葡萄酒泥中果胶的提取工艺优化与脱色

唐小华; 杜鑫; 钟琦琦; 贾玉莹; 查飞

doi:10.13386/j.issn1002-0306.2022070372

葡萄酒泥中果胶的提取工艺优化与脱色

doi: 10.13386/j.issn1002-0306.2022070372

唐小华^1,,
杜鑫¹,
钟琦琦¹,
贾玉莹²,
查飞^1,*, ,

1.
西北师范大学化学化工学院，甘肃兰州 730070
2.
甘肃红桥庄园葡萄酒有限公司，甘肃临泽 734207

基金项目: 甘肃省中小企业创新基金（No.22CX3GG020）

详细信息

作者简介:
唐小华（1979−），女，硕士，副教授，研究方向：精细化学品合成与分离技术，E-mail：tom0725@163.com

通讯作者:
查飞（1970−），男，博士，教授，研究方向：环境与能源化工、现代分离分析技术，E-mail：zhafei@nwnu.edu.cn

中图分类号: TS202.3
计量
- 文章访问数: 9
- HTML全文浏览量: 11
- PDF下载量: 0
- 被引次数: 0
出版历程
- 收稿日期: 2022-08-02
- 刊出日期: 2023-05-01

Optimization of Extraction Process and Decolorization of Pectin from Wine Mud

TANG Xiaohua^1
,,
DU Xin¹,
ZHONG Qiqi¹,
JIA Yuying²,
ZHA Fei^{1,*
, ,}

1.
College of Chemistry & Chemical Engineering, Northwest Normal University, Lanzhou 730070, China
2.
Gansu Chateau Hongqiao Wine Co., Ltd., Linze 734207, China

摘要

摘要: 葡萄酒泥是葡萄酒在发酵、贮存期间产生的沉淀物，含有果胶、蛋白质、多酚等物质。为将酒泥中的有效成分分离提取，实现葡萄酒泥的增值利用，本研究以生产干白葡萄酒中的酒泥为原料，通过单因素实验探讨了料液比、pH、提取温度以及提取时间对果胶得率的影响，采用响应面法优化了果胶的提取工艺条件，并使用大孔树脂对果胶进行脱色，最后用红外光谱和HNMR进行结构表征。结果表明，在料液比（葡萄酒泥:水）为1:14 g/mL、pH为2.0、提取温度65 ℃、提取时间90 min时，果胶得率为6.48%，与响应面模型预测值6.50%相近，各因素对果胶得率的影响大小为：料液比>提取温度>提取时间>pH。选用D101大孔树脂对提取的果胶进行脱色，最佳脱色条件为脱色温度25 ℃、pH为2.0、脱色流速为3 BV/h，解吸液为60%（v/v）乙醇、解吸流速3 BV/h，在此条件下，脱色率可达91.75%。红外光谱和HNMR分析表明提取的果胶为α-半乳糖醛酸。研究为葡萄酒泥的成分分析和分离利用提供参考依据。
- 葡萄酒泥 /
- 果胶 /
- 提取工艺优化 /
- 大孔树脂 /
- 脱色 /
- 结构表征
Abstract: Wine mud is the precipitate produced during fermentation and storage, which contains pectin, protein, polyphenols and other substances. To realize the value-added utilization by separating and extracting the effective components of the mud in white wine production, in this study, the effects of material-liquid ratio, pH, extraction temperature and extraction time on the yield of pectin were investigated by the single-factor test, the extraction condition was optimized by the response surface method, the decolorization of pectin was carried out using macroporous resin, and the structure was characterized by infrared spectroscopy and HNMR. The results showed that the yield of pectin was 6.48% on the condition of wine mud:water=1:14 g/mL, pH was 2.0, extraction temperature was 65 ℃ and extraction time was 90 min, which was near to the predicted value of 6.50% by the response surface model. The factors on the yield followed as material-liquid ratio>extraction temperature>extraction time>pH. Decolorized by D101 macroporous resin under the condition that decolorization temperature was 25 ℃, pH was 2.0, decolorization flow rate was 3 BV/h and desorption solution was 60% (v/v) ethanol, desorption flow rate was 3 BV/h, the decolorization rate could reach 91.75%. IR and HNMR analysis showed that pectin extracted was α-galacturonic acid. This study would provide a reference for the separation and utilization of wine mud.
- wine mud /
- pectin /
- optimization of extraction process /
- macroporous resin /
- decolorization /
- structural characterization

