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Revista Ciência Agronômica

Print version ISSN 0045-6888On-line version ISSN 1806-6690

Rev. Ciênc. Agron. vol.48 no.5spe Fortaleza  2017

https://doi.org/10.5935/1806-6690.20170098 

Crop Science

Adaptability and yield stability of cowpea elite lines of semi-prostrate growth habit in the cerrado biome1

Adaptabilidade e estabilidade produtiva em linhagens elite de feijão-caupi de porte semiprostrado no Cerrado brasileiro

Massaine Bandeira e Sousa2 

Kaesel Jackson Damasceno-Silva3  * 

Maurisrael de Moura Rocha3 

José Ângelo Nogueira de Menezes Júnior3 

Laíze Raphaelle Lemos Lima4 

2Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, Piracicaba-SP, Brasil, massainebandeira@hotmail.com

3Embrapa Meio-Norte, Teresina-PI, Brasil, kaesel.damasceno@embrapa.com, maurisrael.rocha@embrapa.br, jose-angelo.junior@embrapa.br

4Universidade Estadual de Maringá, Maringá-PR, Brasil, dra_lemos@hotmail.com


ABSTRACT

The effects of the genotype × environment interaction can be reduced by using cultivars with high adaptability and good yield stability. Studies on this subject allow identification of genotypes of predictable behavior, and responsive to environmental variations in specific and general conditions, in favorable or unfavorable environments. The objective of this work was to evaluate the adaptability and phenotypic stability of cowpea elite lines of semi-prostrate growth habit in the Cerrado biome in Brazil. Twenty cowpea genotypes of semi-prostrate growth habit were evaluated in nine VCU (value for cultivation and use) tests from 2010 to 2012. Grain yield data were subjected to analysis of variance, and stability and adaptability analyses were carried out by the methods of Eberhart and Russell (1966), Lin and Binns (1988) (modified), Wricke (1965), and Annicchiarico (1992). The method of Wricke (1965) was not very descriptive, since it indicates only the contribution of each genotype to the genotype × environment interaction. The results obtained by the methods of Lin and Binns (1988) (modified), Annicchiarico (1992) and Eberhart and Russell (1966) were more descriptive, and similar in indicating the most promising cultivar (BRS-Xiquexique) and lines (Pingo-de-Ouro-1-2, MNC02-676F-1, MNC01-649F-2-1 and MNC02-677F-2). These lines have potential for the development of new cultivars because they present adaptability and yield stability in the Cerrado biome of Brazil.

Key words: Vigna unguiculata; Genotype × Environment Interaction; Grain yield

RESUMO

Os efeitos da interação genótipos por ambientes podem ser reduzidos, utilizando-se cultivares com ampla adaptabilidade e boa estabilidade produtiva. O estudo desse tema possibilita a identificação de genótipos de comportamento previsível e que sejam responsivos às variações ambientais, em condições específicas (ambientes favoráveis ou desfavoráveis) ou amplas. Este trabalho foi realizado com o objetivo de avaliar a adaptabilidade e estabilidade fenotípica de linhagens elite de feijão-caupi de porte semiprostrado na região de Cerrado do Brasil. Foram avaliados vinte genótipos de feijão-caupi em nove ensaios VCU (Valor de Cultivo e Uso) de porte semiprostrado, no período de 2010 a 2012. Os dados de produtividade de grãos foram submetidos a análises de variância e em seguida a análises de estabilidade e adaptabilidade pelos métodos de Eberhart e Russell (1966), Lin e Binns (1988) modificado, Wricke (1965) e Annicchiarico (1992). A metodologia de Wricke (1965) demonstrou ser pouco informativa, por indicar apenas a contribuição de cada genótipo para a interação genótipo × ambiente. Os resultados obtidos pelos métodos Lin e Binns (1988) modificado, Annicchiarico (1992) e Eberhart e Russell (1966), foram mais informativos, sendo coincidentes em indicar o cultivar BRS Xiquexique e as linhagens Pingo-de-Ouro-1-2, MNC02-676F-1, MNC01-649F-2-1 e MNC02-677F-2 como os mais promissores. Essas linhagens possuem potencial para lançamento como cultivares, por apresentarem adaptabilidade e estabilidade produtiva na região do cerrado brasileiro.

