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Yield adaptability and stability of semi-erect cowpea genotypes in the Northeast region of Brazil by REML/BLUP1 1 Pesquisa desenvolvida pela Embrapa (Empresa Brasileira de Pesquisa Agropecuária), Programa de Melhoramento de Feijão-caupi da Embrapa Meio-Norte, região Nordeste, Teresina-PI, Brasil

Adaptabilidade e estabilidade produtiva de genótipos de feijão-caupi semieretos no Nordeste do Brasil via REML/BLUP

ABSTRACT

Cowpea is grown in the various soil and climatic conditions of the Northeast region of Brazil. Thus, selecting and developing cultivars with high yield, stability, and adaptability for this region is necessary due to the genotype × environment interaction. The objective of this work was to select cowpea lines of semi-erect plant simultaneously for high yield, adaptability, and genotypic stability in the Northeast region of Brazil by the REML/BLUP procedure. Twenty semi-erect genotypes-15 lines and five cultivars-were evaluated in 37 environments of the Northeast region from 2013-2015. The experiments were carried out under rainfed conditions in a randomized complete block design with four replications. The adaptability and genotypic stability were evaluated by the REML/BLUP procedure. The environmental variance was the largest factor in the phenotypic variance and the genotype × environment interaction was complex-type, with a grain yield ranging from 277 kg ha-1 (Serra Talhada PE, 2015) to 2,845 kg ha-1 (São Raimundo das Mangabeiras MA, 2013), and an overall mean of 1,342 kg ha-1. According to the Harmonic Mean of Relative Performance of Genetic Values (HMRPGV) estimates, the lines MNC04-795F-153 and MNC04-795F-159 were those that simultaneously had high yield, adaptability, and genotypic stability, and can be recommended and grown with greater probability of success in the evaluated environments in the Northeast region of Brazil.

Key words:
Vigna unguiculata; Grain yield; Genotype × environment interaction; Mixed models

RESUMO

O feijão-caupi é cultivado em diferentes condições edafoclimáticas da região Nordeste do Brasil. Devido à existência da interação entre genótipos e ambientes, torna-se necessário selecionar e desenvolver cultivares para essa região com alta produtividade, estabilidade e adaptabilidade. Este trabalho teve como objetivo selecionar linhagens de feijão-caupi de porte semiereto, simultaneamente, para alta produtividade, adaptabilidade e estabilidade genotípica na região Nordeste do Brasil, via procedimento REML/BLUP. Foram avaliados 20 genótipos de porte semiereto, sendo 15 linhagens e cinco cultivares, em 37 ambientes da Região Nordeste, no período de 2013 a 2015. Os experimentos foram conduzidos em condições de sequeiro, em delineamento de blocos completos casualizados, com quatro repetições. A adaptabilidade e estabilidade genotípica foram avaliadas via procedimento REML/BLUP. A variância ambiental foi o maior componente da variância fenotípica e a interação genótipos x ambientes foi do tipo complexa, com a produtividade de grãos variando de 277 kg ha-1 (Serra Talhada-PE, 2015) a 2.845 kg ha-1(São Raimundo das Mangabeiras-MA, 2013) e média geral de 1.342 kg ha-1. De acordo com as estimativas de média harmônica de desempenho relativo de valores genotípicos (MHPRVG), as linhagens MNC04-795F-153 e MNC04-795F-159 reúnem simultaneamente alta produtividade, estabilidade e adaptabilidade genotípica, podendo ser indicadas com maior probabilidade de sucesso para o cultivo nos ambientes de avaliação da região Nordeste do Brasil.

Palavras-chave:
Vigna unguiculata; Produtividade de grãos; Interação genótipos x ambientes; Modelos Mistos

INTRODUCTION

Cowpea (Vigna unguiculata (L.) Walp.) is an important legume in the Northeast region of Brazil, and a source of energy and protein. The cultivation of this species generates employment and income for the population of this region. Cowpea is the second most consumed type of bean in Brazil, and its cultivation is concentrated in the North, Northeast, and Center-West regions. There are no official statistics on cowpea production in Brazil; thus, based on the estimates of CONAB (2017)COMPANHIA NACIONAL DE ABASTECIMENTO. Acompanhamento da safra brasileira de grãos. v. 4, safra 2016/17, n. 10. Brasília: CONAB, 2017. p. 95. Disponível em: <http://www.conab.gov.br/OlalaCMS/uploads/arquivos/17_07_12_11_17_01_boletim_graos_julho_2017.pdf>. 2017. Acesso em: 14 jul. 2017.
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, the Northeast region presented in 2016 an area of 1,029,600 ha with a production of 196,100 Mg. This represents 82.56% and 54.00% of the area and production of this legume in Brazil, respectively. The largest national producers are the states of Mato Grosso, Ceará, and Maranhão. The total area for cowpea production in Brazil is 1,247,100 ha and its production is 362,500 Mg, which represents 14.43% of all beans produced in Brazil.

