Feasibility study of FT-MIR spectroscopy and PLS-R for the fast determination of anthocyanins in wine

Romera-Fernández, M.; Berrueta, Luis Á.; Garmón-Lobato, Sergio; Gallo, Blanca; Vicente, Francisca; Moreda, J.M.

doi:10.1016/j.talanta.2011.10.045

Cited by 62 publications

(30 citation statements)

References 31 publications

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“…The crossvalidation results for individual anthocyanins are higher in the present study. In another work, malvidin compounds were used to predict anthocyanin content of red wines with FTIR [25] and their validation results (0.84-0.88) are similar to R 2 values presented in Table 3. The wine samples used here covered a wide range of factors such as different geographic regions, grape varieties and harvest years.…”

Section: Resultsmentioning

confidence: 54%

Combination of visible and mid-infrared spectra for the prediction of chemical parameters of wines

Şen

Öztürk

Tokatlı

et al. 2016

Talanta

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a b s t r a c tRapid and environmentally friendly methods for the prediction of chemical compositions have been an interest in the wine industry. The objective of the study was to show the potentials of combined use of visible and mid-infrared (MIR) spectroscopies to improve the prediction of various chemical compounds of wine as opposed to using mid-infrared range only. Wine samples of twelve grape varieties from two harvest years were analyzed. The chemical composition of wine samples was related to MIR and visible spectra using orthogonal partial least square (OPLS) regression technique. The prediction abilities were tested with crossvalidation and independent validation sets. The coefficient of determination of validation (R 2 val ) for anthocyanin compounds of red wines were between 0.76 and 0.90, and that for total phenol content was 0.90. Range of R 2 val for glycerol, glycerol/ethanol ratio, malic acid, o-coumaric acid and°B rix were between 0.77 and 0.96. The spectral ranges that played significant roles in the predictions were also determined. The validations with independent data sets showed that the combination of visible and MIR ranges with multivariate methods improved the prediction of anthocyanin compounds and total phenols; produced comparable results for the rest of the parameters as MIR. This is the first study in the literature that shows the practical use of visible spectra along MIR. The combined use of these spectral ranges with multivariate models can be applied for the rapid, on-line determination of quality parameters and chemical profiles of wines.

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Section: Resultsmentioning

confidence: 54%

Combination of visible and mid-infrared spectra for the prediction of chemical parameters of wines

Şen

Öztürk

Tokatlı

et al. 2016

Talanta

View full text Add to dashboard Cite

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“…As expected, the dominating absorption peaks belonged to the water and ethanol, which were the most abundant components in rice wine. For water, 2 distinctively negative absorption bands were observed at 1500 to 1700 cm −1 and 3000 to 3700 cm −1 related with O–H stretching vibrations (Romera‐Fernández and others ; Patz and others ), the negative absorption might due to the automatic subtraction of the blank that the equipment carried out by using distilled water as reference (Wu and others ). For ethanol, the most characteristic peak was observed at 1045 cm −1 , it was associated with C–O stretch (Shen and others ).…”

Section: Resultsmentioning

confidence: 99%

Use of Attenuated Total Reflectance Mid‐Infrared Spectroscopy for Rapid Prediction of Amino Acids in Chinese Rice Wine

Long

et al. 2015

Journal of Food Science

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The high content of amino acids of Chinese rice wine (CRW), especially essential amino acids makes it a food increasingly demanded by consumers. Rapid detection technique of amino acid content, which is an important quality and function index of CRW, is highly desirable for consumers, producers as well as administrative authorities. In this study, the potential of Fourier transform infrared spectroscopy (FT-IR) as a novel and rapid analytical technique to determine 17 free amino acids in CRW were investigated. Genetic algorithms (GA) and synergy interval partial least squares (SiPLS) were used to select the most efficient spectral variables to improve the prediction precision of the classic partial least squares (PLS) model constructed on the full-spectrum. The results demonstrated that compared with the PLS model using all wavelengths of FT-IR spectra, the prediction precision of model based on the spectral variables selected by GA and SiPLS was significantly improved, especially for arginine and proline. After systemic comparison and discussion, it was found that GA-SiPLS model achieved the best performance, with the correlation coefficient in calibration (R(2) (cal)) higher than 0.80 and the residual predictive deviation higher than 2.00 for all of the free amino acids analyzed in this study. The overall results confirmed that FT-IR combined with efficient variable selection algorithms is a method that may be useful to replace the traditional methods for routine analysis of free amino acids in CRW.

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“…The use of NIR spectroscopy has also been reported for the measurement of several chemical parameters in wine and other alcoholic beverages, such as volatile acidity [89,90], organic acids [91][92][93], glycerol [94,95], reducing sugars [96,97], sulphur dioxide [98], and minerals [99,100]. With more recent developments in instrument design and sample presentation modes such as short path-length transmission cells and attenuated total reflectance modules (ATR), the use of both Fourier transformed mid-infrared (FT-MIR or FTIR) and NIR spectroscopy have been reported by several authors and implemented for the routine analysis of a large number of beer and wine parameters such as alcohol content [101,102], volatile acidity [103], dry extract [104], sugars and acids [105], glycerol [106], anthocyanins [107], polyphenols [108], and amino-nitrogen [109], among others.…”

Section: Spectroscopymentioning

confidence: 99%

The Application of State-of-the-Art Analytic Tools (Biosensors and Spectroscopy) in Beverage and Food Fermentation Process Monitoring

et al. 2017

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Abstract:The production of several agricultural products and foods are linked with fermentation. Traditional methods used to control and monitor the quality of the products and processes are based on the use of simple chemical analysis. However, these methods are time-consuming and do not provide sufficient relevant information to guarantee the chemical changes during the process. Commonly used methods applied in the agriculture and food industries to monitor fermentation are those based on simple or single-point sensors, where only one parameter is measured (e.g., temperature or density). These sensors are used several times per day and are often the only source of data available from which the conditions and rate of fermentation are monitored. In the modern food industry, an ideal method to control and monitor the fermentation process should enable a direct, rapid, precise, and accurate determination of several target compounds, with minimal to no sample preparation or reagent consumption. Here, state-of-the-art advancements in both the application of sensors and analytical tools to monitor beverage and food fermentation processes will be discussed.

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Feasibility study of FT-MIR spectroscopy and PLS-R for the fast determination of anthocyanins in wine

Cited by 62 publications

References 31 publications

Combination of visible and mid-infrared spectra for the prediction of chemical parameters of wines

Combination of visible and mid-infrared spectra for the prediction of chemical parameters of wines

Use of Attenuated Total Reflectance Mid‐Infrared Spectroscopy for Rapid Prediction of Amino Acids in Chinese Rice Wine

The Application of State-of-the-Art Analytic Tools (Biosensors and Spectroscopy) in Beverage and Food Fermentation Process Monitoring

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