Palavras-chave: Vigna unguiculata; Interação Genótipos × Ambientes; Produtividade de Grãos

INTRODUCTION

Cowpea [Vigna unguiculata (L.) Walp] is cultivated in the Northeast, North and Center-West regions of Brazil. However, the average productivity of cowpea crops varies greatly among different regions, mainly due to environmental variations and the use of genetic materials that are not very productive or with undesirable characteristics (FREIRE FILHO et al., 2011).

One of the main challenges in genetic improvement of species is to understand genotype × environments interaction (G×E), which is assessed by the evaluation of the genotypes in different environments (CRUZ; CARNEIRO; REGAZZI, 2014). The evaluation of G×E is very important because of the possibilities of genotypes behave differently in different environments due to G×E (RESENDE; DUARTE, 2007). This behavior affects the selection gain and makes it difficult to recommend cultivars with wide adaptability.

Studies on adaptability and stability of plant species provide tools to identify genotypes that present high productivity in different environmental conditions (FIGUEIREDO et al., 2015, PEREIRA et al., 2012). The adaptability and stability of cowpea genotypes have been the goal of several studies (BARROS et al., 2013; NUNES et al., 2014; ROCHA et al., 2007; SANTOS et al., 2016; VALADARES et al., 2010). These studies have subsidized the improvement and release of cultivars in several states of the North, Northeast and Center-West regions of Brazil (FREIRE FILHO et al., 2011).

There are several methods to evaluate the G×E and to determine the adaptability and yield stability of the cultivars. According to the Eberhart and Russell (1966) method, based on simple linear regression, an ideal cultivar presents overall adaptability and stability while maintaining a good performance when the environmental conditions are unfavorable. However, when the data do not fulfill the assumptions of the regression analysis, an alternative would be the use of non-parametric analyzes such as the method of Lin and Binns (1988) (modified) described by Cruz, Carneiro and Regazzi (2014). This method allows the identification of the most stable genotypes by a single parameter of stability and adaptability, and includes the deviations in relation to the maximum yield obtained in each environment; making it possible to detail this information for favorable and unfavorable environments. Other examples are the method of Annicchiarico (1992), which presents an easy application and is based on the estimation of a risk index for the recommendation of a given cultivar; and the method of Wricke (1965), called ecovalence, which is estimated by the distribution of the sum of squares of the G×E into parts due to single genotypes. This method has an easy interpretation; however, the data need to be balanced to meet the assumptions of a regression analysis (CARVALHO et al., 2016).

Choosing the method to characterize genotypes regarding adaptability and stability depends on the available experimental data, the required precision, and the type of information desired by the breeder (CRUZ; CARNEIRO; REGAZZI, 2014). Each one of these methods has peculiarities that can contribute to improve the analysis; and in some cases, these methods may be complementary to each other, therefore, it is important to use more than one method (PEREIRA et al., 2009). In this context, the objective of this study was to evaluate the adaptability and phenotypic stability of cowpea elite lines of semi-prostrate growth habit in the Cerrado biome in Brazil.

MATERIAL AND METHODS

Twenty cowpea genotypes of semi-prostrate growth habit from VCU (value for cultivation and use) tests were evaluated, where fifteen lines were from the Embrapa Mid-North Cowpea Breeding Program and five were commercial cultivars (Table 1). Nine experiments were conducted under rainfed conditions, in the 2010, 2011 and 2012 crop seasons, in three locations: Balsas and São Raimundo das Mangabeiras in the State of Maranhão (MA), and Primavera do Leste in the state of Mato Grosso (MT) (Table 2).

