Recent trends in quality control, discrimination and authentication of alcoholic beverages using nondestructive instrumental techniques

[1]  Zou Xiaobo,et al.  In situ prediction of phenolic compounds in puff dried Ziziphus jujuba Mill. using hand-held spectral analytical system. , 2020, Food chemistry.

[2]  Zou Xiaobo,et al.  Rapid Screening of Phenolic Compounds from Wild Lycium ruthenicum Murr. Using Portable near-Infrared (NIR) Spectroscopy Coupled Multivariate Analysis , 2020 .

[3]  A. Cassano,et al.  Membrane separation processes for the extraction and purification of steviol glycosides: an overview , 2020, Critical reviews in food science and nutrition.

[4]  O. Busto,et al.  ATR-MIR spectroscopy and multivariate analysis in alcoholic fermentation monitoring and lactic acid bacteria spoilage detection , 2020 .

[5]  Quansheng Chen,et al.  An Overview on the Applications of Typical Non-linear Algorithms Coupled With NIR Spectroscopy in Food Analysis , 2020, Food Engineering Reviews.

[6]  Wenli Liu,et al.  Comparison of fermentation behaviors and properties of raspberry wines by spontaneous and controlled alcoholic fermentations. , 2020, Food research international.

[7]  P. Oliveri,et al.  Prediction of quality parameters in straw wine by means of FT-IR spectroscopy combined with multivariate data processing. , 2020, Food chemistry.

[8]  Zou Xiaobo,et al.  Recent Progress in Rapid Analyses of Vitamins, Phenolic, and Volatile Compounds in Foods Using Vibrational Spectroscopy Combined with Chemometrics: a Review , 2019, Food Analytical Methods.

[9]  Flaminia Cesare Marincola,et al.  Use of NMR applications to tackle future food fraud issues , 2019, Trends in Food Science & Technology.

[10]  A. Figoli,et al.  Chemical and bio-chemical reactions assisted by pervaporation technology , 2019, Critical reviews in biotechnology.

[11]  J. Barin,et al.  Flow thermal infrared enthalpimetry: Rapid and inexpensive determination of the alcohol content of distilled beverages. , 2019, Talanta.

[12]  R. Castro‐Muñoz,et al.  Pervaporation: The emerging technique for extracting aroma compounds from food systems , 2019, Journal of Food Engineering.

[13]  Zou Xiaobo,et al.  Total polyphenol quantitation using integrated NIR and MIR spectroscopy: A case study of Chinese dates (Ziziphus jujuba). , 2019, Phytochemical analysis : PCA.

[14]  Eric Ziemons,et al.  Vibrational spectroscopy in analysis of pharmaceuticals: Critical review of innovative portable and handheld NIR and Raman spectrophotometers , 2019, TrAC Trends in Analytical Chemistry.

[15]  Zong Tan,et al.  Detection of lethal fake liquors using digitally labelled gas-phase Fourier transform infrared spectroscopy , 2019, Spectroscopy Letters.

[16]  R. Castro‐Muñoz.  Pervaporation-based membrane processes for the production of non-alcoholic beverages , 2019, Journal of Food Science and Technology.

[17]  Senem Kamiloglu.  Authenticity and traceability in beverages. , 2019, Food chemistry.

[18]  Zou Xiaobo,et al.  NIR Spectroscopy Coupled Chemometric Algorithms for Rapid Antioxidants Activity Assessment of Chinese Dates (Zizyphus Jujuba Mill.) , 2019, International Journal of Food Engineering.

[19]  Zhenbo Wei,et al.  Application of the voltammetric electronic tongue based on nanocomposite modified electrodes for identifying rice wines of different geographical origins. , 2019, Analytica chimica acta.

[20]  Daniel Cozzolino,et al.  Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables: A review , 2019, Postharvest Biology and Technology.

[21]  L. Pezza,et al.  Discrimination of Brazilian lager beer by 1H NMR spectroscopy combined with chemometrics. , 2019, Food chemistry.

[22]  R. Sharma,et al.  Classification of illicit liquors based on their geographic origin using Attenuated total reflectance (ATR) - Fourier transform infrared (FT-IR) spectroscopy and chemometrics. , 2019, Forensic science international.

[23]  D. Huo,et al.  A nanophase material and organic dye modified colorimetric sensor array for the discrimination of baijiu , 2018 .

[24]  Leqian Hu,et al.  Rapid detection of three quality parameters and classification of wine based on Vis-NIR spectroscopy with wavelength selection by ACO and CARS algorithms. , 2018, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[25]  Zou Xiaobo,et al.  Colorimetric sensor arrays based on chemo-responsive dyes for food odor visualization , 2018, Trends in Food Science & Technology.

[26]  Jon R. Askim,et al.  The Optoelectronic Nose: Colorimetric and Fluorometric Sensor Arrays. , 2018, Chemical reviews.

[27]  W. Wróblewski,et al.  Hybrid Electronic Tongue as a Tool for the Monitoring of Wine Fermentation and Storage Process , 2018 .

[28]  Zou Xiaobo,et al.  Near infrared spectroscopy coupled with chemometric algorithms for predicting chemical components in black goji berries (Lycium ruthenicum Murr.) , 2018, Journal of Near Infrared Spectroscopy.

