Correlations and path analysis for quantitative characteristics in semi-prostrate cowpea bean genotypes (Vigna unguiculata (L.) Walp)

Correlaciones y análisis de sendero para características cuantitativas en genotipos semi-postrados de fríjol caupí (Vigna unguiculata (L.) Walp)

Main Article Content

Hermes Araméndiz-Tatis
Miguel Espitia-Camacho
Carlos Cardona-Ayala

Abstract

The cowpea is the most important legume in the Colombian Caribbean, due to its positive impact on the food and nutritional security of low-income rural families. It is cultivated by small producers, but its yields per hectare do not exceed 600 kg, due to the use of obsolete cultivars. The objective of the research was to estimate the correlations between seven quantitative characters and the path analysis between grain yield and six quantitative characters, with the results of the evaluation of 10 genotypes of semi-prostrate growth habit, high grain yield, grown in eight environments of the humid and dry tropics of the Colombian Caribbean region, under the randomized complete blocks design, with four repetitions. Significant differences between environments, genotypes and genotype x environment interaction were detected. Genotypic correlations were of greater magnitude than phenotypic, highlighting the correlation between grain width (GW) and grain yield (GY), rP = 0.69 *, rG = 0.78 *, also between the weight of 100 seeds (100SW) and GW, rP = 0.97 **, rG = 0.99 **. The characters GW and number of pods per plant (NPP) had positive direct effects on the GY, with an indirect negative effect of NPP by way of GW, while the height of the first pod (HFP), the number of seeds per pod (NSP) and the 100SW directly and negatively influenced the GY of the 10 semi-prostrate cowpea cultivars.

Keywords:

Downloads

Download data is not yet available.

Article Details

References (SEE)

Abate, F., F. Mekbib, and Y. Dessalegn. 2015. Association of different parametric and non parametric stability models in durum wheat (Triticum turgidum Desf.) genotypes. Int. J. Plant Soil Sci. 7(4), 192-201. Doi: https://doi.org/10.9734/IJPSS/2015/15568

Agrawal, T., A. Kumar, S. Kumar, A. Kumar, R.R. Kumar, S. Kumar, and P.K. Singh. 2018. Correlation and path coefficient analysis for grain yield and yield components in chickpea (Cicer arietinum L.) under normal and late sown conditions of Bihar, India. Int. J. Curr. Microbiol. Appl. Sci. 7(2), 1633-1642. Doi: https://doi.org/10.20546/ijcmas.2018.702.197

Andrade, F.N., M. Moura Rocha, R. Ferreira-Gomes, F.R. Freire Filho, and S. Ramalho-Ramos. 2010. Estimativas de parâmetros genéticos em genótipos de feijão-caupi avaliados para feijão fresco. Rev. Ciênc. Agron. 41(2), 253-258. Doi: https://doi.org/10.1590/S1806-66902010000200012

Bezerra, A.A., C.J. Anunciação Filho, F.R. Freire Filho, and V.Q. Ribeiro. 2001. Inter-relação entre caracteres de caupi de porte ereto e crescimento determinado. Pesq. Agropec. Bras. 36(1), 137-142. Doi: https://doi.org/10.1590/S0100-204X2001000100017

Bhatt, G.M. 1973. Significance of path coefficient analysis in determining the nature of the character association. Euphytica 22(2), 338-343. Doi: https://doi.org/10.1007/BF00022643

Cruz, C. 2016. Programa Genes V.2016.6.0 - Aplicativo computacional em genética e estatística. In: http://www.ufv.br/dbg/genes/genes.htm; consulted, March, 2019.

DANE, Departamento Administrativo Nacional de Estadística de Colombia. 2019. Pobreza multidimensional en Colombia 2018. Boletín técnico Mayo -2019. https://www.dane.gov.co/files/investigaciones/condiciones_vida/pobreza/2018/bt_pobreza_multidimensional_18.pdf; consulted: February, 2019.

