干红葡萄酒单宁质量的多维表征方法分析

doi:10.3864/j.issn.0578-1752.2025.10.013

Abstract

Abstract:

【Objective】 Tannins are important polyphenolic compounds that significantly influence the sensory characteristics of color, aroma, and taste in dry red wine. This study compared various methods for tannin analysis, including spectroscopic quantification, total phenols, monomers, binding characteristics, and astringency quality, so as to provide the methodological support for the comprehensive characterization of tannin quality in dry red wine. 【Method】 The study used 18 Xinjiang dry red wines aged from 1 to 9 years. Tannin spectroscopic quantification was conducted using the Folin-Denis method, Bate-Smith method, hydrochloric acid-vanillin method, protein precipitation method, and methyl cellulose method. Total phenols were measured using the Folin-Ciocalteu reagent method, while flavanols and flavonols were quantified using UV-visible spectrophotometry. Aggregation characteristics were analyzed using the hydrochloric acid, ethanol, and gelatin precipitation methods. Tannin astringency quality was evaluated by a trained sensory panel, assessing six attributes: astringency balance, astringency intensity, acidity intensity, dryness, puckery, and smoothness. 【Result】 In comparison to other spectroscopic quantification methods, the methyl cellulose method showed higher recovery rate, with the recovery rates of mixed tannins added to simulated wine, raw wine, and finished wine being 130.67%, 107.54%, and 76.94%, respectively. Tannin content, as measured by the five spectroscopic methods, decreased with wine age, with the methyl cellulose method (1 247-3 103 mg·L^-1) and the Bate-Smith method (1 643-5 064 mg·L^-1) showing distinct trends. Total phenol (3 145-4 383 mg·L^-1), flavanols (352-1 151 mg·L^-1), and flavonols (107-199 mg·L^-1) content also decreased as wine age increased, with correlation coefficients of 0.71, 0.65, and 0.29 with the methyl cellulose method, respectively. The hydrochloric acid index (0.11-0.35) and ethanol index (0.21-0.44) showed an increasing trend with wine age, while the gelatin index (0.08-0.53) showed no clear trend. Sensory analysis revealed that astringency intensity was most prominent in the 1-3 year group, gradually weakening as the wine aged, with a reduction in puckery and an increase in smoothness. Principal component analysis (PCA) of the tested samples indicated that spectroscopic quantification, flavanol content, astringency intensity, and puckery were the most important factors in most to differentiating between wine samples. Wines in the 1-3 year group had higher tannin content and stronger astringency; wines in the 4-6 year group had weaker astringency but the strongest acidity and dryness; wines in the 7-9 year group had higher tannin polymerization and the weakest astringency but stronger acidity. 【Conclusion】 The methyl cellulose method has been shown to be the most effective for determining total tannin content in dry red wines. Total phenols and flavanols were effective at quantifying both the overall and monomeric tannin characteristics. The hydrochloric acid index and ethanol index were effective indicators of tannin binding characteristics, while astringency intensity and puckery were key indicators for distinguishing the sensory attributes of tannins.

Key words: dry red wine, tannin determination, sensory astringency, sensory evaluation, principal component analysis (PCA)

LI JiaHui, LI YueQi, ZHOU XiaoFang, FAN GuoYuan, LI AiHua, TAO YongSheng. Analysis of Multidimensional Characterization Methods for Tannin Quality in Dry Red Wine[J].Scientia Agricultura Sinica, 2025, 58(10): 2022-2034.

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Figures/Tables 8

Table 1

Table 2

Table 3

Table 4

Spectrophotometric quantification results of tannins in dry red wine"

