Preliminary study on the application of visible–near infrared spectroscopy and chemometrics to classify Riesling wines from different countries

Visible (VIS) and near infrared (NIR) spectroscopy combined with chemometrics was used in an attempt to classify commercial Riesling wines from different countries (Australia, New Zealand, France and Germany). Commercial Riesling wines (n = 50) were scanned in the VIS and NIR regions (400–2500 nm) in a monochromator instrument, in transmission mode. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and stepwise linear discriminant analysis (SLDA) based on PCA scores were used to classify Riesling wines according to their country of origin. Full cross validation (leave-one-out) was used as the validation method when classification models were developed. PLS-DA models correctly classified 97.5%, 80% and 70.5% of the Australian, New Zealand and European (France and Germany) Riesling wines, respectively. SLDA calibration models correctly classified 86%, 67%, 67% and 87.5% of the Australian, New Zealand, French and German Riesling wines, respectively. These results demonstrated that the VIS and NIR spectra contain information that when used with chemometrics allow discrimination between wines from different countries. To further validate the ability of VIS–NIR to classify white wine samples, a larger sample set will be required.     

Effect of microwave heating on the near infrared spectra and on the prediction accuracy of chemical parameters in red grape homogenates

This study reports the effect of microwaving on the chemical composition [pH, total soluble solids (TSS), dry matter (DM) and total anthocyanins extraction], and the visible (VIS) and (NIR) spectra of red grape homogenates. It was observed that microwaving red grape homogenates prior to analysis improved the NIR calibrations for total anthocyanins (SECV: 0.21?C0.13 mg g^?1) and TSS (SECV: 0.89?C0.54 °Brix), however no improvements in the NIR calibrations for DM were observed. Microwaving red grape samples prior to NIR scanning also caused an increased in absorbance for samples heated for up to 3 min, particularly in those wavelengths associated with water (1400 nm and 1930 nm). The practical implication of this study is that microwaving of red grape samples prior to scanning did not improve the NIR calibration statistics for the most common chemical parameters measured in red grapes.     

Determination of 13 Phenolic Compounds in Rice Wine by High-Performance Liquid Chromatography

Rice wines are widely consumed by the general public in Asian countries, while comprehensive studies focused on the individual phenolic compounds in rice wines are limited. A rapid method for simultaneous determination of 13 phenolic compounds in rice wines by high-performance liquid chromatography (HPLC) was developed and validated, and the phenolic compounds in commercial rice wine samples (Chinese rice wine, Japanese sake, and Korean makgeolli) were determined in this paper. The identified compounds contained gallic acid (GA), protocatechuic acid (PRCA), vanillic acid (VA), syringic acid (SRA), caffeic acid (CA), ferulic acid (FA), p-coumaric acid (pCA), sinapic acid (SA), chlorogenic acid (CHA), (+)-catechin (CAT), (?)-epicatechin (EPI), quercetin (QUE), and rutin (RUT). Phenolics were separated with a C18 reversed-phase column at 38 °C by gradient elution using 3 % acetic acid aqueous solution (solvent A) and acetonitrile (solvent B) (0 min, 5 % B; 5 min, 8 % B; 10 min, 15 % B; 20 min, 25 % B; and 25 min, 5 % B) as the mobile phase at 280 nm with flow rate of 1.0 mL min^?1. With direct injection of rice wine samples, the chromatograms of all analytes were observed within 20 min, all calibration curves were linear (R ²?>?0.995) within the range, limits of detection (LOD) ranged from 0.02 to 0.06 μg mL^?1, and good recoveries (88.07–106.80 %) and precision (relative standard deviation (RSD)?<?5.36 % ) were obtained for all compounds. This method was applied to quantify phenolic compounds in commercial rice wine samples (Chinese rice wine, Japanese sake, and Korean makgeolli), and good separation peaks were observed and catechin was the predominant phenolic in the samples. The average values of total phenolic contents of the three groups of rice wine were significantly different (p?<?0.01). In conclusion, this procedure can be used to determine the phenolic compounds in various types of rice wines, as well as to characterize and differentiate rice wine samples.     

