Установление географического происхождения некоторых сухих белых вин по данным ИСП спектрометрического и хемометрического анализа
Аннотация
Важным аспектом при оценке подлинности вин является определение их географического происхождения. Цель настоящей работы – установление географического происхождения вин, изготовленных из выращенных в различных регионах Краснодарского края сортов винограда Шардоне, Рислинг и Мускат, по данным ИСП-спектрометрического и хемометрического анализа. Установлено существенное отличие концентраций Al, Ba, Ca, Rb в винах в зависимости от сорта, и Al, Ba, Rb, Fe, Li, Sr – между регионами произрастания. При этом концентрации элементов отличались в различных группах вин также по величине их отклонения относительно среднего значения. Выявленная дискриминантным анализом кластерная структура образцов вин относительно регионов их происхождения позволила построить модели с высокими прогностическими свойствами для идентификации географического происхождения вин. Критерием качества построенных моделей служила точность классификации – доля правильно идентифицированных образцов вин. Максимальную точность классификации на всей совокупности 153 образцов вин показали автоматизированные нейронные сети (100 %), затем метод опорных векторов (98.69 %) и общий дискриминантный анализ (94.77 %). При предсказании географического происхождения вин по важности вклада концентраций металлов в построенных моделях доминировали Sr, Li и Fe. По результатам проведенных исследований заключили, что ориентированные на данные большой размерности методы машинного обучения совместно с ИСП-спектрометрическим анализом могут успешно решать задачи малой размерности, связанные с установлением географического происхождения вин по компонентному составу и их наименованию, превосходя по точности традиционный метод – общий дискриминантный анализ.
Ключевые слова: ИСП-спектрометрия; вино; элементный анализ; географическое происхождение; хемометрика
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REFERENCES
Ranaweera R.K.R., Souza Gonzaga L., Capone D.L., Bastian S.E.P., Jeffery D.W. Authenticity and Traceability in the Wine Industry: From Analytical Chemistry to Consumer Perceptions. Comprehensive Foodomics. Elsevier, 2021. pp. 452-480.
Casolani N., D’Eusanio M., Liberatore L., Raggi A., Petti L. Life Cycle Assessment in the wine sector: A review on inventory phase. Croat. J. Food Sci. Technol., 2022, vol. 379, article 134404. doi:10.1016/j.jclepro.2022.134404.
Arvanitoyannis I.S. Wine authenticity and traceability. Managing Wine Quality. Elsevier, 2022. pp. 279-338.
Parker R.M. Bordeaux: A Consumer’s Guide to the World’s Finest Wines; 4th Ed. London, Simon & Schuster, 2003. 1274 p.
Spence C. Perceptual learning in the chemical senses: A review. Food Res. Int., 2019, vol. 123, pp. 746-761. doi:10.1016/j.foodres.2019.06.005.
Taladrid D., Lorente L., Bartolomé B., Moreno‐Arribas M.V., Laguna L. An integrative salivary approach regarding palate cleansers in wine tasting. J. Texture Stud., 2019, vol. 50, pp. 75–82. doi:10.1111/jtxs.12361.
Ribéreau-Gayon P., Glories Y., Maujean A., Dubourdieu D. Handbook of Enology -The Chemistry of Wine Stabilization and Treatments, 2nd Ed. John Wiley & Sons, Chichester, West Sussex, England, 2006. p. 301-332
Rodrigues H., Parr W. V. Contribution of cross-cultural studies to understanding wine appreciation: A review. Food Res. Int., 2019, vol. 115, pp. 251-258. doi:10.1016/j.foodres.2018.09.008.
Ranaweera R.K.R., Gilmore A.M., Capone D.L., Bastian S.E.P., Jeffery D.W. Spectrofluorometric analysis combined with machine learning for geographical and varietal authentication, and prediction of phenolic compound concentrations in red wine. Food Chem., 2021, vol. 361, article 130149. doi:10.1016/j.foodchem.2021.130149.
Nyitrainé Sárdy Á.D., Ladányi M., Varga Z., Szövényi Á.P., Matolcsi R. The Effect of Grapevine Variety and Wine Region on the Primer Parameters of Wine Based on 1H NMR-Spectroscopy and Machine Learning Methods. Diversity, 2022, vol. 14, no.2 article 74. doi:10.3390/d14020074.
