Genotype by environment interaction in response to cold stress in a composite beef cattle breed

Extreme weather conditions such as cold stress influence the productivity and survivability of beef cattle raised on pasture. The objective of this study was to identify and evaluate the extent of the impact of genotype by environment interaction due to cold stress on birth weight (BW) and weaning weight (WW) in a composite beef cattle population. The effect of cold stress was modelled as the accumulation of total cold load (TCL) calculated using the Comprehensive Climate Index units, considering three TCL classes defined based on temperature: less than −5°C (TCL5), −15°C (TCL15) and −25°C (TCL25). A total of 4221 and 4217 records for BW and WW, respectively, were used from a composite beef cattle population (50% Red Angus, 25% Charolais and 25% Tarentaise) between 2002 and 2015. For both BW and WW, a univariate model (ignoring cold stress) and a reaction norm model were implemented. As cold load increased, the direct heritability slightly increased in both BW and WW for TCL5 class; however, this heritability remained consistent across the cold load of TCL25 class. In contrast, the maternal heritability of BW was constant with cold load increase in all TCL classes, although a slight increase of maternal heritability was observed for TCL5 and TCL15. The direct and maternal genetic correlation for BW and maternal genetic correlation for WW across different cold loads between all TCL classes were high (r > 0.99), whereas the lowest direct genetic correlations observed for WW were 0.88 for TCL5 and 0.85 for TCL15. The Spearman rank correlation between the estimated breeding value of top bulls (n = 79) using univariate and reaction norm models across TCL classes showed some re-ranking in direct and maternal effects for both BW and WW particularly for TCL5 and TCL15. In general, cold stress did not have a big impact on direct and maternal genetic effects of BW and WW.     

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

The objectives of the present study were: (1) to evaluate the importance of genotype×production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire×contemporary group interaction (S×CG) to model G×E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S×CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype×production environment interaction. Furthermore, the model including S×CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S×CG. Thus, the model that included S×CG can therefore be considered the best model on the basis of these criteria. The genotype×production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S×CG in the model is a feasible and plausible alternative to model the effects of G×E in the genetic evaluations.     

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re-ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.     

(Co)Variance components and genetic parameter estimates for growth traits in Moghani sheep

Genetic parameters were estimated for birth weight (BW), weaning weight (WW), yearling weight (YW), average daily gain from birth to weaning (ADG1) and average daily gain from weaning to yearling (ADG2) in Moghani sheep. Maximum number of data was 4237 at birth, but only 1389 records at yearling were investigated. The data was collected from 1995 to 2007 at the Breeding Station of Moghani sheep in Jafarabad, Moghan, Iran. (Co)Variance components and genetic parameters were estimated with different models which including direct effects, with and without maternal additive genetic effects as well as maternal permanent environmental effects using restricted maximum likelihood (REML) method. The most appropriate model for each trait was determined based on likelihood ratio tests and Akaike's Information Criterion (AIC). Maternal effects were important only for pre-weaning traits. Direct heritability estimates for BW, ADG1, WW, ADG2 and YW were 0.07, 0.08, 0.09, 0.09 and 0.17, respectively. Fractions of variance due to maternal permanent environmental effects on phenotypic variance were 0.08 for ADG1. Maternal heritability estimates for BW and WW were 0.18 and 0.06, respectively. Multivariate analysis was performed using the most appropriate models obtained in univariate analysis. Direct genetic correlations among studied traits were positive and ranged from 0.37 for BW–ADG2 to 0.85 for ADG1–YW. Maternal genetic correlation estimate between BW and WW was 0.33. Phenotypic and environmental correlation estimates were generally lower than those of genetic correlation. Low direct heritability estimates imply that mass selection for these traits results in slow genetic gain.     

