scholarly journals Comparisons of Potentials for General Combining Ability Selection Methods Utilizing One or Two Random-Mating Populations

1963 ◽  
Vol 16 (4) ◽  
pp. 838 ◽  
Author(s):  
B Griffing
Keyword(s):  
Combining Ability ◽  
Arbitrary Number ◽  
Random Mating ◽  
Selection Method ◽  
General Combining Ability ◽  
Single Locus ◽  
Genetic Constitution ◽  
Selection Methods ◽  
Population Mean ◽  
Entire Class

This study is concerned with comparisons of potentials exhibited by the entire class of general combining ability methods which can be generated by one or two random-mating populations. By potential is meant the greatest value the population mean assumes with continued application of a given selection method initially applied to a population of specified genetic constitution. The argument is restricted to an arbitrary number of alleles at a single locus, and it is assumed that the populations are infinite in size.

scholarly journals Prediction Formulae for General Combining Ability Selection Methods Utilizing One or Two Random-Mating Populations

1962 ◽  
Vol 15 (4) ◽  
pp. 650 ◽  
Author(s):  
B Griffing
Keyword(s):  
Combining Ability ◽  
Random Mating ◽  
General Combining Ability ◽  
Specific Combining Ability ◽  
Selection Methods

This study is the first of a series in which theoretical comparisons are made among various general combining ability and specific combining ability selection methods. The particular purpose of this study is to set out the prediction formulae for all possible general combining ability selection methods which can be generated by one or two base populations.

scholarly journals COMPARAÇÕES DE MÉTODOS DE SELEÇÃO EM POPULAÇÕES SIMULADAS DE FRANGOS CAIPIRAS

2017 ◽  
Vol 13 (Especial 2) ◽  
pp. 129-134
Author(s):  
Bruno Eduardo Damacena Silva ◽  
Jeferson Corrêa Ribeiro ◽  
Wallacy Barbacena Rosa dos Santos ◽  
Andreia Santos Cezário ◽  
Eliandra Maria Bianchini Oliveira ◽  
...  
Keyword(s):  
Genetic Gain ◽  
Overlapping Generations ◽  
Mating Systems ◽  
Random Mating ◽  
Selection Method ◽  
The Other ◽  
Individual Selection ◽  
Selection Methods ◽  
Slaughter Weight ◽  
Selection Systems

The purpose of this study was to compare the two types of selection methods known as BLUP and individual selection (IS) in populations of rustic chicken, evaluating the trait of slaughter weight and considering the averages of genetic gain and phenotypic value as response variables. A population of rustic chicken was simulated in the program Genesys, considering the basal population with 500 males and 500 females, from which was randomly chosen 120 males and 240 females. Then, the selected population was simulated considering the sexual ratios of 3, 4, 5 e 6 females per male in two selection types: Individual Selection (IS) and BLUP. In each selection method, the random mating system between breed chickens was used. Selection was performed during 15 consecutive and non-overlapping generations, with 10 simulation repetitions per generation, in order to decrease the genetic oscillation effects. The average genetic gain and the average phenotypic value in all methods and mating systems were evaluated. The results show that the ratio 6:1 was superior to the other sexual ratios in the two types of selection. When comparing the two selection systems, IS was superior to BLUP for the high phenotypic value of slaughter weight. Thus, the sexual ratio of six females for each male is recommended for individual 130 Colloquium Agrariae, vol. 13, n. Especial 2, Jan–Jun, 2017, p. 129-134. ISSN: 1809-8215. DOI: 10.5747/ca.2017.v13.nesp2.000218 selection, with which will allow high phenotypic values, with lower need of males

scholarly journals Influence of Sex on Selection III. Joint Contributions of Sex-Linked and Autosomal Genes

1966 ◽  
Vol 19 (5) ◽  
pp. 775 ◽  
Author(s):  
B Griffing
Keyword(s):  
Combining Ability ◽  
Arbitrary Number ◽  
General Combining Ability ◽  
Arbitrary System ◽  
Selection Procedures ◽  
Locus Model

