ANALYSIS OF GENOTYPE-ENVIRONMENT INTERACTIONS BASED ON THE METHOD OF PATH COEFFICIENT ANALYSIS

1975 ◽  
Vol 17 (2) ◽  
pp. 141-149 ◽  
Author(s):  
G.C.C. Tai
Keyword(s):  
Causal Relationship ◽  
Yield Components ◽  
Path Coefficient ◽  
Environmental Resources ◽  
Path Coefficient Analysis ◽  
Ge Interaction ◽  
Marketable Yield ◽  
Component Trait ◽  
Field Crops ◽  
Component Traits

A method of investigating genotype-environment interactions of field crops is presented. Based on the concept that yield components are determined sequentially at different stages in the ontology of plants and the hypothesis that the environmental resources can be separated into independent groups with each contributing to the development of a component trait, a causal relationship between environmental resources, component traits and yield is established (Fig. 1). The GE interaction effect is then represented by three multiplicative terms which are composed of three genotypic and three environmental components. These components are estimated using the method of path coefficient analysis based on the postulated causal relationship. Data of marketable yield and yield components of seven potato cultivars collected from two series of trials are examined by the proposed method.

scholarly journals Path coefficient analysis of quality of two-row spring barley

Genetika ◽  
2013 ◽  
Vol 45 (1) ◽  
pp. 21-30
Author(s):  
Novo Przulj ◽  
Vojislava Momcilovic ◽  
Jovan Crnobarac
Keyword(s):  
Path Analysis ◽  
Correlation Coefficient ◽  
Direct Effect ◽  
Malting Quality ◽  
Path Coefficient ◽  
Malt Extract ◽  
Path Coefficient Analysis ◽  
Simple Correlation ◽  
Component Trait ◽  
Component Traits

Malting quality is composed of numerous interacting traits with a high complexity concerning their biochemical and genetic basis. Malt extract is key indicator of barley malting quality and it is a mega-trait since it is influenced by a number of independent component traits. Understanding genetic and non-genetic factors that effects grain quality and grain yield is crucial in developing new cultivars, seed and mercantile production. Path analysis is one of the reliable statistical techniques which allow separation of the direct effect of each component trait on malt quality from the indirect effects caused by the interdependence component trait. The aim of this study was to investigate spring two-row barley quality as mega-trait depending on the component traits in the conditions of the Pannonian environments. Regression analysis with extract (EXT) as dependant and other traits (yield-YIL, test weight-TW, grain weight-GW, grading-GRA, grain protein concentration-GPC, viscosity-VIS, Kolbach index-KOL, Hartong number-HAR) as independent traits was performed out. Simple coefficient of correlations were calculated between independent traits and EXT in all pair combination and then used as inputs for path coefficient analysis. The quadratic curve fitted the best relationship between EXT and the independent traits. EXT was in positive (P<0.01) relationship with GW, GRA, KOL, and HAR with simple correlation coefficient of 0.47, 0.42, 0.39 and 0.50, respectively and in negative (P<0.01) relationship with GPC and VIS with simple correlation coefficient of -0.72 and -0.51, respectively. Path analysis explained more than 70% of the variation in EXT of which 34.3% was determined by direct negative path coefficient (P<0.01) of GPC without significant any indirect path effect. VIS negatively directly, (P<0.01) and negatively indirectly via GPC effected EXT. KOL did not have significant direct effect on EXT, but had rather prominent indirect effect via GPC, VIS and HAR. HAR positively directly (P<0.01) and positively indirectly via GPC effected EXT. The direct effect of VIS and HAR determined 13.0% and 14.1% of the variation, respectively.

scholarly journals Correlation and Path Coefficient Studies in F2 Populations of Rice

2012 ◽  
Vol 4 (2) ◽  
pp. 124-127 ◽  
Author(s):  
Ghaffar KIANI ◽  
Ghorbanali NEMATZADEH
Keyword(s):  
Grain Yield ◽  
Yield Components ◽  
Selection Criteria ◽  
Stepwise Regression ◽  
Path Coefficient ◽  
Direct Effects ◽  
Panicle Length ◽  
Path Coefficient Analysis ◽  
Yield Variation ◽  
Rice Genotypes

This study performed to determine the association between grain yield and yield components in fifty-four selected rice genotypes at F2 populations. Results showed that traits, the panicles per plant (r = 0.751) and filled grains per panicle (r = 0.458) correlated significantly with grain yield, while grain yield was negatively associated with non-filled grains per panicle (-0.297). Path coefficient analysis revealed that grain yield was associated with panicles per plant and filled grains per panicle with the direct effects of 0.691 and 0.568, respectively. The greatest indirect effect belonged to panicle length (0.301) through filled grains per panicle. Stepwise regression analysis showed that 72.1 percent of yield variation could be explained by three characters: the panicles per plant, filled grains per panicle and panicle length. Information obtained in this study revealed that traits, the panicles per plant and filled grains per panicle, could be used as selection criteria for grain yield improvement at segregating populations of rice.

Path Coefficient Analysis of Correlation Between Stress and Barley Yield Components 1

1980 ◽  
Vol 72 (6) ◽  
pp. 1012-1016 ◽  
Author(s):  
W. F. Campbell ◽  
R. J. Wagenet ◽  
A. M. Bamatraf ◽  
D. L. Turner
Keyword(s):  
Yield Components ◽  
Path Coefficient ◽  
Path Coefficient Analysis

scholarly journals VARIETAL PERFORMANCE AND CORRELATION OF OKRA POD YIELD AND YIELD COMPONENTS

2017 ◽  
Vol 29 (1) ◽  
pp. 11-20
Author(s):  
D. Aminu ◽  
O. B. Bello ◽  
B. A. Gambo ◽  
A. H. Azeez ◽  
J. O. Agbolade ◽  
...  
Keyword(s):  
Plant Height ◽  
Yield Components ◽  
Path Coefficient ◽  
Path Coefficient Analysis ◽  
Fresh Weight ◽  
Yield Attributes ◽  
Mean Values ◽  
Pod Yield ◽  
Dry Seasons ◽  
Pod Length

Field irrigation experiments were conducted to assess the varietal performance and correlation of pod yield and yield attributes under irrigation at the Teaching and Research Farm, University of Maiduguri, Nigeria, during 2015 and 2016 dry seasons. The results revealed that the most outstanding for fresh pod yield per plant were okra cultivar Kwadag Y’ar gagure Salkade and, Kwadam in descending order with yield ranging from 580.38-622.67g, while the composite cultivar had the lowest value of pod yield of 428.62g over the two years. The highest mean values for number of pods per plant and number of primary branches per plant were observed for Salkade and Y’ar gagure, respectively. Highest fresh pod length and fresh pod diameter were also exhibited for Salkade and Kwadag, respectively. Genotypic coefficient of variation was higher than the phenotypic variation for all the yield contributing characters. Days to 50% flowering were positive and highly significance difference associated with plant height, number of pods per plant and fresh weight per pod. Path coefficient analysis showed that number of pods per plant exhibited positive and direct effects on pod yield across years. Indirect effect of other yield components through this character also contributed mainly towards pod yield. Therefore, plant height, days to 50% flowering, number of pods per plant, pod length, pod diameter, number of primary branches per plant and fresh weight per pod could be considered for selection and improvement for high pod yielding varieties in okra.

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