HTML全文

图 1 料液比（a）、pH（b）、提取温度（c）和提取时间（d）对果胶得率的影响

Figure 1. Effects of material liquid ratio (a), pH (b), extraction temperature (c) and extraction time (d) on the yield of pectin

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图 2 因素交互作用响应曲面图

Figure 2. Response surface diagram of interaction between various factors

下载: 全尺寸图片幻灯片

图 3 不同型号树脂（a）、树脂用量（b）、pH（c）、温度（d）、脱色流速（e）、乙醇浓度（f）和解吸流速（g）对脱色效果的影响

Figure 3. Effects of different resin types (a), resin dosage (b), pH (c), temperature (d), decolorization flow rate (e), ethanol concentration (f) and desorption flow rate (g) on the decolorization

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图 4 果胶的红外光谱图

Figure 4. IR spectrum of pectin

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图 5 果胶的核磁共振氢谱

Figure 5. HNMR spectrum of pectin

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表 1 响应面因素水平设计

Table 1. Factor level design of response surface

因素		水平
因素	−1	0	1
A料液比（g/mL）	1:10	1:15	1:20
B pH	1	2	3
C提取温度（℃）	60	65	70
D提取时间（min）	60	90	120

下载: 导出CSV

表 2 响应面试验设计条件及结果

Table 2. Design conditions and results of response surface experiment

试验号	A	B	C	D	Y（%）
1	0	−1	−1	0	4.28
2	−1	1	0	0	5.05
3	0	0	1	1	4.09
4	−1	0	1	0	4.31
5	1	1	0	0	3.05
6	0	0	1	−1	4.29
7	0	0	0	0	6.42
8	0	1	1	0	3.88
9	0	−1	0	1	4.45
10	0	1	0	−1	4.22
11	1	−1	0	0	3.71
12	1	0	−1	0	3.08
13	0	0	0	0	6.47
14	1	0	0	−1	3.29
15	0	−1	0	−1	4.76
16	−1	0	0	1	4.99
17	1	0	0	1	3.33
18	0	0	0	0	6.31
19	1	0	1	0	2.89
20	0	1	0	1	4.81
21	0	0	0	0	6.43
22	0	0	−1	−1	4.11
23	0	0	−1	1	4.77
24	0	1	−1	0	4.15
25	−1	0	−1	0	4.47
26	−1	−1	0	0	4.59
27	0	−1	1	0	4.08
28	0	0	0	0	6.45
29	−1	0	0	−1	4.83

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表 3 回归方程的方差分析

Table 3. Variance analysis of regression equation

方差来源	平方和	自由度	均方	F值	P值	显著性
模型	30.51	14	2.18	302.24	<0.0001	**
A	6.59	1	6.59	913.41	<0.0001	**
B	0.042	1	0.042	5.83	0.0301	*
C	0.1452	1	0.1452	20.14	0.0005	**
D	0.0736	1	0.0736	10.21	0.0065	**
AB	0.3136	1	0.3136	43.49	<0.0001	**
AC	0.0002	1	0.0002	0.0312	0.8623
AD	0.0036	1	0.0036	0.4993	0.4914
BC	0.0012	1	0.0012	0.1699	0.6864
BD	0.2025	1	0.2025	28.08	0.0001	**
CD	0.1849	1	0.1849	25.64	0.0002	**
A²	12.79	1	12.79	1773.95	<0.0001	**
B²	6.16	1	6.16	853.87	<0.0001	**
C²	11.01	1	11.01	1527.36	<0.0001	**
D²	4.8	1	4.8	666.12	<0.0001	**
残差	0.1009	14	0.0072
失拟项	0.0854	10	0.0085	2.2	0.2323	不显著
纯误差	0.0155	4	0.0039
总和	30.61	28
R²	0.9967
R²_adj	0.9934
注：：差异显著，P<0.05；*：差异高度显著，P<0.01。

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