De Paula, C.D., S. Jarma, and H. Araméndiz-Tatis. 2018. Caracterización nutricional y determinación de ácido fítico como factor antinutricional del frijol caupí. Agron. Mesoam. 29(1), 29-40. Doi: https://doi.org/10.15517/ma.v29i1.27941
Fenalce, Federación Nacional de Cultivadores de Cereales y Leguminosas. 2017. Informe de gestión 2017. http://fenalce.org/siembras/archivos_lt/lt_532IG-FNL-2017-CONSOLIDADO.pdf; consulted: February, 2019.

Ferrari, M., I.V. Carvalho, A.J. Pelegrin, M. Nardino, V.J. Szareski, T. Olivoto, T. Rosa, D.N. Follmann, C. Pegoraro, L.C. Maia, and V.Q. Souza. 2018. Path analysis and phenotypic correlation among yield components of soybean using environmental stratification methods. Aust. J. Crop Sci. 12(02), 193-202. Doi: https://doi.org/10.21475/ajcs.18.12.02.pne488

Godim, T.C., V.S. Rocha, C.S. Sediyama, and G.V. Miranda. 2008. Análise de trilha para componentes do rendimento e caracteres agronômicos de trigo sob desfolha. Pesq. Agropec. Bras. 43(4), 487-493. Doi: https://doi.org/10.1590/S0100-204X2008000400007

Gupta, R.A., C.N. Ram, S.K. Chakravati, Ch. Deo, M.K. Vishwakarma, D.K. Gautam, and P. Kumar. 2017. Studies on correlation and path coefficient analyses in brinjal (Solanum melongena L.). Int. J. Curr. Microbiol. App. Sci. 6(7), 4543-4548. Doi: https://doi.org/10.20546/ijcmas.2017.607.474

Hemavathy, A.T., N. Shunmugavalli, and G. Anand. 2015. Genetic variability, correlation and path co-efficient studies on yield and its components in mungbean [Vigna radiata (L.) Wilezek]. Legume Res. 38(4), 442-446. Doi: https://doi.org/10.5958/0976-0571.2015.00050.8

Kumar, K.P., P.N. Kumar, T.N. Muneeswari, R. Lamror, and U. Kumari. 2013. Morphological and genetic variation studies in cowpea genotypes [Vigna unguiculata (l.)] Walp. Legume Res. 36(4), 351-354.

Lekshmanan, D.R. and A. Vahab. 2018. Correlation and path coefficient analysis of yield and its component characters among different accessions of cluster bean [Cyamopsis tetragonoloba (L.) Taub.]. Legume Res. 41(1), 53-56. Doi: https://doi.org/10.18805/10.18805/LR-3691

Meena, H.K., K.R. Krishna, and B. Singh. 2015. Character associations between seed yield and its components traits in cowpea [Vigna unguiculata (L.) Walp.]. Indian J. Agric. Res. 49(6), 567-570. Doi: https://doi.org/10.18805/ijare.v49i6.6688

Mendonça, O., V. Carpentieri-Pípolo, D.D. Garbuglio, and N.S. Fonseca Junior. 2007. Factor analysis and environmental stratification in the assessment of soybean adaptability and stability. Braz. J. Agric. Res. 42(11), 1567-1575. Doi: https://doi.org/10.1590/S0100-204X2007001100008

Mishili, F.J., J. Fulton, M. Shehu, S. Kushwaha, K. Marfo, M. Jamal, A. Kergna, and J. Lowenberg-DeBoer. 2009. Consumer preferences for quality characters along the cowpea value chain in Nigeria, Ghana, and Mali. Agribusiness 25(1), 16-35. Doi: https://doi.org/10.1002/agr.20184

Mohammed, M.S., Z. Russom, and S.D. Abdul, 2010. Inheritance of hairiness and pod shattering, heritability and correlation studies in crosses between cultivated cowpea (Vigna unguiculata (L.) Walp.) and its wild (var. pubescens) relative. Euphytica 171(3), 397-407. Doi: https://doi.org/10.1007/s10681-009-0058-6

