Genetic parameters of milk production traits and fatty acid contents in milk for Holstein cows in parity 1 – 3

The objective of this study was to estimate genetic parameters of milk, fat, and protein yields, fat and protein contents, somatic cell count, and 17 groups and individual milk fatty acid (FA) contents predicted by mid‐infrared spectrometry for first‐, second‐ and third‐parity Holstein cows. Edited data included records collected in the Walloon region of Belgium from 37 768 cows in parity 1, 22 566 cows in parity 2 and 8221 in parity 3. A total of 69 (23 traits for three parities) single‐trait random regression animal test‐day models were run. Approximate genetic correlations among traits were inferred from pairwise regressions among estimated breeding values of cow having observations. Heritability and genetic correlation estimates from this study reflected the origins of FA: de novo synthetized or originating from the diet and the body fat mobilization. Averaged daily heritabilities of FA contents in milk ranged between 0.18 and 0.47. Average daily genetic correlations (averaged across days in milk and parities) among groups and individual FA contents in milk ranged between 0.31 and 0.99. The genetic variability of FAs in combination with the moderate to high heritabilities indicated that FA contents in milk could be changed by genetic selection; however, desirable direction of change in these traits remains unclear and should be defined with respect to all issues of importance related to milk FA.     

Genetic relationships between calving and carcass traits for Charolais and Hereford cattle in Sweden

The objective of this study was to estimate genetic correlations between calving difficulty score and carcass traits in Charolais and Hereford cattle, treating first and later parity calvings as different traits. Genetic correlations between birth weight and carcass traits were also estimated. Field data on 59,182 Charolais and 27,051 Hereford calvings, and carcass traits of 5,260 Charolais and 1,232 Hereford bulls, were used in bivariate linear animal model analyses. Estimated heritabilities were moderate to high (0.22 to 0.50) for direct effects on birth weight, carcass weight, and (S)EUROP (European Community scale for carcass classification) grades for carcass fleshiness and fatness. Heritabilities of 0.07 to 0.18 were estimated for maternal effect on birth weight, and for direct and maternal effects on calving difficulty score at first parity. Lower heritabilities (0.01 to 0.05) were estimated for calving difficulty score at later parities. Carcass weight was positively genetically correlated (0.11 to 0.53) with both direct and maternal effects on birth weight and with direct effects on calving difficulty score. Carcass weight was, however, weakly or negatively (-0.70 to 0.07) correlated with maternal calving difficulty score. Higher carcass fatness grade was genetically associated with lower birth weight, and in most cases, also with less difficult calving. Genetic correlations with carcass fleshiness grade were highly variable. Moderately unfavorable correlations between carcass fleshiness grade and maternal calving difficulty score at first parity were estimated for both Charolais (0.42) and Hereford (0.54). This study found certain antagonistic genetic relationships between calving performance and carcass traits for both Charolais and Hereford cattle. Both direct and maternal calving performance, as well as carcass traits, should be included in the breeding goal and selected for in beef breeds.     

Direct and maternal genetic relationships of lamb live weight and carcass traits in Swedish sheep breeds

Possibilities to include carcass traits recorded at commercial slaughterhouses in the genetic evaluation of sheep in Sweden were investigated by estimating direct and maternal genetic parameters for 4‐month weight (4MW), carcass weight (CW), carcass fatness grade (FAT), and carcass fleshiness (FLESH) using multiple‐trait animal models. Data included two sets of breeds, the so‐called white breeds (Swedish landrace breeds, Texel, Dorset, Oxford Down, Suffolk, East Friesian Milk Sheep, and Swedish crossbred) and the Gotland breed. There were 30 625 observations on 4MW and 5062 observations on carcass traits for the white breeds. For the Gotland breed the numbers were 43 642 and 7893, respectively. The results showed that it is feasible to use field‐recorded carcass traits in the genetic evaluation. To consider the effects of selection and to utilize all information in an optimal way multiple trait animal models should be used. Direct and maternal heritabilities for 4MW and CW varied between 0.04 and 0.18 and heritabilities for FAT and FLESH between 0.21 and 0.29. Direct and maternal genetic correlations between 4MW and CW were high (0.61–0.97). Genetic correlations were higher between the weights and FLESH (0.11–0.62) than between the weights and FAT (?0.23 to 0.40). Genetic correlations between FAT and FLESH were moderate (0.38–0.45). Heritabilities for CW were higher if 4MW was included in the analyses and the effect of selection on 4MW was stronger for CW than for FAT or FLESH. The importance of maternal effects on carcass traits was discussed.     

