Terroir 2020 banner
IVES 9 IVES Conference Series 9 International Terroir Conferences 9 Terroir 2020 9 History and innovation of terroir 9 Within-vineyard variability in grape composition at the estate scale can be assessed through machine-learning modeling of plant water status in space and time. A case study from the hills of Adelaida District AVA, Paso Robles, CA, USA

Within-vineyard variability in grape composition at the estate scale can be assessed through machine-learning modeling of plant water status in space and time. A case study from the hills of Adelaida District AVA, Paso Robles, CA, USA

Abstract

Aim: Through machine-learning modelling of plant water status from environmental characteristics, this work aims to develop a model able to predict grape phenolic composition in space and time to guide selective harvest decisions at the estate scale.

Methods and Results: Work was conducted during two consecutive seasons in a ~40ha (100ac) premium wine estate located in the Adelaida District AVA of Paso Robles, CA, USA. The vineyard topography was very diverse, with a large variation in slope grade (0-30%) and exposure (0-359). One hundred experimental units were identified by a maximum dissimilarity sampling algorithm based on environmental attributes derived from a digital elevation model and a soil map. Reflecting the estate varietal distribution, ~70% were Cabernet-Sauvignon units, 20% Cabernet-Franc, and 10% Petit-Verdot units grafted on 1103P or 420A (~50-50%). Grapevine water status was monitored by weekly measurements of stem water potentials, Ψstem, and analysis of carbon isotope discrimination of grape musts, δ13C, at harvest. The grape composition during ripening was assessed by measuring total soluble solids, titratable acidity, and pH of musts and by a comprehensive assessment of skin phenolic composition with HPLC-DAD. Additional field measurements included shoot-count and yield assessment. Vegetation indexes were derived from canopy reflectance obtained from ~3m resolution CubeSat satellites. Irrigation amounts were provided by the grower, and weather data were obtained from three on-site stations. 

Grapevine Ψstem was modelled from weather data (temperature, relative humidity, rainfall), irrigation amounts, vegetation indexes, topographic attributes, soil type using a gradient-boosting-machine algorithm. The model was able to predict plant water status with <0.1 MPa of error (estimated as root mean squared error in a cross-validation procedure). Significant differences in water status were observed between rootstocks and main environmental drivers were slope grade and aspect (i.e. exposure). External validation of the model was carried out by correlating predictions with δ13C. The model allowed obtaining high-resolution daily mapping of Ψstem at the estate scale. Time-series of grapevine Ψstem were significantly correlated with the content of total soluble solids of musts, grape anthocyanin amounts, and the ratio of tri-hydroxylated to di-hydroxylated compounds at harvest and mapped. Spatial-clustering of grape anthocyanin composition was obtained from Ψstem model-estimates and used to guide harvest selectively. 

Conclusion: 

Grapevine water status confirmed to be an important driver in the variability of grape composition, even though the vineyard was irrigated. Variability in water status was related to environmental attributes (slope, aspect, incoming radiation) and the machine-learning approach proved to be useful to predict and understand plant-environment interactions and effects on grape composition in a varied and large dataset.

Significance and Impact of the Study: Vineyards are often located on slopes and accurate modelling of grapevine water status in hillslope conditions is a challenging task. This research demonstrates for the first time that it is possible to obtain daily estimates of grapevine water status at the estate scale by re-elaborating routine measurements with machine-learning technologies. This information can be used to drive selective harvest decisions and clustering within-vineyard variability at the estate scale to easily implement selective harvest decisions.

DOI:

Publication date: March 19, 2021

Issue: Terroir 2020

Type: Video

Authors

Luca Brillante

California State University Fresno, Fresno, United States

Contact the author

Keywords

Grapevine water status, machine learning, phenolic composition

Tags

IVES Conference Series | Terroir 2020

Citation

Related articles…

Grapevine varietal diversity as mitigation tool for climate change: Agronomic and oenologic potential of 14 foreign varieties grown in Languedoc region (France)

