To target or not to target: strategies for the aroma analysis of alcoholic beverages
| dc.contributor.advisor | Buica, Astrid | en_ZA |
| dc.contributor.advisor | Stander, Marietjie A. | en_ZA |
| dc.contributor.advisor | Medvedovici, Andrei V. | en_ZA |
| dc.contributor.author | Williams, Cody | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Science. Dept. of Biochemistry. | en_ZA |
| dc.date.accessioned | 2023-11-30T12:52:32Z | |
| dc.date.accessioned | 2024-01-08T21:27:37Z | |
| dc.date.available | 2023-11-30T12:52:32Z | |
| dc.date.available | 2024-01-08T21:27:37Z | |
| dc.date.issued | 2023-12 | |
| dc.description | Thesis (PhD)--Stellenbosch University, 2023. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: Classically, targeted analysis has dominated analytical chemistry research, whereby analytical methods are required for separation, identification and quantitation of specific analytes of interest. The complex wine, gin and beer matrices contain several hundreds of compounds, each with varying concentration levels and unique chemistries. Furthermore, comprehensive analysis of these alcoholic beverages are challenging, as suitable instrumentation and data handling strategies are required to effectively profile these matrices. The use of non-targeted methodologies emerge as an alternative tool used for profiling the aroma space of alcoholic beverages. Non-targeted analysis is an information rich technique which focuses on profiling a sample in its entirety. More data can equal more information, however more noise is also generated; thus, suitable strategies are highly desired to overcome this caveat. The question is now, are these strategies complementary or is the generated information redundant? The aim of this dissertation was to compare targeted and non-targeted strategies for the aroma analysis of wine, beer and gin. This dissertation is comprised of seven chapters showing the evolution of both targeted and non- targeted strategies starting with wine and culminating in the application of these strategies in craft gin and beer, together with the evaluation of the results using appropriate (and sometimes complex) statistical tools. The first part of the study is a comprehensive literature review, with specific focus on terpenoid analysis. Terpenoids are an integral component to the sensory profile in wine, beer and gin. These compounds are present in various concentrations and require advanced analytical tools to profile and quantify. The origin of terpenoids as derived from the raw materials or production practices, common concentration ranges, and sample preparation methods are reported. The use of non-targeted methods is also summarised in this review for wine, beer and gin, with particular focus on the use of hyphenated instrumentation, software processing tools, and multivariate statistical analysis. The first objective (chapter 3) focused on targeted strategies in wine. Terpenoids were selected due to their importance to the aroma profile and inherent challenges associated with the analysis of these compounds. The complexity associated with the analyses stimulated interest and prompted further investigation in the quantitation of terpenoids in wine. Two sample preparation strategies, namely offline-SPE and online-HS-SPME were explored for the quantitation of 20 terpenoids in red and white wine. This study documented which sample preparation was best for the quantitation of terpenoids in wine and reported on various method performance parameters. The second objective (chapter 4) expanded on the quantitation of terpenoids in wine, whereby the method was expanded from 20 to 53 terpenoids in a single method. This was accomplished through method development, optimisation and method performance characterisation. In addition, terpenoid stability was evaluated over a period of forty days. As this extended method includes compounds not found in wine, it was applied to craft gin (n=21) and craft beer (n=34) samples, and it documents for the first time the most terpenoids quantified in a single method using