酒样 Sample	酒龄（年） Wine age (Year)	Folin-Denis法 Folin-Denis method	Bate-Smith法 Bate-Smith method	盐酸香草醛法 Hydrochloric Acid-Vanillin method	蛋白沉淀法 Protein precipitation method	甲基纤维素法 Methyl cellulose method
S1	1—3	1895.34±16.38	3769.35±229.52	1489.35±80.21	482.28±11.22	2077.38±33.88
S2		2011.25±27.58	4194.61±251.31	1387.85±68.51	338.83±3.04	1601.97±59.21
S3		1632.84±18.79	2512.90±150.33	986.35±45.09	259.64±7.43	1536.39±59.57
S4		2083.98±23.45	4445.90±231.67	1432.85±44.27	538.28±8.17	2395.41±36.92
S5		2002.16±36.62	5064.46±296.69	1530.85±47.77	757.17±14.80	3103.61±33.46
S6		1879.43±16.78	3981.98±267.96	1489.35±80.21	553.28±2.58	2080.66±55.62
均值 Mean		1917.50±159.15cd	3994.87±852.60a	1386.43±186.03d	488.25±175.31e	2132.57±575.28bcd
S7	4—6	1512.39±15.34	2222.95±297.68	796.85±69.05	309.94±16.74	1913.88±36.21
S8		1657.84±31.51	2628.88±198.05	803.85±48.71	277.17±3.08	1798.03±43.68
S9		1598.75±36.09	2010.32±289.77	687.35±82.73	287.82±19.18	1758.69±56.64
S10		1502.16±43.17	2570.89±181.38	874.85±83.16	267.51±5.13	1736.83±32.49
S11		1713.52±35.14	2590.22±199.88	1183.35±46.68	281.61±14.01	1763.06±41.71
S12		1716.93±23.04	2628.88±185.83	1293.35±88.48	431.61±8.64	2015.08±52.97
均值 Mean		1616.93±95.33c	2442.02±261.82a	939.43±206.43d	309.28±61.59e	1830.93±110.05bc
S13	7—9	1588.52±15.24	2512.90±178.27	1025.35±74.01	269.94±28.76	1702.95±44.96
S14		1440.80±23.19	2126.30±226.54	776.85±40.80	129.94±25.42	1388.20±33.01
S15		1490.80±34.37	1933.00±177.58	321.35±68.68	277.17±21.48	1594.75±45.31
S16		1349.89±21.16	1643.05±183.32	308.35±89.28	202.03±22.55	1247.21±48.99
S17		1558.98±28.59	2068.31±263.87	665.35±92.04	262.94±15.31	1529.18±34.94
S18		1683.98±19.73	2493.57±180.90	781.85±87.38	335.28±13.03	1894.21±46.72
均值 Mean		1518.83±117.61c	2129.52±334.23a	646.62±261.87d	246.22±71.00e	1559.42±228.75bc

Table 4

Table 5

Analysis results of total phenols, tannin monomers, and aggregation characteristics in the tested wine samples"

酒样 Sample	酒龄（年） Wine age (Year)	总酚 Total phenols (mg∙L^-1)	黄烷醇 Flavanols (mg∙L^-1)	黄酮醇 Flavonols (mg∙L^-1)	盐酸指数 Hydrochloric acid index	乙醇指数 Ethanol index	明胶指数 Gelatin index
S1	1—3	3520.37±57.14	847.91±41.64	156.12±8.41	0.27±0.01	0.23±0.00	0.53±0.05
S2		3821.99±40.55	1020.98±52.98	160.22±1.43	0.26±0.01	0.21±0.01	0.52±0.01
S3		3205.74±163.50	957.79±10.84	176.76±2.89	0.24±0.01	0.21±0.00	0.43±0.01
S4		3758.00±82.66	1151.43±23.57	151.24±2.61	0.24±0.00	0.30±0.02	0.38±0.01
S5		4383.14±144.19	1140.52±57.42	199.15±3.99	0.25±0.01	0.28±0.01	0.33±0.01
S6		3725.07±73.11	856.98±26.70	120.94±5.27	0.19±0.01	0.24±0.01	0.35±0.01
均值 Mean		3735.72±388.45	995.93±132.96	160.74±26.18	0.24±0.03	0.24±0.04	0.42±0.09
S7	4—6	3087.94±46.52	430.47±12.41	114.35±2.98	0.11±0.01	0.25±0.00	0.28±0.01
S8		3477.11±103.91	549.14±15.72	163.28±4.84	0.30±0.00	0.26±0.01	0.13±0.01
S9		3269.45±17.64	646.71±6.29	172.78±8.22	0.32±0.01	0.44±0.01	0.13±0.00
S10		3091.71±204.02	628.07±16.82	166.96±2.54	0.30±0.01	0.31±0.02	0.08±0.00
S11		3349.22±8.60	621.60±32.29	158.73±4.52	0.28±0.00	0.33±0.01	0.20±0.01
S12		3526.58±35.55	679.25±19.00	130.64±1.83	0.24±0.01	0.33±0.01	0.29±0.01
均值 Mean		3300.33±186.77	592.54±90.23	151.12±23.23	0.26±0.08	0.32±0.07	0.19±0.09
S13	7—9	3699.24±186.26	472.99±16.95	178.29±3.40	0.35±0.00	0.33±0.00	0.45±0.01
S14		3208.86±107.98	488.17±8.99	148.26±8.02	0.31±0.00	0.33±0.02	0.46±0.02
S15		3472.54±106.21	435.75±19.58	150.65±3.53	0.21±0.00	0.33±0.01	0.44±0.00
S16		3144.81±227.06	439.67±32.58	127.80±4.12	0.26±0.00	0.38±0.01	0.44±0.02
S17		3675.97±92.12	351.60±11.56	120.22±2.58	0.30±0.00	0.32±0.00	0.28±0.00
S18		3413.62±154.48	540.87±4.50	106.74±0.74	0.27±0.01	0.36±0.01	0.32±0.01
均值 Mean		3435.84±230.26	454.84±63.39	138.66±25.63	0.28±0.05	0.34±0.02	0.40±0.08

