GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 GiESCO 2019 9 Hyperspectral imaging and cnn for on‐the‐go, non‐destructive assessment of grape composition in the vineyard

Hyperspectral imaging and cnn for on‐the‐go, non‐destructive assessment of grape composition in the vineyard

Abstract

Context and purpose of the study ‐ Knowledge of the spatial‐temporal variation of the grape composition within a vineyard may assist decision making regarding sampling and vineyard management, especially if selective harvest is aimed. To have a truthful picture of the spatial‐temporal dynamics of grape composition evolution during ripening in a vineyard, a huge amount of measurements at different timings and spatial positions are required. Unfortunately, the quick in‐field measurement of a vast number of samples is very hard for simple variables such as total soluble solids (TSS), and impossible in the case of analyzing secondary metabolites, like anthocyanin concentrations. The goal of this study was the in‐field assessment and mapping of the TSS, acidity parameters and anthocyanin concentrations in a Tempranillo (Vitis vinifera L.) vineyard, using non‐destructive, on‐the‐go hyperspectral imaging (HSI).

Material and methods ‐ HSI of grapevine canopies was carried out using a line‐scan hyperspectral camera working in the Vis‐NIR range (400‐1000 nm) installed in all‐terrain‐vehicle, moving at 5 km/h in a commercial Tempranillo (Vitis vinifera L.) vineyard, under natural illumination conditions. Measurements were carried out at several dates during the ripening period over two consecutive seasons in 2017 and 2018. TSS, titratable acidity (TA), pH and anthocyanin concentrations analyses were also performed using gold standard, wet chemistry methods for model building and validation purposes. Convolutional neural networks (CNN) were applied for the development of regression models. The prediction results from the regression models were used for mapping (using GIS software) the evolution and distribution of grape composition in time–several datesand space–the vineyard plot.

Results ‐ Prediction models were generated for the different grape composition parameters, yielding 2 determination coefficients (R ) above 0.85 for TSS and TA and ~0.70 for pH and anthocyanin concentrations respectively. The built maps illustrated the seasonal dynamics of TSS and anthocyanin accumulation in the studied vineyard. The obtained results evidenced the potential of hyperspectral imaging acquired on‐the‐go for the non‐destructive, robust and massive assessment of TSS and total anthocyanin contents in grape berries in the vineyard. HIS may become a useful tool for decision‐ making on harvest selection and berry fate for winemaking.

DOI:

Publication date: June 22, 2020

Issue: GiESCO 2019

Type: Article

Authors

Salvador GUTIÉRREZ (1), Juan FERNÁNDEZ‐NOVALES (1), Javier TARDÁGUILA (1), Maria Paz DIAGO (1)

(1) Instituto de Ciencias de la Vid y del Vino (Universidad de La Rioja, CSIC, Gobierno de La Rioja) Finca La Grajera, Ctra. Burgos Km 6. (26007) Logroño, La Rioja, Spain.

Contact the author

Keywords

spatial‐temporal variability, total soluble solids, berry anthocyanins, Vis‐NIR spectral range, acidity parameters, prediction models

Tags

GiESCO 2019 | IVES Conference Series

Citation

Related articles…

An analytical framework to site-specifically study climate influence on grapevine involving the functional and Bayesian exploration of farm data time series synchronized using an eGDD thermal index

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

Terroir analysis and its complexity

Terroir is not only a geographical site, but it is a more complex concept able to express the “collective knowledge of the interactions” between the environment and the vines mediated through human action and “providing distinctive characteristics” to the final product (OIV 2010). It is often treated and accepted as a “black box”, in which the relationships between wine and its origin have not been clearly explained. Nevertheless, it is well known that terroir expression is strongly dependent on the physical environment, and in particular on the interaction between soil-plant and atmosphere system, which influences the grapevine responses, grapes composition and wine quality. The Terroir studying and mapping are based on viticultural zoning procedures, obtained with different levels of know-how, at different spatial and temporal scales, empiricism and complexity in the description of involved bio-physical processes, and integrating or not the multidisciplinary nature of the terroir. The scientific understanding of the mechanisms ruling both the vineyard variability and the quality of grapes is one of the most important scientific focuses of terroir research. In fact, this know-how is crucial for supporting the analysis of climate change impacts on terroir resilience, identifying new promised lands for viticulture, and driving vineyard management toward a target oenological goal. In this contribution, an overview of the last findings in terroir studies and approaches will be shown with special attention to the terroir resilience analysis to climate change, facing the use and abuse of terroir concept and new technology able to support it and identifying the terroir zones.