Genetic analysis of the temperament of Nellore cattle using linear and threshold models

Temperament is an important trait for the management and welfare of animals and for reducing accidents involving people who work with cattle. The present study aimed to estimate the genetic parameters related to the temperament score (T) and weaning weight (WW) of Nellore cattle, reared in a beef cattle breeding program in Brazil. Data were analyzed using two different two-trait statistical models, both considering WW and T: (1) a linear-linear model in which variance components (VCs) were estimated using restricted maximum likelihood; and (2) a linear-threshold model in which VCs were estimated via Bayesian inference. WW was included in the analyses of T to minimize any possible effects of sequential selection and to allow for estimation of the genetic correlation between these two traits. The heritability estimates for T were 0.21±0.003 (model 1) and 0.26 (model 2, with a 95% credibility interval (95% CI) of 0.21 to 0.32). The estimated genetic correlations between WW and T were of a moderate magnitude (−0.33±0.01 (model 1) and −0.34 (95% CI: −0.40, −0.28, model 2). The genetic correlations between the estimated breeding values (EBVs) obtained for the animals based on the two models were high (>0.92). The use of different models had little influence on the classification of animals based on EBVs or the accuracy of the EBVs.     

Development of equations to predict carcass weight,empty body gain,and retained energy of Zebu beef cattle

The accurate supply of energy is essential to optimize livestock productivity and profitability. Furthermore, replacing empty BW gain (EBG) with carcass gain (CG) might be a suitable alternative to estimate the retained energy (RE) of beef cattle. Thus, this multi-analysis study was conducted aiming to estimate and validate new equations to predict carcass weight (CW), EBG, and RE of Zebu, beef crossbred, and dairy crossbred. A database composed by 1 112 animals encompassing bulls, steers, heifers of different genetic groups (Zebu, beef crossbred, and dairy crossbred), and two types of slaughter plants (commercial and experimental) was used for generating the new CW equation. For the development of the EBG and RE equations, a database of 636 observations composed of bulls, steers, and heifers of different genetic groups (Zebu, beef crossbred, and dairy crossbred) was assembled. The validation of new equations was performed using independent databases composed by 137 observations (80 for CW and 57 for EBG and RE). The new approaches for EBG and RE validation also included data from our research group studies (Inside) and independent data from literature publications (Outside). Furthermore, the new RE equation was compared to the current model devised by the nutritional requirements, diet formulation, and performance prediction of Zebu and crossbred cattle (BR-CORTE, 2016). Validation analyses were performed by using the Model Evaluation System (MES; 3.1.13, College Station, US). The CW was accurately estimated by the new equation when using both commercial and experimental data. Also, the equations developed in this study accurately estimated EBG and RE using both inside and outside data. In conclusion, equations proposed in this study accurately and precisely estimated CW, EBG, and RE of Zebu beef cattle that composed validation data set. Therefore, we suggest the following equations to estimate CW, EBG, and RE of Zebu cattle: CW, kg = − 11.0_±1.56 + P + ((0.609_±0.005 + G + B) × SBW); EBG (kg) = 0.044_±0.017 + 1.47_±0.026 × CG; RE (MJ/d) = 4.184 × (0.082_±0.002 × EQEBW^0.75 × CG^0.777±0.039), where P = slaughter plant effect, if commercial = − 10.98, if experimental = 0; G = gender effect, if steer = 0, if bull = 0.008169 and if heifer = − 0.00612; B = genotype effect, if Zebu = 0, if dairy crossbreds = − 0.03301 and if beef crossbreds = − 0.01595; SBW = shrunk BW; CG = carcass gain; EQEBW = equivalent empty BW.     

Correlated genetic trends for production and welfare traits in a mouse population divergently selected for birth weight environmental variability

The objective of this work was to study the changes that, selecting for environmental variability of birth weight (BW), could bring to other interesting traits in livestock such as: survivability at weaning (SW), litter size (LS) and weaning weight (WW), their variability assessed from standard deviations of LS, standard deviation of WW (SDWW) and also the total litter weight at birth (TLBW) and total litter weight at weaning. Data were registered after eight generations of a divergent selection experiment for BW environmental variability in mice. Genetic parameters and phenotypic and genetic evolution were assessed using linear homoscedastic and heteroscedastic models in which the traits were attributed to the female, except BW and WW that were in some models also attributed to the pup. Genetic correlation between the trait and variability levels was −0.81 for LS and −0.33 for WW. Clear divergent phenotypic trends were observed between lines for LS, WW and SDWW. Although animals were heavier in the high line, TLBW and at weaning was greater in the low line. Despite the negative genetic correlation that was obtained, SDWW was also higher in the high line. Heritabilities were 0.21 and 0.06, respectively, for LS and SW. Both phenotypic and genetic trends showed clear superiority of the low line over the high line for these traits, but inferior for WW. Heteroscedastic model performed similar to the homoscedastic model when there was enough information. Considering LS and survival, the low line was preferred from a welfare point of view, but its superiority from the productivity perspective was not clear. Robustness seemed higher as shown by a low variation and having a benefit to the animal welfare, but this still remains unclear. It was concluded that low variation benefits the welfare of animals.     

