GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 Cabernet-Sauvignon ripening in Chile: follow-up study from 2012 to 2018

Cabernet-Sauvignon ripening in Chile: follow-up study from 2012 to 2018

Abstract

Context and purpose of the study – Temperature is a relevant parameter during vineyard development, affecting vine phenology and grape maturity. Moreover, the climate of the different Chilean valleys influences the varieties cultivated, the ripening period and the final quality of the wines. The use of growing degree days (GDD) is known worldwide for the study of climate in viticulture regions. However, little is known about the evolution of maturity and the sugar loading stop, based on this parameter. GDD, as being independent of the date variable, allows incorporating the effect of climate in the analysis. The present study was aimed to understand the variation between seasons and the effect of temperature in grape maturity and in bioclimatic index. We found correlations that allow predict the behavior of next years, based on growing degree days.

Material and methods – Temperatures were collected from national agro climatic network (AGROMET). Four meteorological stations were consulted depending on the location of the company vineyards. Growing degree days (GDD) were calculated with a base temperature of 10°C from September 1 through March 31. Huglin index, a bioclimatic index of the ripening period, was calculated using daily mean temperature, daily maximum temperature and a day length coefficient of 1, because the vineyard is placed in latitude lower 40°00´. Grape maturity was monitored once a week, recording the sugar concentration and the volume of grapes with Dyostem machine. These data was used to calculate the sugar loading dynamics and the date of sugar loading stop. In average, 145 blocks of Cabernet Sauvignon were measured from four different valleys (Maule valley (M), Curicó valley (C), Maipo Valley (Ma) and Rapel valley (R)).

Results – For the three valleys, the sugar loading stop was beginning at lower GDD for 2015 and 2017, influenced by the higher temperatures in January. But the average potential alcohol was lower in these years, reaching 12.1; 12.3; 13.1 and 11.4 %v/v at 2015 and 12.4; 11.3; 13.5 and 11.9 %v/v at 2017 for M, R, Ma y C respectively. The rate of sugar loading was higher in M and C valley than R and Ma valley for 2015 and 2017, indicating that the high temperatures affect greater R and Ma valley than the other valleys studied. Moreover, in 2017, the dynamics of maturity (mg of sugar per berry) were lower compared with 2015, due to the higher temperatures registered in Cabernet sauvignon blocks in January to April. The maximum temperatures in 2017 were 39.4°C including 13 days with temperatures over 35°C in M valley, 36°C including 7 days with temperatures over 35°C in R, 37°C including 5 days with temperatures over 35°C in Ma valley and 35.7°C including 3 days with temperatures over 35°C in C valley. These temperatures generated a blockage of vines. On the other hand, the year 2014 was the best season, with average potential alcohol at the sugar loading stop of 14.5; 13.6; 14 and 13%v/v for M, R, Ma and C valley. In 2014, the maximum quantity of sugar per berry was higher (250-350 mg of sugar per berry), perhaps because the vines have enough time to load sugars, with lower temperatures from January to April compared with the other years. A year to year comparison of the 4 valleys reveals that the maximum quantity of sugar per berry was decreasing the last three years, from 200-300 mg of sugar per berry in 2012, 2013 and 2015 to 170-260 in 2016, 2017 and 2018 approximately. Analyzing the bioclimatic index, M valley has a warm climate from 2014 onwards; C valley has a warm temperate climate from 2014 onwards and R and Ma valley has a warm climate the last two years. The data of bioclimatic index showed a tendency towards a warm climate. The GDD curves have a polynomic tendency respect to the date. These results could be used to predict GDD for 2019 and a probable date of harvest.

DOI:

Publication date: September 28, 2023

Issue: GiESCO 2019

Type: Poster

Authors

M.Isabel MOENNE1*, Ricardo RODRIGUEZ1, Juan CURY1, Miguel RENCORET1

VSPT Wine Group, Avenida Vitacura 2670 Piso 16, Santiago, Chile

Contact the author

Keywords

grapevine, degree day, Cabernet, Sauvignon, climate, ripening, maturity

Tags

GiESCO | GiESCO 2019 | IVES Conference Series

Citation

Related articles…

Variations of soil attributes in vineyards influence their reflectance spectra

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.

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.

Characterization of variety-specific changes in bulk stomatal conductance in response to changes in atmospheric demand and drought stress

In wine growing regions around the world, climate change has the potential to affect vine transpiration and overall vineyard water use due to related changes in atmospheric demand and soil water deficits. Grapevines control their transpiration in response to a changing environment by regulating conductance of water through the soil-plant-atmosphere continuum. Most vineyard water use models currently estimate vine transpiration by applying generic crop coefficients to estimates of reference evapotranspiration, but this does not account for changes in vine conductance associated with water stress, nor differences thought to exist between varieties. The response of bulk stomatal conductance to daily weather variability and seasonal drought stress was studied on Cabernet-Sauvignon, Merlot, Tempranillo, Ugni blanc, and Semillon vines in a non-irrigated vineyard in Bordeaux France. Whole vine sap flow, temperature and humidity in the vine canopy, and net radiation absorbed by the vine canopy were measured on 15-minute intervals from early July through mid-September 2020, together with periodic measurement of leaf area, canopy porosity, and predawn leaf water potential. From this data, bulk stomatal conductance was calculated on 15-minute intervals, and multiple regression analysis was performed to identify key variables and their relative effect on conductance. Attention was focused on addressing multicollinearity and time-dependency in the explanatory variables and developing regression models that were readily interpretable. Variability of vapor pressure deficit over the day, and predawn water potential over the season explained much of the variability in conductance, with relative differences in response coefficients observed across the five varieties. By characterizing this conductance response, the dynamics of vine transpiration can be better parameterized in vineyard water use modeling of current and future climate scenarios.

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.

Analysis of some environmental factors and cultural practices that affect the production and quality of the Manto Negro, Callet and Prensal Blanc varieties

45 non irrigated vineyards distributed in the DO (Denomination) Pla i Llevant de Mallorca and the DO Binissalem Mallorca were used to investigate the characteristics of production and quality and their relationships certain environmental factors and cultural practices. The grape varieties investigated are autochthonous to the island of Mallorca, Manto Negro and Callet as red and Prensal Blanc as white. All plants were measured for four consecutive years in the main production and quality parameters. Among the environmental factors, the type of soil has been studied, more specifically its water retention capacity, the planting density, the age of the vineyard and the level of viral infection. The presence or absence of virus seems to have no effect on any component studied in the varieties studied. For the white variety Prensal Blanc age is negatively correlated with production and the number of bunches, nevertheless it does not cause any effect on the required quality parameters. However, for the red varieties Callet and Manto Negro, the age of the plantation is the variable that best correlates with the quality parameters, therefore the old vines should be the object of preservation by the viticulturists and winemakers in order to guarantee its contribution to the quality of the wines made with these varieties.