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Application of Statistics for Beverages
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Application of Statistics for Beverages

A special issue of Beverages (ISSN 2306-5710). This special issue belongs to the section "Quality, Nutrition, and Chemistry of Beverages".

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 13597

Special Issue Editors

Dr. Alberto Mannu

E-Mail Website
Guest Editor
Department of Chemistry, Materials and Chemical Engineering “G. Natta”, Politecnico di Milano, Via Luigi Mancinelli 7, 20131 Milano, Italy
Interests: eutectic solvents; recycling lithium-ion batteries; design of experiments; extraction procedures; sustainability assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Giacomo L. Petretto

E-Mail Website
Guest Editor
Department of Chemistry and Pharmacy, University of Sassari, Via Vienna, 207100, Sassari, Italy
Interests: volatile organic compounds; wine aroma; chemical composition; gas chromatography
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of statistic techniques and multivariate analysis in food chemistry, particularly for beverages, represents fundamental tools for determining chemical and physical profiles. The combination of analytical techniques and multivariate analysis allows the exploitation of the full potential of acquired data, sometimes revealing hidden information.

All interested authors are welcome to publish research papers and/or reviews based on, but not limited to, the following topics:

- Stratistical analyses of data with the aim to determine chemical and physical fingerprints. These can include partial least square discriminant analysis (PLS-DA) and variable important plots (VIP plots).

- Statistical analyses aimed to classify beverages through the grouping of experimental data in representative clusters. It can include principal component analysis (PCA) and other supervised data treatment methods.

- Data analyses for the development of quality assessment procedures and validation of statistical models for beverage characterization.

- Application of the Design of Experiments (DoE) approach to the analysis of data arising from analytical studies regarding beverages. This can include explorative full factorial designs, analysis of factors, and surface responding studies.

- Metabolomic analysis applied for the detection of recurrent and characteristic chemicals in beverages.

- Analysis of sensorial data for the classification, quality assessment, and market evaluation of beverages.

 

Dr. Alberto Mannu
Dr. Giacomo L. Petretto
Guest Editors

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. Beverages is an international peer-reviewed open access quarterly 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 1600 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

statistical analysis

multivariate analysis

sensorial analysis

design of experiments

beverages fingerprint

beverages classification

beverages characterization

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Published Papers (4 papers)

