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For multivariate, single-step genomic best linear unbiased prediction analyses fitting a breeding value model, it is often assumed that the proportions of total genetic variance accounted for by genomic markers and residual polygenic effects are the same for all traits. Different covariance matrices for the two types of genetic effects are readily taken into account by fitting them separately. However, this can lead to slow convergence rates in iterative solution schemes. We propose an alternative computing strategy which – exploiting a canonical transformation – allows for trait-specific covariances whilst directly fitting total genetic effects only. Its effects on convergence rates and gains in accuracy and bias of genomic evaluation compared to analyses assuming proportionality of covariance matrices are examined using a small simulation study. Results show comparatively little improvement in accuracies but worthwhile reductions in overdispersion of predicted genetic merits for genotyped individuals without phenotypes.

This thesis explores methods for estimating genotype by environment (G×E) interactions in livestock and plants. Genotype by environment interactions occur when the genetic architecture of a trait changes depending on the environment it exists in. They are particularly interesting as a source of genetic variation that could be utilised in breeding programs to select genotypes who have genetic merit that is more robust to environmental variation. This thesis aims to estimate genotype by environment interactions in livestock and plant populations using different methods and improve our understanding of how these interactions could be used in breeding programs to increase the robustness of agricultural populations to environmental variation.

The first experiment of this thesis investigated genotype by environment interactions in the bodyweight of Australian sheep using reaction norm and multi-trait models in combination with genomic data. It found significant variation in the slope of the reaction norm model that could be used to increase robustness of sheep, and that this variation was highly polygenic. It highlighted that both heterogenous genetic variance (scale-type G×E) and heterogenous genetic correlations (rank-type G×E) contributed to the variation in the reaction norm slope and found it could be important to separate these sources to better understand the genetic variation in robustness.

The second experiment of this thesis utilised a multi-environment trial of a Barley population to examine the effectiveness of two methods to partition the different types of G×E interactions when estimating the robustness of genotypes in reaction norm models. It found that genetic regression, which made breeding values for the slope independent of the intercept, was very effective in removing the impact of G×E interactions due to scale and isolating the variability across environments due to heterogenous genetic correlations. This enables the change in genetic architecture of traits across environments to be studied more clearly in reaction norm models. We also showed that factor analytic models, which are an alternative to reaction norms, are better equipped to capture complex G×E interactions because of their flexibility.

The third experiment of this thesis examined the use of factor analytic models to capture genotype by environment interactions in a multi-environment trial of sheep. The factor analytic models were able to approximate the unstructured genetic co(variance) matrix between 31 discrete environments using 85% fewer parameters than what would have been required with a multi-trait model. The model enabled the flock-years to be clustered by their similarity and showed that G×E interactions were large both between flocks and across years within flocks. It was unclear whether factor analytic models were preferrable to reaction norms based on the goodness-of-fit tests, and the estimates of heritability, genetic variance and genetic correlations between environments were inconsistent between the models.

The final experimental chapter assessed the capacity of reaction norm models to predict the robustness of a sire’s progeny performance across different growth environments. Using data collected in a research flock, the reaction norm models were predictive of the ability of a sire’s progeny to reliably gain weight across different growth environments at an accuracy that was consistent with the power of the data. It then found that these breeding values for robustness were consistent with breeding values estimated using data from the wider industry population recorded by commercial stud breeders. Selection based on reaction norm breeding values could be used to increase the robustness of body weight gain in Australian sheep to variation in growth environments.