authentic standards. It also constitutes the first report on terpenoids quantified in South African craft gin and beer. In the non-targeted space, the third objective (chapter 5) highlights the use of various sample prepration strategies (LLE, SPE and HS-SPME) applied to wine of different cultivar (Chenin Blanc, Sauvignon Blanc and Chardonnay) and winemaking style (wooded and unwooded). The data was acquired using a non-targeted profiling method and processed using cloud metabolomics software, XCMS online, followed by multivariate analysis. Importantly, the pipeline methodology for this approach was established to characterise both qualitative and quantitative information on the wine samples. This strategy enabled the identification of the most sensitive and best profiling sample preparation method. In addition, this application conceptualises a pipeline methodology approach, whereby sample preparation, instrument analysis, cloud data processing and multivariate analysis is applied in order to obtain meaningful relationships in complex data sets. As an extension of the targeted and non-targeted strategies reported, the fourth and final objective (chapter 6) showcases an application of this pipeline methodology to craft beer (n=91) and gin (n=67). Craft beer and gin samples were analysed using the targeted terpenoid and non-targeted profiling strategies. Subsequent data processing and curation allowed for application to multivariate statistical analysis. The configurational similarity was compared to reveal differences between the targeted and non-targeted strategies. Further insight was made into identifying characteristic biomarkers for distinguishing between lager-style and ale-style craft beers. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Klassiek het geteikende analise analitiese chemie-navorsing oorheers, waardeur analitiese metodes vereis word vir skeiding, identifikasie en kwantifisering van spesifieke analiete van belang. Die komplekse wyn-, jenewer- en biermatrikse bevat etlike honderde verbindings, elk met wisselende konsentrasievlakke en unieke chemie. Verder is omvattende ontleding van hierdie alkoholiese drank uitdagend, aangesien geskikte instrumentasie en data-hanteringstrategieë vereis word om hierdie matrikse effektief te profileer. Die gebruik van nie-geteikende metodologieë kom na vore as 'n alternatiewe hulpmiddel wat gebruik word vir die profilering van die aromaruimte van alkoholiese drankies. Nie-geteikende analise is 'n inligting ryk tegniek wat fokus op die profilering van 'n monster in sy geheel. Meer data kan gelyk wees aan meer inligting, maar meer geraas word ook gegenereer; dus word geskikte strategieë hoogs verlang om hierdie voorbehoud te oorkom. Die vraag is nou, is hierdie strat. Die doel van hierdie proefskrif was om geteikende en nie-geteikende strategieë vir die aroma-analise van wyn, bier en jenewer te vergelyk. Hierdie proefskrif bestaan uit sewe hoofstukke wat die evolusie van beide geteikende en nie-geteikende strategieë toon wat met wyn begin en uitloop op die toepassing van hierdie strategieë in kunsvlyt-jenever en bier, tesame met die evaluering van die resultate deur toepaslike (en soms komplekse) statistiese gereedskap. egieë aanvullend of is die gegenereerde inligting oorbodig? Die eerste deel van die studie is 'n omvattende literatuuroorsig, met spesifieke fokus op terpenoïedanalise. Terpenoïede is 'n integrale komponent tot die sensoriese profiel in wyn, bier en jenewer. Hierdie verbindings kom in verskeie konsentrasies voor en vereis gevorderde analitiese gereedskap om te profileer en te kwantifiseer. Die oorsprong van terpenoïede soos afgelei van die grondstowwe of produksiepraktyke, algemene konsentrasiereekse en monstervoorbereidingsmetodes word gerapporteer. Die gebruik van nie- geteikende metodes word ook in hierdie oorsig vir wyn, bier en jenewer opgesom, met besondere fokus op die gebruik van koppeltekeninstrumentasie, sagtewareverwerkingsinstrumente en meerveranderlike statistiese analise. Die eerste doelwit (hoofstuk 3) het gefokus op geteikende strategieë in