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Research

17 pages, 445 KiB  
Article
Exploration of Data Fusion Strategies Using Principal Component Analysis and Multiple Factor Analysis
by Mpho Mafata, Jeanne Brand, Martin Kidd, Andrei Medvedovici and Astrid Buica
Beverages 2022, 8(4), 66; https://doi.org/10.3390/beverages8040066 - 21 Oct 2022
Cited by 6 | Viewed by 2948
Abstract
In oenology, statistical analyses are used for descriptive purposes, mostly with separate sensory and chemistry data sets. Cases that combine them are mostly supervised, usually seeking to optimize discrimination, classification, or prediction power. Unsupervised methods are used as preliminary steps to achieving success [...] Read more.
In oenology, statistical analyses are used for descriptive purposes, mostly with separate sensory and chemistry data sets. Cases that combine them are mostly supervised, usually seeking to optimize discrimination, classification, or prediction power. Unsupervised methods are used as preliminary steps to achieving success in supervised models. However, there is potential for unsupervised methods to combine different data sets into comprehensive, information-rich models. This study detailed stepwise strategies for creating data fusion models using unsupervised techniques at different levels. Principal component analysis (PCA) and multiple factor analysis (MFA) were used to combine five data blocks (four chemistry and one sensory). The model efficiency and configurational similarity were evaluated using eigenvalues and regression vector (RV) coefficients, respectively. The MFA models were less efficient than PCA, having gradual distributions of eigenvalues across model dimensions. The MFA models were more representative than PCA, as indicated by high RV coefficients between MFA and each individual block. Therefore, MFA approaches were better suited for multi-modal data than PCA. This work approached data fusion systematically and showed the type of decisions that must be made and how to evaluate their consequences. Proper integration of data sets, instead of concatenation, is an important aspect to consider in multi-modal data fusion. Full article
(This article belongs to the Special Issue Application of Statistics for Beverages)
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12 pages, 1682 KiB  
Article
The Influence of the Bottle’s Price and Label Reported Information on the Perception of the Minerality Attribute in White Wines
by Elvira Zaldívar Santamaría, David Molina Dagá and Antonio Tomás Palacios García
Beverages 2022, 8(3), 42; https://doi.org/10.3390/beverages8030042 - 21 Jul 2022
Cited by 4 | Viewed by 2444
Abstract
The use of the descriptor “minerality” in a wine has increased in the last few years. This term is frequently used to describe wines closely associated with their terroir. This concept represents the complete natural environment in which a particular wine is produced, [...] Read more.
The use of the descriptor “minerality” in a wine has increased in the last few years. This term is frequently used to describe wines closely associated with their terroir. This concept represents the complete natural environment in which a particular wine is produced, including factors such as the soil, topography and climate. In addition, the term “minerality” is frequently used to increase the price of the bottle. However, little is known regarding how this complex concept is perceived by consumers and whether they use this extrinsic information related to the term “minerality” in the purchasing process. The aim of this study is to understand how the term “minerality” could influence consumers when they purchase wine when this descriptor is included as an extrinsic characteristic on the label and in the price of the bottle. For this purpose, the so-called CATA (check-all-that-apply) methodology was used with a panel of 25 judges in order to define the attributes that a “mineral” wine should contain in order to be chosen and if the information displayed on the label and the price could influence consumers in that process. This technique is a dynamic sensory evaluation in which participants select the terms they consider apply at each moment from a list of attributes and deselect them when they no longer apply. The judges blindly tasted two different white wines in eight different glasses displayed with different label information related or not with terms associated with the minerality concept. In a second round, judges tried six glasses presented with the only information of the bottle’s price. In both tasting sessions, the used list of descriptors contained 44 terms, 16 of which were related to the attribute of minerality, 13 were considered antonyms of such a descriptor and 15 referred to extrinsic aspects. The results showed that consumers were not directly influenced by the label reported information or the bottle´s price when they described a wine as mineral. Finally, the statistical evaluation conducted by the CATA analysis divided the list of 44 used terms by their range of importance when a wine is described as mineral. The terms were divided into those that help to classify a wine as mineral and those that are antagonistic to this concept. Full article
(This article belongs to the Special Issue Application of Statistics for Beverages)
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10 pages, 2091 KiB  
Article
Classification of Pummelo (Citrus grandis) Extracts through UV-VIS-Based Chemical Fingerprint
by Giacomo Luigi Petretto, Maria Enrica Di Pietro, Marzia Piroddi, Giorgio Pintore and Alberto Mannu
Beverages 2022, 8(2), 34; https://doi.org/10.3390/beverages8020034 - 13 Jun 2022
Cited by 4 | Viewed by 2908
Abstract
Cold extraction methods with ethanol applied to the flavedo of Citrus fruits have been commonly applied for the preparation of several liquors. In order to obtain the extraction optimization and then the best ratio of functional ingredients in the extract, the flavedo of [...] Read more.
Cold extraction methods with ethanol applied to the flavedo of Citrus fruits have been commonly applied for the preparation of several liquors. In order to obtain the extraction optimization and then the best ratio of functional ingredients in the extract, the flavedo of Citrus grandis Osbeck (pummelo) was subjected to a maceration with absolute ethanol at room temperature as well as at 40 °C. The kinetics of the extraction methods were monitored by UV–VIS spectroscopy, and a chemical fingerprint characteristic of each extract was determined by statistical multivariate analysis of the UV–VIS raw data. Additionally, the extracts were qualitatively characterized by NMR spectroscopy as well as by solid phase micro extraction followed by gas chromatography/mass spectrometry (GC/MS). NMR analysis confirmed the presence of the typical flavanones of Citrus such as naringin and naringenin, while the GC/MS analysis showed that the headspace of the liquor is characterized by two main compounds represented by β-myrcene and limonene. At the end, the temperature seems to not affect the time of extraction, which is complete after 25 h; however, UV–VIS-based multivariate analysis revealed that a different overall chemical composition is obtained depending on the temperature, probably due to the extraction of minor chemicals as well as due to different levels of the same compounds in the two extracts. Full article
(This article belongs to the Special Issue Application of Statistics for Beverages)
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11 pages, 2227 KiB  
Article
Mapping the Sensory Fingerprint of Swedish Beer Market through Text and Data Mining and Multivariate Strategies
by Gonzalo Garrido-Bañuelos, Helia de Barros Alves and Mihaela Mihnea
Beverages 2021, 7(4), 74; https://doi.org/10.3390/beverages7040074 - 10 Nov 2021
Cited by 5 | Viewed by 4075
Abstract
The continuous increase of online data with consumers’ and experts’ reviews and preferences is a potential tool for sensory characterization. The present work aims to overview the Swedish beer market and understand the sensory fingerprint of Swedish beers based on text data extracted [...] Read more.
The continuous increase of online data with consumers’ and experts’ reviews and preferences is a potential tool for sensory characterization. The present work aims to overview the Swedish beer market and understand the sensory fingerprint of Swedish beers based on text data extracted from the Swedish alcohol retail monopoly (Systembolaget) website. Different multivariate strategies such as heatmaps, correspondence analysis and hierarchical cluster analysis were used to understand the sensory space of the different beer styles. Additionally, sensory space for specific hop cultivars was also investigated. Results highlighted Gothenburg as the main producing area in Sweden. The style Indian Pale Ale (IPA) is the largest available at the retail monopoly. From a sensory perspective, commonalities and differences were found between beer types and styles. Based on the aroma description, different types of ale and lager can cluster together (such as Porter and Stout and Dark lagers). Additionally, an associative relationship between specific aromas and hop cultivars from text data information was successfully achieved. Full article
(This article belongs to the Special Issue Application of Statistics for Beverages)
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