Negative affective states such as anxiety and depression pose a risk to animal welfare, however, practical tests for assessing these states in animals are limited. In humans, anxious individuals are shown to pay more attention toward threatening information than non-anxious individuals, known as an attention bias. Previously, an attention bias test was developed and validated as a measure of anxious states in sheep, where more anxious sheep showed increased attention toward a threat (dog) and were more vigilant than Control animals. Studies in humans suggest that attention biases also occur in depressed individuals, with observations of attention biases toward threats, as well as biases away from positive stimuli. Given these findings, we hypothesized that an attention bias test for sheep could also be used to assess states of depression. We predicted that Merino ewes in pharmacologically induced Depressed (para-chlorophenylalanine) and Anxious (m-chlorophenylpiperazine) states would show greater attention toward a threat than Control animals (saline), but that the Depressed sheep would show relatively less interest in a positive stimulus (photograph of a conspecific). During testing, Depressed sheep paid more attention toward the threat and less toward the photograph than Control animals as predicted (Analyses of Variance, P < 0.05, n = 16 per treatment). Interestingly, Anxious sheep showed an attention bias in the opposite direction, paying more attention toward the photograph and less toward the threat than Control animals (P < 0.05). Both Anxious and Depressed sheep were more vigilant than Control animals (P = 0.002). These results suggest the attention bias test can be used to measure and differentiate states of depression and anxiety in livestock. The bidirectional nature of the attention bias identified between treatments highlights the importance of measuring multiple behaviors in the test and considering the context in which the test is applied. This will enable a clearer characterization of the affective state of an animal, as an aspect of its welfare.

The Australian sheep industry has used genomically enhanced breeding values since 2012. The ability to incorporate genomic information was only made possible by industry investment in a national genomic reference. Initiated in 2007, the Sheep CRC Information Nucleus Flock and its later incarnation the MLA Resource Flock has provided growth, carcase, and wool phenotypes on ~40k genotyped individuals across Merino, Terminal and Maternal breed types. Australian Wool Innovation's Merino Lifetime Productivity project and the Australian Merino Sire Evaluation sites also provided valuable data for the Merino breed. By maintaining a successful genomic reference that directly contributes to the national genetic evaluation producers were shown the direct value of genotyping. Currently, across the core national Sheep Genetic analyses, there are over 500k genotyped animals from industry and research contributing to the evaluation. As a result, the genomic reference is expanding beyond the research population and the role of industry levies to fund the reference population is declining. Future funding will depend on co-investment by breeders beyond levy contributions, with investment dependent on breeders perceiving value in a genomic reference. New and hard to measure traits continue to require recording in research flocks. Consequently, the next iteration of the resource flock will focus on underrepresented and future traits of importance. Providing the core population for the recording of methane and feed intake as well as resilience and maternal behaviour traits. The role of the reference population can be further enhanced by creating stronger linkages between different maternal and Merino ram sources, needed for prediction of breeding values across breed types and of crossbred animals. This would achieve more reliable genomic prediction reliability for key traits such as reproduction and meat eating quality across the commercial breeding flocks.

Blowfly strike or cutaneous myiasis, caused principally by the Australian sheep blowfly Lucilia cuprina is endemic to Australian sheep producing areas and is a major cause of suffering and economic loss. This article reports incidence and control practices as determined by three cross-sectional surveys of Australian sheep farmers covering the years 2003 (n = 1365), 2011 (n = 575) and 2018 (n = 354) with more questions relating to blowfly strike in the latter two surveys. Breech strike was reported at a higher rate than body strike in all survey years. Reported annual incidence of breech strike ranged from 2.2 to 4.7% of sheep nationally with minor differences between ewes and lambs. The incidence of body strike ranged from 1.0 to 7.1% with higher incidence in younger sheep in all years. The use of fixed time routine preventative chemical treatments increased during the survey period (43%, 46% and 66%, in 2003, 2011 and 2018 respectively) with dicyclanil (54%-58%) and cyromazine (23-36%) the main insecticides used for control since 2011. The use of the Mules operation (mulesing) to remove skin wrinkles from the breech area as a preventative modification did not change between 2011 and 2018 (47% in both), however, the use of pain relief at mulesing of replacement ewe lambs increased substantially between 2011 (59%) and 2018 (87%). The most commonly used methods to assist with flystrike control were timing of crutching (clipping of wool from susceptible areas) and shearing, with few respondents destroying maggots from treated sheep (21-26%) and very low use of fly traps (5-8%). Phenotypic selection of ewes for reduced susceptibility to flystrike based on visual traits was practiced by 61% of respondents in 2011 and 56% in 2018. Selection of rams for reduced susceptibility using estimated breeding values increased from 10% in 2011 to 17% in 2018. Breeding for resistance was the most commonly nominated (21%) most important change made to flystrike management in 2018. The results indicate that concern for sheep welfare has increased with almost universal use of pain relief at mulesing. Increased use of selection for blowfly resistance indicates farmer commitment to planning for a future without mulesing, although the practice remains prevalent. An increase in the reliance on preventative chemical treatments increases the risk of insecticide resistance.

