Correlations and path analysis in soybean progenies with resistance source to cyst nematode (race 3)

Authors

  • Daniela Sarti Dvorjak University of Kentucky, Lexington, KY, USA.
  • Sandra Helena Unêda-Trevisoli Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brasil.
  • Wallace de Sousa Leite Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brasil.
  • Alysson Jalles da Silva Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brasil.
  • Fabiana Mota da Silva Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brasil.
  • Antonio Orlando Di Mauro Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brasil.

DOI:

https://doi.org/10.14295/cs.v10i1.1697

Abstract

Path analysis is an important study that slices the correlation coefficients between two variables to evaluate whether the relationship between them is of cause and effect. This study aimed to estimate the phenotypic and genotypic correlations between agronomic traits and perform a path analysis in order to identify variables for indirect selection aiming at a higher grain yield. Fourteen soybean F6 lines from the soybean breeding program of FCAV–UNESP, Jaboticabal, São Paulo, Brazil, were analyzed. The experimental design was a randomized block design with three replications. The agronomic traits plant height at maturity (PHM), first pod height (FPH), lodging (Ld), agronomic value (AV), number of pods per plant (NP), number of seeds per plant (NS), and grain yield (GY) were evaluated. Overall, the genotypic correlations were higher than their corresponding phenotypic correlations. The genotypic correlations between grain yield and the traits agronomic value, number of pods per plant, and number of seeds per plant were positive, significant, and of high magnitude. Path analysis showed that the trait number of seeds per plant had the highest direct effect on grain yield, while the trait number of pods per plant had the highest indirect effect through the number of seeds per plant on grain yield

Downloads

Download data is not yet available.

References

Akram, R.M., Fares, W.M., Fateh, H.S.A., Rizk, A.M.A. 2011. Genetic variability, correlation and path analysis in soybean. Egyptian Journal Plant Breed 15: 89 – 102.

Alcântara Neto, F., Gravina, G.A., Monteiro, M.M.S., Morais, F.B., Petter, F.A., Albuquerque, J.A.A. 2011. Análise de trilha do rendimento de grãos de soja na microrregião do Alto Médio Gurguéia. Comunicata Scientiae 2: 07-112.

Almeida, R.D., Peluzio, J.M., Afferri, F.S. 2010. Correlações fenotípicas, genotípicas e ambientais em soja cultivada sob condições várzea irrigada, sul do Tocantins. Bioscience Journal 26: 95-99.

Asmus, G.L., Teles, T.S., Anselmo, J., Rosso, G.T. 2012. Races of Heterodera glycines in the Northeast of Mato Grosso do Sul, Brazil. Tropical Plant Pathology, 37: 146-148.

Bárbaro, I.M., Centurion, M.A.P., MAURO, A.O.D., Unêda-Trevisoli, S.H., Costa, M.M., Muniz, F.R.S.; Silveira, G.D., Sarti, D.G.P. 2007. Variabilidade e correlações entre produtividade de grãos e caracteres agronômicos de soja com aptidão para cultivo em áreas para reforma de canavial. Científica 35: 136-145.

Chandel, K.K., Patel, N.B., Patel, J.B. 2014. Correlation coefficients and path analysis in soybean (Glycine max L. merrill). AGRES – An International e-Journal 3: 25-31.

Cruz, C.D. 2013. GENES - a software package for analysis in experimental statistics and quantitative genetics. Acta Scientiarum 35: 271-276.

Cruz, C. D., Regazzi, A. J., Carneiro, P. C. S. 2012. Modelos Biométricos Aplicados ao Melhoramento Genético. Editora UFV, Viçosa, Brasil. 514 p.

El-Mohsen, A.A.A., Mahmoud, G.O., Safina, S.A. 2013. Agronomical evaluation of six soybean cultivars using correlation and regression analysis under different irrigation regime conditions. Journal of plant breeding and crop science 5: 91-102.

