The research study deals with different components of next generation phenomics for characterizing rice genotypes for water deficit stress. Major sensors used in the study were non-imaging hyperspectal remote sensing, thermal imaging at ground platform and RGB and multispectral imaging sensors from drone platform. Different spectral indices were evaluated along with new proposed index and different multivariate models were studied for noninvasive estimation of relative water content (RWC) and sugar content in rice plant using spectral reflectance data collected in spectral range 350 to 2500 nm. Spectral data were further used for spectral discrimination of rice genotypes. Crop water stress index derived from thermal images acquired for rice genotypes could well characterize the drought resistant and sensitive genotypes. Initial study on field phenotyping through drone remote sensing using multispectral and RGB sensor was also explored to capture differential response of genotypes, trait and heat map mapping. All developed protocols as reliable alternative to conventional methods are fast, economic and non-invasive and in use in plant phenomics centre for high throughput plant phenotyping for water deficit stress studies.
MATERIALS AND METHODS
The study was carried out at ICAR-Indian Agricultural Research Institute (IARI), New Delhi research farms (28°38'28.59"N, 77° 9'28.09"E). The soil is mostly welldrained sandy loam. The minimum temperature is recorded between 0°C to 7°C during the winter season and the maximum temperature ranged between 41°C to 46°C. The average annual rainfall is about 750mm. The relative humidity (RH) is found to be the highest during the monsoon season. In the summer months, the RH is observed between 40 to 45%. Ten rice genotypes, five drought sensitive i.e., MTU 1010, Patchaiperumal, Pusa Basmati-1, Pusa Sugandha-5, IR 64 and five drought tolerant i.e., Sahbhagidhan, CR143, Nerica L44, Moroberekan, APO were grown with three replications. All the genotypes were grown with two moisture conditions i.e., maximum moisture stress and well irrigated.
Methods evaluated-
Excised leaf water loss experiment
Crop water stress index (CWSI) images of rice genotypes
Spectral indices
Multivariate analysis
Spectral discrimination analysis
Drone image acquisition and processing
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https://drive.google.com/file/d/1Q20CFeDchtI3F1yUKshUGp8bBP4DY3K9/view?usp=drivesdk
Other relevant research papers' links-
This analysis was part of PhD research project, See link here
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Mitali Chandra Gopal Krishna
Associate Editor Founder & Principal Editor
GEOINFORMERS. GEOINFORMERS.
