浙江红花油茶优株筛选与综合评价  

Selection and comprehensive evaluation of superior individual plant in Camellia chekiangoleosa

作　　者：董乐 李田[1] 黄文印[1] 王波 徐林初[1] 徐立安[2] 温强[1] DONG Le;LI Tian;HUANG Wenyin;WANG Bo;XU Linchu;XU Li’an;WEN Qiang(Jiangxi Provincial Key Laboratory of Camellia Germplasm Conservation and Utilization,Jiangxi Academy of Forestry,Nanchang 330032,Jiangxi,China;Co-Innovation Center for Sustainable Forestry in Southern China,Nanjing Forestry University,Nanjing 210037,Jiangsu,China)

机构地区：[1]江西省林业科学院江西省油茶种质资源保护与利用重点实验室,江西南昌330032 [2]南京林业大学南方现代林业协同创新中心,江苏南京210037

出　　处：《中南林业科技大学学报》2021年第11期35-45,共11页Journal of Central South University of Forestry & Technology

基　　金：国家自然科学基金项目(31860179,31260184);江西省重点研发计划项目(20201BBF61003,2016IBBF60122);江西省科技支撑项目(20122BBF60125);江西省重大财政专项青年培养项目(2016521101);江西省林业科学院省部级平台开放项目(2019542001)。

摘　　要：【目的】提出浙江红花油茶优树选择标准与筛选方法,以期为发掘和高效利用浙江红花油茶优质种质资源,促进浙江红花油茶良种化进程提供技术参考。【方法】在浙江红花油茶主产区优良林分中通过初选、复选及基于主成分分析法、模糊隶属函数法的优株评价模型构建、层次聚类分析等统计方法进行优株的综合评价。【结果】入选的36个浙江红花油茶优株性状差异明显,11个描述的经济性状变异系数均值为16.63%,总不饱和脂肪酸变异系数最小为1.09%,而油亚比的变异系数最大为29.53%。主成分分析表明前5个主成分能代表11个性状的大部分信息,累计贡献率达84.656%,其中第一主成分反映原始数据信息量的29.491%,油酸、亚油酸、油亚比等性状对第一主成分贡献较大;决定第二主成分大小的主要是果皮厚、鲜出籽率、千粒籽重等性状,其贡献率为20.358%。层次聚类分析将36个浙江红花油茶优株分为6个类群,类群Ⅰ属于高油酸、高出仁率型株系;类群Ⅱ属于高含油率型株系;类群Ⅲ属于高油酸型且综合性状优良的株系;类群Ⅳ属于果皮薄、高出籽率型株系;类群Ⅴ属于高出仁率、高产型株系;类群Ⅵ属于高亚油酸、高产型株系。【结论】制订出了浙江红花油茶高油酸型优树选择的一般标准,并决选出12株表现最优的优株:GHY01、GHY02、GHY03、GHY04、GHY19、GHY20、GHY21、GHY22、GHY32、GHY34、GHY35、GHY36,并按种质资源收集保存标准,嫁接保存了这些优良单株用于后续无性系测定。【Objective】In order to provide technical reference for the exploration and efficient utilization of high-quality germplasm resources of C. chekiangoleosa and to promote the process of improved varieties of C. chekiangoleosa, the selection criteria and screening methods of Camellia chekiangoleosa superior individuals were proposed.【Method】In the superior stands with better germplasm resources in the main distribution area of C. chekiangoleosa, the comprehensive evaluation of superior trees was carried out by means of primary selection, secondary election, superior plant evaluation model based on principal component analysis and Subordinate Function Method and hierarchical cluster analysis.【Result】There were significant differences in the traits of the selected 36 superior plants of C. chekiangoleosa, among the average coefficient of variation of 11 traits was 16.63%. The lowest coefficient of variation of total unsaturated fatty acids was 1.09%, but the coefficient of variation of O/L was the largest(29.53%). Principal component analysis showed that the first five principal components could represent most of the information of 11 traits, and the cumulative contribution rate was 84.656%. Among them, the first principal component reflected 29.491% of the original data information, while oleic acid, linoleic acid and O/L contributed more to the first principal component;the second principal component was mainly determined by fruit skin thickness, fresh seed yield, TKW and with the contribution rate got to 20.358%. According to hierarchical cluster analysis, 36 superior trees of C. chekiangoleosa were divided into six groups, group I belonged to high oleic acid and high kernel rate type;group Ⅱ belonged to high oil content type;group Ⅲ belonged to high oleic acid type and excellent comprehensive characters;group Ⅳ belonged to thin pericarp and high seed rate type;group V belonged to high kernel rate and high yield strains;Group Ⅵ is a high linoleic acid and high yield strain.【Conclusion】The gen

关 键 词：浙江红花油茶 优株筛选 主成分分析 层次聚类分析 综合评价 

分 类 号：S794.4[农业科学—林木遗传育种]