[29]  Roberto Paolesse,et al.  Electronic Tongue for Brand Uniformity Control: A Case Study of Apulian Red Wines Recognition and Defects Evaluation † , 2018, Sensors.

[30]  J. Lopes,et al.  Raman spectroscopy for wine analyses: A comparison with near and mid infrared spectroscopy. , 2018, Talanta.

[31]  Zheng Li,et al.  Colorimetric sensor arrays: development and application to art conservation , 2018, Journal of the American Institute for Conservation.

[32]  Quansheng Chen,et al.  Prediction of amino acids, caffeine, theaflavins and water extract in black tea using FT-NIR spectroscopy coupled chemometrics algorithms , 2018 .

[33]  P. Koczoń,et al.  The application of FT-IR spectroscopy in discrimination of differently originated and aged whisky , 2018, European Food Research and Technology.

[34]  Zou Xiaobo,et al.  Near-infrared spectroscopy coupled chemometric algorithms for prediction of antioxidant activity of black goji berries (Lycium ruthenicum Murr.) , 2018, Journal of Food Measurement and Characterization.

[35]  D P Mesquita,et al.  New PLS analysis approach to wine volatile compounds characterization by near infrared spectroscopy (NIR). , 2018, Food chemistry.

[36]  D. Cozzolino,et al.  Unfrazzled by Fizziness: Identification of Beers Using Attenuated Total Reflectance Mid-infrared Spectroscopy and Multivariate Analysis , 2018, Food Analytical Methods.

[37]  I. Feher,et al.  Wine discrimination based on chemometric analysis of untargeted markers using FT-Raman spectroscopy , 2018 .

[38]  Lujia Han,et al.  Analytical Raman spectroscopic study for discriminant analysis of different animal-derived feedstuff: Understanding the high correlation between Raman spectroscopy and lipid characteristics. , 2018, Food chemistry.

[39]  O. G. Meza-Márquez,et al.  FT-MIR spectroscopy and multivariate analysis for determination of bioactive compounds and antioxidant capacity in Cabernet Sauvignon wines , 2018 .

[40]  Jun Wang,et al.  Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform , 2017, Sensors.

[41]  Zhixi Li,et al.  Evaluation of antioxidant capacity and flavor profile change of pomegranate wine during fermentation and aging process. , 2017, Food chemistry.

[42]  M. Holmes,et al.  A rapid and nondestructive method to determine the distribution map of protein, carbohydrate and sialic acid on Edible bird's nest by hyper-spectral imaging and chemometrics. , 2017, Food chemistry.

[43]  Márcio Talhavini,et al.  Discrimination of whisky brands and counterfeit identification by UV-Vis spectroscopy and multivariate data analysis. , 2017, Food chemistry.

[44]  Zou Xiaobo,et al.  Rapid prediction of phenolic compounds and antioxidant activity of Sudanese honey using Raman and Fourier transform infrared (FT-IR) spectroscopy. , 2017, Food chemistry.

[45]  Yan Shi,et al.  Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose , 2017, Sensors.

[46]  Mark A Thornton,et al.  Discrimination of wine lactic acid bacteria by Raman spectroscopy , 2017, Journal of Industrial Microbiology & Biotechnology.

[47]  Bhagwan Singh Chandravanshi,et al.  Non-destructive determination of ethanol levels in fermented alcoholic beverages using Fourier transform mid-infrared spectroscopy , 2017, Chemistry Central Journal.

[48]  J. Kiefer,et al.  Analysis of single malt Scotch whisky using Raman spectroscopy , 2017 .

[49]  Cecilia Jiménez-Jorquera,et al.  Portable Electronic Tongue Based on Microsensors for the Analysis of Cava Wines , 2016, Sensors.

[50]  Tomasz Dymerski,et al.  Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy , 2016, Sensors.

[51]  Ruedi Aebersold,et al.  Mass-spectrometric exploration of proteome structure and function , 2016, Nature.

[52]  Gurvinder Singh Bumbrah,et al.  Raman spectroscopy – Basic principle, instrumentation and selected applications for the characterization of drugs of abuse , 2016 .

[53]  Zou Xiaobo,et al.  Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques. , 2016, Food chemistry.

[54]  A. Waterhouse,et al.  Understanding Wine Chemistry , 2016 .

[55]  Jun Wang,et al.  Determination of the flavours and marked ages of rice wines using a taste sensing system combined with the Weber–Fechner law and chemometric methods , 2016 .

[56]  Ilda Caldeira,et al.  FTIR-ATR spectroscopy applied to quality control of grape-derived spirits. , 2016, Food chemistry.

[57]  Byoung-Kwan Cho,et al.  Application of Fourier transform-mid infrared reflectance spectroscopy for monitoring Korean traditional rice wine ‘Makgeolli’ fermentation , 2016 .

[58]  F. Shen,et al.  Evaluation of Near‐Infrared and Mid‐Infrared Spectroscopy for the Determination of Routine Parameters in Chinese Rice Wine , 2016 .

[59]  Nathalie Locquet,et al.  Using pH variations to improve the discrimination of wines by 3D front face fluorescence spectroscopy associated to Independent Components Analysis. , 2016, Talanta.

