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食品与发酵工业  2019, Vol. 45 Issue (11): 91-98    DOI: 10.13995/j.cnki.11-1802/ts.018939
  研究报告 本期目录 | 过刊浏览 | 高级检索 |
基于生化成分构建不同地区黑茶分类模型
常睿1, 马梦君2, 罗理勇1,3, 余霞1, 代丽凤1, 曾亮1,3*
1(西南大学 食品科学学院,重庆,400715)
2(咸宁市农业科学院,湖北 咸宁,437000)
3(西南大学 茶叶研究所,重庆,400715)
Construction of a model for classifying dark teas from different areas based onbiochemical components
CHANG Rui1, MA Mengjun2, LUO Liyong1,3, YU Xia1, DAI Lifeng1, ZENG Liang1,3*
1(College of Food Science, Southwest University, Chongqing 400715, China)
2 (Xianning Agriculture Academy of Sciences, Xianning 437000, China)
3(Tea Research Institute, Southwest University, Chongqing 400715, China)
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摘要 为实现不同地区黑茶的区分鉴别,对供试4个地区共55个黑茶样本的主要生化成分进行检测,并结合多元统计方法构建分类模型。单因素方差分析结果表明,云南熟普的茶多酚、总黄酮、游离氨基酸、咖啡碱、茶黄素、茶褐素、草酸含量显著高于其他地区,但表儿茶素没食子酸酯、表没食子儿茶素没食子酸酯含量显著低于其他地区;云南熟普的儿茶素组分以简单儿茶素为主,而其他地区的儿茶素组分以酯型儿茶素为主。主成分和系统聚类分析结果表明,云南熟普聚为一类,与其他地区黑茶品质差异明显。Fisher判别分析对不同地区黑茶的分类效果最好,其原始分类正确率为100.0%,交叉验证正确分类率为97.7%,外部验证正确分类率为91.7%;影响判别结果的主要物质为茶褐素、表儿茶素没食子酸酯、表没食子儿茶素、黄酮、儿茶素、表没食子儿茶素没食子酸酯和表儿茶素。
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常睿
马梦君
罗理勇
余霞
代丽凤
曾亮
关键词:  黑茶  不同地区  生化成分  分类模型    
Abstract: With the purpose of distinguishing and identifying dark teas from different areas, the main biochemical components of 55 dark tea samples from four regions were measured, followed by constructing a classification model based on multivariate statistical analysis methods. The results of single factor analysis of variance showed that the contents of tea polyphenols, flavonoids, free amino acids, caffeine, theaflavin, theabrownin, and oxalic acid in Yunnan ripened Pu′er tea were significantly higher than the others, but its contents of epicatechin gallate, epigallocatechin gallate were significantly lower. Moreover, the composition of catechin in Yunnan ripened Pu′er tea was mainly non-galloylated catechins while others were mainly galloylated catechins. Furthermore, the results of principal component analysis and hierarchical cluster analysis could effectively distinguish dark teas from Yunnan province from those of other areas. In addition, Fisher discriminant analysis had the best classifying effect, as its accuracy rate for original classification was 100.0%, and its correct classification rates for cross validation and external validation were 97.7% and 91.7%, respectively. In addition, the main compounds that affected the classification results were theabrownin, epicatechin gallate, epigallocatechin, flavonoids, catechin, epigallocatechin gallate, and epicatechin.
Key words:  dark teas    different areas    biochemical components    classification model
收稿日期:  2018-09-29                出版日期:  2019-06-15      发布日期:  2019-07-08      期的出版日期:  2019-06-15
基金资助: 重庆市农委现代特色效益农业产业体系专项(2017[6]号);茶叶特质性营养品质评价与关键控制点评估(GJFP201700504)
通讯作者:  硕士研究生(曾亮教授为通讯作者,E-mail:zengliangbaby@126.com)   
引用本文:    
常睿,马梦君,罗理勇,等. 基于生化成分构建不同地区黑茶分类模型[J]. 食品与发酵工业, 2019, 45(11): 91-98.
CHANG Rui,MA Mengjun,LUO Liyong,et al. Construction of a model for classifying dark teas from different areas based onbiochemical components[J]. Food and Fermentation Industries, 2019, 45(11): 91-98.
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http://sf1970.cnif.cn/CN/10.13995/j.cnki.11-1802/ts.018939  或          http://sf1970.cnif.cn/CN/Y2019/V45/I11/91
[1] ZHENGWenjun, WAN Xiaochun, BAO Guanhu. Brick dark tea: a review of the manufacture, chemical constituents and bioconversion of the major chemical components during fermentation[J]. Phytochemistry Reviews, 2015, 14(3): 499-523.
[2] 刘艳丰, 黄惠华. 乌龙茶与普洱茶浸提液对胰α-淀粉酶的抑制作用[J]. 食品与发酵工业, 2010,36(7): 54-57.
[3] WU Zhengmei, TENG Jianwen, HUANG Li, et al. Stability, antioxidant activity and in vitro bile acid-binding of green, black and dark tea polyphenols during simulated in vitro gastrointestinal digestion[J]. Rsc Advances, 2015, 5(112): 92 089-92 095.
