Records on growth and reproductive characteristics collected from 1993 to 2013 at the Breeding Station of Kermani sheep, south-east of Iran, were used for estimating genetic parameters related to parent-of-origin effects. The studied growth traits were birth weight (BWT), weaning weight (WWT), six-month weight (6MW), average daily gain from birth to weaning (ADG1), and average daily gain from weaning to six months of age (ADG2). The reproductive traits were litter size at birth per ewe lambing (LSB), litter size at weaning per ewe lambing (LSW), the sum of litter weight at birth per ewe lambing (LWB), and the sum of litter weight at weaning per ewe lambing (LWW). Models with and without imprinting (maternal and paternal) effects were compared by applying Akaike's information criterion (AIC). Maternal imprinting effects explained 14, 7, 24 and 5% of the phenotypic variances for BWT, WWT, 6MW and ADG1, respectively and their inclusion in the model decreased direct heritability estimates for BWT (from 0.07 to 0.05), WWT (from 0.29 to 0.23), 6MW (from 0.26 to 0.12) and ADG1 (from 0.20 to 0.17). Imprinting effects did not affect ADG2 and studied reproductive traits. The results indicated that a considerable proportion of the maternal imprinting effects overlap with direct additive genetic and maternal effects. Therefore, imprinting effects may be crucial for the genetic assessment of BWT, WWT, 6MW and ADG1 in Kermani sheep.

The partition of the total genetic variance into its additive and non-additive components can differ from trait to trait, and between purebred and crossbred populations. A quantification of these genetic variance components will determine the extent to which it would be of interest to account for dominance in genomic evaluations or to establish mate allocation strategies along different populations and traits. This study aims at assessing the contribution of the additive and dominance genomic variances to the phenotype expression of several purebred Piétrain and crossbred (Piétrain × Large White) pig performances. A total of 636 purebred and 720 crossbred male piglets were phenotyped for 22 traits that can be classified into six groups of traits: growth rate and feed efficiency, carcass composition, meat quality, behaviour, boar taint and puberty. Additive and dominance variances estimated in univariate genotypic models, including additive and dominance genotypic effects, and a genomic inbreeding covariate allowed to retrieve the additive and dominance single nucleotide polymorphism variances for purebred and crossbred performances. These estimated variances were used, together with the allelic frequencies of the parental populations, to obtain additive and dominance variances in terms of genetic breeding values and dominance deviations. Estimates of the Piétrain and Large White allelic contributions to the crossbred variance were of about the same magnitude in all the traits. Estimates of additive genetic variances were similar regardless of the inclusion of dominance. Some traits showed relevant amount of dominance genetic variance with respect to phenotypic variance in both populations (i.e. growth rate 8%, feed conversion ratio 9% to 12%, backfat thickness 14% to 12%, purebreds-crossbreds). Other traits showed higher amount in crossbreds (i.e. ham cut 8% to 13%, loin 7% to 16%, pH semimembranosus 13% to 18%, pH longissimus dorsi 9% to 14%, androstenone 5% to 13% and estradiol 6% to 11%, purebreds-crossbreds). It was not encountered a clear common pattern of dominance expression between groups of analysed traits and between populations. These estimates give initial hints regarding which traits could benefit from accounting for dominance for example to improve genomic estimated breeding value accuracy in genetic evaluations or to boost the total genetic value of progeny by means of assortative mating.

