Abstract
Main conclusion A new imaging platform was constructed to analyze drought-tolerant traits of rice. Rice was used to quantify drought phenotypes through image-based parameters and analyzing tools.Climate change has increased the frequency and severity of drought, which limits crop production worldwide. Developing new cultivars with increased drought tolerance and short breeding cycles is critical. However, achieving this goal requires phenotyping a large number of breeding populations in a short time and in an accurate manner. Novel cutting-edge technologies such as those based on remote sensors are being applied to solve this problem. In this study, new technologies were applied to obtain and analyze imaging data and establish efficient screening platforms for drought tolerance in rice using the drought-tolerant mutant osphyb. Red–Green–Blue images were used to predict plant area, color, and compactness. Near-infrared imaging was used to determine the water content of rice, infrared was used to assess plant temperature, and fluorescence was used to examine photosynthesis efficiency. DroughtSpotter technology was used to determine water use efficiency, plant water loss rate, and transpiration rate. The results indicate that these methods can detect the difference between tolerant and susceptible plants, suggesting their value as high-throughput phenotyping methods for short breeding cycles as well as for functional genetic studies of tolerance to drought stress.
Highlights
The worldwide population is projected to increase to 90 billion people by 2050, and the availability of water is an important problem (Rockström et al 2009; Ray et al 2013)
In spring barley exposed to drought stress, phenotypic traits were analyzed in detail, including geometric traits, color-related traits, fluorescence-related traits, and NIR-related traits (Chen et al 2014)
wild type (WT) and osphyb seeds were divided into two groups; one group was grown under normal conditions, and the other was exposed to drought stress
Summary
The worldwide population is projected to increase to 90 billion people by 2050, and the availability of water is an important problem (Rockström et al 2009; Ray et al 2013). Planta (2020) 252:38 level during the growth of rice, production decreases by > 50% (Lafitte et al 2007; Lesk et al 2016) These issues have led to the development of drought-resistant cultivars, and techniques are being developed to accurately select them in a short period of time. Image-based traits were extracted from 507 rice accessions were classified into biomass, greenness, morphological, and histogram texture (Guo et al 2018). Duan et al (2018) analyzed four RGB traits including green projected area ratio, total projected area area/bounding rectangle of area ratio, perimeter/projected area ratio, and total projected plant area/convex hull area ratio from 40 drought-resistant and drought-sensitive accessions of rice. Drought stress analysis platforms in rice are mostly based on RGB traits, and various imaging analysis techniques including RGB are needed to develop them
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