Genetic parameters of pelt character,feed efficiency and size traits in Finnish blue fox (Vulpes lagopus)

Pelt character traits (size, quality, colour clarity, darkness) are important economic traits in blue fox breeding. Better feed efficiency (FE) is another economically important and new breeding goal for fur animals. The purpose of this study was to determine the correlations between pelt character traits, FE and size traits and to estimate genetic parameters for pelt character traits. Pelt size (pSI_cm) had a high positive genetic correlation with animal grading size (gSI), final body weight (BW_Fin), body length and daily gain (DG), and a moderate correlation with body condition score (BCS). Animal body length and BCS (describing fatness) were considered as genetically different traits. Genetic correlations between pelt quality and size traits were estimated without precision and did not differ from zero, but colour clarity (pCL) had a low antagonistic genetic correlation with FE. Pelt size and DG had a favourable genetic correlation with FE but a fairly high unfavourable genetic correlation with dry matter feed intake. The current emphasis on selection for larger animal and pelt size improves FE indirectly, but selection for larger pelt size favours fast‐growing and fat individuals and simultaneously increases feed intake. The detected genetic connections between FE, size, feed intake and pCL should be taken into account in the Finnish blue fox breeding programme.     

Estimates of non-genetic effects and genetic parameters for body measures and subjectively scored traits in Finnhorse trotters

This study examined non-genetic effects and genetic parameters of body measures and subjectively scored traits in the Finnhorse trotter population. The data was based on studbook inspections from 1971 to 2004 covering observations on 6381 horses. There were five body measures – height at withers, height at croup, circumference of girth, length of body and circumference of cannon bone – and six subjectively scored traits – character, body conformation, leg stances, quality of legs, hooves and movements – included in the analyses. Multivariate mixed models were applied with year–sex and age as fixed effects and animal as a random effect. The year–sex effect had a significant influence on body measures and scored traits. Age at judging had a significant influence on all traits but height at withers and body conformation. Heritability estimates were from 0.53 to 0.78 for body measures and 0.10 to 0.19 for scored traits. Genetic correlations between body measures were highly positive, from 0.75 to 0.98, whilst genetic correlations between scored traits varied between − 0.20 and 0.51. Genetic correlations between body measures and scored traits were mainly negative, from − 0.38 to 0.09. Our results indicate that additive genetic effects are relevant determinants for body measures of Finnhorse trotters. The scored traits were of low to moderate heritability and were relevantly influenced by environmental effects.     

Genetic analysis of fat‐to‐protein ratio,milk yield and somatic cell score of Holstein cows in Japan in the first three lactations by using a random regression model

We estimated the genetic parameters of fat‐to‐protein ratio (FPR) and the genetic correlations between FPR and milk yield or somatic cell score in the first three lactations in dairy cows. Data included 3 079 517 test‐day records of 201 138 Holstein cows in Japan from 2006 to 2011. Genetic parameters were estimated with a multiple‐trait random regression model in which the records within and between parities were treated as separate traits. The phenotypic values of FPR increased soon after parturition and peaked at 10 to 20 days in milk, then decreased slowly in mid‐ and late lactation. Heritability estimates for FPR yielded moderate values. Genetic correlations of FPR among parities were low in early lactation. Genetic correlations between FPR and milk yield were positive and low in early lactation, but only in the first lactation. Genetic correlations between FPR and somatic cell score were positive in early lactation and decreased to become negative in mid‐ to late lactation. By using these results for genetic evaluation it should be possible to improve energy balance in dairy cows.     

Genetic parameters for fur quality graded on live animals and dried pelts of American mink (Neovison vison)

