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茶叶科学 ›› 2020, Vol. 40 ›› Issue (2): 194-204.doi: 10.13305/j.cnki.jts.2020.02.006

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基于计算机视觉的绿茶炒干中在制品理化变化研究

伍洵1,2, 刘飞3, 陈之威2,4, 王玉婉2, 陈琳2, 涂政2, 周小芬5, 杨云飞2, 叶阳2*, 童华荣1*   

  1. 1. 西南大学食品科学学院,重庆 400715;
    2. 中国农业科学院茶叶研究所,浙江 杭州 310008;
    3. 四川省农业科学院茶叶研究所,四川 成都 610066;
    4. 浙江理工大学机械与自动控制学院,浙江 杭州 310018;
    5. 武义县农业农村局,浙江 武义 321200
  • 收稿日期:2019-11-12 修回日期:2019-12-30 出版日期:2020-04-15 发布日期:2020-04-20
  • 通讯作者: *yeyang@tricaas.com,491214217@qq.com
  • 作者简介:伍洵,男,硕士研究生,主要从事茶叶加工方面的研究。
  • 基金资助:
    国家茶叶产业技术体系(CARS-19)、国家重点研发计划专项(2019YFC0840503-2)

Study on the Changes of Physical and Chemical Components during the Frying Process of Green Tea by Computer Vision

WU Xun1,2, LIU Fei3, CHEN Zhiwei2,4, WANG Yuwan2, CHEN Lin2, TU Zheng2, ZHOU Xiaofen5, YANG Yunfei2, YE Yang2*, TONG Huarong1*   

  1. 1. College of Food Science, Southwest University, Chongqing 400715, China;
    2. Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China;
    3. Tea Research Institute of Sichuan Academy of Agricultural Science, Chengdu 610066, China;
    4. Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou 310018, China;
    5. Agricultural and rural Bureau, Wuyi 321200, China
  • Received:2019-11-12 Revised:2019-12-30 Online:2020-04-15 Published:2020-04-20

摘要: 为探明绿茶炒干过程中在制品理化变化规律,利用计算机视觉技术对其外形和色泽的变化进行实时监测,同时测定其主要成分变化。结果显示,随着炒干时间的增加:(1)在制品曲率半径值逐渐下降,10~30 min下降最快;R、G、B和平均灰度值呈先下降后上升的趋势,一致性则呈相反趋势;色相H值显著上升,饱和度S值显著下降。(2)表没食子儿茶素没食子酸酯(EGCG)、表没食子儿茶素(EGC)、叶绿素a、叶绿素b和类胡萝卜素含量显著下降,没食子儿茶素没食子酸酯(GCG)含量显著上升。试验结果表明,曲率半径值与含水率、叶温呈极显著相关,H值与叶绿素a、叶绿素b含量等呈极显著相关,S值与叶绿素a、类胡萝卜素和表儿茶素没食子酸酯(ECG)含量呈极显著相关。EGCG和H值线性拟合度最高,为0.922 1。今后可通过在线监测含水率、叶温和H值等来预测绿茶炒干过程中曲率半径值和化学成分的变化。

关键词: 计算机视觉, 绿茶, 炒干, 曲率半径, 相关性

Abstract: In order to find out the physical and chemical changes during the frying process of green tea, the computer vision technology was applied to real-time monitor the changes of color and shape, and chemical changes were simultaneously measured. The results show that with the increase of frying time, (1) the radius of curvature of unfinished tea gradually decreased, which showed the highest decreasing rate from 10-30 min. R, G, B and average gray value decreased first and then rose. The consistency value was opposite to their trends, with the extreme value in 20 min. H value increased significantly, S value decreased significantly. (2) Epigallocatechin gallate (EGCG), epigallocatechin (EGC), chlorophyll a, chlorophyll b and carotenoids decreased significantly, while gallocatechin gallate (GCG) increased significantly. Experimental results show that the radius of curvature was highly correlated with water content and leaf temperature. H was significantly correlated with chlorophyll a, chlorophyll b. S was significantly correlated with chlorophyll a, carotenoids and epicatechin gallate (ECG). The linear fit of EGCG and H values showed the highest value at 0.922 1. In the future, water content, leaf temperature and H value could be monitored online to predict changes of the radius of curvature and chemical composition during frying.

Key words: computer vision, green tea, the frying process, the radius of curvature, correlation

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