Macrowine 2021
IVES 9 IVES Conference Series 9 Kinetics modeling of a sangiovese wine chemical and physical parameters during one-year aging in different tank materials

Kinetics modeling of a sangiovese wine chemical and physical parameters during one-year aging in different tank materials

Abstract

AIM: The use of different tank materials during red wine aging has become increasingly popular, but little is known about their impact on wine chemical and physical parameters. The present study aims to model the evolution of Sangiovese red wine during one-year aging at industrial scale in different tank materials (stainless steel, epoxy-coated concrete, uncoated concrete, raw earthenware amphora, new oak barrel and used oak barrel), in order to describe how the tank material could both allow the mass transfer of different amount of oxygen, or tannins and affect the oxidation and reduction reactions in wine.

METHODS: A Sangiovese red wine from 2018 harvest was monitored during one-year aging in six different tank materials in industrial scale (5 hL) and in triplicate. The wine chemical and physical parameters monitored were: dissolved oxygen (DO), redox potential (EH), Cielab coordinates, acetaldehyde, monomer anthocyanins and polymeric pigments content. The tank materials (M), storage time (t) and temperature (T) were considered as factors. Stainless steel (SS) was chosen as reference material. The kinetic models of the collecting data were performed as described in literature when available, otherwise a polynomial curve was adopted to obtain a good phenomenological fitting.

RESULTS: The experimental data were modeled and the kinetic models were able to describe the differences between the wine samples aged in the different tank materials. The same equation was used to describe the kinetics of oxygen consumption (DO) and six equations were instead necessary to model redox potential (EH) trend for the wines aged in the different tank materials (1,2,3). The DO and EH were also related to the chemical phenomena which were monitored and modeled for polymeric pigments, monomeric anthocyanins, acetaldehyde, and CIELab coordinates measurements during wine aging (4,5). Through the modeling of the different chemical parameters it was possible to evidence differences between the wines aged in different tank materials. In particular, the tanks in stainless steel and in epoxy-coated concrete were the least suitable to let the variation of the redox state of the wines and consequently to activate the polymerization reaction of wine phenolic fraction, exactly the opposite of the oak barrels; earthenware raw amphorae and uncoated concrete, on the other hand, had an intermediate behavior, but tended to be more similar to oak barrels.

CONCLUSIONS

The kinetics modeling of chemical and physical wine parameters was able to describe differences among wines aged in different tank materials. In particular, the one-year evolution of the phenolic composition, dissolved oxygen and redox potential of wines showed significant differences between aging tanks involved, differentiating the wines according to the material.

DOI:

Publication date: September 13, 2021

Issue: Macrowine 2021

Type: Article

Authors

Francesco Maioli

Department of Agricultural, Food, Environmental, and Forestry Sciences and Technologies – University of Florence, via Donizetti, 6 – 50144 Firenze (Italy),Lorenzo GUERRINI, Department of Agricultural, Food, Environmental, and Forestry Sciences and Technologies – University of Florence, via Donizetti, 6 – 50144 Firenze (Italy)  Monica PICCHI, Department of Agricultural, Food, Environmental, and Forestry Sciences and Technologies – University of Florence, via Donizetti, 6 – 50144 Firenze (Italy)  Alessandro PARENTI, Department of Agricultural, Food, Environmental, and Forestry Sciences and Technologies – University of Florence, via Donizetti, 6 – 50144 Firenze (Italy)  Bruno ZANONI, Department of Agricultural, Food, Environmental, and Forestry Sciences and Technologies – University of Florence, via Donizetti, 6 – 50144 Firenze (Italy)  Valentina CANUTI, Department of Agricultural, Food, Environmental, and Forestry Sciences and Technologies – University of Florence, via Donizetti, 6 – 50144 Firenze (Italy)

Contact the author

Keywords

dissolved oxygen, enological tank materials, earthenware raw amphora, redox potential, uncoated concrete, wine aging kinetics