[60]  Zou Xiaobo,et al.  Rapid Determination of Antioxidant Compounds and Antioxidant Activity of Sudanese Karkade (Hibiscus sabdariffa L.) Using Near Infrared Spectroscopy , 2016, Food Analytical Methods.

[61]  Zhengyu Jin,et al.  A Feasibility Study on the Evaluation of Quality Properties of Chinese Rice Wine Using Raman Spectroscopy , 2016, Food Analytical Methods.

[62]  J. Lopes,et al.  Application of Fourier-transform infrared spectroscopy for the determination of chloride and sulfate in wines , 2016 .

[63]  Zhengyu Jin,et al.  Comparison between ATR-IR, Raman, concatenated ATR-IR and Raman spectroscopy for the determination of total antioxidant capacity and total phenolic content of Chinese rice wine. , 2016, Food chemistry.

[64]  Hui Zhao,et al.  Monitoring of alcohol strength and titratable acidity of apple wine during fermentation using near-infrared spectroscopy , 2016 .

[65]  Zou Xiaobo,et al.  Near-Infrared (NIR) Spectroscopy for Rapid Measurement of Antioxidant Properties and Discrimination of Sudanese Honeys from Different Botanical Origin , 2016, Food Analytical Methods.

[66]  Jianxue Liu,et al.  Determination of Three Alcohols in Chinese Dukang Base Liquor by FT-NIR Spectroscopy , 2016, Food Analytical Methods.

[67]  B. Cho,et al.  Rapid monitoring of the fermentation process for Korean traditional rice wine ‘Makgeolli’ using FT-NIR spectroscopy , 2015 .

[68]  S. Azcarate,et al.  Modeling excitation-emission fluorescence matrices with pattern recognition algorithms for classification of Argentine white wines according grape variety. , 2015, Food chemistry.

[69]  Fang Wang,et al.  Measurement of fermentation parameters of Chinese rice wine using Raman spectroscopy combined with linear and non-linear regression methods , 2015 .

[70]  Rong Li,et al.  Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence, UV and visible spectroscopies. , 2015, Food chemistry.

[71]  O. Busto,et al.  Data fusion methodologies for food and beverage authentication and quality assessment - a review. , 2015, Analytica chimica acta.

[72]  Haiyan Yu,et al.  Characterization of Chinese rice wine taste attributes using liquid chromatographic analysis, sensory evaluation, and an electronic tongue. , 2015, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[73]  Soo-Hyun Park,et al.  Colorimetric Sensor Array for White Wine Tasting , 2015, Sensors.

[74]  Fang Wang,et al.  Use of Attenuated Total Reflectance Mid-Infrared Spectroscopy for Rapid Prediction of Amino Acids in Chinese Rice Wine. , 2015, Journal of food science.

[75]  Maria Luz Rodriguez-Mendez,et al.  Beer discrimination using a portable electronic tongue based on screen-printed electrodes , 2015 .

[76]  Fang Wang,et al.  Rapid Determination of Process Variables of Chinese Rice Wine Using FT-NIR Spectroscopy and Efficient Wavelengths Selection Methods , 2015, Food Analytical Methods.

[77]  J. Sádecká,et al.  Synchronous Fluorescence Spectroscopy for Rapid Classification of Fruit Spirits , 2015, Food Analytical Methods.

[78]  Zhengyu Jin,et al.  Monitoring of fermentation process parameters of Chinese rice wine using attenuated total reflectance mid-infrared spectroscopy , 2015 .

[79]  Zhengyu Jin,et al.  Application of FT-NIR spectroscopy and FT-IR spectroscopy to Chinese rice wine for rapid determination of fermentation process parameters , 2015 .

[80]  Zhengyu Jin,et al.  Discrimination of Chinese rice wines of different geographical origins by UV–vis spectroscopy and chemometrics , 2015 .

[81]  Edgar Guevara,et al.  Quality control of mezcal combining multivariate analysis techniques and Raman spectroscopy , 2015, 2015 International Conference on Electronics, Communications and Computers (CONIELECOMP).

[82]  D. Milde,et al.  Study of phenolic profile and antioxidant activity in selected Moravian wines during winemaking process by FT-IR spectroscopy , 2015, Journal of Food Science and Technology.

[83]  Xavier Ceto,et al.  Application of electronic tongues in the qualitative and quantitative analysis of beers , 2014, IEEE SENSORS 2014 Proceedings.

[84]  Zhenhe Ma,et al.  Real time monitoring of multiple components in wine fermentation using an on-line auto-calibration Raman spectroscopy , 2014 .

[85]  Xiao-Gang Luo,et al.  Development of a colorimetric sensor array for the discrimination of Chinese liquors based on selected volatile markers determined by GC-MS. , 2014, Journal of agricultural and food chemistry.

[86]  Xiaoli Lu,et al.  Detection of the Chinese Rice Wine Using an Electronic Tongue , 2014 .

[87]  Tong Wu,et al.  Discrimination between authentic and adulterated liquors by near-infrared spectroscopy and ensemble classification. , 2014, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[88]  J. Sádecká,et al.  Fluorescence spectroscopy and multivariate methods for the determination of brandy adulteration with mixed wine spirit. , 2014, Food chemistry.

