摘要
为筛选适宜河北省露地栽培的加工辣椒品种,从不同地区引进10个品种进行筛选试验,对各品种辣椒的生长、果实、产量相关指标进行主成分分析,并对综合评价较高和田间表现较优的品种进行品质指标测定。主成分分析结果表明:前3个主成分特征值均大于1,并且累计方差贡献率达到83.81%,能综合辣椒生长和产量的大部分指标,且云辣素1号、天宇、艳红等综合得分较高。综合主成分分析以及单株结果数、红绿果比和667 m^(2)产量等田间表现,选取综合指标较优的深红8号、美红9号、天宇、内黄新一代和湘辣702共5个品种进行品质指标分析;其中,天宇的可溶性蛋白、二氢辣椒素和降二氢辣椒素含量均高于其他品种,且产量也存在优势。因此,初步筛选出天宇作为河北省加工辣椒的推广品种。
In order to select cultivars of processing pepper suitable for open-field cultivation in Hebei province,10 cultivars were introduced from different regions for screening test.Principal Component Analysis was carried out on the growth,fruit and yield indicators of each cultivar of pepper,and the quality indicators of pepper cultivars with higher comprehensive evaluation and better field performance were determined.The results of Principal Component Analysis showed that the eigenvalues of the first three principal components were all more than 1,and the contribution rate of cumulative variance reached 83.81%,which could integrate most of the growth and yield indicators of pepper,and the comprehensive scores of'Yunlasu No.1''Tianyu''Yanhong'were higher.Based on the results of Principal Component Analysis and field performance such as number of fruits per plant,ratio of red and green fruits,and yield per 667 m^(2),five cultivars with better comprehensive indicators were selected for quality analysis,including'Shenhong No.8''Meihong No.9''Tianyu''Neihuang new generation'and'Xiangla 702'.The contents of soluble protein,dihydrocapsaicin and dehydrocapsaicin of'Tianyu'were all higher than those of other cultivars,and the yield also had advantages.Therefore,'Tianyu'was preliminarily selected as a suitable cultivar of processing pepper for promotion in Hebei province.
作者
张庆银
王子凡
王丹丹
李燕
师建华
牛瑞生
齐连芬
ZHANG Qingyin;WANG Zifan;WANG Dandan;LI Yan;SHI Jianhua;NIU Ruisheng;QI Lianfen(Shijiazhuang Academy of Agriculture and Forestry Sciences,Shijiazhuang 050041,China)
出处
《蔬菜》
2022年第7期17-21,共5页
Vegetables
基金
河北省现代农业产业技术体系蔬菜创新团队(HBCT2018030211)。
关键词
加工辣椒
品种
筛选
主成分分析
品质
processing pepper
cultivar
selection
Principal Component Analysis
quality
