Genetic parameters, yield adaptability and stability of common bean obtained through mixed models analyses

  • Rodrigo Chimenez-Franzon Universidade Estadual de Maringá
  • Maria Celeste Gonçalves-Vidigal Universidade Estadual de Maringá
  • Giseli Valentini Universidade Estadual de Maringá https://orcid.org/0000-0002-5876-5888
  • Leonel Domingos Moiana Institute of Mozambique
  • Rodrigo Ivan Contreras Soto Universidad de O'Higgins
  • Lorenna Lopes Sousa Universidade Estadual de Maringá https://orcid.org/0000-0002-1154-5394
  • Pedro Soares Vidigal Filho Universidade Estadual de Maringá

Resumo

The common bean provides a diet rich in vitamins, fiber, minerals and especially in proteins, which can provide food security for poor people in many countries. With the increase in demand for food production, cultivars with high grain yield potential that can be planted in different environments have been the focus of common bean breeding programs. Therefore, this study aimed to evaluate genetic parameters, grain yield, adaptability and stability simultaneously of common bean lines that compose the Value for Cultivation and Use trials of the South region of Brazil. The experiments were conducted in 13 environments in the states of Paraná, Santa Catarina and Rio Grande do Sul. The analysis of adaptability and stability were performed

The common bean provides a diet rich in vitamins, fiber, minerals and especially in proteins, which can provide food security for poor people in many countries. With the increase in demand for food production, cultivars with high grain yield potential that can be planted in different environments have been the focus of common bean breeding programs. Therefore, this study aimed to evaluate genetic parameters, grain yield, adaptability and stability simultaneously of common bean lines that compose the Value for Cultivation and Use trials of the South region of Brazil. The experiments were conducted in 13 environments in the states of Paraná, Santa Catarina and Rio Grande do Sul. The analysis of adaptability and stability were performed using mixed linear models by the Residual Maximum Likelihood and the Best Linear Unbiased Predictor for predicting the genotypic values through Selegen statistical program. The selective accuracy of genotypes for their genotypic values was 87% and the broad-sense heritability for grain yield was 13%. The genotypes CHC 98-42, BRS Esteio, CNFP-10794, CHP 01-238, FT 08-75, IPR Campos Gerais, LP 09-40, CNFC 10762, C 4-7-8-1-2 and LEC 01-11 were superior based on the method of Harmonic Mean of Relative Performance of Genotypic Values. These genotypes presented a higher mean grain yield in comparison to the other evaluated genotypes, and could be recommended for cultivation in these regions. In addition, it was possible to obtain genetic gains of up to 9.5% for the CHC 98-42 line, showing its high genetic potential.

Downloads

Não há dados estatísticos.

Biografia do Autor

Giseli Valentini, Universidade Estadual de Maringá

Department of Agronomy

Referências

Annicchiarico, P. (1992) Cultivar adaptation and recommendation from alfalfa trials in Northern Italy. Journal of Plant Breeding, 46, 269-278.

Bertoldo, J. G., Coimbra. J. L. M., Guidolin, A. F., Nodari, R. O., Elias, H. T., Barili, L. D. Vale, N, M., & Rozzetto, D. S. (2009) Rendimento de grãos em feijão preto: o componente que mais interfere no valor fenotípico é o ambiente. Ciência Rural, 39, 1974-1982. http://dx.doi.org/10.1590/S0103-84782009005000166

Borges, V., Soares, A. A., Reis, M. S., Resende, M. D. V., Cornélio, V. M. O., Leite, N. A., & Vieira, A. R. (2010) Desempenho genotípico de linhagens de arroz de terras altas utilizando metodologia de modelos mistos. Bragantia, 69, 833-842. http://dx.doi.org/10.1590/S0006-87052010000400008

Broughton, W. J., Hernandez, G., Blair, M. W., Beebe, S. E., Gepts, P., & Vanderleyden, J. (2003) Bean (Phaseolus sp.) model food legumes. Plant and Soil, 252, 55-128. http://dx.doi.org/10.1023/A:1024146710611

