Diallel analysis for technological traits in upland cotton.

Final cotton quality is of great importance, and it depends on intrinsic and extrinsic fiber characteristics. The objective of this study was to estimate general (GCA) and specific (SCA) combining abilities for technological fiber traits among six upland cotton genotypes and their fifteen hybrid combinations, as well as to determine the effective genetic effects in controlling the traits evaluated. In 2015, six cotton genotypes: FM 993, CNPA 04-2080, PSC 355, TAM B 139-17, IAC 26, and TAMCOT-CAMD-E and fifteen hybrid combinations were evaluated at the Experimental Station of Embrapa Algodão, located in Patos, PB, Brazil. The experimental design was a randomized block with three replications. Technological fiber traits evaluated were: length (mm); strength (gf/tex); fineness (Micronaire index); uniformity (%); short fiber index (%), and spinning index. The diallel analysis was carried out according to the methodology proposed by Griffing, using method II and model I. Significant differences were detected between the treatments and combining abilities (GCA and SCA), indicating the variability of the study material. There was a predominance of additive effects for the genetic control of all traits. TAM B 139-17 presented the best GCA estimates for all traits. The best combinations were: FM 993 x TAM B 139-17, CNPA 04-2080 x PSC 355, FM 993 x TAMCOT-CAMD-E, PSC 355 x TAM B 139-17, and TAM B 139-17 x TAMCOT-CAMD-E, by obtaining the best estimates of SCA, with one of the parents having favorable estimates for GCA.

Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.

Cotton produces one of the most important textile fibers of the world and has great relevance in the world economy. It is an economically important crop in Brazil, which is the world's fifth largest producer. However, studies evaluating the genotype x environment (G x E) interactions in cotton are scarce in this country. Therefore, the goal of this study was to evaluate the G x E interactions in two important traits in cotton (fiber yield and fiber length) using the method proposed by Eberhart and Russell (simple linear regression) and reaction norm models (random regression). Eight trials with sixteen upland cotton genotypes, conducted in a randomized block design, were used. It was possible to identify a genotype with wide adaptability and stability for both traits. Reaction norm models have excellent theoretical and practical properties and led to more informative and accurate results than the method proposed by Eberhart and Russell and should, therefore, be preferred. Curves of genotypic values as a function of the environmental gradient, which predict the behavior of the genotypes along the environmental gradient, were generated. These curves make possible the recommendation to untested environmental levels.

Genetic diversity among cotton cultivars in two environments in the State of Mato Grosso.

Using commercial cultivars to compose crossing blocks in cotton is a promising strategy, because these materials have desirable agronomic and technological characteristics. The objective of this study was to evaluate the genetic diversity among 16 cotton cultivars cultivated in two environments in the State of Mato Grosso, the largest national producer, using agronomical and technological traits. There was significant effect to cultivars for all traits, while genotype x environment interaction was significant only for average boll weight, short fiber index, and maturity of fibers. Therefore, because of the presence of genotype x environment interaction for three traits, we chose to study genetic diversity among cotton cultivars separately in each environment and investigate the interaction impact on the diversity among genotype pairs. Based on agronomical and technological performance and genetic diversity among cultivars in both environments, the most promising cross involves FM 910 and LD CV 02. We also observed that lint percentage and average boll weight presented a higher discrimination capacity in both environments.

Genetic diversity among exotic cotton accessions as for qualitative and quantitative traits.

Studying genetic diversity among a group of genotypes is important in genetic breeding because identifying hybrid combinations of greater heterotic effect also increases the chance of obtaining plants with favorable allele combinations in an intra-population selection program. The objective of this study was to compare different types of long and extra-long staple cotton and their genetic diversity in relation to the fiber traits and some agronomic traits in order to grant breeding programs. Diversity analysis among 29 cotton accessions based on qualitative and quantitative traits and joint including qualitative and quantitative traits was performed. Analysis based on qualitative and quantitative traits and joint met the accessions in three, two, and three groups, respectively. The cross between genotypes Giza 59 and Pima unknown was the most promising to generate segregating populations, comprising simultaneously resistance (based on molecular markers) to blue disease and bacterial blight, partial resistance to root-knot nematode, smaller size, in addition to good fiber characteristics. These populations can be used in recurrent selection programs as donors of alleles for development of long-staple cotton genotypes.

Usefulness of the HMRPGV method for simultaneous selection of upland cotton genotypes with greater fiber length and high yield stability.

