Determining relationships among yield and some yield components using path coefficient analysis in chickpea (Cicer arietinum L.)

Güler, Mustafa; Adak, M. Sait; Ulukan, Hakan

doi:10.1016/s1161-0301(00)00086-1

Cited by 76 publications

(41 citation statements)

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“…Selection of promising genotypes in a breeding program based on various criteria, most importantly final crop yield and its quality. Relationships between yield and yield contributing traits also plays an important role (Diz et al, 1994;Guler et al, 2001;Mohammadi et al, 2003 andRabiei et al, 2004).…”

Section: Correlations Of Yield With Different Yield Components Of Alfmentioning

confidence: 99%

Evaluation of Some Alfalfa (Medicago sativa L.) Germplasm for Yield and Yield Component Traits

2015

Egypt. J. Agron.

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ORTY-TWO alfalfa (Medicago sativa L.) landraces collected from different regions in Egypt and three commercial varieties were evaluated in this study. The data collected and analyzed were for plant height, number of tillers per m 2 , leaf to stem ratio, green forage weight and dry matter weight. The results indicated that plant height, number of tillers per square meter (m-2 ) , green forage yield, and dry matter weight were higher in the second year than the first year. There was a strong positive correlation between green forage yield with plant height and number of tillers per m 2 in addition, between dry forage yield with plant height and number of tillers per m 2 . There was also a highly significant positive relationship between green forage yield and dry forage yield. Using cluster analysis all genotypes were divided into two groups. The first group contained varieties Ismailia 1, Siwa and Nubaria, while the second group contained other genotypes collected from different regions. Maximum similarity index was recorded between genotypes (S18 and S09), while minimum similarity was between genotypes (D12 and Siwa).

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Section: Correlations Of Yield With Different Yield Components Of Alfmentioning

confidence: 99%

Evaluation of Some Alfalfa (Medicago sativa L.) Germplasm for Yield and Yield Component Traits

2015

Egypt. J. Agron.

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“…Correlation coeff icients generally show relationships among independent characters and the degree of linear relation between these characteristics (Guler et al, 2001). In plant breeding research, usually more than one character or variable is taken for measurement from the same plant.…”

Section: Introductionmentioning

confidence: 99%

Canonical correlation analysis for the determination of relationships between plant characters and yield components in red pepper (Capsicum annuum L. var. conoides (Mill.) Irish) genotypes

Çankaya

Balkaya

Karaağaç³

2010

Span. j. agric. res.

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In this study, a canonical correlation analysis (CCA) was used to estimate relationships between plant characters [X set-fruit length (FL), fruit width (FW), fruit wall thickness (FWT), placenta length, stem thickness, plant height (PH), leaf length, leaf width, flowering time (50%), and time to maturity], and yield components [Y set-total fruit weight per plant (FW/P), average fruit weight and number of fruits per plant (FN/P)] of 56 red peppers [Capsicum annuum L. var. conoides (Mill.) Irish] in populations collected from the Samsun province in the Black Sea Region of Turkey. All canonical correlation coefficients (0.708, 0.635, 0.413) between the pairs of canonical variables were found to be significant (P < 0.01). The findings obtained from the CCA indicate that FN/P had the largest contribution for the explanatory capacity of canonical variables estimated from yield components of 56 red pepper populations when compared with other yield components. FL and PH had largest contribution for the explanatory capacity of canonical variables estimated from plant characters when compared with other characters. The results of this study show that PH, FWT and FW should be used with the aim of increasing yield per plant in red pepper genotypes.Additional key words: canonical correlation coefficient, canonical variable, multivariate analysis, population, variation. ResumenAnálisis de correlación canónica para relacionar caracteres de la planta con componentes del rendimiento en genotipos de pimiento rojo [Capsicum annuum L. var. conoides (Mill.) Irish] En este estudio se utilizó un análisis de correlación canónica (CCA) para estimar las relaciones existentes entre caracteres de la planta [X set -longitud del fruto (FL), anchura del fruto (FW), espesor de la pared del fruto (FWT), longitud de la placenta, espesor del tallo, altura de la planta (PH), longitud y anchura de la hoja, tiempo a 50% de floración y tiempo de madurez], y componentes del rendimiento [Y set-peso de frutos total por planta (FW/P), peso y número medio de frutos por planta (FN/P)] de 56 pimientos rojos [Capsicum annuum L. var. conoides (Mill.) Irish] en poblaciones recolectadas en la provincia Samsun de la región del Mar Negro de Turquía. Se encontró que todos los coeficientes de correlación canónica (0,708; 0,635; 0,413) entre las parejas de variables canónicas fueron significativos (P < 0,01). El CCA indicó que, entre los componentes del rendimiento, la relación FN/P fue la que más contribuyó en la capacidad explicatoria de las variables canónicas estimadas de las 56 poblaciones de pimiento. En el caso de los caracteres de la planta, FL y PH fueron los que más contribuyeron en la capacidad explicatoria de las variables canónicas estimadas. Este estudio muestra que se deben usar los caracteres PH, FWT y FW para incrementar el rendimiento de los genotipos de pimiento rojo.Palabras clave adicionales: análisis multivariante, coeficiente de correlación canónica, población, variable canó-nica, variación.

