GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 GiESCO 2019 9 Data mining approaches for time series data analysis in viticulture. Potential of the bliss (Bayesian functional linear regression with sparse step functions) method to identify temperature effects on yield potential

Data mining approaches for time series data analysis in viticulture. Potential of the bliss (Bayesian functional linear regression with sparse step functions) method to identify temperature effects on yield potential

Abstract

Context and purpose of the study – Vine development, and hence management, depends on dynamic factors (climate, soil moisture, cultural practices etc.) whose impact can vary depending upon their temporal modalities (timing, duration, threshold, eventually trajectory and memory effects). Therefore, understanding the effect of the temporal variation of these factors on grapevine physiology would be of strategic benefit in viticulture, for example in establishing yield potential. Today many estates own data that can support temporal analyses, while the emergence of precision viticulture allows management at higher spatial and temporal resolutions. These data are a great opportunity to advance knowledge about the dynamics of grapevine physiology and production, and promote an improved precision of vineyard practices. The exploitation of these data needs analytical methods that fully explore time series data. However, current methods tend to only focus on a few key phenological stages or time steps. Such approaches do not fully address the potential information captured by continuous temporal measurements because they introduce limitations : i) they rely on choices of variables and timing, ii) they often require suppressing data or analysing only parts of a time series and iii) data correlation over time is not taken into account. A new approach is explored in this paper, using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS method). The BLiSS method overcomes the mentioned limitations and leads to a more complete and objective analysis of time series data. Based on the identification of climatic periods affecting yield, the objective of the study is to evaluate the potential of the BLiSS method.

Materials and method ‐ Minimum and maximum daily temperatures during the year preceding the harvest year were regressed against the number of clusters per vine using the BLiSS method on one block of a commercial vineyard in the Bordeaux region over 11 years. The reliability and pertinence of the BLiSS method to reveal already reported, ignored or underestimated temperature effects on the number of clusters per vine are tested by comparison with literature results.

Results ‐ The BLiSS method allowed the detection of periods when temperature influenced the number of clusters per vine during the year preceding the harvest year. Some of the detected periods of influence had already been reported in literature. However, the BLiSS outcomes suggested that some of those known periods may have a different duration or several effects, thus challenging actual knowledge. Finally, some new periods of influence were identified by the BLiSS method. These results confirmed the potential of the BLiSS method to undertake a fuller exploration of time series data in the case of climate influence on grape yield.

DOI:

Publication date: June 22, 2020

Issue: GiESCO 2019

Type: Article

Authors

Cécile LAURENT (1,2,3), Meïli BARAGATTI (4), James TAYLOR (1), Bruno TISSEYRE (1), Aurélie METAY (2), Thibaut SCHOLASCH (3)

(1) ITAP, Univ. Montpellier, Montpellier SupAgro, Irstea, France
(2) SYSTEM, Univ Montpellier, CIHEAM-IAMM, CIRAD, INRA, Montpellier SupAgro, France
(3) Fruition Sciences, Montpellier, France
(4) MISTEA, Univ Montpellier Montpellier SupAgro, INRA, France

Contact the author

Keywords

climate, functional analysis, temporal variability, cluster number

Tags

GiESCO 2019 | IVES Conference Series

Citation

Related articles…

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.

A blueprint for managing vine physiological balance at different spatial and temporal scales in Champagne

In Champagne, the vine adaptation to different climatic and technical changes during these last 20 years can be seen through physiological balance disruptions. These disruptions emphasize the general grapevine decline. Since the 2000s, among other nitrogen stress indicators, the must nitrogen has been decreasing. The combination of restricted mineral fertilizers and herbicide use, the growing variability of spring rainfall, the increasing thermal stress as well as the soil type heterogeneity are only a few underlying factors that trigger loss of physiological balance in the vineyards. It is important to weigh and quantify the impact of these factors on the vine. In order to do so, the Comité Champagne uses two key-tools: networking and modelization. The use of quantitative and harmonized ecophysiological indicators is necessary, especially in large spatial scales such as the Champagne appellation. A working group with different professional structures of Champagne has been launched by the Comité Champagne in order to create a common ecophysiology protocol and thus monitor the vine physiology, yearly, around 100 plots, with various cultural practices and types of soil. The use of crop modelling to follow the vine physiological balance within different pedoclimatic conditions enables to understand the present balance but also predict the possible disruptions to come in future climatic scenarios. The physiological references created each year through the working group, benefit the calibration of the STICS model used in Champagne. In return, the model delivers ecophysiology indicators, on a daily scale and can be used on very different types of soils. This study will present the bottom-up method used to give accurate information on the impacts of soil, climate and cultural practices on vine physiology.

Effects of graft quality on growth and grapevine-water relations

Climate change is challenging viticulture worldwide compromising its sustainability due to warmer temperatures and the increased frequency of extreme events. Grafting Vitis vinifera L.

VINIoT – Precision viticulture service

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

20-Year-Old data set: scion x rootstock x climate, relationships. Effects on phenology and sugar dynamics

Global warming is one of the biggest environmental, social, and economic threats. In the Douro Valley, change to the climate are expected in the coming years, namely an increase in average temperature and a decrease in annual precipitation. Since vine cultivation is extremely vulnerable and influenced by the climate, these changes are likely to have negative effects on the production and quality of wine.
Adaptation is a major challenge facing the viticulture sector where the choice of plant material plays an important role, particularly the rootstock as it is a driver for adaptation with a wide range of effects, the most important being phylloxera, nematode and salt, tolerance to drought and a complex set of interactions in the grafted plant.
In an experimental vineyard, established in the Douro Region in 1997, with four randomized blocs, with five varieties, Touriga Nacional, Tinta Barroca, Touriga Franca and Tinta Roriz, grafted in four rootstocks, Rupestris du Lot, R110, 196-17C, R99 and 1103P, data was collected consecutively over 20 years (2001-2020). Phenological observations were made two to three times a week, following established criteria, to determine the average dates of budbreak, flowering and veraison. During maturation, weekly berry samples were taken to study the dynamics of sugar accumulation, amongst other parameters. Climate data was collected from a weather station located near the vineyard parcel, with data classified through several climatic indices.
The results achieved show a very low coefficient of variations in the average date of the phenophases and an important contribution from the rootstock in the dynamic of the phenology, allowing a delay in the cycle of up to10-12 days for the different combinations. The Principal Component Analysis performed, evaluating trends in the physical-chemical parameters, highlighted the effect of the climate and rootstock on fruit quality by grape varieties.