Body weight and body measurements are commonly used to represent growth and measured at several growth stages in beef cattle. Those economically important traits should be genetically improved. To achieve breeding programs, genetic parameters are prerequisite, as they are needed for designing and predicting outcomes of breeding programs, as well as estimating of breeding values. (Co)variance components were estimated for BW and body measurements on Brahman cattle born between 1990 and 2016 from 17 research herds across Thailand. The traits measured were BW, heart girth (GR), hip height (HH) and body length (BL) and were measured at birth, 200 days, 400 days and 600 days of age. The number of records varied between traits from 18 890 for birth BW to 876 for GR at 600 days. Estimation of variance components was performed using restricted maximum likelihood using univariate and multivariate animal models. Pre-weaning traits were influenced by genetic and/or permanent environmental effects of the dam, except for BL. Heritability estimates from birth to 600 days of age ranged from 0.28±0.01 to 0.50±0.06 for BW, 0.27±0.01 to 0.43±0.09 for GR, 0.28±0.01 to 0.58±0.08 for HH and 0.34±0.01 to 0.51±0.08 for BL using univariate analysis. Heritability estimates for the traits studied increased with age. A similar trend was observed for the phenotypic and genetic correlations between subsequent BW and body measurements. A positive correlation was observed between different traits measured at a similar age, ranging from 0.22±0.01 to 0.72±0.01 for the phenotypic correlation and 0.25±0.04 to 0.97±0.11 for the genetic correlation. Also, a positive correlation was observed for similar traits across different age classes ranging from 0.07±0.03 to 0.76±0.02 for the phenotypic correlation and 0.24±0.11 to 0.92±0.05 for the genetic correlation. Therefore, all correlations between body measurements at the same age and across age classes were positive. The results show the potential improvement of growth traits in Brahman cattle, and those traits can be improved simultaneously under the same breeding program.

Crop scientists occasionally compute sample correlations between traits based on observed data from designed experiments, and this is often accompanied by significance tests of the null hypothesis that traits are uncorrelated. This simple approach does not account for effects due to the randomization layout and treatment structure of the experiments and hence statistical inference based on standard procedures is not appropriate. The present paper describes how valid inferences accounting for all relevant effects can be obtained using bivariate mixed linear model procedures. A salient feature of the approach is that the bivariate model is commensurate with the model used for univariate analysis of individual traits and allows bivariate correlations to be computed at the level of effects. Heterogeneity of correlations between effects can be assessed by likelihood ratio tests or by graphical inspection of bivariate scatter plots of effect estimates. if heterogeneity is found to be substantial, it is crucial to focus on the correlation of effects, and usually, the main interest will be in the treatment effects. If heterogeneity is judged to be negligible, the marginal correlation can be estimated from the bivariate model for an overall assessment of association. The proposed methods are illustrated using four examples. Hints are given to alternative routes of analysis accounting for all treatment and design effects such as regression with groups and analysis of covariance.

Objective of this study was to estimate genetic parameters of milk coagulation properties (MCPs) and individual laboratory cheese yield (ILCY) in a sample of 1018 Sarda breed ewes farmed in 47 flocks. Rennet coagulation time (RCT), curd-firming time (k20) and curd firmness (a30) were measured using Formagraph instrument, whereas ILCY were determined by a micromanufacturing protocol. About 10% of the milk samples did not coagulate within 30 min and 13% had zero value for k20. The average ILCY was 36%. (Co)variance components of considered traits were estimated by fitting both single- and multiple-trait animal models. Flock-test date explained from 13% to 28% of the phenotypic variance for MCPs and 26% for ILCY, respectively. The largest value of heritability was estimated for RCT (0.23±0.10), whereas it was about 0.15 for the other traits. Negative genetic correlations between RCT and a30 (−0.80±0.12), a30 and k20 (−0.91±0.09), and a30 and ILCY (−0.67±0.08) were observed. Interesting genetic correlations between MCPs and milk composition (rG>0.40) were estimated for pH, NaCl and casein. Results of the present study suggest to use only one out of three MCPs to measure milk renneting ability, due to high genetic correlations among them. Moreover, negative correlations between ILCY and MCPs suggest that great care should be taken when using these methods to estimate cheese yield from small milk samples.