Burgueño, J., Crossa, J., Cornelius, P.L., & Yang, R.-C. (2008) Using factor analytic models for joining environments and genotypes without crossover genotype �? environment interaction. Crop Science, 48, 1291-1305. http://dx.doi.org/%2010.2135/cropsci2007.11.0632

Carbonell, S. A. M., Chiorato, A. F., Resende, M. D. V., Dias, L. A. S., Beraldo, A. L. A., & Perina, E. F. (2007) Estabilidade de cultivares e linhagens de feijoeiro em diferentes ambientes no Estado de São Paulo. Bragantia, 66, 193-201. http://dx.doi.org/10.1590/S0006-87052007000200003

Chiorato, A. F., Carbonell, S. A. M., Dias, L. A. S., & Resende, M. D. V. (2008) Prediction of genotypic values and estimation of parameters in common bean. Brazilian Archives of Biology and Technology, 51(3), 465-472. http://dx.doi.org/10.1590/S1516-89132008000300005

Coêlho, M., Gonçalves-Vidigal, M. C., Vidigal Filho, P. S., Franzon, R. C., & Martins, V. S. R. (2020). Genetic diversity of Colletotrichum lindemuthianum races based on ITS-rDNA regions. Agronomy Science and Biotechnology, 6, 1�??18. https://doi.org/10.33158/asb.r112.v6.2020

Coimbra, J. L. M., Barili, L. D., Vale, N. M., Guidolin, A. F., Bertoldo, J. G., Rocha, F., & Toaldo, D. (2008). Seleção para caracteres adaptativos em acessos de feijão usando REML/BLUP. Magistra, 20, 177-185.

Coimbra, J. L. M., Guidolin, A. F., Carvalho, F. I. F., Coimbra, S. M. M., & Hemp, S. (1999) Reflexos da interação genótipo �? ambiente e suas implicações nos ganhos de seleção em genótipos de feijão (Phaseolus vulgaris L.). Ciência Rural, 29, 433-439. http://dx.doi.org/10.1590/S0103-84781999000300009

Colombari-Filho, J. M., Resende, M. D. V., Morais, O. P., Castro, A. P., Guimarães, E. P., Pereira, J. A., Utumi, M. M., & Breseghello, F. (2013) Upland rice breeding in Brazil: a simultaneous genotypic evaluation of stability, adaptability and grain yield. Euphytica, 192, 117-129. http://dx.doi.org/10.1007/s10681-013-0922-2

Corte, A. D., Moda-Cirino, V., & Destro, D. (2002) Adaptability and phenotypic stability in early common bean cultivars and lines. Crop Breeding and applied Biotechnology, 2(4), 525-534. http://dx.doi.org/%2010.12702/1984-7033.v02n04a05

Crossa, J. (2012) From genotype �? environment interaction to gene �? environment interaction. Current Genomics, 13, 225-244. http://dx.doi.org/%2010.2174/138920212800543066

Cruz, C. D., Torres, R. A. A., & Vencovsky, R. (1989) An alternative approach to the stability analysis proposed by Silva and Barreto. Genetics and Molecular Biology, 12, 567-580.

Eberhart, S. A., & Russell, W. A. (1966) Stability parameters for comparing varieties. Crop Science, 6, 36 40. http://dx.doi.org/10.2135/cropsci1966.0011183X000600010011x

FAO - Food and Agriculture Organization (2018) http://www.fao.org

Farias, F. J. C., Carvalho, L. P., Silva Filho, J. L., & Teodoro, P. E. (2016) Usefulness of the HMRPGV method for simultaneous selection of upland cotton genotypes with greater fiber length and high yield stability. Genetics and Molecular Research, 15, 1-7. DOI http://dx.doi.org/10.4238/gmr.15038439

Ferreira, L. L. F., Carvalho, I. R., Conte, G. G., Amaral, G. C. L., Campos, J. N., Tomazele, A. A. S., �?� Loro, M. V. (2021). Effect of biostimulant on yield characters of common bean cultivars under Southwestern Goiás conditions. Agronomy Science and Biotechnology, 8, 1�??13. https://doi.org/10.33158/asb.r148.v8.2022

Finlay, K. W., & Wilkinson, G. N. (1963) The analysis of adaptation in a plant-breeding programme. Australian Journal of Agricultural Research, 14, 742-754.

