A review of the issues, methods and perspectives for yield estimation, prediction and forecasting in viticulture

Autor: Thibaut Scholasch, James Taylor, Aurélie Metay, Baptiste Oger, Bruno Tisseyre, Cécile Laurent
Přispěvatelé: Fruition Sciences SAS [Montpellier], Agrosystèmes Biodiversifiés (UMR ABSys), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Information – Technologies – Analyse Environnementale – Procédés Agricoles (UMR ITAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), This work was funded by Fruition Sciences and supported by the French National Research Agency under the Investments for the Future Program, named #DigitAg, and referred as ANR-16-CONV-0004., ANR-16-CONV-0004,DIGITAG,Institut Convergences en Agriculture Numérique(2016)
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: European Journal of Agronomy
European Journal of Agronomy, 2021, 130, ⟨10.1016/j.eja.2021.126339⟩
ISSN: 1161-0301
DOI: 10.1016/j.eja.2021.126339⟩
Popis: International audience; Highlights:• Operational grapevine yield development includes vineyard/winery specific operations.• Operational needs drive the challenges that yield reporting methods have to meet.• Yield reporting methods are related to measurement, sampling and modelling issues.• Yield estimation, prediction and forecast address different levels of uncertainty.• Yield reporting methods should ensure a temporal, local, operational yield monitoring.Abstract: Grapevine yield is defined as the quantity of harvest, expressed as either grape mass or wine volumeunits, which has been collected per surface unit are and per crop cycle. The information about current and future yield, termed a yield assessment in this paper, is an essential decision-making element for the grape and wine industry. Crop management, wine-making, commercial, accounting and strategic operations are all adapted to and all impact on the expected yield of the current vintage. Numerous yield assessment approaches have been proposed in the scientific literature. However, only a few of them have considered their adaptation to the operational context under the constraints, needs and strategies of commercial vineyards and wineries. The few studies that have worked on the operational implementation of yield assessment methods have only partially addressed this issue, concentrating their improvement efforts on a single step in the yield assessment process. This paper first proposes to review the characteristics of yield development in an operational context that must be taken into account by yield assessment methodsThese characteristics are consolidated into three main challenges for yield assessment methods: (i) addressing the complex temporality of yield development, (ii) ensuring a local monitoring of yield development and (iii) fitting to the operational needs and constraints to allow for relevant decision support systems in the field. The approaches of yield estimation, prediction and forecast are discussed in the context of these challenges. In a second step, the paper proposes a generic framework for the yield assessment process, including a review of the variables that are used to explain grapevine yield. Issues and proposals from the literature associated respectively with measurement, sampling and yield modelling are reviewed and the need for improved modelling of relationships between explanatory variables and the desired, reported yield variable is discussed. The yield assessment methods found in the literature are categorised and compared according to measurement, estimation and modelling approaches, and then according to the three challenges identified for yield assessment in operational conditions, such that the yield assessment method is adapted to commercial needs and not to research objectives. In conclusion, concrete proposals for new grape yield assessment methods are discussed in order to investigate the as yet unexplored opportunities for the improvement in yield assessment in operational contexts that have been identified in the paper. These considerations could easily be transposed to other perennial crops.
Databáze: OpenAIRE
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