Fur quality and skin size are integral qualities in the mink industry and are main determinants of sales price and subsequent income for mink fur producers. Parental animals of future generations are selected based on quality grading from live animals, but selection response is obtained from dried skins sold after pelting. In this study, we evaluated traits assessed during live grading and pelt traits examined on dried skins to determine correlation between live and pelt traits. Grading traits and body weight were measured during live animal grading for 9,539 Brown American mink, and pelt quality traits and skin size were evaluated on 8,385 dried mink skins after pelting. Data were sampled from 2 yearly production cycles. Genetic parameters were estimated using the REML method implemented in the DMU package. Heritabilities and proportions of litter variance were calculated from estimated variance components for all traits, and genetic and phenotypic correlations between all traits were estimated in a series of bivariate analyses. Heritability estimates for live grading traits ranged from 0.06 to 0.28, heritability estimates for pelt quality traits ranged from 0.20 to 0.30, and finally heritability estimates for body size traits ranged from 0.43 to 0.48. Skin size and body weight were regarded as different traits for the two sexes and were therefore analysed for each sex separately. Genetic correlations between grading traits exhibited a range of 0.30–0.99 and genetic correlations between pelt quality traits ranged from 0.38 to 0.86. Genetic correlations between quality, wool density and silky appearance evaluated during live animal grading and on dried skin after pelting were 0.74, 0.41 and 0.33, respectively. Skin size and body weight were negatively correlated with pelt quality traits and ranged from −0.55 to −0.25. Using standard selection index theory and combined information from both live grading and skin evaluation increase of reliability of selection ranged from 0.6% to 14%. Due to moderate genetic correlations between traits evaluated during live grading and on dried skins, and negative correlations between pelt quality traits and body size, we concluded that traits should be selected simultaneously.     

Genetic relationships between calving performance and beef production traits in Piemontese cattle

The aim of the study was to obtain estimates of genetic correlations between direct and maternal calving performance of heifers and cows and beef production traits in Piemontese cattle. Beef production traits were daily gain, live fleshiness, and bone thinness measured on 1,602 young bulls tested at a central station. Live fleshiness (six traits) and bone thinness were subjectively scored by classifiers using a nine-point linear grid. Data on calving performance were calving difficulty scores (five classes from unassisted to embryotomy) routinely recorded in the farms. Calving performance of heifers and cows were considered different traits. A total of 30,763 and 80,474 calving scores in first and later parities, respectively, were used to estimate covariance components with beef traits. Data were analyzed using bivariate linear animal models, including direct genetic effects for calving performance and beef traits and maternal genetic effects only for calving performance. Due to the nature of the data structure, which involved traits measured in different environments and on different animals, covariances were estimated mostly through pedigree information. Genetic correlations of daily gain were positive with direct calving performance (0.43 in heifers and 0.50 in cows) and negative with maternal calving performance (-0.23 and -0.28 for heifers and cows, respectively). Live fleshiness traits were moderately correlated with maternal calving performance in both parities, ranging from 0.06 to 0.33. Correlations between live fleshiness traits and direct calving performance were low to moderate and positive in the first parity, but trivial in later parities. Bone thinness was negatively correlated with direct calving performance (-0.17 and -0.38 in heifers and cows, respectively), but it was positively correlated to maternal calving performance (0.31 and 0.40). Estimated residual correlations were close to zero. Results indicate that, due to the existence of antagonistic relationships between the investigated traits, specific selection strategies need to be studied.     

Genetic parameters for mastitis incidence and its indicators based on somatic cell score for Holsteins in Hokkaido,Japan

The objectives of this study were to estimate the heritability of mastitis incidence and genetic correlations between the mastitis and the somatic cell score (SCS) statistics, and to compare the practicability between different models. We used test‐day records with the mastitis incidence and SCS collected from Holstein cows calving from 1988 to 2015 in Hokkaido, Japan. As indicators of mastitis, the average SCS (avSCS), the standard deviation of SCS (sdSCS), and the maximum SCS (maxSCS) were calculated using test‐day records up to the first 305 days in milk within a lactation. We compared a four‐trait repeatability animal model (MTRP) with a four‐trait multiple‐lactation animal model (MTML). The heritability for mastitis was equal to or lower than 0.05 in all the models. Genetic correlations between lactations with MTML within the same trait were positive and close to 1. With MTRP, the estimated genetic correlations of the mastitis incidence with avSCS, sdSCS, and maxSCS were 0.66, 0.79, and 0.82, respectively. A joint evaluation with SCS statistics is expected to give an extra reliability for mastitis because of high and positive genetic correlations among the traits.     

