<![CDATA[The utilization of phenotype technology in breeding is directed to see and select plants based on the appearance of the targeted phenotype. One is modern technology based on geographic information systems and remote sensing. The unmanned aerial drone (UAV) uses computing and machine learning in image processing and information extraction. This research focuses on developing tolerance screening of several varieties to drought based on the drone-vegetation index. This study used nine rice varieties in the rice fields of Kab. Bone-SulSel in the dry season. This research aims to identify the best selection character as a measure of tolerance of rice varieties to drought based on image and morphophysiology, which will be used to develop image-based phenotype-based selection methods. This research was conducted with Randomized Block Design (RAK) consisting of 3 replications. The morpho-physiological parameters of several rice varieties showed a significant effect, including the Inpago 15 variety, which gave the best results on NDVI characters and was followed by other characters. The vegetation index, or the greenness of the vegetation value obtained from digital signal processing of several channels of satellite sensor data, can provide information that a plant has good vegetation. The varieties that gave the best treatment were the Inpago 15 and Jeliteng varieties. The results of the correlation analysis showed that the parameter with a significant positive correlation with productivity was the weight parameter of 1000 grain (r=0.35). ]]>
