GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 Assessing macro-elements contents in vine leaves and grape berries of Vitis vinifera using near-infrared spectroscopy coupled with chemometrics

Assessing macro-elements contents in vine leaves and grape berries of Vitis vinifera using near-infrared spectroscopy coupled with chemometrics

Abstract

Context and purpose of the study – The cultivated vine (Vitis vinifera) is the main species cultivated in the world to make wine. In 2017, the world wine market represents 29 billion euros in exports, and France contributes 8.2 billion (28%) to this trade, making it a traditional market of strategic importance. Viticulture is therefore a key sector of the French agricultural economy. It is in this context that the nutritional diagnosis of the vine is of real strategic interest to winegrowers. Indeed, the fertilization of the vine is a tool for the winegrower that allows him to influence and regulate the quality of the wine. Nowadays, nutrition analysis is made with CHNS analyzer for elemental particles, and mass-spectroscopy for macro and microelements. Such methods are destructive and time consuming, then results could be obsolete for the vine grower. Near-infrared spectroscopy coupled with chemometrics tools allows to developed models of prediction that can provide accurate information about nutrition status of the vine in the field. In this study, we concentrate on the relative amount of Carbon [C], Hydrogen [H], Nitrogen [N], Sulphur [S] in dry matter (DM) and the C:N ratio.

Material and methods – 252 samples of different organs (leaves blade, leaves petioles, pea sized berries and berries at véraison) of 4 varieties (Muscat, Chasselas, Négrette and Sauvignon blanc) were analyzed. Spectrum were taken on both fresh material and dried ones with a reflectance spectrometer. The spectra were pre-processed using multiple scatter correction (MSC) and 1st and 2nd order Savitsky-Golay derivative (D1 and D2), before developing the cross-validation models using partial least square (PLS) regression and test it on a prediction set.

Results – The coefficient of determination in prediction (r²), the roots mean square error of prediction (RMSEP) and the ratio of performance of prediction (RPD) were obtained for C (0.49, 14.6% of DM and 1.33 on fresh material with MSC, 0.45, 15.4% of DM and 1.26 on dry material with MSC), H (0.56, 1.71% of DM and 1.45 on fresh material with D1, 0.49, 1.88% of DM and 1.32 on dry material with D1), N (0.91, 1.12% of DM, 3.32 on fresh material with raw spectra, 0.95, 0.84% of DM and 4.39 on dry material with MSC), S (0.47, 0.319% of DM and 1.31 on fresh material with MSC, 0.46, 0.322% of DM and 1.30 on dry material with D2) and C:N ratio (0.85, 8.20 and 2.58 on fresh material with raw spectra, 0.87, 7.55 and 2.80 on dry material with D2). Results show that the near-infrared reflectance spectroscopy can be used to assessing the level of nitrogen nutrition in vine and the C:N ratio. All model performance could be improved by increasing the number of samples.

DOI:

Publication date: March 11, 2024

Issue: GiESCO 2019

Type: Poster

Authors

Sebastien CUQ1*, Valerie LEMETTER2, Olivier GEFFROY1, Didier KLEIBER1, Cecile LEVASSEUR-GARCIA3

1 Physiologie, Pathologie et Génétique Végétales (PPGV), Université de Toulouse, INP-PURPAN, Toulouse, France
2 Plateforme TOAsT, Université de Toulouse, INP-PURPAN, Toulouse, France
3 Laboratoire de Chimie Agro-industrielle (LCA), Université de Toulouse, INRA, INPT, INP-PURPAN, Toulouse, France

