Characterisation of grapevine berry samples with infrared spectroscopy methods and multivariate data analyses tools

Musingarabwi, Davirai M. (2015-04)

Thesis (MSc)--Stellenbosch University, 2015.

Thesis

ENGLISH ABSTRACT: Grape quality is linked to the organoleptic properties of grapes, raisins and wine. Many advances have been made in understanding the grape components that are important in the quality of wines and other grape products. A better understanding of the compositional content of grapes entails knowing when and how the various components accumulate in the berry. Therefore, an appreciation of grape berry development is vitally important towards the understanding of how vineyard practices can be used to improve the quality of grapes and eventually, wines. The more established methods for grape berry quality assessment are based on gravimetric methods such as colorimetry, fluorescence and chromatography. These conventional methods are accurate at targeting particular components, but are typically multi-step, destructive, expensive, polluting procedures that might be technically challenging. Very often grape berries are evaluated for quality (only) at harvest. This remains a necessary exercise as it helps viticulturists and oenologists to estimate some targeted metabolite profiles that are known to greatly influence chemical and sensory profiles of wines. However, a more objective measurement of predicting grape berry quality would involve evaluation of the grapes throughout the entire development and maturation cycle right from the early fruit to the ripe fruit. To achieve this objective, the modern grape and wine industry needs rapid, reliable, simpler and cost effective methods to profile berry development. By the turn of the last millennium, developments in infrared instrumentation such as Fourier-transform infrared (FT NIR) and attenuated total reflectance Fourier-transform infrared spectroscopy (ATR FT-IR) in combination with chemometrics resulted in the development of rapid methods for evaluating the internal and external characteristics of fresh fruit, including grapes. The advancement and application of these rapid techniques to fingerprint grape compositional traits would be useful in monitoring grape berry quality. In this project an evaluation of grape berry development was investigated in a South African vineyard setting. To achieve this goal, Sauvignon blanc grape berry samples were collected and characterised at five defined stages of development: green, pre-véraison, véraison, post-véraison and ripe. Metabolically inactivated (frozen in liquid nitrogen and stored at -80oC) and fresh berries were analysed with FT-IR spectroscopy in the near infrared (NIR) and mid-infrared (MIR) ranges to provide spectral data. The spectral data were used to provide qualitative (developmental stage) and quantitative (metabolite concentration of key primary metabolites) information of the berries. High performance liquid chromatography (HPLC) was used to separate and quantify glucose, fructose, tartaric acid, malic acid and succinic acid which provided the reference data needed for quantitative analysis of the spectra. Unsupervised and supervised multivariate analyses were sequentially performed on various data blocks obtained by spectroscopy to construct qualitative and quantitative models that were used to characterise the berries. Successful treatment of data by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) gave statistically significant chemometric models that discriminated the berries according to their stages of development. The loadings from MIR models highlighted the important discriminant variables responsible for the observed developmental stage classification. The best calibration models to predict metabolite concentrations were obtained from MIR spectra for glucose, fructose, tartaric acid and malic acid. The results showed that both NIR and MIR spectra in combination with multivariate analysis could be reliably used to evaluate Sauvignon blanc grape berry quality throughout the fruit’s development cycle. Moreover, the methods used were fast and required minimal sample processing and no metabolite extractions with organic solvent. In addition, the individual major sugar and organic acids were accurately predicted at the five stages under investigation. This study provides further proof that IR technologies are robust and suitable to explore high-throughput and in-field application of grape compound profiling.

