Genetic Diversity of Mature Leaves of Tea Germplasms Based on Image Features

CHEN Qiyu; MA Jianqiang; CHEN Jiedan; CHEN Liang

doi:10.13305/j.cnki.jts.2022.05.002

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Journal of Tea Science ›› 2022, Vol. 42 ›› Issue (5) : 649-660. DOI: 10.13305/j.cnki.jts.2022.05.002

Research Paper

Genetic Diversity of Mature Leaves of Tea Germplasms Based on Image Features

CHEN Qiyu, MA Jianqiang, CHEN Jiedan^*, CHEN Liang^*

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Abstract

The genetic diversity of tea germplasm in China is an important basis for its effective utilization. In this study, the genetic diversity of tea germplasm in China was elucidated by statistical analysis, principal component analysis, correlation analysis and cluster analysis of 18 image features of mature leaves from 504 tea germplasm accessions preserved in China National Germplasm Hangzhou Tea Repository. The results show that the coefficient of variation and genetic diversity index of this population were 15.97% and 1.98, respectively. Among different provinces, the average coefficient of variation was the largest in Fujian province, which was 16.29%. The data of Jiangsu province was on the bottom, accounting for 10.58%. Zhejiang province had the highest average genetic diversity index at 2.01. The average genetic diversity index of Chongqing municipality reached the lowest point, occupying 1.67. The dimension of 18 image features were streamlined by principal component analysis and characterized into 4 principal components, with a cumulative contribution rate of 82.63%, and 12 image features were screened out from 18 image features with significant differences. According to the image features, the tea germplasms were clustered into 6 groups. The results provided a theoretical basis and reference for further exploration and utilization of tea germplasm in China.

Key words

genetic diversity / germplasm / image characteristics / mature leaves / tea plant

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CHEN Qiyu, MA Jianqiang, CHEN Jiedan, CHEN Liang. Genetic Diversity of Mature Leaves of Tea Germplasms Based on Image Features[J]. Journal of Tea Science. 2022, 42(5): 649-660 https://doi.org/10.13305/j.cnki.jts.2022.05.002

