A chemometric approach to investigating South African wine behaviour using chemical and sensory markers
| dc.contributor.advisor | Buica, Astrid | en_ZA |
| dc.contributor.advisor | Brand, Jeanne | en_ZA |
| dc.contributor.advisor | Medvedovici, Andrei V. | en_ZA |
| dc.contributor.author | Mafata, Mpho | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of AgriSciences. Dept. of Viticulture and Oenology. | en_ZA |
| dc.date.accessioned | 2021-03-07T19:11:40Z | |
| dc.date.accessioned | 2021-04-22T10:13:51Z | |
| dc.date.available | 2022-03-08T03:00:10Z | |
| dc.date.issued | 2021-03 | |
| dc.description | Thesis (PhDAgric)--Stellenbosch University, 2021. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: The aim of this dissertation was to demonstrate the value of comprehensive narratives and elucidate critical steps in data handling in Oenology, while highlighting some common misconceptions and misinterpretations related to the process. This compilation was a journey through different stages of dealing with oenological data, with increasing complexity in both the strategies and the techniques used (sensory, chemistry, and statistics). To achieve this aim, different strategies and multivariate tools were used under two prime objectives. Firstly, several multivariate descriptive approaches were used to investigate two oenological problems and lay out the contextual foundations for the statistics-focused work (Chapters 3 and 5). Secondly, in increasing levels of complexity, statistical strategies of constructing comprehensive data fusion as well as pattern recognition models were investigated (Chapters 4 and 6). A comprehensive literature review (Chapter 2) examined and addressed common misconceptions in the different stages of data handling Oenology. The first oenological problem, described in Chapter 3, investigated the evolution of the sensory perception of aroma, as well as the antioxidant-related parameters and volatile compound composition of Sauvignon Blanc and Chenin Blanc wines stored under different conditions and durations. The study applied an appropriate sensory method for this research question, namely, Pivot©Profiling. The study was able to show the evolution of Sauvignon Blanc from ‘fruity’ and ‘herbaceous’ and of Chenin Blanc from ‘fruity’ and ‘tropical’ both towards ‘toasted’, ‘oak’, and ‘honey’ attributes. Chemically, the volatile composition did not show any trends. However, wines stored at higher temperatures for longer periods had relatively higher UV-Vis absorbance, colour density as well as higher b* (yellow) values and lower clarity in terms of L* index, compared to the control. The second oenological problem, described in Chapter 5, investigated the typicality of South African old vine Chenin Blanc perceptually and conceptually using a typicality rating and a flexible sorting task. The sensory methodology followed published strategies for investigating typicality. This study did not find a unique sensory space of the old vine Chenin Blanc due to a lack of perceptual consensus among the industry professionals for the wines included in the study. However, it did find that the industry professionals had unified ideas about the attributes of an ideal old vine Chenin Blanc wine. The first of the statistics-focused studies, described in Chapter 4, explored data fusion at low and mid-level using principal component analysis - PCA (low and mid-level) and multiple factor analysis - MFA (mid-level). The study looked at data pre-processing and matrix compatibility, which are important data handling stages for data fusion. Like the contextual chapters (Chapter 3 and 5), and keeping with the aim of this compilation, this chapter gave a detailed descriptive narrative of the data handling. Through detailed examination of the process, the study found that MFA was the most appropriate data fusion strategy. The second statistics-focused study, described in Chapter 6, continued to exploit the multiple advantages of multiblock approach of MFA. Additionally, this chapter showed the reliability of fuzzy k-means clustering compared to agglomerative hierarchical clustering (AHC). | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Die doel van hierdie proefskrif was om die waarde van omvattende vertellings te demonstreer en om kritiese stappe in die hantering van data in die wynkunde