scholarly journals Identifying early indicator traits for sow longevity using a linear-threshold model in Thai Large White and Landrace females

2021 ◽  
Vol 34 (1) ◽  
pp. 20-25
Author(s):  
Suppasit Plaengkaeo ◽  
Monchai Duangjinda ◽  
Kenneth J. Stalder
Keyword(s):  
Litter Size ◽  
Genetic Parameters ◽  
Threshold Model ◽  
Genetic Associations ◽  
Genetic Trait ◽  
Large White ◽  
Linear Threshold ◽  
Sow Longevity ◽  
Linear Threshold Model ◽  
Indicator Traits

Objective: The objective of the study was to investigate the possibility of utilizing an early litter size trait as an indirect selection trait for longevity and to estimate genetic parameters between sow stayability and litter size at different parities using a linear-threshold model for longevity in Thai Large White (LW) and Landrace (LR) populations.Methods: The data included litter size at first, second, and third parities (NBA1, NBA2, and NBA3) and sow stayability from first to fourth farrowings (STAY14). The data was obtained from 10,794 LR and 9,475 LW sows. Genetic parameters were estimated using the multipletrait animal model. A linear-threshold model was used in which NBA1, NBA2, and NBA3 were continuous traits, while STAY14 was considered a binary trait.Results: Heritabilities for litter size were low and ranged from 0.01 to 0.06 for both LR and LW breeds. Similarly, heritabilities for stayability were low for both breeds. Genetic associations between litter size and stayability ranged from 0.43 to 0.65 for LR populations and 0.12 to 0.55 for LW populations. The genetic correlation between NBA1 and STAY14 was moderate and in a favorable direction for both LR and LW breeds (0.65 and 0.55, respectively).Conclusion: A linear-threshold model could be utilized to analyze litter size and sow stayability traits. Furthermore, selection for litter size at first parity, which was the genetic trait correlated with longevity, is possible when one attempts to improve lifetime productivity in Thai swine populations.

scholarly journals Linear and linear-threshold model for genetic parameters for SEUROP carcass traits in Czech beef cattle

2011 ◽  
Vol 56 (No. 9) ◽  
pp. 414-426 ◽  
Author(s):  
Z. Veselá ◽  
L. Vostrý ◽  
P. Šafus
Keyword(s):  
Beef Cattle ◽  
Linear Model ◽  
Legendre Polynomial ◽  
Model Equation ◽  
Genetic Parameters ◽  
Threshold Model ◽  
Genetic Parameter ◽  
Carcass Traits ◽  
Linear Threshold ◽  
Linear Threshold Model

The objective of this study was to estimate genetic parameters for the results of classifying of carcass traits by the SEUROP method in beef cattle in the Czech Republic using linear and linear-threshold models. Genetic parameters were calculated and evaluated in a set of 4276 animals of eleven beef breeds and crosses with dairy and dual-purpose breeds (Aberdeen Angus – 1376, Hereford – 994, Simmental – 651, Charolais – 524, Piemontese – 185, Galloway – 162, Blonde d’Aquitaine – 147, Limousine – 106, Highland – 53, Gasconne – 44, Belgian Blue – 34) in 2005–2008. Aberdeen Angus, Hereford, Charolais and beef Simmental were the most numerous breeds. Fixed effect of a classifier, fixed regression on age at slaughter by means of Legendre polynomial of the second degree separately for the each breed and sex and fixed regression on heterosis coefficient were included in a model equation. Genetic parameters were estimated by a multi-trait animal model using a linear model and a linear-threshold model in which carcass weight (CW) was considered as the linear trait and carcass conformation (CC) and carcass fatness (CF) grading as threshold traits. The heritability coefficient for CW differed only moderately according to the method of the genetic parameter estimation (0.295 in linear model and 0.306 in linear-threshold model). The heritability coefficient for CC was 0.187 in linear model and 0.237 in linear-threshold model. The heritability coefficient for CF grading was 0.089 in linear model and 0.146 in linear-threshold model. Genetic correlation between CW and CC was high (0.823 in linear model and 0.959 in linear-threshold model), the correlation between CW and CF was intermediate (0.332 and 0.328, respectively) and it was low between CF and CC (0.071 and 0.053). If CW was included in the model equation as fixed regression using Legendre polynomial, lower heritability coefficients for CC (0.077 and 0.078) and CF (0.086 and 0.123) were calculated and the correlation between CC and CF was negative (–0.430 and –0.429).

Genetic parameters and phenotypic trends in the mean and variability of number of stillborn piglets and changes in their relationships with litter size and gestation length

2013 ◽  
Vol 53 (5) ◽  
pp. 395 ◽  
Author(s):  
Craig R. G. Lewis ◽  
Susanne Hermesch
Keyword(s):  
Genetic Parameters ◽  
Gestation Length ◽  
Genetic Associations ◽  
Large White ◽  
Factors Affecting ◽  
Breed Differences ◽  
Trends Over Time ◽  
The Mean ◽  
Using Data ◽  
Over Time

This study examined changes in genetic and phenotypic factors affecting stillborn piglets (SB). Over 15 years, 76 851 litter records were available from Large White (LW), Landrace (LR) and Duroc (DU) sows to investigate SB. The analyses focussed on trends over time in SB and the changes in the number of SB per litter, in factors associated with SB and in genetic parameters for SB. Breed differences were identified with DU producing more SB than the white breeds (mean of 1.46 ± 0.02 vs 1.11 ± 0.01 and 1.07 ± 0.01). However, maximum differences between levels of each factor were 0.73 and 0.65 SB for parity and herd, respectively. Over the 15 years studied, SB had increased by 0.2 piglets accompanied by an increase in the total numbers of piglets born per litter (TB) of ~0.5 piglets. This increase in SB was driven by higher occurrence of more than two SB within a single litter. The effect of TB on SB changed over time with solutions of 0.127 ± 0.002 and 0.150 ± 0.002 SB/TB in 1996 and 2010, respectively. Heritability estimates for SB ranged from 0.06 ± 0.01 to 0.09 ± 0.01 for alternative models and time periods. The unfavourable genetic correlation between SB and TB of 0.46 ± 0.03 based on all data available was slightly lower using only data from the first 5 years (0.38 ± 0.07) versus using data from the last 5 years (0.46 ± 0.06). However, this increase in phenotypic and genetic associations between SB and TB over time may be larger in populations that have observed a larger increase in TB.

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