Prescriptive watering: Data-driven optimization of water consumption in kiwifruit orchards

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Authors: Alex Baiardi, Matteo Francia, Matteo Golfarelli, Alessandro Vittorio Papadopoulos, Manuele Pasini
Cited by: 0
References: 30

Abstract

Climate change and increasing water scarcity demand innovative irrigation strategies, especially for high-value crops like kiwifruit that require precise water management. Traditional irrigation systems often fail to address the spatial and temporal variability of soil moisture in orchards, where factors like canopy coverage and localized watering patterns complicate remote monitoring. This paper introduces SMARTER , a soil-agnostic, prescriptive irrigation system designed specifically for kiwifruit orchards. It uses a two-dimensional grid of sensors to construct detailed, real-time soil moisture profiles, which are then processed to recommend irrigation volumes. SMARTER operates in two phases: an offline phase, where agronomists define optimal soil moisture targets, and an online phase, where data-driven monitoring and Proportional–Integral control algorithms guide irrigation decisions. Field evaluations during the 2023 and 2024 irrigation seasons in two commercial kiwifruit orchards in Italy demonstrated water savings of up to 40% compared to traditional irrigation practices, without compromising fruit quality and with a break-even point of two years. Unlike traditional simulators or data-hungry machine learning models, SMARTER does not require complex parameter calibration, soil-specific tuning, or historical data, making it deployable and actionable as soon as sensors are deployed. Furthermore, SMARTER effectively adapts to events like rainfall and irrigation deviations.

Fields of Study & Subjects

Smart Agriculture and AI Irrigation Practices and Water Management Soil Moisture and Remote Sensing

Publication details

Journal / source
Computers and Electronics in Agriculture
Volume
243
Pages
111306–111306
Publication date
10 January 2026
Language
EN