Prediction of non-recoverable collapse in Eucalyptus globulus from near infrared scanning of radial wood samples

Near infrared (NIR) spectroscopy calibrations was used to predict radial profiles of cellulose content, wood density, cellulose microfibril angle (MFA) and modulus of elasticity (MOE) in 20-year-old plantation Eucalyptus globulus to identify non-recoverable collapse zones associated with tension wood. Radial (cambium-to-pith) wood cores were extracted at a height of 1.0 m from trees selected to represent a range of silvicultural treatments. NIR spectra were measured at 1 mm intervals along the radial-longitudinal face of each core after drying to 12 % equilibrium moisture content (EMC) at 40 °C. Tangential shrinkage was measured at eight points along each core, following steam reconditioning and re-drying to 12 % EMC. Additional cores from 20 of the sample trees were collected. Radial profiles of density, MFA and MOE were obtained for wood strips prepared from these cores, using the SilviScan 3 wood assessment system. Trait profiles were matched to radial NIR scans of these cores, enabling the development of NIR calibrations using partial least squares (PLS) regression. These, and an existing NIR calibration for cellulose content, were used to predict the radial profiles of the four wood properties for the first set of cores. Predicted wood properties were then related to actual tangential shrinkage measurements and the occurrence of visible bands of non-recoverable collapse. A regression model was developed to reliably predict regions of non-recoverable collapse from NIR-predicted cellulose content and MOE. Micrography of stained wood sections indicated that the collapse was caused by the presence of tension wood.     

Simultaneous Determination of Phenolic Acids and Scopoletin in Brandies Using Synchronous Fluorescence Spectrometry Coupled with Partial Least Squares

Brandy, a spirit drink produced from wine (grape), is rich in phenolic acids due to its maturation in wooden barrels. Phenolic acids play a significant role in defining the sensorial characteristics of wines and brandies, and therefore, it is very useful to determine them. Synchronous fluorescence spectra of mixtures containing phenolic acids (gallic, vanillic, syringic and ferulic) and scopoletin have been used for the determination of these compounds by partial least squares (PLS)2. Synchronous fluorescence spectra were collected by simultaneously scanning the excitation and emission monochromator in the excitation wavelength range 200–500 nm, with constant wavelength difference 100 nm between them. The leave-one-out cross-validation method was used to select the optimum number of five PLS2 components (latent variables). The PLS2 model captured for 100 % of variance in the spectral block, and it accounted for 99.34 % of variance in the concentration block. The performance of the model was evaluated by means of root mean square error of cross-validation, root mean square error of prediction and coefficient of determination. The best model was used for the determination of the above-mentioned compounds in brandy samples at concentration levels 2–74 mg L^?1 for phenolic acids and 0.06–0.43 mg L^?1 for scopoletin. The PLS2 results were found to be in good agreement with those obtained by HPLC method.     

Discrimination between Chinese rice wines of different geographical origins by NIRS and AAS

The feasibility of near infrared spectroscopy (NIRS) for discrimination between Chinese rice wine of different geographical origins (Shaoxing and Jiashan, China) is presented in this research. NIR spectra were collected in transmission mode in the wavelength range of 800–2500 nm. Qualitative analysis models were developed based on partial least squares regression (PLSR). The prediction performance of calibration models in different wavelength range was also investigated. The best models gave a 100% classification of wines of the two geographical origins in the range of 1300–1650 nm. The content of trace metals (potassium, magnesium, zinc, and iron) was also investigated to classify wines of the two categories by atomic absorption spectroscopy (AAS). The AAS results were in agreement with NIRS, with 100% classification for wines of the two categories. In addition, the correlation between NIRS and AAS was also investigated by PLSR. Potassium and magnesium were well predicted by quantitative models based on NIR spectra and AAS data. The correlation coefficient of calibration (R _cal) for potassium and magnesium were 0.958 and 0.885, respectively, and the correlation coefficient of validation (R _val) were 0.861 and 0.700, respectively. The results demonstrated that NIRS technique could be used as a rapid method for classification of geographical origin of Chinese rice wine, and AAS could be used as an alternative technique or to validate the discrimination results.     