Franzon, R. C., Gonçalves-Vidigal, M. C., Caixeta, M. P., Vidigal Filho, P.S., Gilio, T. A. S., & Castro, S. A. L. (2016) Genotype x environment interaction analysis by mixed models in Brazilian common bean inbred lines. Annual report of the Bean Improvement Cooperative, 59, 51-52.

Friesen, L. F., Brûlé-Babel, A. L., Crow, G. H., & Rothenburger, P. A. (2016) Mixed model and stability analysis of spring wheat genotype yield evaluation data from Manitoba, Canada. Canadian Journal of Plant Science, 96, 305-320. http://dx.doi.org/10.1139/cjps-2015-0252

Huehn, M. (1990) Nonparametric measures of phenotypic stability. Part 1. Euphytica, 47, 189-194. http://dx.doi.org/10.1007/BF00024241

Laidig, F., Drobek, T., & Meyer, U. (2008) Genotypic and environmental variability of yield for cultivars from 30 different crops in German official variety trials. Plant Breeding, 127, 541�??547. http://dx.doi.org/10.1111/j.1439-0523.2008.01564.x

Levene, H. (1960) Robust tests for equality of variances. In: Olkin, I., Ghurye, S. G., Hoeffding, W., Madow, W. G., & Mann H. B. (Eds.) Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling, Menlo Park, CA: Stanford University Press, p.278�??292.

Lin, C. S., & Binns, M. R. (1988) A method of analysing cultivars x location x year experiments: a new stability parameter. Theoretical and Applied Genetics, 76(3), 425-430. http://dx.doi.org/10.1007/BF00265344.

Maia, M. C. C., Resende, M. D. V., Paiva, J. R., Cavalcanti, J. J. V., & Barros, L. M. (2009) Seleção simultânea para produção, adaptabilidade e estabilidade genotípicas em clones de cajueiro, via modelos mistos. Pesquisa Agropecuária Tropical, 39, 43-50.

MAPA - Ministério da Agricultura, Pecuária e do Abastecimento (2013) Registro Nacional de Cultivares (RNC). Brasília, DF: MAPA https://www.gov.br/agricultura/pt-br/assuntos/insumos-agropecuarios/insumos-agricolas/sementes-e-mudas/registro-nacional-de-cultivares-2013-rnc-1

Moiana, L. D., Vidigal Filho, P. S., Gonçalves-Vidigal, M. C., Maleia, M. P., & Mindo, N. (2014) Application of mixed models for the assessment genotype and environment interactions in cotton (Gossypium hirsutum) cultivars in Mozambique. African Journal of Biotechnology, 13(19), 1985-1991. http://dx.doi.org/10.5897/AJB2013.12926

Oliveira, R. A., Resende, M. D. V., Daros, E. J., Bespalhok, F. J. C., Zambon, J. L. C., Ido, O. T., Weber, H., & Koehle, H. S. (2005) Genotypic evaluation and selection for sugarcane clones in three environments in state of Parana. Crop Breeding and Applied Biotechnology, 5, 426-434. http://dx.doi.org/%2010.12702/1984-7033.v05n04a08

Paulino, P. P. S., Gonçalves-Vidigal, M. C., Bisneta, M. V., Vidigal Filho, P. S., Nunes, M. P. B. A., Xavier, L. F. S., �?� Lacanallo, G. F. (2021). Occurrence of anthracnose pathogen races and resistance genes in common bean across 30 years in Brazil. Agronomy Science and Biotechnology, 8, 1�??21. https://doi.org/10.33158/asb.r140.v8.2022