Considering that cowpea is cultivated in a wide range of environments in Brazil, but the occurrence of genotype × environment interaction (G×E) may hinder the selection of superior genotypes and the recommendation of cultivars (CARVALHO et al., 2016CARVALHO, L. C. B. et al. Evolution of methodology for the study of adaptability and stability in cultivated species. African Journal of Agricultural Research, v. 11, n. 12, p. 990-1000, 2016.; OLIVEIRA; FONTES; ROCHA, 2015OLIVEIRA, I. J.; FONTES, J. R. A.; ROCHA, M. M. Seleção de genótipos de feijão-caupi para adaptabilidade e estabilidade produtiva no Estado do Amazonas. Revista de Ciência Agrárias, v. 58, n. 3, p. 292-300, 2015.; ROCHA et al., 2012). Thus, in the final stages of a breeding program, elite lines are tested in various environments; this allows an investigation of the magnitude of the G×E, adaptability, and yield stability, which subsidize the recommendation of cultivars for broad or specific conditions of adaptation.

In the last 60 years, several methodologies to study the adaptability and stability of genotypes in multiple environments were developed to help the breeder to select the most stable and suitable genotypes for crops in different environments (CARVALHO et al., 2016CARVALHO, L. C. B. et al. Evolution of methodology for the study of adaptability and stability in cultivated species. African Journal of Agricultural Research, v. 11, n. 12, p. 990-1000, 2016.). The most commonly methodologies used in cowpea are the AMMI (BARROS et al., 2013BARROS, M. A. et al. Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesquisa Agropecuária Brasileira, v. 48, n. 4, p. 403-410, 2013.; DDAMULIRA et al., 2015DDAMULIRA, G. et al. Grain yield and protein content of Brazilian cowpea genotypes under diverse Ugandan environments. American Journal of Plant Science, v. 6, p. 2074-2084, 2015.; SANTOS et al., 2015SANTOS, A. et al. Adaptability and stability of cowpea genotypes to Brazil Midwest. African Journal of Agricultural Research, v. 10, n. 41, p. 3901-3908, 2015.), GGE Biplot (OKORONKWO; NWOFIA, 2016OKORONKWO, C. M.; NWOFIA, G. E. Yield stability and inter relationships between seed yield and associated traits of 25 cowpea (Vigna unguiculata [L.] Walp.) genotypes. African Journal of Agricultural Science and Technology, v. 4, n. 5, p. 728-734, 2016.; OLAYIWOLA; SOREMI; OKELEYE, 2015OLAYIWOLA, M. O.; SOREMI, P. A. S.; OKELEYE, K. A. Evaluation of some cowpea (Vigna unguiculata L. [Walp.]) genotypes for stability of performance over 4 years. Current Research in Agricultural Sciences, v. 2, n. 1, p. 22- 30, 2015.; SANTOS et al., 2016SANTOS, A. et al. Adaptabilidade e estabilidade de genótipos de feijão-caupi ereto via REML/BLUP e GGE Biplot. Bragantia, v. 75, n. 3, p. 55-62, 2016.), Bayesian approache (BARROSO et al., 2016BARROSO, L. M. A. et al. Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genetics and Molecular Research, v. 15, n. 1, p. 1-11, 2016.; TEODORO et al., 2015TEODORO, P. E. et al. Perspectiva bayesiana na seleção de genótipos de feijão-caupi em ensaios de valor de cultivo e uso. Pesquisa Agropecuária Brasileira, v. 50, n. 10, p. 878-885, 2015.), and artificial neural networks (TEODORO et al., 2015TEODORO, P. E. et al. Perspectiva bayesiana na seleção de genótipos de feijão-caupi em ensaios de valor de cultivo e uso. Pesquisa Agropecuária Brasileira, v. 50, n. 10, p. 878-885, 2015.).

The REML/BLUP procedure has been one of the most used techniques in studies on adaptability and genotypic stability; it is based on mixed models. This procedure estimates the components of variance by the Restricted Maximum Likelihood (REML) and the prediction of genetic values by the Best Linear Unbiased Prediction (BLUP) (CARIAS et al., 2014CARIAS, C. M. O. M. et al. Produtividade de grãos de cafeeiro conilon de diferentes grupos de maturação pelo procedimento REML/BLUP. Semina: Ciências Agrárias, v. 35, n. 2, p. 707-718, 2014.). It was originally recommended for studies on quantitative genetics and selection of perennial plants (RESENDE, 2007aRESENDE, M. D. V. Matemática e estatística na análise de experimentos e no melhoramento genético. Colombo: Embrapa Florestas, 2007a. 362 p.,bRESENDE, M. D. V. Selegen-Reml/Blup: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Colombo: Embrapa Florestas , 2007b. 359 p.); however, it has also been used in annual species such as rice (BORGES et al., 2010BORGES, V. et al. Desempenho genotípico de linhagens de arroz de terras altas utilizando metodologia de modelos mistos. Bragantia, v. 69, n. 4, p. 833-842, 2010.), common bean (CHIORATO et al., 2008CHIORATO, A. F. et al. Prediction of genotypic values and estimate of genetic parameters in common bean. Brazilian Archives of Biology and Technology, v. 51, n. 3, p. 465-472, 2008.; PEREIRA et al., 2016PEREIRA, T. C. V. et al. Reflexos da interação genótipo x ambiente sobre o melhoramento genético de feijão. Ciência Rural, v. 46, n. 3, p. 411-417, 2016.), soybean ( TESSELE et al.,2016)TESELLE, A. et al. Adaptability and stability of soybean cultivars under different times of sowing in Southern Brazil. Journal of Plant Sciences, v. 4, n. 2, p. 17-22, 2016., and wheat (SILVA et al., 2011SILVA, R. R. et al. Adaptabilidade e estabilidade de cultivares de trigo em diferentes épocas de semeadura, no Paraná. Pesquisa Agropecuária Brasileira, v. 46, n. 11, p. 1439-1447, 2011.).