toe te lig, terwyl enkele algemene wanopvattings en verkeerde interpretasies in verband met die proses uitgelig word. Hierdie samestelling was 'n reis deur verskillende stadiums van die hantering van wynkundige data, met toenemende kompleksiteit in beide die strategieë en die gebruikte tegnieke (sensoriese, chemie en statistieke). Om hierdie doel te bereik, is verskillende strategieë en meerveranderlike instrumente onder twee hoofdoelstellings gebruik. Eerstens is verskeie multivariate beskrywingsbenaderings gebruik om twee oenologiese probleme te ondersoek en die kontekstuele grondslae vir die statistiekgerigte werk uit te lê (hoofstukke 3 en 5). Tweedens, in toenemende vlakke van kompleksiteit, is statistiese strategieë vir die konstruering van omvattende datafusie sowel as patroonherkenningsmodelle ondersoek (hoofstukke 4 en 6). 'N Omvattende literatuuroorsig (hoofstuk 2) het algemene misverstande in die verskillende stadiums van datahantering van wynkunde ondersoek en behandel. Die eerste wynprobleem, wat in hoofstuk 3 beskryf word, het die evolusie van die sintuiglike waarneming van aroma ondersoek, asook die antioksidant-verwante parameters en die vlugtige samestelling van Sauvignon Blanc- en Chenin Blanc-wyne wat onder verskillende toestande en duur gestoor is. Die studie het 'n toepaslike sensoriese metode vir hierdie navorsingsvraag toegepas, naamlik Pivot©Profiling. Die studie kon die evolusie van Sauvignon Blanc van 'vrugtige' en 'kruidagtige' en van Chenin Blanc van 'vrugtige' en 'tropiese' sowel as 'geroosterde', 'eikehout' en 'heuning'-eienskappe aantoon. Chemies het die vlugtige samestelling geen neigings getoon nie. Wyne wat vir langer tydperke by hoër temperature gestoor is, het egter relatief hoër UV-Vis- absorbansie, kleurdigtheid sowel as hoër b * (geel) waardes en laer helderheid in terme van L * - indeks, vergeleke met die kontrole. Die tweede wynprobleem, wat in hoofstuk 5 beskryf word, het die tipiesheid van die Suid- Afrikaanse ou wingerdstok Chenin Blanc perseptueel en konseptueel ondersoek met behulp van 'n tipiese klassifikasie en 'n buigsame sorteertaak. Die sensoriese metodologie het gepubliseerde strategieë vir die ondersoek na tipiesheid gevolg. Hierdie studie het nie 'n unieke sensoriese ruimte vir die ou wingerdstok Chenin Blanc gevind nie, omdat daar 'n gebrek aan konseptuele konsensus tussen die professionele persone vir die wyne wat in die studie opgeneem is, was. Dit het egter gevind dat professionele persone in die bedryf eenvormige idees gehad het oor die eienskappe van 'n ideale ou wynstok Chenin Blanc-wyn. Die eerste van die statistiekgerigte studies, wat in hoofstuk 4 beskryf word, het datafusie op lae en middelvlak ondersoek met hoofkomponentanalise - PCA (lae en middelvlak) en meervoudige faktorontleding - MFA (middelvlak). Die studie het gekyk na die voorverwerking van data en matriksversoenbaarheid, wat belangrike stadiums vir die hantering van data is vir die versmelting van data. Net soos die kontekstuele hoofstukke (Hoofstuk 3 en 5), en in ooreenstemming met die doel van hierdie samestelling, het hierdie hoofstuk 'n gedetailleerde beskrywende vertelling van die datahantering gegee. Deur middel van 'n uitvoerige ondersoek van die proses, het die studie bevind dat MFA die mees geskikte strategie vir data-fusie was. Die tweede statistiekgerigte studie, wat in hoofstuk 6 beskryf word, het voortgegaan om die veelvuldige voordele van multiblokke benadering van MFA te benut. Verder het hierdie hoofstuk die betroubaarheid van fuzzy k-middelgroepering vergeleke met agglomeratiewe hiërargiese groepering (AHC) getoon. | af_ZA |
| dc.description.version | Doctoral | en_ZA |
| dc.embargo.terms | 2022-03-08 | |
| dc.format.extent | 163 pages : illustrations | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/10019.1/110318 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject | Chemometrics | en_ZA |
| dc.subject | Sensometrics | en_ZA |
| dc.subject | Data fusion | en_ZA |
| dc.subject | Data handling | en_ZA |
| dc.subject | Wine and wine making -- South Africa | en_ZA |
| dc.subject | Wine -- Flavor and odor | en_ZA |
| dc.subject | Wine -- Sensory evaluation | en_ZA |
| dc.subject | UCTD | en_ZA |
| dc.title | A chemometric approach to investigating South African wine behaviour using chemical and sensory markers | en_ZA |
| dc.type | Thesis | en_ZA |