Medidas de precisão experimental e número de repetições em ensaios de genótipos de arroz irrigado

Filho, Alberto Cargnelutti; Marchesan, Enio; Silva, Leandro Souza da; Toebe, Marcos

doi:10.1590/s0100-204x2012000300004

Cited by 26 publications

(32 citation statements)

References 7 publications

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“…Considering the existence of genetic variability in a population as a decisive factor in any breeding program (Cruz et al, 2004;Lynch and Walsh, 1998;Falconer and MacKay, 1996;Falconer et al, 1987;Falconer and MacKay et al, 1996), the studied population proved to be promising for selection and crossing works which aim at improving these traits. Similar results were obtained in other studies with rice crop (CARGNELUTTI FILHO et al, 2012;NASCENTE et al, 2011;REIS et al, 2007). In general, the estimated values of the coefficients of experimental variation denote moderate to high experimental precision (CARGNELUTTI FILHO et al, 2012), except for NP and NS, which obtained values above 20%.…”

Section: Resultssupporting

confidence: 89%

“…Similar results were obtained in other studies with rice crop (CARGNELUTTI FILHO et al, 2012;NASCENTE et al, 2011;REIS et al, 2007). In general, the estimated values of the coefficients of experimental variation denote moderate to high experimental precision (CARGNELUTTI FILHO et al, 2012), except for NP and NS, which obtained values above 20%. Coefficients estimates of genotypic variation ranged from 0.98 (DM) and 133.63% (YIE), indicating that among traits, YIE is that which shows greater variability, being highly promising for selection.…”

Section: Resultssupporting

confidence: 89%

See 1 more Smart Citation

Genetic parameters, correlations and path analysis in upland rice genotypes

Abreu¹,

Teodoro²,

Pantaleão³

et al. 2016

Biosci. J.

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ABSTRACT:Trying to obtain information relevant to the genetic improvement of rice, the aim of research was to estimate genetic parameters and identify agronomic characters directly and indirectly correlated with the grain yield of ten cultivars of upland rice. The experiment was conducted in the municipality of Aquidauna-MS, region of transition among the Savanna and Pantanal biomes. The experimental design was a randomized block with three replications. Treatments consisted of ten genotypes (BRS Aimoré, BRS Coringa, BRS Pepita, BRS Bonança, BRS Talento, BRS Maravilha, BRS Primavera, BRS Caiapó, BRS Monarca and BRS Aroma). The following variables were measured: days to flowering and maturity, plant height, number of stems and panicles, thousand grains mass and grain yield. It was determined the following genetic parameters: environmental, phenotypic and genotypic variances; coefficients of experimental and genotypic variation; heritability; b quotient; environmental, phenotypic and genetic correlations. Phenotypic correlations among traits and grain yield (principal dependent variable) were unfolded in direct and indirect effects. The population under study proved to be promising for improvement based on the traits plant height, days to flowering, thousand grains mass and grain yield. Plant height, number of panicles and thousand grains mass directly influence the yield, being recommended for direct selection of superior genotypes.

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Section: Resultssupporting

confidence: 89%

Section: Resultssupporting

confidence: 89%

Genetic parameters, correlations and path analysis in upland rice genotypes

Abreu¹,

Teodoro²,

Pantaleão³

et al. 2016

Biosci. J.

View full text Add to dashboard Cite

show abstract

“…Besides the significance of the F test for genotypes, the classification of the experiments by means of statistical experimental accuracy is crucial (CARGNELUTTI FILHO et al, 2012). The analysis of the experimental accuracy is important to guarantee that the results obtained in field experiments are reliable, and consequently the differences between genotypes are not due to the high experimental error.…”

Section: Resultsmentioning

confidence: 99%

Repeatability reveals to be a useful method to evaluate the quality of an experiment with common beans

Gurgel¹,

Peixoto²,

Bhering³

et al. 2017

Biosci. J.

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Field experiment should be carried out with high accuracy since the discarding of a trial involves waste of time and resources, and can mislead breeders in selecting inferior genotypes. The simulation of a large number of experiments with great variability of traits is the main strategy to assist breeders on how to perform the experiment. Therefore, the objective of this study was to evaluate two criteria to infer the experimental quality: Coefficient of Variation (CV) and repeatability coefficient. Experimental data from evaluations of common bean lines carried out in 104 experiments were used in this study. The simulation of the scenarios used the following parameters: number of cultivars, number of blocks, genetic variance, mean yield, and coefficient of variation. Two thousand replications for each scenario were simulated. Genotypes means were arranged in an order, and the Spearman correlation was obtained between the estimated genotypes mean and the true genotypic values. Results revealed that CV is not a reliable parameter to evaluate the quality of experiment in the field. In conclusion, repeatability coefficient is the parameter that defines the discarding criteria of evaluation experiments and the recommendation of cultivars, as long as the values for each response variable are established.

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“…In RCBD, estimates of SA and FDI were lower than those obtained by the Papadakis method for any number of replicates. In a study of 175 competition trials of irrigated rice in RCBD, with number of genotypes in the range of 5-36, SA was suitable to evaluate experimental precision in the trials and use of more than five replicates was of little contribution to precision gains (CARGNELUTTI FILHO et al, 2012). In another study with 101 maize yield trials, in RCBD, FDI was also suitable to classify the experimental precision (CARGNELUTTI FILHO & STORCK, 2007).…”

Section: Number Of Replicatesmentioning

confidence: 99%

Methods of analysis and number of replicates for trials with large numbers of soybean genotypes

et al. 2017

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The aim of this study was to evaluate the experimental precision of different methods of statistical analysis for trials with large numbers of soybean genotypes, and their relationship with the number of replicates. Soybean yield data (nine trials; 324 genotypes; 46 cultivars; 278 lines; agricultural harvest of 2014/15) were used. Two of these trials were performed at the same location, side by side, forming a trial with six replicates. Each trial was analyzed by the randomized complete block, triple lattice design, and use of the Papadakis method. The selective accuracy, least significant difference, and Fasoulas differentiation index were estimated, and model assumptions were tested. The resampling method was used to study the influence of the number of replicates, by varying the number of blocks and estimating the precision measurements. The experimental precision indicators of the Papadakis method are more favorable as compared to the randomized complete block design and triple lattice. To obtain selective accuracy above the high experimental precision range in trials with 324 soybean genotypes, two repetitions can be used, and data can be analyzed using the randomized complete block design or Papadakis method.

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Medidas de precisão experimental e número de repetições em ensaios de genótipos de arroz irrigado

Cited by 26 publications

References 7 publications

Genetic parameters, correlations and path analysis in upland rice genotypes

Genetic parameters, correlations and path analysis in upland rice genotypes

Repeatability reveals to be a useful method to evaluate the quality of an experiment with common beans

Methods of analysis and number of replicates for trials with large numbers of soybean genotypes

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