MULTIVARIATE ANALYSIS OF GENETIC DIVERGENCE IN COTTON (*)

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1 MULTIVARIATE ANALYSIS OF GENETIC DIVERGENCE IN COTTON (*) Fábio A. Suinaga (Embrapa Algodão / suinaga@cnpa.embrapa.br), Eleusio C. Freire (Embrapa Algodão), Cristina S. Bastos (Embrapa Algodão), Luis E. P. Rangel (MAPA). ABSTRACT - The objective of this research was to study the genetic dissimilarity among sixteen cotton cultivars. Nine agronomic and fiber technology characters were evaluated. Considering these data, it was estimated the Mahalanobis distance (D 2 ij) between a pair of genotypes, the number of varieties groups found in Tocher s technique and the plot of the first two canonical variables, as well as the relative contribution of each character. Based on D 2 ij, the most divergent cultivars were BRS Jatobá and FM 977. The multivariate methods were congruent in their results. The ascendant order of importance of the evaluated characters were: length uniformity; reflectance; lint yield; lint strength; yellowness; micronaire; upper-half mean length; lint percentage and plant height. Key words: Gossypium hirsutum, genetic distance, canonical variables. ANÁLISE MULTIVARIADA DA DIVERGÊNCIA GENÉTICA DO ALGODOEIRO RESUMO - Este trabalho foi realizado com o objetivo de avaliar a divergência genética de dezesseis cultivares de algodão herbáceo. Foram avaliadas nove características agronômicas e de qualidade da fibra do algodoeiro. De posse destes dados, foi possível realizar a dispersão gráfica das duas primeiras variáveis canônicas, o estudo da importância relativa dos caracteres, bem como estimar a distância generalizada de Mahalanobis (D 2 ij) e com base nesta distância proceder a análise de agrupamento de Tocher. Os cultivares mais divergentes, de acordo com a D 2 ij, foram as cultivares BRS Jatobá e FM 977. Os métodos multivariados utilizados neste estudo apresentaram agrupamentos semelhantes entre si. Os caracteres avaliados em ordem crescente de importância foram: uniformidade do comprimento da fibra, reflectância da fibra, produtividade de algodão em caroço, resistência da fibra, grau de amarelecimento da fibra, índice de micronaire, comprimento da fibra, percentagem de fibra e altura de plantas. Palavras-chave Gossypium hirsutum, distância genética, variáveis canônicas. INTRODUCTION Genetic diversity among parentals is considered an important factor for obtaining heterotic hybrids. This diversity is one of the restraining tools for breeding programs based on hybridization, because it generates parameters for identifying superior parentals. According to Cruz and Carneiro. (2003), this distance is essential to increase the chance of recovering superior genotypes. In a cotton breeding program, several characters are simultaneously measured, then it is possible to estimate the genetic divergence by using multivariate methods. Thhis divergence is based on physiological, morphological and agricultural characters of a group of genotypes (MACHADO et al., 2002). The efficacy of the genetic divergence as a criterion for choosing parents to be crossed has been reported by several authors (DIAS and KAGEYAMA, 1997; MACHADO et al., 2002). Moreover, the Principal Component Analysis and the Canonical Variable Analysis have analogous efficacy to

