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…

The concept of terroir: what place for microbiota?

Microbes play key roles on crop nutrient availability via biogeochemical cycles, rhizosphere interactions with roots as well as on plant growth and health. Recent advances in technologies, such as High Throughput Sequencing Techniques, allowed to gain deeper insight on the structure of bacterial and fungal communities associated with soil, rhizosphere and plant phyllosphere. Over the past 10 years, numerous scientific studies have been carried out on the microbial component of the vineyard. Whether the soil or grape compartments have been taken into account, many studies agree on the evidence of regional delineations of microbial communities, that may contribute to regional wine characteristics and typicity. Some authors proposed the term “microbial terroir” including “yeast terroir” for grapes to describe the connection between microbial biogeography and regional wine characteristics. Many factors are involved in terroir including climate, soil, cultivar and human practices as well as their interactions. Studies considering “microbial terroir” greatly contributed to improve our knowledge on factors that shape the vineyard microbial structure and diversity. However, the potential impact of “microbial terroir” on wine composition has yet not received strong scientific evidence and many questions remain to be addressed, related to the functional characterization of the microbial community and its impact on plant physiology and grape composition, the origins and interannual stability of vineyard microbiota, as well as their impact on wine sensorial attributes. The presentation will give an overview on the role of microbiota as a terroir component and will highlight future perspectives and challenges on this key subject for the wine industry.

The use of rootstock as a lever in the face of climate change and dieback of vineyard

As viticulture faces challenges such as climate change or vineyard dieback, the choice of the variety and rootstock becomes more and more crucial. To study rootstock levers in the Bordeaux region, a parcel of Cabernet Sauvignon (CS) was planted with four rootstocks in 2014. Twenty repetitions of each of the following four rootstocks were set up: 101-14 MGt, Nemadex AB, 420A MGt and Gravesac. The number of bunches, yields and pruning weights of the vine shoots were measured individually on 240 vines from 2017 to 2021. Since 2020, nitrogen status assessed by assimilable nitrogen level, hydric status assessed by δ13C and berry maturity were measured on 80 samples taken from 20 repetitions of the four rootstocks. A lower yield was measured for CS grafted onto Nemadex AB due to the lower number of bunches and the lower weight of berries. The differences between the other three rootstocks are small, but CS grafted onto 420A MGt was the most productive. The CS grafted onto Nemadex AB had the lowest pruning weight while 101-14 MGt had the highest. In 2020, δ13C showed a more moderate water stress with 101-14 MGt and 420A MGt than with Nemadex AB. Surprisingly, the Gravesac was under more stress than the 101-14 MGt. The nitrogen status in the berries was better for Nemadex AB but this was perhaps due to the significantly lower weight of the berries.Rootstock 101-14 MGt attained the highest accumulation of sugars in the berries while 420A MGt allows to preserve higher acidity. The parcel is still young which may explain some of the results. These measures must therefore be continued over the next several years to fully assess the effects of these rootstocks on the development of the vines and the quality of the production under new climatic conditions.

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).

Modeling island and coastal vineyards potential in the context of climate change

Climate change impacts regional and local climates, which in turn affects the world’s wine regions. In the short term, these modifications rises issues about maintaining quality and style of wine, and in a longer term about the suitability of grape varieties and the sustainability of traditional wine regions. Thus, adaptation to climate change represents a major challenge for viticulture. In this context, island and coastal vineyards could become coveted areas due to their specific climatic conditions. In regions subject to warming, the proximity of the sea can moderate extremes temperatures, which could be an advantage for wine. However, coastal and island areas are particular prized spaces and subject to multiple pressures that make the establishment or extension of viticulture complex.
In this perspective, it seems relevant to assess the potentialities of coastal and island areas for viticulture. This contribution will present a spatial optimization model that tends to characterize most suitable agroclimatic patterns in historical or emerging vineyards according to different scenarios. Thanks to an in-depth bibliography a global inventory of coastal and insular vineyards on a worldwide scale has been realized. Relevant criteria have been identified to describe the specificities of these vineyards. They are used as input data in the optimization process, which will optimize some objectives and spatial aspects. According to a predefined scenario, the objectives are set in three main categories associated with climatic characteristics, vineyards characteristics and management strategies. At the end of this optimization process, a series of maps presents the different spatial configurations that maximize the scenario objectives.

Co-design and evaluation of spatially explicit strategies of adaptation to climate change in a Mediterranean watershed

Climate change challenges differently wine growing systems, depending on their biophysical, sociological and economic features. Therefore, there is a need to locally design and evaluate adaptation strategies combining several technical options, and considering the local opportunities and constraints (e.g. water access, wine typicity). The case study took place in a typical and heterogeneous Mediterranean vineyard of 1,500 ha in the South of France. We developed a participatory modeling approach to (1) conceptualize local climate change issues and design spatially explicit adaptation strategies with stakeholders, (2) numerically evaluate their effects on phenology, yield and irrigation needs under the high-emissions climate change scenario RCP 8.5, and (3) collectively discuss simulation results. We organized five sets of workshops, with in-between modeling phases. A process-based model was developed that allowed to evaluate the effects of six technical options (late varieties, irrigation, water saving by reducing canopy size, adjusting cover cropping, reducing density, and shading) with various distributions in the watershed, as well as vineyard relocation. Overall, we co-designed three adaptation strategies. Delay harvest strategy with late varieties showed little effects on decreasing air temperature during ripening. Water constraint limitation strategy would compensate for production losses if disruptive adaptations (e.g. reduced density) were adopted, and more land got access to irrigation. Relocation strategy would foster high premium wine production in the constrained mountainous areas where grapevine is less impacted by climate change. This research shows that a spatial distribution of technical changes gives room for adaptation to climate change, and that the collaboration with local stakeholders is a key to the identification of relevant adaptation. Further research should explore the potential of adaptation strategies based on soil quality improvement and on water stress tolerant varieties.