安徽农业科学2024,Vol.52Issue(11) :176-178.DOI:10.3969/j.issn.0517-6611.2024.11.037

基于主成分分析的5个蓝莓品种果实评价

Fruit Evaluation of Five Blueberry Varieties Based on Principal Component Analysis

杨洪涛 余莹 杨正松 杨燕林 和文佳 毕海林 和加卫
安徽农业科学2024,Vol.52Issue(11) :176-178.DOI:10.3969/j.issn.0517-6611.2024.11.037

基于主成分分析的5个蓝莓品种果实评价

Fruit Evaluation of Five Blueberry Varieties Based on Principal Component Analysis

杨洪涛 1余莹 1杨正松 1杨燕林 1和文佳 1毕海林 1和加卫1
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作者信息

  • 1. 云南省农业科学院高山经济植物研究所,云南丽江 674199
  • 折叠

摘要

以从国外引进的5个蓝莓品种为供试材料,研究其在丽江种植条件下果实的外观指标(果实横径、纵径、单果重、果形指数、色泽等)、营养成分(维生素C、可溶性蛋白质、游离氨基酸、可溶性糖、淀粉和花青素等),并利用主成分分析法对所有指标参数进行分析.结果表明:奥尼尔有最优的果形指数(0.86)、最高的单果重(1.87 g)和花青素含量(440.5μg/g),较高的可溶性糖含量(16.69%)、维生素C含量(0.35 mg/g)和游离氨基酸含量(41.11μg/g).主成分分析提取了2个主成分,累计方差贡献率为85.635%,综合评分奥尼尔最高,为最优品种,适合引种栽培及作为育种材料.

Abstract

Taking five blueberry varieties introduced from abroad as the experimental materials,the appearance indicators (such as transverse diameter, vertical diameter, single fruit weight, fruit shape index, color, etc.) and nutritional components (such as vitamin C, soluble pro-tein, free amino acids, soluble sugars, starch and anthocyanins) of their fruits under planting conditions in Lijiang were studied. Principal component analysis was used to analyze all indicator parameters.The results showed that O'Neal had the highest fruit shape index (0.86), single fruit weight (1.87 g) and anthocyanin content (440. 5 μg/g), as well as a higher content of soluble sugars (16. 69%), vitamin C (0.35 mg/g) and free amino acids (41.11 μg/g). Two principal components were extracted in the principal component analysis, with a cu-mulative variance contribution rate of 85.635%. The comprehensive evaluation of O'Neal was the highest, making it the best variety suitable for introduction and cultivation, and also the best variety as a breeding material.

关键词

蓝莓/引种栽培/果实/外观指标/营养成分/主成分分析/丽江

Key words

Blueberries/Introduction and cultivation/Fruit/Appearance indicators/Nutrient composition/Principal component analysis/Lijiang

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基金项目

云南省科技人才与平台计划(院士专家工作站)项目(202205AF150029)

国家自然科学基金项目(32160695)

云南省基础研究计划项目(202101BC070003)

云南省财政厅高山农业科技创新及成果展示转化专项经费(53000021000000-0017045)

云南省农业科学院科研预研项目(2023KYZX-01)

出版年

2024
安徽农业科学
安徽省农业科学院

安徽农业科学

影响因子:0.413
ISSN:0517-6611
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