摘要
以“山东大绵球”与“新宾软籽”杂交F1代(151株)混交获得的F2代群体中10个性状较好的软核山楂株系为研究对象,测定其果实外观性状、内在品质、营养品质共19个指标,分析各株系的品质性状差异性,并运用主成分分析进行综合评价。结果表明:19个果实品质性状均有显著性差异,部分性状表现较好,单果重最高达5.27 g(株系18-27,下同),果皮颜色主要为鲜红色,可食率最高达90.96%(17-17),维生素C含量最高达965.2 mg/kg(16-35)。通过主成分分析提取出了6个主成分,累计贡献率达93.695%,其中第一主成分(27.76%)和第二主成分(25.29%)累计贡献率最高,主要包括可溶性糖、果实颜色、果实硬度、含水量等指标。综合评分较高的是20-9、15-38和25-37这3个株系,均可作为优良软核山楂种质资源加以利用。
Ten soft-endorcarp hawthorn strains with good traits in the F2-generation population obtained from the F1 cross population(151 plants)of"Shandong Damianqiu"×"Xinbin Soft Seed"were used as research objects.A total of 19 indices of fruit appearance,intrinsic quality and nutritional quality were measured to analyze the differences in quality traits among the strains,and a comprehensive evaluation was conducted using principal component analysis.The results showed that there were significant differences in the 19 fruit quality traits,and some of the traits performed better;the highest weight per fruit reached 5.27 g(strain 18-27),the skin color was mainly bright red,the highest edible rate reached 90.96%(strain 17-17),and the highest vitamin C content was 965.2 mg/kg(strain 16-35).Six principal components were extracted by principal component analysis,with a cumulative contribution of 93.695%.Among them,the first and second principal components,including soluble sugar,fruit color,fruit hardness,and water content,had two highest cumulative contribution rates,reaching 27.76%and 25.29%,respectively.Three strains with high overall scores were strains 20-9,15-38,and 25-37,all of which can be utilized as excellent soft-endorcarp hawthorn germplasm resources.
作者
王昊
张吉军
郭晓雨
朱京涛
WANG Hao;ZHANG Ji-jun;GUO Xiao-yu;ZHU Jing-tao(College of Horticultural Science and Technology,Hebei Normal University of Science and Technology,Hebei Key Laboratory of Horticultural Germplasm Excavation and Innovative Utilization,Qinhuangdao 066000,PRC)
出处
《湖南农业科学》
2023年第4期76-81,共6页
Hunan Agricultural Sciences
基金
河北省科技厅项目(20537101D)。
关键词
软核山楂
果实品质
主成分分析
综合评价
soft-endorcarp hawthorn
fruit quality
principal component analysis
comprehensive evaluation