Heritability estimates and genetic correlations for body weight and scrotal circumference adjusted to 12 and 18 months of age for male Nellore cattle

Heritability estimates and genetic correlations were obtained for body weight and scrotal circumference, adjusted, respectively, to 12 (BW12 and SC12) and 18 (BW18 and SC18) months of age, for 10 742 male Nellore cattle. The adjustments to SC12 and SC18 were made using a nonlinear logistic function, while BW12 and BW18 were obtained by linear adjustment. The contemporary groups (CGs) were defined from animals born on the same farm, in the same year and birth season. The mean heritability estimates obtained using the restricted maximum likelihood method in bi-trait analysis were 0.25, 0.25, 0.29 and 0.42 for BW12, BW18, SC12 and SC18, respectively. The genetic correlations were 0.30 ± 0.11, 0.21 ± 0.13, 0.21 ± 0.11, -0.08 ± 0.15, 0.16 ± 0.12 and 0.89 ± 0.04 between the traits BW12 and BW18; BW12 and SC12; BW12 and SC18; BW18 and SC12; BW18 and SC18; and SC12 and SC18. The heritability for SC18 was considerably greater than for SC12, suggesting that this should be included as a selection criterion. The genetic correlation between BW18 and SC12 was close to zero, indicating that these traits did not influence each other. The contrary occurred between SC12 and SC18, indicating that selection using one of these could alter the other. Because of the mean magnitudes of heritabilities in the various measurements of weight and scrotal perimeter, it is suggested that the practice of individual selection for these traits is possible.     

ENVIRONMENTAL AND GENETIC CONTROL OF BRAIN AND SONG STRUCTURE IN THE ZEBRA FINCH

Birdsong is a classic example of a learned trait with cultural inheritance, with selection acting on trait expression. To understand how song responds to selection, it is vital to determine the extent to which variation in song learning and neuroanatomy is attributable to genetic variation, environmental conditions, or their interactions. Using a partial cross fostering design with an experimental stressor, we quantified the heritability of song structure and key brain nuclei in the song control system of the zebra finch and the genotype‐by‐environment (G × E) interactions. Neuroanatomy and song structure both showed low levels of heritability and are unlikely to be under selection as indicators of genetic quality. HVC, in particular, was almost entirely under environmental control. G × E interaction was important for brain development and may provide a mechanism by which additive genetic variation is maintained, which in turn may promote sexual selection through female choice. Our study suggests that selection may act on the genes determining vocal learning, rather than directly on the underlying neuroanatomy, and emphasizes the fundamental importance of environmental conditions for vocal learning and neural development in songbirds.     

Breeding for robustness: investigating the genotype‐by‐environment interaction and micro‐environmental sensitivity of Genetically Improved Farmed Tilapia (Oreochromis niloticus)

Robustness has become a highly desirable breeding goal in the globalized agricultural market. Both genotype‐by‐environment interaction (G × E) and micro‐environmental sensitivity are important robustness components of aquaculture production, in which breeding stock is often disseminated to different environments. The objectives of this study were (i) to quantify the degree of G × E by assessing the growth performance of Genetically Improved Farmed Tilapia (GIFT) across three countries (Malaysia, India and China) and (ii) to quantify the genetic heterogeneity of environmental variance for body weight at harvest (BW) in GIFT as a measure of micro‐environmental sensitivity. Selection for BW was carried out for 13 generations in Malaysia. Subsets of 60 full‐sib families from Malaysia were sent to China and India after five and nine generations respectively. First, a multi‐trait animal model was used to analyse the BW in different countries as different traits. The results indicate a strong G × E. Second, a genetically structured environmental variance model, implemented using Bayesian inference, was used to analyse micro‐environmental sensitivity of BW in each country. The analysis revealed the presence of genetic heterogeneity of both BW and its environmental variance in all environments. The presence of genetic variation in residual variance of BW implies that the residual variance can be modified by selection. Incorporating both G × E and micro‐environmental sensitivity information may help in selecting robust genotypes with high performance across environments and resilience to environmental fluctuations.     

