首页> 外文期刊>International Journal of Statistical Distributions and Applications >Multivariate Genotype and Genotype by Environment Interaction Biplot Analysis of Sugarcane Breeding Data Using R
【24h】

Multivariate Genotype and Genotype by Environment Interaction Biplot Analysis of Sugarcane Breeding Data Using R

机译:利用R进行甘蔗育种数据的多态性基因型和环境相互作用Biplot分析

获取原文
           

摘要

Complexity of Genotype by environment interaction (GxEI) in sugarcane multi-environmental trial (MET) requires further evaluation for genotypes performance determination. Genotype and genotype by environment (GGE) is one of the many statistical techniques for evaluating the interaction with emphasis on genotypes. Many statistical analysis tools for GGE exists with usage depending on cost and knowhow. R open source analytical software ensures availability and the knowledge on the necessary packages is required thus the objective of the paper on utilization of GGE using R software in the evaluation of genotypes with presence GxEI. The application used secondary data of Kenyan Mtwapa series of 96 and 97 preliminary varietal trial stage 4 established under randomized complete block design (RCBD), consisting of 15 test genotypes and three controls in the environments of SONYsugar, Mumias and KibosF9 with the plant crop and ratoon crop cycles as seasons. The 2-way GEI data was handled using singular value decomposition (SVD) through the R package; GGEbiplot programmed scripts and graphical user interface (GUI) were used in ranking genotypes and environments, determining genotypes performance overall and in each environment, determining stabilities and adaptability of the genotypes and identifying mega trial environments. GGEbiplot unpacked the GEI through the principle components (PC) 1 and 2 that sufficiently explained 85.37% of the variations.
机译:在甘蔗多环境试验(MET)中,通过环境相互作用(GxEI)进行基因型的复杂性需要进一步评估基因型性能。基因型和环境基因型(GGE)是许多评估基因型相互作用的统计技术之一。存在许多用于GGE的统计分析工具,其用法取决于成本和专有技术。 R开源分析软件可确保可用性,并且需要有关必需软件包的知识,因此,本文的目的是使用R软件在评估存在GxEI的基因型时利用GGE。该应用程序使用了肯尼亚Mtwapa系列96和97初选试验4的二级数据,该试验是在随机完整区组设计(RCBD)下建立的,包括SONYsugar,Mumias和KibosF9环境下的15种测试基因型和3种对照,以及植物作物和再生农作物的生长周期随季节而变。通过R包使用奇异值分解(SVD)处理2路GEI数据; GGEbiplot编程脚本和图形用户界面(GUI)用于对基因型和环境进行排名,确定基因型在每个环境中的总体性能,确定基因型的稳定性和适应性以及确定大型试验环境。 GGEbiplot通过主要成分(PC)1和2解压缩了GEI,这些成分足以解释85.37%的变化。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号