Enoforum 2021
IVES 9 IVES Conference Series 9 Enoforum Web 9 Enoforum Web Conference 2021 9 A new AI-based system for early and accurate vineyard yield forecasting

A new AI-based system for early and accurate vineyard yield forecasting

Abstract

Vineyard yield forecasting is a key issue for vintage scheduling and optimization of winemaking operations. High errors in yield forecasting can be found in the wine industry, mainly due to the high spatial variability in vineyards, strong dependency on historical yield data, insufficient use of agroclimatic data and inadequate sampling methods. Today, errors can reach values within the range of 20%-30% per block. Thus, improved methodologies for early and accurate vineyard yield forecasting are needed. We proposed a new system for vineyard yield forecasting that integrates: systematic cluster counting, sampling and weight measurement; key agroclimatic parameters; vineyards spatial variability and the use of forecasting models based on artificial intelligence (AI). We carried out trials in high yield Cabernet Sauvignon (CS) vineyards located in Maule Valley (Chile), during seasons 2019 and 2020. We covered 13 blocks (66 ha) and two trellis systems (pergola and free-cordon). We characterized the spatial variability of blocks using Sentinel 2 images and NDVI analysis. We defined sampling units based on NDVI levels and we counted and sampled grape clusters and measured their weights during fruit-set and veraison. Key agroclimatic data were taken from public databases and we collected yield historical data from 2017 onwards. We trained and applied machine-learning models based on MARS, Random Forest and SVR algorithms. For the 2020 trial, in veraison, we obtained an average error of 7.6% per block against a 10.1% given by the traditional method (error is 23.5% for all the CS grapes of the company). Time dedicated to counting and sampling was significantly lower. As a result, we obtained a cost-efficient, early and accurate new system for vineyard yield forecasting.

DOI:

Publication date: April 23, 2021

Issue: Enoforum 2021

Type: Article

Authors

Cuevas-Valenzuela, José1*; Caris-Maldonado, Carlos1; Reyes-Suárez, José Antonio2; González-Rojas, Álvaro1

1 Center for Research and Innovation (CRI) Viña Concha y Toro, Ruta k-650 km 10, Pencahue, Maule, Chile
2 Bioinformatics Department, Faculty of Engineering, Universidad de Talca, Campus Lircay, Talca, Maule, Chile

Contact the author

Tags

Enoforum 2021 | IVES Conference Series

Citation

Related articles…

Phenolic composition profile of cv. Tempranillo wines obtained from severe shoot pruning vines under semiarid conditions

One of the limitations of vineyards in warm areas is the loss of wine quality due to higher temperatures during the grape ripening period. In order to adapt the vineyards to these new climatic conditions, a possible solution is to delay the ripening process of the grapes towards periods with milder temperatures, by means of management practices and thus improve the quality of the fruit and the wine produced. The technique of severe shoot pruning (SSP) has proven useful in achieving this objective.

Variety and climatic effects on quality scores in the Western US winegrowing regions

Wine quality is strongly linked to climate. Quality scores are often driven by climate variation across different winegrowing regions and years, but also influenced by other aspects of terroir, including variety. While recent work has looked at the relationship between quality scores and climate across many European regions, less work has examined New World winegrowing regions. Here we used scores from three major rating systems (Wine Advocate, Wine Enthusiast and Wine Spectator) combined with daily climate and phenology data to understand what drives variation across wine quality scores in major regions of the Western US, including regions in California, Oregon and Washington. We examined effects of variety, region, and in what phenological period climate was most predictive of quality. As in other studies, we found climate, based mainly on growing degree day (GDD) models, was generally associated with quality—with higher GDD associated with higher scores—but variety and region also had strong effects. Effects of region were generally stronger than variety. Certain varieties received the highest scores in only some areas, while other varieties (e.g., Merlot) generally scored lower across regions. Across phenological stages, GDD during budbreak was often most strongly associated with quality. Our results support other studies that warmer periods generally drive high quality wines, but highlight how much region and variety drive variation in scores outside of climate.

Achieving Tropical Fruit Aromas in White Wine through Innovative Winemaking Processes

Tropical fruit aroma is highly desirable in certain white wine styles and there is a significant group of consumers that show preference for this aroma.

Estudio de la adaptación y del comportamiento productivo y enológico de variedades blancas foráneas en la zona vitícola del Penedés

Estudio comparativo del comportamiento de ocho variedades de viníferas blancas en el Penedés, injertadas sobre los portainjertos 41-B y 110-R.
Se describen los comportamientos

Assessment of environmental sustainability of wine growing activity in France

To meet the demand of assessment tool of vine growers and their advisers we adapted to the vine production the INDIGO® method to developed initially for arable farming.