Table 5

Fig. 1

Fig. 2

Fig. 3

References 32

[1]	ROUSSERIE P, LACAMPAGNE S, VANBRABANT S, RABOT A, GENY-DENIS L. Wine tannins: Where are they coming from? A method to access the importance of berry part on wine tannins content. MethodsX, 2020, 7: 100961.
[2]	FOLIN O, DENIS W. On phosphotungstic-phosphomolybdic compounds as color reagents. Journal of Biological Chemistry, 1912, 12(2): 239-243.
[3]	BATE-SMITH E C, LERNER N H. Leuco-anthocyanins. 2. Systematic distribution of leuco-anthocyanins in leaves. Biochemical Journal, 1954, 58(1): 126-132. pmid: 13198863
[4]	BROADHURST R B, JONES W T. Analysis of condensed tannins using acidified vanillin. Journal of the Science of Food and Agriculture, 1978, 29(9): 788-794.
[5]	HAGERMAN A E, BUTLER L G. Protein precipitation method for the quantitative determination of tannins. Journal of Agricultural and Food Chemistry, 1978, 26(4): 809-812.
[6]	SARNECKIS C J, DAMBERGS R G, JONES P, MERCURIO M, HERDERICH M J, SMITH P A. Quantification of condensed tannins by precipitation with methyl cellulose: Development and validation of an optimised tool for grape and wine analysis. Australian Journal of Grape and Wine Research, 2006, 12(1): 39-49.
[7]	张亮亮, 汪咏梅, 徐曼, 吴冬梅, 陈笳鸿. 植物单宁化学结构分析方法研究进展. 林产化学与工业, 2012, 32(3): 107-116.
	ZHANG L L, WANG Y M, XU M, WU D M, CHEN J H. Research progress in analytical methods of vegetable tannins. Chemistry and Industry of Forest Products, 2012, 32(3): 107-116. (in Chinese)
[8]	YACCO R S, WATRELOT A A, KENNEDY J A. Red wine tannin structure-activity relationships during fermentation and maceration. Journal of Agricultural and Food Chemistry, 2016, 64(4): 860-869. doi: 10.1021/acs.jafc.5b05058 pmid: 26766301
[9]	SINGLETON V L, ROSSI J A. Colorimetry of total phenolics with phosphomolybdic-phosphotungstic acid reagents. American Journal of Enology and Viticulture, 1965, 16(3): 144-158.
[10]	WÜRDIG G, WOLLER R. Chemie des Weins. Eugen Ulmer GmbH & Co, Stuttgart, 1989.
[11]	RIBÉREAU-GAYON P, GLORIES Y, MAUJEAN A, DUBOURDIEU D. Chimie du vin. Stabilisation et traitements. Traité d’ Œnologie, Vol. 2. Paris: Dunod, 1998: 163-237.
[12]	ARNOLD R A, NOBLE A C, SINGLETON V L. Bitterness and astringency of phenolic fractions in wine. Journal of Agricultural and Food Chemistry, 1980, 28(3): 675-678.
[13]	CHIRA K, PACELLA N, JOURDES M, TEISSEDRE P L. Chemical and sensory evaluation of Bordeaux wines (Cabernet-Sauvignon and Merlot) and correlation with wine age. Food Chemistry, 2011, 126(4): 1971-1977. doi: 10.1016/j.foodchem.2010.12.056 pmid: 25213985
[14]	郭玉呈, 李桂善, 王俊婷, 郭安鹊, 吴帅. 不同类型发酵柿子果酒的质量和抗氧化活性. 食品与发酵工业, 2017, 43(12): 108-113.
	GUO Y C, LI G S, WANG J T, GUO A Q, WU S. Quality evaluation and antioxidant activity of fermented persimmon wines. Food and Fermentation Industries, 2017, 43(12): 108-113. (in Chinese) doi: 10.13995/j.cnki.11-1802/ts.015155
[15]	FIGUEIREDO-GONZÁLEZ M, CANCHO-GRANDE B, SIMAL-GÁNDARA J. Garnacha tintorera-based sweet wines: Chromatic properties and global phenolic composition by means of UV-vis spectrophotometry. Food Chemistry, 2013, 140(1/2): 217-224.
[16]	PINEAU N, GIRARDI A, LACOSTE GREGORUTTI C, FILLION L, LABBE D. Comparison of RATA, CATA, sorting and Napping® as rapid alternatives to sensory profiling in a food industry environment. Food Research International, 2022, 158: 111467.
[17]	ZHAO Q H, DU G R, ZHAO P T, GUO A Q, CAO X M, CHENG C, LIU H, WANG F, ZHAO Y F, LIU Y, WANG X Y. Investigating wine astringency profiles by characterizing tannin fractions in Cabernet Sauvignon wines and model wines. Food Chemistry, 2023, 414: 135673.
