scholarly journals Simulation Study on the Integration of Health Traits in Horse Breeding Programs

Animals ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1153
Author(s):  
Lisa Büttgen ◽  
Johannes Geibel ◽  
Henner Simianer ◽  
Torsten Pook
Keyword(s):  
Osteochondrosis Dissecans ◽  
Selection Index ◽  
R Package ◽  
Breeding Value ◽  
Index Selection ◽  
Threshold Selection ◽  
Horse Breeding ◽  
Frequency Of Use ◽  
Performance Traits ◽  
And Performance

Osteochondrosis dissecans (OCD) is a degenerative disease of the cartilage leading to osseous fragments in the joints. It is important in horse breeding both from an animal welfare and an economic perspective. To study adequate breeding strategies to reduce OCD prevalence, a lifelike simulation of the breeding program of German Warmblood horses was performed with the R package MoBPS. We simulated complex breeding schemes of riding horses with different selection steps and realistic age structure, mimicking the German situation. As an example, osseous fragments in fetlock and hock joints were considered. Different scenarios, either using threshold selection, index selection or genomic index selection, respectively, were compared regarding their impact on health and performance traits. A rigorous threshold selection as well as the integration of OCD in a selection index at the stage of stallion licensing and chosen frequency of use in breeding cases on a selection index that includes breeding values for OCD traits performed best on a comparable level. Simply integrating OCD in this breeding value was less effective in terms of OCD reduction. Scenarios with a higher reduction of OCD also showed a slightly reduced improvement in the riding horse performance traits.

An economic selection index for lean meat production in New Zealand sheep

1987 ◽  
Vol 45 (3) ◽  
pp. 465-475 ◽  
Author(s):  
G. Simm ◽  
M. J. Young ◽  
P. R. Beatson
Keyword(s):  
New Zealand ◽  
Selection Index ◽  
Live Weight ◽  
Breeding Value ◽  
Index Selection ◽  
Meat Production ◽  
Total Fat ◽  
Terminal Sire ◽  
Economic Selection ◽  
Lean Weight

ABSTRACTAn economic selection index was derived for terminal sire sheep breeds or strains, using physical and financial results from New Zealand export lamb-producing flocks. The aggregate breeding value of the index comprised carcass lean weight and carcass total fat weight. Index measurements were live weight, ultrasonic fat depth and ultrasonic muscle depth. Economic values used for lean and fat weights (NZ$5·65 and NZ$–1·2 per kg, respectively) were the change in profit per kg increase in lean or fat weight from that in the average carcass of lambs slaughtered in 1984/85. The s.d. of the aggregate breeding value was NZS3·20, and the correlation between the full index and the aggregate breeding value was 0·23. This correlation fell to 0·18, 0·15 and 0·07, respectively, when muscle depth or fat depth or muscle and fat depths were omitted from the index. Selection on the full index, or on the index omitting muscle depth was expected to lead to an increase in carcass lean weight and a slight decrease in carcass fat weight. Selection on the index omitting fat depth, or selection on live weight alone, was expected to lead to an increase in both fat and lean weights.

scholarly journals Optimal breeding-value prediction using a Sparse Selection Index

Genetics ◽  
2021 ◽  
Author(s):  
Marco Lopez-Cruz ◽  
Gustavo de los Campos
Keyword(s):  
Sample Size ◽  
Dna Sequences ◽  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Regularization Parameter ◽  
Selection Index ◽  
Prediction Method ◽  
Training Data ◽  
Breeding Value ◽  
Data Set

Abstract Genomic prediction uses DNA sequences and phenotypes to predict genetic values. In homogeneous populations, theory indicates that the accuracy of genomic prediction increases with sample size. However, differences in allele frequencies and in linkage disequilibrium patterns can lead to heterogeneity in SNP effects. In this context, calibrating genomic predictions using a large, potentially heterogeneous, training data set may not lead to optimal prediction accuracy. Some studies tried to address this sample size/homogeneity trade-off using training set optimization algorithms; however, this approach assumes that a single training data set is optimum for all individuals in the prediction set. Here, we propose an approach that identifies, for each individual in the prediction set, a subset from the training data (i.e., a set of support points) from which predictions are derived. The methodology that we propose is a Sparse Selection Index (SSI) that integrates Selection Index methodology with sparsity-inducing techniques commonly used for high-dimensional regression. The sparsity of the resulting index is controlled by a regularization parameter (λ); the G-BLUP (the prediction method most commonly used in plant and animal breeding) appears as a special case which happens when λ = 0. In this study, we present the methodology and demonstrate (using two wheat data sets with phenotypes collected in ten different environments) that the SSI can achieve significant (anywhere between 5-10%) gains in prediction accuracy relative to the G-BLUP.

