Maximizing nitrogen stress tolerance through high-throughput phenotyping in rice

Abstract

Nitrogen (N) is a significant nutrient element limiting rice yield and quality, a major staple crop consumed worldwide. N deficiency negatively affects the growth and development of rice by impacting vital physiological processes. Plants have developed multiple resilience strategies, including enhanced nitrogen use efficiency (NUE) to cope with N-deprived situations. NUE in rice is less than 40 %, and increased N application leads to high production costs and ecosystem damage. Improving NUE has been one of the major challenges of agriculture research in the recent past. NUE is an obfuscated trait governed by diverse physiological traits and controlled by complex genetic mechanisms. In recent years, a combination of multi-omics techniques (phenomics and genomics) has enhanced the N resilience maximization efforts of the agricultural research community. Phenomics technology has displayed the ability to perform systematic, organism-wide phenotyping of N stress response in diverse crops over the entire life cycle using non-invasive sensors on high throughput platforms (HTPs) in a more precise manner. These HTPs augment precision phenotyping (at the spatiotemporal scale) of component traits of NUE, which are difficult to phenotype mainly due to its dynamic interactive nature with the environment. Phenomics has drastically reduced the phenotype-genotype gap by optimally utilising other omics data for breeding climate smart cultivars with enhanced N stress tolerance. This review focuses on the recent advances in HTP-based phenotyping of NUE-related traits to identify novel QTLs/genes/signaling pathways associated with improved NUE both in controlled environments and field conditions.