Genetic parameter estimates for pre-weaning performance and reproduction traits in Markhoz goats

Genetic parameters for growth, mortality and reproductive performances of Markhoz goats were estimated from data collected during 1993–2010 at Markhoz goat Performance Testing Station in Sanandaj, Iran. For kid performance traits 3763 records were available for birth weight (BW), 2931 for weaning weight (WW), average daily gain (ADG) and Kleiber ratio (KR) (approximated as ADW/WW^0.75) and 3032 for pre-weaning mortality (PWM). For doe reproductive performance traits there were 2920 records available for litter size at birth (LSB), litter size at weaning (LSW), total litter weight at birth (TLWB) and litter mean weight per kid born (LMWKB), and 2182 for total litter weight at weaned (TLWW) and litter mean weight per kid weaned (LMWKW). Genetic parameters were estimated with univariate and bivariate models using restricted maximum likelihood (REML) procedures. Random effects were explored by fitting additive direct genetic effects, maternal additive genetic effects, maternal permanent environmental effects, the covariance between direct and maternal genetic effects, and common litter effects in different models for pre-weaning traits of kids. Also, in addition to an animal model, sire and threshold models, using a logit link function, were used for analyses of PWM. Models for LSB, LSW, TLWB, TLWW, LMWKB, and LMWKW included direct additive genetic effects, permanent environmental effects due to the animal as well as service sire effects. Estimated direct heritabilities were moderate for pre-weaning traits (0.22 for BW, 0.16 for WW, 0.21 for ADG, and 0.27 for KR and 0.29 for PWM), and low for reproduction traits (0.01 for LSB, 0.01 for LSW, 0.02 for TLWB, 0.03 for TLWW, 0.07 for LMWKB, and 0.06 for LMWKW). The estimates for the maternal additive genetic variance ratios were lower than direct heritability for BW (0.07) and KR (0.04). The estimate for the maternal permanent environmental variance ratios (c²) varied from 0.01 for KR to 0.07 for WW and ADG. The magnitude of common litter variance ratios (l²) was more substantial for BW (0.46) than the PWM (0.19) and KR (0.16). The estimate for the permanent environmental variance due to the animal (c²) ranged from 0.03 for LMWKB to 0.07 for TLWB and LMWKW, whereas service sire effects (s²) ranged from 0.02 to 0.04. The correlation between direct and maternal genetic effects were negative and high for BW (?0.51) and KR (?0.62). The genetic correlations between pre-weaning growth traits were positive and moderate to strong, as were genetic correlations between reproductive traits. Between BW and PWM the correlation was ?0.35. Phenotypic and environmental correlations for all traits were generally lower than genetic correlations.     

Genetic correlations between mature cow weight and productive and reproductive traits in Nellore cattle

We investigated genetic associations between mature cow weight (MW) and weaning weight (WW), yearling weight (YW), weight gain from birth to weaning (GBW), weight gain from weaning to yearling (GWY), weaning hip height (WHH), yearling hip height (YHH), scrotal circumference (SC), and age at first calving (AFC). Data from 127,104 Nellore animals born between 1993 and 2006, belonging to Agropecuária Jacarezinho Ltda., were analyzed. (Co)variance components were obtained by the restricted maximum likelihood method, applying an animal model in a multi-traits analysis. The model included direct genetic and residual effects as random effects, the fixed effects of contemporary group, and the linear and quadratic effects of animal age at recording (except for AFC, GBW, and GWY) and age of cow at calving as covariates (except for MW). The numbers of days from birth to weaning and from weaning to yearling were included as covariates for GBW and GWY, respectively. Estimated direct heritabilities were 0.43 ± 0.02 (MW), 0.33 ± 0.01 (WW), 0.36 ± 0.01 (YW), 0.28 ± 0.02 (GBW), 0.31 ± 0.01 (GWY), 0.44 ± 0.02 (WHH), 0.48 ± 0.02 (YHH), 0.44 ± 0.01 (SC), and 0.16 ± 0.03 (AFC). Genetic correlations between MW and productive traits were positive and of medium to high magnitude (ranging from 0.47 ± 0.03 to 0.71 ± 0.01). A positive and low genetic correlation was observed between MW and SC (0.24 ± 0.04). A negative genetic correlation (-0.19 ± 0.03) was estimated between MW and AFC. Selection to increase weight or weight gains at any age, as well as hip height, will change MW in the same direction. Selection for higher SC may lead to a long-term increase in MW. The AFC can be included in selection indices to improve the reproductive performance of beef cattle without significant changes in MW.     

