•  
  •  
 

Corresponding Author(s)

刘亚兵(1991—),男,贵州省茶叶研究所助理研究员,硕士。E-mail:lybgz628@163.com

Abstract

Fermentation is the key to the formation of characteristics and quality of black tea. It is very important to evaluate the fermentability of black tea quickly and accurately. In this paper, the application of artificial sensory evaluation technology, biochemical component detection technology, intelligent biomimetic technology, data fusion technology and intelligent biomimetic equipment in the evaluation of black tea fermentation quality in recent years was reviewed, and the development trend of intelligent biomimetic technology in the evaluation of black tea fermentation in the future was prospected.

Publication Date

4-25-2023

First Page

233

Last Page

240

DOI

10.13652/j.spjx.1003.5788.2022.80762

References

[1] NAVEED M, BIBI J, KAMBOH A A, et al. Pharmacological values and therapeutic properties of black tea (Camellia sinensis): A comprehensive overview[J]. Biomedicine & Pharmacotherapy, 2018, 100: 521-531.
[2] CHEN L, LIU F, YANG Y F, et al. Oxygen-enriched fermentation improves the taste of black tea by reducing the bitter and astringent metabolites[J]. Food Research International, 2021, 148: 110613.
[3] MUTHUMANI T, KUMAR R S S. Influence of fermentation time on the development of compounds responsible for quality in black tea[J]. Food Chemistry, 2007, 101(1): 98-102.
[4] 崔宏春, 张建勇, 赵芸, 等. 发酵条件对红茶茶色素形成的影响研究进展[J]. 食品与机械, 2022, 38(8): 227-233.
[5] 贾梦伟, 张婕, 周顺风, 等. 环境响应水凝胶的非对称结构设计与智能仿生[J]. 材料导报, 2022, 36(12): 175-183.
[6] 刘奇, 欧阳建, 刘昌伟, 等. 茶叶品质评价技术研究进展[J]. 茶叶科学, 2022, 42(3): 316-330.
[7] 马玉青, 方成刚, 夏丽飞, 等. 不同发酵程度对重萎凋“云抗10号”红茶香气成分的影响[J]. 西南农业学报, 2020, 33(4): 760-768.
[8] 刘亚芹, 王辉, 杨霁虹, 等. 基于滋味成分变化的祁门红茶发酵程度差异研究[J]. 茶叶通讯, 2022, 49(2): 193-201.
[9] 杨晨. 基于代谢组学的不同花色种类白茶滋味品质研究[D]. 北京: 中国农业科学院, 2018: 1-6.
[10] 张颖彬, 刘栩, 鲁成银. 中国茶叶感官审评术语的形成与发展现状[J]. 茶叶科学, 2019, 39(2): 123-130.
[11] 尹杰, 范仕胜, 宋勤飞, 等. 工夫红茶发酵过程中的品质变化[J]. 四川农业大学学报, 2012, 30(4): 415-418.
[12] 钟兴刚, 黄怀生, 黎娜, 等. 不同萎凋和发酵处理对“汝城白毛茶”加工红茶品质的影响[J]. 食品与发酵工业, 2022, 48(4): 137-144.
[13] GHOSH S, TUDU B, BHATTACHARYYA N, et al. A recurrent Elman network in conjunction with an electronic nose for fast prediction of optimum fermentation time of black tea[J]. Neural Computing and Applications, 2019, 31(2): 1 165-1 171.
[14] WANG H J, SHEN S, WANG J J, et al. Novel insight into the effect of fermentation time on quality of Yunnan Congou black tea[J]. LWT-London Weekend Television, 2022, 155: 112939.
[15] 费璠, 张梓莹, 胡松, 等. HPLC同时检测红茶中儿茶素和茶黄素含量[J]. 食品与发酵工业, 2022, 48(5): 275-280.
[16] 潘海波. 茶黄素的UPLC分析及其对人卵巢癌细胞抑制作用和机制的研究[D]. 杭州: 浙江大学, 2018: 17-24.
[17] 李伟, 张春燕, 李凤, 等. 超高效液相色谱—串联质谱法同时测定茶叶中儿茶素和茶黄素[J]. 现代预防医学, 2019, 46(22): 4 179-4 184.
[18] 乔阳. 基于GC-MS及电子鼻的云南红茶香气成分的研究[D]. 天津: 天津科技大学, 2016: 20-38.
[19] TAN J F, DAI W D, LU M L, et al. Study of the dynamic changes in the non-volatile chemical constituents of black tea during fermentation processing by a non-targeted metabolomics approach[J]. Food Research International, 2016, 79: 106-113.
[20] 桂安辉. 工夫红茶发酵过程中挥发性物质及品质成分变化研究[D]. 北京: 中国农业科学院, 2016: 35-43.
[21] 温立香, 张芬, 何梅珍, 等. 茶叶品质评价技术的研究现状[J]. 食品研究与开发, 2018, 39(15): 197-204.
[22] CHEN Q S, ZHANG D L, PAN W X, et al. Recent developments of green analytical techniques in analysis of tea's quality and nutrition[J]. Trends in Food Science & Technology, 2015, 43(1): 63-82.
[23] DAO D H, TANG N C, PHAM B T. Monitoring and evaluating the fermentation level of black tea using the random forest model[C]//International Conference on Engineering Research and Applications. [S.l.]: Springer, Cham, 2021: 739-753.
[24] OUYANG Q, ZHAO J W, CHEN Q S. Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm[J].Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 151: 280-285.
