Image Based-Phenotyping and Selection Index Based on Multivariate Analysis for Rice Hydroponic Screening under Drought Stress

The development of rice varieties that are tolerant of drought stress needs to be detected with Image-based phenotyping. This Image-based phenotyping method in combination with selection index and multivariate analysis can characterize the morphological response easily within a short time, which makes it is suitable for rice screening under drought stress. Therefore, this study aims to determine the selection index based on multivariate analysis and assess the effectiveness of using image-based phenotyping in drought rice screening. This study was conducted in two stages, the first was in static hydroponic and the second was in dynamic hydroponic. In static hydroponic, a split-plot design was used, where the levels of drought were the main plots and varieties were the subplots. However, in dynamic hydroponic, a nested design was used, where the replicates were nested in the drought level treatments. Also, The drought level factors used were PEG 0%, PEG 10%, and PEG 20%, and the variety factor consisted of 5 varieties which were repeated three times. The results showed that the selection index for static hydroponic consisted of shoot area (0.421), green shoot area (0.4177), and the area growth rate (0.4192). Meanwhile, the selection index in dynamic hydroponics consisted of object extent Y from the side (0.4516) and convex hull from the side (0.4177). The regression of the two-selection index has a good determination of 0.84. Hence, these results showed that rice screening based on image-based phenotyping can be recommended for rapid screening under drought stress.