Phenomics Enabled Biology
Rising global temperatures during cropping seasons are resulting in yield losses. These yield losses are emerging as a major obstacle for important cereal crops such as wheat and rice and hence global food security. Rice grain development is very sensitive to high temperatures. Given the heat sensitivity of developing grains, we aimed to explore the natural variation for high temperature tolerance using a suite of phenotyping approaches including an image-based, non-destructive platform for panicle imaging. We have analyzed these data using image analysis pipelines for 3D-feature extraction. To associate genomic linkages with these image-derived features, we have performed genome-wide association analysis (GWAS) to identify loci for high temperature tolerance that explain the natural variation within the rice germplasm. We will present results from this genetic analysis at panicle level over spatial and temporal scale in response to high temperatures.