Combining plant-based sensing and mechanistic modelling to quantify hydraulic resistance and capacitance for real-time irrigation in Mediterranean yellow-fleshed kiwifruit orchards

Climate change and increasing water scarcity, especially in the Mediterranean region, are major challenges for modern agriculture, requiring the implementation of real-time irrigation management methods to improve whole-plant water use efficiency. In the present study, two plant-based measurements (trunk sap flow and trunk water potential, ψtrunk) were used in combination with a dynamic water flow model to estimate hydraulic capacitance (C) and hydraulic resistance (R) along the water transport pathway in yellow-fleshed kiwifruit vines grown in a Mediterranean environment under both well-watered and drought conditions. A sensitivity analysis of the model was performed to select a subset of identifiable parameters, accounting for most of the variability in model predictions of ψtrunk. Based on the identifiable parameters, two model calibrations were performed: (1) model calibration of C and R; (2) model calibration of C, R and the initial amount of water stored in the stem compartment. These parameters were recalibrated daily based on a 1-day moving window. The best model performance under soil water limiting conditions was achieved when all three parameters were used for calibration. C and R parameters strongly correlated with ψtrunk, revealing the hydraulic behavior and drought response of kiwifruit vines. In particular, C was found to decrease with more negative ψtrunk values, whereas R showed an increase. In addition, C and R varied within a narrow range of ψtrunk fluctuations, as occurred in well-watered vines. While the proposed modelling approach requires investments in sensor technologies and a data management and modelling platform, it offers the potential to quantify and visualize daily dynamics in plant hydraulic parameters and provide farmers with valuable tools to improve real-time management of irrigation in the era of precision agriculture.