A new study unravels why maize has higher yields and sorghum is more drought tolerant using a cropping systems modeling platform.

A new study uses drought patterns, sowing date, and genotype phenology to reduce sorghum water stress during critical stages.

Dynamic crop simulation models can be transformed into gene-based models by replacing an existing process module with a gene-based module for simulating the same process.

A new model uncovers the possible mechanisms underlying the robustness of flat leaf production.

Combing new tools for the rapid advancement of genetic gain in sorghum breeding programs.

Researchers use 3D modelling of rice canopies to determine how nitrogen availability affects photosynthetic productivity.

Incorporating genotype-specific parameters and realistic trait physiology will advance crop growth models.

An update on major microarray and RNA-seq studies, exploration of data integration approaches using gene coexpression network, and outline of important web resources.

The use of mechanistic crop models can optimize the efficiency of breeding programs.

A combination of high resolution multi-spectral imagery and supervised learning effectively distinguishes between pasture species and seasonal changes in botanical composition.

Modeling the activity of enzymes in the Calvin Benson Cycle identifies key enzymes to improve photosynthesis.

How can plant modelers introduce a genetic dimension into physiological models at different organizational scales in a meaningful way?