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Vineyard Yield Estimation, Prediction, and Forecasting : A Systematic Literature Review

dc.contributor.authorBarriguinha, André
dc.contributor.authorNeto, Miguel de Castro
dc.contributor.authorGil, Artur José Freire
dc.date.accessioned2021-11-13T14:07:35Z
dc.date.available2021-11-13T14:07:35Z
dc.date.issued2021-09
dc.description.abstractPurpose—knowing in advance vineyard yield is a critical success factor so growers and winemakers can achieve the best balance between vegetative and reproductive growth. It is also essential for planning and regulatory purposes at the regional level. Estimation errors are mainly due to the high inter-annual and spatial variability and inadequate or poor performance sampling methods; therefore, improved applied methodologies are needed at different spatial scales. This paper aims to identify the alternatives to traditional estimation methods. Design/methodology/approach—this study consists of a systematic literature review of academic articles indexed on four databases collected based on multiple query strings conducted on title, abstract, and keywords. The articles were reviewed based on the research topic, methodology, data requirements, practical application, and scale using PRISMA as a guideline. Findings—the methodological approaches for yield estimation based on indirect methods are primarily applicable at a small scale and can provide better estimates than the traditional manual sampling. Nevertheless, most of these approaches are still in the research domain and lack practical applicability in real vineyards by the actual farmers. They mainly depend on computer vision and image processing algorithms, data-driven models based on vegetation indices and pollen data, and on relating climate, soil, vegetation, and crop management variables that can support dynamic crop simulation models. Research limitations—this work is based on academic articles published before June 2021. Therefore, scientific outputs published after this date are not included. Originality/value—this study contributes to perceiving the approaches for estimating vineyard yield and identifying research gaps for future developments, and supporting a future research agenda on this topic. To the best of the authors’ knowledge, it is the first systematic literature review fully dedicated to vineyard yield estimation, prediction, and forecasting methods.en
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBarriguinha, A., Neto, M. C. & Gil, A. (2021). Vineyard yield estimation, prediction, and forecasting: a systematic literature review. "Agronomy", 11(9), 1-27. [1789]. DOI:10.3390/agronomy11091789en
dc.identifier.doi10.3390/agronomy11091789pt_PT
dc.identifier.eissn2073-4395
dc.identifier.urihttp://hdl.handle.net/10400.3/6108
dc.identifier.urihttp://hdl.handle.net/10362/124761
dc.identifier.wos000699161500001
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relation.publisherversionhttps://www.mdpi.com/2073-4395/11/9/1789pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectEstimationen
dc.subjectForecastingen
dc.subjectPredictionen
dc.subjectSystematic Literature Reviewen
dc.subjectVineyarden
dc.subjectYielden
dc.titleVineyard Yield Estimation, Prediction, and Forecasting : A Systematic Literature Reviewen
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceSwitzerlandpt_PT
oaire.citation.endPage27pt_PT
oaire.citation.issue9pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleAgronomypt_PT
oaire.citation.volume11pt_PT
person.familyNameFreire Gil
person.givenNameArtur José
person.identifierI-7520-2012
person.identifier.ciencia-id6E1A-0689-D573
person.identifier.orcid0000-0003-4450-8167
person.identifier.scopus-author-id37064609200
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication24d6aa34-c843-42df-b790-912f09560a80
relation.isAuthorOfPublication.latestForDiscovery24d6aa34-c843-42df-b790-912f09560a80

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