[89]  M. Vázquez,et al.  Determination of polyphenolic compounds of red wines by UV-VIS-NIR spectroscopy and chemometrics tools. , 2014, Food chemistry.

[90]  Yahong Yuan,et al.  Application of FT-NIR Spectroscopy to Apple Wine for Rapid Simultaneous Determination of Soluble Solids Content, pH, Total Acidity, and Total Ester Content , 2014, Food and Bioprocess Technology.

[91]  Zuobing Xiao,et al.  Application of Gas Chromatography-Based Electronic Nose for Classification of Chinese Rice Wine by Wine Age , 2014, Food Analytical Methods.

[92]  M. L. Rodriguez-Mendez,et al.  Evaluation of oxygen exposure levels and polyphenolic content of red wines using an electronic panel formed by an electronic nose and an electronic tongue. , 2014, Food chemistry.

[93]  M. Valle,et al.  Cava Wine Authentication Employing a Voltammetric Electronic Tongue , 2014 .

[94]  Zhao Li,et al.  Application of Vis/NIR Spectroscopy for Chinese Liquor Discrimination , 2014, Food Analytical Methods.

[95]  Manfred Spraul,et al.  Synergistic effect of the simultaneous chemometric analysis of ¹H NMR spectroscopic and stable isotope (SNIF-NMR, ¹⁸O, ¹³C) data: application to wine analysis. , 2014, Analytica chimica acta.

[96]  Hyun-Jin Park,et al.  Electronic tongue-based discrimination of Korean rice wines (makgeolli) including prediction of sensory evaluation and instrumental measurements. , 2014, Food chemistry.

[97]  J. Sádecká,et al.  Simultaneous Determination of Phenolic Acids and Scopoletin in Brandies Using Synchronous Fluorescence Spectrometry Coupled with Partial Least Squares , 2014, Food Analytical Methods.

[98]  Jiewen Zhao,et al.  Nondestructive measurement of total volatile basic nitrogen (TVB-N) in pork meat by integrating near infrared spectroscopy, computer vision and electronic nose techniques. , 2014, Food chemistry.

[99]  Feng Chen,et al.  Characterization of aroma compounds of Chinese famous liquors by gas chromatography-mass spectrometry and flash GC electronic-nose. , 2014, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[100]  A. Bansal,et al.  Chemometrics: A new scenario in herbal drug standardization , 2014, Journal of pharmaceutical analysis.

[101]  J. Sádecká,et al.  RIGHT-ANGLE FLUORESCENCE SPECTROSCOPY FOR DIFFERENTIATION OF DISTILLED ALCOHOLIC BEVERAGES , 2013 .

[102]  M. del Valle,et al.  Beer classification by means of a potentiometric electronic tongue. , 2013, Food chemistry.

[103]  Andrea Bellincontro,et al.  Feasibility of an electronic nose to differentiate commercial Spanish wines elaborated from the same grape variety , 2013 .

[104]  Quansheng Chen,et al.  Classification of rice wine according to different marked ages using a portable multi-electrode electronic tongue coupled with multivariate analysis , 2013 .

[105]  Floyd E. Dowell,et al.  Qualitative and quantitative analysis of lignocellulosic biomass using infrared techniques: A mini-review , 2013 .

[106]  S. Capone,et al.  Aroma analysis by GC/MS and electronic nose dedicated to Negroamaro and Primitivo typical Italian Apulian wines , 2013 .

[107]  Manel del Valle,et al.  Hybrid electronic tongue based on multisensor data fusion for discrimination of beers , 2013 .

[108]  Manuel Vázquez,et al.  Ultraviolet/visible/near-infrared spectral analysis and chemometric tools for the discrimination of wines between subzones inside a controlled designation of origin: a case study of Rías Baixas , 2013 .

[109]  Manel del Valle,et al.  Data fusion in electronic tongue for qualitative analysis of beers , 2012, 2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC).

[110]  Tahir Mehmood,et al.  A review of variable selection methods in Partial Least Squares Regression , 2012 .

[111]  Daniel Cozzolino,et al.  Recent Trends on the Use of Infrared Spectroscopy to Trace and Authenticate Natural and Agricultural Food Products , 2012 .

[112]  K. Tu,et al.  Application of electronic nose in Chinese spirits quality control and flavour assessment , 2012 .

[113]  Stefan Castritius,et al.  Rapid determination of the attenuation limit of beer using middle-infrared (MIR) spectroscopy and a multivariate model. , 2012, Journal of agricultural and food chemistry.

[114]  B. Ozen,et al.  Application of Mid-infrared Spectroscopy for the Measurement of Several Quality Parameters of Alcoholic Beverages, Wine and Raki , 2012, Food Analytical Methods.

[115]  Changjun Hou,et al.  Colorimetric artificial nose for baijiu identification , 2012 .

[116]  P. Fernández-Zurbano,et al.  Contribution of Nonvolatile Composition to Wine Flavor , 2012 .

[117]  Dirk W Lachenmeier,et al.  Rapid Quantification of Ethyl Carbamate in Spirits Using NMR Spectroscopy and Chemometrics , 2012 .