References

[1] Opuwari C, Monsees T.Green tea consumption increases sperm concentration and viability in male rats and is safe for reproductive, liver and kidney health[J]. Scientific Reports, 2020, 10(1): 15269. doi: 10.1038/s41598-020-72319-6.
[2] Qiao Q, Zhu M.Development strategies of tea culture tourism in the age of experience economy[J]. Journal of Landscape Research, 2010, 2(12): 97-99.
[3] Meegahakumbura M K, Wambulwa M C, Thapa K K, et al.Indications for three independent domestication events for the tea plant (Camellia sinensis (L.) O. Kuntze) and new insights into the origin of tea germplasm in China and India revealed by nuclear microsatellites[J]. PloS ONE, 2016, 11(5): e0155369. doi: 10.1371/journal.pone.0155369.
[4] 冯夏莲, 何承忠, 张志毅, 等. 植物遗传多样性研究方法概述[J]. 西南林学院学报, 2006, 26(1): 69-74, 79.
Feng X L, He C Z, Zhang Z Y, et al.Summarization on research methods of plant genetic diversity[J]. Journal of Southwest Forestry College, 2006, 26(1): 69-74, 79.
[5] 蒋会兵, 宋维希, 矣兵, 等. 云南茶树种质资源的表型遗传多样性[J]. 作物学报, 2013, 39(11): 2000-2008.
Jiang H B, Song W X, Yi B, et al.Genetic diversity of tea germplasm resources in Yunnan province based on phenotypic characteristics[J]. Acta Agronomica Sinica, 2013, 39(11): 2000-2008.
[6] 黄政, 李芳, 尹杰, 等. 贵州低热河谷地方茶树种质资源基于表型性状的遗传多样性分析[J/OL]. 分子植物育种, 2021: 1-28 [2022-01-13]. http://kns.cnki.net/kcms/detail/46.
1068.s.20210702.1115.004.html.Huang Z, Li F, Yin J, et al. Analysis of genetic diversity based on phenotypic traits of local tea germplasm resources in low heat valley of Guizhou province [J/OL]. Molecular Plant Breeding, 2021: 1-28 [2022-01-13]. http://kns.cnki.net/kcms/detail/46.1068.s.20210702.1115.004.html.
[7] 李华锋, 滕杰, 杨家干, 等. 连南栽培型古茶树资源叶片表型性状遗传多样性及聚类分析[J]. 中国农学通报, 2016, 32(36): 109-114.
Li H F, Teng J, Yang J G, et al.Genetic diversity and cluster analysis of leaf phenotypic traits of Liannan cultivated ancient tea[J]. Chinese Agricultural Science Bulletin, 2016, 32(36): 109-114.
[8] 潘宇婷, 袁正仿, 袁红雨, 等. 河南省地方茶树种质资源表型性状遗传多样性研究[J]. 信阳师范学院学报(自然科学版), 2018, 31(4): 578-585.
Pan Y T, Yuan Z F, Yuan H Y, et al.Diversity analysis of phenotypic characteristics for Henan local tea germplasm resources[J]. Journal of Xinyang Normal University (Natural Science Edition), 2018, 31(4): 578-585.
[9] 张慧春, 周宏平, 郑加强, 等. 植物表型平台与图像分析技术研究进展与展望[J]. 农业机械学报, 2020, 51(3): 1-17.
Zhang H C, Zhou H P, Zheng J Q, et al.Research progress and prospect in plant phenotyping platform and image analysis technology[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(3): 1-17.
[10] Dong C W, Zhu H K, Zhao J W, et al.Sensory quality evaluation for appearance of needle-shaped green tea based on computer vision and nonlinear tools[J]. Journal of Zhejiang University-SCIENCE B, 2017, 18(6): 544-548.
[11] Xu M, Wang J, Gu S.Rapid identification of tea quality by E-nose and computer vision combining with a synergetic data fusion strategy[J]. Journal of Food Engineering, 2019, 241: 10-17.
[12] 王文明, 肖宏儒, 陈巧敏, 等. 基于图像处理的茶叶智能识别与检测技术研究进展分析[J]. 中国农机化学报, 2020, 41(7): 178-184.
Wang W M, Xiao H R, Chen Q M, et al.Research progress analysis of tea intelligent recognition and detection technology based on image processing[J]. Journal of Chinese Agricultural Mechanization, 2020, 41(7): 178-184.
[13] 刘自强. 鲜茶叶图像特征提取及在茶树品种识别中的应用研究[D]. 长沙: 湖南农业大学, 2014.
Liu Z Q.Features extraction of fresh tea images and its application on the recognition of tea varieties [D]. Changsha: Hunan Agricultural University, 2014.
[14] 王键, 梁春娇, 郭俊先, 等. 基于OpenCV确定植物叶片面积[J]. 分子植物育种, 2020, 18(6): 2023-2027.
Wang J, Liang C J, Guo J X, et al.Measurement of plant leaf area based on OpenCV[J]. Molecular Plant Breeding, 2020, 18(6): 2023-2027.
[15] 王红军, 熊俊涛, 黎邹邹, 等. 基于机器视觉图像特征参数的马铃薯质量和形状分级方法[J]. 农业工程学报, 2016, 32(8): 272-277.
Wang H J, Xiong J T, Li Z Z, et al.Potato grading method of weight and shape based on imaging characteristics parameters in machine vision system[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(8): 272-277.
[16] 高程程, 惠晓威. 基于灰度共生矩阵的纹理特征提取[J]. 计算机系统应用, 2010, 19(6): 195-198.
Gao C C, Hui X W.GLCM-based texture feature extraction[J]. Computer Systems & Applications, 2010, 19(6): 195-198.
[17] 毕智健, 张若宇, 齐妍杰, 等. 基于机器视觉的番茄成熟度颜色判别[J]. 食品与机械, 2016, 32(12): 133-136.
Bi Z J, Zhang R Y, Qi Y J, et al.Tomato maturity color discrimination based on machine vision[J]. Food & Machinery, 2016, 32(12): 133-136.
[18] 王述民, 曹永生, Redden R J, 等. 我国小豆种质资源形态多样性鉴定与分类研究[J]. 作物学报, 2002, 28(6): 727-733.
Wang S M, Cao Y S, Redden R J, et al.The morphological diversity and classification of adzuki bean [Vigna angularis (Willd) Ohwi & Ohashi] germplasm resources in China[J]. Acta Agronomica Sinica, 2002, 28(6): 727-733.
[19] 张羽翔, 朱志雄, 陈石泉, 等. 海南八门湾红树林保护区海水富营养化评价及其主成分分析[J]. 海洋湖沼通报, 2021, 43(5): 159-168.
Zhang Y X, Zhu Z X, Chen S Q, et al.Eutrophication assessment and principal component analysis of Bamen mangrove natural reserve of Hainan[J]. Transactions of Oceanology and Limnology, 2021, 43(5): 159-168.
[20] 乔婷婷. 茶树资源遗传多样性及其表型性状关联EST-SSR位点的初步鉴定[D]. 北京: 中国农业科学院, 2010.
Qiao T T.Genetic diversity of tea (Camellia sinensis (L.) O. Kuntze) and association analysis of phenotypic traits with EST-SSR markers [D]. Beijing: Chinese Academy of Agricultural Sciences, 2010.
[21] 丁帅涛, 程晓梅, 张亚, 等. 陕西古茶树种质资源表型性状遗传多样性研究[J]. 广东农业科学, 2018, 45(2): 52-60.
Ding S T, Chen X M, Zhang Y, et al.The research on phenotypic traits genetic diversity of the ancient tea germplasm resources in Shaanxi province[J]. Guangdong Agricultural Sciences, 2018, 45(2): 52-60.
[22] 陶萍, 宋燚, 张晴晖, 等. 云南普洱茶种古茶树资源表型性状数据分析研究[J]. 西部林业科学, 2020, 49(6): 144-151, 157.
Tao P, Song Y, Zhang Q H, et al.Data analysis of phenotypic characteristics of ancient tea resources of Yunnan Pu'er tea species[J]. Journal of West China Forestry Science, 2020, 49(6): 144-151, 157.
[23] 林丽惠. 基于纹理特征的武夷岩茶叶片分类方法[J]. 武夷学院学报, 2019, 38(12): 14-17.
Lin L H.Research on leaf classification for Wuyi rock tea based on textural features[J]. Journal of Wuyi University, 2019, 38(12): 14-17.