The effect of sample storage and homogenisation techniques on the chemical composition and near infrared spectra of white grapes

Abstract not availableWieslawa Cynkar, Daniel Cozzolino, Robert G. Damberg

Rapid analytical sensor systems (spectroscopy and electronic noses) as tools to understand taste and aroma in alcoholic beverages

Cozzolino, D ORCiD: 0000-0001-6247-8817The increasing control of the quality in the beverage and wine industries demands the development of innovative analytical systems. It is well known that chemical analysis of complex samples such as wine and other alcoholic beverages is becoming important to achieve and adequate quality of production, in order to ensure uniformity and consistency within a brand and even to avoid fraud. The sensory characteristics that define wine and other alcoholic beverages such as smell, taste and colour, are influenced by a broad range of factors such as raw material (e.g. grape variety and raw materials), geographical origin, method of production and climate conditions, among others. In such a complex matrix the use of sensor systems combined with multivariate data analysis (chemometrics) is specially promising in order to obtain information for monitoring quality in wine and other alcoholic beverages. This chapter will review the use of sensor systems as tools to understand taste in wine and other alcoholic beverages

Varietal differentiation of grape juice based on the analysis of near- and mid-infrared spectral data

The aim of this study was to evaluate the usefulness of visible (VIS), near-infrared reflectance (NIR) and mid-infrared (MIR) spectroscopy combined with pattern recognition methods as tools to differentiate grape juice samples from commercial Australian Chardonnay (n = 121) and Riesling (n = 91) varieties. Principal component analysis (PCA), partial least squares discriminant analysis and linear discriminant analysis (LDA) were applied to classified grape juice samples according to variety based on both NIR and MIR spectra using full cross-validation (leave-one-out) as a validation method. Overall, LDA models correctly classify 86% and 80% of the grape juice samples according to variety using MIR and VIS-NIR, respectively. The results from this study demonstrated that spectral differences exist between the juice samples from different varietal origins and confirmed that the infrared (IR) spectrum contains information able to discriminate among samples. Furthermore, analysis and interpretation of the eigenvectors from the PCA models developed verified that the IR spectrum of the grape juice has enough information to allow the prediction of the variety. These results also suggested that IR spectroscopy coupled with pattern recognition methods holds the necessary information for a successful classification of juice samples of different varieties.Daniel Cozzolino, Wies Cynkar, Nevil Shah, Paul Smit

Feasibility study on the use of attenuated total reflectance mid-infrared for analysis of compositional parameters in wine

Cozzolino, D ORCiD: 0000-0001-6247-8817A simple and fast method was developed for simultaneously determining ethanol, specific gravity (SG), volatile acidity (VA), glucose plus fructose (G. +. F), pH and titratable acidity (TA) in commercial Australian red and white wine samples using mid-infrared (MIR) spectroscopy and attenuated total reflectance (ATR). Wine samples (n = 130) were analysed using an MIR instrument equipped with a single bounce ATR cell. Results from this study demonstrated the capability of ATR-MIR coupled with partial least squares (PLS) regression to measure compositional parameters in wine. The standard errors of prediction (SEP) obtained were of 0.11 (%) for ethanol, 0.0007 for SG, 0.10 for pH, 0.53. g/L for TA, 1.35. g/L for G. +. F, and 0.12. g/L for VA. Both the sample preparation time of analysis and volume of sample required were considerably reduced compared to the transmission MIR measurements currently used by the wine industry. © 2010 Elsevier Ltd.Associated Grant:Grape and Wine Research and Development Corporation, with matching funds from the Australian governmen

Comparison of metal oxide-based electronic nose end mess spectrometry-based electronic nose for the prediction of red wine spoilage

Taints caused by Brettanomyces sp. spoilage are of concern to winemakers and consumers. Typically the taints are described as "barnyard", "sweaty saddle", and "Band-aid" when present in red wine at concentrations of several hundred micrograms per liter or more. The two main components of the taint are 4-ethylphenol (4EP) and 4-ethylguaiacol (4EG), which are metabolites produced by Brettanomyces yeasts. There is a need for a rapid instrumental method to quantify these compounds in wines. In this paper are compared two techniques, the metal oxide sensor-based electronic nose (MOS-Enose) and the mass spectrometry-based electronic nose (MS-Enose). Gas chromatography-mass spectrometry (GC-MS) was used for quantification and prediction purposes. Following ethanol removal, the limits of detection of a MOS-Enose were determined as 44 microg L(-1) for 4EP and 91 microg L(-1) for 4EG, using the SY/gCT sensor. These values are significantly lower than the reported human sensory thresholds. Partial least-squares (PLS) regression of electronic nose signals against known levels of 4EP and 4EG in 46 Australian red wines showed that the MOS-Enose was unable to identify "brett" spoilage reliably because of the response of the gas sensors to intersample variation in volatile compounds other than ethylphenols. Conversely, the MS-Enose was capable of reliably estimating concentrations of 4EP higher than 20 microg L(-1). Correlations (r2) of 0.97 and 0.98 were obtained between estimates of 4EP and 4EG concentrations with the concentrations determined by conventional GC-MS. It is concluded that, following ethanol removal, existing metal oxide sensors are sufficiently sensitive to detect brett taints in wine but lack the selectivity needed to perform this task when the aroma volatile background varies.Amalia Z. Berna, Stephen Trowell, Wies Cynkar, and Daniel Cozzolin

Can spectroscopy geographically classify Sauvignon Blanc wines from Australia and New Zealand?

