Grape and Wine Metabolites: Biotechnological Approaches to Improve Wine Quality

Although wine has been produced for several thousands of years, the ancient beverage has remained popular and even more affordable in modern times. Among all wine making regions, Bordeaux, France is probably one of the most prestigious wine areas in history. Since hundreds of wines are produced from Bordeaux each year, humans are not likely to be able to examine all wines across multiple vintages to define the characteristics of outstanding 21st century Bordeaux wines. Wineinformatics is a newly proposed data science research with an application domain in wine to process a large amount of wine data through the computer. The goal of this paper is to build a high-quality computational model on wine reviews processed by the full power of the Computational Wine Wheel to understand 21st century Bordeaux wines. On top of 985 binary-attributes generated from the Computational Wine Wheel in our previous research, we try to add additional attributes by utilizing a CATEGORY and SUBCATEGORY for an additional 14 and 34 continuous-attributes to be included in the All Bordeaux (14,349 wine) and the 1855 Bordeaux datasets (1359 wines). We believe successfully merging the original binary-attributes and the new continuous-attributes can provide more insights for Naïve Bayes and Supported Vector Machine (SVM) to build the model for a wine grade category prediction. The experimental results suggest that, for the All Bordeaux dataset, with the additional 14 attributes retrieved from CATEGORY, the Naïve Bayes classification algorithm was able to outperform the existing research results by increasing accuracy by 2.15%, precision by 8.72%, and the F-score by 1.48%. For the 1855 Bordeaux dataset, with the additional attributes retrieved from the CATEGORY and SUBCATEGORY, the SVM classification algorithm was able to outperform the existing research results by increasing accuracy by 5%, precision by 2.85%, recall by 5.56%, and the F-score by 4.07%. The improvements demonstrated in the research show that attributes retrieved from the CATEGORY and SUBCATEGORY has the power to provide more information to classifiers for superior model generation. The model build in this research can better distinguish outstanding and class 21st century Bordeaux wines. This paper provides new directions in Wineinformatics for technical research in data science, such as regression, multi-target, classification and domain specific research, including wine region terroir analysis, wine quality prediction, and weather impact examination.

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Influence of L. thermotolerans and S. cerevisiae Commercial Yeast Sequential Inoculation on Aroma Composition of Red Wines (Cv Trnjak, Babic, Blatina and Frankovka)

Fermentation ◽

10.3390/fermentation7010004 ◽

2020 ◽

Vol 7 (1) ◽

pp. 4

Author(s):

Ana-Marija Jagatić Korenika ◽

Ivana Tomaz ◽

Darko Preiner ◽

Marina Lavrić ◽

Branimir Šimić ◽

...

Keyword(s):

Yeast Strain ◽

Isoamyl Alcohol ◽

Starter Cultures ◽

Geranyl Acetate ◽

Red Wines ◽

Wine Quality ◽

Volatile Phenol ◽

Sequential Inoculation ◽

Commercial Yeast ◽

The Impact

Even though Saccharomyces cerevisiae starter cultures are still largely used nowadays, the non-Saccharomyces contribution is re-evaluated, showing positive enological characteristics. Among them, Lachancea thermotolerans is one of the key yeast species that are desired for their contribution to wine sensory characteristics. The main goal of this work was to explore the impact of L. thermotolerans commercial yeast strain used in sequential inoculation with S. cerevisiae commercial yeast on the main enological parameters and volatile aroma profile of Trnjak, Babić, Blatina, and Frankovka red wines and compare it with wines produced by the use of S. cerevisiae commercial yeast strain. In all sequential fermented wines, lactic acid concentrations were significantly higher, ranging from 0.20 mg/L in Trnjak up to 0.92 mg/L in Frankovka wines, while reducing alcohol levels from 0.1% v/v in Trnjak up to 0.9% v/v in Frankovka wines. Among volatile compounds, a significant increase of ethyl lactate and isobutyl acetate, geraniol, and geranyl acetate was detected in all wines made by use of L. thermotolerans. In Babić wines, the strongest influence of sequential fermentation was connected with higher total terpenes and total ester concentrations, while Trnjak sequentially fermented wines stood up with higher total aldehyde, volatile phenol, and total lactone concentrations. Control wines, regardless of variety, stood up with higher concentrations of total higher alcohols, especially isoamyl alcohol. The present work contributed to a better understanding of the fermentation possibilities of selected non-Saccharomyces strains in the overall red wine quality modeling.

