AUTHOR=Dwivedi Priyanka , Ramawat Naleeni , Raju Dhandapani , Dhawan Gaurav , Gopala Krishnan S. , Chinnusamy Viswanathan , Bhowmick Prolay Kumar , Vinod K. K. , Pal Madan , Nagarajan Mariappan , Ellur Ranjith Kumar , Bollinedi Haritha , Singh Ashok K. 

TITLE=Drought Tolerant Near Isogenic Lines of Pusa 44 Pyramided With qDTY2.1 and qDTY3.1, Show Accelerated Recovery Response in a High Throughput Phenomics Based Phenotyping

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2021.752730

DOI=10.3389/fpls.2021.752730

ISSN=1664-462X

ABSTRACT=Reproductive stage drought stress (RSDS) is a major challenge in rice production worldwide. Cultivar development with drought tolerance has been slow due to lack of precise high throughput phenotyping tools to quantify drought stress-induced effects. Most of the available techniques are based on destructive sampling and do not assess the progress of the plant's response to drought. In this study, we have used state-of-the-art image-based phenotyping in a phenomics platform that offers a controlled environment, non-invasive phenotyping, high accuracy, speed, and continuity. In rice, several QTLs which control grain yield under drought governs RSDS tolerance. Among these, qDTY2.1 and qDTY3.1 are being used for marker assisted breeding. A set of 35 near isogenic lines (NILs), introgressed with these QTLs in the background of Pusa 44, were used to assess the efficiency of image-based phenotyping for RSDS tolerance selection. NILs offered the most reliable contrast since they differed from Pusa 44 only for the QTLs. Four traits namely projected shoot area (PSA), water use (WU), transpiration rate (TR) derived from automated weighing and watering, and RGB and NIR images were used. Differential temporal responses could be seen under drought and not under unstressed conditions. NILs showed a significant difference in tolerance as compared to Pusa 44. Among the traits, PSA showed a strong association with yield (80%) as well as with two drought tolerances indices, SSI and TOL (90%), rendering its suitability in identifying the best tolerant NILs. The results revealed that the introgression of QTLs helped minimize mean WU per unit of biomass per day, suggesting the potential role of these QTLs in WUE. We identified eleven NILs based on phenomics traits as well as performance under imposed drought in the field. The study emphasizes the use of phenomics traits as selection criteria for RSDS tolerance at an early stage. This study forms the first report of using phenomics parameters in RSDS selection in rice.