[18]	ALEIXANDRE-TUDO J L, BUICA A, NIEUWOUDT H, ALEIXANDRE J L, DU TOIT W. Spectrophotometric analysis of phenolic compounds in grapes and wines. Journal of Agricultural and Food Chemistry, 2017, 65(20): 4009-4026.
[19]	白雪冰, 杨佳宁, 姜醒, 赵宇, 武运. 西北地区干红葡萄酒产地与酒龄的理化判别方法. 农业工程学报, 2022, 38(13): 319-326.
	BAI X B, YANG J N, JIANG X, ZHAO Y, WU Y. Discrimination method for the origin and age of dry red wine by physico-chemical indices in northwest China. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(13): 319-326. (in Chinese)
[20]	MARTINS G R, MONTEIRO A F, DO AMARAL F R L, DA SILVA A S. A validated Folin-Ciocalteu method for total phenolics quantification of condensed tannin-rich açaí (Euterpe oleracea Mart.) seeds extract. Journal of Food Science and Technology, 2021, 58(12): 4693-4702.
[21]	蒋静, 王伟华. 原花青素含量测定方法考察及应用. 食品工业, 2019, 40(4): 168-172.
	JIANG J, WANG W H. Procyanidins content determination method and application. The Food Industry, 2019, 40(4): 168-172. (in Chinese)
[22]	JENSEN J S, RØNSTED N, CORNETT C, JÄGER A K. Direct qualitative and quantitative determination of alkamides in Echinacea purpurea (L.) Moench by UHPLC-DAD-MS-MS. Journal of Agricultural and Food Chemistry, 2008, 56(19): 8903-8908.
[23]	WATRELOT A A. Tannin content in Vitis species red wines quantified using three analytical methods. Molecules, 2021, 26(16): 4923.
[24]	PANDEYA A, RAYAMAJHI S, POKHREL P, GIRI B. Evaluation of secondary metabolites, antioxidant activity, and color parameters of Nepali wines. Food Science & Nutrition, 2018, 6(8): 2252-2263.
[25]	SOTO VÁZQUEZ E, RIO SEGADE S, FERNÁNDEZ GOMEZ E. Incidence of the winemaking technique on metal content and phenolic composition of red wines. International Journal of Food Properties, 2013, 16(3): 622-633.
[26]	曲睿, 陈胜, 唐利萨, 张雪, 张学忠, 刘延琳. 河西走廊新引品种红葡萄酒酚类物质及颜色分析. 食品与发酵工业, 2022, 48(14): 107-112. doi: 10.13995/j.cnki.11-1802/ts.029861
	QU R, CHEN S, TANG L S, ZHANG X, ZHANG X Z, LIU Y L. Analysis of phenolics and color in red wines brewed by grape varieties newly introduced in Hexi Corridor. Food and Fermentation Industries, 2022, 48(14): 107-112. (in Chinese) doi: 10.13995/j.cnki.11-1802/ts.029861
[27]	强文乐, 余飞, 赵晓兰, 李恺安, 陈建军, 马腾臻. 陈酿期不同调配比例对赤霞珠-美乐葡萄酒化学成分和感官品质的影响. 核农学报, 2024, 38(4): 703-714. doi: 10.11869/j.issn.1000-8551.2024.04.0703
	QIANG W L, YU F, ZHAO X L, LI K A, CHEN J J, MA T Z. Effect of different blending ratio on chemical parameters and sensory properties of Cabernet Sauvignon-Merlot wines during barrel aging period. Journal of Nuclear Agricultural Sciences, 2024, 38(04): 703-714. (in Chinese)
[28]	RIOU V, VERNHET A, DOCO T, MOUTOUNET M. Aggregation of grape seed tannins in model wine: Effect of wine polysaccharides. Food Hydrocolloids, 2002, 16(1): 17-23.
[29]	苏洁, 张军翔. 葡萄酒圆润度研究进展. 食品与机械, 2013, 29(2): 238-241.
	SU J, ZHANG J X. Progress on research in rounded taste of wine. Food & Machinery, 2013, 29(2): 238-241. (in Chinese)
[30]	DARIAS-MARTÍN J, CARRILLO-LÓPEZ M, ECHAVARRI-GRANADO J F, DÍAZ-ROMERO C. The magnitude of copigmentation in the colour of aged red wines made in the Canary Islands. European Food Research and Technology, 2007, 224(5): 643-648.
[31]	WANG S Y, OLARTE MANTILLA S M, STOKES J R, SMITH P A, SMYTH H E. pH dominates the temporal perception of astringency sub-qualities and saliva friction response-A study under Iso-pH and Iso-titratable acidity conditions in model wine. Food Hydrocolloids, 2024, 146: 109274.
[32]	WILHELMY C, PAVEZ C, BORDEU E, BROSSARD N. A review of tannin determination methods using spectrophotometric detection in red wines and their ability to predict astringency. South African Journal of Enology and Viticulture, 2021, 42(1): 1-9.

