摘要
为揭示马铃薯主要农艺性状的变异规律,筛选出适宜冬闲稻田种植的优良品种,采用双因素分析、相关性分析和主成分分析对6个品种连续3年(2018-2021年)的主要农艺性状进行综合评价。结果显示,不同品种主要农艺性状差异显著或极显著。参试品种各性状年份效应和基因型效应极显著,年份效应大于基因型效应,但株高的基因型效应大于年份效应。相关性分析表明,株高与单薯重、单株薯重、大中薯率和鲜薯产量呈极显著正相关;主茎数与单株薯数呈极显著正相关,与单薯重、大中薯率呈极显著负相关。本研究基于主成分分析建立了鲜食型马铃薯品种在冬闲稻田适应性的综合评价模型,并筛选出适宜栽培推广的优质品种2份。
In order to reveal the variation pattern of potato main agronomic traits and screen out the superior cultivars suitable for winner paddy field,six potato cultivars were used as test materials in three years(2018-2021),and main agronomic characteristics were detected and analyzed by variance analysis,correlation analysis and principal component analysis.The results showed that there were different or significantly different among main agronomic characteristics of different cultivars.The year effects and genetic effects of all characteristics were different or significantly different,and the year effects were more than genetic effects,but only the plant height exhibited a greater genetic effects.Correlation analysis indicated that the plant height was extremely significantly positively correlated with single tuber weight,potato weight of per plant,large-medium potato rate and fresh potato yield.The number of main stems was extremely significantly positively correlated with tuber number per plant,but extremely significantly negatively correlated with single tuber weight and large-medium potato rate.Based on principal component analysis,the comprehensive evaluation model for the adaptability of table potato cultivars in winner paddy field were established and two quality cultivars suitable for popularization were screened out.
作者
李璐
杨丹
王素华
万国安
蒋万
李树举
张曙光
李兵
Li Lu;Yang Dan;Wang Suhua;Wan Guoan;Jiang Wan;Li Shuju;Zhang Shuguang;Li Bing(Changde Academy of Agricultural and Forestry Sciences,Changde 415000,Hunan,China;Crop Research Institute,Hunan Academy of Agricultural Sciences,Changsha 410125,Hunan,China)
出处
《作物杂志》
北大核心
2024年第3期47-53,共7页
Crops
基金
国家马铃薯产业技术体系(CARS-09-ES17)。
关键词
马铃薯
冬闲田
主成分分析
适应性
评价模型
Potato
Winner paddy field
Principal component analysis
Adaptability
Evaluation model