Table 1 Cowpea genotypes of semi-prostrate growth habit evaluated in nine experiments conducted in Balsas MA, São Raimundo das Mangabeiras MA, and Primavera do Leste MT, in the 2010, 2011 and 2012 crop seasons 

Genotype code Genotype type Commercial Subclass
MNC01-649F-1-3 Line Rajado
MNC01-649F-2-1 Line Rajado
MNC01-649F-2-11 Line Rajado
MNC02-675-4-9 Line Mulato
MNC02-675F-9-5 Line Mulato
MNC02-676F-1 Line Mulato
MNC02-677F-2 Line Sempre verde
MNC02-677F-5 Line Mulato
MNC02-680F-1-2 Line Sempre verde
MNC02-689F-2-8 Line Sempre verde
MNC02-701F-2 Line Branco
MNC03-736F-2 Line Branco
MNC03-736F-6 Line Branco
MNC03-761F-1 Line Sempre verde
Pingo-de-ouro-1-2 Line Canapu
BRS Xiquexique Cultivar Branco
BRS Juruá Cultivar Verde
BRS Aracê Cultivar Verde
BR17 Gurguéia Cultivar Sempre verde
BRS Marataoã Cultivar Sempre verde

Table 2 Geographic coordinates, average annual precipitation and soil class of the sites used for nine experiments conducted in Balsas MA, São Raimundo das Mangabeiras MA, and Primavera do Leste MT, in the 2010, 2011 and 2012 crop seasons 

Location/State Elevation Latitude (S) Longitude (W) 1/ Average annual precipitation Soil
Balsas MA 324 m 07º54' 45º96' 1190 mm Oxisol
São Raimundo das Mangabeiras MA 511 m 06º53' 45º39' 1157 mm Oxisol
Primavera do Leste MT 636 m 15°33' 54°17' 1784 mm Oxisol

1/ Source: www.climate-data.org

All experiments were conducted in a complete randomized block experimental design with four replications. The randomization was performed individually for each environment. The plots of the experiments consisted of four 5.0-meter rows spaced 0.80 m apart, with 0.25 m between plants, and the evaluation area consisted of the two central rows. Weed, pest and disease control was carried out according to the recommendations for cowpea (FREIRE FILHO; LIMA; RIBEIRO, 2005).

The statistical analysis was carried out assuming that each combination of years with locations represents an environment, making nine environments. The yield data were subjected to analysis of variance, considering the mixed model with effect of treatments as fixed and the others as random. A joint analysis of the environments was performed after evaluating the homogeneity of the residual variances. According to Pimentel-Gomes (2000), if the ratio between the largest and the smallest mean square of the residue is less than seven, the residual variances are homogeneous. However, due to the lack of homogeneity of variance, the degrees of freedom of the mean error and the G×E were adjusted according to the method of Cochran (1954). The Scott-Knott test at 5% probability was used to identify the existence of homogeneous groups, by minimizing the variation within, and maximizing between groups.

The evaluation of genotype adaptability and stability was performed using the following methods: Eberhart and Russell (1966), Lin and Binns (1988) (modified) (CRUZ; CARNEIRO; REGAZZI, 2014), Wricke (1965) and Annicchiarico (1992).

In the method of Eberhart and Russell (1966), the adaptability was given by the estimation of the parameter β1i and by the average yield β0i; and the stability by the variance of the regression deviations δij, according to the following model Yij = β0i + β1iIj + δij + Σij, where: Yij is the average grain yield (kg ha-1) of genotype . in environment . ; β0i is the overall mean; β1i is the linear regression coefficient; . j is the environmental index; δij is the variance of the regression deviations; and Σij is the mean experimental error.

According to the method of Lin and Binns (1988) (modified) described by Cruz, Carneiro and Regazzi (201)4, the decomposition of Pi in the parts related to favorable and unfavorable environments was performed. The estimate of Pi was given by the equation: Pi=j=1nYijMj2x , where: Pi is the estimation of the adaptability and stability of the genotype i ; Yij is the yield of the genotype i in the environment j; Mj is the maximum observed response among all genotypes in the j environment; and α is the number of environments.