Pereira, H. S., Bueno, L. G., Del Peloso, M. J., Abreu, A. F. B., Moreira, J. A. A., Martins, M., Wendland, A., Faria, L. C., Souza, T. L. P. O., & Melo, L. C. (2014) Agronomic performance and stability of Andean common bean lines with white grains in Brazil. Bragantia, 73 (2), 130-137. http://dx.doi.org/10.1590/brag.2014.020

Petry, N., Boy, E., Wirth, J. P., & Hurrell, R. F. (2015). Rewiew: The potential of the common bean (Phaseolus vulgaris) as a vehicle for iron biofotification. Nutrients, 7(2), 1144-1173. http://dx.doi.org/10.3390/nu7021144

Piepho, H. P., Möhring, J., Melchinger, A. E., & Büchse, A. (2008) BLUP for phenotypic selection in plant breeding and variety testing. Euphytica, 161, 209-228. http://dx.doi.org/10.1007/s10681-007-9449-8

Plaisted, R. L., & Peterson, L. C. (1959) A technique for evaluating the ability of selection to yield consistently in different locations or seasons. American Potato Journal, 36, 385-395. http://dx.doi.org/%2010.1007/BF02852735

Resende, M. D. V. (2007) SELEGEN-REML/BLUP: Sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Colombo, PR: Embrapa Florestas.

Resende, M. D. V., & Duarte, J. B. (2007) Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesquisa Agropecuária Tropical, 37(3), 182-194.

Resende, M. D. V., Furlani Júnior, E., Moraes, M. L. T., & Fazuoli, L. C. (2001) Estimação de parâmetros genéticos e predição de valores genotípicos no melhoramento do cafeeiro pelo procedimento REML/BLUP. Bragantia, 60(3), 185-193. http://dx.doi.org/10.1590/S0006-87052001000300005

Robinson, G. K. (1991) That BLUP is a good thing: the estimation of random effects. Statistical Science, 6(1), 15-32. http://dx.doi.org/10.1214/ss/1177011926

Rodovalho, M. A., Coan, M. M. D., Scapim, C. A., Barth Pinto, R. J., & Contreras-Soto, R. I. (2015) Comparison of HMRPGV, Lin and Binn's, and Annichiarico's methods for maize hybrid selection for high and stable yield. Maydica, 60(1), M 10.

SAS - Statistical Analysis System (2009) Software SAS 9.1. Cary, NC: SAS Institute Inc.

Shapiro, S. S., & Wilk, M. B. (1965) An Analysis of Variance Test for Normality (Complete Samples). Biometrika, 52(3/4), 591-611. http://dx.doi.org/%2010.1093/biomet/52.3-4.591

Verma, M. M., Chahal, G. S., & Murty, B. R. (1978) Limitations of conventional regression analysis: a proposed modification. Theoretical and Applied Genetics, 53, 89-91. http://dx.doi.org/10.1007/BF00817837

Wang, W. (2016) Identifiability of covariance parameters in linear mixed effects models. Linear Algebra and its Applications, 506, 603-613. http://dx.doi.org/10.1016/j.laa.2016.06.022

Wricke, G. (1965) Zur berechnung der okovalenz bei sommerweizen und hafer. Zeitschrift fur Pflanzenzuchtung, 52, 127-138.

Zobel, R. W., Wright, M. J., & Gauch, H. G. (1988). Statistical analysis of a yield trial. Agronomy Journal, 80, 388-393. http://dx.doi.org/10.2134/agronj1988.00021962008000030002x

Publicado
2022-02-25
Como Citar
Chimenez-Franzon, R., Gonçalves-Vidigal, M. C., Valentini, G., Domingos Moiana, L., Soto, R. I. C., Sousa, L. L., & Filho, P. S. V. (2022). Genetic parameters, yield adaptability and stability of common bean obtained through mixed models analyses. ASB Journal, 8, 1-16. https://doi.org/10.33158/ASB.r158.v8.2022
Seção
Artigos

##plugins.generic.recommendByAuthor.heading##