Quantifying the sources of variation in eosinophilia among Scottish blackface lambs with mixed, predominantly Teladorsagia circumcincta nematode infection

Eosinophils play a key role in defence against gastrointestinal nematodes. There is considerable variation among animals in the intensity of eosinophilia following nematode infection. However, the statistical distribution of eosinophils among animals has still to be determined. A better description of the variation among animals could provide biological insight and determine the most appropriate way to analyse the effect of eosinophils. We estimated blood eosinophil numbers in a flock of Scottish Blackface sheep that were naturally exposed to mixed, predominantly Teladorsagia circumcincta infection. Three of the four eosinophil counts were better described by a gamma distribution than by a lognormal distribution. The scale and shape parameters of the gamma distribution varied over time. Eosinophil counts differed among animals kept on separate fields before weaning and between singletons and twins but were not significantly different between years and genders. Eosinophil counts also differed among offspring from different sires and dams. The parameters of the gamma distribution were used to enable a power analysis. Large numbers of animals were required to reliably detect even large differences between two groups. These results indicate that methods appropriate for gamma distributions, such as generalized linear mixed models, will provide more reliable inferences than traditional methods of analysis and experimental design. © 2021 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “David Piedrafita and Sarah Preston” is provided in this record*

The repeatability and heritability of traits derived from accelerometer sensors associated with grazing and rumination time in an extensive sheep farming system

IntroductionThe automated collection of phenotypic measurements in livestock is of interest to both researchers and farmers. Real-time, low-cost, and accurate phenotyping can enhance precision livestock management and could lead to the optimized utilization of pasture and breeding of efficient animals. Wearable sensors provide the tools for researchers to develop novel phenotypes across all production systems, which is especially valuable for grazing conditions. The objectives of this study were to estimate the repeatability and heritability of traits related to grazing and rumination activities and their correlations with other traits.MethodsThis study was conducted on a commercial Merino farm in the west of Victoria, Australia, from 4 May 2020 to 29 May 2020. A total of 160 ActiGraph sensors embedded in halters were attached to the left side of the muzzles of Merino sheep (M = 74, F = 86) aged 10–11 months while the sheep were grazing on pasture. Support vector machine (SVM) algorithms classified the sensor output into the categories of grazing, rumination, walking, idle, and other activities. These activities were further classified into daily grazing time (GT), number of grazing events (NGE), grazing length (GL), rumination time (RT), number of rumination events (NRE), rumination length (RL), walking time (WT), and idle time (IT). The data were analyzed using univariate and bivariate models in ASReml-SA to estimate the repeatability, heritability, and phenotypic correlations among traits.ResultsThe heritability of GT was estimated to be 0.44 ± 0.23, whereas the other traits had heritability estimates close to zero. The estimated repeatability for all traits was moderate to high, with the highest estimate being for GT (0.70 ± 0.03) and the lowest for RT (0.44 ± 0.03). The intraclass correlation or repeatability at a 1-day interval (i.e., 2 consecutive days) was high for all traits, and steadily reduced when the interval between measurements was longer than 1 week.DiscussionThe estimated repeatability for the grazing traits showed that wearable sensors and SVM methods are reliable methods for recording sheep activities on pasture, and have a potential application in the ranking of animals for selective breeding

The heritability of Nematodirus battus fecal egg counts

Although Nematodirus battus is a serious threat to the health and survival of young lambs, there are few options to control this parasite. Bayesian Monte Carlo Markov Chain modelling with a zero-inflated Poisson distribution was used to estimate the heritability of egg counts in both June and July for each of five consecutive cohorts of 200 Scottish Blackface lambs. In one of the 10 analyses, the results failed the diagnostic tests. In seven of the analyses, there was no convincing evidence that the variation in egg counts was heritable. In the 2 years of high infection, the heritability was approximately 0.4 in June but the estimates lacked precision and the 95% highest posterior density credible intervals ranged from just above zero to 0.7. Selective breeding for resistance to N. battus will be difficult because genetically resistant or susceptible lambs cannot be consistently identified by phenotypic markers

Quantification of behavioural variation among sheep grazing on pasture using accelerometer sensors

Context: Monitoring the behaviour of animals can provide early warning signs of disease or indicate loss of appetite. Also, an understanding of the variation in behaviours among animals and their distributions is essential for meaningful statistical inference. Therefore, quantifying the variation of behaviours is of both biological and statistical interest. Aim: The objectives of this study were to determine the distributions and quantify the variation among animals with respect to the times spent grazing, ruminating, idling, walking, and licking. Methods: The activities of 147 (male = 67, female = 80) Merino lambs at 10-11 months of age on a commercial farm in Edenhope, Victoria, Australia were recorded for 26 days, using ActiGraph accelerometer sensors attached to the left side of the sheep's muzzle. The male and female sheep were kept in separate paddocks. A Support Vector Machine algorithm was used to differentiate sheep behaviour into six categories: Grazing, ruminating, idling, walking, licking, and other activities. The distributions of behaviours were analysed using energy statistics-based tests and Generalised Additive Models for Location, Scale, and Shape (GAMLSS). Different distributions were compared using Akaike Information Criterion (AIC) values. Key results: Among the distributions that were considered, we found that times spent ruminating in both male and female sheep populations as well as idling in male sheep were best described by the skew exponential type 2 distribution. Grazing, walking and licking behaviours were best described by the Box-Cox t distribution. The distribution of time spent grazing was symmetrical and unimodal in males, and adequately modelled by a normal distribution, but the distribution in females had a prominent left skew. Also, we found that females typically grazed for a longer time than males. However, males spent more time ruminating than grazing. Conclusions: The time spent by the animal in each activity varied during the day. Within each population, the variation among animals in the time spent grazing was best described by a Box-Cox t distribution. Implications: This study has enhanced our understanding of grazing behaviour and will facilitate more appropriate analyses of the causes of variation among animals in grazing behaviour