园艺学报 ›› 2019, Vol. 46 ›› Issue (2): 237-251.doi: 10.16420/j.issn.0513-353x.2018-0373

• 研究论文 • 上一篇    下一篇



  1. 福建省农业科学院果树研究所,福建省落叶果树工程技术研究中心,福州 350013
  • 出版日期:2019-02-25 发布日期:2019-02-25
  • 基金资助:


Fruit Character Diversity Analysis and Numerical Classification of Local Pear Germplasm Resources in Fujian

ZENG Shaomin,CHEN Xiaoming,and HUANG Xinzhong*   

  1. Fruit Research Institute,Fujian Academy of Agricultural Sciences,Research Centre for Engineering Technology of Fujian Deciduous Fruits,Fuzhou 350013,China
  • Online:2019-02-25 Published:2019-02-25


对保存的50份福建省地方梨资源的26个果实性状进行数据采集,分析果实性状的分布频率、变异系数和Shannon-Weaver指数,应用Q型和R型聚类分析法对种质和性状进行分类,并基于果实性状进行主成分分析。结果表明:(1)所收集种质的果实描述性状多样性丰富,以果点明显、果锈多、果面粗糙、果肉脆、风味酸甜、无涩味、果心小和成熟期为9月的种质居多,分别占92%、52%、54%、50%、50%、70%、54%和80%。(2)数量性状中维生素C含量变异系数(67.60%)最大,其次为可滴定酸含量(48.26%)、糖酸比(42.22%)和固酸比(41.14%)。(3)描述性状Shannon-Weaver指数范围0.324 ~ 1.660,其中颜色和形状较高,多样性最丰富,而数量性状Shannon-Weaver指数范围达1.698 ~ 2.074,表现出更丰富的多样性。(4)Q型聚类分析在欧式距离为14.71时将供试种质分为5个组,组内具有一定的特征,组间存在差异,但并未发现按地域聚类的趋势;R型聚类分析在相关系数1.236处将果实性状聚为5组,多数性状间表现两两相关,部分性状间逻辑相关性明显。(5)主成分分析发现前10个主成分反映86.545%的贡献率,各性状贡献率较为分散,性状变异具有多向性;第1主成分的正向增长有利于提高果实内在品质,而第2、4主成分的正向增长有利于提高果实外观品质,第3主成分负向增长有利于增大果实大小。

关键词: 梨, 种质资源, 果实, 性状, 多样性, 数量分类


Twenty-six fruit characters were collected and determined from 50 local pear germplasm resources in Fujian Province. Distribution frequency,coefficient of variation,and Shannon-Weaver index were analyzed. Q cluster,R cluster and principal component analysis were used to evaluate the germplasm resources and characters. The results showed that the diversity of local pear fruit description characters was abundant. Conspicuous fruit dot,many fruit russeting,rough skin,crisp flesh,sour-sweet flavor,absent astringency,small fruit core and maturity in September had more proportion than other corresponding descriptors,accounting for 92%,52%,54%,50%,50%,70%,54% and 80%,respectively. The average variation coefficient of content of vitamin C and titratable acid,ratio of SS and TA,and ratio of TSS and TA was 67.60%,48.26%,42.22% and 41.14%,respectively,which was higher than that of other numerical characters. The fruit peel color and shape was found to have the richest diversity among 13 description characters,with 1.660 and 1.605 of Shannon-Weaver index. And the indexes of 13 numerical characters range from 1.698 to 2.074,which was higher than that of 13 description characters with 0.324 to 1.660 of Shannon-Weaver index,indicating that the numerical characters had richer diversity than description characters. Q cluster analysis showed that all the tested germplasm resources were divided into five groups at the Euclidean distance of 14.71,and there were differences of fruit characters among difference groups without regional trend. R cluster analysis showed that 26 characters closely related were significantly clustered into five groups at coefficient of 1.236. Twenty-six characters were mainly composed of 10 independent principal components with the cumulative contribution rate of 86.545%,which showed dispersion of contribution rate and multi-directional variation of local pear fruit characters. Positively increasing the first principal component factor will be favorable for improving the fruit interior quality,while positively increasing the second and fourth principal component factor will be favorable for improving the fruit exterior quality,and negatively increasing the third principal component factor will be beneficial to increase fruit size.

Key words: pear, germplasm resource, fruit, character, diversity, numerical classification