In the Annicchiarico method (1992), the confidence index Ii was calculated for the favorable and unfavorable environments according to the equation: Ii = Ȳi - Z(1-α)Si, wherein Ȳi is the overall mean of genotype . in percentage; Z is the percentile (1-α) of the cumulative normal distribution function; α is the level of significance; and Si is the standard deviation of the percentage values. The coefficient of confidence was 75%, i.e., α = 0.25.

The stability parameter proposed by Wricke (1965) was estimated using the statistic ωi, through the equation: ωi = rΣfĜA2IJ = rΣf(Yij - Ȳi. - Ȳ.i + Ȳ..)2 , where: Yij is the mean of the genotype i in the environment j ; Ȳi. is the mean of genotype i ; Ȳ.i is the mean of the environment j ; and Ȳ.. is the overall mean.

The individual and joint analysis of variance, and tests of comparison of means, stability and adaptability were performed using the software GENES (CRUZ, 2013).

RESULTS AND DISCUSSION

The genotypes presented significant differences (p <0.05) by the analysis of individual variances, in all environments, except Balsas in 2010 (Table 3). This result denotes genetic variability among the genotypes evaluated, which is essential to proceed with the genotype selection process.

Table 3 Individual analysis of variance of the grain yield (GY) of 20 cowpea genotypes of semi-prostrate growth habit evaluated in nine experiments conducted in Balsas MA, São Raimundo das Mangabeiras MA, and Primavera do Leste MT, in the 2010, 2011 and 2012 crop seasons 

Experiment Grain Yield
Mean (kg ha-1) Mean Square CV (%)
Year 2010
Balsas 1657.38 216471.26ns 23.28
Primavera do Leste 1398.97 249295.42** 13.85
São Raimundo das Mangabeiras 767.41 194414.47** 24.48
Year 2011
Balsas 1976.72 148775.03** 16.35
Primavera do Leste 1103.32 204804.67** 19.55
São Raimundo das Mangabeiras 1113.26 391413.48* 36.10
Year 2012
Balsas 1146.25 204175.44** 25.83
Primavera do Leste 1248.67 426068.87** 29.03
São Raimundo das Mangabeiras 627.35 161742.90** 25.61

**significant at 1% probability;

*significant at 5% probability; and

nsnot significant by the F test; CV = coefficient of variation (%)

The coefficient of variation (CV) of the experiments evaluated ranged from 13.85 to 36.10% (Table 3). The means and CV of the tests varied, denoting the different conditions to which the genotypes were subjected. The coefficient of variation (CV) is an estimate of the experimental error of the overall mean of the test, and an indication of the experimental accuracy. According to Pimentel-Gomes (2000), observed CV can be classified as low (lower than 10%), average (10% to 20%), high (20% to 30%), and very high (higher than 30%). The CV values found in this work were within the range found in other studies on cowpea, such as Barros et al. (2013), Benvindo et al. (2010), Bertini, Teófilo and Dias (2009), and Silva and Neves (2011).

The joint analysis of variance showed significant differences (. <0.01) for the sources of variation of environments, genotypes, and G×E (Table 4). The significant effect of the G×E indicates the different response of the genotypes to the environments, thus requiring analyzes of adaptability and phenotypic stability.

Table 4 Joint analysis of variance of the grain yield (kg ha-1) of 20 cowpea genotypes of semi-prostrate growth habit evaluated in nine experiments conducted in Balsas MA, São Raimundo das Mangabeiras MA, and Primavera do Leste MT, in the 2010, 2011 and 2012 crop seasons 

Source of Variation DF Mean Square
Block/Environment 27 231841.49
Environment (E) 8 13829048.67**
Genotypes (G) 19 685650.21**
G×E 1131/ 254147.92**
Residual 3661/ 120566.11
Mean (kg ha-1) 1226.59
CV (%) 28.30

**significant at 1% probability, and

* = significant at 5% probability by the F test; CV = coefficient of variation (%);

1/ DF adjusted by the method described by Cochran (1954)