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Non-Saccharomyces as Biotools to Control the Production of Off-Flavors in Wines

Molecules ◽

10.3390/molecules26154571 ◽

2021 ◽

Vol 26 (15) ◽

pp. 4571

Author(s):

Antonio Morata ◽

Iris Loira ◽

Carmen González ◽

Carlos Escott

Keyword(s):

Global Warming ◽

Lactic Acid ◽

Lactic Acid Bacteria ◽

Wine Quality ◽

Microbial Spoilage ◽

Spoilage Yeasts ◽

Off Flavors ◽

Chemical Preservatives ◽

Saccharomyces Yeasts ◽

Lachancea Thermotolerans

Off-flavors produced by undesirable microbial spoilage are a major concern in wineries, as they affect wine quality. This situation is worse in warm areas affected by global warming because of the resulting higher pHs in wines. Natural biotechnologies can aid in effectively controlling these processes, while reducing the use of chemical preservatives such as SO2. Bioacidification reduces the development of spoilage yeasts and bacteria, but also increases the amount of molecular SO2, which allows for lower total levels. The use of non-Saccharomyces yeasts, such as Lachancea thermotolerans, results in effective acidification through the production of lactic acid from sugars. Furthermore, high lactic acid contents (>4 g/L) inhibit lactic acid bacteria and have some effect on Brettanomyces. Additionally, the use of yeasts with hydroxycinnamate decarboxylase (HCDC) activity can be useful to promote the fermentative formation of stable vinylphenolic pyranoanthocyanins, reducing the amount of ethylphenol precursors. This biotechnology increases the amount of stable pigments and simultaneously prevents the formation of high contents of ethylphenols, even when the wine is contaminated by Brettanomyces.

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Somatic variants for seed and fruit set in grapevine

BMC Plant Biology ◽

10.1186/s12870-021-02865-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Laura Costantini ◽

Paula Moreno-Sanz ◽

Chinedu Charles Nwafor ◽

Silvia Lorenzi ◽

Annarita Marrano ◽

...

Keyword(s):

Single Nucleotide Polymorphisms ◽

Fruit Set ◽

Climatic Factors ◽

Embryo Sac ◽

Wine Industry ◽

Nucleotide Polymorphisms ◽

Wine Quality ◽

Single Nucleotide ◽

Germplasm Collections

Abstract Background Grapevine reproductive development has direct implications on yield. It also impacts on berry and wine quality by affecting traits like seedlessness, berry and bunch size, cluster compactness and berry skin to pulp ratio. Seasonal fluctuations in yield, fruit composition and wine attributes, which are largely driven by climatic factors, are major challenges for worldwide table grape and wine industry. Accordingly, a better understanding of reproductive processes such as gamete development, fertilization, seed and fruit set is of paramount relevance for managing yield and quality. With the aim of providing new insights into this field, we searched for clones with contrasting seed content in two germplasm collections. Results We identified eight variant pairs that seemingly differ only in seed-related characteristics while showing identical genotype when tested with the GrapeReSeq_Illumina_20K_SNP_chip and several microsatellites. We performed multi-year observations on seed and fruit set deriving from different pollination treatments, with special emphasis on the pair composed by Sangiovese and its seedless variant locally named Corinto Nero. The pollen of Corinto Nero failed to germinate in vitro and gave poor berry set when used to pollinate other varieties. Most berries from both open- and cross-pollinated Corinto Nero inflorescences did not contain seeds. The genetic analysis of seedlings derived from occasional Corinto Nero normal seeds revealed that the few Corinto Nero functional gametes are mostly unreduced. Moreover, three genotypes, including Sangiovese and Corinto Nero, were unexpectedly found to develop fruits without pollen contribution and occasionally showed normal-like seeds. Five missense single nucleotide polymorphisms were identified between Corinto Nero and Sangiovese from transcriptomic data. Conclusions Our observations allowed us to attribute a seedlessness type to some variants for which it was not documented in the literature. Interestingly, the VvAGL11 mutation responsible for Sultanina stenospermocarpy was also discovered in a seedless mutant of Gouais Blanc. We suggest that Corinto Nero parthenocarpy is driven by pollen and/or embryo sac defects, and both events likely arise from meiotic anomalies. The single nucleotide polymorphisms identified between Sangiovese and Corinto Nero are suitable for testing as traceability markers for propagated material and as functional candidates for the seedless phenotype.

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Inoculation with Mycorrhizal Fungi and Irrigation Management Shape the Bacterial and Fungal Communities and Networks in Vineyard Soils

Microorganisms ◽

10.3390/microorganisms9061273 ◽

2021 ◽

Vol 9 (6) ◽

pp. 1273

Author(s):

Nazareth Torres ◽

Runze Yu ◽

S. Kaan Kurtural

Keyword(s):