Effects of Vinification Techniques Combined with UV‐C Irradiation on Phenolic Contents of Red Wines

Red wines are typically high in phenolic and antioxidant capacity and both of which can be increased by vinification techniques. This study employed 3 vinification techniques to assess the increase in phenolic compounds and antioxidant capacity. Wines were obtained from Bo?azkere grape cultivar by techniques of classical maceration, cold maceration combined with ultraviolet light (UV) irradiation, and thermovinification combined with UV irradiation and changes in phenolic contents were examined. Total phenolic and anthocyanin contents and trolox equivalent antioxidant capacity of wines were measured spectrophotometrically and phenolic contents (+)‐catechin, (–)‐epicatechin, rutin, quercetin, trans‐resveratrol, and cis‐resveratrol were measured by High Pressure Liquid Chromatography with Diode Array Detection (HPLC‐DAD). As a result of the study, the highest phenolic content except for quercetin was measured in the wines obtained by thermovinification combined with UV irradiation. We demonstrated that the highest phenolic compounds with health effect, total phenolic compounds, total anthocyanin, and antioxidant activity were obtained from thermovinification with UV‐C treatment than classical wine making.     

Employment of near infrared spectroscopy to determine oak volatile compounds and ethylphenols in aged red wines

The aim of this work was to study the ability of NIR spectroscopy to determine oak volatile compounds and ethylphenols levels in aged red wines. For this purpose 510 wines aged with different storage time and in different oak barrel types were analyzed. Calibration models were developed from SBSE-GC–MS and NIR data using partial least squares (PLS) regression. In order to validate the calibration, full cross validation was employed. Results showed that the calibration statistics were very good (R² > 0.86) for all the compounds studied. In wines aged in French and in American and French oak barrels, and in “reserva” and “gran reserva” wines, the residual predictive deviation (RPD) obtained was higher than 1.5 in all the compounds and it was higher than 2 in some of the cases. In conclusion, near infrared spectroscopy can be used as a rapid tool to determine oak volatile compounds and ethylphenols in aged red wines.     

Interactions of phenolic and volatile compounds with yeast lees,commercial yeast derivatives and non toasted chips in model solutions and young red wines

Ageing of wines on lees, the use of commercial yeast derivative products and the addition of oak chips to wine permit the release of different compounds such as mannoproteins and polysaccharides into wines during yeast autolysis. These compounds released can interact with phenolic compounds and/or aromatic compounds, also modifying wine sensory perception. For that reason, the aim of this work was to evaluate the interaction of phenolic and volatile compounds of wines with yeast lees, non-toasted oak wood chips and different commercial yeast derivative preparations in model wine solutions and in a real red wine. The results found in this study have shown that most of the phenolic and volatile compounds studied are adsorbed by wood and bound by lees in model wine solutions. However, in the model wines in general, the commercial yeast derivative products studied only interacted with the volatile compounds but not with the phenolic compounds. The adsorption of the phenolic compounds occurred in the first 15 days of treatment, remaining constant for 2 months; however, in the case of volatile compounds, these compounds initially displayed a retention effect, but after 30–60 days, the release of the previously bound compounds was instigated. The adsorption effect on the phenolic and volatile compounds in the model wine solution was not always the same as in the red wine studied, which highlights the important presence of other wine compounds in these interactions.     

Effect of variety, vintage and winery on the prediction by visible and near infrared spectroscopy of the concentration of glycosylated compounds (G-G) in white grape juice

The use of visible (Vis) and near infrared (NIR) spectroscopy was explored as a rapid, simple and low cost measurement of the concentration of total glycosylated compounds in white grape juice. The effects of variety (Chardonnay, Riesling and Sauvignon Blanc), winery and vintage (2004 to 2006) on the Vis-NIR spectra were also examined. Juice samples from South Australian wineries were scanned in transmittance mode on a FOSS NIRSystems6500 instrument and subjected to laboratory analyses for the measurement of the concentration of total glycosylated compounds (G-G), total soluble solids (TSS), pH and total phenolics (TP). Partial least squares (PLS) regression method was used to relate the G-G reference data to the Vis-NIR spectra. For all samples, PLS regression resulted in a coefficient of determination in calibration ( R ²_cal) and standard error of cross validation (SECV) of 0.82 and 49.15 μM, respectively. Splitting the sample set by variety, winery or vintage improved the PLS calibrations for the variety sets. The results show that Vis-NIR spectroscopy has potential for use as a rapid, semi-quantitative technique to predict G-G concentration in white grape juices as 'low', 'medium' or 'high'. This method will be valuable when taking decisions at the winery during vintage to allocate juices according to their aroma potential. Further studies are in progress to validate the robustness and accuracy of the calibration models.     