Adaptability and stability studies in cowpea using the REML/BLUP procedure have increased (SANTOS et al., 2016SANTOS, A. et al. Adaptabilidade e estabilidade de genótipos de feijão-caupi ereto via REML/BLUP e GGE Biplot. Bragantia, v. 75, n. 3, p. 55-62, 2016.; TORRES et al., 2015TORRES, F. E. et al. Interação genótipos x ambientes em genótipos de feijão-caupi semiprostrados via modelos mistos. Bragantia, v. 74, n. 3, p. 15-20, 2015., 2016). This is because it allows simultaneous selection for yield, adaptability, and stability in the context of mixed models through the use of the Harmonic Mean of Relative Performance of Genetic Values (HMRPGV) method, proposed by Resende (2004)RESENDE, M. D. V. Métodos estatísticos ótimos na análise de experimentos de campo. Colombo: Embrapa Florestas, 2004. 65 p. (Embrapa Florestas. Documentos, 100)..

The objective of this work was to select semi-erect cowpea lines simultaneously for high yield, adaptability, and genotypic stability in the Northeast region of Brazil by the REML/BLUP procedure.

MATERIAL AND METHODS

Twenty cowpea genotypes of semi-erect plant were evaluated-15 lines and five cultivars-from the Embrapa Meio-Norte Cowpea Breeding Program (Table 1). These lines are part of the value-of-cultivation and use (VCU) trials, which are required for registering new cultivars by the National Register of Cultivars (RNC) of the Ministry of Agriculture, Livestock, and Food Supply (MAPA). These genotypes were selected in intermediate trials, which precede the VCU trials.

Table 1
Semi-erect cowpea genotypes evaluated in the Northeast region of Brazil, from 2013 to 2015, their genealogy and commercial subclass (CS)

The genotypes were evaluated for grain yield (kg ha-1) in 22 locations in the Northeast region of Brazil (Table 2) under rainfed conditions from 2013 to 2015. Some VCU trials were conducted in 1, 2, or 3 crop seasons totaling 37 environments. Each environment was represented by the location initial letters and year of the crop season: APOD13, ARAP13, BARR13, CARI13, FREI13, ITAP13, MATA13, REDE13, SRMA13, UMBA13, URUC13, ARAR14, CARI14, BARR14, FEIR14, FREI14, GOIA14, IPAN14, ITAP14, MATA14, SERT14, SUMBA14, ARAR15, AROE15, CAMP15, FEIR15, FREI15, IPAN15, GOIA15, LAGS15, NSDO15, PACA15, SAOJ15, SERT15, SRMA15, UMBA15, and URUC15.

Table 2
Altitude, geographic coordinate, biome, ecosystem, and climate of the locations where the value-of-cultivation and use trials of semi-erect cowpea were conducted in the Northeast region of Brazil, from 2013 to 2015

The planting season varied according to the rainy season in the states, which occurred in January to March, except in Alagoas and Sergipe, which occurred in June. All the trials were conducted in a complete randomized block design with 20 treatments and four replications. The treatments were represented by a plot of 2.0 m x 5.0 m with four 5.0 m rows spaced 0.50 m apart, with 0.25 m between plants. The evaluation area was represented by the two central rows. Four seeds were sown per hole, and 20 days after sowing the plants were thinned, leaving two plants per hole. Cultural practices were carried out for the crop as recommended.

Individual analysis of variance for environments and joint analysis of variance for all environments were performed. The joint analysis of variance considered the effect of genotypes as fixed, and the effect of environments as random. The statistical model used followed the equation:

(1) Y ijk = μ + g i + e j + ge ij + β k J + ε ijk

where in: Yijk is the observed value of the genotype i in the environment j and block k ; µ is the overall mean of the trait; gi is the effect of the genotype i ; ej is the effect of the environment j ; geij is the effect of the interaction of the genotype i with the environment j ; βk(J) is the effect of the block k within the environment j ; and εijk is the experimental error associated with the plot ijk.

