GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 Correspondence between physiological plant variables and carbon isotope composition in different climate winegrape regions

Correspondence between physiological plant variables and carbon isotope composition in different climate winegrape regions

Abstract

Context and purpose of the study – The climate is the environmental factor that contributes with greater weight in the variability of the yield and the composition of the grape, therefore, it is key in the determination of the typicity of the product. Of the environmental factors, the evolution of water availability conditions, among other things, the biochemical evolution of the compounds of the grape and the type of wine to be elaborated. An integrating parameter of the hydric state of the plant is the carbon isotopic composition (δ13C). This indicator is a useful parameter to characterize the water status during the maturation period and estimate the transpiration efficiency or water use efficiency (EUA) in the vine. The aim of this study was to evaluate the ability of δ13C to differentiate wine growing regions of Uruguay by the relationship between the isotope indicator and the main productive variables.

Material and methods – The study was conducted in 2018 in commercial vineyards of the Tannat variety grafted on to SO4 rootstock, trained in a trellis system. The vines were planted in a four different climate regions for Uruguay determined by Multicriterial Classification system (MCC): 1-IH5, IF2, IS1-Salto (North, corresponds to a warm climate, cool nights and moderate drought), 2- IH4, IF2, IS1-Durazno (Center, corresponds toa temperate-warm climate, nights and moderate drought), 3- IH4, IF1, IS1-Colonia (Northwest, corresponds to a temperate-warm climate, warm nights, moderate drought), and 4- IH3, IF2,IS1-Canelones (South corresponds to a temperate climate, cool nights and moderate drought). Climatic data were obtained from meteorological stations in each region according to World Meteorological Otganization (WMO standards). For each climatic region, the state hydric of the plant (ψb) was determined in four moments in the cycle; at harvest: berry weight, free amino nitrogen in must, δ13C in berries, pH, acidity, sugars and total and extractable anthocyanins it was determined.

Results – In the studied zones, under rainfed conditions, the values of δ13C were correlated to the water deficit. The δ13C was strongly correlated with the hydric state of the plant and allowed to differentiate the two most extreme climatic regions (1 and 4). The most negative δ13C values were obtained in climatic zone 1 (warm), explained by the rainfall accumulated during the maturation period. The δ13C showed significant correlations with the weight of the berry for each of the zones, free amino nitrogen in the berry, total and extractable anthocyanins, and the total acidity. These results indicate that δ13C, is an interesting indicator to evaluate the quality of the grape and confirm climatic regions.

DOI:

Publication date: September 28, 2023

Issue: GiESCO 2019

Type: Poster

Authors

Gustavo PEREYRA1*, Leandro ARRILLAGA1, Julia SALVARREY1, Veronica BERRIEL2, Milka FERRER1

1 Producción Vegetal-Viticultura, FAGRO-UdelaR, 780 Garzón,12900 Montevideo, Uruguay
2 Suelos y Aguas, FAGRO-UdelaR, 780 Garzón, 12900 Montevideo, Uruguay

Contact the author

Keywords

δ13C, Tannat, water status, climatic regions

Tags

Citation

Related articles…

A better understanding of the climate effect on anthocyanin accumulation in grapes using a machine learning approach

The current climate changes are directly threatening the balance of the vineyard at harvest time. The maturation period of the grapes is shifted to the middle of the summer, at a time when radiation and air temperature are at their maximum. In this context, the implementation of corrective practices becomes problematic. Unfortunately, our knowledge of the climate effect on the quality of different grape varieties remains very incomplete to guide these choices. During the Innovine project, original experiments were carried out on Syrah to study the combined effects of normal or high air temperature and varying degrees of exposure of the berries to the sun. Berries subjected to these different conditions were sampled and analyzed throughout the maturation period. Several quality characteristics were determined, including anthocyanin content. The objective of the experiments was to investigate which climatic determinants were most important for anthocyanin accumulation in the berries. Temperature and irradiance data, observed over time with a very thin discretization step, are called functional data in statistics. We developed the procedure SpiceFP (Sparse and Structured Procedure to Identify Combined Effects of Functional Predictors) to explain the variations of a scalar response variable (a grape berry quality variable for example) by two or three functional predictors (as temperature and irradiance) in a context of joint influence of these predictors. Particular attention was paid to the interpretability of the results. Analysis of the data using SpiceFP identified a negative impact of morning combinations of low irradiance (lower than about 100 μmol m−2 s−1 or 45 μmol m−2 s−1 depending on the advanced-delayed state of the berries) and high temperature (higher than 25oC). A slight difference associated with overnight temperature occurred between these effects identified in the morning.

Grapevine sugar concentration model in the Douro Superior, Portugal

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

VINIoT: Precision viticulture service for SMEs based on IoT sensors network

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

‘Cabernet Sauvignon’ (Vitis vinifera L.) berry skin flavonol and anthocyanin composition is affected by trellis systems and applied water amounts

Trellis systems are selected in wine grape vineyards to mainly maximize vineyard yield and maintain berry quality. This study was conducted in 2020 and 2021 to evaluate six commonly utilized trellis systems including a vertical shoot positioning (VSP), two relaxed VSPs (VSP60 and VSP80), a single high wire (SH), a high quadrilateral (HQ), and a guyot (GY), combined with three levels of irrigation regimes based on different crop evapotranspiration (ETc) replacements, including a 25% ETc, 50% ETc, and 100% ETc. The results indicated SH yielded the most fruits and accumulated the most total soluble solids (TSS) at harvest in 2020, however, it showed the lowest TSS in the second season. In 2020, SH and HQ showed higher concentrations in most of the anthocyanin derivatives compared to the VSPs. Similar comparisons were noticed in 2021 as well. SH and HQ also accumulated more flavonols in both years compared to other trellis systems. Overall, this study provides information on the efficacy of trellis systems on grapevine yield and berry flavonoid accumulation in a currently warming climate.

A multidisciplinary approach to evaluate the effects of the training system on the performance of “Aglianico del Vulture” vineyards

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.