Improving crop modeling using machine learning
Integration of machine learning and crop modelling can optimize predictions of plant growth and yield.
Category: in silico Plants
Modelling pollen competition
Identification of traits affecting pollen performance
New open source software for identifying candidate genes
Introducing cageminer, an R/Bioconductor package to prioritize candidate genes by integrating GWAS and gene coexpression networks
Simulating red:far red ratio in your model
The best method depends on your goal, need for accuracy, and computing allowance
MARSHAL, a novel tool for modeling root system hydraulics
A new computational tool couples a root architecture model with fast and accurate algorithms of water flow through hydraulic architectures and plant-scale parameter calculations.
How do you combine simplicity and realism in plant models?
Parsimony and biological reality are often seen as antagonistic goals in plant modelling. Hammer and colleagues argue that isn’t always the case, and combining the two approaches could bring benefits to scientists as well as plants.
Modelling molecular-level processes using parametric extension of L-systems
It is now possible to simulate molecular and higher-level spatially explicit stochastic processes and study their behavior in the presence of stochastic perturbations
We asked the members of the in silico Plants editorial board what they do to achieve work/life balance.
This is what they said:
What experience has had the biggest impact on your career? (Part Two)
What is the best conference or workshop you ever attended? Are there any upcoming conferences or workshops that you are looking forward to?
Scaling photosynthesis from gene to leaf
Scientists combine models to create a powerful multiscale model that can identify key transcription factors regulating leaf photosynthesis.
What experience has had the biggest impact on your career?
HydroShoot: a functional-structural plant model for simulating hydraulic structure, gas and energy exchange dynamics
A new model is able to predict the effect of training systems on grapevine gas-exchange dynamics under drought.
Dynamic modeling of the iron deficiency in plants
Scientists unravel the mysteries of the iron deficiency-induced transcriptional response in plants using a dynamic model.