Abstract
Reproductive stage drought stress (RSDS) is a major challenge in rice production worldwide. Cultivar development with drought tolerance has been slow due to the 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 quantitative trait loci (QTLs) which govern grain yield under drought determine RSDS tolerance. Among these, qDTY2.1 and qDTY3.1 were used for marker-assisted breeding. A set of 35 near-isogenic lines (NILs), introgressed with these QTLs in the popular variety, Pusa 44 were used to assess the efficiency of image-based phenotyping for RSDS tolerance. NILs offered the most reliable contrast since they differed from Pusa 44 only for the QTLs. Four traits, namely, the projected shoot area (PSA), water use (WU), transpiration rate (TR), and red-green-blue (RGB) and near-infrared (NIR) values were used. Differential temporal responses could be seen under drought, but not under unstressed conditions. NILs showed significant level of RSDS tolerance as compared to Pusa 44. Among the traits, PSA showed strong association with yield (80%) as well as with two drought tolerances indices, stress susceptibility index (SSI) and tolerance index (TOL), establishing its ability in identifying the best drought tolerant NILs. The results revealed that the introgression of QTLs helped minimize the mean WU per unit of biomass per day, suggesting the potential role of these QTLs in improving WU-efficiency (WUE). We identified 11 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, and is the first report of using phenomics parameters in RSDS selection in rice.
Highlights
Abiotic stresses such as drought are detrimental to the growth, development, productivity, and grain quality in rice (Kumar et al, 2012; Raman et al, 2012), because more than 80% of its growth period is water-dependent
A set of 35 Near isogenic lines (NILs) of Pusa 44 was simultaneously evaluated for drought response in a field evaluation as well as in a phenomics platform under induced drought
The field tolerance of the lines was confirmed from two years of evaluation and compared with the image-based phenomics traits such as projected shoot area (PSA), water use (WU), NIR, and transpiration rate (TR)
Summary
Abiotic stresses such as drought are detrimental to the growth, development, productivity, and grain quality in rice (Kumar et al, 2012; Raman et al, 2012), because more than 80% of its growth period is water-dependent. In India, in states such as Odisha, Chhattisgarh, eastern Uttar Pradesh, Bihar, and Jharkhand, recent episodes of severe drought had resulted in significant yield losses in rice (Kumar A. et al, 2014; Kumar S. et al, 2014). Some of these states suffered yield losses of up to 40%.1. Some of these states suffered yield losses of up to 40%.1 Drought-related yield loss in rice during 2015–2016 alone is estimated to be 1.17 million tonnes (DACFW, 2017)
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