Genetic Correlations Between Beef Traits Measured on Young Performance Test Bulls and Daughter Milk Yield

In a breeding programme where young potential breeding bulls are reared on performance test stations, selection based on own results can be carried out before test inseminations. Both beef and milk production traits are included in the total merit index used for selection, and estimates of genetic and phenotypic parameters of these traits are therefore of interest for an optimal construction of such indices. Data on first lactation milk records from the field and beef records of potential dairy breeding bulls from the Danish performance test stations were analysed in bivariate animal-sire models using the AI-REML algorithm. Genetic correlations of 0.16, 0.25 and 0.43 between feed intake capacity and protein yield were obtained for Red Danish (RD), Danish Black and White (DBW) and Danish Jersey (DJ), respectively. These correlations were significantly different from zero for the two populations (DBW and DJ). Genetic correlations around zero between feed efficiency and protein yield were obtained for all three populations. Genetic correlations of 0.44, 0.19 and 0.47 between average daily gain and protein yield were obtained for RD, DBW and DJ, respectively. The genetic correlations between protein yield and muscle area was close to zero for DBW, while it was -0.31 for RD. Selection index calculations indicate that indices composed of different beef performance traits can be used as early predictors for milk yield. Selection on such an index could increase the breeding value of the young bulls for milk production traits by 0.8-2.0% of the population mean.     

Digestive Tract Anatomy of Norwegian Sheep: Difference Between Breeds

Data on 216,428 Danish Red, 798,152 Danish Friesian and 232,953 Danish Jersey cows were used to estimate phenotypic and genetic parameters for actual and production‐corrected survival traits and for milk production. Genetic effects of imported breeds were also estimated. Phenotypic trends in days in milk were similar for Danish Red and Danish Friesian, and showed influences of the milk quota system, whereas Danish Jersey showed a continuous downwards trend. Significant additive and non‐additive effects due to imported breeds were found. Heritabilities differed between breeds, ranging from 0.072 to 0.122 for actual continuous lifetime traits, and from 0.048 to 0.076 for production‐corrected continuous lifetime traits. Binary stayability traits showed lower heritability. Genetic correlations between milk production and actual or production‐corrected days in milk were 0.63 and 0.31 respectively. Genetic correlations between binary stayabilities and continuous lifetime traits were high (>0.78), which indicates that stayabilities can be used as early predictors of the lifetime traits.     

Breeding for better eye health in Finnish blue fox (Vulpes lagopus)

The frequency of eye infections in the Finnish blue fox population has increased during the past decade. Eye infection may incur economic losses to producers due to reduced selection intensity, but ethical aspects need to be considered as well because eye infection can be quite painful and reduce animal well‐being. The purpose of this study was to determine the potential for genetic selection against susceptibility to eye infection. The data were collected from 2076 blue foxes at the MTT fur animal research station. Genetic parameters were estimated using single‐ and multiple‐trait animal models. The heritability estimate for eye infection was analysed as a binary trait (EYE) and was moderate (0.24 ± 0.07). EYE had a moderate antagonistic genetic correlation (–0.49 ± 0.20) with grading density (thick underfur). The genetic correlation of EYE with grading size or body condition score was estimated without precision, but all size traits had a low antagonistic phenotypic correlation with EYE. Our results suggest that there is genetic variance in susceptibility to EYE, indicating that eye health can be improved through selection. The current recommendation is that the sick animals should be culled immediately. If more efficient selection is needed, the selection index and multiple‐trait animal models can be applied in breeding for better eye health.     

Genetic and phenotypic parameters of milk yield, milk composition and age at first kidding in Saanen goats from Mexico

A total of 4007 lactation records from 1520 Saanen goats kidding from 1999 to 2006 and obtained from 10 herds in Guanajuato, Mexico, were analyzed to estimate the heritabilities, repeatabilities, as well as genetic, environmental and phenotypic correlations for milk yield (MILK), fat yield (FAT), protein yield (PROT), fat content (%FAT), protein content (%PROT) and age at fist kidding (AFK). A five-trait repeatability model was used to estimate (co)variances for milk traits, and a four-trait animal model for first lactation records was used to estimate (co)variances involving AFK. For MILK, FAT, PROT, %FAT, %PROT and AFK, heritability estimates were 0.17 ± 0.04, 0.19 ± 0.05, 0.17 ± 0.04, 0.32 ± 0.06, 0.38 ± 0.07 and 0.31 ± 0.09, respectively. Repeatabilities for MILK, FAT, PROT, %FAT and %PROT were 0.43 ± 0.02, 0.42 ± 0.02, 0.42 ±0.02, 0.64 ± 0.02, and 0.63 ± 0.02, respectively. The genetic correlations between MILK and FAT, and between MILK and PROT, were high and positive (0.72 ± 0.08 and 0.87 ± 0.04, respectively). Genetic correlations between MILK and %FAT, between MILK and %PROT and between MILK and AFK, were − 0.24 ± 0.16, − 0.30 ± 0.15 and − 0.18 ± 0.23, respectively. Genetic correlations between AFK and FAT and between AFK and PROT were − 0.09 ± 0.24 and − 0.17 ± 0.25, respectively; and genetic correlations between AFK and %FAT and between AFK and %PROT were 0.29 ± 0.35 and 0.14 ± 0.27, respectively. Selection for milk traits is possible using a repeatability animal model. Selection for milk production traits would probably not increase AFK, but more precise estimates of the genetic correlations are required. Selection to lower AFK is possible. These (co)variance estimates would make it possible to predict the selection responses from different economic indices in order to maximize the economic responses for the local markets.     