[118]  Yibin Ying,et al.  Discrimination Between Shaoxing Wines and Other Chinese Rice Wines by Near-Infrared Spectroscopy and Chemometrics , 2012, Food and Bioprocess Technology.

[119]  L. Lencioni,et al.  Chemical profile of white wines produced from 'Greco bianco' grape variety in different Italian areas by nuclear magnetic resonance (NMR) and conventional physicochemical analyses. , 2012, Journal of agricultural and food chemistry.

[120]  Amadou Dicko,et al.  Aging fingerprint characterization of beer using electronic nose , 2011 .

[121]  Eduard Llobet,et al.  A novel humid electronic nose combined with an electronic tongue for assessing deterioration of wine , 2011 .

[122]  O. Busto,et al.  Quantification of phenolic compounds during red winemaking using FT-MIR spectroscopy and PLS-regression. , 2011, Journal of agricultural and food chemistry.

[123]  Mauro Bertotti,et al.  Use of copper and gold electrodes as sensitive elements for fabrication of an electronic tongue: Discrimination of wines and whiskies , 2011 .

[124]  Daniel Cozzolino,et al.  Discrimination between Shiraz wines from different Australian regions: the role of spectroscopy and chemometrics. , 2011, Journal of agricultural and food chemistry.

[125]  Zhenbo Wei,et al.  Classification and prediction of rice wines with different marked ages by using a voltammetric electronic tongue. , 2011, Biosensors & bioelectronics.

[126]  Andrea Bellincontro,et al.  Discrimination of sweet wines partially fermented by two osmo-ethanol-tolerant yeasts by gas chromatographic analysis and electronic nose. , 2011, Food chemistry.

[127]  F. Shen,et al.  Prediction of sugars and acids in Chinese rice wine by mid-infrared spectroscopy , 2011 .

[128]  Daniel Cozzolino,et al.  Can spectroscopy geographically classify Sauvignon Blanc wines from Australia and New Zealand , 2011 .

[129]  David Littlejohn,et al.  Detection of counterfeit Scotch whisky samples using mid-infrared spectrometry with an attenuated total reflectance probe incorporating polycrystalline silver halide fibres. , 2011, Analytica chimica acta.

[130]  Christophe Blecker,et al.  Fluorescence Spectroscopy Measurement for Quality Assessment of Food Systems—a Review , 2011 .

[131]  Y. Numata,et al.  Quantitative analysis of alcohol–water binary solutions using Raman spectroscopy , 2011 .

[132]  Mahdi Ghasemi-Varnamkhasti,et al.  Potential application of electronic nose technology in brewery , 2011 .

[133]  A. R. Guesalaga,et al.  Rapid Measurement of Phenolics Compounds in Red Wine Using Raman Spectroscopy , 2011, IEEE Transactions on Instrumentation and Measurement.

[134]  O. Busto,et al.  Characterization and classification of the aroma of beer samples by means of an MS e-nose and chemometric tools , 2011, Analytical and bioanalytical chemistry.

[135]  C. Pizarro,et al.  Prediction of total and volatile acidity in red wines by Fourier-transform mid-infrared spectroscopy and iterative predictor weighting , 2011, Analytical and bioanalytical chemistry.

[136]  J. Saja,et al.  Prediction of bitterness and alcoholic strength in beer using an electronic tongue , 2010 .

[137]  A. Riul,et al.  Recent advances in electronic tongues. , 2010, The Analyst.

[138]  G. Downey,et al.  Mid-infrared spectroscopy coupled with chemometrics: a tool for the analysis of intact food systems and the exploration of their molecular structure-quality relationships - a review. , 2010, Chemical reviews.

[139]  Yibin Ying,et al.  Determination of amino acids in Chinese rice wine by fourier transform near-infrared spectroscopy. , 2010, Journal of agricultural and food chemistry.

[140]  M. Schmitt,et al.  Quantitative mineral analysis using Raman spectroscopy and chemometric techniques , 2010 .

[141]  J. Lammertyn,et al.  Electronic tongue as a screening tool for rapid analysis of beer. , 2010, Talanta.

[142]  Robert G. Dambergs,et al.  Two-dimensional correlation analysis of the effect of temperature on the fingerprint of wines analysed by mass spectrometry electronic nose , 2010 .

[143]  Ernestina Casiraghi,et al.  NIR and MIR spectroscopy as rapid methods to monitor red wine fermentation , 2010 .

[144]  Daniel Cozzolino,et al.  Classification of Tempranillo wines according to geographic origin: combination of mass spectrometry based electronic nose and chemometrics. , 2010, Analytica chimica acta.

[145]  J. Sádecká,et al.  Classification of brandies and wine distillates using front face fluorescence spectroscopy. , 2009 .

[146]  José Pedro Santos,et al.  Evaluation of wine aromatic compounds by a sensory human panel and an electronic nose. , 2009, Journal of agricultural and food chemistry.

[147]  Naresh Magan,et al.  Early discrimination of fungal species responsible of ochratoxin A contamination of wine and other grape products using an electronic nose , 2009, Mycotoxin Research.

[148]  Robert G. Dambergs,et al.  Mid infrared spectroscopy and multivariate analysis: a tool to discriminate between organic and non-organic wines grown in Australia , 2009 .

