pheno.corr: Phenotypic Correlation Analysis

In variability: Genetic Variability Analysis for Plant Breeding Research

Description

Phenotypic Correlation Analysis

Usage

pheno.corr(data, genotypes, replication)

Arguments

data	traits to be analyzed
genotypes	vector containing genotypes
replication	vector containing replications

Value

Phenotypic correlation

Examples

data(vardata)
pheno.corr(vardata[3:11],vardata$Genotypes,vardata$Replication)

Example output

$PhenotypicCorrelation
     DFF        PH         PL         PW         HI         TW        
DFF  1 **       0.6302 **  0.1513 NS  0.2217 *   -0.2163 *  0.4128 ** 
PH   0.6302 **  1 **       0.203 *    0.101 NS   -0.2416 ** 0.343 **  
PL   0.1513 NS  0.203 *    1 **       0.1289 NS  -0.0594 NS -0.1281 NS
PW   0.2217 *   0.101 NS   0.1289 NS  1 **       0.2288 *   -0.1436 NS
HI   -0.2163 *  -0.2416 ** -0.0594 NS 0.2288 *   1 **       -0.263 ** 
TW   0.4128 **  0.343 **   -0.1281 NS -0.1436 NS -0.263 **  1 **      
MILL -0.0667 NS -0.0794 NS -0.1905 *  0.0181 NS  0.1157 NS  0.0634 NS 
HRR  0.1159 NS  0.0359 NS  -0.0053 NS 0.0037 NS  0.0806 NS  0.0852 NS 
GY   0.0341 NS  0.1531 NS  0.1477 NS  0.3338 **  0.4594 **  -0.2724 **
     MILL       HRR        GY        
DFF  -0.0667 NS 0.1159 NS  0.0341 NS 
PH   -0.0794 NS 0.0359 NS  0.1531 NS 
PL   -0.1905 *  -0.0053 NS 0.1477 NS 
PW   0.0181 NS  0.0037 NS  0.3338 ** 
HI   0.1157 NS  0.0806 NS  0.4594 ** 
TW   0.0634 NS  0.0852 NS  -0.2724 **
MILL 1 **       0.3025 **  0.1822 *  
HRR  0.3025 **  1 **       -0.0794 NS
GY   0.1822 *   -0.0794 NS 1 **      

$Note
[1] "The sig of phenotypic correlation was tested using t test (two-tail). The degree of freedom used is (genotypes*replication) - 2"

variability documentation built on Oct. 24, 2020, 9:10 a.m.