The grain yield of the genotypes presented homogeneous groups by the Scott-Knott test (p <0.05) (Table 5). The edaphoclimatic conditions of São Raimundo das Mangabeiras MA, affected the performance of the genotypes, decreasing their productive performance. Regarding the average grain yield, the line MNC02-701F-2 (1451.20 kg ha-1) and the cultivar BRS-Xiquexique (1439.60 kg ha-1)-both from the branco commercial subclass-stood out from the others, presenting promising yields, with good adaptation to the edaphoclimatic conditions of the cerrado biome in Maranhão. However, the overall average yield found in this study (1226.60 kg ha-1) is lower than the averages found by Teixeira et al. (2010) (1307.00 kg ha-1) and Silva and Neves (2011) (1436.35 kg ha-1) in cowpea crops also in the Cerrado biome.

Table 5 Estimates of adaptability and phenotypic stability by the methods of Eberhart and Russel (1966) and Wricke (1965) for 20 cowpea genotypes of semi-prostrate growth habit evaluated in nine experiments conducted in Balsas MA, São Raimundo das Mangabeiras MA, and Primavera do Leste MT, in the 2010, 2011 and 2012 crop seasons 

Genotypes Mean1/ Eberhart and Russell Wricke
β2/1i Wi Wi(%) σ23/di R2(%)
BRS Xiquexique 1451.20 a 0.83ns 1402892 4.88 23235* 75
MNC02-701F-2 1439.61 a 1.39** 2404072 8.37 32845* 88
MNC02-675-4-9 1324.23 b 1.11ns 2253794 7.85 56209** 76
MNC02-677F-5 1323.40 b 1.27* 1577257 5.49 20179ns 88
MNC02-676F-1 1308.84 b 0.88ns 699581 2.44 656ns 87
Pingo-de-ouro-1-2 1299.41 b 0.80ns 902563 3.14 3119ns 84
MNC01-649F-1-3 1298.85 b 1.05ns 1628026 5.67 36047* 79
MNC01-649F-2-11 1282.84 b 0.70* 2174646 7.57 38410** 62
MNC02-675F-9-5 1243.80 b 0.72* 1225799 4.27 6783ns 78
MNC01-649F-2-1 1241.37 b 0.83ns 647764 2.26 4041ns 89
MNC02-677F-2 1239.02 b 1.19ns 1326516 4.62 18648ns 87
BRS Marataoã 1233.84 b 1.33** 2127175 7.41 32685* 87
MNC02-689F-2-8 1219.27 b 1.18ns 687196 2.39 -3592ns 94
MNC03-761F-1 1211.27 b 0.73* 1128896 3.93 4692ns 80
MNC03-736F-2 1183.71 b 1.22ns 1030329 3.59 5523ns 92
BR17 Gurguéia 1141.99 c 1.01ns 871283 3.03 9559ns 87
MNC02-680F-1-2 1131.18 c 0.78ns 1183909 4.12 11901ns 79
MNC03-736F-6 1087.52 c 1.41** 1912348 6.66 12679ns 92
BRS Aracê 1031.32 c 0.80ns 1653783 5.76 29855* 71
BRS Juruá 839.15 d 0.70* 1880888 6.55 27992* 66
Overall Mean 1226.60 28718716 100

**significant at 1% probability;

*significant at 5% probability; and

nsnot significant by the t test;

1/Means followed by the same letter belong to the same class (p ≤ 0.05);

2/H0: β1i = 1; 3/H0: σ2di = 0

3/H0: σ2di = 0

The regression coefficient (β1i = 1) of the model proposed by Eberhart and Russell (1966), measures the adaptability of the genotypes, and the stability of their behavior is measured by the variance of regression deviations (σ2di = 0) and by the coefficient of determination (R2). According to Cruz, Carneiro and Regazzi (2012), the R2 assists in the evaluation of stability, when the σ2di are significant. The lines MNC02-676F-1, MNC01-649F-2-1, MNC02-677F-2 and Pingo-de-Ouro-1-2 presented high grain yields, wide adaptability (β1i = 1), high stability (σ2di = 0) and coefficient of determination (R2) greater than 84 (Table 5).