[149]  Dafang Zhuang,et al.  Advances in Multi-Sensor Data Fusion: Algorithms and Applications , 2009, Sensors.

[150]  Adisorn Tuantranont,et al.  Au-doped zinc oxide nanostructure sensors for detection and discrimination of volatile organic compounds , 2009 .

[151]  Daniel Cozzolino,et al.  Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose. , 2009, Analytica chimica acta.

[152]  Dominique Chevalier-Lucia,et al.  Off-flavours detection in alcoholic beverages by electronic nose coupled to GC , 2009 .

[153]  M. Peris,et al.  A 21st century technique for food control: electronic noses. , 2009, Analytica chimica acta.

[154]  Oliver Tomic,et al.  Characterization of selected South African young cultivar wines using FTMIR spectroscopy, gas chromatography, and multivariate data analysis. , 2009, Journal of agricultural and food chemistry.

[155]  Fei Liu,et al.  Variable selection in visible/near infrared spectra for linear and nonlinear calibrations: a case study to determine soluble solids content of beer. , 2009, Analytica chimica acta.

[156]  Yibin Ying,et al.  A feasibility study on on-line determination of rice wine composition by Vis–NIR spectroscopy and least-squares support vector machines , 2009 .

[157]  Carolyn F. Ross,et al.  Sensory science at the human–machine interface , 2009 .

[158]  Pavla Polášková,et al.  Wine flavor: chemistry in a glass. , 2008, Chemical Society reviews.

[159]  J. A. Ragazzo‐Sánchez,et al.  Identification of different alcoholic beverages by electronic nose coupled to GC , 2008 .

[160]  José Pedro Santos,et al.  Electronic nose for wine ageing detection , 2008 .

[161]  Daniel Cozzolino,et al.  Comparison of metal oxide-based electronic nose and mass spectrometry-based electronic nose for the prediction of red wine spoilage. , 2008, Journal of agricultural and food chemistry.

[162]  Manuel Aleixandre,et al.  Portable e-nose to classify different kinds of wine , 2008 .

[163]  Kumar Mallikarjunan,et al.  Discrimination of Wines Produced from Cabernet Sauvignon Grapes Treated with Aqueous Ethanol Post-Bloom Using an Electronic Nose , 2008 .

[164]  Colm P. O'Donnell,et al.  Better Quality Food and Beverages: The Role of near Infrared Spectroscopy , 2008 .

[165]  N. Bârsan,et al.  Electronic nose: current status and future trends. , 2008, Chemical reviews.

[166]  Robert G. Dambergs,et al.  Preliminary study on the application of visible–near infrared spectroscopy and chemometrics to classify Riesling wines from different countries , 2008 .

[167]  M Gishen,et al.  Analysis of elements in wine using near infrared spectroscopy and partial least squares regression. , 2008, Talanta.

[168]  Li Wang,et al.  Feasibility of the use of visible and near infrared spectroscopy to assess soluble solids content and pH of rice wines , 2007 .

[169]  A. Peirs,et al.  Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .

[170]  José Pedro Santos,et al.  Correlating e-nose responses to wine sensorial descriptors and gas chromatography–mass spectrometry profiles using partial least squares regression analysis , 2007 .

[171]  Patrycja Ciosek,et al.  Sensor arrays for liquid sensing--electronic tongue systems. , 2007, The Analyst.

[172]  F. J. Acevedo,et al.  Classification of wines produced in specific regions by UV-visible spectroscopy combined with support vector machines. , 2007, Journal of agricultural and food chemistry.

[173]  Y. Roggo,et al.  A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies. , 2007, Journal of pharmaceutical and biomedical analysis.

[174]  Yibin Ying,et al.  Discrimination between Chinese rice wines of different geographical origins by NIRS and AAS , 2007 .

[175]  Daniel Cozzolino,et al.  Feasibility study on the use of a head space mass spectrometry electronic nose (MS e_nose) to monitor red wine spoilage induced by Brettanomyces yeast , 2007 .

[176]  Chen Zhang,et al.  Colorimetric sensor array for soft drink analysis. , 2007, Journal of agricultural and food chemistry.

[177]  Ioan Notingher,et al.  Progress in Raman spectroscopy in the fields of tissue engineering, diagnostics and toxicological testing , 2006, Journal of materials science. Materials in medicine.

[178]  Tao Lin,et al.  Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy , 2006, SPIE Optics East.

[179]  A. Makarov,et al.  Orbitrap Mass Analyzer – Overview and Applications in Proteomics , 2006, Proteomics.

[180]  D. Cozzolino,et al.  Geographic classification of spanish and Australian tempranillo red wines by visible and near-infrared spectroscopy combined with multivariate analysis. , 2006, Journal of agricultural and food chemistry.

[181]  Miguel de la Guardia,et al.  Combination of mid- and near-infrared spectroscopy for the determination of the quality properties of beers. , 2006, Analytica chimica acta.

[182]  G. Corrieu,et al.  Discrimination of Cognacs and other distilled drinks by mid-infrared spectropscopy. , 2006, Journal of agricultural and food chemistry.

[183]  K. Suslick,et al.  Colorimetric sensor arrays for the analysis of beers: a feasibility study. , 2006, Journal of agricultural and food chemistry.

