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不同苋科饲草的生长特性及生产性能初步评价
引用本文:不同苋科饲草的生长特性及生产性能初步评价.不同苋科饲草的生长特性及生产性能初步评价[J].畜牧与饲料科学,2019,40(11):42-46.
作者姓名:不同苋科饲草的生长特性及生产性能初步评价
作者单位:1.重庆市南川区畜牧兽医渔业局,重庆 408400; 2.重庆市畜牧科学院,重庆 400015
摘    要:为了挖掘利用苋科饲草资源,以采自重庆市的16份苋科饲草为供试材料,对其物候期、农艺性状和生产性能方面的11项性状指标进行了测定,并采用主成分分析法和聚类分析法进行综合评价。结果表明,16份苋科饲草材料中,15号材料(编号:2015502019,名称:飞天苋)综合得分最高,表现最优,其次是3号(编号:xky201703002,名称:籽粒苋)、5号(编号:2016501818,名称:红苋菜)和9号(编号:2015502704,名称:天荨米)。这4份材料有进一步观察选育和开发利用的价值。

关 键 词:苋科饲草  生长特性  生产性能  主成分分析  聚类分析  
收稿时间:2019-09-05

Preliminary Evaluation on Growth Characteristics and Production Performance of Different Amaranthaceae Forage
WU Ping,LUO Gui-qiao,FAN Yan,HE Wei,XU Yuan-dong.Preliminary Evaluation on Growth Characteristics and Production Performance of Different Amaranthaceae Forage[J].Animal Husbandry and Feed Science,2019,40(11):42-46.
Authors:WU Ping  LUO Gui-qiao  FAN Yan  HE Wei  XU Yuan-dong
Institution:1.Bureau of Animal Husbandry,Veterinary Medicine and Fishery of Nanchuan District of Chongqing,Chongqing 408400,China; 2.Chongqing Academy of Animal Husbandry Sciences,Chongqing 400015,China
Abstract:In order to exploit and utilize the Amaranthaceae forage resources, a total of 16 Amaranthaceae forage samples collected from Chongqing were used as experimental materials in this study, and the phenological period, agronomic traits and production performance of the tested samples were determined and compared. Furthermore, principal component analysis and cluster analysis were used to evaluate the comprehensive quality of the 16 Amaranthaceae forage. The results showed that among the 16 materials, the No.15 sample (serial number: 2015502019, name:′Feitianxian′) had the highest comprehensive score and the best performance, followed by No.3 sample (serial number: xky201703002, name:Amaranthus hypochondriacus), No.5 sample (serial number: 2016501818, name: Amaranthus tricolor) and No.9 sample (serial number: 2015502704, name:′Tianxunmi′). In conclusion, these four materials have the value for further breeding, development and utilization.
Keywords:Amaranthaceae forage  growth characteristics  production performance  principal component analysis  cluster analysis  
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