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Agronomy
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Grape Yields and Wine Quality and Composition as Affected by...
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Grape Yields and Wine Quality and Composition as Affected by Terroir

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Horticultural and Floricultural Crops".

Deadline for manuscript submissions: closed (30 December 2022) | Viewed by 4365

Special Issue Editor

Dr. Helder Fraga

E-Mail Website
Guest Editor
Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
Interests: viticulture; grapevines; wine; olive trees; olive oil; climate modelling; crop modelling; adaptation measures
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues

Viticultural terroir defines the uniqueness of a given region to produce specific wine types. The concept of terroir is primarily based on the distinct environmental characteristics within a wine-growing region. Terroir elements, such as atmospheric conditions, soil profiles and terrain characteristics, are linked to the winemaking suitability and potential. Grape and wine quality attributes and composition, yields and phenology are some viticultural parameters that are affected by terroir elements. Furthermore, cultural practices, growers’ decisions and planning are also determining factors for this concept. The term terroir is also associated with other broader aspects, appealing to the distinctiveness and origin of the wines, such as branding, wine type and landscape features. Grapevine yields and berry quality attributes are usually linked to the abovementioned terroir characteristics. The current Special Issue in Agronomy focuses on the links between terroir elements, such as climate/weather, soil and terrain characteristics, and the typical wine and grape characteristics, such as yield and quality attributes, within a certain winemaking region. Theoretical (modelling/simulations) and practical (field work/data) approaches are welcome.

Dr. Helder Fraga
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • phenology
  • yield
  • tannins
  • brix
  • sugar
  • alcohol
  • anthocyanins
  • pH
  • tannins
  • climate relations
  • weather factors
  • soil

Published Papers (2 papers)

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Research

27 pages, 5052 KiB  
Article
Climate Projections for Pinot Noir Ripening Potential in the Fort Ross-Seaview, Los Carneros, Petaluma Gap, and Russian River Valley American Viticultural Areas
by Brian Skahill, Bryan Berenguer and Manfred Stoll
Agronomy 2023, 13(3), 696; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy13030696 - 27 Feb 2023
Cited by 1 | Viewed by 1954
Abstract
An unbiased MACA CMIP5 ensemble that optimized calculation of the growing season average temperature (GST) viticulture climate classification index throughout Northern California’s Fort Ross-Seaview (FRS), Los Carneros (LC), Petaluma Gap (PG), and Russian River Valley (RRV) American Viticultural Areas (AVAs) was applied to [...] Read more.
An unbiased MACA CMIP5 ensemble that optimized calculation of the growing season average temperature (GST) viticulture climate classification index throughout Northern California’s Fort Ross-Seaview (FRS), Los Carneros (LC), Petaluma Gap (PG), and Russian River Valley (RRV) American Viticultural Areas (AVAs) was applied to compute the GST index and Pinot noir specific applications of the grapevine sugar ripeness (GSR) model on a mean decadal basis from the 1950s to the 2090s using RCP4.5 and RCP8.5 projections of minimum and maximum daily temperature. From the 1950s to the 2090s, a 2.1/3.6, 2.4/4.2, 2.3/4.0, 2.3/4.0, and 2.3/4.0 °C increase in the GST index and a rate advance of 1.3/1.9, 1.1/1.8, 1.3/2.0, 1.2/1.9, and 1.2/1.9 days a decade was computed for FRS, LC, PG, RRV, and across all four AVAs while using the RCP4.5/RCP8.5 climate projections, respectively. The GST index and GSR model calculations were highly correlated across both climate projections and their fitted models were used to update the Pinot noir specific upper bound for the GST index throughout each AVA using a published optimal harvest window for the northern hemisphere. At a 220 g/L target sugar concentration, the updated upper bound was 17.6, 17.5, 17.6, 17.5, and 17.6 °C for FRS, LC, PG, RRV, and across all four AVAs. For a 240 g/L sugar concentration, it was 17.9, 17.8, 17.9, 17.8, and 17.9 °C. The results from this study together with comparable results recently reported for the Willamette Valley AVA of Oregon using a different downscaled CMIP5 model archive suggest spatial invariance, albeit sugar concentration dependent, for the updated Pinot noir specific upper bound for the GST climate index. Full article
(This article belongs to the Special Issue Grape Yields and Wine Quality and Composition as Affected by Terroir)
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17 pages, 3038 KiB  
Article
Grapevine Sugar Concentration Model (GSCM): A Decision Support Tool for the Douro Superior Winemaking Region
by Nicolò Clemente, João A. Santos, Natacha Fontes, António Graça, Igor Gonçalves and Helder Fraga
Agronomy 2022, 12(6), 1404; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12061404 - 11 Jun 2022
Cited by 7 | Viewed by 1872
Abstract
Climate-smart agriculture involves practices and crop modelling techniques aiming to provide practical answers to meet growers’ demands. For viticulturists, early prediction of harvest dates is critical for the success of cultural practices, which should be based on accurate planning of the annual growing [...] Read more.
Climate-smart agriculture involves practices and crop modelling techniques aiming to provide practical answers to meet growers’ demands. For viticulturists, early prediction of harvest dates is critical for the success of cultural practices, which should be based on accurate planning of the annual growing cycle. We developed a modelling tool to assess the sugar concentration levels in the Douro Superior sub-region of the Douro wine region, Portugal. Two main cultivars (cv. Touriga-Nacional and Touriga-Francesa) grown in five locations across this sub-region were studied. Grape berry sugar data, with concentrations between 170 and 230 g L−1, were analyzed for the growing season campaigns, from 2014–2020, as an indicator of grape ripeness conditioned by temperature factors. Field data were collected by ADVID (“Associação Desenvolvimento Da Viticultura Duriense”), a regional winemaker association, and by Sogrape, the leading wine company from Portugal. The “Phenology Modeling Platform” was used for calibrating the model with sigmoid functions. Subsequently, model optimizations were performed to achieve a harmonized model, suitable for all estates. Model performance was assessed through two metrics: root mean square error (RMSE) and the Nash–Sutcliffe coefficient of efficiency (EFF). Both a leave-one-out cross-validation and a validation with an independent dataset (for 1991–2013) were carried out. Overall, our findings demonstrate that the model calibration achieved an average EFF of 0.7 for all estates and sugar levels, with an average RMSE < 6 days. Model validation, at one estate for 15 years, achieved an R2 of 0.93 and an RMSE < 5. These models demonstrate that air temperature has a high predictive potential of sugar ripeness, and ultimately of the harvest dates. These models were then used to build a standalone easy-to-use computer application (GSCM—Grapevine Sugar Concentration Model), which will allow growers to better plan and manage their seasonal activities, thus being a potentially valuable decision support tool in viticulture and oenology. Full article
(This article belongs to the Special Issue Grape Yields and Wine Quality and Composition as Affected by Terroir)
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