Genetically reducing boar taint using low-taint lines is considered the most sustainable and economic long-term alternative to surgical castration of male pigs. Owing to the high heritability of the main boar taint components (androstenone, skatole and indole), breeding is an excellent tool for reducing the number of tainted carcasses. To incorporate boar taint into breeding programmes, standardized performance testing is required. The objective of this study was to develop and formally present a performance test for the main boar taint compounds on live breeding candidates. First, a standardized performance test for boar taint was established. A biopsy device was developed to extract small tissue samples (200 to 300 mg) from breeding candidates. Quantification of boar taint components from these small samples using specialized chemical extraction methods proved accurate and repeatable (r = 0.938). Following establishment of the method, biopsy samples of 516 live boars (100 to 130 kg live weight) were collected in the second step. Various mixed linear models were tested for each boar taint compound; models were ranked in terms of their information content. Pedigree information of 2245 ancestors of biopsied animals was included, and genetic parameters were estimated using univariate and multivariate models. Androstenone (in μg/g liquid fat (LF): mean = 0.578, σ = 0.527), skatole (in μg/g LF: mean = 0.033, σ = 0.002) and indole (in μg/g LF: mean = 0.032, σ = 0.002) levels obtained by biopsy were plausible. Heritability estimates for androstenone calculated with univariate (0.453) and multivariate (0.452) analyses were comparable to those in the literature. Heritabilities for skatole (0.495) and indole (0.550) were higher than that for androstenone. Genetic and phenotypic correlations were similar to those published previously. Our results show that data on boar taint compounds from small adipose samples obtained by biopsy provide similar genetic parameters as that described in the literature for larger samples and are therefore a reliable performance test for boar taint in live breeding candidates.

One can find in the literature three main sets of estimators for the variance components in the hierarchical credibility model. This paper presents these estimators in a unified notation, studies some of their properties important for numerical evaluation and compares their relative performance by simulation. The paper also demonstrates how function cm of the R package actuar can be used to fit hierarchical models to insurance data.

Covariance components for test day milk yield using 263 390 first lactation records of 32 448 Holstein cows were estimated using random regression animal models by restricted maximum likelihood. Three functions were used to adjust the lactation curve: the five-parameter logarithmic Ali and Schaeffer function (AS), the three-parameter exponential Wilmink function in its standard form (W) and in a modified form (W*), by reducing the range of covariate, and the combination of Legendre polynomial and W (LEG+W). Heterogeneous residual variance (RV) for different classes (4 and 29) of days in milk was considered in adjusting the functions. Estimates of RV were quite similar, rating from 4.15 to 5.29 kg2. Heritability estimates for AS (0.29 to 0.42), LEG+W (0.28 to 0.42) and W* (0.33 to 0.40) were similar, but heritability estimates used W (0.25 to 0.65) were highest than those estimated by the other functions, particularly at the end of lactation. Genetic correlations between milk yield on consecutive test days were close to unity, but decreased as the interval between test days increased. The AS function with homogeneous RV model had the best fit among those evaluated.

A total of 19 376 test day (TD) milk yield records from the first three lactations of 1618 cows daughters of 162 sires were used to estimate genetic and phenotypic parameters and determine the relationship between daily milk yield and lactation milk yield in the Sahiwal cattle in Kenya. Variance components were estimated using animal models based on a derivative free restricted maximum likelihood procedure. Variance components were estimated using various univariate and multi-trait fixed regression test day models (TDM) that defined contemporary groups either based on the year-season of calving (YSCV) or on the year-season of TD milk sampling (YSTD). Variance components were influenced by CG which resulted in differences in heritability and repeatability estimates between TDM. Models considering YSTD resulted in higher additive genetic variances and lower residual variances compared with models in which YSCV was considered. Heritability estimates for daily yield ranged from 0.28 to 0.46, 0.38 to 0.52 and 0.33 to 0.52 in the first, second and third lactation, respectively. In the first and second lactation, the heritability estimates were highest between TD 2 and TD 4. Genetic correlations among daily milk yields ranged from 0.41 to 0.93, 0.50 to 0.83 and 0.43 to 86 in the first, second and third lactation, respectively. The phenotypic correlations were correspondingly lower. Genetic correlations were different from unit when fitting multi-trait TDM. Therefore, a multiple trait model would be more ideal in determining the genetic merit of dairy sires and bulls based on daily yield records. Genetic and phenotypic correlations between daily yield and lactation yields were high and positive. Genetic correlations ranged from 0.84 to 0.99, 0.94 to 1.00 and 0.94 to 0.97 in the first, second and third lactations, respectively. The corresponding phenotypic correlation estimates ranged from 0.50 to 0.85, 0.50 to 0.83 and 0.53 to 0.87. The high genetic correlation between daily yield and lactation yield imply that both traits are influenced by similar genes. Therefore daily yields records could be used in genetic evaluation in the Sahiwal cattle breeding programme.