The mixed models approach through Restricted Maximum Likelihood (REML) and Best Linear Unbiased Prediction (BLUP) multivariate, i.e., REML/BLUP procedure, (RESENDE, 2007bRESENDE, M. D. V. Selegen-Reml/Blup: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Colombo: Embrapa Florestas , 2007b. 359 p.) was used for the analysis of adaptability and stability. This procedure is a method for ordering the genotype simultaneously regarding their genetic values (yield) and stability; it represents the BLUP procedure under the harmonic mean of the data. The lower the standard deviation of the genotypic behavior in the environments, the greater the harmonic mean of genotypic values (HMGV) in the environments. Thus, selection by the highest HMGV implies both selection for yield and stability (RESENDE, 2007bRESENDE, M. D. V. Selegen-Reml/Blup: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Colombo: Embrapa Florestas , 2007b. 359 p.).

In the context of the mixed models, a simple and efficient measure is the relative performance of genotypic values (RPGV) in the environments, i.e., the adaptability of genetic values. The quantity RPGV*OM refers to the relative performance genotypic value multiplied by the overall mean of all environments, providing the average genotypic value, capitalizing the adaptability (RESENDE, 2007bRESENDE, M. D. V. Selegen-Reml/Blup: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Colombo: Embrapa Florestas , 2007b. 359 p.).

Simultaneous selection for yield adaptability and stability in the context of mixed models can be performed by the Harmonic Mean of Relative Performance of Genetic Values (HMRPGV), proposed by Resende (2004)RESENDE, M. D. V. Métodos estatísticos ótimos na análise de experimentos de campo. Colombo: Embrapa Florestas, 2004. 65 p. (Embrapa Florestas. Documentos, 100).. The quantity HMRPGV*OM refers to the HMRPGV multiplied by the overall mean of all environments, which provides the mean genotypic value penalized by instability and capitalized by adaptability.

The following statistical model was used for the randomized block designs with one observation per plot and several environments:

(2) Y = Xb + Zg + Wga + e

where in: y, b, g, ga, and . are the data vectors of fixed effects (mean of blocks through environments), of genotypic effects of the genotype (random), of effects of the genotype × environment interaction (G×E) (random), and of random errors, respectively; X, Z and . are the incidence matrices for b, g, and ga, respectively.

The Harmonic Mean of Genotypic Values (HMGV) was used for the evaluation of stability; the RPGV was used for the simultaneous evaluation of yield and adaptability; and the HMRPGV was used for the simultaneous evaluation of yield, adaptability, and stability. These evaluation were carried out using the following expressions:

(3) HMGV i = a / i = 1 a 1 / Vg j

(4) RPGV i = 1 / a Vg j / M j

(5) HMRPGV i = n / j = 1 n 1 / Vg ij

where in: n is the number of evaluation environments of the genotype i ; Vgij is the genotypic value of the genotype i in the environment j , expressed as a proportion of the average of this environment.

The HMRPGV method (RESENDE, 2007aRESENDE, M. D. V. Matemática e estatística na análise de experimentos e no melhoramento genético. Colombo: Embrapa Florestas, 2007a. 362 p.) has the advantages of providing adaptability and genotypic-rather than phenotypic-stability; allowing the managing of heterogeneity of variances; and providing already-penalized genetic values of instability. Moreover, this method can be applied to any number of environments, eliminate noises of the genotype × environment interaction (G×E), while considering the heritability of these effects; and allows the computation of genetic gain with selection by the three attributes simultaneously.

The analysis of variance was performed using the SAS software (SAS INSTITUTE, 2002SAS INSTITUTE INC. SAS/STAT user's guide. Version 8.1. Cary, 2002. v. 1, 890 p.). The analyses of adaptability and genotypic stability were performed by the model 54 of the Selegen-Reml/Blup software (RESENDE, 2007bRESENDE, M. D. V. Selegen-Reml/Blup: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Colombo: Embrapa Florestas , 2007b. 359 p.).

RESULTS AND DISCUSSION

The joint analysis of variance for grain yield is presented in Table 3. Although all genotypes have shown a high inbreeding level and some parentage (Table 1) and underwent several selection cycles, they differed significantly (. <0.0001), denoting the existence of selectable variability.

Table 3
Joint analysis of variance for grain yield of 20 semi-erect cowpea genotypes evaluated in 37 environments of the Northeast region of Brazil, from 2013 to 2015

Barros et al. (2013)BARROS, M. A. et al. Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesquisa Agropecuária Brasileira, v. 48, n. 4, p. 403-410, 2013., Santos et al. (2015)SANTOS, A. et al. Adaptability and stability of cowpea genotypes to Brazil Midwest. African Journal of Agricultural Research, v. 10, n. 41, p. 3901-3908, 2015. and Barroso et al. (2016)BARROSO, L. M. A. et al. Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genetics and Molecular Research, v. 15, n. 1, p. 1-11, 2016., evaluated 20 cowpea genotypes for yield adaptability and stability in the Mid-North region and in Mato Grosso do Sul, Brazil, respectively, and also found differences between homozygous genotypes.

The environments also differed for grain yield (. <0.0001), denoting that their eco-physiographic differences (Table 2) combined with the climatic variations affected this trait.

