In recent decades, plant-based sensors have been increasingly used to monitor plant water status, detecting water stress and improving irrigation scheduling. Among these sensors, microtensiometer (MT) continuously measures trunk water potential (TWP) supporting real-time monitoring of TWP and in turn plant water need assessment. However, MT response to environmental stimuli as mediated by plant has not yet fully elucidated. This study reports on a two-year experiment modelling the response of MT-based TWP to changing soil water content (SWC) and air vapor pressure deficit (VPD). During summer time, at a commercial kiwifruit vineyard, vines (n = 63) were differentially irrigated (100%, 50%, 25% of full irrigation need) for ~ 52 days and grouped in CTRL, Mild and Severe, respectively. In two vines per group, the TWP was monitored using MT (20-min interval). Parallel VPD and SWC (× 3 FDR probes) were also recorded. During the experiments drought stressed vines were recovered. Across treatments, soil moisture ranged from approx. 40% to 18%, and the corresponding TWP from approx. – 0.01 to – 1.1 MPa. Results show that a piecewise linear regression model explains the relationship between MT-based TWP and the pressure chamber-based stem water potential (SWP) (R2 = 0.78) showing different slopes when SWP drops below – 1.6 MPa. The response of TWP to changing VPD and SWC was analyzed at daily scale and throughout the season. A model accounting for time-lag between TWP and VPD and for the hysteresis of TWP shows that the diurnal TWP is mostly driven by VPD (R2 = 0.74) in well-irrigated vines. To explain TWP response in Mild and Severe irrigation treatment, the model also included the SWC term achieving R2 = 0.66. Potential application of MT for irrigation management along with some limitations (e.g., long-term durability) are also discussed.

Microtensiometer-based trunk water potential as a plant water status indicator in kiwifruit under different soil water availability

Di Biase, Roberto;Calabritto, Maria;Mininni, Alba N.
;
Montanaro, Giuseppe;Dichio, Bartolomeo
2025-01-01

Abstract

In recent decades, plant-based sensors have been increasingly used to monitor plant water status, detecting water stress and improving irrigation scheduling. Among these sensors, microtensiometer (MT) continuously measures trunk water potential (TWP) supporting real-time monitoring of TWP and in turn plant water need assessment. However, MT response to environmental stimuli as mediated by plant has not yet fully elucidated. This study reports on a two-year experiment modelling the response of MT-based TWP to changing soil water content (SWC) and air vapor pressure deficit (VPD). During summer time, at a commercial kiwifruit vineyard, vines (n = 63) were differentially irrigated (100%, 50%, 25% of full irrigation need) for ~ 52 days and grouped in CTRL, Mild and Severe, respectively. In two vines per group, the TWP was monitored using MT (20-min interval). Parallel VPD and SWC (× 3 FDR probes) were also recorded. During the experiments drought stressed vines were recovered. Across treatments, soil moisture ranged from approx. 40% to 18%, and the corresponding TWP from approx. – 0.01 to – 1.1 MPa. Results show that a piecewise linear regression model explains the relationship between MT-based TWP and the pressure chamber-based stem water potential (SWP) (R2 = 0.78) showing different slopes when SWP drops below – 1.6 MPa. The response of TWP to changing VPD and SWC was analyzed at daily scale and throughout the season. A model accounting for time-lag between TWP and VPD and for the hysteresis of TWP shows that the diurnal TWP is mostly driven by VPD (R2 = 0.74) in well-irrigated vines. To explain TWP response in Mild and Severe irrigation treatment, the model also included the SWC term achieving R2 = 0.66. Potential application of MT for irrigation management along with some limitations (e.g., long-term durability) are also discussed.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/201837
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