Towards estimating the proportion of dead and missing vines at the field level

This work aimed to improve practices for estimating dead and missing vines, particularly when these estimations are made via sampling. Vine mortality is a well-known phenomenon that many studies have attempted to better explain, but only a few have focused on estimating the number of dead and missing vines at the field-level, which remains a challenging task for grapegrowers. The present article aimed to determine to what extend an increased an increased sampling effort improves estimation accuracy and thus help practitioners define a sample size adapted to vineyard properties and the accuracy expected by the grower. The first part of the study investigated whether vineyard properties (year of planting and variety) and available ancillary data (soil resistivity and fraction of vegetation cover [Fcover]) can provide a priori information on the proportion of dead and missing vines and guide the sampling strategy. The analysis was based on an exhaustive dataset created by individually mapping 14,199 dead and missing vines across 29 fields in a 20 ha vineyard. In this vineyard, regression models showed an increase in dead and missing vines of around 2.2 % per year from the tenth year onwards. Plantation year, variety and vigour (assessed by Fcover) were identified as providing valuable prior information on the proportion of dead and missing vines within the fields. The second part of the study focused on characterising the estimation error values that can result from these estimations. It focuses on sampling estimation, highlighting to what extent field properties (such as the number of dead and missing vines and their spatial autocorrelation) affect the accuracy of estimates. The results showed that the same sampling protocol can result in different accuracies from one field to another. Thus, they underline the importance of leveraging prior information, such as available field data, to tailor sampling efforts accordingly. Based on these results, this article introduces new guidelines to facilitate the estimation of the proportion of dead and missing vines in vineyards.

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Publication Details

Journal
OENO One
Published
2025-01-10
DOI
https://doi.org/10.20870/oeno-one.2025.59.1.8061
Citations
1
Primary Topic
Horticultural and Viticultural Research
Type
article
Field-Weighted Citation Impact
1.75

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article

Towards estimating the proportion of dead and missing vines at the field level

Philippe Vismara, Baptiste Oger, Bruno Tisseyre, Cécile Laurent
1 citations
OENO One
Horticultural and Viticultural Research
1.75
article

Towards estimating the proportion of dead and missing vines at the field level

Philippe Vismara, Baptiste Oger, Bruno Tisseyre, Cécile Laurent
article en
1 citations

Abstract

This work aimed to improve practices for estimating dead and missing vines, particularly when these estimations are made via sampling. Vine mortality is a well-known phenomenon that many studies have attempted to better explain, but only a few have focused on estimating the number of dead and missing vines at the field-level, which remains a challenging task for grapegrowers. The present article aimed to determine to what extend an increased an increased sampling effort improves estimation accuracy and thus help practitioners define a sample size adapted to vineyard properties and the accuracy expected by the grower. The first part of the study investigated whether vineyard properties (year of planting and variety) and available ancillary data (soil resistivity and fraction of vegetation cover [Fcover]) can provide a priori information on the proportion of dead and missing vines and guide the sampling strategy. The analysis was based on an exhaustive dataset created by individually mapping 14,199 dead and missing vines across 29 fields in a 20 ha vineyard. In this vineyard, regression models showed an increase in dead and missing vines of around 2.2 % per year from the tenth year onwards. Plantation year, variety and vigour (assessed by Fcover) were identified as providing valuable prior information on the proportion of dead and missing vines within the fields. The second part of the study focused on characterising the estimation error values that can result from these estimations. It focuses on sampling estimation, highlighting to what extent field properties (such as the number of dead and missing vines and their spatial autocorrelation) affect the accuracy of estimates. The results showed that the same sampling protocol can result in different accuracies from one field to another. Thus, they underline the importance of leveraging prior information, such as available field data, to tailor sampling efforts accordingly. Based on these results, this article introduces new guidelines to facilitate the estimation of the proportion of dead and missing vines in vineyards.

OENO OneVol. 59(1)
Université de Montpellier (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Mathématiques, Informatique et Statistique pour l'Environnement et l'Agronomie (FR), Technologies & méthodes pour les agricultures de demain (FR)
Région Occitanie Pyrénées-Méditerranée
Openalex Percentile: Top 18%
Horticultural and Viticultural Research
1.75
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