Genetic gains in agronomic and technological traits of elite cotton genotypes

Ribeiro, Larissa Pereira; Carvalho, Luiz Paulo de; Farias, F. J. C.; Rodrigues, Josiane Isabela da Silva; Teodoro, Paulo Eduardo; Bhering, Leonardo Lopes

doi:10.1590/1678-4499.2017329

Cited by 11 publications

(8 citation statements)

References 22 publications

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“…The other traits showed moderate heritability estimates. Similar results were found by Ribeiro et al (2018), Khan et al (2010), andKilli et al (2005) when estimating the heritability of fiber quality traits in cotton grown in multiple environments. However, Peixoto et al ( 2021) observed low heritability estimates for fiber quality traits in cotton and attributed these findings to the high estimates of residual variance obtained.…”

Section: Discussionsupporting

confidence: 86%

Genotype selection for fiber quality traits in cotton in the Brazilian Northeast

et al. 2022

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The search for cotton (Gossypium hirsutum L.) genotypes gathering high yield and fiber quality is the main objective of breeding programs. The objectives of this study were: (a) to verify which effects contribute the largest fraction of the total phenotypic variance of cotton fiber quality traits and (b) to recommend the best genotypes for these traits. Eight competition trials of cotton cultivars were carried out between the 2017 and 2019 seasons. Field trials were carried out in Alagoinha (crops seasons 2017, 2018, and 2019) and Barbalha (2017 and in a randomized block design with three repetitions. Fifteen genotypes developed by the cotton plant breeding program of Embrapa Algodão were evaluated. The following fiber quality traits were evaluated: fiber percentage (FP), average boll weight (BW), upper-half mean length, fiber uniformity (UNIF), short fiber index (SFI), fiber strength (STR), elongation (ELG), micronaire (MIC), and fiber maturity. Genotypic values (GVs) for the evaluated traits were estimated. The total phenotypic variance of the fiber quality traits evaluated is mostly composed of genotypic effects. Only the traits FP, BW, and ELG showed significant genotypes × sites interaction. The genotype G1 has high GVs for the traits FP, BW, fiber length, and fiber uniformity. The G15 stood out by gathering high values for UNIF, SFI, and STR.

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Section: Discussionsupporting

confidence: 86%

Genotype selection for fiber quality traits in cotton in the Brazilian Northeast

et al. 2022

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“…Longer fibers improve the processing speed in the textile industry (Joy et al., 2012). Conversely, for fiber fineness (MIC) finer fiber is desired, with target values ranging between 0.149 and 0.165 μg mm −1 (Ribeiro et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

Reaction norms‐based approach applied to optimizing recommendations of cotton genotypes

et al. 2020

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Reaction norms fitted through random regression models (RRM) have been widely used in animal and plant breeding for analyses of genotype × environment (G × E) interaction. However, in annual crops, they remain unexplored. Thus, this study aimed to evaluate the applicability and efficiency of RRM fitted through Legendre polynomials as a tool to recommend cotton (Gossypium hirsutum L.) genotypes. To this end, a data set with 12 genotypes of cotton evaluated in 10 environments for fiber length (FL) and fiber fineness was used. The restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) procedure was used to estimate the variance components and to predict the genetic values. Results showed that there was genetic variability among cotton genotypes and that the reaction norms over the environmental gradient illustrated the G × E interaction. Very high selective accuracies (̂> 0.90) were found for both traits in all environments, which indicates high reliability in the genotype's recommendation. The areas under the reaction norms were calculated for the recommendation of genotypes for unfavorable, favorable, and overall environments. Regarding genotypes recommendation, areas under reaction norms allow recommending genotypes for unfavorable and favorable environments, as well as for overall recommendation, for both traits. This study is the first considering reaction norms fitted through RRM for the recommendation of cotton genotypes and demonstrated the potential of this technique in cotton breeding, besides its great potential to deal with G × E interactions.

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“…As a result, fiber quality traits are relevant in the analyses toward the cotton ideotype. However, the fiber quality traits are, generally negative correlated with SY, which implies in difficult for breeders in the selection process (Ribeiro et al, 2018). The GYT-biplot combines the yield information with other traits and allowed the combined selection of the best cultivars.…”

Section: Resultsmentioning

confidence: 99%

“…In this point, the challenge emerges once the correlation between pair of traits is not always positive or even large. Both aspects are crucial in a cotton breeding program, in which both yield and quality traits (such as fiber length) are desirable for improving the final value of the product (Teodoro et al, 2018) and the correlation between the yield and quality traits are lower or even negative (Ribeiro et al, 2018;Teodoro et al, 2019). Then, for cotton breeding programs, methodologies that encompass multivariate analyses are core important in the breeding process toward the cotton ideotype.…”

Section: Introductionmentioning

confidence: 99%

Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot

et al. 2022

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In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.

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Genetic gains in agronomic and technological traits of elite cotton genotypes

Cited by 11 publications

References 22 publications

Genotype selection for fiber quality traits in cotton in the Brazilian Northeast

Genotype selection for fiber quality traits in cotton in the Brazilian Northeast

Reaction norms‐based approach applied to optimizing recommendations of cotton genotypes

Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot

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