[4] ZHAO Lanjun, JIA Shuting, TANG Wenru, et al. Pu-erh tea inhibits tumor cell growth by down-regulating mutant p53[J]. International Journal of Molecular Sciences, 2011, 12(11): 7 581-7 593.
[5] DU Wanhong, PENG Shengming, LIU Zhonghua, et al. Hypoglycemic effect of the water extract of Pu-erh tea[J]. Journal of Agricultural and Food Chemistry, 2012, 60(40): 10 126-10 132.
[6] 金裕范. 不同产地、加工工艺及储存年限普洱茶化学成分和药理活性的比较研究[D]. 北京:北京中医药大学, 2012.
[7] 向琴, 高柳,车振明,等. 基于电子鼻的花椒油氧化判别分析[J]. 食品与发酵工业, 2018, 44(7): 288-294.
[8] NING Jingming, LI Daxiang, LUO Xianjingli, et al. Stepwise identification of six tea (Camellia sinensis (L.)) categories based on catechins, caffeine, and theanine contents combined with Fisher discriminant analysis[J]. Food Analytical Methods, 2016, 9(11): 3 242-3 250.
[9] 王淑慧, 龙立梅,宋沙沙,等. 3种名优绿茶的特征滋味成分研究及种类判别[J]. 食品科学, 2016, 37(2): 128-131.
[10] 戴悦雯, 支瑞聪,赵镭,等. 基于龙井茶香气风味特性的品质判定[J]. 食品科学, 2015, 36(10): 110-113.
[11] 苏悦娟, 孔祥军. 六堡茶的地理标志产品保护分析[J]. 安徽农业科学, 2011, 39(34): 21 388-21 390.
[12] 国家质量监督检验检疫总局. GB/T 9833.1—2013 紧压茶[S]. 北京:中国标准出版社,2013.
[13] 国家质量监督检验检疫总局. GB/T 22111—2008 地理标志产品:普洱茶[S]. 北京:中国标准出版社,2008.
[14] XIE Guoxiang, YE Mao, WANG Yungang, et al. Characterization of pu-erh tea using chemical and metabolic profiling approaches[J]. Journal of Agricultural and Food Chemistry, 2009, 57(8): 3 046-3 054.
[15] 黄意欢. 茶学实验技术[M]. 北京:中国农业出版社, 1997: 120-135.
[16] MAGNÉ C, LARHER F. High sugar content of extracts interferes with colorimetric determination of amino acids and free proline[J]. Analytical Biochemistry, 1992, 200(1): 115-118.
[17] BUYSSE J A N, MERCKX R. An improved colorimetric method to quantify sugar content of plant tissue[J]. Journal of Experimental Botany, 1993, 44(10): 1 627-1 629.
[18] 马梦君, 常睿,罗理勇,等. 花香绿茶饮料的生化成分变化及物性特征[J]. 食品科学, 2015, 35(6): 109-113.
[19] 赵仁亮, 胥伟,吴丹,等. 黑毛茶不同产区发花对茯砖茶品质的影响[J]. 食品科学, 2017, 38(21): 8-14.
[20] 雷雨. 我国不同类别黑茶品质差异的研究[D]. 长沙:湖南农业大学, 2010.
[21] 鲍晓华. 普洱茶贮藏年限的品质变化及种类差异研究[D]. 华中农业大学, 2010.
[22] 吕海鹏, 张悦,杨停,等. 普洱茶滋味品质化学成分分析[J]. 食品与发酵工业, 2016, 42(2): 178.
[23] 宁井铭, 张正竹,谷勋刚,等. 云南晒青毛茶HPLC指纹图谱的研究[J]. 食品与发酵工业, 2009, 35(9): 36-40.
[24] 齐桂年, 田鸿,刘爱玲,等. 四川黑茶品质化学成分的研究[J]. 茶叶科学, 2004, 24(4): 266-269.
[25] 陈应娟, 齐桂年,陈盛相,等. 四川黑茶加工过程中感官品质和化学成分的变化[J]. 食品科学, 2012, 33(23): 55-59.
[26] LV Haipeng, ZHANG Yingjun, LIN Zhi, et al. Processing and chemical constituents of Pu-erh tea: a review[J]. Food Research International, 2013, 53(2): 608-618.
[27] 刘盼盼, 钟小玉,许勇泉,等. 茶叶中有机酸及其浸出特性研究[J]. 茶叶科学, 2013, 33(5): 405-410.
[28] 颜鸿飞, 彭争光,李蓉娟,等. GC—TOF MS结合化学计量学用于安化黑茶的识别[J]. 食品与机械, 2017, 33(8): 34-37.
[29] 吴殿廷, 吴迪. 用主成分分析法作多指标综合评价应该注意的问题[J]. 数学的实践与认识, 2015, 45(20): 143-150.
[30] 唐柯, 马磊,徐岩,等. 基于游离氨基酸水平对葡萄酒产地和品种的判别分析[J]. 食品与发酵工业, 2015, 41(9): 159.
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