中国蔬菜 ›› 2024, Vol. 1 ›› Issue (1): 29-37.DOI: 10.19928/j.cnki.1000-6346.2024.0003

• 研究论文 • 上一篇    下一篇

基于多元统计分析对芥菜营养品质的综合评价

李建忠1,2,戴昀1,叶鑫雨1,2,李国亮1,章时蕃1,李菲1,张慧1,袁凌云2,陈国户2,汪承刚2,张淑江1*   

  1. 1 中国农业科学院蔬菜花卉研究所,蔬菜生物育种全国重点实验室,北京 100081;2 安徽农业大学园艺学院,安徽省园艺作物育种工程实验室,安徽合肥 230036
  • 收稿日期:2023-06-01 修回日期:2023-08-08 出版日期:2024-01-01 发布日期:2024-01-10
  • 通讯作者: 张淑江,男,研究员,博士生导师,专业方向:十字花科蔬菜遗传育种,E-mail:zhangshujiang@caas.cn
  • 作者简介:李建忠,男,硕士研究生,专业方向:蔬菜学,E-mail:18335863430@163.com
  • 基金资助:
    中国农业科学院创新工程项目(CAAS-ASTIP-IVFCAAS),农业农村部园艺作物生物学与种质创制重点实验室项目,国家大宗蔬菜产业技术体系项目(CARS-23-A-14)

Comprehensive Evaluation of Nutritional Quality Using Multivariate Statistical Analysis in Brassica juncea

LI Jianzhong1,2,DAI Yun1,YE Xinyu1,2,LI Guoliang1,ZHANG Shifan1,LI Fei1,ZHANG Hui1,YUAN Lingyun2,CHEN Guohu2,WANG Chenggang2,ZHANG Shujiang1*   

  1. 1State Key Laboratory of Vegetable Biobreeding,Institute of Vegetables and Flowers,Chinese Academy of Agricultural Sciences,Beijing 100081,China;2College of Horticulture,Anhui Provincial Engineering Laboratory of Horticultural Crop Breeding,Anhui Agricultural University,Hefei 230036,Anhui,China
  • Received:2023-06-01 Revised:2023-08-08 Online:2024-01-01 Published:2024-01-10

摘要: 为建立芥菜营养品质标准评价体系,筛选优良品质的芥菜品种,采用多元统计分析方法(相关性分析、主成分分析、模糊数学隶属函数分析、聚类分析),对14 份芥菜材料的干物质、VC、粗蛋白、粗纤维、葡萄糖、果糖、草酸、苹果酸、柠檬酸9 个品质指标进行综合评价。结果表明:14 份芥菜材料的9 个品质指标均存在显著差异,变异系数在16.46%~66.67% 之间,说明不同芥菜材料单一指标间的差异较大。主成分分析综合品质得分较高的是1917012、1917396、1917381,较低的是1917351、祥瑞182;通过模糊数学隶属函数分析和聚类分析评价,营养品质优良的芥菜材料为1917396、1917397、1917381,较差的为1917152、祥瑞182。综合来看,芥菜材料1917396 和1917381 表现优异,营养品质好。这2 份材料的干物质、VC 等含量较高,也证明该评价体系可以极大的消除单一指标的差异。

关键词: 芥菜, 营养品质, 多元统计分析, 综合评价

Abstract: To establish a standardized evaluation system for assessing the nutritional quality and to identify varieties of superior quality in Brassica juncea,this study comprehensively assessed nine quality indices:dry matter,vitamin C(VC),crude protein,crude fiber,glucose,fructose,oxalic acid,malic acid,and citric acid across 14 Brassica juncea lines.Multivariate statistical analysis methods,including correlation analysis,principal component analysis,fuzzy mathematical subordinate function analysis,and cluster analysis were employed in this study.The results revealed significant difference at coefficients of variation ranging from 16.46% to 66.67%.This indicated substantial variability among the individual indices of different Brassica juncea lines.Principal component analysis identified the‘1917012’‘1917396’and‘1917381’lines showing superior overall performance,whereas the‘1917351’and‘Xiangrui 182’lines were less favorable.According to fuzzy mathematical affiliation function analysis and cluster analysis,the‘1917396’‘1917397’and‘1917381’lines contained high nutritional quality,in contrast to the‘1917152’and‘Xiangrui 182’lines.Consequently,the‘1917396’and‘1917381’lines excelled in this evaluation system,indicating that they were rich in dry matter,VC,etc.This study demonstrated that the evaluation method could effectively decrease the impact of individual index variations,offering guidance for the selection.

Key words: Brassica juncea, nutritional quality, multivariate statistical analysis, comprehensive evaluation