This Small Business Technology Transfer (STTR) Phase I project proposes to develop new tools that will make it possible to better predict crop yields under changing climatic and environmental conditions, associate phenotypic expression of desired plant traits with genetic markers, and enable plant breeders to accelerate the development of new crops and varieties under changing climatic conditions. Plant growth and crop models may be limited by a lack of detailed environmental data inputs and detailed knowledge of crop physiology. A new approach to greatly improve the estimates potential of new crops will be explored by using existing crops as data surrogates for potential new crops, and to estimate performance of known crops under changing environmental conditions. To identify which species and varieties can serve as the best surrogates, an integrated approach will be utilized involving sequencing the genomes/transcriptomes of various species-wide genotypes and bioinformatics analysis. Genotypes will be identified based on their phenotypic performance in geographically and environmentally diverse locations, building a reference genome guided and/or denovo transcriptomes from treated samples, identifying genetic markers (SSRs and SNPs) and resolving their placement in the angiosperm phylogeny. The broader impact/commercial potential of this project, if successful, will be improvement in the production of food and energy crops under changing climatic conditions, which will benefit consumers and commercially benefit farmers, seed companies, agricultural input and service companies and food processors and distributors. The development of new crops and varieties is essential to help meet the food, fiber and energy needs of the nation and the world. Global climate change and increasing weather variability means that even existing crops will need to be modified to perform well under new environmental conditions. Using traditional plant breeding can take years to develop new crops that are optimized to perform well in specific locations. While the new tools of genomics and genetic mapping hold the promise of greatly reducing the time that it takes to develop new crop, these tools have not yet been fully integrated into assessing how plants respond to specific environmental conditions and determining how to isolate and develop the genetic determinants of desired phenotypic expressions. In this proposed project, plant production models will be integrated with genetic mapping to produce tools that make it possible to project crop yield potentials in the context of local environments as distributed across the landscape.