Contact the author

Keywords

Infrared, Spectroscopy, Elemental analysis, Vitis vinifera

Tags

GiESCO | GiESCO 2019 | IVES Conference Series

Citation

Related articles…

Mobile device to induce heat-stress on grapevine berries

Studying heat stress response of grapevine berries in the field often relies on weather conditions during the growing season. We constructed a mobile heating device, able to induce controlled heat stress on grapes in vineyards. The heater consisted of six 150 W infrared lamps mounted in a profile frame. Heating power of the lamps could be controlled individually by a control unit consisting of a single board computer and six temperature sensors to reach a pre-set temperature. The heat energy applied to individual berries within a cluster decreases by the squared distance to the heat source, enabling the establishment of temperature profiles within individual clusters. These profiles can be measured by infrared thermography once a steady state has been reached. Radiant flux density received by a berry depending on the distance was calculated based on a view factor and measured lamp surface temperature and resulted to 665 Wm-2 at 7cm. Infrared thermography of the fruit surface was in good agreement with measurements conducted with a thermocouple inserted at epidermis level. In combination with infrared thermography, the presented device offers possibilities for a wide range of applications like phenotyping for heat tolerance in the field to proceed in the understanding of the complex response of plants to heat stress. Sunburn necrosis symptoms were artificially induced with the aid of the device for cv. Bacchus and cv. Sylvaner in the 2020 and 2021 growing season. Threshold temperatures for sunburn induction (LT5030min) were derived from temperature data of single berries and visual sunburn assessment, applying logistic regression. A comparison of threshold temperatures for the occurrence of sunburn necrosis confirmed the higher susceptibility of cv. Bacchus. The lower susceptibility of cv. Sylvaner did not seem to be related to its phenolic composition, rendering a thermoprotective role of berry phenolic compounds unlikely.

Grapevine yield estimation in a context of climate change: the GraY model

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

Effect of regulated deficit irrigation regime on amino acids content of Monastrell (Vitis vinifera L.) grapes

Irrigation is an important practice to influence vine quality, especially in Mediterranean regions, characterized by hot summers and severe droughts during the growing season. This study focused on deficit irrigation regime influence on amino acids composition of Monastrell grapevines under semiarid conditions (Albacete, Southeastern of Spain). In 2019, two treatments were applied: non-irrigation (NI) and regulated deficit irrigation (RDI), watered at 30% of the estimated crop evapotranspiration from fruit set to onset of veraison. Grape amino acids content was analyzed by HPLC. Berries from non-irrigated vines showed higher concentration of several amino acids, such as tryptophan (73%), arginine (70%), lysine (36%), isoleucine (27%), and leucine (21%), compared to RDI grapes. Arginine is, together with ammonium ion, the principal nitrogen source for yeasts during the alcoholic fermentation; while isoleucine, tryptophan, and leucine are precursors of fermentative volatile compounds, key compounds for wine quality. Moreover, NI treatment increased in a 14% the total amino acids content in grapes compared to RDI treatment. The reported effects might be because yield was 70% higher in RDI vines than in the NI ones and, therefore, the sink demand was increased in the irrigated vines. In addition, NI vines suffered more severe water stress and it is known that the amino acids synthesis and accumulation can be influenced by the plant response to stress. According to the results, the irrigation regime showed effect on amino acids concentration in Monastrell grapes under semiarid conditions. Grapes from non-irrigated vines showed a higher content of several amino acids relevant to the fermentative process and to the wine aroma compounds formation. It is demonstrated that the final content of nitrogen-related components in grapes is influenced by the irrigation regime. The convenience of the irrigation strategy to suggest will depend on the desired wine style and the target yield levels.

Frost risk projections in a changing climate are highly sensitive in time and space to frost modelling approaches

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports.
The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ > 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90.
Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.

Influence of climatic conditions on grape composition of Tempranillo in La Mancha DO (Spain)

The aim of this work was to analyze the variability in grape composition of the Tempranillo cultivar related to climatic conditions, in La Mancha Designation of Origin. Grape composition (sugar content, total acidity, pH, malic acid, and total and extractable anthocyanins) recorded during ripening, were analysed for the period 2000-2019. The weather conditions at daily time scale, recorded during the same period, were also evaluated. The relationships between grape parameters with climatic variables related to temperature and to water deficits, referring different periods between phenological events along the growing cycle, were evaluated using regression analysis. High variability in grape composition was observed in the period analysed. Total acidity varied between 3.7 and 7.3 gL-1 while malic acid varied between 1.2 and 4 gL-1. The extractable anthocyanins ranged between 526 and 972 mgL-1, and total anthocyanins ranged between 922 and 1388 mgL-1, being the lowest values recorded in the hottest year (2017). Total acidity decreased 0.77 gL-1 for an increase of 100 GDD, while malic acid decrease in 0.42 gL-1 for the same GDD increase, being the period between veraison and harvest the one that seemed to have higher influence on acidity. In addition, it was confirmed that increasing water deficits decreased acidity. Total and extractable anthocyanins increased in about 210 and 105 mgL-1, respectively, with an increase of 100 GDD from veraison to harvest, and the increase in water deficits favour the increase of anthocyanins, both total and extractable anthocyanins. Total and extractable anthocyanins concentration increased in 35 and 22 mgL-1 per an increase of 10 mm in the water deficit. These results can be of interest to understand the potential changes that grapes composition may suffer under future warmer climates.