Computational Models
Climate-Proof Wheat: Insights on Key Traits for Yield Stability in a Dynamic Environment
Assessing the impact of traits on wheat yield and stability under climate change.
Computational Models
Exploring the Influence of Phloem Resistance on Root System Architecture
Studies model the local influence of phloem resistance on taproot and lateral root growth.
Computational Models
Increasing yield prediction accuracy
Researchers find combining multiple types of models improves crop yield predictions, outperforming single models.
Computational Models
Weathering the Storm: Understanding Maize Lodging Resistance
A new model identifies the morphological features that determine stalk bending strength.
Computational Models
Introducing the new CPlantBox
Computational model may help unravel the complex processes of drought tolerance.
Close Encounters
Imaginary Plants Reveal the Physics of Real Killers
A novel approach uniting maths, physics, and biology has uncovered how diverse rim shapes in carnivorous pitcher plants relate to strategies for catching different insect prey.
Cells, Genes & Molecules
Using Genomic Prediction to Improve Ecophysiological Crop Models
A guide to combining ecophysiological and genomic models.
Cells, Genes & Molecules
Five Root Models Compete in Benchmarking Challenge
Assessing the reliability of root water uptake simulations
Computational Models
“Virtual Leaf” Unveils Hidden Realities of Plant Physiology
The ‘virtual leaf’ that simulates leaf physiology in 3D, promises breakthroughs in understanding plant responses to environmental changes and boosting our agricultural strategies.
Computational Models
Traitor: Unleashing the Power of Automation for Studying Seed Traits
Are you using callipers and microscopes to measure seeds? Well, not anymore! Traitor comes to the rescue of seed scientists and technicians.
Computational Models
SIMPLACE: The Next Generation Platform for Agricultural Systems Analysis
SIMPLACE offers a flexible and transparent approach to developing customized crop models
Computational Models
Machine Learning Unfolds New Insights Into Leaf Traits and Climate
A novel machine learning-based study using digitized herbarium collections provides insights into the relationship between leaf size and climate across different plant species, and demonstrates the benefit of human involvement in training the AI model.