The joint contributions of sex-linked and autosomal genes to mass and general combining ability selection procedures are examined. Detailed results are given for n consecutive cycles of selection, and for relaxation from selection, with regard to a two�locus model which involves both sex-linked and autosomal loci. This model permits (1) an arbitrary number of alleles at each locus; (2) an arbitrary system of dominance parameters; (3) an arbitrary system of sex-linked-autosomal epistatic parameters; and (4) different genotypic values for the same autosomal genotype in the two sexes. This last condition implies that the model incorporates "sex-influenced" as well as "sex-linked" inheritance.

The Effectiveness of the Fused Weighted Filter Feature Selection Method to Improve Software Fault Prediction

2016 ◽  
Vol 8 ◽  
pp. 5 ◽  
Author(s):  
Fatemeh Alighardashi ◽  
Mohammad Ali Zare Chahooki
Keyword(s):  
Feature Selection ◽  
Feature Selection Method ◽  
Selection Method ◽  
Machine Learning Algorithms ◽  
Fault Prediction ◽  
Filter Method ◽  
Selection Methods ◽  
Software Projects ◽  
Software Fault Prediction ◽  
Software Fault

Improving the software product quality before releasing by periodic tests is one of the most expensive activities in software projects. Due to limited resources to modules test in software projects, it is important to identify fault-prone modules and use the test sources for fault prediction in these modules. Software fault predictors based on machine learning algorithms, are effective tools for identifying fault-prone modules. Extensive studies are being done in this field to find the connection between features of software modules, and their fault-prone. Some of features in predictive algorithms are ineffective and reduce the accuracy of prediction process. So, feature selection methods to increase performance of prediction models in fault-prone modules are widely used. In this study, we proposed a feature selection method for effective selection of features, by using combination of filter feature selection methods. In the proposed filter method, the combination of several filter feature selection methods presented as fused weighed filter method. Then, the proposed method caused convergence rate of feature selection as well as the accuracy improvement. The obtained results on NASA and PROMISE with ten datasets, indicates the effectiveness of proposed method in improvement of accuracy and convergence of software fault prediction.

A fuzzy gaussian rank aggregation ensemble feature selection method for microarray data

2021 ◽  
Vol 24 (4) ◽  
pp. 289-301
Author(s):  
B. Venkatesh ◽  
J. Anuradha
Keyword(s):  
Feature Selection ◽  
Microarray Data ◽  
Classification Accuracy ◽  
Performance Metrics ◽  
Feature Selection Method ◽  
Selection Method ◽  
Support Vector ◽  
Svm Classifier ◽  
Binary Particle Swarm Optimization ◽  
Selection Methods

In Microarray Data, it is complicated to achieve more classification accuracy due to the presence of high dimensions, irrelevant and noisy data. And also It had more gene expression data and fewer samples. To increase the classification accuracy and the processing speed of the model, an optimal number of features need to extract, this can be achieved by applying the feature selection method. In this paper, we propose a hybrid ensemble feature selection method. The proposed method has two phases, filter and wrapper phase in filter phase ensemble technique is used for aggregating the feature ranks of the Relief, minimum redundancy Maximum Relevance (mRMR), and Feature Correlation (FC) filter feature selection methods. This paper uses the Fuzzy Gaussian membership function ordering for aggregating the ranks. In wrapper phase, Improved Binary Particle Swarm Optimization (IBPSO) is used for selecting the optimal features, and the RBF Kernel-based Support Vector Machine (SVM) classifier is used as an evaluator. The performance of the proposed model are compared with state of art feature selection methods using five benchmark datasets. For evaluation various performance metrics such as Accuracy, Recall, Precision, and F1-Score are used. Furthermore, the experimental results show that the performance of the proposed method outperforms the other feature selection methods.

scholarly journals Genetic Dissection of the General Combining Ability of Yield-Related Traits in Maize

2020 ◽  
Vol 11 ◽  
Author(s):  
Xin Lu ◽  
Zhiqiang Zhou ◽  
Zhaohui Yuan ◽  
Chaoshu Zhang ◽  
Zhuanfang Hao ◽  
...  
Keyword(s):  
Combining Ability ◽  
General Combining Ability ◽  
Genetic Dissection

HETEROSIS, COMBINING ABILITY, AND PREDICTED SYNTHETICS FROM A DIALLEL CROSS IN SUNFLOWERS (HELIANTHUS ANNUUS L.)

