Microsoft Word - 18-Agra_41559 1287 Original Article Biosci. J., Uberlândia, v. 34, n. 5, p. 1287-1297, Sept./Oct. 2018 ADAPTABILITY AND PRODUCTIVE STABILITY OF SOYBEAN GENOTYPES UNDER NATURAL RUST INFECTION WITHOUT FUNGICIDE ADAPTABILIDADE E ESTABILIDADE PRODUTIVA DE GENÓTIPOS DE SOJA SOB INFECÇÃO NATURAL POR FERRUGEM, SEM FUNGICIDA Nathália Salgado SILVA1; Ana Paula Oliveira NOGUEIRA2; Osvaldo Toshiyuki HAMAWAKI3; Fábio Serafim MARQUES4; Luíza Amaral MEDEIROS5; Géssyca Ferreira GOMES5; Bianca Gonçalves GUIMARÃES6; Lucas Oliveira Araújo PENA7; Cristiane Divina Lemes HAMAWAKI8; Fernando Cezar JULIATTI3 1. Doutoranda em Genética e Melhoramento de Plantas na Escola Superior de Agricultura “Luiz de Queiroz”, Piracicaba, SP, Brasil. nathalia_salgadosilva@yahoo.com.br; 2. Professora do Instituto de Biotecnologia, Universidade Federal de Uberlândia, Uberlândia, MG, Brasil; 3. Professores Titulares do Instituto de Ciências Agrárias na Universidade Federal de Uberlândia, Uberlândia, MG, Brasil; 4. Mestrando em Fitotecnia na Universidade Federal de Lavras, Lavras, MG, Brasil; 5. Estudantes de Biotecnologia na Universidade Federal de Uberlândia, Uberlândia, MG, Brasil; 6. Estudante de Agronomia na Universidade Federal de Uberlândia, Uberlândia, MG, Brasil; 7. Biólogo formado na Universidade Federal de Uberlândia, Uberlândia, MG, Brasil; 8. Doutoranda em Agronomia na Universidade Federal de Uberlândia, Uberlândia, MG, Brasil. ABSTRACT: The genetic breeding of soybean aims to obtain productive genotypes, so it is necessary that the genetic components, environment and the interaction between them be understood. The G x E interaction is the differential behavior of the genotypes against environmental. The objective was to study the G x E interaction and analyze the adaptability and stability of soybean genotypes under natural rust infection without fungicide. The experiment was conducted in the Genetic Breeding Program of the Federal University of Uberlândia. Fourteen soybean genotypes were evaluated, with 10 lines developed by the UFU Program (UFUS1117: 01, 02, 03, 05, 06, 07, 08, 09, 10 and 11) and 4 cultivars: UFUS 7415, UFUS Riqueza, TMG 801 and BRSGO 7560 in four seasons: 2013/14, 2014/15, 2015/16 and 2016/17, in a randomized complete block design. The G x E interaction was complex and the H2 was 85.97% indicating superiority of genetic variation in relation to the environment. The average grain yield was 2284.13kg ha-1. The genotype UFUS 1117-01 was identified by Eberhart and Russel, Wricke, AMMI 2 and Centroid as being a highly productive stability genotype. The UFUS 1117-07 showed high stability by Eberhart and Russel, Wricke, Lin and Binns modified by Carneiro methods and wide adaptability by Eberhart and Russel and Centroid. The genotype UFUS 1117-09 was identified as being adaptable to unfavorable environments by the Lin and Binns modified by Carneiro and Centroid methods, and UFUS 1117-10 presented favorable environmental adaptability by the Centroid method and high stability by Eberhart and Russel. KEYWORDS: Glycine max. G x E interaction. Cultivar recommendation. Biometric analysis. INTRODUCTION Variations in soybean yield grain occur not only as a function of cultivar and environmental conditions but also of genotype interaction by environments (SEDIYAMA; SILVA; BORÉM, 2015). The genotype interaction by environments ( G x E) is characterized as the differential behavior of genotypes due to environmental variations (CRUZ; CARNEIRO; REGAZZI, 2014), hinders the evaluation of productive potential and the selection of superior materials, inflates estimates of genetic variance resulting in overestimation of the expected gains with selection and in less successful breeding programs (DUARTE; VENCOVSKY, 1999). A interaction has fundamental importance in the phenotypic manifestation, because it reflects the sensitivity differences of the genotypes towards environmental variations, resulting in changes in the behavior of the materials (RAMALHO et al., 2012), and should, therefore, be estimated and considered in the genetic improvement and indication of cultivars. Due to the inconsistency of genotype superiority in environments, the use of specific cultivars for each environment or with high adaptability and high stability has been recommended (GARBUGLIO; FERREIRA, 2015). Adaptability is comprehended as the ability of the genotype to benefit from environmental variations, while stability reflects is the ability of genotypes to show a highly predictable behavior in data environmental stimuli (CRUZ; CARNEIRO; REGAZZI, 2014). From the studies of adaptability and stability, it is possible to infer about the productive characteristics of the genotypes to recommend the appropriate cultivars to different regions of cultivation, allowing to the farmer a greater profitability. In this way, it is possible to obtain more productive cultivars with desirable agronomic characteristics, consistently superior and responsive to environmental variations, which are the main objectives of a breeding program of any economic species. Received: 05/12/17 Accepted: 15/06/18 1288 Adaptability and productive… SILVA, N. S. et al. Biosci. J., Uberlândia, v. 34, n. 5, p. 1287-1297, Sept./Oct. 2018 The objective was to evaluate the productive performance of soybean lines and cultivars in four seasons in the city of Uberlândia, MG and to determine the adaptability and productive stability by parametric, non-parametric and multivariate methods of soybean genotypes under natural rust infection without fungicide. MATERIAL AND METHODS The experiments were conducted in the 2013/14, 2014/15, 2015/16 and 2016/17 crop seasons at Capim Branco farm, in Uberlândia, belonging to the Federal University of Uberlândia. Fourteen soybean genotypes were evaluated, of which 10 were developed by the UFU Soybean Breeding Program (UFUS 1117-01, UFUS 1117-02, UFUS 1117-03, UFUS 1117-05, UFUS 1117-06, UFUS 1117-07, UFUS 1117-08, UFUS 1117-09, UFUS 1117-10 and UFUS 1117-11) and 4 cultivars (UFUS 7415, UFUS Riqueza, TMG 801 and BRSGO 7560). The experiments were conducted in a randomized complete block design with three replicates. Each plot consisted of four rows of soybean plants, 5.0 m in length with spacing between rows of 0.5 m, totaling 10.0 m2. The useful area was the two central lines of each plot, being eliminated 0.50 m from each end, referring to the border, totaling 4.0 m2. The soil was prepared conventionally, with a plowing and two harrowing. Before sowing, the area was furrowed and fertilized with the formulation 02-28-18 at the dose of 400 kg ha-1. The seeds were treated with the fungicide composed of Carbendazim and Tiram and then inoculated with Bradyrhizobium japonicum. The sowing occurred on 12/12/2013, 11/29/2014, 02/12/2015 and 11/5/2016, in a depth of 3 to 5 cm. Soon after sowing, the herbicides of active principles S-Metolachlor and Haloxyfop-P- Methyl were applied. The thinning was performed maintaining 15 seeds per linear meter. Manual weeding was performed during the cycle to maintain the culture clean. Thirty days after emerging, foliar fertilizer composed of Cobalt and Molybdenum at a dose of 100 mL ha-1 was applied and pest control was performed with Acefate at the dose of 0.4 kg ha-1 and insecticide composed of Tiametoxam and Lambda- Cyhalothrin at a dose of 200 mL ha-1. Grain yield was determined by harvesting the useful area of each plot followed by grain weighing. We proceeded with the analysis of joint variance with 14 genotypes in 4 environments, in which the effects of genotypes and environment were considered fixed. The statistical analyzes were performed in the Genes Program (CRUZ, 2016). A study of the G x E interaction was carried out from the decomposition in a complex part between environment pairs, as described by Cruz and Castoldi (1991). Thus, the complex part was obtained by the expression: where: Q1 and Q2: correspond to the average squares of genotypes in environments 1 and 2 respectively; r: correlation between the means of the genotypes in the two environments. The experimental precision was evaluated by the coefficient of variation (CV %) and then the genotype determination coefficient was determined (H2). Once the significant G x E interaction was detected, adaptability and productive stability were analyzed by the methods of Eberhart and Russel (1966): e , where QMDi: is the mean square of the deviations of genotype i; QMR: is the mean square of the residue; r: is the number of repetitions; Wricke (1965): , where Yij: mean of genotype i in the environment j; mean of genotype i; : environment average j; : overall mean; Lin and Binns (1988) modified by Carneiro (1998): where Pi is the estimate of the stability parameter of the i-th genotype, Yij: is the productivity of the i-th genotype in the jth environment; Mj: is the maximum observed response among all genotypes in the jth environment; n: is the number of environments. Centroid (ROCHA et al., 2005): where : mean of genotype i in environment j; Y: total of observations; a: number of environments; g: number of genotypes. AMMI 2 (ZOBEL et al., 1988): where: : mean observed for the response variable of genotype i in environment j; µ: overall mean; : effect of genotype i, i = 1,2,3 ..., g; : effect of the environment j, j = 1,2,3 ..., a; :: eigenvalue of the c-major main component related to the G x E interaction; : eigenvalue of the c-th major component related to genotype i; : eigenvalue of the c-th major component related to the environment j; : residue or noise not explained by the main components; and : mean experimental error. 