Multiple-breed reaction norm animal model accounting for robustness and heteroskedastic in a Nelore–Angus crossed population

Our objective was to genetically characterize post-weaning weight gain (PWG), over a 345-day period after weaning, of Brangus-Ibagé (Nelore×Angus) cattle. Records (n=4016) were from the foundation herd of the Embrapa South Livestock Center. A Bayesian approach was used to assess genotype by environment (G×E) interaction and to identify a suitable model for the estimation of genetic parameters and use in genetic evaluation. A robust and heteroscedastic reaction norm multiple-breed animal model was proposed. The model accounted for heterogeneity of residual variance associated with effects of breed, heterozygosity, sex and contemporary group; and was robust with respect to outliers. Additive genetic effects were modeled for the intercept and slope of a reaction norm to changes in the environmental gradient. Inference was based on Monte Carlo Markov Chain of 110 000 cycles, after 10 000 cycles of burn-in. Bayesian model choice criteria indicated the proposed model was superior to simpler sub-models that did not account for G×E interaction, multiple-breed structure, robustness and heteroscedasticity. We conclude that, for the Brangus-Ibagé population, these factors should be jointly accounted for in genetic evaluation of PWG. Heritability estimates increased proportionally with improvement in the environmental conditions gradient. Therefore, an increased proportion of differences in performance among animals were explained by genetic factors rather than environmental factors as rearing conditions improved. As a consequence response to selection may be increased in favorable environments.     

Estimates of genetic parameters and genetic trends for growth,reproduction, milk production and milk composition traits of Awassi sheep

Genetic parameters and genetic trends for growth, reproduction, milk production and composition traits were estimated for Syrian (S) and Turkish (T) Awassi sheep and their crosses maintained at the International Center for Agricultural Research in the Dry Areas Tal Hadya station, Aleppo, Syria (now in Terbol station in Lebanon). The data were spread over 9 years. The individual breed additive effects of T were positive and significant (P<0.05) for birth weight (BW). However, the values for weaning weight (WW) and pre-weaning weight gain (WG) were negative, even though they were significant (P<0.05). These estimates were positive and significant (P<0.05) for all reproduction and milk traits, except for litter weight at birth (LWB). The additive contributions of T were 60.72±0.94 days, 1.643±0.359 kg, 13.09±0.89 days, 16.13±0.89 kg, 1.12±0.44 kg, 0.71±0.26 kg, 2.80±0.72 kg and 0.83±0.32 kg for lambing interval (LI), litter weight at weaning (LWW), lactation length, milk yield, fat yield, protein yield, total solids yield and lactose yield, respectively. The heterosis effects, both individual and maternal, were non-significant (P>0.05) for most growth traits. Crossing of T with S, however, resulted in desirable and significant (P<0.05) individual heterosis effects for all the reproduction, milk production and constituent yields. The heritability (h²) estimates, both direct and maternal, were low for BW, WW, WG and all reproductive traits indicating major influence of environmental factors, whereas milk yield and composition had medium values. Birth weight had moderate genetic correlation with WW and WG. The genetic correlation between WW and WG was high (0.724±0.951). Lambing interval had large negative genetic correlation with LWB and LWW. However, LI had medium significant correlations with all the milk production and composition traits. Larger litter weights at birth had high and negative influence on milk yield of the dam and its constituents. Genetic changes over years for all traits were non-significant. The lack of genetic change in the studied traits calls for systematic and organized selection scheme.     

Effects of Exogenous Melatonin and Tryptophan on Fecal Shedding of <Emphasis Type="Italic">E. Coli</Emphasis> O157:H7 in Cattle

