Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing

Precise irrigation scheduling is critical to efficient water use, particularly in high-value tree crops with limited irrigation supply. This study evaluates an irrigation scheduling methodology for almond orchards, previously studied in experimental fields, applied to a commercial almond farm (cv. L...

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Main Authors: Rafael Orozco-Moran, Jose A. Jimenez-Berni, Elias Fereres, Francisco Orgaz
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Agricultural Water Management
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0378377425001696
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author Rafael Orozco-Moran
Jose A. Jimenez-Berni
Elias Fereres
Francisco Orgaz
author_facet Rafael Orozco-Moran
Jose A. Jimenez-Berni
Elias Fereres
Francisco Orgaz
author_sort Rafael Orozco-Moran
collection DOAJ
description Precise irrigation scheduling is critical to efficient water use, particularly in high-value tree crops with limited irrigation supply. This study evaluates an irrigation scheduling methodology for almond orchards, previously studied in experimental fields, applied to a commercial almond farm (cv. Lauranne) over a four-year period and incorporating new technologies for canopy characterization and water stress assessment. Four irrigation treatments were studied: a control (F) based on the crop evapotranspiration estimated using crop coefficient derived from LiDAR, two over-irrigation treatments (SR1, SR2) with 22 % and 44 % increment of irrigation, and a deficit (D) with 30 % reduction over F. Despite increasing the amount of water by 22 % and 44 % in the over-irrigated treatments, no significant increase in yield was observed compared to the control treatment (2800 kg/ha), suggesting that F represents an optimal irrigation level. By contrast, the deficit treatment showed a cumulative yield reduction of 20 % over the four years, highlighting the impact of the reduction in water supply below that of F on cumulative yield. Advanced technologies such as LiDAR to capture canopy information and remote thermography to monitor the crop’s water status were essential to finetuning and improving irrigation scheduling decisions. This study emphasizes the need for long-term studies in established commercial orchards to enhance the sustainability and efficiency of agricultural practices.
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spelling doaj-art-684d2153457f44dabe82dcbd753729a52025-08-20T02:13:59ZengElsevierAgricultural Water Management1873-22832025-05-0131310945510.1016/j.agwat.2025.109455Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensingRafael Orozco-Moran0Jose A. Jimenez-Berni1Elias Fereres2Francisco Orgaz3Department of Agronomy, Institute of Sustainable Agriculture (IAS-CSIC), Córdoba, Spain; Programa de Doctorado de Ingeniería Agraria, Alimentaria, Forestal y del Desarrollo Rural Sostenible, Universidad de Córdoba, Spain; Corresponding author at: Department of Agronomy, Institute of Sustainable Agriculture (IAS-CSIC), Córdoba, Spain.Department of Agronomy, Institute of Sustainable Agriculture (IAS-CSIC), Córdoba, Spain; Corresponding author.Department of Agronomy, Institute of Sustainable Agriculture (IAS-CSIC), Córdoba, Spain; Departamento de Agronomía, Universidad de Córdoba, SpainDepartment of Agronomy, Institute of Sustainable Agriculture (IAS-CSIC), Córdoba, SpainPrecise irrigation scheduling is critical to efficient water use, particularly in high-value tree crops with limited irrigation supply. This study evaluates an irrigation scheduling methodology for almond orchards, previously studied in experimental fields, applied to a commercial almond farm (cv. Lauranne) over a four-year period and incorporating new technologies for canopy characterization and water stress assessment. Four irrigation treatments were studied: a control (F) based on the crop evapotranspiration estimated using crop coefficient derived from LiDAR, two over-irrigation treatments (SR1, SR2) with 22 % and 44 % increment of irrigation, and a deficit (D) with 30 % reduction over F. Despite increasing the amount of water by 22 % and 44 % in the over-irrigated treatments, no significant increase in yield was observed compared to the control treatment (2800 kg/ha), suggesting that F represents an optimal irrigation level. By contrast, the deficit treatment showed a cumulative yield reduction of 20 % over the four years, highlighting the impact of the reduction in water supply below that of F on cumulative yield. Advanced technologies such as LiDAR to capture canopy information and remote thermography to monitor the crop’s water status were essential to finetuning and improving irrigation scheduling decisions. This study emphasizes the need for long-term studies in established commercial orchards to enhance the sustainability and efficiency of agricultural practices.http://www.sciencedirect.com/science/article/pii/S0378377425001696Tree water statusEvapotranspirationCrop water requirementsYield modelingCanopy characterizationLiDAR
spellingShingle Rafael Orozco-Moran
Jose A. Jimenez-Berni
Elias Fereres
Francisco Orgaz
Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing
Agricultural Water Management
Tree water status
Evapotranspiration
Crop water requirements
Yield modeling
Canopy characterization
LiDAR
title Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing
title_full Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing
title_fullStr Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing
title_full_unstemmed Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing
title_short Irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing
title_sort irrigation scheduling of an almond orchard using the water balance and remote and proximal sensing
topic Tree water status
Evapotranspiration
Crop water requirements
Yield modeling
Canopy characterization
LiDAR
url http://www.sciencedirect.com/science/article/pii/S0378377425001696
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AT eliasfereres irrigationschedulingofanalmondorchardusingthewaterbalanceandremoteandproximalsensing
AT franciscoorgaz irrigationschedulingofanalmondorchardusingthewaterbalanceandremoteandproximalsensing