Present paper 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 phenotyhping for water deficit stress studies.