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“…Garcia del Moral et al (1991) and Guler et al (2001) investigated the direct and indirect effects of nontarget traits on target traits using path analysis, which revealed internal relationships among the traits. However, this method is not performed in breeding due to the direct and multiple indirect effects involved (i.e., some effects might be positive, whereas others might be negative).…”

Section: Discussionmentioning

confidence: 99%

“…Mixed linear model approaches have also been widely applied in cotton genetic studies (Wu et al 1995;Tang et al 1996;McCarty et al 1998aMcCarty et al , b, 2004aJenkins et al 2007Jenkins et al , 2009Mei et al 2007). Many researchers have applied correlation or path coefficients to improve targeted characters (Guler et al 2001). Selection of the main fiber quality traits may be conducted by indirectly selecting the boll shape (Zhang and Mei 2004).…”

Section: Introductionmentioning

confidence: 99%

Analysis of decision-making coefficients of three main fiber quality traits for upland cotton (Gossypium hirsutum L.)

Mei

Fan

et al. 2013

Euphytica

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The analysis of genetic correlations between fiber length (Len), strength (Str), micronaire, and 12 other traits was conducted using the additive (A)-dominance (D) genetic model, which considers genotype 9 environment interaction effects, in intraspecific upland cotton (Gossypium hirsutum L.) hybrids to effectively improve the quality of cotton cultivars in high planting density cases. Decisionmaking coefficients were computed based on the genetic correlation and path analysis of three fiber quality traits. The decision-making coefficient analysis of three fiber traits in cross breeding was beneficial for the improvement of Len by increasing the additive effects of Str and length of boll (LB) and decreasing lint percentage (LP), boll number of the top three fruitbearing branches. The analysis was also beneficial for the improvement of Str and fiber fineness by increasing or decreasing the additive effects of other traits. Utilizing heterosis in hybrids was beneficial to the heterosis of Len by selecting the high dominance effects of number of nodes of the 1st fruit-bearing branch and LB and decreasing the dominance effects of diameter of boll (DB) and LP and for improving Str by increasing the dominance effects of DB and decreasing the dominance effects of number of fruitbearing branches and number of nodes of the main stem (NNMS). Utilizing heterosis was also beneficial for improving fineness by increasing the dominance effects of LB, Str, and lint yield and decreasing the dominance effects of NNMS and Len.

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Determining relationships among yield and some yield components using path coefficient analysis in chickpea (Cicer arietinum L.)

Cited by 76 publications

References 3 publications

Evaluation of Some Alfalfa (Medicago sativa L.) Germplasm for Yield and Yield Component Traits

Evaluation of Some Alfalfa (Medicago sativa L.) Germplasm for Yield and Yield Component Traits

Canonical correlation analysis for the determination of relationships between plant characters and yield components in red pepper (Capsicum annuum L. var. conoides (Mill.) Irish) genotypes

Analysis of decision-making coefficients of three main fiber quality traits for upland cotton (Gossypium hirsutum L.)

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