Articles
Using stomatal conductance as a water status indicator in grapevine: implementation into a decision support system for irrigation management
Article number
1314_1
Pages
1 – 8
Language
English
Abstract
Prediction of grapevine water status can be performed nowadays with decision support systems (DSS). In some cases, the DSS predicts predawn leaf water potential (Ψpd), modelling the soil-plant-atmosphere continuum, and provides irrigation recommendations to maintain a desired Ψpd. Although Ψpd is a good indicator of water status, leaf stomatal conductance (gs) can provide additional feedback on how the vine is responding to its water status from a physiological point of view.
Moreover, leaf gs measured with portable porometers can be a good ground-truthing alternative to pressure chamber measurements.
The objective of this research was to propose a model of leaf gs as a complementary indicator of water status.
In 2017, Ψpd and early-morning, mid-morning and midday leaf gs were measured eight days between budbreak and harvest in 10 plant replicates in four vineyards (Grenache, Cinsault and two plots of Syrah) under irrigated and non-irrigated conditions (about 640 measurements for each trait). Ψpd was able to explain 59% of the variability observed in leaf gs and the best model consisted in an exponential regression including Ψpd and mean air temperature as independent variables (R2=0.70). In 2018, additional data was collected for model evaluation.
The variation in leaf gs that was explained by the previous model varied significantly between different data sets used for model validation (75% in a new plot of Macabeu, 55% for the same plots used in 2017, and 25% in a new plot of Merlot). These results may indicate that the development of a robust empirical model of leaf gs may require a larger data set.
The construction of models including specific coefficients for each cultivar and hour of measurement is another alternative to increase the robustness of gs predictions but from a practical point of view they may be difficult to implement in a DSS. The coefficients of the model equation for all the existing cultivars are not known and the hourly specific models limit the time when the grower can perform gs measurements to ground-truth the DSS. Having in mind that a generic model of leaf gs using Ψpd and mean air temperature may not capture the variability of all existing vineyards, it could be strategic to implement a generic model into a DSS as a first step and improve the model as information on leaf gs from multiple vineyards is collected from users.
Moreover, leaf gs measured with portable porometers can be a good ground-truthing alternative to pressure chamber measurements.
The objective of this research was to propose a model of leaf gs as a complementary indicator of water status.
In 2017, Ψpd and early-morning, mid-morning and midday leaf gs were measured eight days between budbreak and harvest in 10 plant replicates in four vineyards (Grenache, Cinsault and two plots of Syrah) under irrigated and non-irrigated conditions (about 640 measurements for each trait). Ψpd was able to explain 59% of the variability observed in leaf gs and the best model consisted in an exponential regression including Ψpd and mean air temperature as independent variables (R2=0.70). In 2018, additional data was collected for model evaluation.
The variation in leaf gs that was explained by the previous model varied significantly between different data sets used for model validation (75% in a new plot of Macabeu, 55% for the same plots used in 2017, and 25% in a new plot of Merlot). These results may indicate that the development of a robust empirical model of leaf gs may require a larger data set.
The construction of models including specific coefficients for each cultivar and hour of measurement is another alternative to increase the robustness of gs predictions but from a practical point of view they may be difficult to implement in a DSS. The coefficients of the model equation for all the existing cultivars are not known and the hourly specific models limit the time when the grower can perform gs measurements to ground-truth the DSS. Having in mind that a generic model of leaf gs using Ψpd and mean air temperature may not capture the variability of all existing vineyards, it could be strategic to implement a generic model into a DSS as a first step and improve the model as information on leaf gs from multiple vineyards is collected from users.
Authors
P. Juillion, M. Gelly, J. Chopard, D. Tarsitano, L. Chalayer, A. Guaus, P. Hublart, G. Lopez, D. Fumey
Keywords
crop modelling, irrigation scheduling, plant physiology, precision agriculture, Vitis vinifera, water stress
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