[25] ZAREEF M, CHEN Q, OUYANG Q, et al. Rapid screening of phenolic compounds in congou black tea (Camellia sinensis) during in vitro fermentation process using portable spectral analytical system coupled chemometrics[J]. Journal of Food Processing and Preservation, 2019, 43(7): e13996.
[26] 张彬. 基于光学传感器技术的红茶通氧发酵过程在线监测研究[D]. 镇江: 江苏大学, 2017: 41-56.
[27] 刘飞, 李春华, 龚雪蛟, 等. 高光谱成像技术在茶叶中的应用研究进展[J]. 核农学报, 2016, 30(7): 1 386-1 394.
[28] BHATTACHARYA N, SETH S, TUDU B, et al. Detection of optimum fermentation time for black tea manufacturing using electronic nose[J]. Sensors and Actuators B: Chemical, 2007, 122(2): 627-634.
[29] BHATTACHARYA N, BANDYOPADHYAY R, BHUYAN M, et al. Electronic nose for black tea classification and correlation of measurements with “Tea Taster” marks[J]. IEEE Transactions on Instrumentation and Measurement, 2008, 57(7): 1 313-1 321.
[30] SHARMA M, GHOSH D, BHATTACHARYA N. Electronic nose: A new way for predicting the optimum point of fermentation of black tea[J]. Int JEng Sci Invent, 2013, 2: 56-60.
[31] 邹小波, 赵杰文, 殷晓平, 等. 嗅觉可视化技术在白酒识别中的应用[J]. 农业机械学报, 2009, 40(1): 110-113.
[32] CHEN Q, SUN C, OUYANG Q, et al. Classification of different varieties of Oolong tea using novel artificial sensing tools and data fusion[J]. LWT-Food Science and Technology, 2015, 60(2): 781-787.
[33] REN G X, LI T H, WEI Y M, et al. Estimation of Congou black tea quality by an electronic tongue technology combined with multivariate analysis[J]. Microchemical Journal, 2021, 163: 105899.
[34] DENG X J, HUANG G H, TU Q, et al. Evolution analysis of flavor-active compounds during artificial fermentation of Pu-erh tea[J]. Food Chemistry, 2021, 357: 129783.
[35] GUEDES M D V, MARQUES M S, GUEDES P C, et al. The use of electronic tongue and sensory panel on taste evaluation of pediatric medicines: A systematic review[J]. Pharmaceutical Development and Technology, 2021, 26(2): 119-137.
[36] BORAH S, BHUYAN M. Non-destructive testing of tea fermentation using image processing[J]. Insight-Non-Destructive Testing and Condition Monitoring, 2003, 45(1): 55-58.
[37] BORAH S, BHUYAN M. A computer based system for matchingcolours during the monitoring of tea fermentation[J]. Int J Food Sci Technol, 2005, 40(6): 675-682.
[38] SINGH G, KAMAL N. Machine vision system for tea quality determination-Tea quality index (TQI) [J]. IOSR Journal of Engineering, 2013, 3(7): 46-50.
[39] DONG C W, LIANG G Z, HU B, et al. Prediction of Congou black tea fermentation quality indices from color features using non-linear regression methods[J]. Scientific Reports, 2018, 8(1): 10535.
[40] DONG C W, LI J, WANG J J, et al. Rapid determination by near infrared spectroscopy of theaflavins-to-thearubigins ratio during Congou black tea fermentation process[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2018, 205: 227-234.
[41] 董春旺, 梁高震, 安霆, 等. 红茶感官品质及成分近红外光谱快速检测模型建立[J]. 农业工程学报, 2018, 34(24): 306-313.
[42] DONG C W, ZHU H K, WANG J J, et al. Prediction of black tea fermentation quality indices using NIRS and nonlinear tools[J]. Food Science and Biotechnology, 2017, 26(4): 853-860.
[43] 杨崇山, 董春旺, 江用文, 等. 基于高光谱的工夫红茶发酵品质程度判别方法[J]. 光谱学与光谱分析, 2021, 41(4): 1 320-1 328.
[44] YANG C S, ZHAO Y, AN T, et al. Quantitative prediction and visualization of key physical and chemical components in black tea fermentation using hyperspectral imaging[J]. LWT-Food Science and Technology, 2021, 141: 110975.
[45] DONG C W, YANG C S, LIU Z Y, et al. Nondestructive testing and visualization of catechin content in black tea fermentation using hyperspectral imaging[J]. Sensors, 2021, 21(23): 8 051-8 063.
[46] PODRAZKA M, BACZYNSKA E, KUNDYS M, et al. Electronic tongue: A tool for all tastes[J]. Biosensors, 2017, 8(1): 3-27.