In the evaluation using the method of Wricke (1965), the most stable genotypes, those that contributed least to the interaction, were MNC01-649F-2-1, MNC02-689F-2-8, MNC02-676F-1 and Pingo-de-Ouro-1-2 and BR17-Gurguéia (Table 5). However, the results were not very descriptive in detecting stable and adapted genotypes. The limitation of this methodology is that it indicates only the contribution of each genotype to the G×E; thus, it cannot show the performance of the genotypes, requiring complementation by other methodologies of adaptability analysis.

According to the methodology of Lin and Binns (1988) (modified) (CRUZ; CARNEIRO; REGAZZI, 2014), which classifies genotypes for adaptability and phenotypic stability in favorable and unfavorable environments, the most stable genotype is the one that shows the smallest deviation in maximum yield in each environment, i.e., the smallest Pi. Therefore, the lines MNC04-677F-5, MNC02-701F-2 and MNC02-676F-1, and the cultivar BRS-Xiquexique, in addition to presenting the lowest overall Pi, also presented the first positions for the parameters Pi, favorable and unfavorable (Table 6).

Table 6 Estimates of adaptability and phenotypic stability by the method of Lin and Binns (1988) (modified), with distribution of Pi (parameter of stability and adaptability) in favorable (Pif) and unfavorable (Pid) environments; and by the method of Annicchiarico (1992) (Wi - confidence index), with distribution in favorable (Wif) and unfavorable (Wid) environments, of 20 cowpea genotypes of semi-prostrate growth habit evaluated in nine experiments conducted in Balsas MA, São Raimundo das Mangabeiras MA, and Primavera do Leste MT, in the 2010, 2011 and 2012 crop seasons 

Mean1/ Lin and Binns modified Annicchiarico
Pi(x103) C2/ Pif(x103) C Pid(x103) C Ei C2/ Wif Rank Wid Rank
BRS Xiquexique 1451.20 a 48 1 44 2 51 1 116 1 112 2 120 1
MNC02-701F-2 1439.61 a 62 2 21 1 94 7 108 2 118 1 101 8
MNC02-675-4-9 1324.23 b 108 7 49 5 154 15 100 7 111 3 92 10
MNC02-677F-5 1323.40 b 93 4 65 4 116 10 99 10 109 4 91 12
MNC02-676F-1 1308.84 b 81 3 85 3 77 5 105 3 101 7 109 4
Pingo-de-ouro-1-2 1299.41 b 94 5 143 9 55 2 104 4 97 11 112 2
MNC01-649F-1-3 1298.85 b 104 6 67 6 135 9 101 6 105 6 97 9
MNC01-649F-2-11 1282.84 b 114 8 130 10 102 8 102 5 100 8 103 7
MNC02-675F-9-5 1243.80 b 125 11 171 14 89 4 100 8 91 14 109 3
MNC01-649F-2-1 1241.37 b 124 10 157 12 98 3 99 9 94 12 105 5
MNC02-677F-2 1239.02 b 118 9 70 7 157 17 92 13 106 5 81 17
BRS Marataoã 1233.84 b 134 13 107 8 156 16 87 17 100 9 79 18
MNC02-689F-2-8 1219.27 b 129 12 113 11 141 12 93 12 99 10 88 15
MNC03-761F-1 1211.27 b 141 14 205 17 89 6 98 11 90 15 104 6
MNC03-736F-2 1183.71 b 151 15 153 13 149 14 90 14 92 13 88 13
BR17 Gurguéia 1141.99 c 164 16 193 16 141 13 88 15 88 17 88 14
MNC02-680F-1-2 1131.18 c 169 17 246 18 107 11 88 16 84 18 91 11
MNC03-736F-26f-6 1087.52 c 217 18 177 15 250 19 78 19 90 16 71 19
BRS Aracê 1031.32 c 246 19 302 19 202 18 80 18 76 19 84 16
BRS Juruá 839.15 d 401 20 438 20 371 20 64 20 68 20 61 20
Overall Mean 1226.60

1/Means followed by the same letter belong to the same class (p≤0.05);

2/Genotype stability classification.