Estimation of genetic parameters for milk and fertility traits within and between low,medium and high dairy production systems in Kenya to account for genotype-by-environment interaction

Dairy records from the Dairy Recording Service of Kenya were classified into low, medium and high production systems based on mean 305-day milk yield using the K-means clustering method. Milk and fertility records were then analysed to develop genetic evaluation systems accounting for genotype-by-environment interaction between the production systems. Data comprised 26,638 lactation yield, 3,505 fat yield, 9,235 age at first calving and 17,870 calving interval records from 12,631 cows which were descendants of 2,554 sires and 8,433 dams. An animal model was used to estimate variance components, genetic correlations and breeding values for the production systems. Variance components increased with production means, apart from genetic group variances, which decreased from the low to the high production system. Moderate heritabilities were estimated for milk traits (0.21–0.27) and fat traits (0.11–0.38). Low heritabilities were estimated for lactation length (0.04–0.10) and calving interval (0.03–0.06). Moderate heritabilities (0.25–0.26) were estimated for age at first calving, except under the high production system (0.05). Within production systems, lactation milk yield, 305-day milk yield and lactation length had high positive genetic correlations (0.52–0.96), while lactation milk yield and lactation length with age at first calving had negative genetic correlations. Milk yield and calving interval were positively correlated except under the low production system. The genetic correlations for lactation milk yield and 305-day milk yield between low and medium (0.48 ± 0.20 and 0.46 ± 0.21) and low and high production systems’ (0.74 ± 0.15 and 0.62 ± 0.17) were significantly lower than one. Milk yield in the low production system is, therefore, a genetically different trait. The low genetic correlations between the three production systems for most milk production and fertility traits suggested that sires should be selected based on progeny performance in the targeted production system.     

Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models

Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49 583 female calves born during 1998 and 2009 were considered in five age periods as days 1–30, 31–180, 181–365, 366–760 and full period (day 1–760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd‐year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82–0.95 and 0.61–0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31–180 and 181–365 (r_g = 0.59), 31–180 and 366–760 (r_g = 0.52), and 181–365 and 366–760 (r_g = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection.     

Estimates of environmental effects and genetic parameters for body measurements and weight in Brahman cattle raised in Mexico

A Derivative Free Restricted Maximum Likelihood (DFREML) algorithm was used with single trait and two traits animal models to estimate the variance and covariance components and thus, heritabilities and phenotypic, genetic and environmental correlations among nine different body measurements and weights of Brahman cattle raised in Mexico. The following measurements were considered: hip width, pin width, hip‐pin width, anterior height, posterior height, body length, thorax perimeter, scrotal circumference and weight. The analysis was based on a total of 1018 animals, born between 1992 and 1995, from 17 herds in the Mexican States of Chiapas, San Luis Potosi, Tabasco, Tamaulipas and Veracruz. The model included the following fixed effects: herd, year‐season of birth, sex, age of the animal and feed management. The only random effect was the direct additive genetic contribution of each animal. All fixed effects in the model were significant for all traits (p < 0.05). Estimated heritabilities for the traits were: hip width 0.57, pin width 0.32, hip‐pin width 0.41, anterior height 0.56, posterior height 0.54, body length 0.32, thorax perimeter 0.49, scrotal circumference 0.02 and weight 0.66. The magnitude of the heritabilities was medium to high, with the exception of scrotal circumference. The genetic correlations among all body measurements were consistently positive and high, ranging from 0.64 to 1.00. Although other measures showed higher genetic correlations with weight, thorax perimeter combines a high value (0.70) with ease and repeatability, making it a useful field measurement to estimate body weight when scales are not available.     