Shortwave-near infrared spectroscopy for determination of reducing sugar content during grape ripening,winemaking, and aging of white and red wines

The feasibility of near infrared (NIR) spectroscopy for predicting reducing sugar content during grape ripening, winemaking, and aging was assessed. NIR calibration models were developed using a set of 146 samples scanned in a quartz flow cell with a 50 mm path length in the NIR region (800–1050 nm), in a fiber spectrometer system working in transmission mode. Principal component analysis (PCA), partial least squares (PLS), and multiple linear (MLR) regressions were used to interpret spectra and to develop calibrations for reducing sugar content in grape, must, and wine. The PLS model based on the full spectral range (800–1050 nm), yielded a determination coefficient (r²) of 0.98, a standard error of cross validation (SECV) of 13.62 g/l and a root mean square error of cross validation (RMSECV) of 13.58 g/l. The mathematical model was tested with independent validation samples (n = 48); the resulting values for r², the standard error of prediction (SEP) and the root mean square error of prediction (RMSEP) for the same parameter were 0.98, 10.84, and 12.20 g/l, respectively. The loading weights of latent variables from the PLS model were used to identify sensitive wavelengths. To assess their suitability, MLR models were built using these wavelengths. Wavelength significance was analyzed by ANOVA, and four wavelengths (909, 951, 961, and 975 nm) were selected, setting statistical significance at the 99% confidence level. The MLR model yielded acceptable results for r² (0.92), SEP (19.97 g/l) and RMSEP (20.51 g/l). The results suggest that NIR spectroscopy is a promising technique for predicting reducing sugar content during grape ripening, as well as during the fermentation and aging of white and red wines. Individual fingerprint wavelengths strongly associated with reducing sugar content could be used to enhance the efficacy of this simple, efficient and low-cost instrument.     

基于偏最小二乘(PLS)法白酒中乙醇含量的近红外检测

将近红外光谱与偏最小二乘法相结合,对白酒中乙醇含量进行快速准确检测。研究了标准溶液的近红外吸收光谱和一阶导数光谱,采用偏最小二乘法建立校正模型,选择了最佳主成分数,并对实际酒样中乙醇进行预测,得到了比较满意的结果。     

Measurement of Soluble Solid Contents and pH of White Vinegars Using VIS/NIR Spectroscopy and Least Squares Support Vector Machine

Visible and near-infrared (VIS/NIR) spectroscopy combined with least squares support vector machine (LS-SVM) was employed to determine soluble solid contents (SSC) and pH of white vinegars. Three hundred twenty vinegar samples were distributed into a calibration set (240 samples) and a validation set (80 samples). Partial least squares (PLS) analysis was implemented for the regression model and extraction of latent variables (LVs). The selected LVs were used as LS-SVM input variables. Finally, LS-SVM models with radial basis function kernel were achieved with the comparison of PLS models. The results indicated that LS-SVM outperformed PLS models. The correlation coefficient (r), root mean square error of prediction, bias, and residual prediction deviation for the validation set were 0.988, 0.207°Brix, 0.183, and 6.4 for SSC whereas these were 0.988, 0.041, ?0.002, and 6.5 for pH, respectively. The overall results indicated that VIS/NIR spectroscopy and LS-SVM could be used as a rapid alternative method for the prediction of SSC and pH of white vinegars, and the results could be helpful for the fermentation process and quality control monitoring of white vinegar production.     