[47] ROSS C F. Considerations of the use of the electronic tongue in sensory science[J]. Current Opinion in Food Science, 2021, 40: 87-93.
[48] ESBENSEN K, KIRSANOV D, LEGIN A, et al. Fermentation monitoring using multisensor systems: Feasibility study of the electronic tongue[J]. Analytical and Bioanalytical Chemistry, 2004, 378(2): 391-395.
[49] CETO X, VOELCKER N H, PRIETO-SIMON B. Bioelectronic tongues: New trends and applications in water and food analysis[J]. Biosensors and Bioelectronics, 2016, 79: 608-626.
[50] GHOSH A, BAG A K, SHARMA P, et al. Monitoring the fermentation process and detection of optimum fermentation time of black tea using an electronic tongue[J]. IEEE Sensors Journal, 2015, 15(11): 6255-6 262.
[51] TAN J Z, XU J. Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review[J]. Artificial Intelligence in Agriculture, 2020, 4: 104-115.
[52] 代良超, 乌日娜, 陶冬冰, 等. 智能仿生在食品发酵中的应用及研究进展[J]. 食品工业科技, 2022, 43(19): 14-21.
[53] SHARMILAN T, PREMARATHNE I, WANNIARACHCHI I, et al. Electronic nose technologies in monitoring black tea manufacturing process[J]. Journal of Sensors, 2020, 2 020: 3073104.
[54] SHARMA P, GHOSH A, TUDU B, et al. Monitoring the fermentation process of black tea using QCM sensor based electronic nose[J]. Sensors and Actuators B: Chemical, 2015, 219: 146-157.
[55] 丁煜函, 葛东营, 荆磊, 等. 基于嗅觉可视化技术的眉茶等级分类方法[J]. 食品科学, 2022, 43(24): 335-341.
[56] 陈琳, 叶阳, 董春旺, 等. 基于嗅觉可视化技术的工夫红茶发酵程度判定方法[J]. 茶叶科学, 2017, 37(3): 258-265.
[57] JIN G, WANG Y J, LI L Q, et al. Intelligent evaluation of black tea fermentation degree by FT-NIR and computer vision based on data fusion strategy[J]. LWT-London Weekend Television, 2020, 125: 109216.
[58] JIN G, WANG Y G, LI M H, et al. Rapid and real-time detection of black tea fermentation quality by using an inexpensive data fusion system[J]. Food Chemistry, 2021, 358: 129815.
[59] AN T, HUANG W Q, TIAN X, et al. Hyperspectral imaging technology coupled with human sensory information to evaluate the fermentation degree of black tea[J]. Sensors and Actuators B: Chemical, 2022, 366: 131994.
[60] JANDRIC Z, TCHAIKOVSKY A, ZITEK A, et al. Multivariate modelling techniques applied to metabolomic, elemental and isotopic fingerprints for the verification of regional geographical origin of Austrian carrots[J]. Food Chemistry, 2021, 338: 127924.
[61] ZHOU L, ZHANG C, QIU Z G, et al. Information fusion of emerging non-destructive analytical techniques for food quality authentication: A survey[J]. TrAC Trends in Analytical Chemistry, 2020, 127: 115901.
[62] LI L Q, JIN S S, WANG Y J, et al. Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2021, 247: 119096.
[63] WANG Y J, LI T H, LI L Q, et al. Evaluating taste-related attributes of black tea by micro-NIRS[J]. Journal of Food Engineering, 2021, 290: 110181.
[64] TOZLU B H, OKUMUS H I. A new approach to automation of black tea fermentation process with electronic nose[J]. Automatika: Journal for Control, Measurement, Electronics, Computing & Communications, 2018, 59(3/4): 373-381.
[65] 李杨, 董春旺, 陈建能, 等. 茶叶智能采摘技术研究进展与展望[J]. 中国茶叶, 2022, 44(7): 1-9.
[66] 沈帅, 袁海波, 朱宏凯, 等. 茶叶数字化加工技术研究进展[J]. 中国茶叶, 2022, 44(8): 1-8.
[67] 宁井铭, 颜玲, 张正竹, 等. 祁门红茶加工中氨基酸和儿茶素快速检测模型建立[J]. 光谱学与光谱分析, 2015, 35(12): 3 422-3 426.
[68] 宁井铭, 孙京京, 朱小元, 等. 基于图像和光谱信息融合的红茶萎凋程度量化判别[J]. 农业工程学报, 2016, 32(24): 303-308.
[69] WANG Y W, LIU Y, CUI Q Q, et al. Monitoring the withering condition of leaves during black tea processing via the fusion of electronic eye (e-eye), colorimetric sensing array (CSA), and micro-near-infrared spectroscopy (NIRS) [J]. Journal of Food Engineering, 2021, 300: 110534.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.