Fecal prevalence of Escherichia coli O157 in ruminants is highest in the summer decreasing to very low levels in the winter. We hypothesize that this seasonal variation is a result of physiological responses within the host animal to changing day-length. To determine the effects of melatonin (MEL) on fecal shedding of E. coli O157:H7 in cattle, eight crossbred beef steers identified as shedding E. coli O157:H7, were allotted to treatment: control or MEL (0.5 mg/kg body weight (BW); 1×) administered orally daily for 7 days. After a 5-day period of no treatment, a second MEL dose (5.0 mg/kg BW; 10×) was administered daily for 4 days. Fecal samples were collected daily for qualification of E. coli O157:H7. No differences (P > 0.10) were observed in the percentage of E. coli O157:H7 positive fecal samples in steers receiving the 1× MEL dose, however the 10× dose decreased (P = 0.05) the percentage of fecal samples E. coli O157:H7 positive. Serum MEL concentrations were higher in the 1×, but not 10×, treated animals compared to control animals. Although it is difficult to explain, this may be a result of decreasing day-length increasing serum melatonin concentrations that may have masked any treatment effect on serum melatonin. In a second similar experiment, a second group of cattle (heifers and steers) were administered tryptophan (TRP) over a 17-day experimental period (5 g/head/day for 10 days followed by 10 g/head/day for 7 days). Tryptophan had no effect (P > 0.20) on the percentage of fecal samples positive for E. coli O157. Serum TRP (P < 0.05), but not MEL (P > 0.20), concentrations were elevated in TRP-treated animals. The decrease in the number of positive fecal samples observed in the first experiment, may be related to gastrointestinal MEL, affected by the 10×, but not 1× MEL dose.     

Genetic parameters estimation for preweaning traits and their relationship with reproductive,productive and morphological traits in alpaca

The aim of this study was to estimate the genetic parameters for preweaning traits and their relationship with reproductive, productive and morphological traits in alpacas. The data were collected from 2001 to 2015 in the Pacomarca experimental farm. The data set contained data from 4330 females and 3788 males corresponding to 6396 and 1722 animals for Huacaya and Suri variants, respectively. The number of records for Huacaya and Suri variants were 5494 and 1461 for birth weight (BW), 5429 and 1431 for birth withers height (BH), 3320 and 896 for both weaning weight (WW) and average daily gain (DG) from birth to weaning, 3317 and 896 for weaning withers height (WH), and 5514 and 1474 for survival to weaning. The reproductive traits analyzed were age at first calving and calving interval. The fiber traits were fiber diameter (FD), standard deviation of FD (SD), comfort factor and coefficient of variation of FD and the morphological traits studied were density, crimp in Huacaya and lock structure in Suri, head, coverage and balance. Regarding preweaning traits, model of analysis included additive, maternal and residual random effects for all traits, with sex, coat color, number of calving, month–year and contemporary group as systematic effects, and age at weaning as linear covariate for WW and WH. The most relevant direct heritabilities for Huacaya and Suri were 0.50 and 0.34 for WW, 0.36 and 0.66 for WH, 0.45 and 0.20 for DG, respectively. Maternal heritabilities were 0.25 and 0.38 for BW, 0.18 and 0.32 for BH, 0.29 and 0.39 for WW, 0.19 and 0.26 for WH, 0.27 and 0.36 for DG, respectively. Direct genetic correlations within preweaning traits were high and favorable and lower between direct and maternal genetic effects. The genetic correlations of preweaning traits with fiber traits were moderate and unfavorable. With morphological traits they were high and positive for Suri but not for Huacaya and favorable for direct genetic effect but unfavorable for maternal genetic effect with reproductive traits. If the selection objective was meat production, the selection would have to be based on the direct genetic effect for WW but not on the maternal genetic effect that has been shown to have less relevance. Other weaning traits such as WH or DG would be indirectly selected.     

Development of equations to predict the influence of floor space on average daily gain,average daily feed intake and gain : feed ratio of finishing pigs

Floor space allowance for pigs has substantial effects on pig growth and welfare. Data from 30 papers examining the influence of floor space allowance on the growth of finishing pigs was used in a meta-analysis to develop alternative prediction equations for average daily gain (ADG), average daily feed intake (ADFI) and gain : feed ratio (G : F). Treatment means were compiled in a database that contained 30 papers for ADG and 28 papers for ADFI and G : F. The predictor variables evaluated were floor space (m²/pig), k (floor space/final BW^0.67), Initial BW, Final BW, feed space (pigs per feeder hole), water space (pigs per waterer), group size (pigs per pen), gender, floor type and study length (d). Multivariable general linear mixed model regression equations were used. Floor space treatments within each experiment were the observational and experimental unit. The optimum equations to predict ADG, ADFI and G : F were: ADG, g=337.57+(16 468×k)−(237 350×k²)−(3.1209×initial BW (kg))+(2.569×final BW (kg))+(71.6918×k×initial BW (kg)); ADFI, g=833.41+(24 785×k)−(388 998×k²)−(3.0027×initial BW (kg))+(11.246×final BW (kg))+(187.61×k×initial BW (kg)); G : F=predicted ADG/predicted ADFI. Overall, the meta-analysis indicates that BW is an important predictor of ADG and ADFI even after computing the constant coefficient k, which utilizes final BW in its calculation. This suggests including initial and final BW improves the prediction over using k as a predictor alone. In addition, the analysis also indicated that G : F of finishing pigs is influenced by floor space allowance, whereas individual studies have concluded variable results.     