Falconer, D.S. 1987. Introdução à genética quantitativa. Tradução de Silva MA. & Silva JC. Universidade Federal de Viçosa. Imprensa Universitária, Viçosa, Brasil. 279 p.

Fehr, W.R., Caviness, J.A. 1977. Stages of soybean development. Aimes: Iowa State University, 11 p. (Special Report, 80).

Ghodrati, G.R., Sekhavat, R., Mahmoodinezhadedezfully, S.H., Gholami, A. 2013. Evaluation of correlations and path analysis of components seed yield in soybean. International Journal of Agriculture 3: 795-800.

Haghi, Y., Boroomandan, P., Moradin, M., Hassankhali, M., Farhadi, P., Farsaei, F., Dabiri, S. 2012. Correlation and path analysis for yield, oil and protein content of Soybean (Glycine max L.) genotypes under different levels of nitrogen starter and plant density. Biharean Biologist 6: 32-37.

Hamawaki, O.T., Sousa, L.B., Romanato, F.N., Nogueira, A.P.O., Santos Júnior, C.D., Polizel, A.C. 2012. Genetic parameters and variability in soybean genotypes. Comunicata Scientiae 3: 76-83.

Li Y.S., Du M., Zhang Q.Y., Hashemi M., Liu X.B., Hebert S.J. 2013. Correlation and path coefficient analysis for yield components of vegetable soybean in Northeast China. Legume Research – An International Journal 36: 284-288.

Machikowa, T., Laosuwan, P. 2011. Path coefficient analysis for yield of early maturing soybean. Sonklanakarin Journal of Science and Technology 33: 365-368.

Montgomery, D.C., Peck E.A. 1981. Introduction to linear regression analysis. John Wiley e Sons, New York, 504 p.

Nogueira, A.P.O., Sediyama, T., Sousa, L.B., Hamawaki, O.T., Cruz, C.D., Pereira, D.G., Matsuo, E. 2012. Análise de trilha e correlações entre caracteres em soja cultivada em duas épocas de semeadura. Bioscience Journal 28: 877-888.

Resende, M. D. V. 2007. SELEGEN-REML/BLUP: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Embrapa Florestas, Colombo, Brasil. 359 p.

Santana, H., Pires, E., Comerlato, A.P., Nasu, E.G., Furlanetto, C. 2009. Genetic variability in field populations of the soybean cyst nematode from the States of Paraná and Rio Grande do Sul, Brazil. Tropical Plant Pathology, 34: 261-264.

Sedghi, M., Amanpour-Balaneji, B. 2010. Sequential path model for grain yield in soybean. Notulae Scientia Biologicae, 2: 104-109.

Showkat, M., Tyagi, D. 2010. Correlation and path analysis of some quantitative traits in soybean (Glycine max L. Merrill). Research Journal of Agricultural Sciences 1: 102-106.

Silva, A.F., Sediyama, T., Silva, F.C.S., Bezerra, A.R.G., Ferreira, L. V. 2015. Correlation and path analysis of soybean yield components. International Journal of Plant, Animal and Environmental Sciences 5: 177-179.

Vianna, V.F., Unêda-Trevisoli, S.H., Desidério, J.A., Santiago, S., Charnai, K., Ferreira Júnior, J.A., Ferraudo, A.S., Mauro, A.O. 2013. The multivariate approach and influence of characters in selecting superior soybean genotypes. African Journal of Agricultural Research 8: 4162-4169.

Wright, S. 1921. Correlation and causation. Journal of Agricultural Research 20: 557-585.

Downloads

Published

2019-04-17

How to Cite

Dvorjak, D. S., Unêda-Trevisoli, S. H., Leite, W. de S., Silva, A. J. da, Silva, F. M. da, & Mauro, A. O. D. (2019). Correlations and path analysis in soybean progenies with resistance source to cyst nematode (race 3). Comunicata Scientiae, 10(1), 168–175. https://doi.org/10.14295/cs.v10i1.1697

Issue

Section

Original Article