Giesco
21st GiESCO International Meeting: ‘A Multidisciplinary Vision towards Sustainable Viticulture’ CROP WATER STRESS INDEX AS A TOOL TO ESTIMATE VINE WATER STATUS 1
Carlos ESPARTOSA , Julián RAMOS, Elena GONZÁLEZ-SEARA, Concepción GONZÁLEZ-GARCÍA, Adolfo MOYA, Antonio HUESO, Pilar BAEZA * 1 Centro de Estudios e Investigación para la Gestión de Riesgos Ambientales. ETSI-Agronómica, Alimentaria y Biosistemas. 28040 Madrid, España *Corresponding author:pilar.baeza@upm.es
Abstract: Context and purpose of the study – Crop Water Stress Index (CWSI) has long been a ratio to quantify relative plant water status in several crop and woody plants. Given its rather well relationship to either leaf or stem water potential and the feasibility to sample big vineyard areas as well as to collect quite a huge quantity of data with airborne cameras and image processing applications, it is being studied as a tool for irrigation monitoring in commercial vineyards. The objective of this paper was to know if CWSI estimated by measuring leaf temperature with an infrared hand held camera could be used to substitute the measure of stem water potential (SWP) without losing accuracy of plant water status measure. Material and methods – Four vine water status were set up in 2017 on a Cabernet-Sauvignon vineyard grafted onto 110R at Morata de Tajuña (Madrid). Data herein involved correspond to 2018 growing season. Total Irrigation amount was 157, 241, 470 and 626 mm for treatments 1, 2, 3 and 4 respectively in 2018. Plants were 2-bud spur pruned along a unilateral cordon with 11-12 shoots per meter of raw. Training system was a Vertical Shoot Position (VSP). Experimental design was a randomize complete 4-block design with 3 rows per single plot, one central control row and two adjacent ones acting as buffer. Canopy development was measured by determining shaded soil at 10:30. Weather data were collected from a weather station at the same vineyard site. To calculate CWSI, leaf-treatment, wet leaf temperature and dryleaf temperatures were measured with an infrared camera model FLIR E60. All data were collected around th th noon at the same time as stem water potential (Ψs), on 5 cloudless days along 2018 - June 19 , July 24 , th th th August 7 , September 4 and 25 -. Four leaves per treatment were sampled each time of measurement. It was established a linear regression between CWSI and stem water potential. One treatment per measuring date (4 pair data) was kept out of the lineal regression and saved them to validate the model; All statistics analysis was performed with the Statistix10 package. th Results – Differences in CWSI arose from the first date of measure, June 19 . Differences in CWSI arise even before than in SWP; Highest SWP was -5.32 and the lowest was -13.80bar. At the end of the season, when overwhelming ambient conditions stayed long time CWSI did not show any difference between treatments despite SWP widely ranged between -6.85 and -10.53 bar between treatments. We found a significant linear relationship between CWSI and SWP (Ψs = 23.58·CWSI -2.87 R2= 0.63***). In an attempt to dig into the variables involved in plant water status we looked into a multiple regression in which SWP was dependent either on CWSI, vapor pressure deficit (VPD), canopy development (SS) and soil water content (Θs). However, none of these variables turned out to be significant but CWSI (R2=0.63**). Shaded soil was significant for P = 0.08. So far we can conclude that CWSI works out when stem water potential is below 14.0 bar.
Keywords: Grapevine, Stem Water Potential, Leaf temperature, Vapor Pressure Deficit, Canopy development, soil water content, Crop Water Stress Index, infrared camera data
Abstract: Context and purpose of the study – Crop Water Stress Index (CWSI) has long been a ratio to quantify relative plant water status in several crop and woody plants. Given its rather well relationship to either leaf or stem water potential and the feasibility to sample big vineyard areas as well as to collect quite a huge quantity of data with airborne cameras and image processing applications, it is being studied as a tool for irrigation monitoring in commercial vineyards. The objective of this paper was to know if CWSI estimated by measuring leaf temperature with an infrared hand held camera could be used to substitute the measure of stem water potential (SWP) without losing accuracy of plant water status measure. Material and methods – Four vine water status were set up in 2017 on a Cabernet-Sauvignon vineyard grafted onto 110R at Morata de Tajuña (Madrid). Data herein involved correspond to 2018 growing season. Total Irrigation amount was 157, 241, 470 and 626 mm for treatments 1, 2, 3 and 4 respectively in 2018. Plants were 2-bud spur pruned along a unilateral cordon with 11-12 shoots per meter of raw. Training system was a Vertical Shoot Position (VSP). Experimental design was a randomize complete 4-block design with 3 rows per single plot, one central control row and two adjacent ones acting as buffer. Canopy development was measured by determining shaded soil at 10:30. Weather data were collected from a weather station at the same vineyard site. To calculate CWSI, leaf-treatment, wet leaf temperature and dryleaf temperatures were measured with an infrared camera model FLIR E60. All data were collected around th th noon at the same time as stem water potential (Ψs), on 5 cloudless days along 2018 - June 19 , July 24 , th th th August 7 , September 4 and 25 -. Four leaves per treatment were sampled each time of measurement. It was established a linear regression between CWSI and stem water potential. One treatment per measuring date (4 pair data) was kept out of the lineal regression and saved them to validate the model; All statistics analysis was performed with the Statistix10 package. th Results – Differences in CWSI arose from the first date of measure, June 19 . Differences in CWSI arise even before than in SWP; Highest SWP was -5.32 and the lowest was -13.80bar. At the end of the season, when overwhelming ambient conditions stayed long time CWSI did not show any difference between treatments despite SWP widely ranged between -6.85 and -10.53 bar between treatments. We found a significant linear relationship between CWSI and SWP (Ψs = 23.58·CWSI -2.87 R2= 0.63***). In an attempt to dig into the variables involved in plant water status we looked into a multiple regression in which SWP was dependent either on CWSI, vapor pressure deficit (VPD), canopy development (SS) and soil water content (Θs). However, none of these variables turned out to be significant but CWSI (R2=0.63**). Shaded soil was significant for P = 0.08. So far we can conclude that CWSI works out when stem water potential is below 14.0 bar.
Keywords: Grapevine, Stem Water Potential, Leaf temperature, Vapor Pressure Deficit, Canopy development, soil water content, Crop Water Stress Index, infrared camera data