About this Research Topic
This research topic aims to showcase the latest developments in genotype-phenotype modeling of plants, with a particular focus on crop plants. The primary objective is to explore how emerging methodologies, such as high-throughput phenotyping, improved genomics tools, and functional-structural plant modeling, can enhance our understanding and application of GPMs. Specific questions to be addressed include how genetic information can be effectively integrated into models to predict phenotypic outcomes, and how these models can be used to accelerate plant breeding processes. Hypotheses to be tested may involve the accuracy of GPMs in simulating the performance of new genotypes under various environmental conditions and the potential of these models to predict ideotypes for future breeding programs.
To gather further insights into the boundaries of genotype-phenotype modeling, we welcome articles addressing, but not limited to, the following themes:
- Development and validation of metabolic network models regulated by genetic information.
- Advances in ecophysiological functional-structural plant models (FSPM) incorporating quantitative trait locus information.
- Population models enabling interactive simulation of genetic processes such as recombination and crossing-over.
- Novel methodologies in high-throughput phenotyping and their integration into GPMs.
- Case studies on the application of GPMs in plant breeding programs.
- Reviews and opinion papers on the current state and future directions of genotype-phenotype modeling
Keywords: #CollectionSeries, Plant Growth, Genotype-phenotype models, functional-structural plant models, genotype phenotype modelling, crop plants, plant breeding
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.