Citation

Related articles…

austrianvineyards.com: online viewer of all designations of Austrian wine

To digitally record and present all the origins of Austrian wines in the same perfect and clear way was the motivation for the Austrian Wine Marketing Board (Austrian Wine) to start with the project in 2018. In June 2021 the results were presented to the public in an online viewer showing all the designations of Austrian wine, available at https://austrianvineyards.com in a largely barrier-free manner. The online viewer provides tailored individual maps fitted to the respective zoom level. The smallest unit of wine-origins in Austria is called Ried and is displayed in a plot-specific manner highlighting areas under vine. Information on the Ried include administrative district, winegrowing municipality, cadastral municipality, large collective vineyard site, specific winegrowing region, generic winegrowing region, winegrowing area and, in many cases, an illustrative picture. Complementary data on the size, elevation (minimum-maximum), orientation (in 8 sectors plus flat) and gradient (minimum, maximum, average) are based on the area under vine according to the EU’s Integrated Administration and Control System. Additional information covers climate data. The diagrams are taken from the monthly breakdown of data in the annals of the Central Institute for Meteorology and Geodynamics, Austria provide a display of values for air temperature, precipitation, and sunshine hours for the reference year and the long-term average. Seasonal aggregated data on temperature, precipitation, and sunshine hours complete the display. Short descriptions with emphasis on geology and soil, field name in historical maps, etymology of the denomination, and main planted variety complements the available information for the main designations in the online viewer. These descriptions are compiled by winegrowers, geologists, historians, and journalists. All the information and data can be extracted to a pdf-file. Printed vineyard maps are also available. Missing content regarding wine origins in Styria will be completed in winter 2021/22.

Impact of geographical location on the phenolic profile of minority varieties grown in Spain. II: red grapevines

Because terroir and cultivar are drivers of wine quality, is essential to investigate theirs effects on polyphenolic profile before promoting the implantation of a red minority variety in a specific area. This work, included in MINORVIN project, focuses in the polyphenolic profile of 7 red grapevines minority varieties of Vitis vinifera L. (Morate, Sanguina, Santafe, Terriza Tinta Jeromo Tortozona Tinta) and Tempranillo) from six typical viticulture Spanish areas: Aragón (A1), Cataluña (A2), Castilla la Mancha (A3), Castilla –León (A4), Madrid (A5) and Navarra (A6) of 2020 season. Polyphenolic substances were extracted from grapes. 35 compounds were identified and quantified (mg subtance/kg fresh berry) by HPLC and grouped in anthocyanins (ANT) flavanols (FLAVA), flavonols (FLAVO), hydroxycinnamic (AH), benzoic (BA) acids and stilbenes (ST). Antioxidant activity (AA, mmol TE /g fresh berry) was determined by DPPH method. The results were submitted to a two-way ANOVA to investigate the influence of variety, area and their interaction for each polyphenolic family and cluster analysis was used to construct hierarchical dendrograms, searching the natural groupings among the samples. Sanguina (A3) had the most of total polyphenols while Tempranillo (A5) those of ANT. Sanguina (A2) and (A3) reached the highest values of FLAVO, FLAVA and AA. These two last samples had also the maximum of AA. The effect cultivar and area were significant for all polyphenolic families analyzed. A high variability due to variety (>50%) was observed in FLAVA and the maximum value of variability due to growing area was detected in AA (86.41%), ANT and FLAVO (51%); the interaction variety*zone was significant only for ANT, FLAVO, EST and AA. Finally, dendrograms presented five cluster: i) Sanguina (A2); ii) Sanguina (A3); iii) Tempranillo (A5); iv) Tempranillo (A3); Terriza (A3,A5), Morate (A5,A6); v) Santafé (A1,A6); Tortozona tinta (A1,A3,A6); Tinta Jeromo (A3,A4).

Impact of yeast derivatives to increase the phenolic maturity and aroma intensity of wine

Using viticultural and enological techniques to increase aromatics in white wine is a prized yet challenging technique for commercial wine producers. Equally difficult are challenges encountered in hastening phenolic maturity and thereby increasing color intensity in red wines. The ability to alter organoleptic and visual properties of wines plays a decisive role in vintages in which grapes are not able to reach full maturity, which is seen increasingly more often as a result of climate change. A new, yeast-based product on the viticultural market may give the opportunity to increase sensory properties of finished wines. Manufacturer packaging claims these yeast derivatives intensify wine aromas of white grape varieties, as well as improve phenolic ripeness of red varieties, but the effects of this application have been little researched until now. The current study applied the yeast derivative, according to the manufacture’s instructions, to the leaves of both neutral and aromatic white wine varieties, as well as on structured red wine varieties. Chemical parameters and volatile aromatics were analyzed in grape musts and finished wines, and all wines were subjected to sensory analysis by a tasting panel. Collective results of all analyses showed that the application of the yeast derivative in the vineyard showed no effect across all varieties examined, and did not intensify white wine aromatics, nor improve phenolic ripeness and color intensity in red wine.

A predictive model of spatial Eca variability in the vineyard to support the monitoring of plant status

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...

Comparison of imputation methods in long and varied phenological series. Application to the Conegliano dataset, including observations from 1964 over 400 grape varieties

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.