Moura, J., M. Moura Rocha, R. Ferreira Gomes, F. Freire Filho, K.J. Silva, and V.Q. Ribeiro. 2012. Path analysis of iron and zinc contents and others traits in cowpea. Crop Breed. Appl. Biotechnol. 12(4), 245-252. Doi: https://doi.org/10.1590/S1984-70332012000400003

Oliveira, R.L., J.A. Muniz, M.J. Andrade, and R.L. Reis. 2009. Precisão experimental em ensaios com a cultura do feijão. Ciênc. Agrotec. 33(1), 113-119. Doi: https://doi.org/10.1590/S1413-70542009000100016

Pantoja, D., K.Z. Muñoz, and O.C. Checa. 2014. Evaluación y correlación de componentes de rendimiento en líneas avanzadas de arveja Pisum sativum con gen afila. Rev. Ciênc. Agríc. 31(2), 24-39. Doi: https://doi.org/10.22267/rcia.143102.29

Ribeiro, H.L., C.A. Santos, L. Diniz, L.A. Nascimento, and E.D. Nunes. 2016. Phenotypic correlations and path analysis for plant architecture traits and grain production in three generations of cowpea. Rev. Ceres 63(1), 033-038. Doi: https://doi.org/10.1590/0034-737X201663010005

Rocha, F., L.D. Barili, S.H. García, R. Modena, J.M.L. Coimbra, A.F. Guidolin, and J.G. Bertoldo. 2009. Seleção em populações mutantes de feijão (Phaseolus vulgaris L.) para caracteres adaptativos. Biotemas 22(2), 19-27. Doi: https://doi.org/10.5007/2175-7925.2009v22n2p19

Salinas, R.A., J.A. Acosta, E. López, C.A. Torres, F.J. Ibarra, and R.F. Gastelum. 2008. Rendimiento y características morfológicas relacionadas con tipo de planta erecta en frijol para riego. Rev. Fitotec. Mex. 31(3), 203-211.

Santos, A., G. Ceccon, L.M. Chamma, A.M. Correa, and V.B. Alves. 2014. Correlations and path analysis of yield components in cowpea. Crop Breed. Appl. Biotechnol. 14(2), 82-87. Doi: https://doi.org/10.1590/1984-70332014v14n2a15

Silva, J.A.L. and J.A. Neves. 2011. Componentes de produção e suas correlações em genótipos de feijãocaupí em cultivo de sequeiro e irrigado. Rev. Ciênc. Agron. 42(3), 702-713. Doi: https://doi.org/10.1590/S1806-66902011000300017

Silva, C.A., M.O. Morais, L.J. Santos, O.L. D´Arede, J.C. Silva, and M.M. Rocha. 2014. Estimativa de parâmetros genéticos em Vigna unguiculata. Rev. Ciênc. Agríc. 37(4), 399-407.

Singh, S.K., V.P. Singh, S. Srivastava, A.K. Singh, B.K. Chaubey, and R.K. Srivastava, 2018. Estimation of correlation coefficient among yield and attributing traits of field pea (Pisum sativum L.). Legume Res. 41(1), 20-26. Doi: 18805/LR-3449.

Ullah, M.Z., M.J. Hasan, A.H.M.A. Rahman, and A.I. Saki. 2011. Genetic variability, carácter association and path analysis in yard long bean. SAARC J. Agric. 9(2), 9-16.

Velho, L.P., M.S. Gemeli, N. Tevisan, T. Pereira, P. Cerutti, R. Melo, A. Guidolin, J. Coimbra, and S. Correa. 2017. Phenotypic correlation and direct and indirect effects of aerial part components with root distribution of common bean. Pesq. Agropec. Bras. 52(5), 328-334. Doi: https://doi.org/10.1590/s0100-204x2017000500006

Citado por: