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

Matei, Gilvani; Benin, Giovani; Storck, Lindolfo; Milioli, Anderson Simionato; Bozi, Antonio Henrique; Dalló, Samuel Cristian; Lucion, Ricardo Antonio

doi:10.1590/0103-8478cr20160629

Cited by 4 publications

(5 citation statements)

References 9 publications

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“…Despite the advances obtained, the function of the genetic breeding must be continuous in the reach of the varietal ideotype, and for that, the final stage of evaluation of cultivars in field experiments demands precision (MATEI et al, 2017). In this stage, expressive phenotypic characters are usually evaluated for the identification and selection of superior individuals and according to Martin et al (2016), subject to both natural and artificial selection, in addition to suffering great environmental influence.…”

Section: Introductionmentioning

confidence: 99%

Experimental planning for the evaluation of phenotipic descriptors in banana

et al. 2018

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This work aimed to subsidize experimental planning for the evaluation of phenotypic characters in banana. The experiment consisted of a uniformity trial with Tropical cultivar spaced of 3 m x 2 m, in a useful area with nine rows of 40 plants. Vegetative and yield aspects were evaluated in two production cycles. Plants and basic units (UB) were combined to form various plot sizes, from which the variation coefficient and the soil heterogeneity index were estimated. To define the experimental design, the Hatheway method was used. Variability, resulting from the soil anisotropy and other factors such as desuckering cultural practice increases between mother plant and daughter plant cycles, with effects on experimental design. The variation coefficient and number of replicates are the factors that most influenced the experimental design. For the same precision level required, the combination that maximizes efficient in the use of experimental area can be adopted, that is, smaller plot size and higher number of replicates or larger plot size and fewer replicates. Estimates of plot size and number of replicates are subsides for the design of experiments for the evaluation of phenotypic descriptors in banana.

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Section: Introductionmentioning

confidence: 99%

Experimental planning for the evaluation of phenotipic descriptors in banana

et al. 2018

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“…In simulation studies developed by Matei et al (2017), the ideal number of repetitions and adequate statistical analysis were evaluated to obtain reliable estimates of genetic parameters for the productivity trait in 324 soybean genotypes. When using two repetitions, it was possible to obtain a selective accuracy that was considered high (<90).…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, it is important to use an appropriate number of repetitions to provide a good estimate of the experimental error and consequently increase the accuracy and power of the statistical tests (Silva Filho, 2013;Storck et al, 2016;Ribeiro et al, 2017). The adequate number of repetitions and progenies to estimate genetic parameters and dissimilarity or to compare genotypes has been studied by several authors for the most diverse crops and traits (Matei et al, 2017;Cargnelutti Filho et al, 2018;Toebe, 2020;Woyann et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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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“…Thus, the accuracy is an important tool to inform about the correct ordering of the cultivars for selection purposes and high values of this estimate should be desired within the experiments of breeding programs [13]. It was observed values of accuracy between 63% (rice blast severity) and 98% (days until flowering), showing experimental moderate to high precision, according to [14] [15]. Values already expected, because the accuracy is related to the heritability of the characters, it will be greater when it is heritability, so characters of high heritability as 100-grain weight (g) and days until flowering (days) were those that presented the highest accuracy values.…”

Section: Resultsmentioning

confidence: 99%

Genetic and Phenotypic Parameters in the Selection of Upland Rice Genotypes

Silva¹,

Botelho²,

Rodrigues³

et al. 2017

AJPS

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To assist in upland rice breeding programs, estimated genetic and phenotypic parameters are extremely important in the selection of superior lines. Thus, the objective of this study was estimate the genetic and phenotypic parameters of upland rice lines of the breeding program of UFLA in partnership with Embrapa Arroz e Feijão and Epamig. The experiment was installed in an experimental area of the Department of Agriculture at UFLA. It was evaluated 36 upland rice lines of the preliminary trial of the 2014/15 season, in randomized blocks, with three replications and plots consisted of five rows and each row has four meters. For this, it was evaluated the characters: plant height (cm), yield (kg•ha −1 ), 100-grain weight, days until flowering, percentage of filled grains and rice blast severity. The variance analysis and genetic parameters were estimated using the software SAS. To evaluate the experimental precision was estimated the accuracy, which varied between 63% and 98%, showing experimental precision, moderate to high. The lines differed significantly for all characters, meaning there is genetic variability among genotypes evaluated. With intensity of selection of 10% of lines, it was obtained a genetic gain of 325.29 kg•ha −1 in the character productivity, a plant height (cm) reduction in 5.50 cm, and days until flowering, with a reduction of 9.23 days, with selection of earlier plants. The estimated values for heritability ranged from 38% -96%. Estimates confirm the possible success with the selection of the upland rice lines for these characters.

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

Cited by 4 publications

References 9 publications

Experimental planning for the evaluation of phenotipic descriptors in banana

Experimental planning for the evaluation of phenotipic descriptors in banana

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

Genetic and Phenotypic Parameters in the Selection of Upland Rice Genotypes

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