2 determine the most suitable combinations for a breeding program (MACHADO et al., 2000; SUINAGA et al., 2003). Estimation of genetic diversity is an important step for a breeding program, but not the last one. Another helpful issue to be evaluated is the relative importance of the characters. One method to estimate the relative importance was proposed by Singh (1981). In this procedure (based on Mahalanobis distance), each character has a percentage which refers to its contribution to the whole divergence. Theoretically, the characteristic with the least percentage is able to be omitted from the following genotype evaluations (CRUZ and CARNEIRO, 2003). Thus, the objectives of this research were to study the genetic divergence among sixteen cotton cultivars by using multivariate analysis in order to select the most suitable combinations, as well as, to investigate the importance of the evaluated characters. MATERIAL AND METHODS This research was carried out in seven locations (environments) from Mato Grosso, Brazil. These locations were: Itiquira, Lucas do Rio Verde, Novo São Joaquim, Primavera do Leste, Rondonópolis, Sapezal and Pedra Preta. The sixteen genotypes were represented by the following cultivars: 1) BRS Aroeira; 2) BRS Ipê; 3) BRS Cedro; 4) BRS Jatobá; 5) FM 966; 6) FM 977; 7) SG 821; 8) Delta Penta; 9) Delta Opal; 10) Acala 90; 11) IAC 24; 12) CD 406; 13) Makina; 14) Fabrika; 15) CD 407and 16) ST 474. All evaluations were conducted in the cotton agricultural year of 2003/2004. The experimental design used in this study was the complete blocks with four replications. Each plot was composed by four rows (spaced each other by 0.90 m) of five meters length and four meters width. Central rows represented the harvested plot, in which all the evaluations were realized. The assessed characters in field/gin were the plant height (m), lint percentage (%) and the total lint yield (Kg/ha). Besides, a sample of the lint was addressed to a HVI (High Volume Instruments) laboratory, in order to determine the fiber characteristics. These were: the upper-half mean length (mm); length uniformity (%); lint strength (g/tex); micronaire (index); reflectance (%) and yellowness (index). Initially, the analysis of variance (F test) for all nine evaluated characters was carried out considering each particular location. In this study, the effects of cultivars and environments were considered as fixed. The differences among cultivars were determined by the Scott and Knott s test (SCOTT and KNOTT, 1974) with α = After this step, the dissimilarity among cotton cultivars was estimated by Mahalanobis distance (D 2 ij), and these varieties were grouped using two multivariate procedures: Tocher s optimization method applied to Mahalanobis distance matrix (RAO, 1952) and the dispersion of the first two canonical variables (CRUZ and CARNEIRO, 2003). In order to study the relative importance of the assessed characters on the genetic divergence, Singh s analysis (Singh, 1981) were performed based on Mahalanobis distance matrix. All statistical procedures were carried out with the help of the software GENES (CRUZ, 2001).

3 RESULTS AND DISCUSSION The Mahalanobis distances between each pair (D 2 ij) of cotton cultivars, considering nine quantitative characters were shown on Table 1. The highest distances were observed between BRS Jatobá x FM 977 (22.76) and BRS Jatobá x FM 966 (20.12). The least D 2 ij were estimated between BRS Cedro and ST 474 (0.58) (Table 1). Machado et al. (2002), in order to obtain the best combinations, choose parents which have the greatest genetic divergence. However, not only the genetic divergence might be used to choose parents for crossing, but also their per se performance. As reported by Abreu et al. (1999) the best hybrids to be tested in a breeding program might involve both divergent and highly productive parents. In cotton, superior genotypes possess average plant height of 100 cm, lint percentage greater than 42%, total yield (lint + seed) greater than 4500 Kg/ha, and suitable fiber characteristics (CARVALHO et al., 2003). Considering these parameters, the best hypothetical hybrids for this study might involve: a) BRS Cedro (one of the best lint percentage) and FM 966, FM 977, SG 821, Delta Penta, Makina and b) FM 977 and SG 821, Delta Penta, Makina (Tables 1 and 2). Table 1. Mahalanobis distances between pairs of cotton cultivars based on nine quantitative characters. Itiquira, Lucas do Rio Verde, Novo São Joaquim, Primavera do Leste, Rondonópolis, Sapezal and Pedra Preta, Mato Grosso State, 2003/2004 Cultivars BRS Aroeira BRS Ipê BRS Cedro BRS Jatobá FM 966 FM 977 SG 821 BRS Aroeira BRS Ipê BRS Cedro BRS Jatobá FM FM SG Delta Penta Delta Opal Acala IAC CD Makina Fabrika CD ST

4 Cultivars DeltaPenta DeltaOpal Acala90 IAC24 CD406 Makina Fabrika CD407 ST474 BRS Aroeira BRS Ipê BRS Cedro BRS Jatobá FM FM SG DeltaPenta Delta Opal Acala IAC CD Makina Fabrika CD ST Table 2. Average distances within and between five clusters of cotton cultivars based on Tocher s optimization method. Itiquira, Lucas do Rio Verde, Novo São Joaquim, Primavera do Leste, Rondonópolis, Sapezal and Pedra Preta, Mato Grosso State, 2003/2004 Cluster 1 (Number of varieties) I II III IV V I (10 varieties) II (2 varieties) III (2 varieties) IV (1 varieties) V (1 varieties) Clusters: I) BRS Cedro, ST 474, Delta Opal, Acala 90, Fabrika, CD 406, Delta Penta, BRS Ipê, Makina e SG 821; II) FM 966 e FM 977; III) BRS Aroeira e CD 407; IV) IAC 24 e V) BRS Jatobá. Regarding the canonical variable analysis under the joint environment data, the first three canonical variables explained % of the total variability. The bidimensional plot of these first two canonical axes was shown on Figure 1. The other possible graphic, considering the canonical variables 1 and 3 were not shown due to its distortion. According to Cruz and Carneiro (2003), when the first three axes retain more than 80% of the whole variability, the most suitable procedure is to plot two graphics. One based on the first and second canonical variables and the other based on the first and third canonical axes. However, as concluded by these authors, in cases of greater distortion the latter graphic might be discarded. The sixteen varieties evaluated in this study were grouped in five clusters by Tocher s optimization analysis (Table 2). The same trend was observed in the dispersion of the first two canonical variables graphic (Fig. 1). Both methods show the great similarity among them, which means that by using these techniques it was possible to determine parents with high genetic divergence. Similar results were observed by Vidigal et al. (1997) in cassava clones.

