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Instituto de Investigação
em Vulcanologia e Avaliação de Riscos
Última hora:
  • Ilha de S. Jorge (Sistema Vulcânico Fissural de Manadas) em Alerta Científico V3, após reativação do sistema vulcânico em profundidadeIlha Terceira (Vulcão de Santa Bárbara) em Alerta Científico V2 devido aos níveis de atividade microssísmicaAtividade sísmica na ilha de São Jorge encontra-se acima dos valores normais de referênciaAtividade sísmica no Vulcão de Santa Bárbara (ilha Terceira) encontra-se acima dos valores normais de referênciaIlha de S. Jorge, último sismo sentido: 17 de agosto às 22:04h, intensidade máxima III na freguesia de UrzelinaCIVISA apela ao preenchimento do inquérito de macrossísmica em caso de sentir um sismo

Artigos em revistas ► internacionais com arbitragem


Referência Bibliográfica

BARRIGUINHA, A., NETO, M.C., GIL, A. (2021) - Vineyard yield estimation, prediction, and forecasting: a systematic literature review. Agronomy, 11(9): 1789, doi: 10.3390/agronomy11091789.


​Purpose - 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.