[184]  A. Gupta,et al.  Quantitative Analysis of Alcohol, Sugar, and Tartaric Acid in Alcoholic Beverages Using Attenuated Total Reflectance Spectroscopy , 2006, Journal of automated methods & management in chemistry.

[185]  Rasmus Bro,et al.  Multivariate autofluorescence of intact food systems. , 2006, Chemical reviews.

[186]  Eric Dufour,et al.  Investigation of variety, typicality and vintage of French and German wines using front-face fluorescence spectroscopy , 2006 .

[187]  Bahram Hemmateenejad,et al.  Ant colony optimisation: a powerful tool for wavelength selection , 2006 .

[188]  Márcio José Coelho Pontes,et al.  Classification of distilled alcoholic beverages and verification of adulteration by near infrared spectrometry , 2006 .

[189]  M. C. Horrillo,et al.  Differentiation of red wines using an electronic nose based on surface acoustic wave devices. , 2006, Talanta.

[190]  Yibin Ying,et al.  Quality Determination of Chinese Rice Wine Based on Fourier Transform near Infrared Spectroscopy , 2006 .

[191]  José Pedro Santos,et al.  Identification of typical wine aromas by means of an electronic nose , 2006, IEEE Sensors Journal.

[192]  A. M. Gil,et al.  Composition of beer by 1H NMR spectroscopy: effects of brewing site and date of production. , 2006, Journal of agricultural and food chemistry.

[193]  Daniel Cozzolino,et al.  Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin. , 2005, Talanta.

[194]  Zou Xiaobo,et al.  Apple quality assessment by fusion three sensors , 2005, IEEE Sensors, 2005..

[195]  José Pedro Santos,et al.  Classification of white wine aromas with an electronic nose. , 2005, Talanta.

[196]  L. R. Sahagun,et al.  Qualitative study of ethanol content in tequilas by Raman spectroscopy and principal component analysis. , 2005, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[197]  Pascale Chalier,et al.  Coupling gas chromatography and electronic nose for dehydration and desalcoholization of alcoholized beverages: Application to off-flavour detection in wine , 2005 .

[198]  A. Smilde,et al.  Relating the sensory sensation ‘creamy mouthfeel’ in custards to rheological measurements , 2005 .

[199]  G. Dent,et al.  Modern Raman Spectroscopy: A Practical Approach , 2005 .

[200]  Dirk W Lachenmeier,et al.  Quality control of beer using high-resolution nuclear magnetic resonance spectroscopy and multivariate analysis , 2005 .

[201]  Ricard Boqué,et al.  Determination of ageing time of spirits in oak barrels using a headspace–mass spectrometry (HS-MS) electronic nose system and multivariate calibration , 2005, Analytical and bioanalytical chemistry.

[202]  C. Di Natale,et al.  Nonspecific sensor arrays ("electronic tongue") for chemical analysis of liquids (IUPAC Technical Report) , 2005 .

[203]  Yubin Lan,et al.  Artificial senses for characterization of food quality , 2004 .

[204]  S. Buratti,et al.  Characterization and classification of Italian Barbera wines by using an electronic nose and an amperometric electronic tongue , 2004 .

[205]  José Pedro Santos,et al.  A comparative study of sensor array and GC–MS: application to Madrid wines characterization , 2004 .

[206]  E. Martinelli,et al.  Application of metalloporphyrins-based gas and liquid sensor arrays to the analysis of red wine , 2004 .

[207]  D. Cozzolino,et al.  Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy , 2004 .

[208]  M. Penza,et al.  Chemometric characterization of Italian wines by thin-film multisensors array and artificial neural networks , 2004 .

[209]  R. Gutierrez-Osuna,et al.  Fusion of three sensory modalities for the multimodal characterization of red wines , 2004, IEEE Sensors Journal.

[210]  A. M. Gil,et al.  Multivariate analysis of NMR and FTIR data as a potential tool for the quality control of beer. , 2004, Journal of agricultural and food chemistry.

[211]  D. Cozzolino,et al.  Feasibility study on the use of visible and near-infrared spectroscopy together with chemometrics to discriminate between commercial white wines of different varietal origins. , 2003, Journal of agricultural and food chemistry.

[212]  Paul Geladi,et al.  Chemometrics in spectroscopy. Part 1. Classical chemometrics , 2003 .

[213]  J. Roger,et al.  Fusion of aroma, FT-IR and UV sensor data based on the Bayesian inference. Application to the discrimination of white grape varieties , 2003 .

[214]  Vincent Baeten,et al.  Spectroscopy: Developments in instrumentation and analysis , 2002 .

[215]  A. M. Gil,et al.  High-resolution nuclear magnetic resonance spectroscopy and multivariate analysis for the characterization of beer. , 2002, Journal of agricultural and food chemistry.

[216]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[217]  A. Szwengiel,et al.  Comparison of sorghum and maize raw distillates: Factors affecting ethanol efficiency and volatile by-product profile , 2020 .

[218]  A. Cassano,et al.  Membrane technologies assisting plant-based and agro-food by-products processing: A comprehensive review , 2020 .

[219]  M. L. Rodriguez-Mendez,et al.  Analysis of red wines using an electronic tongue and infrared spectroscopy. Correlations with phenolic content and color parameters , 2020 .