When the laboratory methods employed are qualitative, the statistical methodologies used in testing for the adventitious presence (AP) of transgenic material in conventional seed and grain lots are well defined. However, when the response from the method used by the laboratory is quantitative (e.g. percent transgenic DNA), the statistical methodologies developed for qualitative laboratory methods are not fully appropriate. In this paper, we present the details of procedures specific to quantitative laboratory methods. In particular we consider: (1) the assessment of quantitative laboratory method errors using linear modelling; and (2) the process of deciding whether or not a lot meets pre-specified purity standards, including the development of probability calculations needed to develop operating characteristic curves and estimate consumer and producer risks for a given lower quality limit (LQL), acceptable quality limit (AQL) and testing plan. We also describe implementation of this approach in a useful spreadsheet application.

Polymorphisms at codons 136, 154 and 171 of the gene encoding the prion protein (PrP) are associated with susceptibility to classical scrapie in sheep. Genetic selection for scrapie resistance based on PrP genotypes is central to the scrapie eradication programme in Great Britain but there are concerns about how this may affect other economically important traits. The objective of this study was to evaluate associations of PrP genotypes with live weight and slaughter traits in a hill sheep breed in Great Britain. Data used were from an experimental flock of Swaledale sheep in which the alleles ARR, ARQ, AHQ and VRQ were present. About 1450 genotyped lambs with birth, marking and weaning weights, and 620 with slaughter records were used for the study. Mixed models with various fixed effects and random direct genetic and maternal effects were tested to determine the appropriate model to use for each trait. None of the differences in lamb performance between PrP genotypes consistently reached significance. Therefore, this study does not support existence of significant relationships between PrP genotype and lamb performance traits in this breed.

In this paper a brief review of Sage adaptive filtering is followed by an analysis of the shortcomings of covariance matrices formed by windowing residual vectors, innovation vectors and correction vectors of the dynamic states. A new adaptive Kalman filter is developed by combining the Sage filter and the variance components and its use tested against various other schemes.

The statistical aggregation of parasites among hosts is often described empirically by the negative binomial (Poisson-gamma) distribution. Alternatively, the Poisson-lognormal model can be used. This has the advantage that it can be fitted as a generalized linear mixed model, thereby quantifying the sources of aggregation in terms of both fixed and random effects. We give a worked example, assigning aggregation in the distribution of sheep ticks Ixodes ricinus on red grouse Lagopus lagopus scoticus chicks to temporal (year), spatial (altitude and location), brood and individual effects. Apparent aggregation among random individuals in random broods fell 8-fold when spatial and temporal effects had been accounted for.