AFRIKAANSE OPSOMMING: Druifkwaliteit word gekoppel aan die organoleptiese eienskappe van druiwe, rosyntjies en wyn. Baie vooruitgang is reeds gemaak in die begrip van druifkomponente wat belangrik is vir die kwaliteit van wyn en ander druifprodukte. ’n Beter begrip van die samestellende inhoud van druiwe behels om te weet wanneer en hoe die verskeie komponente in die korrel opgaar. ’n Evaluasie van druiwekorrel-ontwikkeling is dus uiters belangrik vir ’n begrip van hoe wingerdpraktyke gebruik kan word om die kwaliteit van druiwe, en uiteindelik van wyne, te verbeter. Die meer gevestigde maniere vir die assessering van druiwekorrelkwaliteit is gebaseer op gravimetriese metodes soos kolorimetrie, fluoressensie en chromatografie. Hierdie konvensionele metodes is akkuraat om spesifieke komponente te teiken, maar behels tipies veelvuldige stappe en is prosesse wat destruktief en duur is, besoedeling veroorsaak, asook moontlik tegnies uitdagend is. In baie gevalle word druiwekorrels (eers) tydens oes vir kwaliteit geëvalueer. Hierdie is steeds ’n noodsaaklike oefening omdat dit wingerdkundiges en wynkundiges help om die metabolietprofiele wat daarvoor bekend is om ’n groot invloed op die chemiese en sensoriese profiele van wyn te hê en dus geteiken word, te skat. ’n Meer objektiewe meting om druiwekorrelkwaliteit te voorspel, sou die evaluering van die druiwe dwarsdeur hulle ontwikkeling- en rypwordingsiklus behels, vanaf die vroeë vrugte tot die ryp vrugte. Om hierdie doelwit te behaal, benodig die moderne druiwe- en wynbedryf vinnige, betroubare, eenvoudiger en kostedoeltreffende metodes om ’n profiel saam te stel van korrelontwikkeling. Aan die einde van die vorige millennium het ontwikkelings in infrarooi instrumentering soos Fourier-transform infrarooi (FT NIR) en attenuated total reflectance Fourier-transform infrarooi spektroskopie (ATR FT-IR) in kombinasie met chemometrika gelei tot die ontwikkeling van vinnige metodes om die interne en eksterne kenmerke van vars vrugte, insluitend druiwe, te meet. Die vooruitgang en toepassing van hierdie vinnige tegnieke om ‘vingerafdrukke’ te bekom van die samestellende kenmerke sal nuttig wees vir die verbetering van druiwekorrelkwaliteit. In hierdie projek is ’n evaluering van druiwekorrelontwikkeling in ’n Suid-Afrikaanse wingerdligging ondersoek. Ten einde hierdie doel te bereik, is Sauvignon blanc druiwekorrelmonsters op vyf gedefinieerde stadiums van ontwikkeling versamel en gekarakteriseer: groen, voor deurslaan, deurslaan, ná deurslaan en ryp. Metabolies geïnaktiveerde (bevrore in vloeibare stikstof en gestoor teen -80oC) en vars korrels is met FT-IR spektroskopie in die naby infrarooi (NIR) and mid-infrarooi (MIR) grense geanaliseer om spektrale data te verskaf. Die spektrale data is gebruik om kwalitatiewe (ontwikkelingstadium) en kwantitatiewe (metabolietkonsentrasie van belangrikste primêre metaboliete) inligting van die korrels te verskaf. High performance liquid chromatography (HPLC) is gebruik om glukose, fruktose, wynsteensuur, appelsuur en suksiensuur te skei en te kwantifiseer, wat die verwysingsdata verskaf het wat vir die kwantitatiewe analise van die spektra benodig word. Ongekontroleerde en gekontroleerde meervariantanalises is opeenvolgend op verskeie datablokke uitgevoer wat met spektroskopie verkry is om kwalitatiewe en kwantitatiewe modelle te verkry wat gebruik is om die korrels te karakteriseer. Suksesvolle behandeling van die data deur hoofkomponent analise (principal component analysis (PCA)) en ortogonale parsiële kleinstekwadraat diskriminant analise (partial least squares discriminant analysis (OPLS-DA)) het statisties betekenisvolle chemometriese modelle verskaf wat die korrels op grond van hulle ontwikkelingstadia onderskei het. Die ladings vanaf die MIR-modelle het die belangrike diskriminantveranderlikes beklemtoon wat vir die klassifikasie van die waargenome ontwikkelingstadium verantwoordelik is. Die beste kalibrasiemodelle om metabolietkonsentrasies te verkry, is vanuit die MIR-spektra vir glukose, fruktose, wynsteensuur en appelsuur bekom. Die resultate toon dat beide die NIR- en MIR-spektra, in kombinasie met meervariantanalise, betroubaar gebruik kan word om Sauvignon blanc druiwekorrelkwaliteit dwarsdeur die vrug se ontwikkelingsiklus te evalueer. Verder is die metodes wat gebruik word, vinnig en het hulle minimale monsterprosessering en geen metabolietekstraksies met organiese oplosmiddel benodig nie. Daarbenewens is die vernaamste suiker en organiese sure individueel akkuraat voorspel op die vyf stadia wat ondersoek is. Hierdie studie verskaf verdere bewys dat IR-tegnologieë robuus en geskik is om hoë-deurset en in-veld toepassings van profielsamestelling van druiweverbindings te ondersoek.

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