High throughput phenomics in elucidating drought stress responses in rice (Oryza sativa L.)

Global rice productivity is severely hampered by drought, which is becoming more frequent and severe due to climate change. In response to drought stress, the rice plant exhibits a number of morpho-physiological changes including, reduced plant height, stomatal closure, leaf rolling, senescence, changed chlorophyll content, warmth in the canopy, and spikelet sterility, leading to severe decline in crop productivity. Development of rice varieties with higher drought tolerance with shorted breeding cycles can be achieved only through crop improvement methods augmented with precise phenomics strategies. The traditional methods of phenotyping, which rely on manual measurements and observations, which are time-consuming, labour-intensive, and often subject to human error. High throughput phenomics addresses these challenges by leveraging cutting-edge technologies like remote sensing, imaging, robotics, and sensor networks to collect data from large numbers of plants concurrently. By integrating imaging sensors with unmanned aerial vehicles (UAVs) and specialized automated phenotyping platforms, significant strides have been made in the large-scale measurement and analysis of multiple plant traits with unprecedented speed and precision. This brief review covers importance of high-throughput phenomics technologies that can be used dissect drought associated responses in rice, current status regarding practical application of these platforms with special focus on drought related physiological, biochemical parameters and yield trait modulations. Finally, we explored the existing bottlenecks in high throughput phenotyping, their implications and future prospects for screening for drought tolerance using artificial intelligence coupled next generation phenomics strategies for attaining climate smart agriculture and food security.