Hordeum spontaneum shows a large genetic variation and occupies a wide range of different habitats. The aim of this study was to quantify variation in growth characteristics of H. spontaneum from different sites in Israel and to relate this variation to different environmental conditions. To this end, 84 accessions of 21 populations were grown in a growth chamber in near-optimal conditions and a range of physiological, morphological, allocation- related and chemical characteristics were measured. These parameters included rates of photosynthesis, shoot and root respiration, specific leaf area, biomass allocation and seed mass. Averaged over all traits variation explained by differences between populations was 26%, between accessions 21%, whereas that within accessions was 53%. By contrast with most genetic studies, we found variation between populations larger than between accessions. The largest between-population variation (46%) was for morphological traits. In particular, seed mass, leaf thickness and leaf width differed strongly between populations. Variation in growth characteristics between populations was poorly related to mean annual rainfall, mean humidity or January temperature at the sites of origin. We expect that differences between populations to be larger and correlation with environmental parameters stronger in plants grown in stressful conditions. According to our study, seed mass is more important than relative growth rate in determining variation in early plant biomass in H. spontaneum.

There have been many attempts to characterize day-to-day variation in nutrient intake. This variation has a fixed component, associated with particular days of the week, and a random component. Both components were studied for a range of nutrients, using 4 d weighed diary data from a large, nationally representative survey of people aged 65 years or over. Since day-to-day variation may distort the characterization of the population distribution of habitual nutrient intakes, especially when diets are studied over only a small number of days, a statistical method was developed to correct for this distortion. Results suggested that population distributions of habitual nutrient intake could be accurately constructed from 4 d weighed diary data and that the method might be successfully applied to studies based on as little as 2 d of observation. The method is particularly valuable for correcting estimates of extreme nutrient intakes for biases induced by uneven representation of days of the week and by within-person variation.

The Baluchi breed is the most common native breed of Iran adapted to harsh environments in the eastern parts of the country. The data used in the present study, collected from two research flocks at the Abbasabad sheep breeding station in north-east Iran, included 20 534 animals descended from 363 sires, 5992 dams, 282 maternal grandsires, and 2865 maternal granddams during the period 1966 to 1989. The traits recorded were: birth weight (BW), weaning weight (WW), weight at 6 months (W6), weight at 12 months (YW), pre-weaning gain (WG), post-weaning gain (PWG), lamb fleece weight (LFW), ewe fleece weight sheared before first joining (FW1) and adult ewe fleece weight (FW). Genetic parameters, estimated with restricted maximum likelihood and a two-trait animal model, were similar in the two flocks. Direct heritabilities for the various body weight traits were moderate and varied between 0·13 and 0·32, while the maternal heritabilities were low and varied between 0·01 and 0·12. Direct and maternal genetic correlations between WW and weights at later ages were moderate to high (0·59 to 0·96). Direct heritabilities of weight gain measures varied between 0·12 and 0·19, while no significant maternal influence on either of these weight gain measures could be detected. The estimates of direct genetic correlation between WG and PWG were positive and varied between 0·54 and 0·74, while negative maternal genetic correlation (0·17 on average) between WG and PWG was detected. For LFW, direct heritability was low and no maternal heritability could be shown. For FW1, both direct and maternal genetic influences were demonstrated (0·07 to 0·26). Direct genetic correlation between LFW and FW1 was very low and close to zero, while maternal genetic correlation was positive and relatively high (0·72 on average). The relative contributions to phenotypic variance from variance components due to common environmental effects ranged from 0·01 to 0·15 for all traits. The repeatability of FW was low (0·03 to 0·12).

We study the situation in which individuals occur in ‘families' or similar groups, individuals within a ‘family' being correlated with one another, as for example a biological population. In such a population, the number of individuals will usually vary from one family to another. We assume that a sample chosen from the population consists of whole families rather than unrelated individuals. A similar situation might occur in experimental design, if individuals occur in ‘blocks' (of varying sizes) within which they share a common environment. In the simplest case considered here two measurements are made on each individual, namely y, the character of interest, and x (not necessarily a random variable), some other character which is believed to influence y. We discuss how to estimate the regression of y on x, and the within and between family variance components for y (and hence the intrafamily correlation) when the effect of x is eliminated. Generalizations of this are briefly discussed.