Hao X., Gao F., Wu H., Song Y., Zhang L., Li H., Wang H. From Soil to Grape and Wine: Geographical Variations in Elemental Profiles in Different Chinese Regions. Foods, 2021, vol, 10, article 3108. doi:10.3390/foods10123108.
Delgado J.A., Sánchez-Palomo E., Osorio Alises M., González Viñas M.A. Chemical and sensory aroma typicity of La Mancha Petit Verdot wines. LWT - Food Science and Technology, 2022, vol. 162, article 113418. doi:10.1016/j.lwt.2022.113418.
Baker A.K., Ross C.F. Sensory Evaluation of Impact of Wine Matrix on Red Wine Finish: A Preliminary Study. J. Sens. Stud., 2014, vol. 29, pp. 139-148. doi:10.1111/joss.12089.
He Y., Wang X., Li P., Lv Y., Nan H., Wen L., Wang Z. Research progress of wine aroma components: A critical review. Food Chem., 2023, vol. 402, article 134491. doi:10.1016/j.foodchem.2022.134491.
Tian T., Sun J., Wu D., Xiao J., Lu J. Objective measures of greengage wine quality: From taste-active compound and aroma-active compound to sensory profiles. Food Chem., 2021, vol. 340, article 128179. doi:10.1016/j.foodchem.2020.128179.
Cordente A.G., Espinase Nandorfy D., Solomon M., Schulkin A., Kolouchova R., Francis I.L., Schmidt S.A. Aromatic Higher Alcohols in Wine: Implication on Aroma and Palate Attributes during Chardonnay Aging. Molecules, 2021, vol. 26, article 4979. doi:10.3390/molecules26164979.
Cortez P., Cerdeira A., Almeida F., Matos T., Reis J. Modeling wine preferences by data mining from physicochemical properties. Decis. Support Syst., 2009, vol. 47, pp. 547-553. doi:10.1016/j.dss.2009.05.016.
Gómez-Meire S., Campos C., Falqué E., Díaz F., Fdez-Riverola F. Assuring the authenticity of northwest Spain white wine varieties using machine learning techniques. Food Res. Int., 2014, vol. 60, pp. 230-240. doi:10.1016/j.foodres.2013.09.032.
Del Barrio-Galán R., Valle-Herrero H. del, Bueno-Herrera M., López-de-la-Cuesta P., Pérez-Magariño S. Volatile and Non-Volatile Characterization of White and Rosé Wines from Different Spanish Protected Designations of Origin. Beverages, 2021, vol. 7, article 49. doi:10.3390/beverages7030049.
Rinaldi A., Moio L. Effect of enological tannin addition on astringency subqualities and phenolic content of red wines. J. Sens. Stud., 2018, vol. 33, article 12325. doi:10.1111/joss.12325.
Vidal L., Antúnez L., Giménez A., Ares G. Evaluation of Palate Cleansers for Astringency Evaluation of Red Wines. J. Sens. Stud., 2016, vol. 31, pp. 93-100. doi:10.1111/joss.12194.
Vidal L., Antúnez L., Giménez A., Medina K., Boido E., Ares G. Astringency evaluation of Tannat wines: Comparison of assessments from trained assessors and experts. J. Sens. Stud., 2018, vol. 33, article 12330. doi:10.1111/joss.12330.
Temerdashev Z., Khalafyan A., Kaunova A., Abakumov A., Titarenko V., Akin’shina V. Using neural networks to identify the regional and varietal origin of Cabernet and Merlot dry red wines produced in Krasnodar region. Foods Raw Mater., 2019, pp.124-130. doi:10.21603/2308-4057-2019-1-124-130.
Kapusta I., Cebulak T., Oszmiański J. The anthocyanins profile of red grape cultivars growing in south-east Poland (Subcarpathia region). J. Food Meas. Charact., 2017, vol. 11, pp. 1863-1873. doi:10.1007/s11694-017-9568-4.