The harmonic mean of the relative performance of genotypic predicted value (HMRPGV) method has been used to measure the genotypic stability and adaptability of various crops. However, its use in cotton is still restricted. This study aimed to use mixed models to select cotton genotypes that simultaneously result in longer fiber length, higher fiber yield, and phenotypic stability in both of these traits. Eight trials with 16 cotton genotypes were conducted in the 2008/2009 harvest in Mato Grosso State. The experimental design was randomized complete blocks with four replicates of each of the 16 genotypes. In each trial, we evaluated fiber yield and fiber length. The genetic parameters were estimated using the restricted maximum likelihood/best linear unbiased predictor method. Joint selection considering, simultaneously, fiber length, fiber yield, stability, and adaptability is possible with the HMRPGV method. Our results suggested that genotypes CNPA MT 04 2080 and BRS CEDRO may be grown in environments similar to those tested here and may be predicted to result in greater fiber length, fiber yield, adaptability, and phenotypic stability. These genotypes may constitute a promising population base in breeding programs aimed at increasing these trait values.

Number of repetitions for evaluating technological traits in cotton genotypes.

With the changes in spinning technology, technological cotton traits, such as fiber length, fiber uniformity, fiber strength, fineness, fiber maturity, percentage of fibers, and short fiber index, are of great importance for selecting cotton genotypes. However, for accurate discrimination of genotypes, it is important that these traits are evaluated with the best possible accuracy. The aim of this study was to determine the number of measurements (repetitions) needed to accurately assess technological traits of cotton genotypes. Seven experiments were conducted in four Brazilian States (Ceará, Rio Grande do Norte, Goiás, and Mato Grosso do Sul). We used nine brown and two white colored fiber lines in a randomized block design with four replications. After verifying the assumptions of residual normality and homogeneity of variances, analysis of variance was performed to estimate the repeatability coefficient and calculating the number of repetitions. Trials with four replications were found to be sufficient to identify superior cotton genotypes for all measured traits except short fiber index with a selective accuracy >90% and at least 81% accuracy in predicting their actual value. These results allow more accurate and reliable results in future researches with evaluating technological traits in cotton genotypes.

Correlations and path analysis among agronomic and technological traits of upland cotton.

To date, path analysis has been used with the aim of breeding different cultures. However, for cotton, there have been few studies using this analysis, and all of these have used fiber productivity as the primary dependent variable. Therefore, the aim of the present study was to identify agronomic and technological properties that can be used as criteria for direct and indirect phenotypes in selecting cotton genotypes with better fibers. We evaluated 16 upland cotton genotypes in eight trials conducted during the harvest 2008/2009 in the State of Mato Grosso, using a randomized block design with four replicates. The evaluated traits were: plant height, average boll weight, percentage of fiber, cotton seed yield, fiber length, uniformity of fiber, short fiber index, fiber strength, elongation, maturity of the fibers, micronaire, reflectance, and the degree of yellowing. Phenotypic correlations between the traits and cotton fiber yield (main dependent variable) were unfolded in direct and indirect effects through path analysis. Fiber strength, uniformity of fiber, and reflectance were found to influence fiber length, and therefore, these traits are recommended for both direct and indirect selection of cotton genotypes.

Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso.

Seed cotton yield is a trait governed by multiple genes that cause changes in the performance of genotypes depending on the cultivation environment. Breeding programs examine the genotype x environment interaction (GE) using precise statistical methods, such as AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction). The AMMI method combines the analysis of variance and principal components, to adjust the main effects (genotypes and environments) and the effects of GE interaction, respectively. The GGE biplot groups the genotype additive effect together with the multiplicative effect of the GE interaction, and submits both of these to the principal components analysis. The aim of this study was to investigate the association between the AMMI and GGE biplot methods and select cotton genotypes that simultaneously showed high productivity of seed cotton and stability in Mato Grosso environments. Trials were conducted with cotton cultivars in eight environments across Mato Grosso State in the 2008/2009 crop season. The experiment used a randomized block design with 16 genotypes and four replicates per genotype x environment combination. Data for seeds cotton productivity were analyzed by AMMI and GGE biplot methods. Both methods were concordant in the discrimination of environments and genotypes for phenotypic stability. The genotypes BRS ARAÇÁ and LD 05 CV had high seed cotton productivity and phenotypic stability, and could be grown in all environments across Mato Grosso State.