L. Schüler

Monthly model for genetic evaluation of laying hens II. Random regression

1. We investigated the use of monthly production records for genetic evaluation of laying hens, derived from a test day model with random regression in dairy cattle and compared it with other models. 2. Records of 6450 hens, daughters of 180 sires and 1335 dams, were analysed using a model with restricted maximum likelihood (REML): traits considered were monthly and cumulative egg production. Five models were studied: (1) random regression with covariates derived from the regression of Ali and Schaeffer ( Canadian Journal of Animal Science , 67 : 637-644, 1987) (RRMAS), (2) random regres7 sion with covariates derived from quartic polynomial (RRMP4), (3) fixed regression with covariates derived from Ali and Schaeffer (FRM), (4) multiple trait (MTM) and (5) cumulative (CM). 3. The models were compared on the basis of Spearman rank correlations of individual breeding values and sire breeding values estimated from subsets of full-sib split data. The hens (about 10% per generation) which ranked highest on their estimated breeding values from different models were compared phenotypically with their full records. 4. The estimates of heritability resulting from RRMP4 were biased upward from the estimates obtained from MTM, so this model was discarded. The heritabilities for monthly productions from RRMAS and MTM showed a similar pattern. They were high for the 1st month of production, decreased to their lowest value at about month 5 of production and increased again to the end of lay. 5. Spearman rank correlations between animal breeding values estimated by monthly models (RRMAS, FRM and MTM) were high, between 0.91 and 0.98, whereas those between estimates of monthly models and CM were lower, from 0.85 to 0.87. The correlations estimated either from intermittent months of measurements (odd vs even months) or full records were generally high, from 0.93 to 0.99. Information from odd months of production could be sufficient for cost-efficient recording schemes. The RRMAS generally had the highest correlation of sire breeding values between subsets of full-sib records, followed by MTM, RM and CM. Monthly models selected hens with higher productivity than the cumulative model. 6. In conclusion, genetic evaluation based on monthly production may be better than using cumulative production and RRMAS appeared to be the best among the models tested here.

Genetic parameters for egg production and egg weight of laying hens housed in single and group cages

The present study was conducted to estimate the heritability and genetic correlation of monthly egg production and egg weight of 2 lines White Leghorn hens in single and group cages. A total of 2289 records (line A) and 2596 records (line D) from single cages, 518 and 541 records (for line A and D, respectively) from group cages, were analysed. (Co) variance components of single cage data were analysed using the programme VCE4 applying the REML method and a multiple trait animal model. An EM-algorithm was used to obtain (co) variance components for group cage data. Genetic correlations between single and group cages were analysed using the programme VCE4 based on sire model. Heritability estimates for monthly egg production in single cages ranged from 0.08 to 0.44 (line A); 0.04 to 0.43 (line D) and those for group cages were 0.02 to 0.42 (line A); 0.02 to 0.19 (line D). Egg weight was highly heritable for single and group cages (heritability = 0.25 to 0.54). The genetic correlations between monthly and cumulative egg production were 0.25 to 0.95 (line A); 0.26 to 0.86 (line D) for single cage and 0.24 to 0.84 (line A); 0.26 to 0.96 (line D) for group cage. Cumulative egg production in single cage were highly correlated with those of group cages (0.89 and 0.63, respectively for line A and line D). Single cage records gave higher estimates of genetic parameter than group records. However, the trend of estimates is almost the same. High genetic correlations were found between single- and group cages in most of the production periods.

Monthly model for genetic evaluation of laying hens 1. Fixed regression

1. This paper addresses the possibility of using a monthly model for the genetic evaluation of laying hens, based on the definition of a test day model with fixed regression as used in dairy cattle, in which monthly records were treated as repeated measurements of the same trait. 2. Production records of 6450 hens, daughters of 180 sires and 1335 dams were analysed using an animal model with restricted maximum likelihood (REML). The traits considered were individual monthly egg production and cumulative egg production in 11 months. Four different models were fitted to various combinations of monthly and cumulative records. The covariates were derived from the regression of Ali and Schaeffer (1987). 3. Spearman rank correlations were computed to compare breeding values from different models. Two types of correlations were computed: between individual breeding values and between sire breeding values based on subsets of full-sib records. 4. The results indicated that a monthly model with nested covariates produced higher heritability and permanent environmental variance than the models with non-nested or without covariates. The estimates of heritability obtained from monthly model were lower than the estimates from the cumulative model. The monthly model resulted in higher correlations of sire breeding values between two subsets of full-sib records than those from cumulative models. 5. In conclusion, the monthly model with nested covariates appears to be better than the model with non-nested covariates or without covariate. Although the heritability estimates obtained from the monthly model were lower, the monthly model with nested covariates could be better than the cumulative model for genetic evaluation of laying hens in the 1st cycle of laying period when using either full or part records. The use of information from odd months of production could be of interest for the evaluation of full records.

Statistical analysis of test-day milk yields using random regression models for the comparison of feeding groups during the lactation period

Abstract Random regression models are widely used in the field of animal breeding for the genetic evaluation of daily milk yields from different test days. These models are capable of handling different environmental effects on the respective test day, and they describe the characteristics of the course of the lactation period by using suitable covariates with fixed and random regression coefficients. As the numerically expensive estimation of parameters is already part of advanced computer software, modifications of random regression models will considerably grow in importance for statistical evaluations of nutrition and behaviour experiments with animals. Random regression models belong to the large class of linear mixed models. Thus, when choosing a model, or more precisely, when selecting a suitable covariance structure of the random effects, the information criteria of Akaike and Schwarz can be used. In this study, the fitting of random regression models for a statistical analysis of a feeding experiment with dairy cows is illustrated under application of the program package SAS. For each of the feeding groups, lactation curves modelled by covariates with fixed regression coefficients are estimated simultaneously. With the help of the fixed regression coefficients, differences between the groups are estimated and then tested for significance. The covariance structure of the random and subject-specific effects and the serial correlation matrix are selected by using information criteria and by estimating correlations between repeated measurements. For the verification of the selected model and the alternative models, mean values and standard deviations estimated with ordinary least square residuals are used.

Behavioural and endocrinological changes in Syrian hamsters (Mesocricetus auratus) under domestication

This study aimed to quantify differences in response to stress between two strains of Syrian hamsters to evaluate the consequences of domestication in this species by measuring behavioural traits in the open-field, adrenal gland masses (ADR), and faecal and blood corticosterone concentrations (CC). We studied a laboratory (lab)- and a wild-derived population (wild). The lab hamsters were significant heavier than the wild hamsters. The lab males had the highest ADR, and it was independent of their high body mass (BM). The ADR of lab females and wild hamsters was linearly dependent of BM. The lab males had the highest faecal and blood CC, whereas the lab females had the lowest CC. In the open field, the lab hamsters began later to groom, groomed shorter, groomed less frequently, began later to rear, reared longer and reared less frequently. In the lab population, females reared more often and groomed longer than males. The sex differences in the behaviours of the lab population and the differences between the populations mirror the differences neither in the ADR nor in the CC. The founder effect and the breeding history of lab Syrian hamsters are discussed as causes of the differences between the studied populations.