Classification and characterisation of Spanish red wines according to their appellation of origin based on chromatographic profiles and chemometric data analysis

Chromatographic profiles of wines have been used as a fingerprint for the discrimination of Spanish wines based on oenological practices. In order to extract information of different families of phenolic compounds, profiles of different UV-vis absorption wavelengths (280, 310, 370 and 520nm) and fluorescence (ex=260nm; em=360nm) were analysed. A total of thirteen phenolic compounds which allowed the discrimination of wines of three different Spanish appellations (Penedes, Rioja and Ribera del Duero) were selected by means of principal component analysis (PCA). Afterwards, these compounds were used to build partial least squares discriminant analysis (PLS1-DA and PLS2-DA) models which allowed the discrimination of wines according to their appellation with classification rates for independent test sets higher than 96% and 93% for PLS1-DA and PLS2-DA models respectively. Finally, characteristic compounds of each appellation were tentatively identified by means of liquid chromatography-mass spectrometry (LC-MS) analysis. Thus, ten out of thirteen compounds (i.e., gallic acid for Penedes, trans-coumaroyltartaric and trans-caffeoyltartaric acids for Rioja and myricetin for Ribera del Duero wines) have been proposed.     

Winery Trial on Application of Pulsed Electric Fields for Improving Vinification of Garnacha Grapes

The potential of pulsed electric fields (PEF) to improve polyphenol extraction during winemaking was investigated in a winery trial. Four thousand five hundred kilograms of Garnacha grapes were treated with PEF (4.3 kV/cm, 60 μs) at a flow of 1,900 kg/h using a collinear treatment chamber. Wine obtained from PEF-treated grapes with a maceration time of 7 days was compared with wines obtained from untreated and PEF-treated grapes with the current maceration time (14 days) used by the winery. After 7 days of maceration, the color intensity, anthocyanin content, and polyphenol index in the tank containing grapes treated by PEF were 12.5, 25, and 23.5 % higher, respectively, than in the tank containing untreated grapes. However, after 14 days of maceration, no significant differences were observed between the control wine and the wine obtained from grapes treated by PEF for these three indices. An HPLC analysis indicated that the concentrations of major individual phenolic compounds were similar among the three wines at bottling. A sensory analysis revealed that the wine obtained from PEF-treated grapes macerated for 7 days was significantly preferable to the other two wines.     

Grape and wine analysis - enhancing the power of spectroscopy with chemometrics.

Spectroscopic techniques offer the potential to simplify and reduce analytical times for a range of grape and wine analytes. It is this aspect, together with the ability to simultaneously measure several analytes, which was the impetus for developing spectroscopic methods. The Australian Wine Research Institute (AWRI) has long used spectroscopic analysis of wines in the ultraviolet (UV) and visible (Vis) wavelengths, and since 1998 has been investigating applications of spectroscopic techniques in the near infrared (NIR) and mid-infrared (MIR) wavelength regions of the electromagnetic spectrum for the rapid analysis and quality control of both grapes and wine by the Australian wine industry. This paper reviews the use of several spectroscopic techniques, including NIR, MIR, and Vis, combined with chemometrics, to assess grape and wine composition in the Australian wine industry. The achievements, current research, and proposed further applications of different spectroscopic techniques are discussed in studies into the assessments of red grape composition and of fungal diseases in grapes, monitoring phenolic compounds during red wine fermentations, quality grading of red, white and fortified wine styles, monitoring wine distillation processes, and yeast strain classification.     

Discrimination Between Shaoxing Wines and Other Chinese Rice Wines by Near-Infrared Spectroscopy and Chemometrics

Shaoxing rice wine (also called Shaoxing wine) is the most well-known Chinese rice wine in China. The common fraudulent practice in the commercialization of Chinese rice wine is to sell wines from different geographical origins under the denomination of Shaoxing rice wine. In this study, the use of near-infrared (NIR) spectroscopy combined with chemometrics as a rapid tool for the discrimination of Chinese rice wine from three geographical origins (“Fujian”, “non-Shaoxing”, “Shaoxing”) has been preliminarily investigated. NIR spectra were collected in transmission mode in the wavelength range of 800–2,500 nm. Discriminant models were developed by principal component analysis (PCA), discriminant analysis (DA), and discriminant partial least-squares analysis (DPLS). The chemical properties of Chinese rice wine were also investigated to find out the difference between samples from three varied origins. The results showed that good classification could be obtained after spectral pre-treatment. The percentage of samples correctly classified by both DA and DPLS methods in calibration and validation set was 97.2% and 100%, respectively. The results demonstrated that NIR could be used as a simple and rapid technique to distinguish Shaoxing wines from non-Shaoxing wines and Fujian wines. To further validate the ability of NIR spectroscopy, more samples should be incorporated to build a more robust model.     

