Rg Dambergs

Analysis of grapes and wine by near infrared spectroscopy

Spectroscopic techniques such as near infrared (NIR) spectroscopy are used in the food industry to monitor and assess the composition and quality of products. Similar to other food industries, the wine industry has a clear need for simple, rapid and cost-effective techniques for objectively evaluating the quality of grapes, wines and spirits. Thirty years have passed since the first work reported by Kaffka and Norris on the use of NIR spectroscopy to analyse wine. Since then, NIR spectroscopy has been used for grape and wine compositional analysis, fermentation monitoring and wine grading. However, the use of NIR spectroscopy in the wine industry is still in its infancy. From the analysis of the scatter information available, it appears that NIR spectroscopy is applied in different steps during the wine production. This review highlights the most recent applications of NIR spectroscopy in the grape and wine industry. Additional information is also provided on the use of mid infrared spectroscopy for wine analysis.

Classification of Tempranillo wines according to geographic origin: combination of mass spectrometry based electronic nose and chemometrics.

Rapid methods employing instruments such as electronic noses (EN) or gas sensors are used in the food and beverage industries to monitor and assess the composition and quality of products. Similar to other food industries, the wine industry has a clear need for simple, rapid and cost effective techniques for objectively evaluating the quality of grapes, wine and spirits. In this study a mass spectrometry based electronic nose (MS-EN) instrument combined with chemometrics was used to predict the geographical origin of Tempranillo wines produced in Australia and Spain. The MS-EN data generated were analyzed using principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA) and stepwise linear discriminant analysis (SLDA) with full cross validation (leave-one-out method). The SLDA classified correctly 86% of the samples while PLS-DA 85% of Tempranillo wines according to their geographical origin. The relative benefits of using MS-EN will provide capability for rapid screening of wines. However, this technique does not provide the identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.

Analysis of elements in wine using near infrared spectroscopy and partial least squares regression.

The use of visible (VIS) and near infrared spectroscopy (NIRS) to measure the concentration of elements in Australian wines was investigated. Both white (n=32) and red (n=94) wine samples representing a wide range of varieties and regions were analysed by inductively coupled plasma mass spectrometry (ICP-MS) for the concentrations of calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), sodium (Na), sulphur (S), iron (Fe), boron (B) and manganese (Mn). Samples were scanned in transmittance mode (1mm path length) in a monochromator instrument (400-2500nm). The spectra were pre-treated by second derivative and standard normal variate (SNV) prior to developing calibration models using partial least squares (PLS) regression method with cross-validation. The highest coefficients of determination in cross-validation (R(val)(2)) and the lowest errors of cross-validation (SECV) were obtained for Ca (0.90 and 9.80mgL(-1)), Fe (0.86 and 0.65mgL(-1)) and for K (0.89 and 147.6mgL(-1)). Intermediate R(val)(2) (<0.80) and SECV were obtained for the other minerals analysed. The results showed that some macro- and microelements present in wine might be measured by VIS-NIRS spectroscopy.

Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis.

This study outlines the use of mid-infrared (MIR) spectroscopy combined with principal component analysis (PCA) and linear discriminant analysis (LDA) for the varietal classification of commercial red and white table wines. Three red varieties (Cabernet Sauvignon, Shiraz and Merlot) and four white varieties (Chardonnay, Riesling, Sauvignon Blanc and Viognier) were sourced from different wine regions in Australia. Wine samples were scanned in transmission on a FOSS WineScan FT 120 from wave numbers 926 to 5012cm(-1). All samples were sourced from the 2006 vintage and had not been blended with any other variety or wine from other regions. Spectral data were reduced to a small number of principal components (PCs) and LDA was then performed to successfully separate the wines into the different varieties. To test the robustness of the LDA models developed for the red wines, a set of red wines scanned in 2005 were used. Correct classification of over 95% was achieved for the validation set.

Measurement of condensed tannins and dry matter in red grape homogenates using near infrared spectroscopy and partial least squares.

Samples (n = 620) of homogenized red grape berries were analyzed using a visible and near-infrared (NIR) spectrophotometer (400-2500 nm) in reflectance. The spectra and the analytical data were used to develop partial least-squares calibrations to predict dry matter (DM) content and condensed tannins (CT) concentrations. The coefficient of determination in cross-validation and the standard error of cross-validation were 0.92 and 0.83% w/w for DM and 0.86 and 0.46 mg/g epicatechin equivalents for CT, respectively. The standard error in prediction was 1.34% w/w for DM and 0.89 mg/g epicatechin equivalents for CT, respectively. By implementing a NIR spectroscopy method to measure DM and CT in red grape homogenates, we have developed an approach that is suited to large-scale compositional analysis in commercial wine production facilities, as it enables the analysis of large numbers of samples needed to stream batches of fruit. From an economical point of view, the calibration models could be achieved with relatively small data sets. Thus, NIR offers a suitable and efficient tool for the simultaneous measurement of DM and CT in addition to other important parameters in red grape homogenates such as total anthocyanins, total soluble solids, and pH, with minimal sample preparation and low cost.

Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin

A combination of mass spectrometry-based electronic nose (MS e_nose) and chemometrics was explored to classify two Australian white wines according to their varietal origin namely Riesling and unwooded Chardonnay. The MS e_nose data were analysed using principal components analysis (PCA), discriminant partial least squares (DPLS) and linear discriminant analysis (LDA) applied to principal components scores and validated using full cross validation (leave one out). DPLS gave the highest levels of correct classification for both varieties (>90%). LDA classified correctly 73% of unwooded Chardonnay and 82% of Riesling wines. Even though the conventional analysis provides fundamental information about the volatile compounds present in the wine, the MS e_nose method has a series of advantages over conventional analytical techniques due to simplicity of the sample-preparation and reduced time of analysis and might be considered as a more convenient choice for routine process control in an industrial environment. The work reported here is a feasibility study and requires further development with considerably more commercial samples of different varieties. Further studies are needed in order to improve the calibration specificity, accuracy and robustness, and to extend the discrimination to other wine varieties or blends.

Prediction of colour and pH in grapes using a diode array spectrophotometer (400–1100 nm)

One hundred and twenty thawed samples of homogenised and whole frozen grape berries were analysed using a diode array spectrophotometer (400–1100 nm) (CORONA 45VISNIR, Carl Zeiss, Germany). The spectra and the analytical data were used to develop partial least squares calibrations to predict colour and pH in both presentation modes to the instrument. The visible (vis: 400–700 nm), near infrared (NIR: 700–1100 nm) and vis + NIR (400–1100 nm) regions were used to perform the calibrations. Cross validation models for colour and pH on homogenised samples gave a coefficient of determination in validation (R2val) and the root mean square error of cross-validation (RMSECV) of 0.92 and 0.07 mg g−1 for colour, and 0.90 and 0.04 for pH, respectively, using the vis region. Presentation of intact whole grape berries gave R2val and RMSECV values of 0.50 and 0.14 mg g−1 for colour, 0.60 and 0.08 for pH using the NIR region. It was concluded that homogenised samples gave the best calibration statistics. More research needs to be done to improve calibration on whole samples if the technology is to be used for rapid analysis for either on-farm or on-harvester applications.

A brief introduction to multivariate methods in grape and wine analysis

Real-world systems are usually multivariate and hence usually cannot be adequately described by one selected variable without the risk of serious misrepresentation. Analyzing the effect of one variable at a time by analysis of variance techniques can give useful descriptive information, but this will not give specific information about relationships among variables and other important relationships in the entire matrix. Multivariate data analysis was developed in the late 1960s, and used by a number of research groups in analytical and physical organic chemistry due to the introduction of instrumentation giving multivariate responses for each sample analyzed. Development of such methods was also made possible by the availability of computers. Multivariate data analysis involves the use of mathematical and statistical techniques to extract information from complex data sets. The objective of this paper is to briefly describe and illustrate some multivariate data analysis methods used for grape and wine analysis.

The determination of red grape quality parameters using the LOCAL algorithm

In a study of visible (vis) and near infrared (NIR) spectra collected from grape samples representing many growing vintages, varieties and regions, WinISI LOCAL performed better than modified partial least squares in the prediction of anthocyanin and pH. However, both algorithms performed equally well for the prediction of total soluble solids (TSS). Calibrations for anthocyanins and pH relied mainly on the visible wavelengths, but pH calibrations may result from pH effects on the spectral properties of anthocyanin. On the other hand, calibrations for TSS relied mainly on NIR wavelengths. An examination of the LOCAL match sets showed that, in addition to spectral matching, there appeared to be concomitant compositional matching, possibly due to dominant spectral features related to the relevant analyte. Observations imply that calibrations for anthocyanins, pH and TSS in grapes are not restrained by vintage, variety and region. A more important factor in determining a robust, global application may be to ensure that the full concentration range of the analyte is well represented in the calibration database.

Phenolic Compositions of 50 and 30 Year Sequences of Australian Red Wines: The Impact of Wine Age

The phenolic composition of red wine impacts upon the color and mouthfeel and thus quality of the wine. Both of these characteristics differ depending on the age of a wine, with the purple of young wines changing to brick red and the puckering or aggressive astringency softening in older wines. This study investigated the color parameters, tannin concentrations and tannin composition of a 50 year series of Cabernet Sauvignon wines from a commercial label as well as 30 year series of Cabernet Sauvignon and Shiraz wines from a separate commercial label to assess the impact of wine age on phenolic composition and concentration. The wine color density in wines of 40 to 50 years old was around 5 AU compared with 16 AU of wine less than 12 months old, which correlated well with the concentration of non-bleachable pigments and pigmented polymers. Conversely, the anthocyanin concentrations in 10 year old wines were substantially lower than that of recently bottled wines (around 100 mg/L compared with 627 mg/L, respectively), adding further evidence that non-bleachable pigments including pigmented polymers play a much larger role in long-term wine color than anthocyanins. No age-related trend was observed for tannin concentration, indicating that the widely noted softer astringency of older red wines cannot necessarily be directly related to lower concentrations of soluble wine tannin and is potentially a consequence of changes in tannin structure. Wine tannins from older wines were generally larger than tannins from younger wines and showed structural changes consistent with oxidation.