Assessing Trade Show Functions and Performance: An Exploratory Study

1987 ◽  
Vol 51 (3) ◽  
pp. 87-94 ◽  
Author(s):  
Roger A. Kerin ◽  
William L. Cron
Keyword(s):  
Exploratory Study ◽  
Trade Show ◽  
Frequency Of Use ◽  
Marketing Tool ◽  
And Performance ◽  
Trade Shows

Though trade shows are an important marketing tool, as evidenced by their frequency of use and expenditure level, little research has examined this activity. The authors document the selling and non-selling roles of trade shows and identify marketing and trade show strategy-related variables that affect performance. Their study is a necessary first step in understanding how trade shows are used and identifying factors that should be considered in the management of this promotion medium.

scholarly journals Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens

2018 ◽  
Vol 63 (No. 6) ◽  
pp. 230-236 ◽  
Author(s):  
J.O. Rosa ◽  
G.C. Venturini ◽  
T.C.S. Chud ◽  
B.C. Pires ◽  
M.E. Buzanskas ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Fixed Effects ◽  
Egg Production ◽  
Genetic Parameters ◽  
Laying Hens ◽  
Reproductive Traits ◽  
A Posteriori ◽  
White Leghorn ◽  
Performance Traits ◽  
And Performance

This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inference. The data of 1894 animals from three generations of White Leghorn laying hens were analyzed for fertility (FERT), hatchability (HATC), and birth rate measurements at 60 weeks of age (BIRTH), body weight at 16 and 60 weeks of age (BW16 and BW60), age at sexual maturity (ASM), egg height/width ratio, weight, and density at 28, 36, and 40 weeks of age (RHW28, RHW36, RHW40, WEGG28, WEGG36, WEGG40, DENS28, DENS36, and DENS40, respectively) traits. The genetic parameters were estimated by the Bayesian inference method of multi-trait animal model. The model included the additive and residual genetic random effects and the fixed effects of generation. The a posteriori mean distributions of the heritability estimates for reproductive traits ranged from 0.14 ± 0.003 (HATC) to 0.22 ± 0.005 (FERT) and performance from 0.07 ± 0.001 (RHW28) to 0.42 ± 0.001 (WEGG40). The a posteriori mean distributions of the genetic correlation between reproductive traits ranged from 0.18 ± 0.026 (FERT and HACT) to 0.79 ± 0.007 (FERT and BIRTH) and those related to performance ranged from –0.49 ± 0.001 (WEGG36 and DENS36) to 0.75 ± 0.003 (DENS28 and DENS36). Reproductive and performance traits showed enough additive genetic variability to respond to selection, except for RHW28. This trait alone would have little impact on the genetic gain because environmental factors would have a higher impact compared to those from the additive genetic factors. Based on the results of this study, the selection applied on the BIRTH trait can be indicated to improve FERT and HATC of eggs. Furthermore, the use of the WEGG40 could improve egg quality in this population.

scholarly journals MoBPSweb: A web-based framework to simulate and compare breeding programs

2020 ◽  
Author(s):  
T. Pook ◽  
L. Büttgen ◽  
A. Ganesan ◽  
N.T. Ha ◽  
H. Simianer
Keyword(s):  
Selection Index ◽  
Relevant Information ◽  
Simulation Software ◽  
Breeding Program ◽  
Breeding Value ◽  
Long Term Effects ◽  
General Applicability ◽  
Breeding Programs ◽  
Web Based ◽  
Value Estimation