wyn. Terpenoïede is gekies weens hul belangrikheid vir die aromaprofiel en inherente uitdagings wat met die ontleding van hierdie verbindings geassosieer word. Die kompleksiteit verbonde aan die ontledings het belangstelling geprikkel en verdere ondersoek in die kwantifisering van terpenoïede in wyn aangespoor. Twee monstervoorbereidingstrategieë, naamlik vanlyn-SPE en aanlyn-HS-SPME is ondersoek vir die kwantifisering van 20 terpenoïede in rooi en witwyn. Hierdie studie het gedokumenteer watter monstervoorbereiding die beste was vir die kwantifisering van terpenoïede in wyn en het gerapporteer oor verskeie metode prestasie parameters. Die tweede doelwit (hoofstuk 4) het uitgebrei oor die kwantifisering van terpenoïede in wyn, waardeur die metode van 20 na 53 terpenoïede in 'n enkele metode uitgebrei is. Dit is bereik deur metode-ontwikkeling, optimalisering en metodeprestasie-karakterisering. Daarbenewens is terpenoïedstabiliteit oor 'n tydperk van veertig dae geëvalueer. Aangesien hierdie uitgebreide metode verbindings insluit wat nie in wyn gevind word nie, is dit toegepas op kunsjin (n=21) en handwerkbier (n=34) monsters, en dit dokumenteer vir die eerste keer die meeste terpenoïede wat in 'n enkele metode gekwantifiseer is met behulp van outentieke standaarde . Dit vorm ook die eerste verslag oor terpenoïede wat in Suid-Afrikaanse kunsvlyt-jenever en -bier gekwantifiseer is. In die nie-geteikende ruimte beklemtoon die derde doelwit (hoofstuk 5) die gebruik van verskeie monstervoorbereidingstrategieë (LLE, SPE en HS-SPME) wat toegepas word op wyn van verskillende kultivars (Chenin Blanc, Sauvignon Blanc en Chardonnay) en wynmaakstyl (bebost en ongehout). Die data is verkry met behulp van 'n nie-geteikende profilering metode en verwerk met behulp van wolk metabolomics sagteware, XCMS aanlyn, gevolg deur meerveranderlike analise. Dit is belangrik dat die pyplynmetodologie vir hierdie benadering vasgestel is om beide kwalitatiewe en kwantitatiewe inligting oor die wynmonsters te karakteriseer. Hierdie strategie het die identifikasie van die mees sensitiewe en beste profileringsmonster- voorbereidingsmetode moontlik gemaak. Daarbenewens konseptualiseer hierdie toepassing 'n pyplynmetodologiebenadering, waardeur monstervoorbereiding, instrumentanalise, wolkdataverwerking en meerveranderlike analise toegepas word om betekenisvolle verwantskappe in komplekse datastelle te verkry. As 'n uitbreiding van die geteikende en nie-geteikende strategieë wat gerapporteer is, toon die vierde en laaste doelwit (hoofstuk 6) 'n toepassing van hierdie pyplynmetodologie op handwerkbier (n=91) en jenewer (n=67). Handwerkbier- en jenewermonsters is ontleed deur gebruik te maak van die geteikende terpenoïde en nie-geteikende profileringstrategieë. Daaropvolgende dataverwerking en samestelling het toegelaat vir toepassing op meerveranderlike statistiese analise. Die konfigurasie-ooreenkoms is vergelyk om verskille tussen die geteikende en nie-geteikende strategieë te openbaar. Verdere insig is gemaak in die identifisering van kenmerkende biomerkers om tussen lagerstyl- en bierstyl-handwerkbiere te onderskei. | af_ZA |
| dc.description.version | Doctoral | en_ZA |
| dc.format.extent | xviii, 347 pages : illustrations (some color) | en_ZA |
| dc.identifier.uri | https://scholar.sun.ac.za/handle/10019.1/129074 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject.lcsh | Alcoholic beverages -- Flavor and odor | en_ZA |
| dc.subject.lcsh | Gin | en_ZA |
| dc.subject.lcsh | Aromatic compounds | en_ZA |
| dc.subject.lcsh | Beer | en_ZA |
| dc.subject.lcsh | Terpenoids | en_ZA |
| dc.subject.lcsh | Wine -- Sensory evaluation | en_ZA |
| dc.subject.lcsh | Wine and wine making -- Chemistry | en_ZA |
| dc.subject.lcsh | Alcoholic beverages -- South Africa | en_ZA |
| dc.subject.lcsh | Multivariate analysis -- Data processing | en_ZA |
| dc.subject.name | UCTD | en_ZA |
| dc.title | To target or not to target: strategies for the aroma analysis of alcoholic beverages | en_ZA |
| dc.type | Thesis | en_ZA |
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