Genetic relationship between growth and reproductive traits in Nellore cattle

The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 ± 0.00, 0.42 ± 0.02, 0.49 ± 0.01, 0.11 ± 0.01 and 0.19 ± 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.     

Genetic parameters for body weight,longissimus muscle depth and fat depth for Suffolk sheep in the Czech Republic

In this study, heritabilities and (co)variance components for body weight at 100 days (BW), muscle depth (MD) and fat depth (FD) were estimated for Suffolk, the most common sheep breed in the Czech Republic. Data from 1996 to 2004 were extracted from the sheep recording database of the Czech Sheep and Goat Breeding Association. Genetic parameters were estimated using multivariate animal models, including both direct and maternal genetic effects and permanent environmental effects. Average values for BW, MD and FD were 27.91 kg, 25.5 mm and 3.3 mm, respectively. Direct and maternal heritability for BW were 0.17 and 0.08, respectively, and direct heritabilities were 0.16 for MD and 0.08 for FD. Maternal heritability estimates for ultrasonic measurements were generally low. Direct genetic correlations between BW and MD and maternal genetic correlations between BW and MD were positive and favourable. Both direct genetic correlations between BW and FD and maternal genetic correlations between BW and FD were negative, but not significantly different from zero. The favourable genetic correlations between BW and MD make ultrasound measurements a valuable tool in breeding programs focusing on growth and carcass characteristics.     

Genetic parameters for performance,feed efficiency,and carcass traits in Senepol heifers

Improving feed efficiency is a key breeding goal in the beef cattle industry. In this study, we estimated the genetic parameters for feed efficiency and carcass traits in Senepol cattle raised in tropical regions. Various indicators of feed efficiency [gain to feed ratio (G:F), feed conversion ratio (FCR), residual weight gain (RG), residual intake and body weight gain (RIG), and residual feed intake (RFI)] as well as growth [final BW, average daily gain (ADG), and DM intake (DMI)], and carcass [rib-eye area (REA), backfat thickness (BF), intramuscular fat score, and carcass conformation score] traits were included in the study. After data editing, records from 1 393 heifers obtained between 2009 and 2018 were used for the analyses. We fitted an animal model that included contemporary group (animals from the same farm that were evaluated in the same test season) as the fixed effect, and a linear effect of animal age at the beginning of the test as a covariate; in addition to random direct additive genetic and residual effects. The (co)variance components were estimated by Bayesian inference in uni- and bivariate analyses. Our results showed that feed efficiency indicators derived from residual variables such as RG, RIG, and RFI can be improved through genetic selection (h² = 0.14 ± 0.06, 0.13 ± 0.06, and 0.20 ± 0.08, respectively). Variables calculated as ratios such as G:F and FCR were more influenced by environmental factors (h² = 0.08 ± 0.05 and 0.09 ± 0.05), and were, therefore, less suitable for use in breeding programs. The traits with the greatest and impact on genetic progress in feed efficiency were ADG, REA, and BF. The traits with the greatest and least impact on growth and carcass traits were RG and RFI, respectively. Selection for feed efficiency will result in distinct overall effects on the growth and carcass traits of Senepol heifers. Direct selection for lower RFI may reduce DMI and increase carcass fatness at the finishing stage, but it might also result in reduced growth and muscle deposition. Residual BW gain is associated with the highest weight gain and zero impact on REA and BF, however, it is linked to higher feed consumption. Thus, the most suitable feed efficiency indicator was RIG, as it promoted the greatest decrease in feed intake concomitant with faster growth, with a similar impact on carcass traits when compared to the other feed efficiency indicators.