1289 Adaptability and productive… SILVA, N. S. et al. Biosci. J., Uberlândia, v. 34, n. 5, p. 1287-1297, Sept./Oct. 2018 RESULTS AND DISCUSSION The analysis of variance was performed as it was found homogeneity of the variances from the ratio between the largest and the smallest mean square, 4.81 (Table 1), a value lower than seven which is the limit (RAMALHO et al., 2012 ). The coefficient of variation (CV %) was estimated at 21.26% (Table 1), which is acceptable since productivity is quantitative and highly influenced by the environment (LEITE et al., 2015). Significance was verified by the F test (P <0.01), for the effects of genotypes, environments and G x E interaction (Table 1). The interaction G x E reflects on significant changes in the behavior of the genotypes when submitted to environmental differences and are frequently reported in different autogamous cultures (RAMALHO et al., 2012) as soybean, and it appears due to the different responses of the same set in different environments (COCKERHAM, 1963). The heritability (H2) is a genetic parameter of great importance for the breeding, however, in advanced generations, in which the genotypes present high homozygosity, it is called the genotypic determination coefficient (VASCONCELOS et al., 2012; YOKOMIZO; VELLO, 2000). The parameter H2 provides information of the proportion of phenotypic variability that is attributed to genetic causes (RAMALHO et al., 2012), thereby measuring the reliability of phenotypic value as an indicator of genotypic value. The estimate of H2 for the productivity trait was 85.97% (Table 1), being of high magnitude (CRUZ; CARNEIRO; REGAZZI, 2014) and indicating that the genetic variation was superior to environmental. Table 1. Summary of the joint variance analysis for grain yield (kg ha-1) evaluated in 14 soybean genotypes grown in 4 seasons, in Uberlândia-MG. The nature of the G x E interaction was estimated by the method of Cruz and Castoldi (1991), in which it was possible to identify complex type interaction in all pairs of environments. The interaction of the complex type denotes an inconsistency in the superiority of the genotype with the environmental variation, which hinders the process of improvement in the indication of the materials (BORÉM; MIRANDA, 2013), in addition, the interaction between the two species is associated with a lack of genetic correlation between the genotypes. Through the environmental index of Finlay and Wilkinson (1963), it was possible to identify favorable environments (2013/14 and 2015/16) and unfavorable ones (2014/15 and 2016/17). Favorable environments are those where the influence of abiotic and biotic factors was not able to drastically reduce productivity when compared to unfavorable environments. In the 2013/14 crop, the averages ranged from 1820 kg ha-1 to UFUS 1117-02, to 3645.6 kg ha-1 to TMG 801 (Table 2). A group with 5 genotypes was formed, which had higher yields, 3 of them coming from the UFU Program: UFUS 7415, UFUS 1117-05 and UFUS 1117-07. These genotypes had productivity above the national average (season 2013/14), which was 2854 kg ha-1 (CONAB, 2017). In Table 2 it was possible to observe that in relation to the 2014/15 crop, the averages ranged from 1126.42 kg ha-1 for UFUS Riqueza, to 2088.943 kg ha-1 for UFUS 1117-08. Among the most productive genotypes, the UFUS 7415 cultivar was also identified, coinciding with the previous harvest. For the 2015/16 crop, the averages ranged from 1853.33 kg ha-1 to UFUS 1117-02, to 3628.53 kg ha-1 to TMG 801 (Table 2). Three genotypes of the program were highlighted: UFUS: 1117-05, 1117-07 and 1117-10, which obtained productivity above the national average, which was 2870 kg ha-1 (CONAB, 2017). When comparing the first and third harvests, we can see that UFUS 1117-05, Sources of Variation Degrees of Freedom Medium Square Blocks / Environment 8 646959.64 Genotypes (G) 13 1681942.95** Environments (E) 3 10964484.27** G x E interaction 39 513957.88** Error 104 235944.99 Average 2284.13 CV (%) 21.26 H2 85.97 Relation >QME/