Simultaneous determination of ketoacids and dicarbonyl compounds, key Maillard intermediates on the generation of aged wine aroma

ABSTRACT:  The aim of this work was the simultaneous determination of both ketoacids and dicarbonyl compounds in wine. To detect ketoacid compounds in wine, a method based on the quinoxaline derivatives by the reaction with diaminobenzene, currently employed to detect α-dicarbonyl compounds, was developed. The quinoxaline derivatives were detected by RP-HPLC with UV detection, which allows the determination of the major dicarbonyl compounds in wine: glyoxal, methylglyoxal, diacetyl and pentane-2,6-dione, and the quinoxaline/quinoxalinol derivatives of α-keto-γ-(methylthio)butyric acid and β-phenylpyruvic acid (intermediate ketoacid compounds of methional and phenylacetaldehyde) were simultaneously detected by a fluorescence detector. The identification was performed by comparison with standards and also by using LC-MSMS. The levels found in 15 wines analyzed (white wines, Madeira wines, and Port wines) diverge according to the type and the age of the wine. The ketoacid compounds ranged from 0.2 to 5.7 mg/L for α-keto-γ-(methylthio)butyric acid and 0.1 to 9.6 mg/L for β-phenylpyruvic acid. The quantities observed for dicarbonyl compounds were similar to those already reported.     

Using Wavelet Textural Features of Visible and Near Infrared Hyperspectral Image to Differentiate Between Fresh and Frozen–Thawed Pork

In this study, wavelet textural analysis was applied to hyperspectral images in the visible and near-infrared (VIS/NIR) region (400–1,000 nm) for differentiation between fresh and frozen–thawed pork. The spectral data of acquired hyperspectral images were analyzed using partial least squares (PLS) regression and five wavelengths (462, 488, 611, 629, and 678 nm) were selected as the feature wavelengths by the regression coefficients from the PLS model. The fourth-order daubechies wavelet (“db4”) was used to serve as the wavelet mother function for wavelet textural extraction of the feature images at the above selected feature wavelengths with the wavelet decomposition level from 1 to 4. Four textural features were calculated in the horizontal, vertical, and diagonal orientations at each level. Forty-eight textural features were extracted from each feature image and used to differentiate between fresh and frozen–thawed pork samples by least-squares support vector machine (LS-SVM) model. Wavelet texture extracted from all five feature images at first decomposition level was identified as optimal wavelet texture combination, resulting in the highest classification accuracy for the LS-SVM models (98.48 % for the training set and 93.18 % for the testing set). Based on the texture combination, the quality attributes of pork meat could be predicted with correlation coefficients of calibration (r _c ) of 0.982 and 0.913, and correlation coefficients of prediction (r _p ) of 0.845 and 0.711 for pH and thawing loss, respectively. The results showed the possibility of developing a fast and reliable hyperspectral system for discrimination between fresh and frozen–thawed pork samples based on wavelet texture in the VIS/NIR wavelength range.     

Prediction of red wine colour and phenolic parameters from the analysis of its grape extract

Herein, the phenolic composition and colour attributes of red grapes extracts (obtained with a fast methodology) were correlated with those of their corresponding wines to predict the final quality properties of wines. The phenolic parameters were evaluated as total phenolic compounds (TPC), total anthocyanins (TA) and total condensed tannins (TCT), whereas the chromatic parameters were evaluated as colour intensity (CI), tonality (To), and the percentages of yellow, red and blue tones. All of them were determined by usual UV–Vis spectrophotometric methods. To get robust models, grapes of five red varieties were collected at three different ripening stages throughout the 2009 vintage. Good correlations between the results from grapes and wines were obtained, showing high regression coefficients and low prediction errors for TPC (R² = 0.929, RMSE = 5.99%), TA (R² = 0.953, RMSE = 7.23%) and CI (R² = 0.954, RMSE = 7.58), concluding that these wine phenolic properties can be predicted reliably from the extracts obtained with an optimised fast extraction method from grapes on the ripening controls along the maturity process.