The cultivar BRS-Xiquexique was the most stable, the second most responsive to the favorable environments, and the most adapted to unfavorable environments. The line MNC02-701F-2 was the most responsive to the favorable environments. The most stable and adapted genotypes are the most productive ones.

According to Pereira et al. (2009), an advantage of the method of Lin and Binns (1988) is the immediate identification of more stable genotypes due to the use of the single parameter Pi. Nunes et al. (2014) and Shiringani and Shimelis (2011) evaluated cowpea crops and found similar results regarding the parameter Pi, thus confirming that the most adapted and stable genotypes always have the highest yields.

According to the method of Annicchiarico (1992), the genotypes BRS-Xiquexique, MNC02-676F-1, MNC02-701F-2, Pingo-de-Ouro-1-2, MNC01-649F-1-3 and MNC01-649F-2-11 were identified with confidence indexes (Wi) greater than 100% (Table 6). The genotypes BRS-Xiquexique, MNC02-701F-2, MNC02-675-4-9, MNC02-677F-5, MNC02-676F-1, MNC01-649F-1-3 and MNC02-677F-2 stood out in favorable environments (Wif); and in unfavorable environments (Wid), 45% of the genotypes surpassed the average of the environments, especially BRS-Xiquexique and Pingo-de-Ouro-1-2.

The Eberhart and Russell (1966) methodology was efficient to indicate genotypes of wide adaptability and high stability, especially the genotypes MNC02-676F-1, MNC01-649F-2-1, MNC02-677F-2 and Pingo-de-Ouro-1-2. This is probably the most appropriate method, since it considers the productivity, adaptability and stability of each cultivar. The genotypes MNC02-676F-1, MNC01-649F-2-1 are among the most stable genotypes, according to methodology of Wricke (1965). This result is similar to that found by Mendes de Paula et al. (2014), where the methods of Wricke (1965) and Eberhart and Russell (1966) tended to select the most stable genotypes.

On the other hand, the method based on non-parametric statistics of Lin and Binns (1988) (modified), and the method of Annicchiarico (1992) indicate the genotypes BRS-Xiquexique and MNC02-701F-2 as those that had the highest yields with high instability and responsiveness to favorable environments. This result is an advantage of this method over methods based on analysis of variance. Conversely, Pereira et al. (2009) reported that the methods of Lin and Binns (1988) (modified) and Annicchiarico (1992) are indicated to be used singly, because they are simple to use and allow the classification of favorable and unfavorable environments, and identification of the most stable and adapted genotypes among the most productive ones. According to the same author, the joint use of methods that presented high correlation is not recommended; in this case, the method of Eberhart and Russell (1966) must be used together with the method of Lin and Binns (1988) (modified) or the method of Annicchiarico (1992), since there was no correlation between these methods.

CONCLUSIONS

  1. 1. Considering the results obtained by the joint use of the methods Lin and Binns (1988) (modified), Annicchiarico (1992) and Eberhart and Russell (1966) is important for analyses in cowpea, since each one has peculiarities that can contribute to the choice of adapted, stable and productive genotypes;

  2. The cultivar BRS-Xiquexique and the lines Pingo-de-ouro-1-2, MNC02-676F-1, MNC01-649F-2-1 and MNC02-677F-2 were considered promising. The lines of the commercial subclasses canapu, mulatto, rajado and sempre-verde have potential to be released as commercial cultivars, because they have adaptability and stability for the evaluated environments. The line MNC02-701F-2 presented adaptability and stability for the Cerrado biome, however, it does not have potential as commercial cultivar, since it does not exceed the cultivar BRS-Xiquexique, both belonging to the branco commercial subclass.

1Parte da Dissertação de Mestrado do primeiro autor, financiada pela CAPES

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Received: August 29, 2016; Accepted: January 09, 2017

*Autor para correspondência

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