Barroso et al. (2016)BARROSO, L. M. A. et al. Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genetics and Molecular Research, v. 15, n. 1, p. 1-11, 2016. evaluated the grain yield of 20 cowpea genotypes in six environments of Mato Grosso do Sul and also found differences between the testing environments; affirming that the edaphoclimatic factors had the greatest effect on the adaptability and stability of the genotypes. Ddamulira et al. (2015)DDAMULIRA, G. et al. Grain yield and protein content of Brazilian cowpea genotypes under diverse Ugandan environments. American Journal of Plant Science, v. 6, p. 2074-2084, 2015., who evaluated the yield adaptability and stability of 25 cowpea genotypes in three environments in Uganda, and Oliveira, Fontes and Rocha (2015)OLIVEIRA, I. J.; FONTES, J. R. A.; ROCHA, M. M. Seleção de genótipos de feijão-caupi para adaptabilidade e estabilidade produtiva no Estado do Amazonas. Revista de Ciência Agrárias, v. 58, n. 3, p. 292-300, 2015., who evaluated cowpea genotypes in several environments in the state of Amazonas in Brazil, also found different grain yields depending on the environment.

The overall mean grain yield was 1,342 kg ha-1. This mean is well above the national (369 kg ha-1) and world (461.30 kg ha-1) mean for yield of cowpea (FREIRE FILHO, 2011FREIRE FILHO, F. R. (Ed.). Feijão-caupi no Brasil: produção, melhoramento genético, avanços e desafios. Teresina: Embrapa Meio-Norte, 2011. 84 p.) and is also above the means obtained in other studies on cowpea genotypes in Brazil (BARROS et al., 2013BARROS, M. A. et al. Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesquisa Agropecuária Brasileira, v. 48, n. 4, p. 403-410, 2013.; BARROSO et al., 2016BARROSO, L. M. A. et al. Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genetics and Molecular Research, v. 15, n. 1, p. 1-11, 2016.; SANTOS et al., 2015SANTOS, A. et al. Adaptability and stability of cowpea genotypes to Brazil Midwest. African Journal of Agricultural Research, v. 10, n. 41, p. 3901-3908, 2015.; TORRES et al., 2015TORRES, F. E. et al. Interação genótipos x ambientes em genótipos de feijão-caupi semiprostrados via modelos mistos. Bragantia, v. 74, n. 3, p. 15-20, 2015., 2016TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016.). This shows the great potential of this line group in regard to grain yield and the possibility of selecting lines with higher means than the commercial cultivars.

The environment São Raimundo das Mangabeiras-MA 2013 (SRMA13) was the most favorable for grain yield (2,485 kgha-1), while Serra Talhada-PE 2015 (SERT15) was the least favorable (277 kg ha-1) (Figure 1).

Figure 1
Behavior of the grain yield of 37 testing environments obtained from evaluation of 20 semi-erect cowpea genotypes in the Northeast region of Brazil from 2013 to 2015

The G×E for grain yield was highly significant (. <0.0001) (Table 3); it showed the different behavior of the genotypes depending on the testing environments. This lead to difficulties in the selection of superior genotypes and recommending cultivars (CARVALHO et al., 2016CARVALHO, L. C. B. et al. Evolution of methodology for the study of adaptability and stability in cultivated species. African Journal of Agricultural Research, v. 11, n. 12, p. 990-1000, 2016.; ROCHA et al., 2012ROCHA, M. M. et al. Adaptabilidade e estabilidade de genótipos de feijão-caupi quanto à produção de grãos frescos, em Teresina-PI. Revista Científica Rural, v. 14, n. 1, p. 40-55, 2012.), since the cultivars adapted to a particular condition may not perform well in other environmental conditions (OLAYIWOLA, SOREMI; OKELEYE, 2015OLAYIWOLA, M. O.; SOREMI, P. A. S.; OKELEYE, K. A. Evaluation of some cowpea (Vigna unguiculata L. [Walp.]) genotypes for stability of performance over 4 years. Current Research in Agricultural Sciences, v. 2, n. 1, p. 22- 30, 2015.; TEODORO et al., 2015TEODORO, P. E. et al. Perspectiva bayesiana na seleção de genótipos de feijão-caupi em ensaios de valor de cultivo e uso. Pesquisa Agropecuária Brasileira, v. 50, n. 10, p. 878-885, 2015.).

According to estimates of components of variance (REML), the environmental variance contributed most to the phenotypic variance (Table 4). It represented 64% of this variance, followed by the G×E (30%), and genotypic (6%) variances.

Table 4
Estimates of components of variance (individual REML) and genetic parameters obtained from the evaluation of 20 semi-erect cowpea genotypes in 37 environments in the Northeast region of Brazil, from 2013 to 2015

The preponderance of the environmental variance in relation to the other components of the phenotypic variance are in agreement with the results found in the analysis of variance (Table 3), the information of the test environments (Table 2), and the environment means (Figure 1), which showed marked contrasts between testing environments for grain yield.

