Browsing by Author "Musingarabwi, Davirai M."

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    Characterisation of grapevine berry samples with infrared spectroscopy methods and multivariate data analyses tools
    (Stellenbosch : Stellenbosch University, 2015-04) Musingarabwi, Davirai M.; Vivier, Melane A.; Nieuwoudt, Helene; Stellenbosch University. Faculty of Agrisciences. Dept. of Viticulture and Oenology. Institute for Wine Biotechnology.
    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.