1966 ◽  
Vol 46 (1) ◽  
pp. 59-67 ◽  
Author(s):  
Eric D. Putt
Keyword(s):  
Helianthus Annuus ◽  
Combining Ability ◽  
Oil Content ◽  
Diallel Cross ◽  
General Combining Ability ◽  
Specific Combining Ability ◽  
Helianthus Annuus L ◽  
The Mean ◽  
Seed Characters ◽  
Mature Weight

Heterosis occurred for the eight plant and seed characters studied. It was most frequent for yield of seed and height of plant. Mean squares for general combining ability (gca) and specific combining ability (sca) were significant (P =.01) for all characters. The estimated components for gca were greater than for sca for days to mature, weight per bushel, and percent oil in the seed; less for height and yield of seed; and essentially the same for days to bloom, diameter of head, and weight per 1000 seeds.The yield of seed and percent oil in the seed, for the highest ranking 100 synthetics that could be composed from the 10 lines, was predicted in F6 assuming 50 and 60% outcrossing between F2 and F6. Virtually all values exceeded the mean performance of four check samples of commercial hybrids. Many exceeded the highest rank check for oil content in the seed. Fourteen of the highest ranking 100 synthetics for yield and 30 for oil content consisted of two or three lines. It was concluded that synthetics can be superior to the present hybrids in heterosis and that desirable synthetics can be made from only a few lines.

HETEROSIS IN DIALLEL CROSSES AMONG SIX VARIETIES OF HARD RED SPRING WHEAT

1969 ◽  
Vol 11 (4) ◽  
pp. 810-822 ◽  
Author(s):  
D. R. Knott ◽  
S. S. Sindagi
Keyword(s):  
Spring Wheat ◽  
Combining Ability ◽  
General Combining Ability ◽  
Specific Combining Ability ◽  
Diallel Crosses ◽  
Hard Red Spring Wheat

Diallel crosses were made among six varieties of hard red spring wheat that differed considerably in yield and other characteristics. The F1 hybrids were tested at two seeding rates and the F2, hybrids at one. Heterosis was not great in either generation and no cross appeared to be promising. General combining ability was much more important than specific combining ability and parental yields gave reasonable predictions of hybrid yields. Yields of hybrids at the two seeding rates were closely correlated.

scholarly journals Association between Griffing's diallel and the adaptability and stability of Eberhart and Russel

1999 ◽  
Vol 22 (3) ◽  
pp. 451-456 ◽  
Author(s):  
Cleso Antônio Patto Pacheco ◽  
Cosme Damião Cruz ◽  
Manoel Xavier dos Santos
Keyword(s):  
Combining Ability ◽  
General Combining Ability ◽  
Genetic Effects ◽  
Specific Combining Ability ◽  
Regression Coefficients ◽  
Stability Parameters ◽  
The Mean ◽  
Additive Genetic Effects ◽  
F1 Cross

The objective of the present work was to provide a methodology to study the inheritance of adaptability and stability through the breakdown of Eberhart and Russell regression coefficients and regression deviations in effects due to the mean and additive genetic effects (gi's and gj's) as well as dominance effects (sij's) of Griffing´s methodology, when the diallel is conducted in several environments. It was concluded that the adaptability and stability parameters are determined in the same manner as are genetic effects. So an F1 cross inherits half the general combining ability (GCA) mean effect from each parent, while the effects due to specific combining ability (SCA) are subjected to the same considerations relative to sij's, i.e., they are dependent on specific combinations.

Sign in / Sign up

Export Citation Format

Share Document