园艺学报 ›› 2018, Vol. 45 ›› Issue (7): 1371-1381.doi: 10.16420/j.issn.0513-353x.2017-0794

• 研究报告 • 上一篇    下一篇



  1. (中国热带农业科学院南亚热带作物研究所,农业部热带果树生物学重点实验室,广东湛江 524091)
  • 出版日期:2018-07-25 发布日期:2018-07-25

Assessment of Mineral Elements Contents at the Mango Germplasm Level Based on Factor Analysis and Cluster Analysis

MA Xiaowei,MA Yongli,WU Hongxia,ZHOU Yigang,SU Muqing,and WANG Songbiao*   

  1. (Ministry of Agriculture Key Laboratory of Tropical Fruit Biology,South Subtropical Crops Research Institute,Chinese Academy of Tropical Agricultural Sciences,Zhanjiang,Guangdong 524091,China)
  • Online:2018-07-25 Published:2018-07-25

摘要: 以53个杧果品种的套袋果实为试材,测定其10个矿质元素含量,运用因子分析和聚类分析等统计方法对矿质元素含量特征进行分析。结果表明,不同品种果实中矿质元素含量存在显著差异,10种元素平均含量依次为:K > P > Mg > Ca > Na > Mn > Fe > Zn > Cu > B,变异系数在16.79%(P)~ 52.28%(Mn)之间;各矿质元素含量均服从正态分布;Mg与Mn、Zn、Cu、P、K、B之间,Zn、Cu、K两两之间,P与K之间均呈显著正相关;K、P、Ca、Mn和B是杧果果实的特征矿质元素;53个品种可以分为4类:(1)高K、P、Mg、Zn和Cu 含量的品种11个,(2)高Na和Fe含量的品种18个,(3)低Mg、Zn和K含量的品种8个,(4)低Ca、B和Mn含量的品种16个。

关键词: 杧果, 矿质元素, 因子分析, 聚类分析

Abstract: Contents of 10 mineral elements in bagged fruits of 53 mango cultivars were determined and analyzed by factor analysis and cluster analysis. The results showed that there were significant differences with wide variability regarding the mineral content in different cultivars,and the average contents of 10 mineral elements followed by the order of K > P > Mg > Ca > Na > Mn > Fe > Zn > Cu > B. The coefficient of variation ranged from 16.79%(P)–52.28%(Mn). All of the 10 mineral contents distributed normally. Significant correlations were found between Mg and Mn,Zn,Cu,P,K and B,and between P and K. Zn,Cu and K were significantly correlated with each other. K,P,Ca,Mn and B were the characteristic elements of mango. The 53 mango cultivars were divided into 4 clusters;(1) 11 cultivars with high K,P,Mg,Zn and Cu contents,(2) 18 cultivars with high Na and Fe contents,(3) 8 cultivars with low Mg,Zn and K contents,and (4) 16 cultivars with low Ca,B and Mn contents.

Key words: mango, mineral element, factor analysis, cluster analysis