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dc.contributor.authorMiras-Ávalos, José M.
dc.contributor.authorRubio-Asensio, José S.
dc.contributor.authorRamírez-Cuesta, Juan M.
dc.contributor.authorMaestre-Valero, José F.
dc.contributor.authorIntrigliolo, Diego S.
dc.date.accessioned2020-04-24T16:10:09Z
dc.date.available2020-04-24T16:10:09Z
dc.date.issued2019
dc.identifier.citationMirás-Avalos, J. M., Rubio-Asensio, J. S., Ramírez-Cuesta, J. M., Maestre-Valero, J. F., & Intrigliolo, D. S. (2019). Irrigation-Advisor—A Decision Support System for Irrigation of Vegetable Crops. Water, 11(11), 2245.
dc.identifier.issn2073-4441
dc.identifier.urihttp://hdl.handle.net/20.500.11939/6401
dc.description.abstractClimate change will intensify water scarcity, and therefore irrigation must be adapted to save water. Operational tools that provide watering recommendations to end-users are needed. This work presents a new tool, Irrigation-Advisor (IA), which is based on weather forecasts and is able to separately determine soil evaporation and crop transpiration, and thus is adaptable to a broad range of agricultural situations. By calculating several statistical indicators, IA was tested against the FAO-56 crop evapotranspiration (ETcFAO) methodology using local crop coe cients. Additionally, IA recommendations were compared with current standard practices by experienced farmers (F). Six field experiments with four widely cultivated species (endive, lettuce, muskmelon and potato) were performed in Southeast Spain. Irrigation water applied, crop yield, aboveground biomass and water productivity were determined. Crop water needs underestimations (5%–20%) were detected when comparing IA against ETcFAO, although the index of agreement proved reasonable adjustments. The IA recommendations led to water savings up to 13% when compared to F, except for lettuce, with a 31% surplus in irrigation when using IA. Crop yield was not compromised and water productivity was increased by IA. Therefore, IA mimicked the farmers0 irrigation strategies fairly well without deploying sensors on-site. Nevertheless, improvements are needed for increasing the accuracy of IA estimations.es
dc.language.isoenes
dc.publisherMDPIes
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectModellinges
dc.titleIrrigation-Advisor—A Decision Support System for Irrigation of Vegetable Cropses
dc.typearticlees
dc.authorAddressInstituto Valenciano de Investigaciones Agrarias (IVIA), Carretera CV-315, Km. 10’7, 46113 Moncada (Valencia), Españaes
dc.entidadIVIACentro para el Desarrollo de la Agricultura Sosteniblees
dc.identifier.doi10.3390/w11112245es
dc.identifier.urlhttps://www.mdpi.com/2073-4441/11/11/2245es
dc.journal.issueNumber11es
dc.journal.titleWateres
dc.journal.volumeNumber11es
dc.page.final2245es
dc.page.initial2245es
dc.source.typeelectronicoes
dc.subject.agrisF06 Irrigationes
dc.subject.agrovocEvapotranspirationes
dc.subject.agrovocSoil water balancees
dc.subject.agrovocWater use efficiencyes
dc.subject.agrovocWeather forecastinges
dc.type.hasVersionpublishedVersiones


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Atribución-NoComercial-SinDerivadas 3.0 España
Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España