The combination of UV, visible (Vis), near-infrared (NIR) and mid-infrared (MIR) spectroscopy with multivariate data analysis was explored as a tool to classify commercial Sauvignon Blanc (Vitis vinifera L., var. Sauvignon Blanc) wines from Australia and New Zealand. Wines (n = 64) were analysed in transmission using UV, Vis, NIR and MIR regions of the electromagnetic spectrum. Principal component analysis (PCA), soft independent modelling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) were used to classify Sauvignon Blanc wines according to their geographical origin using full cross validation (leave-one-out) as a validation method. Overall PLS-DA models correctly classified 86% of the wines from New Zealand and 73%, 86% and 93% of the Australian wines using NIR, MIR and the concatenation of NIR and MIR, respectively. Misclassified Australian wines were those sourced from the Adelaide Hills of South Australia. These results demonstrate the potential of combining spectroscopy with chemometrics data analysis techniques as a rapid method to classify Sauvignon Blanc wines according to their geographical origin

Use of attenuated total reflectance midinfrared for rapid and real-time analysis of compositional parameters in commercial white grape juice

A simple and fast midinfrared (MIR) spectroscopy method was developed for simultaneously determining total soluble solids (TSS, degrees Brix), pH, total phenolics, ammonia, free amino nitrogen (FAN), and yeast assimilable nitrogen (YAN) contents in grape juice samples using attenuated total reflectance (ATR). Results from this study demonstrated the capability of ATR-MIR coupled with partial least-squares regression to measure TSS and pH and to monitor FAN, ammonia, and YAN in a wide range of grape juice samples. The standard error in cross-validation and the residual predictive deviation obtained were 0.20 degrees Brix and 9 for TSS, 0.07 and 3.3 for pH, 14.8 mg/L and 2 for ammonia, 28.3 mg/L and 2 for FAN, and 36.9 mg/L and 2 for YAN, respectively. Both the time of analysis and the volume of sample required were considerably reduced as compared to the transmission MIR measurements currently used by the wine industry.Nevil Shah, Wies Cynkar, Paul Smith and Daniel Cozzolin

Quantitative analysis of minerals and electric conductivity of red grape homogenates by near infrared reflectance spectroscopy

Cozzolino, D ORCiD: 0000-0001-6247-8817The use of near infrared (NIR) reflectance spectroscopy to measure the concentration of minerals and electric conductivity (EC) in red grape homogenates was investigated. Wine grape samples (n=209) from two vintages, representing a wide range of varieties and regions were analysed by Inductively Coupled Plasma Optical Emission Spectrometry (ICPOES) for the concentrations of calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), sulphur (S), iron (Fe), and manganese (Mn) and scanned in reflectance in a NIR instrument (400-2500nm). The spectra were pre-processed using multiple scatter correction (MSC) before developing the calibration models using partial least squares (PLS) regression and cross validation. Coefficients of determination in cross validation (R2) and the standard errors of cross validation (SECV) obtained were for Fe (0.60 and 1.49mgkg-1), Mn (0.71 and 0.41mgkg-1), Ca (0.75 and 60.89mgkg-1), Mg (0.84 and 12.93mgkg-1), K (0.78 and 285.34mgkg-1), P (0.70 and 40.19mgkg-1), S (0.88 and 14.45mgkg-1) and EC (0.87 and 7.66mS). The results showed that Mg, S and EC in grape berries might be measured by NIR reflectance spectroscopy. © 2011 Elsevier B.V.Associated Grant:Grape and Wine Research and Development Corporation, with matching funds from the Australian Governmen

Technical solutions for analysis of grape juice, must, and wine: The role of infrared spectroscopy and chemometrics

Cozzolino, D ORCiD: 0000-0001-6247-8817Information about constituents of grape juice, must, and wine can be used for management and decision support systems in order to improve, monitor, and adapt grape and wine production to new challenges. Numerous sensors that gather this information are either currently available or in development. Nevertheless there is still a need to adapt these sensors to special requirements, for example robustness, calibration and maintenance, operating costs, duration, sensitivity, and specificity to a particular application. The sensors commonly used by the wine industry are those that are based on mid-infrared (MIR), near-infrared (NIR), visible (VIS) and ultraviolet (UV) spectroscopy. This article reviews some recent technical solutions for analysis of juice, must and wine based on the combination of infrared spectroscopy and chemometrics. © 2011 Springer-Verlag.Associated Grant:Grape and Wine Research and Development Corporation, with matching funds from the Australian governmen

Two-dimensional correlation analysis of the effect of temperature on the fingerprint of wines analysed by mass spectrometry electronic nose

Abstract not availableDaniel Cozzolino, Wies Cynkar, Robert Dambergs, Paul Smit