Computational Models
Resolving interactions between plant structure and function
A new study reveals the impact of spatial resolution on accurately representing the interactions between plant canopy structure and function.
Cells, Genes & Molecules
How will plant communities respond to climate change?
Functional-structural plant modelling is the key to predicting how plant communities will respond to climate change.
Uncategorized
Prediciendo el rendimiento de arroz en condiciones de sequía
Modelos metabólicos y de crecimiento integrado predicen el metabolismo del arroz cultivado en condiciones normales y limitantes de agua.
Cells, Genes & Molecules
Predicting rice yield under drought
Integrated growth and metabolic models predict the metabolism of rice growth under normal and water-limited conditions.
Cells, Genes & Molecules
Wheat adaptation to climate change
Models fill in the data gaps to identify genotypes to maximize yield across the NE Australian wheat-belt under climate change.
Computational Models
The Why and How of Horizontally Expanding Leaf Patterns
A new study uses multiple approaches to determine why horizontally expanding leaf patterns exist and how they are formed.
Cells, Genes & Molecules
Modeling the circadian clock
A novel circadian clock model based on real-world clocks delivers simplicity, entrainment, reliability, and accuracy.
Computational Models
The future of digital technologies for crops
Cyber physical technologies such as earth observation and biophysical crop modelling can play a major role in production, sustainability, and profitability of production systems in the face of climate change.
Computational Models
What drives plant diversity?
Computer simulations confirm that plant diversity can be explained by three assumptions.
Computational Models
A more realistic model of sucrose accumulation in sugarcane
Detailed kinetic modelling of sucrose translocation and metabolism captures the spatio-temporal evolution of the advection-diffusion-reaction system.
Computational Models
Man vs machine: Which model is superior at predicting phenology?
A comparison of the performance of knowledge-based models, data-driven machine-learned models, and an ensemble of both.
Computational Models
Evaluating yield components leads to yield improvement
Yield dissection models in tomato identify promising yield components and corresponding QTLs.