Co-Authors:
Sela, E., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel, Faculty of Agricultural, R. H. Smith Institute of Plant Sciences and Genetics in Agriculture, Hebrew University of Jerusalem, Rehovot, Israel
Cohen, Y., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel
Alchanatis, V., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel
Saranga, Y., Faculty of Agricultural, R. H. Smith Institute of Plant Sciences and Genetics in Agriculture, Hebrew University of Jerusalem, Rehovot, Israel
Cohen, S., Agricultural Research Organization, Volcani Center, Institute of Soil, Bet Dagan, Israel
Möller, M., Agricultural Research Organization, Volcani Center, Institute of Soil, Bet Dagan, Israel
Meron, M., Crop Ecology Laboratory, MIGAL Kiryat Shmona, Israel
Bosak, A., Southern Growers Organization, Israel
Tsipris, J., Crop Ecology Laboratory, MIGAL Kiryat Shmona, Israel
Orolov, V., Crop Ecology Laboratory, MIGAL Kiryat Shmona, Israel
Abstract:
Water is a scarce resource and a major factor limiting crop productivity. Precision irrigation might promote water saving. In order to implement precision irrigation, efficient techniques for estimating spatial crop water status are needed. Thermal and visible images of cotton canopies were used in this study for estimating and mapping leaf water potential (LWP) and their application in cotton fields. Data were collected from cotton canopies representing a range of plant water status, phenological stages, growing seasons, species and locations. Fusion of visible and thermal images was used for detecting temperatures of sunlit canopy. The crop water stress index (CWSI) statistics were calculated using canopy temperatures and theoretical and empirical references. Models for estimating LWP from the thermal index CWSI were built. The models that were based on empirical references showed good correlation with measured LWP. The accuracy of the LWP-CWSI model was highest during the last phenological stage. The model was then used for generating LWP maps of plots with different water status.