Mycorrhizal Fungi ◽

Time Course ◽

Management Practices ◽

Irrigation Management ◽

Fungal Communities ◽

Soil Microbiome ◽

Wine Quality ◽

Network Analyses ◽

Vineyard Soil ◽

Vineyard Soils

Vineyard-living microbiota affect grapevine health and adaptation to changing environments and determine the biological quality of soils that strongly influence wine quality. However, their abundance and interactions may be affected by vineyard management. The present study was conducted to assess whether the vineyard soil microbiome was altered by the use of biostimulants (arbuscular mycorrhizal fungi (AMF) inoculation vs. non-inoculated) and/or irrigation management (fully irrigated vs. half irrigated). Bacterial and fungal communities in vineyard soils were shaped by both time course and soil management (i.e., the use of biostimulants and irrigation). Regarding alpha diversity, fungal communities were more responsive to treatments, whereas changes in beta diversity were mainly recorded in the bacterial communities. Edaphic factors rarely influence bacterial and fungal communities. Microbial network analyses suggested that the bacterial associations were weaker than the fungal ones under half irrigation and that the inoculation with AMF led to the increase in positive associations between vineyard-soil-living microbes. Altogether, the results highlight the need for more studies on the effect of management practices, especially the addition of AMF on cropping systems, to fully understand the factors that drive their variability, strengthen beneficial microbial networks, and achieve better soil quality, which will improve crop performance.

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High Potential of Pichia kluyveri and Other Pichia Species in Wine Technology

International Journal of Molecular Sciences ◽

10.3390/ijms22031196 ◽

2021 ◽

Vol 22 (3) ◽

pp. 1196

Author(s):

Javier Vicente ◽

Fernando Calderón ◽

Antonio Santos ◽

Domingo Marquina ◽

Santiago Benito

Keyword(s):

Ethanol Yield ◽

Color Stability ◽

Quality Parameters ◽

Wine Industry ◽

Wine Aroma ◽

Wine Quality ◽

Promising Tool ◽

Pichia Kluyveri ◽

The Impact ◽

Fermentative Yeast

The surfaces of grapes are covered by different yeast species that are important in the first stages of the fermentation process. In recent years, non-Saccharomyces yeasts such as Torulaspora delbrueckii, Lachancea thermotolerans, Metschnikowia pulcherrima, and Pichia kluyveri have become popular with regard to winemaking and improved wine quality. For that reason, several manufacturers started to offer commercially available strains of these non-Saccharomyces species. P. kluyveri stands out, mainly due to its contribution to wine aroma, glycerol, ethanol yield, and killer factor. The metabolism of the yeast allows it to increase volatile molecules such as esters and varietal thiols (aroma-active compounds), which increase the quality of specific varietal wines or neutral ones. It is considered a low- or non-fermentative yeast, so subsequent inoculation of a more fermentative yeast such as Saccharomyces cerevisiae is indispensable to achieve a proper fermented alcohol. The impact of P. kluyveri is not limited to the grape wine industry; it has also been successfully employed in beer, cider, durian, and tequila fermentation, among others, acting as a promising tool in those fermentation processes. Although no Pichia species other than P. kluyveri is available in the regular market, several recent scientific studies show interesting improvements in some wine quality parameters such as aroma, polysaccharides, acid management, and color stability. This could motivate yeast manufacturers to develop products based on those species in the near future.

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Evaluation of the effect of micronutrient fertilizers based on chelates on grape and wine quality characteristics

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/699/1/012024 ◽

2021 ◽

Vol 699 (1) ◽

pp. 012024

Author(s):

S Cherviak ◽

N Anikina ◽

M Ermikhina ◽

N Aleinikova ◽

P Didenko

Keyword(s):

Quality Characteristics ◽

Wine Quality

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Clustering in Wineinformatics with Attribute Selection to Increase Uniqueness of Clusters

Fermentation ◽

10.3390/fermentation7010027 ◽

2021 ◽

Vol 7 (1) ◽

pp. 27

Author(s):

Jared McCune ◽

Alex Riley ◽

Bernard Chen

Keyword(s):

Unsupervised Learning ◽

Data Science ◽

Science Research ◽

Research Area ◽

Attribute Selection ◽

Short List ◽

Wine Quality ◽

Filtration Process ◽

Target Region ◽

Related Data

Wineinformatics is a new data science research area that focuses on large amounts of wine-related data. Most of the current Wineinformatics researches are focused on supervised learning to predict the wine quality, price, region and weather. In this research, unsupervised learning using K-means clustering with optimal K search and filtration process is studied on a Bordeaux-region specific dataset to form clusters and find representative wines in each cluster. 14,349 wines representing the 21st century Bordeaux dataset are clustered into 43 and 13 clusters with detailed analysis on the number of wines, dominant wine characteristics, average wine grades, and representative wines in each cluster. Similar research results are also generated and presented on 435 elite wines (wines that scored 95 points and above on a 100 points scale). The information generated from this research can be beneficial to wine vendors to make a selection given the limited number of wines they can realistically offer, to connoisseurs to study wines in a target region/vintage/price with a representative short list, and to wine consumers to get recommendations. Many possible researches can adopt the same process to analyze and find representative wines in different wine making regions/countries, vintages, or pivot points. This paper opens up a new door for Wineinformatics in unsupervised learning researches.

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