ABSTRACTSelective breeding is a continued element of both crop and livestock breeding since early prehistory. In this work, we are proposing a new web-based simulation framework (“MoBPSweb”) that is combining a unified language to describe breeding programs with the simulation software MoBPS, standing for ‘Modular Breeding Program Simulator’. Thereby, MoBPSweb is providing a flexible environment to enter, simulate, evaluate and compare breeding programs. Inputs can be provided via modules ranging from a Vis.js-based flash environment for “drawing” the breeding program to a variety of modules to provide phenotype information, economic parameters and other relevant information. Similarly, results of the simulation study can be extracted and compared to other scenarios via output modules (e.g. observed phenotypes, accuracy of breeding value estimation, inbreeding rates). Usability of the framework is showcased along a toy example of a dairy cattle breeding program on farm level, with comparing scenarios differing in implemented breeding value estimation, selection index and selection intensity being considered. Comparisons are made considering both short and long-term effects of the different scenarios in terms of genomic gains, rates of inbreeding and the accuracy of the breeding value estimation. Lastly, general applicability of the MoBPSweb framework and the general potential for simulation studies for genetics and in particular in breeding are discussed.

scholarly journals Breeding techniques to form final parent groups of sows (F1) with a high adaptive ability

2020 ◽  
Vol 58 (2) ◽  
pp. 185-198
Author(s):  
R. I. Sheiko ◽  
I. N. Kazarovets
Keyword(s):  
Pork Production ◽  
Individual Assessment ◽  
Innovative Methodology ◽  
Performance Traits ◽  
Parent Groups ◽  
Breeding Animal ◽  
And Performance ◽  
Adaptive Ability ◽  
Initial Forms ◽  
Breeding Techniques

Global experience related to increased pork production shows that breeding work has become an integral part of the technology, since it is impossible to further improve breeding and performance traits of animals without it and therefore the greater production of better quality pork. The paper presents the results of the breeding process arrangement for creation of F1 parental pig. Substantiation of breeding techniques when creating the final parental groups of sows (F1) with a high adaptive ability was based on complex methods to evaluate breeding animals, including traditional methods of domestic breeding and breeding indices. Evaluation of combination compatibility of breed-linear hybrids with the use of breeding indices during mating of parent initial forms allows to determine efficiency of using Yorkshire sows with Landrace boars, and Landrace sows with Yorkshire boars (final parental sows (F1)), which had significantly better reproductive indicators in comparison with BLW х BM genotype sows. Particularly efficient compatibility was recorded when selecting Yorkshire sows and Landrace boars. It was determined that in modern conditions an increase in the efficiency of breeding and pedigree work in pig breeding was based on the use of genetic methods, including: individual assessment of pedigree species according to the main breeding traits, evaluation of genome of each breeding animal, and use of breeding indices allowing to identify the true genetic potential of animals and predict performance traits of their offspring. The research relevance lies in using the innovative methodology for comprehensive assessment of combination compatibility of parental pairs, unified for pig husbandries and pig farms, which will make it possible to 10% accelerate the breeding process of forming the final parental forms of sows, ensure obtaining offspring with predictable reproductive, fattening and meat traits, and good adaptive ability.

scholarly journals Application of selection index method to combine two generations of estimated breeding value in pigs.

1989 ◽  
Vol 26 (3) ◽  
pp. 188-196
Author(s):  
Hiroshi TAKAHASHI ◽  
Takashige SUGIMOTO ◽  
Akio NIBE ◽  
Allan SCHINCKEL ◽  
Yasuo AMEMIYA
Keyword(s):  
Selection Index ◽  
Breeding Value ◽  
Index Method ◽  
Two Generations ◽  
Estimated Breeding Value

Using Learning Analytics to Enhance Student Learning in Online Courses Based on Quality Matters Standards

2016 ◽  
Vol 45 (2) ◽  
pp. 165-187 ◽  
Author(s):  
Florence Martin ◽  
Abdou Ndoye ◽  
Patricia Wilkins
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Online Course ◽  
Design Quality ◽  
Descriptive Data ◽  
Quality Matters ◽  
Frequency Of Use ◽  
And Performance ◽  
Enhance Student Learning

Quality Matters is recognized as a rigorous set of standards that guide the designer or instructor to design quality online courses. We explore how Quality Matters standards guide the identification and analysis of learning analytics data to monitor and improve online learning. Descriptive data were collected for frequency of use, time spent, and performance and analyzed to identify patterns and trends on how students interact with online course components based on the Quality Matters standards. Major findings of this article provide a framework and guidance for instructors on how data might be collected and analyzed to improve online learning effectiveness.

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