EGU25-2520, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-2520
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 30 Apr, 09:15–09:25 (CEST)
 
Room -2.21
Linking Citrus Fruit Cracking Intensity to Plant Water Status: Insights from UAV-Derived Metrics Validated by Ground-Based Data
Moshe (Vladislav) Dubinin1, Michael Morozov2, Avi Sadka2, and Tarin Paz-Kagan1
Moshe (Vladislav) Dubinin et al.
  • 1Ben-Gurion University, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, French Associates Institute for Agriculture and Biotechnology of Dryland, Israel (dubinin@post.bgu.ac.il)
  • 2Department of Fruit Tree Sciences, Agricultural Research Organization, The Volcani Institute, 7528809, Rishon LeZion, Israel

Citrus fruit cracking, a physical failure of the peel, causes yield losses of 10% to 35%, peaking during October-November. Water status of the tree and water flow into the fruit influence this phenomenon. with excessive irrigation during critical fruit development stages exacerbates cracking. As part of the EU-Horizon CrackSense project, this study is aimed to link citrus tree plant water status (PWS) to fruit cracking, emphasizing how deficit irrigation can reduce yield loss due to cracking. Using UAV and eco-physiological measurements, we developed models to predict PWS and its relationship with cracking intensity early in the season. The study, conducted in 2023-2024 in a commercial orchard near Kfar Chabad, Israel, tested four irrigation treatments: control, defined as the standard irrigation, two deficits irrigations regimes (50% of control) early and late in the season, and excessive irrigation (150% of control) throughout the season. Ground-based measurements included fruit and trunk diameter, stem water potential (SWP), stomatal conductance, plant area index (PAI), and growth rate (TG). UAV flights integrated multispectral, thermal, and LiDAR sensors to capture spatial-temporal variability in PWS. Canopy metrics, such as height, volume, LiDAR-based PAI, and spectral and thermal indices, were incorporated into PWS models. Results revealed significant differences in TG, SWP, and stomatal conductance for 50% of early and late deficit irrigation treatments compared to other treatments. Random forest models demonstrated strong predictive performance for SWP (R² > 0.77) and TG (R² > 0.76). LiDAR-derived PA correlated highly with field optical measurements (R² = 0.92), yield (R² = 0.67), and cracked fruit percentages (R² > 0.50). This study underscores the importance of precise irrigation management in reducing fruit cracking. It highlights the potential of remote sensing systems for predicting cracking and managing water status at the tree level. The developed models equip farmers with tools to apply controlled water stress, minimizing cracking and improving yield.

How to cite: Dubinin, M. (., Morozov, M., Sadka, A., and Paz-Kagan, T.: Linking Citrus Fruit Cracking Intensity to Plant Water Status: Insights from UAV-Derived Metrics Validated by Ground-Based Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2520, https://doi.org/10.5194/egusphere-egu25-2520, 2025.