Optimizing the number of progenies and replications in plant breeding experiments

Filho, J. L. da Silva

doi:10.1590/s1984-70332013000300001

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…Note that the use of this design is common in initial stages of breeding cycles, primarily because of the high number of genotypes and restricted resources (Peternelli, Souza, Barbosa, & Carvalho, 2009;Prado et al, 2013). However, this design might result in selective gains, and the accuracy might be improved with the use of spatial analysis and intereffect recovery (Silva Filho, 2013;Rodriguez-Álvarez, Boer, van Eeuwijk, & Eilers, 2018). In the present study, the analysis was performed with interblock and intergenotypic information recovery.…”

Section: Resultsmentioning

confidence: 99%

Visual selection of Urochloa ruziziensis genotypes for green biomass yield

et al. 2019

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The breeding program of Urochloa ruziziensis evaluates many genotypes in initial phases. Evaluations through grades might make the selection less costly. The aim of this study was to verify the efficiency of visual selection for green biomass yield in relation to different selection strategies, such as mass selection by phenotypic mean, BLUP (Best Linear Unbiased Prediction) and at random. For this purpose, 2,309 regular genotypes were evaluated in an augmented block design in two cuts. The evaluators gave grades for plant vigor, and later, the plots were measured for green biomass yield. The coincidences of the selected genotypes were estimated by different selection strategies. Then, 254 clones of the genotypes selected in different strategies were evaluated in a clonal test in a triple lattice design in four cuts. The statistical analyses were performed in SAS using the Mixed procedure. The regular genotype level and clone-mean basis heritabilities were 31.16 and 62.91%, respectively, for green mass yield. The expected selection gains were 21.09% (visual), 25.43% (phenotypic mean), and 27.5% (BLUP). Moreover, the realized heritabilities for these strategies were 15.58, 11.87, and 15.86%, respectively, which might be associated with genotype by environment interaction. Therefore, the visual selection could be a useful strategy in initial phases of a U. ruziziensis breeding program because the efficiency was moderate to high in relation to phenotypic mean and BLUP.

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Section: Resultsmentioning

confidence: 99%

Visual selection of Urochloa ruziziensis genotypes for green biomass yield

et al. 2019

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Number of progenies and repetitions for reciprocal full-sib recurrent selection programs in maize

et al. 2021

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For a reciprocal recurrent selection (RRS) program to succeed, it is essential to maintain genetic variability throughout the selection cycles and to obtain accurate estimates of genetic parameters, which in turn are directly related to the number of progenies and repetitions evaluated. This study evaluates the potential of maize progenies of the sixth cycle of RRS and proposes, using simulation methods, the ideal combination of the number of progenies and repetitions to employ in reciprocal full-sib recurrent selection. A total of 163 full-sib progenies were evaluated in a randomized block design with six repetitions. Based on the yield data, analysis of variance was carried out, and different scenarios were simulated using the Monte Carlo chain method. These scenarios varied in the number of repetitions (two, four, and six) and progenies (30 to 163). The contrast between progenies and controls was significant, revealing the potential of the progenies of the sixth cycle of RRS. The high magnitude of the selective accuracy (0.77) was reflected in high estimates of heritability, which allowed for efficient phenotypic selection, obtaining selection gains of 14.07%. From the estimates of phenotypic and genotypic variance, heritability, accuracy, and standard error, it was found that a repetition number above two results in drastic changes in the estimates of these parameters; however, with the use of 130 progenies, these estimates tend to stabilize, implying that a high number of progenies does not interfere decisively in the quality of most parameters, except for the limits of maximum and minimum variation.

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Repeatability of some phenotypic stability parameters - a resampling approach

Mendes

Ramalho

2018

Crop Breed. Appl. Biotechnol.

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The aim of this study was to estimate the repeatability of some phenotypic stability parameters: reliability index (I), regression coefficient (b 0 e b 1), ecovalence, and the mean of the absolute scores (MAS), and to check the implications of estimating stability parameters using a reduced number of environments. A dataset comprising 25 common bean lines assessed in 36 environments was used. These environments comprise different locations, sowing seasons, and years. Different experimental groups, from three to 18 environments, were simulated. For each group, analysis of variance was performed and the stability parameters were estimated. The greater repeatability estimates were observed for the mean (b 0), followed by the I and b 1. Ecovalence and MAS had the lowest values for the repeatability estimates, which is not desirable for breeding programs aiming at selection for high stability. The phenotypic stability parameter should not be estimated from fewer than 12 environments.

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Optimizing the number of progenies and replications in plant breeding experiments

Abstract: -A determination criterion was proposed for the number of replications, r, and of evaluated progenies, N r , given P experimental plots, with N r

Cited by 4 publications

References 19 publications

Visual selection of Urochloa ruziziensis genotypes for green biomass yield

Visual selection of Urochloa ruziziensis genotypes for green biomass yield

Number of progenies and repetitions for reciprocal full-sib recurrent selection programs in maize

Repeatability of some phenotypic stability parameters - a resampling approach

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