Climate change effects in Languedoc include an expected rise in temperatures, increased evapotranspiration as well as more severe and frequent climatic hazards, such as frost, drought periods and heat waves. For winegrowers theses phenomena impact both yield and quality, resulting in more frequent unbalanced wines. Research on identified mitigation tools for vineyard management is necessary to improve resilience of grapevine agrosystems. Varietal assortment is one of them. This study focuses on agronomic and oenologic potential of 14 foreign varieties grown in Languedoc French region. Fourteen grapevine varieties were monitored during 2021 from June until harvest on eight different sites, some of which occurring on more than one site adding up to 21 different modalities: 7 white varieties Alvarinho B, Assyrtiko B (2), Malvasia Istriana B, Parellada B, Verdejo B, Verdelho B, Xarello B, and 7 black varieties Saperavi N (2), Touriga nacional N, Baga N, Aleatico N, Montepulciano N (2), Primitivo N (3), Calabrese N (3). Varietals were compared through the following parameters: phenology was assessed by using the information collected in the Database Network of French Vine Conservatories (INRAE-SupAgro-IFV, 2005-2015). The number of inflorescences for shoots from secondary buds and bourillons and suckers were observed to assess post-bud break frost tolerance potential. Grapevine water status was studied through stem water potential measurement, observation of foliage symptoms of drought, and 𝛿13C on must. Frequencies and intensities of downy mildew, powdery mildew, and black rot attacks were estimated before harvest on leaves and clusters and botrytis at harvest to assess disease susceptibilities. Berry composition was monitored from end of veraison until harvest. Yield and mean bunch weight were also calculated. Varieties were then ranked on a 1-4 scale for each parameter and compared through PCA. Forty two stations of the Mediterranean basin were compared by PCA with the Multicriteria Climatic Classification indicators in order to confront the collected information during 2021 campaign to the hypothesis that plants coming from dry and hot regions are genetically adapted to such climatic conditions.

Towards adaptation to climate change in Rioja: Quality evaluation of wines obtained from Grenache x Tempranillo selections

The wine sector is of great relevance and tradition in Mediterranean countries, however, it may be most susceptible to climate change. In recent years, wine production is facing changes worldwide, both at environmental as well as commercial levels, due to global warming and the shift in consumers’ preferences. Wine growers and wine makers are in search of solutions that allow to face these new challenges. One of the most promising initiatives in the long term is the introduction of new plant materials, specifically intraspecific hybridizations between premium varieties that may improve traditional germplasm in its adaptation to climate change. These inter-varietal crosses have the potential to generate quality wines, whilst maintaining the regional typicity, and constitute an attractive alternative for the consumer due to their sensory attributes. In this study, we have evaluated wines from 29 intraspecific Garnacha x Tempranillo hybrids in two different locations, with the aim to assess their oenological potential and sensory attributes. Thirteen of the selections were white and 16 were red. Microvinifications were conducted with two or three replications depending on grape availability. Conventional oenological parameters were determined for all wines. The sensory evaluation and hedonic scores were given by five experts. Red selections obtained higher quality scores than white ones. Among the white selections with higher quality scores, GT-41 Varea and GT-159 Varea outstand, due to their high total acidity and high malic acid content. Regarding red selections, GT-57 Varea and GT-57 UR were perceived as higher in quality, highlighted for their moderate alcoholic and high anthocyanin content. Our results indicate that intraspecific hybridization may be a powerful tool for adapting traditional cultivars to climate change in Rioja.

Spatiotemporal patterns of chemical attributes in Vitis vinifera L. cv. Cabernet Sauvignon vineyards in Central California

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.

Influence of weather and climatic conditions on the viticultural production in Croatia

The research includes an analysis of the impact of weather conditions on phenological development of the vine and grape quality, through monitoring of four experimental cultivars (Chardonnay, Graševina, Merlot and Plavac mali) over two production years. In each experimental vineyard, which were evenly distributed throughout the regions of Slavonia and The Croatian Danube, Croatian Uplands,

Understanding graft union formation by using metabolomic and transcriptomic approaches during the first days after grafting in grapevine

Since the arrival of Phyloxera (Daktulosphaira vitifolia) in Europe at the end of the 19th century, grafting has become essential to cultivate Vitis vinifera. Today, grafting provides not only resistance to this aphid, but it used to adapt the cultivars according to the type of soil, environment, or grape production requirements by using a panel of rootstocks. As part of vineyard decline, it is often mentioned the importance of producing quality grafted grapevine to improve vineyard longevity, but, to our knowledge, no study has been able to demonstrate that grafting has a role in this context. However, some scion/rootstock combinations are considered as incompatible due to poor graft union formation and subsequently high plant mortality soon after grafting. In a context of climate change where the creation of new cultivars and rootstocks is at the centre of research, the ability of new cultivars to be grafted is therefore essential. The early identification of graft incompatibility could allow the selection of non-viable plants before planting and would have a beneficial impact on research and development in the nursery sector. For this reason, our studies have focused on the identification of metabolic and transcriptomic markers of poor grafting success during the first days/week after grafting; we have identified some correlations between some specialized metabolites, especially stilbenes, and grafting success, as well as an accumulation of some amino acids in the incompatible combination. The study of the metabolome and the transcriptome allowed us to understand and characterise the processes involved during graft union formation.