OENO IVAS 2019 banner
IVES 9 IVES Conference Series 9 Exploring multisensory interactions through the study of astringency diversity of mono-varietal Italian red wines

Exploring multisensory interactions through the study of astringency diversity of mono-varietal Italian red wines

Abstract

According to the OIV Focus 2017 estimating the vine varieties distribution in the world, Italy is the richest grape producing country in terms of varieties. This rich biodiversity translates into a wide sensory diversity of the wines that was never systematically investigated. The D-Wines (Diversity of Italian Wines) project, is aimed to start filling this gap by getting a wide chemical and sensorial multi-parametric dataset about 11 mono-varietal red wines (Aglianico, Cannonau, Corvina, Montepulciano, Nebbiolo, Nerello Mascalese, Primitivo, Raboso, Sagrantino, Sangiovese, Teroldego) representative of the Italian territory and by focusing on tannins and astringency.

In this frame, the astringency diversity of a set of 112 wines belonging to the 11 varieties, was investigated by sensory analysis adopting a multi-steps analytical strategy. A first experiment by sorting, allowed to reduce (AHC analysis) the sample-set to 77 wines, representative of the intra-varietal similarities and diversities in terms of astringency sub-qualities. A second experiment by descriptive analysis was performed on the selected wines and allowed to obtain their sensory profiles (astringency, taste, odor). Both intra- and inter-varietal significant differences of each sensory variable was tested by ANOVA (p<0.05).

Quantitative data concerning astringency were analyzed through Discriminant Analysis (DA).

Results showed that the 6 variables describing astringency (drying, harsh, unripe, dynamic, complex, surface smoothness; Gawel et al., 2000) allowed a good discrimination (F1+F2: 78 %) of the wines according to the grape variety. Factor scores of each sample allowed their reclassification into the variety for which the probability of belonging was the greatest. The 57 % of the wines resulted correctly reclassified, with Nebbiolo showing the highest value (83 %) and Nerello Mascalese the lowest (0 %).

The quantitative data concerning the well reclassified wines were used to develop “Astringency spectra”, models representing the astringency features of each mono-varietal wine.

These “Spectra” were compared to those of the corresponding deodorized wines in order to investigate the multisensory interactions between astringency, taste and odor variables. Several significant correlations were detected (e.g. R2>0.5: drying and dynamic, drying and dehydrated fruit, complex and spicy were positively correlated while harsh and acid were negatively correlated).

Acknowledgements:

MIUR project N. 20157RN44Y. Other components of D-Wines project: P. Arapitsas, A. Gambuti, S. Giacosa, M. Marangon, A. Ricci, L. Rolle, S. Río Segade, B. Simonato, G. Tornielli, A. Versari, S. Vincenzi

DOI:

Publication date: June 19, 2020

Issue: OENO IVAS 2019

Type: Article

Authors

Paola Piombino (1), E. Pittari (1), M. Ugliano (2), A. Curioni (3), F. Mattivi (4,5), V. Gerbi (6), G.P. Parpinello (7), L. Moio (1)

(1) Department of Agricultural Sciences, University of Naples Federico II, Division of Vine and Wine Sciences, University of Naples Federico II – V.le Italia s.n.c. 83100 – Avellino Italy
(2) Department of Biotechnology, University of Verona, It
(3) Department of Agronomy, University of Padova, It
(4) Department of Food Quality and Nutrition, Fondazione Edmund Mach, It
(5) Center Agriculture Food Environment, University of Trento, It
(6) Department of Agricultural, Forestry and Food Sciences, University of Torino, It
(7) Department of Agricultural and Food Sciences, University of Bologna, It

Contact the author

Keywords

mouthfeel and odor, diversity, interactions, chemometrics 

Tags

IVES Conference Series | OENO IVAS 2019

Citation

Related articles…

Modeling the suitability of Pinot Noir in Oregon’s Willamette Valley in a changing climate

Air temperature is the key driver of grapevine phenology and a significant environmental factor impacting yield and quality for a winegrape growing region. In this study the optimal downscaled CMIP5 ensemble for computing thegrowing season average temperature (GST) viticulture climate classification index was determined to spatially compute on a decadal basis predictions of the GST climate index and the grapevine sugar ripeness (GSR) model for Pinot Noir throughout the Willamette Valley (WV) American Viticultural Area (AVA). Forecasts for average temperature and a 220 g/L target sugar concentration level were computed using daily Localized Constructed Analogs (LOCA) downscaled CMIP5 historic and Representative Concentration Pathways (RCP) future climate projections of minimum and maximum daily temperature. We explore spatiotemporal trends of the GST climate classification index and Pinot Noir specific applications of the GSR phenology model for the WV AVA. Spatiotemporal computations of the GST climate index and Pinot Noir specific applications of the GSR model enable the opportunity to explore relationships between their computed values with one intent being to provide updated GST ranges that better align with current temperature-based modeling understanding of Pinot Noir grapevine phenology and the viticultural application of LOCA CMIP5 climate projections for the WV AVA. The Pinot Noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot Noir production is currently at or near its peak value in the upper 80s to lower 90s of this century.

Updating the Winkler index: An analysis of Cabernet sauvignon in Napa Valley’s varied and changing climate

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

Assessment of the impact of actions in the vineyard and its surrounding environment on biodiversity in Rioja Alavesa (Spain)

Traditional viticulture areas have experienced in the last decades an intensification of field practices, linked to an increased use of fertilisers and phytosanitary products, and to a more intensive mechanization and uniformization of the landscape. This change in management has sometimes led to higher rates of soil erosion andloss of soil structure, fertility decline, groundwater contamination, and to an increased pressure of pests and diseases. Additionally, intensification usually leads to a simplification of landscapes, of particular concern in prestigious wine grape regions where the economical revenue encourages the conversion of land use from natural habitats to high value wine grape production. To revert this trend, it is necessary that growers implement actions that promote biodiversity in their vineyards. The aim of this study is to assess the impact of the implementation of cover crops, vegetational corridors, dry stone walls and vineyard biodiversity hotspots estimated through the study of arthropods. The work has been carried out in four vineyards in Rioja Alavesa belonging to Ostatu winery, where these infrastructures were implemented in 2020. The presence and diversity of arthropods was studied by capturing them at different times in the season and at different distances from the infrastructure using pit-fall traps in the soil and yellow, white and blue chromatic traps at the canopy level. This is a preliminary study in which all adult insects were sorted to the taxonomic level of order and Coleoptera were classified to morphospecies. The results obtained show that there is a relationship between the basic characteristics of the vineyard and the arthropods captured, with a positive effect, although also dependent on the vineyard, of the presence of infrastructure.

Climate, Viticulture, and Wine … my how things have changed!

The planet is warmer than at any time in our recorded past and increasing greenhouse emissions and persistence in the climate system means that continued warming is highly likely. Climate change has already altered the basic framework of growing grapes for wine production worldwide and will likely continue to do so for years to come. The wine sector can continue to play an important role in leading the agricultural sector in addressing climate change. From developing on…

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.