Grape must quality and mesoclimatic variability in Fruška Gora wine-growing region, Serbia

The Fruška Gora mountain is a traditional wine-growing region in Serbia situated in the Pannonian Basin. Due to such a position, the vicinity of the Danube River and the presence of concave configuration, it is suitable for grape production. This paper provides analyses of spatial variations in meteorological parameters and grape juice quality within Fruška Gora wine region over three consecutive vintages (2018-2020). The examined period can be defined as warm with cool nights during September (AVG 18,9°C; GDD 1918°C; CI 12°CF) and with the presence of mesoclimatic variability. The East part of the study area was somewhat drier and hotter compared to other parts of the region. The analyses of grape must samples (190 in total) of five cultivars (Cabernet-Sauvignon, Merlot, Chardonnay, Sauvignon blanc and Grašac (Welschriesling)) commonly grown across the region (19 sites), were performed using Fourier Transform Infrared Technology (FTIR). Among all cultivars, Sauvignon blanc was harvested first in the East area (DOY=246±5, GDD at harvest=1552±74, 22.2±0.7 °Brix), while the latest harvest was recorded for Cabernet-Sauvignon in the West (DOY=283±5, GDD at harvest=1936±187, 23.4±1.0 °Brix ). Both the red and white cultivars had higher acidity and YAN in the grape must if the vines were grown in the North and East compared to South and West areas. According to PCA analysis, Grašac showed the lowest variation in grape must chemical composition. Thus, the results confirm that Grašac is the most stable cultivar in Fruška Gora. All monitored cultivars reached technological fruit ripeness by the end of the growing season. However, it was difficult to reach full ripeness of red cultivars, mostly beacuse of uncoupling of technolocical and phenolic ripeness. Thus, Cabernet-Sauvignon had higher variations in GDD sums at harvest compared to other cultivars, which probably increased variations in grape must quality.

Evaluation of climate change impacts at the Portuguese Dão terroir over the last decades: observed effects on bioclimatic indices and grapevine phenology

In the last decades the growers of the Portuguese Dão winegrowing region (center of Portugal) are experiencing changes in climate that are influencing either grape phenology berry health and ripening. Aiming to study the relationships between climate indices (CI), seasonal weather and grapevine phenology, in this work long-term climate and phenological data collected at the experimental vineyard of the Portuguese Dão research centre between 1958 and 2019 (61 years) for the red variety Touriga Nacional, was analyzed. The trends over time for the classical temperature-based indices (Growing Season Temperature – GST -, Growing Degree Days – GDD, Huglin Index – HI and Cool Night Index – CI) presented a significantly positive slope while the Dryness Index (DI) showed a negative trend over the last 61 years. Regarding grapevine phenology, an average advance of 4.5 days per decade in the harvest day was observed throughout the last 61 years. Consequently, the weather conditions during the ripening period have changed, showing an increasing trend over time in the average temperature (higher magnitude in the maximum than in the minimum temperature) and a decrease in the accumulated rainfall. A regression analysis showed that ~50% of harvest date variability over years was explained by the temperature-based indices variability. These observed effects of climate change on bioclimatic indices and corresponding anticipation of harvest date can still be considered advantageous for the Dão terroir as it allows to achieve an optimal berry ripening before the common equinox rains and, therefore, avoid the potential negative impacts of the rainfall on berry health and composition.

Different soil types and relief influence the quality of Merlot grapes in a relatively small area in the Vipava Valley (Slovenia) in relation to the vine water status

Besides location and microclimatic conditions, soil plays an important role in the quality of grapes and wine. Soil properties influence…