TraitCapture: genomic and environment modelling of plant phenomic data
Language English Country England, Great Britain Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't, Review
PubMed
24646691
DOI
10.1016/j.pbi.2014.02.002
PII: S1369-5266(14)00018-1
Knihovny.cz E-resources
- MeSH
- Databases as Topic * MeSH
- Phenotype MeSH
- Genomics methods MeSH
- Quantitative Trait, Heritable * MeSH
- Plants genetics MeSH
- Environment * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
Agriculture requires a second green revolution to provide increased food, fodder, fiber, fuel and soil fertility for a growing population while being more resilient to extreme weather on finite land, water, and nutrient resources. Advances in phenomics, genomics and environmental control/sensing can now be used to directly select yield and resilience traits from large collections of germplasm if software can integrate among the technologies. Traits could be Captured throughout development and across environments from multi-dimensional phenotypes, by applying Genome Wide Association Studies (GWAS) to identify causal genes and background variation and functional structural plant models (FSPMs) to predict plant growth and reproduction in target environments. TraitCapture should be applicable to both controlled and field environments and would allow breeders to simulate regional variety trials to pre-select for increased productivity under challenging environments.
Division of Plant Sciences Research School of Biology Australian National University Australia
High Resolution Plant Phenomics Centre Plant Industry CSIRO Australia
References provided by Crossref.org
Machine Learning-Based Plant Detection Algorithms to Automate Counting Tasks Using 3D Canopy Scans
Review: New sensors and data-driven approaches-A path to next generation phenomics
Using Phenomic Analysis of Photosynthetic Function for Abiotic Stress Response Gene Discovery