Genetic and phenotypic parameters and annual trends for milk production and fertility traits of the Sahiwal cattle in semi arid Kenya

Data comprising 7211 lactation records of 2894 cows were used to estimate genetic and phenotypic parameters for milk production (lactation milk yield, LMY and lactation length, LL) and fertility (calving interval, CI; number of services per conception, NSC and age at first calving, AFC) traits. Genetic, environmental and phenotypic trends were also estimated. Variance components were estimated using univariate, bivariate and trivariate animal models on based restricted maximum likelihood procedures. Univariate models were used for each trait, while bivariate models were used to estimate genetic and phenotypic correlations between milk production and fertility traits and between LMY, LL, CI and NSC within each lactation. Trivariate models were used in the analysis of LMY, LL, CI and NSC in the first three lactations. Heritability estimates from the univariate model were 0.16, 0.07, 0.03, 0.04 and 0.01 for LMY, LL, CI, AFC and NSC, respectively. The heritability estimates from trivariate analysis were higher for milk production traits than those from univariate analyses. Genetic correlations were high and undesirable between milk production and fertility traits, while phenotypic correlations were correspondingly low. Genetic trends were close to zero for all traits, while environmental and phenotypic trends fluctuated over the study period.     

Genetic correlations between body weight,scrotal circumference and visual evaluation scores in Bos indicus cattle

The objective was to estimate genetic correlations between body weight (BW), scrotal circumference and visual evaluation scores of body conformation measured at standard ages in Guzerat cattle. All measurements were performed at 205 (weaning age), 365, 450 and 550 days of age; for BW, two additional measurements (at birth and 120 days of age) were realized. The data utilized in this study were retrieved from a database of the Brazilian Association of Zebu Breeders that contained information of registered Guzerat animals born between 1970 and 2013. Genetic parameters were estimated in bi‐trait analyses by using Bayesian inference. Genetic correlations between BW at 205 and 450 days of age with other traits were high and positive, whereas the correlations between visual evaluation scores with other traits were moderate. Based on correlations herein obtained, we conclude that selection based on BW results in increased visual scores and scrotal circumference, leading to improvements in productive performance and animals with best body conformation.     

Stereotypic behaviour in farm mink (Neovison vison) can be reduced by selection

In this article we present the first estimation of genetic variation of stereotypic behaviour (SB). Stereotypic behaviour is defined as an unvarying behaviour without any specific goal or function repeated at least five times. All types of SB were included in the analyses. Altogether 1484 adult mink females of the brown colour type were assessed for behaviour traits: SB, active or inactive behaviour, staying in nest box. Genetic correlations were based on estimates of additive genetic (co)variances obtained from a trivariate linear animal model fitted to behaviour traits, body weight and litter size. The SB has an intermediate genetic variation ( h ²∼0.3) and divergent selection for SB confirmed that the frequency of SB can be altered by selection. The results confirmed the hypotheses of negative genetic correlation between SB and body weight and negative genetic correlation between body weight and litter size. The hypotheses of positive correlation between SB and active behaviour and SB and litter size were not confirmed. Consequences of selection for reduced SB can be changes in other behaviour traits, body weight and litter size, depending on the genetic correlation between the traits.     

Genetic relationships between length of productive life and lifetime production efficiency in a commercial swine herd in Northern Thailand

Genetic parameters and trends for length of productive life (LPL), lifetime number of piglets born alive per year (LBAY), lifetime number of piglets weaned per year (LPWY), lifetime litter birth weight per year (LBWY) and lifetime litter weaning weight per year (LWWY) were estimated using phenotypic records of 3085 sows collected from 1989 to 2013 in a commercial swine farm in Northern Thailand. The five‐trait animal model included the fixed effects of first farrowing year‐season, breed group and age at first farrowing. Random effects were animal and residual. Heritability estimates ranged from 0.04 ± 0.02 for LBWY to 0.17 ± 0.04 for LPL. Genetic correlations ranged from 0.66 ± 0.14 between LPL and LBAY to 0.95 ± 0.02 between LPWY and LWWY. Spearman rank correlations among estimated breeding values for LPL and lifetime production efficiency traits tended to be higher for boars than for sows. Sire genetic trends were negative and significant for all traits, except for LPWY. Dam genetic trends were positive and significant for all traits. Sow genetic trends were mostly positive and significant only for LPWY and LBWY. Improvement of LPL and lifetime production efficiency traits will require these traits to be included in the selection indexes used to choose replacement boars and gilts in this population.