[220]  Dirk W Lachenmeier,et al.  The Threat to Quality of Alcoholic Beverages by Unrecorded Consumption , 2019, Alcoholic Beverages.

[221]  M. Nikšić,et al.  Medicinal Fungus Ganoderma lucidum as Raw Material for Alcohol Beverage Production , 2019, Alcoholic Beverages.

[222]  Jun Wang,et al.  Rapid identification of tea quality by E-nose and computer vision combining with a synergetic data fusion strategy , 2019, Journal of Food Engineering.

[223]  L. Tenori,et al.  NMR applications in food analysis: Part A , 2017 .

[224]  Xavier Cetó,et al.  Electronic tongues to assess wine sensory descriptors. , 2017, Talanta.

[225]  L. Mannina,et al.  Advances in Nuclear Magnetic Resonance Spectroscopy for Food Authenticity Testing , 2016 .

[226]  Zhao Li,et al.  Rapid detection of volatile compounds in apple wines using FT-NIR spectroscopy. , 2016, Food chemistry.

[227]  Zhenhe Ma,et al.  Quantitative Analysis of Multiple Components in Wine Fermentation using Raman Spectroscopy , 2015 .

[228]  Mahdi Ghasemi-Varnamkhasti,et al.  From simple classification methods to machine learning for the binary discrimination of beers using electronic nose data , 2014 .

[229]  Manel del Valle,et al.  Voltammetric BioElectronic Tongue for the analysis of phenolic compounds in rosé cava wines , 2014 .

[230]  Mahdi Ghasemi-Varnamkhasti,et al.  NIR spectroscopy coupled with multivariate computational tools for qualitative characterization of the aging of beer , 2014 .

[231]  J. Sádecká,et al.  Determination of the adulterants in adulterant–brandy blends using fluorescence spectroscopy and multivariate methods , 2014 .

[232]  Yennifer Yuliana Rios Diaz,et al.  Electronic tongue for wine discrimination, using PCA and ANN , 2014, 2014 III International Congress of Engineering Mechatronics and Automation (CIIMA).

[233]  Haidy A. Gad,et al.  Application of chemometrics in authentication of herbal medicines: a review. , 2013, Phytochemical analysis : PCA.

[234]  H. Qin,et al.  Colorimetric artificial nose for identification of Chinese liquor with different geographic origins , 2012 .

[235]  Constantin Apetrei,et al.  Monitoring of evolution during red wine aging in oak barrels and alternative method by means of an electronic panel test , 2012 .

[236]  Y. Ying,et al.  Determination of Ethanol Concentration in Chinese Rice Wine by Dispersive Raman Spectroscopy , 2011 .

[237]  Y. Ying,et al.  Use of Visible and Short-Wavelength Near-Infrared Spectroscopy and Least-Squares Support Vector Machines for Non-Destructive Rice Wine Quality Determination , 2011 .

[238]  Daniel Cozzolino,et al.  Feasibility study on the use of attenuated total reflectance mid-infrared for analysis of compositional parameters in wine , 2011 .

[239]  Adisorn Tuantranont,et al.  ortable electronic nose based on carbon nanotube-SnO 2 gas sensors and its pplication for detection of methanol contamination in whiskeys , 2010 .

[240]  Yibin Ying,et al.  Non-invasive determination of enological parameters of rice wine by Vis-NIR spectroscopy and least-squares support vector machines , 2008 .

[241]  J. Sádecká,et al.  Characterization and Classification of Distilled Drinks Using Total Luminescence and Synchronous Fluorescence Spectroscopy , 2008 .

[242]  Hongjian Lin,et al.  Prediction of enological parameters and discrimination of rice wine age using least-squares support vector machines and near infrared spectroscopy. , 2008, Journal of agricultural and food chemistry.

[243]  Davide Ballabio,et al.  Prediction of Italian red wine sensorial descriptors from electronic nose, electronic tongue and spectrophotometric measurements by means of Genetic Algorithm regression models , 2007 .

[244]  Dirk W. Lachenmeier,et al.  Rapid quality control of spirit drinks and beer using multivariate data analysis of Fourier transform infrared spectra , 2007 .

[245]  Yukihiro Ozaki,et al.  Near-infrared spectroscopy in food science and technology , 2007 .

[246]  M. Martí,et al.  Electronic noses in the quality control of alcoholic beverages , 2005 .

[247]  H. Smyth.  The compositional basis of the aroma of Riesling and unwooded Chardonnay wine. , 2005 .

[248]  J. Weiner,et al.  Fundamentals and applications , 2003 .

[249]  S. Sikdar,et al.  Fundamentals and applications , 1998 .

[250]  James Llinas,et al.  An introduction to multisensor data fusion , 1997, Proc. IEEE.

[251]  T. Fearn,et al.  Near infrared spectroscopy in food analysis , 1986 .

[252]  J. Lakowicz.  Principles of fluorescence spectroscopy , 1983 .

[253]  R. Goodacre,et al.  Provided for Non-commercial Research and Educational Use Only. Not for Reproduction, Distribution or Commercial Use. Shining Light on the Microbial World: the Application of Raman Microspectroscopy , 2022 .