Towards increased shading capacity : A combined phenotypic and genetic analysis of rice shoot architecture

Samenvatting

Societal Impact Statement: Rice farming is transitioning from transplanting rice seedlings towards the less labour-intensive and less water-demanding method of directly seeding rice. This, however, is accompanied by increased weed proliferation. To tackle this issue, this study seeks to identify how the crop itself can better suppress weeds, with a focus on light competition via shading. Using a rice diversity panel, traits were identified that contribute to enhanced shading capacity, and these traits were encapsulated into a single shading capacity metric. This was followed by the identification of the genetic loci underpinning variation in the core traits. The identified haplotypes can be used in breeding programmes to improve weed suppression by rice, thus contributing to sustainable agriculture. Summary: In modern rice farming, one of the major constraints is weed proliferation and the entailed ecological impact of herbicide application. This requires increased weed competitiveness in current rice varieties, achieved via enhanced shade casting to limit the growth of shade-sensitive weeds. To identify traits that increase rice shading capacity, we exhaustively phenotyped a rice diversity panel of 344 varieties at an early vegetative stage. A genome-wide association study (GWAS) revealed genetic loci underlying variation in canopy architecture traits linked with shading capacity. The screen shows considerable natural variation in shoot architecture for 13 examined traits, of which shading potential is mostly determined by projected shoot area, number of leaves, culm height and canopy solidity. The shading rank, a metric based on these core traits, identifies varieties with the highest shading potential. Five genetic loci were found to be associated with canopy architecture, shading potential and early vigour. Identification of traits contributing to shading capacity and underlying allelic variation will serve future genomic-assisted breeding programmes. Implementing the presented genetic resources for increased shading and weed competitiveness in rice breeding will make its farming less dependent on herbicides and contribute towards more environmentally sustainable agriculture.