Studies evaluating genotypes of common bean (CHIORATO et al., 2008CHIORATO, A. F. et al. Prediction of genotypic values and estimate of genetic parameters in common bean. Brazilian Archives of Biology and Technology, v. 51, n. 3, p. 465-472, 2008.; PEREIRA et al., 2016PEREIRA, T. C. V. et al. Reflexos da interação genótipo x ambiente sobre o melhoramento genético de feijão. Ciência Rural, v. 46, n. 3, p. 411-417, 2016.) and cowpea (TORRES et al., 2015TORRES, F. E. et al. Interação genótipos x ambientes em genótipos de feijão-caupi semiprostrados via modelos mistos. Bragantia, v. 74, n. 3, p. 15-20, 2015.; OLIVEIRA; FONTES; ROCHA, 2015OLIVEIRA, I. J.; FONTES, J. R. A.; ROCHA, M. M. Seleção de genótipos de feijão-caupi para adaptabilidade e estabilidade produtiva no Estado do Amazonas. Revista de Ciência Agrárias, v. 58, n. 3, p. 292-300, 2015.) in multi-environments also found a higher proportion of environmental variance than genotypic and environmental variances for grain yield.

The low genotype variance found in the group of genotypes evaluated (Table 4) was expected considering that some lines showed relation to each other (Table 1) and all are highly inbred, i.e., they have already undergone several selection cycles for high grain yield. Torres et al. (2015TORRES, F. E. et al. Interação genótipos x ambientes em genótipos de feijão-caupi semiprostrados via modelos mistos. Bragantia, v. 74, n. 3, p. 15-20, 2015., 2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016. evaluated the grain yield of 20 cowpea genotypes in multi-environments of Mato Grosso do Sul and also found lower estimates for the genotypic variance than environmental and G×E variances.

The trait yield is controlled by several genes and, therefore, is heavily affected by the environment. In spite of the great effect of the environmental factors, denoted by the relative coefficient of variation (0.32), the heritability at an average genotypic level among the various environments was high (0.84) since the environmental effects were minimized. This allowed a high accuracy (0.92) in the selection of lines based on the average of the environments (Table 4). The heritability obtained in the present study was higher than those estimated by Torres et al. (2015TORRES, F. E. et al. Interação genótipos x ambientes em genótipos de feijão-caupi semiprostrados via modelos mistos. Bragantia, v. 74, n. 3, p. 15-20, 2015., 2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016., who evaluated the grain yield of 20 cowpea genotypes in multi-environment of Mato Grosso do Sul and found estimates of 0.68 and 0.54.

According to Chiorato et al. (2008)CHIORATO, A. F. et al. Prediction of genotypic values and estimate of genetic parameters in common bean. Brazilian Archives of Biology and Technology, v. 51, n. 3, p. 465-472, 2008., heritability at average level is determined based on the number of replicates and evaluated plants. In the case of the present study, the size of the evaluation area in the experimental unit may have contributed positively to minimize the environmental effects, since the genotypes were represented by 80 plants in the evaluation area of the plot.

The G×E variance was the second most important (30%) (Table 4), which resulted from the low genotypic correlation between environments (0.18). These results showed the existence of G×E of complex-type, and that the best lines in one environment will not necessarily be the best in others (RESENDE, 2007aRESENDE, M. D. V. Matemática e estatística na análise de experimentos e no melhoramento genético. Colombo: Embrapa Florestas, 2007a. 362 p.). This represents a certain difficulty in the selection of genotypes with wider adaptation, which justifies considering in the selection of the lines, their stabilities and adaptabilities.

Barros et al. (2013)BARROS, M. A. et al. Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesquisa Agropecuária Brasileira, v. 48, n. 4, p. 403-410, 2013. evaluated the grain yield of 20 cowpea genotypes in the Mid-North region of Brazil and also found the G×E as the second factor affecting the phenotypic variance. On the other hand, Torres et al. (2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016. observed similar percentages for the G×E and environmental variances.

According to the mean component estimates (BLUP) and the confidence intervals associated with genotypic values (u+g), the lines G31 (MNC04-795F-153), G34 (MNC04-795F-159), and G26 (MNC04-769F-62) were superior than most of the genotypes evaluated and presented the highest genetic gains compared to the overall mean, with 12.45%; 11.22%; and 9.51%, respectively (Table 5). These gains were lower than those observed by Torres et al. (2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016., who evaluated the grain yield of 20 cowpea genotypes in four environments of Mato Grosso do Sul and found gain estimates for the two best genotypes of 18.79% and 18.04%.

Table 5
Estimates of mean components (individual BLUP) of the effects (g) and predicted genotypic values (u+g) free from interaction with environments, confidence interval lower limit (CILL), confidence interval higher limit (CIHL) and genetic gain (Gg) of 20 semi-erect cowpea genotypes evaluated in 37 environments of the Northeast region of Brazil, from 2013 to 2015

The genetic gain depends on the differential of the selection and heritability of the trait. Although the heritability of grain yield was high, a factor that may have led to lower gains than those observed by Torres et al. (2015TORRES, F. E. et al. Interação genótipos x ambientes em genótipos de feijão-caupi semiprostrados via modelos mistos. Bragantia, v. 74, n. 3, p. 15-20, 2015., 2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016. was the differences between the overall mean and the means of the superior genotypes, which in the present study were small, relatively to the selection differentials founded by the authors above.

