Co-Authors:
Cohen, Y., Agricultural Research Organization, The Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel
Alchanatis, V., Agricultural Research Organization, The Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel
Sela, E., Agricultural Research Organization, The Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel, R. H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
Saranga, Y., R. H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
Cohen, S., Agricultural Research Organization, The Volcani Center, Institute of Soil, Water and Environmental Sciences, Bet Dagan, Israel
Meron, M., Crop Ecology Laboratory, MIGAL, Kiryat Shmona, Israel
Bosak, A., Drom Yehuda Growers Association, Havat Shikmim, Israel
Tsipris, J., Crop Ecology Laboratory, MIGAL, Kiryat Shmona, Israel
Ostrovsky, V., Agricultural Research Organization, The Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel
Orolov, V., Crop Ecology Laboratory, MIGAL, Kiryat Shmona, Israel
Levi, A., Agricultural Research Organization, The Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel
Brikman, R., Agricultural Research Organization, The Volcani Center, Institute of Agricultural Engineering, Bet Dagan, Israel
Abstract:
Thermal crop sensing technologies have potential as tools for monitoring and mapping crop water status. To create maps of water status from thermal images, a reliable relationship between direct water status measures like leaf water potential (LWP) and thermal water status measures like temperature and crop water stress index (CWSI) should be established for different crops and for different growth stages. The objective of this study was to define the relationships for cotton between LWP and CWSI derived from high-resolution ground-based thermal images and more specifically to examine whether robust relationships exist between the two measures for different varieties, through a cotton growing season, across seasons and under different geographical areas (different climate and soils). A dataset from three cotton growing seasons and from different geographical areas was built to explore the relationship between CWSI and LWP in cotton. CWSI was calculated based on ground-based thermal images and measured dry (Tair + 5 °C) and wet references (Artificial wet reference surface—AWRS). A linear CWSI–LWP relationship was found with high coefficient of determination (R2 = 0.7). This relationship changed over the cotton growth stages and different CWSI–LWP relationships were established to the flowering, boll-filling and defoliation stages. The boll-filling relationship was found to be insensitive to a range of meteorological conditions. The flowering and the boll-filling models were initially validated using diagonal (oblique) thermal images from dates that were not used for calibration. For CWSI calculation, the average temperature of the lowest decile was used for the wet reference instead of the AWRS. The comparison between predicted and observed values of the validation sets yielded RMSE of 0.18 and 0.15 for the flowering and boll-filling stages, respectively. The successful use of the lowest decile as the wet reference enables a future application of the CWSI–LWP relationship to map LWP at a commercial field scale. © 2014, Springer Science+Business Media New York.
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