M. Gishen

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.

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.

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.

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.

Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine

The aim of this study was to investigate the potential use of a direct headspace-mass spectrometry electronic nose instrument (MS e_nose) combined with chemometrics as rapid, objective and low cost technique to measure aroma properties in Australian Riesling wines. Commercial bottled Riesling wines were analyzed using a MS e_nose instrument and by a sensory panel. The MS e_nose data generated were analyzed using principal components analysis (PCA) and partial least squares (PLS1) regression using full cross validation (leave one out method). Calibration models between MS e_nose data and aroma properties were developed using partial least squares (PLS1) regression, yielding coefficients of correlation in calibration (R) and root mean square error of cross validation of 0.75 (RMSECV: 0.85) for estery, 0.89 (RMSECV: 0.94) for perfume floral, 0.82 (RMSECV: 0.62) for lemon, 0.82 (RMSECV: 0.32) for stewed apple, 0.67 (RMSECV: 0.99) for passion fruit and 0.90 (RMSECV: 0.86) for honey, respectively. The relative benefits of using MS e_nose will provide capability for rapid screening of wines before sensory analysis. However, the basic deficiency of this technique is lack of possible identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.

Effect of both homogenisation and storage on the spectra of red grapes and on the measurement of total anthocyanins, total soluble solids and pH by visual near infrared spectroscopy

The effect of homogenisation and storage on both the visible (Vis) and near infrared (NIR) spectra as well as on the calibration performance for the measurement of total anthocyanins (colour), total soluble solids (TSS) and pH in red grapes were investigated. Homogenates obtained from fresh and previously frozen red grapes (overnight freezing for 24 hours, and after one, three, six and 12 months frozen storage) were scanned in reflectance mode (400–2500 nm) using a monochromator instrument (Foss NIRSystems 6500). Principal component analysis was used to examine the influence of homogeniser type and frozen storage on the spectra. Neither the homogeniser type used nor overnight freezing had visual effects on the spectra. Spectra and analytical data were used to develop partial least squares calibrations to quantify the influence of storage on the measurement of total anthocyanins (colour), TSS and pH. When cross-predicting between fresh and frozen samples, the standard error of prediction was slightly increased when compared with calibrations developed on fresh samples alone. On the other, hand frozen samples were predicted well with the fresh sample calibration for the chemical parameters evaluated. However, although there may be some increases in error, these results suggest that it might be possible to use Vis-NIR calibrations developed on frozen samples alone to measure the concentration of total anthocyanins, TSS and pH in either fresh or frozen samples after appropriate slope and bias correction.

Relationship between wine scores and visible-near-infrared spectra of Australian red wines

Sensory analysis of wine involves the measurement, interpretation and understanding of human responses to the properties perceived by the senses such as sight, smell and taste. The sensory evaluation of wine is often carried out by wine judges, winemakers and technical staff, and allows characterization of the quality of the wine. However, this method is lengthy, expensive, and its results depend on panel training and the specific vocabulary used by the panel. A robust, rapid, unbiased and inexpensive method to assist in quality assessment purposes will therefore be beneficial for the modern wine industry. This study aims to investigate the relationship between sensory analysis, visible (VIS) and near-infrared (NIR) spectroscopy to assess sensory properties of commercial Australian wine varieties. For the purposes of this study 118 red wine samples (Cabernet Sauvignon, Shiraz, Pinot Noir, Tempranillo, Nebbiolo and blends) graded by a panel of experienced tasters and scored according to the Australian wine show system were scanned in transmission in the VIS and NIR range (400–2,500nm). Partial least squares regression models were developed between the overall score given by the judges and the combined VIS–NIR spectra, using full cross validation (leave-one-out method). The results showed that NIR spectroscopy was able to predict wine quality scores in red wine samples (R = 0.61 and standard error of prediction of 0.81). The practical implication of this study is that instrumental methods such as VIS–NIR spectroscopy can be used to complement sensory analysis and can facilitate the task at early stages of product development, making high-throughput screening of novel products feasible or maintaining the consistency of the product.

A Review of the State of the Art, Limitations, and Perspectives of Infrared Spectroscopy for the Analysis of Wine Grapes, Must, and Grapevine Tissue

Abstract As a fast and easy-to-operate technique, infrared (IR) spectroscopy has gained wide industrial acceptance for routine wine analysis. Considering the continuing improvements in hardware and software design and the analytical requirements of real-time or multiparametric analysis by the modern grape and wine industry, it is anticipated that in the near future IR spectroscopy will progressively become a routine method for process monitoring and process control in different stages of grape and wine production. This review highlights recent developments and applications of IR spectroscopy (near- and mid-infrared) to measure compositional parameters in wine grapes, grape juice, and grapevine tissues (e.g., leaves, stems, grapevine wood). In addition, some critical aspects and limitations in instrument availability, type of application, and overall understanding of the technology, which can be barriers for adoption of IR technologies by the grape and wine industry, will be discussed.

Combining near infrared spectroscopy and multivariate analysis as a tool to differentiate different strains of Saccharomyces cerevisiae : A metabolomic study

Near‐infrared (NIR) spectroscopy has gained wide acceptance within the food and agriculture industries as a rapid analytical tool. NIR spectroscopy offers the advantage of rapid, non‐destructive analysis and routine operation is simple and opens the possibility of using spectra to obtain the ‘fingerprint’ of a sample. The aim of this study was to explore the potential of combining visible (VIS) and near‐infrared (NIR) spectroscopy, together with multivariate analysis, in establishing the function of genes, by investigating the metabolic profiles produced by Saccharomyces cerevisiae deletion strains sourced from the EUROSCARF yeast collection. Spectra (400–2500 nm) were acquired with a FOSS NIRSystems6500 (Foss NIRSystems), in transmittance mode. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used in order to visualize graphically the relative differences and similarities of yeast deletion strains. VIS and NIR spectroscopy showed great promise as a screening tool for both discriminating between yeast strains and grouping strains with deletions in genes that disturb similar metabolic pathways. These results indicate that the methods may be useful in defining the function of genes that produce no obvious phenotype. Copyright