding |
Lukas Roth |
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14:58 |
Phenomic Prediction as a Tool for Enhancing Functional Modeling of Plants in a Breeding Context |
Alexis Comar |
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15:15-15:45 |
Coffee/tea break |
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15:45-17:15 |
Physiology |
15:45 |
Coping with GxExM – A simulation approach to support context-specific crop improvement at CGIAR |
Jana Kholova |
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16:07 |
Roles of physiological crop modelling in analysing GxExM: Past experiences and future prospects |
Xinyou Yin |
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16:24 |
Beyond GxExM: Ensuring that new crop varieties from CGIAR and partners are fit for purpose |
Dorcus Gemenet |
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16:41 |
Gene model redundancy and mechanisms of high grain yield under low N in maize and sorghum |
John McKay |
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16:58 |
Research Bottlenecks to Crop Productivity |
Matthew Reynolds |
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17:15-17:30 |
Poster flash talks |
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17:30-19:00 |
Poster session |
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19:15-21:00 |
Dinner |
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Date |
Time |
Session |
Starting time |
Title |
Speaker |
31-Oct |
9:00-10:30 |
Corteva Session |
9:00 |
GxExM at Corteva |
Jhonathan dos Santos |
AI in GxExM |
9:15 |
Towards GxExM modelling by integrating machine learning and mechanistic models in the context of breeding for resilient crops |
Aalt-Jan van Dijk |
Organized by: |
9:30 |
Accurate multi-trait prediction across cycles of selection by interpretable deep learning |
István Dékány |
Aike Potze Hugo Dorado |
9:45 |
Hybrid Phenology Modelling for Predicting Temperature Effects on Fruit Tree Dromancy |
Ron van Bree |
Junita Solin Jonathan Kunst Killian Melsen |
10:00 |
LearnMET: an R package to apply machine learning methods for genomic prediction using environmental and genomic data |
Cathy Westhues |
Yingjie Shao |
10:15 |
Panel discussion |
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10:30-11:00 |
Coffee/tea break |
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11:00-12:30 |
Corteva Session |
11:00 |
Model-assisted plant breeding with statistical genetics for higher yield in tomato recombinant inbred line |
Ep Heuvelink |
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Beyond conventional GxExM |
11:15 |
Breeding progress in terms of carbon footprint reduction for five cereal crops in Germany |
Donghui Ma |
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Organized by: |
11:30 |
Exploring the breeding implications of diversified cropping systems – GxG or GxM? |
Max Wellens |
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Aike Potze Hugo Dorado Junita Solin Jonathan Kunst Killian Melsen Yingjie Shao |
11:45 |
Hierarchical genomic prediction to tackle genotype-by-environment-by-management interactions |
Owen Powell |
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12:00 |
GxExM in vegetable seeds challenges and opportunities |
Marcos Malosetti |
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12:15 |
Panel discussion |
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12:30-13:30 |
Lunch |
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13.30-15.00 |
Environmental characterization & climate change |
13:30 |
Environmental characterization of maize European trial networks |
Boris Parent |
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13:52 |
Multivariate characterisation of environment types influencing wheat G×E in Australian National Variety Trials |
Javier Fernandez |
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14:09 |
Assessing Maize Breeding under Climate Change: A Digital Lens on Genotype-Environment Interactions |
Randall J. Wisser |
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14:26 |
Spatiotemporal suitability analysis of sorghum in Germany under climate change |
Amir Hajjarpoor |
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14:43 |
Understanding rates of genetic gain in sorghum (Sorghum bicolor Moench) in the U.S. |
Carlos Messina |
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15:00-15:30 |
Coffee/tea break |
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15:30-17:00 |
Integration |
15:30 |
Crop-XR: Integrating data with mechanistic modeling, machine learning and control for smart breeding approaches |
Kirsten ten Tusscher |
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15:52 |
Multi-modal prediction of GxExM |
Aike Potze |
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16:09 |
Leveraging Parsimonious Model PSoup for Cross-Scale Plant Modeling: A Case Study on Plant Branching |
Christos Mitsanis |
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16:26 |
Phenotypic and genetic modelling of photosynthesis at the Jan Ingenhousz Institute |
Tom Theeuwen |
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16:43 |
Developing predictive breeding capability for grapevine improvement |
Kai Voss-Fels |
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17:00 - 17:15 |
End |
17:00 |
Closing word GxExM III |
Fred van Eeuwijk |