The results of stability (HMGV), adaptability (RPGV), and simultaneous stability and adaptability (HMRPGV) of the genotypes evaluated are presented in Table 6. The five best genotypes, based on the criteria HMGV, RPGV, and HMRPGV were not necessarily the best based on the criterion of the mean genotypic value (Table 5). The coincidence was 80% among the five best genotypes and there was an inversion of order among the coincident ones between HMGV and RPGV. According to Resende (2007a)RESENDE, M. D. V. Matemática e estatística na análise de experimentos e no melhoramento genético. Colombo: Embrapa Florestas, 2007a. 362 p., the use of these attributes or selection criteria can provide further refinement in selection.

Table 6
Genetic value stability (HMGV), genetic values adaptability (RPGV), simultaneous genetic value adaptability and stability (HMRPGV), genotypic value capitalizing the adaptability (RPGV*OM) and genotypic value penalized by instability and capitalized by adaptability (HMRPGV*OM) of 20 semi-erect cowpea genotypes evaluated in 37 environments of Northeast region of Brazil, from 2013 to 2015

Similar results were obtained by Torres et al. (2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016., who evaluated the yield of 20 cowpea genotypes in the state of Mato Grosso do Sul, and also observed the same percentage of coincidence between the ordering provided by HMGV and RPGV.

The three best lines (G31 - MNC04-795F-153, G34 - MNC04-795F-159 and G26 - MNC04-769F-62) by the criterion HMRPGV*OM, had grain yield of 1,512 kg ha-1, 1,485 kg ha-1 and 1,419 kg ha-1 (Table 6), i.e., an average superiority of 13%, 11%, and 10%, respectively, over the overall mean of the 37 environments. According to Resende (2007a)RESENDE, M. D. V. Matemática e estatística na análise de experimentos e no melhoramento genético. Colombo: Embrapa Florestas, 2007a. 362 p., these values are obtained through a process that already penalizes the lines for the instability in the environments and capitalizes the capacity of response (adaptability) to the improvement of the environment. These properties are intrinsic to the HMRPGV method.

The values of RPGV and HMRPGV (Table 6) indicate the average superiority of the genotype in relation to the average of a given environment. Thus, the line MNC04-795F-153 (G31) responds on average 1.1272 times the mean of any environment in which it is grown.

The four best genotypes in genotypic value (Table 5) were also the best in HMRPGV. Similar results were found by Torres et al. (2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016., who evaluated the yield adaptability and stability of 20 cowpea genotypes in several environments in the State of Mato Grosso do Sul. Based on these authors, this is an indication that the genotypes evaluated in the present work had high adaptive synergism in the 37 environments tested and good predictability, i.e., maintenance of yield in the environments.

In general, the lines MNC04-795F-159 (G31) and MNC04-795F-153 (G34) were superior for yield, adaptability, and stability, and can be recommended for the evaluated environments in the Northeast region of Brazil, with a lower risk of losses in grain yield due to unpredictable environmental factors. According to Torres et al. (2016)TORRES, F. E. et al. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016., genotypes that simultaneously have these three attributes can be used as selection criteria in breeding programs.

The lines G31 and G34 are sisters, presenting the same genealogy, and belong to the same commercial subclass-mulatto (Table 1). Their grain yield is also similar (Table 6). Thus, regarding the releasing of cultivars, the line G31 should be chosen, since this line better combines the attributes of yield, adaptability, and stability.

CONCLUSIONS

  1. The line MNC04-795F-159 presents greater predictability of grain yield in the environmental conditions evaluated in the Northeast region of Brazil;

  2. The line MNC04-795F-153 combines high yield, adaptability and genotypic stability, and can be recommended and grown with greater probability of success in the edaphoclimatic conditions evaluated in the Northeast region of Brazil.

  • 1
    Pesquisa desenvolvida pela Embrapa (Empresa Brasileira de Pesquisa Agropecuária), Programa de Melhoramento de Feijão-caupi da Embrapa Meio-Norte, região Nordeste, Teresina-PI, Brasil

ACKNOWLEDGEMENTS

The authors thank the partners of the genetic breeding network for cowpea in the Northeast Region for the structural support and personnel in conducting the tests; and Dr. Marcos Deon Vilela de Resende, for the assistance in the statistical analysis of adaptability and stability via REML/BLUP procedure.

