Repeatability of agronomic traits in Panicum maximum (Jacq.) hybrids

Abstract

ABSTRACT. When evaluating plants, in particular perennial species, it is common to obtain repeated measures of a given trait from the same individual to evaluate the traits' repeatability in successive harvests. The degree of correlation among these measures defines the coefficient of repeatability, which has been widely utilized in the study of forage traits of interest for breeding. The objective of the present study was to evaluate the repeatability of agronomic traits in Panicum maximum hybrids. Hybrids from three progenies totaling 320 hybrids were evaluated in an incompleteblock design, with consideration of production and morpho-agronomic traits. Of the production traits, total dry matter and leaf dry matter showed the highest repeatability and varied from 0.540 to 0.769, whereas stem dry matter had lower coefficients (0.265-0.632). Among the morpho-agronomic traits, plant height and incidence of Bipolaris maydis had higher coefficients (0.118-0.460). The repeatability values of the agronomic traits were low-to- 19283 Repeatability in Panicum maximum©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 14 (4): 19282-19294 (2015) moderate, and six evaluations were sufficient to provide accuracy in the selection of hybrids regarding total dry matter, leaf dry matter, plant height, and incidence of B. maydis, whereas the other traits require more repeated measures to increase reliability in the prediction of their response.

Repeatability and genotypic stability of agronomic characteristics in Panicum maximum Jacq.

“…Regardless of the method used, the coefficient of determination was higher than 82.89, indicating reliability in the identification of the best P. maximum genotypes for DM production (Table 1). Braz et al (2015b), evaluating agronomic characteristics of different progenies of P. maximum in six harvests, found similar results to those of this study, and regardless of the method used, the authors found a coefficient of determination above 82.55. These results indicate that TDM evaluation requires a smaller number of repeated measures for a good level of reliability in the prediction of the response and identification of superior genotypes.…”

“…According to the authors, in general, variations in the estimate of the repeatability coefficient indicate the need to use the several methods available to obtain an accurate range within which, more likely, the actual value for this parameter is found. The same response was also observed by Cargnelutti Filho et al (2004), Braz et al (2015b) and Fernandes et al (2017) in P. maximum. Braz et al (2015b) highlighted a large discrepancy between methods, which was attributed to the bias of the principal component analysis methods when the actual value of the coefficient approaches zero (Mansour et al, 1981).…”

“…This may be justified by the fact that the experiment lasted for two consecutive years, including periods of drought and transitions, periods in which the stem yields can vary greatly and, consequently, affect L%. Lower repeatability coefficients for L% were also observed by Braz et al (2015b), who found mean values of 0.2498 for full-sib progenies of P. maximum. According to these authors, these results may be associated to the low degree of genetic control of the characteristic L%, which is subject to environmental variation and tends to present a high coefficient of variation.…”

“…The TDM and LDM characteristics presented very close values. According to Braz et al (2015b) this behavior can be explained by the large amount of leaves that is usually found in forage mass samples in P. maximum genotypes. Also, the fact that the genotypes evaluated in this study are considered to perform well for characteristics of interest in breeding, such as LDM, also contribute to this result.…”

Statistical models for genomic selection in <em>Panicum maximum</em> considering allelic dosage

“…In perennial crops, such as Panicum maximum, the evaluation process is performed by repeated measures in the same individual, in order to infer the genotype's ability to repeat its performance over sucessive evaluations (Braz et al, 2015). Analysis of mixed models allows modeling different structures of variance and covariance (VCOV) to investigate different assumptions of heterogeneity and dependence between observations (Crossa et al, 2006).…”