Perestrelo R., Silva C., Silva P., Câmara J.S. Rapid spectrophotometric methods as a tool to assess the total phenolics and antioxidant potential over grape ripening: a case study of Madeira grapes. J. Food Meas. Charact., 2018, vol.12, pp. 1754-1762. doi:10.1007/s11694-018-9790-8.
Tang K., Xi Y.-R., Ma Y., Zhang H.-N., Xu Y. Chemical and Sensory Characterization of Cabernet Sauvignon Wines from the Chinese Loess Plateau Region. Molecules, 2019, vol. 24, article 1122. doi:10.3390/molecules24061122.
Jackson R.S. Oral Sensations (Taste and Mouth-Feel). Wine Tasting. Elsevier, 2017. pp. 103-136.
Monteiro B., Vilela A., Correia E. Sensory profile of pink port wines: Development of a flavour lexicon. Flavour Fragr. J., 2014, vol. 29, pp. 50-58. doi:10.1002/ffj.3178.
Urvieta R., Buscema F., Bottini R., Coste B., Fontana A. Phenolic and sensory profiles discriminate geographical indications for Malbec wines from different regions of Mendoza, Argentina. Food Chem., 2018, vol. 265, pp. 120-127. doi:10.1016/j.foodchem.2018.05.083.
Jackson R.S. Wines: Wine Tasting. Encyclopedia of Food and Health. Elsevier, 2016. pp. 577-584.
Jose-Coutinho A., Avila P., Ricardo-Da-Silva J.M. Sensory Profile of Portuguese White Wines Using Long-Term Memory: A Novel Nationwide Approach. J. Sens. Stud., 2015, vol. 30, pp. 381-394. doi:10.1111/joss.12165.
Catarino S., Madeira M., Monteiro F., Caldeira I., Bruno de Sousa R. Curvelo-Garcia A. Mineral Composition through Soil-Wine System of Portuguese Vineyards and Its Potential for Wine Traceability. Beverages, 2018, vol. 4, article 85. doi:10.3390/beverages4040085.
Khalafyan A.A., Temerdashev Z.A., Kaunova A.A., Abakumov A.G., Titarenko V.O., Akin’shina V.A., Ivanovets E.A. Determination of the Wine Variety and Geographical Origin of White Wines Using Neural Network Technologies. J. Anal. Chem., 2019, vol. 74, pp. 617-624. doi:10.1134/S1061934819060042.
Temerdashev Z.A., Abakumov A.G., Khalafyan A.A., Ageeva N.M. Correlations between the elemental composition of grapes, soils of the viticultural area and wine. Ind. Lab. Diagnostics Mater., 2021, vol. 87, pp. 11-18. doi:10.26896/1028-6861-2021-87-11-11-18.
Wu H., Tian L., Chen B., Jin B., Tian B., Xie L., Rogers K.M., Lin G. Verification of imported red wine origin into China using multi isotope and elemental analyses. Food Chem., 2019, vol. 301, article 125137. doi:10.1016/j.foodchem.2019.125137.
Espinoza Cruz T.L., Guerrero Esperanza M., Wrobel K., Yanez Barrientos E., Acevedo Aguilar F.J., Wrobel K. Determination of major and minor elements in Mexican red wines by microwave-induced plasma optical emission spectrometry, evaluating different calibration methods and exploring potential of the obtained data in the assessment of wine provenance. Spectrochim. Acta Part B, 2020, vol. 164. article 105754. doi:10.1016/j.sab.2019.105754.
Gao F., Hao X., Zeng G., Guan L., Wu H., Zhang L., Wei R., Wang H., Li H. Identification of the geographical origin of Ecolly (Vitis vinifera L.) grapes and wines from different Chinese regions by ICP-MS coupled with chemometrics. J. Food Compos. Anal., 2022, vol. 105, article 104248. doi:10.1016/j.jfca.2021.104248.
Wang Q.J., Spence C. Wine complexity: An empirical investigation. Food Qual. Prefer., 2018, vol. 68, pp. 238-244. doi:10.1016/j.foodqual.2018.03.011.