5 CV CV 2 Figure 1. Representation of sixteen cotton cultivars 1 on the first two axes of canonical variables analysis (CV 1 and CV 2 ). Itiquira, Lucas do Rio Verde, Novo São Joaquim, Primavera do Leste, Rondonópolis, Sapezal and Pedra Preta, Mato Grosso State, 2003/2004. ( 1 Cultivars: 1) BRS Aroeira; 2) BRS Ipê; 3) BRS Cedro; 4) BRS Jatobá; 5) FM 966; 6) FM 977; 7) SG 821; 8) Delta Penta; 9) Delta Opal; 10) Acala 90; 11) IAC 24; 12) CD 406; 13) Makina; 14) Fabrika; 15) CD 407; 16) ST 474) The rank of characters in an ascendant order of importance, according to Singh s analysis was: length uniformity (2.41 %); reflectance (2.79 %); lint yield (3.20 %); lint strength (6.04 %); yellowness (8.37 %); micronaire (11.34 %); upper-half mean length (17.53 %); lint percentage (23.03 %) and plant height (25.29%). CONCLUSIONS 1. The most divergent cultivars were BRS Jatobá and FM 977. On the other side, the most similar varieties were BRS Cedro and ST 474; 2. Both multivariate methods showed similar results: five clusters of varieties;

6 3. The most suitable crosses might involve the following combinations: BRS Cedro x FM 966, BRS Cedro x FM 977, BRS Cedro x SG 821, BRS Cedro x Delta Penta, BRS Cedro x Makina, FM 977 x SG 821, FM 977 x Delta Penta and FM 977 x Makina; 4. The ascendant order of importance of the evaluated characters were: length uniformity; reflectance; lint yield; lint strength; yellowness; micronaire; upper-half mean length; lint percentage and plant height. (*) This research was sponsored by FACUAL. REFERENCES ABREU, A. de F. B.; RAMALHO, M. A. P.; FERREIRA, D. F. Selection potential for seed yield from intra end inter-racial populations in common bean. Euphytica, v.108, n. 2, p CARVALHO, L. P.; LANZA, M. A.; FALLIERI, J. et al. Análise da diversidade genética entre acessos de banco ativo de germoplasma de algodão. Pesquisa Agropecuária Brasileira, v. 38, n. 10, p CRUZ, C. D. Programa GENES: aplicativo computacional em genética e estatística. Viçosa: Imprensa Universitária, p. CRUZ, C. D.; CARNEIRO, P. C. S. Modelos biométricos aplicados ao melhoramento genético. Viçosa: Imprensa Universitária, p. Vol. 2. DIAS, L. A.; KAGEYAMA, P. Y. Multivariate genetic divergence and hybrid performance of cacao (Theobroma cacao L.). Revista Brasileira de Genética, v. 20, n. 1, p MACHADO, C. F.; NUNES, G. H. S.; FERREIRA, D. F. et al. Divergência genética entre genótipos de feijoeiro a partir de técnicas multivariadas. Ciência Rural, v. 32, n. 2, p RAO, C. R. Advanced statistical methods in biometric research. New York: John Wiley, p. SCOTT, A. J.; KNOTT, M. A. A cluster analysis method for grouping means in the analysis of variance. Biometrics, v. 30, n. 3, p SINGH, D. The relative importance of characters affecting genetic divergence. Indian Journal of Genetic and Plant Breeding, v. 41, n. 2, p SUINAGA, F. A.; CASALI, V. W. D.; SILVA, D. J. H. da et al. Dissimilaridade genética de fontes de resistência de Lycopersicon spp. a Tuta absoluta (Lepidoptera: Gelechiidae). Revista Brasileira de Agrociência, v. 9, n. 4, p VIDIGAL, M. C. G.; VIDIGAL FILHO, P. S.; AMARAL JUNIOR, A. T. do. et al. Diversidade genética entre cultivares de mandioca por meio de estatística multivariada. Bragantia, v. 56, n. 2, p