REFERENCES

  • BARROS, M. A. et al Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesquisa Agropecuária Brasileira, v. 48, n. 4, p. 403-410, 2013.
  • BARROSO, L. M. A. et al Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability. Genetics and Molecular Research, v. 15, n. 1, p. 1-11, 2016.
  • BORGES, V. et al Desempenho genotípico de linhagens de arroz de terras altas utilizando metodologia de modelos mistos. Bragantia, v. 69, n. 4, p. 833-842, 2010.
  • CARIAS, C. M. O. M. et al Produtividade de grãos de cafeeiro conilon de diferentes grupos de maturação pelo procedimento REML/BLUP. Semina: Ciências Agrárias, v. 35, n. 2, p. 707-718, 2014.
  • CARVALHO, L. C. B. et al Evolution of methodology for the study of adaptability and stability in cultivated species. African Journal of Agricultural Research, v. 11, n. 12, p. 990-1000, 2016.
  • CHIORATO, A. F. et al Prediction of genotypic values and estimate of genetic parameters in common bean. Brazilian Archives of Biology and Technology, v. 51, n. 3, p. 465-472, 2008.
  • COMPANHIA NACIONAL DE ABASTECIMENTO. Acompanhamento da safra brasileira de grãos v. 4, safra 2016/17, n. 10. Brasília: CONAB, 2017. p. 95. Disponível em: <http://www.conab.gov.br/OlalaCMS/uploads/arquivos/17_07_12_11_17_01_boletim_graos_julho_2017.pdf>. 2017. Acesso em: 14 jul. 2017.
    » http://www.conab.gov.br/OlalaCMS/uploads/arquivos/17_07_12_11_17_01_boletim_graos_julho_2017.pdf
  • DDAMULIRA, G. et al Grain yield and protein content of Brazilian cowpea genotypes under diverse Ugandan environments. American Journal of Plant Science, v. 6, p. 2074-2084, 2015.
  • FREIRE FILHO, F. R. (Ed.). Feijão-caupi no Brasil: produção, melhoramento genético, avanços e desafios. Teresina: Embrapa Meio-Norte, 2011. 84 p.
  • OKORONKWO, C. M.; NWOFIA, G. E. Yield stability and inter relationships between seed yield and associated traits of 25 cowpea (Vigna unguiculata [L.] Walp.) genotypes. African Journal of Agricultural Science and Technology, v. 4, n. 5, p. 728-734, 2016.
  • OLAYIWOLA, M. O.; SOREMI, P. A. S.; OKELEYE, K. A. Evaluation of some cowpea (Vigna unguiculata L. [Walp.]) genotypes for stability of performance over 4 years. Current Research in Agricultural Sciences, v. 2, n. 1, p. 22- 30, 2015.
  • OLIVEIRA, I. J.; FONTES, J. R. A.; ROCHA, M. M. Seleção de genótipos de feijão-caupi para adaptabilidade e estabilidade produtiva no Estado do Amazonas. Revista de Ciência Agrárias, v. 58, n. 3, p. 292-300, 2015.
  • PEREIRA, T. C. V. et al Reflexos da interação genótipo x ambiente sobre o melhoramento genético de feijão. Ciência Rural, v. 46, n. 3, p. 411-417, 2016.
  • RESENDE, M. D. V. Matemática e estatística na análise de experimentos e no melhoramento genético Colombo: Embrapa Florestas, 2007a. 362 p.
  • RESENDE, M. D. V. Métodos estatísticos ótimos na análise de experimentos de campo Colombo: Embrapa Florestas, 2004. 65 p. (Embrapa Florestas. Documentos, 100).
  • RESENDE, M. D. V. Selegen-Reml/Blup: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Colombo: Embrapa Florestas , 2007b. 359 p.
  • ROCHA, M. M. et al Adaptabilidade e estabilidade de genótipos de feijão-caupi quanto à produção de grãos frescos, em Teresina-PI. Revista Científica Rural, v. 14, n. 1, p. 40-55, 2012.
  • SANTOS, A. et al Adaptabilidade e estabilidade de genótipos de feijão-caupi ereto via REML/BLUP e GGE Biplot. Bragantia, v. 75, n. 3, p. 55-62, 2016.
  • SANTOS, A. et al Adaptability and stability of cowpea genotypes to Brazil Midwest. African Journal of Agricultural Research, v. 10, n. 41, p. 3901-3908, 2015.
  • SAS INSTITUTE INC. SAS/STAT user's guide Version 8.1. Cary, 2002. v. 1, 890 p.
  • SILVA, R. R. et al Adaptabilidade e estabilidade de cultivares de trigo em diferentes épocas de semeadura, no Paraná. Pesquisa Agropecuária Brasileira, v. 46, n. 11, p. 1439-1447, 2011.
  • TEODORO, P. E. et al Perspectiva bayesiana na seleção de genótipos de feijão-caupi em ensaios de valor de cultivo e uso. Pesquisa Agropecuária Brasileira, v. 50, n. 10, p. 878-885, 2015.
  • TESELLE, A. et al Adaptability and stability of soybean cultivars under different times of sowing in Southern Brazil. Journal of Plant Sciences, v. 4, n. 2, p. 17-22, 2016.
  • TORRES, F. E. et al Interação genótipos x ambientes em genótipos de feijão-caupi semiprostrados via modelos mistos. Bragantia, v. 74, n. 3, p. 15-20, 2015.
  • TORRES, F. E. et al Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models. Genetics and Molecular Research, v. 15, n. 2, p. 1-11, 2016.

Publication Dates

  • Publication in this collection
    2017

History

  • Received
    31 Aug 2016
  • Accepted
    08 Mar 2017
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