Ruiz J., Kiene F., Belda I., Fracassetti D., Marquina D., Navascués E., Calderón F., Benito A., Rauhut D., Santos A. Effects on varietal aromas during wine making: a review of the impact of varietal aromas on the flavor of wine. Appl. Microbiol. Biotechnol., 2019, vol. 103, pp. 7425-7450. doi:10.1007/s00253-019-10008-9.
Mirás-Avalos J.M., Bouzas-Cid Y., Trigo-Córdoba E., Orriols I., Falqué E. Effects of Two Different Irrigation Systems on the Amino Acid Concentrations, Volatile Composition and Sensory Profiles of Godello Musts and Wines. Foods, 2019, vol. 8, article135. doi:10.3390/foods8040135.
Gu H.-W., Zhou H.-H., Lv Y., Wu Q., Pan Y., Peng Z.-X., Zhang X.-H., Yin X.-L. Geographical origin identification of Chinese red wines using ultraviolet-visible spectroscopy coupled with machine learning techniques. J. Food Compos. Anal., 2023, vol. 119, article 105265. doi:10.1016/j.jfca.2023.105265.
Bouzas-Cid Y., Falqué E., Orriols I., Mirás-Avalos J.M. Effects of irrigation over three years on the amino acid composition of Treixadura (Vitis vinifera L.) musts and wines, and on the aromatic composition and sensory profiles of its wines. Food Chem., 2018, vol. 240, pp. 707-716. doi:10.1016/j.foodchem.2017.08.013.
Vilanova M., Campo E., Escudero A., Graña M., Masa A., Cacho J. Volatile composition and sensory properties of Vitis vinifera red cultivars from North West Spain: Correlation between sensory and instrumental analysis. Anal. Chim. Acta, 2012, vol. 720, pp. 104-111. doi:10.1016/j.aca.2012.01.026.
Bevin C.J., Dambergs R.G., Fergusson A.J., Cozzolino D. Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis. Anal. Chim. Acta, 2008, vol. 621, pp. 19-23. doi:10.1016/j.aca.2007.10.042.
Pohl P. What do metals tell us about wine? TrAC Trends Anal. Chem., 2007, vol. 26, pp. 941-949. doi:10.1016/j.trac.2007.07.005.
Gonzálvez A., Armenta S., Pastor A., de la Guardia M. Searching the Most Appropriate Sample Pretreatment for the Elemental Analysis of Wines by Inductively Coupled Plasma-Based Techniques. J. Agric. Food Chem., 2008, vol. 56, pp. 4943-4954. doi:10.1021/jf800286y.
Grindlay G., Mora J., Gras L., de Loos-Vollebregt M.T.C. Atomic spectrometry methods for wine analysis: A critical evaluation and discussion of recent applications. Anal. Chim. Acta, 2011, vol. 691, pp. 18-32. doi:10.1016/j.aca.2011.02.050.
Kaunova A.A., Petrov V.I., Tsyupko T.G., Temerdashev Z.A. Perekotii V. V., Luk’yanov A.A. Identification of wine provenance by ICP-AES multielement analysis. J. Anal. Chem., 2013, vol. 68, pp. 831-836. doi:10.1134/S1061934813090050.
Hopfer H., Nelson J., Collins T.S., Heymann H., Ebeler S.E. The combined impact of vineyard origin and processing winery on the elemental profile of red wines. Food Chem., 2015, vol. 172, pp. 486-496. doi:10.1016/j.foodchem.2014.09.113.
Kment P., Mihaljevič M., Ettler V., Šebek O., Strnad L., Rohlová L. Differentiation of Czech wines using multielement composition – A comparison with vineyard soil. Food Chem., 2005, vol. 91, pp. 157-165. doi:10.1016/j.foodchem.2004.06.010.
Moreno I., Gonzalezweller D., Gutierrez V., Marino M., Camean A., Gonzalez A., Hardisson A. Differentiation of two Canary DO red wines according to their metal content from inductively coupled plasma optical emission spectrometry and graphite furnace atomic absorption spectrometry by using Probabilistic Neural Networks. Talanta. 2007, vol. 72, pp. 263-268. doi:10.1016/j.talanta.2006.10.029.
DOI: https://doi.org/10.15826/analitika.2023.27.4.006
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