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基于主成分分析和聚类分析对11个辣椒品种产量和品质综合评价及引进筛选 被引量:3

The Research on the Yield and Quality of 11 Pepper Varieties with Principal Component Analysis and Cluster Analysis
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摘要 为了综合评价石家庄地区引进的辣椒品种产量和品质,采用主成分、聚类分析法,构建了一种辣椒引种筛选体系,将红齐1号,贵族818,冀长红1号,天红2号,天红15,天红16,腾飞,腾飞14,腾飞15,腾飞58,腾飞59等11个辣椒品种的8个产量、品质指标转化成2个主成分,代表原指标数据83.479%信息,进行品种引进推广综合评价。结果表明:红齐1号的维生素C,产量在所有品种中最高,可作为提取维生素C专用品种;贵族818综合表现最佳,可用于提取维生素C,辣椒素,鲜食等多种用途,推广前景最佳;腾飞14,腾飞,腾飞15,腾飞58,腾飞59含辣椒素量高,可作为提取辣椒素种植或食用。通过主成分分析和聚类分析将多个产量、品质指标转化为少数主成分,对不同辣椒品种进行综合评价的方法,可有效用于辣椒品种引进筛选。 A screening system for pepper introduction was constructed with principal component analysis and cluster analysis to comprehensively evaluate the yield and quality of introduced pepper varieties in Shijiazhuang area.The yield and quality indexes of pepper varieties were converted into two principal components,representing 83.479%information of the original index data.The comprehensive evaluation of the introduction and promotion of pepper varieties was carried out.The results showed that the Vc in Hongqi No.1 was the highest among all varieties,which could be used as a special variety for Vc extraction.Guizu No.818 has the best comprehensive performance and bright future,which is good for eating or extracting Vc and capsaicin.Tengfei 14,Tengfei,Tengfei 15,Tengfei 58,Tengfei 59 contains higher amounts of capsaicin,which are also good vegetables.The pepper varieties could be evaluated and screened with the principal component analysis and cluster analysis through converting the yield and quality indicators into principal components.
作者 李燕 侯大山 张庆银 郭敬华 董灵迪 齐连芬 LI Yan;HOU Dashan;ZHANG QingYin;GUO JingHua;DONG LingDi;QI Lianfen(Shijiazhuang Academy of Agricultural and Forestry Sciences,Shijiazhuang Hebei,050021,China;Shijiazhuang Referral Center for Agricultural Technology;Hebei Academy of Agriculture and Forestry Sciences)
出处 《河北科技师范学院学报》 CAS 2022年第3期22-28,共7页 Journal of Hebei Normal University of Science & Technology
基金 河北省现代农业产业技术体系蔬菜创新团队项目(项目编号:HBCT2018030211)。
关键词 辣椒 产量和品质 综合评价 主成分分析 聚类分析 pepper comprehensive evaluation principal component analysis cluster analysis
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