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单宁涩感质量 Astringency quality	定义 Definition	参考标准 Reference standard
涩感平衡度 Astringency balance	对涩感质量的整体评价 Overall evaluation of the astringency quality	S19（2019年吐鲁番楼兰酒庄赤霞珠） S19 (Cabernet Sauvignon, Turpan Loulan Winery, 2019)
涩感强度 Astringency intensity	在口腔中感官期间的最强烈涩感强度 The strongest astringent sensation during sensory evaluation in the mouth	0.50、1.00、2.00、3.00和4.00 g·L^-1单宁酸 0.50, 1.00, 2.00, 3.00, and 4.00 g·L^-1 tannic acid
酸感强度 Acidity intensity	在口腔中感官期间的最强烈酸感强度 The strongest acidity sensation during sensory evaluation in the mouth	0.50 、1.00 、2.00、3.00 和4.00 g·L^-1酒石酸 0.50, 1.00, 2.00, 3.00, and 4.00 g·L^-1 tartaric acid
干燥感 Dryness	口腔中缺乏润滑或干燥的感觉 The sensation of lack of lubrication or dryness in the mouth	0.5 g·L^-1单宁酸 0.5 g·L^-1 tannic acid
褶皱感 Puckering	口腔表面被挤压并放开的反射动作 Reflex action of the mouth's surface being squeezed and released	0.5 g·L^-1硫酸铝+1.0 g·L^-1酒石酸 0.5 g·L^-1 aluminum sulfate + 1.0 g·L^-1 tartaric acid
平滑度 Smoothness	与丝滑感相关的质地 Texture associated with silky smoothness	10.0 g·L^-1甘露蛋白+1.0 g·L^-1单宁酸 10.0 g·L^-1 mannan + 1.0 g·L^-1 tannic acid

酒样 Sample	Folin-Denis法 Folin-Denis method	Bate-Smith法 Bate-Smith method	盐酸香草醛法 Hydrochloric Acid-Vanillin method	蛋白沉淀法 Protein precipitation method	甲基纤维素法 Methyl cellulose method
S-T	89.52±5.36	0.00±0.00	18.37±0.58	5.92±1.47	222.47±2.73
S-P	64.90±2.04	130.16±8.05	0.70±0.10	0.00±0.00	56.79±3.93
S-TP	74.07±0.60	65.72±3.87	4.70±0.00	3.28±0.56	130.67±4.97
B-T	16.52±0.59	65.72±5.47	191.00±19.71	43.82±6.25	153.88±9.67
B-P	10.83±0.49	215.21±33.11	5.00±3.83	13.20±6.43	69.95±16.24
B-TP	6.89±0.42	97.94±26.03	50.00±8.64	18.61±5.91	107.54±10.07
F-T	40.08±6.76	28.58±7.73	37.00±8.43	56.68±3.42	156.94±17.71
F-P	16.89±6.77	92.78±13.20	33.00±8.27	29.27±3.42	39.78±15.61
F-TP	32.35±7.46	69.59±14.81	24.33±8.74	49.24±3.70	76.94±11.00

Analysis of Multidimensional Characterization Methods for Tannin Quality in Dry Red Wine

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