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Assessing the Impact of Deficit Irrigation and Kaolin Application on Almond Orchards: Statistical Relationships with Crop Yields and Spectral Vegetation Indices

2025Artigo científico Acesso aberto
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datacite.subject.fosCiências Agrárias::Agricultura, Silvicultura e Pescas
datacite.subject.fosEngenharia e Tecnologia::Engenharia do Ambiente
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg13:Ação Climática
dc.contributor.authorSilveira, Carlos
dc.contributor.authorBarreales, David
dc.contributor.authorCastro, João Paulo
dc.contributor.authorMiranda, Fabiani
dc.contributor.authorRibeiro, António C.
dc.date.accessioned2026-06-19T12:56:14Z
dc.date.available2026-06-19T12:56:14Z
dc.date.issued2025
dc.description.abstractGiven the current climate change scenario, it is essential to find strategies to reduce environmental risks and obtain economically sustainable agricultural productions. This study investigated the impact of various agronomic treatments on an almond orchard in northeastern Portugal, focusing on their relationships with crop growth/vigour and yield. The experiment was conducted using a factorial design that combined three variables: almond cultivar (Constantí and Vairo), irrigation regime (full and regulated deficit irrigation), and kaolin application (with or without application). These combinations resulted in eight distinct treatments, each replicated across two experimental plots. To monitor the crop physiological status, two drone flights equipped with a multispectral camera were flown during the kernel-filling stage (3 and 30 August 2021). Vegetation indices (VI) derived from the multispectral images were used to assess the crop vigour. In relation to the production data, including kernel and in-shell almond weights, these were collected in 14 representative trees of each treatment. Lastly, parametric and nonparametric regression analyses were performed to better understand relationships between VI and crop yields and derive predictive models. The main results can be summarised as follows: (a) cv. Vairo was more vulnerable to the regulated deficit irrigation strategy with striking repercussions on almond production, translating into an average reduction per tree of 22% and 16% in almond kernel and in-shell almonds compared to full irrigation, respectively; (b) kaolin application did not reflect statistically significant differences in the mean crop yield, as Tukey’s pairwise comparisons involving kaolin as a differentiating factor (e.g., C100+k—C100, V100+K—V100) showed confidence intervals with central value close to zero; and (c) regression analysis using the nonparametric random forest model and individualised treatments demonstrated a better agreement with the observed data (R2 > 0.7). This research provided valuable insights into how cultivar selection, irrigation strategy, and kaolin application can influence the almond crop performance. When integrating multispectral aerial monitoring and advanced statistical modelling, it enables an effective assessment of both crop vigour and expected yield, supporting the development of more informed and adaptive management practices to face emerging environmental challenges.eng
dc.description.sponsorshipThis work was supported by national funds through FCT/MCTES (PIDDAC): CIMO UID/00690/2025 (10.54499/UID/00690/2025) and UID/PRR/00690/2025 (10.54499/UID/PRR/00690/2025); SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020).
dc.identifier.citationSilveira, Carlos; Barreales, David; Castro, João Paulo; Miranda, Fabiani; Ribeiro, António C. (2025). Assessing the Impact of Deficit Irrigation and Kaolin Application on Almond Orchards: Statistical Relationships with Crop Yields and Spectral Vegetation Indices. AgriEngineering. ISSN 2624-7402. 7:11, p. 1-28
dc.identifier.doi10.3390/agriengineering7110395
dc.identifier.issn2624-7402
dc.identifier.urihttp://hdl.handle.net/10198/36910
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relationCIMO - Mountain Research Center - UID/PRR/00690/2025
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
dc.relationMountain Research Center - UID/00690/2025
dc.relation.ispartofAgriEngineering
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAlmond orchards
dc.subjectMultispectral aerial monitoring
dc.subjectOn-farm experiments
dc.subjectStatistical modelling
dc.subjectCrop yield predictions
dc.titleAssessing the Impact of Deficit Irrigation and Kaolin Application on Almond Orchards: Statistical Relationships with Crop Yields and Spectral Vegetation Indiceseng
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberUID/PRR/00690/2025
oaire.awardNumberLA/P/0007/2020
oaire.awardNumberUID/00690/2025
oaire.awardTitleCIMO - Mountain Research Center - UID/PRR/00690/2025
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
oaire.awardTitleMountain Research Center - UID/00690/2025
oaire.awardURIhttp://hdl.handle.net/10198/36356
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.awardURIhttp://hdl.handle.net/10198/35759
oaire.citation.endPage28
oaire.citation.issue11
oaire.citation.startPage1
oaire.citation.titleAgriEngineering
oaire.citation.volume7
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamCIMO
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameSilveira
person.familyNameBarreales
person.familyNameCastro
person.familyNameRibeiro
person.givenNameCarlos
person.givenNameDavid
person.givenNameJoão Paulo
person.givenNameAntónio C.
person.identifier.ciencia-id351A-FA79-885E
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person.identifier.ciencia-id8D19-DBCC-8EF5
person.identifier.ciencia-id9D19-E833-BE97
person.identifier.orcid0000-0002-9424-174X
person.identifier.orcid0000-0002-8425-0167
person.identifier.orcid0000-0003-0647-8892
person.identifier.orcid0000-0002-8280-9027
person.identifier.ridX-1640-2018
person.identifier.ridA-8581-2014
person.identifier.scopus-author-id55849743000
person.identifier.scopus-author-id57202136257
person.identifier.scopus-author-id21233448700
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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