Australian Wool Innovation Limited (AWI) commissioned three cross-sectional surveys of sheep producers' sheep parasite control practices over a 15-year period from 2003 to 2018. The aims were to document current sheep parasite incidence and control practices, to measure change in sheep parasite control practices over time and to inform extension messages for sheep industry advisors and sheep farmers. The surveys were conducted in 2004, 2012 and 2019 measuring sheep parasite control practices in the years 2003, 2011 and 2018. The surveys focused on incidence and control of the three major sheep parasite groups; gastrointestinal nematodes, blowflies and lice. The 2003 and 2011 surveys were paper-based and the 2018 survey was accessed via a link to an online survey. This article is the first in a series of four presenting the results of the three surveys and will cover methods, demographics, production systems and general parasite management. Response rates to the surveys declined each year from the peak response rate in 2003 (n = 1365 in 2003; n = 575 in 2011 and n = 354 in 2018). Mean reported rainfall was significantly lower in 2018 (407 mm) than in 2003 (611 mm) and 2011 (650 mm). The demographics of the respondents and their production systems were largely similar between the three surveys for respondent age, median property size, income from wool and sheep meat, proportion of the property area cropped, median sheep dry sheep equivalent (DSEs), ewes as a proportion of the total flock and median cattle DSEs. Month of weaning was more likely to be in summer months for summer dominant rainfall areas and spring for intermediate and winter dominant rainfall areas. There was a marked increase in the proportion of respondents asking for an animal health history when introducing sheep to their flock from 2011 (9%) to 2018 (65%). Similarly, a greater proportion of respondents isolated introduced sheep for at least 2 weeks in 2018 (82%) compared with 2011 (19%). However, there was a decrease in the use of a quarantine lice treatment for introduced sheep from 2011 (50%) to 2018 (21%). Farmers rated themselves, other farmers or member of their staff as most important sources of information on parasite control in both 2011 and 2018. There was a significant increase in the proportion of respondents visiting the ParaBoss suite of websites from 2011 to 2018 confirming their growing importance for information delivery and decision support.

Precision Livestock Farming (PLF) is the application of process engineering principles to livestock management, utilising automation, sensor-based monitoring, and intelligent systems to augment the expertise of livestock producers, and to facilitate the continuous monitoring of livestock biological responses. Livestock vocalisations have been shown to contain a wealth of information pertaining to animal welfare and health, presenting a significant opportunity to facilitate the noninvasive observation of livestock. The automated detection of livestock vocalisations has been demonstrated in numerous applications, such as welfare monitoring, disease diagnosis, and reproduction efficiency.

Recent advancements in machine learning have accelerated the progress of acoustic identification technologies, and this thesis will explore their application to the problem of livestock vocalisation detection. An automated livestock detection algorithm is proposed, utilising novel features derived from a Discrete Wavelet Transform (DWT), combined with a Support Vector Machine (SVM) approach to machine learning. A computationally efficient energy-based thresholding method was employed to facilitate automated segmentation. To date, a complete end-to-end realtime vocalisation detection system has not been demonstrated in the literature. This thesis culminates in the creation of prototype real-time automated vocalisation detection hardware, deployed using a low-resource single board computer (SBC).

To investigate the plausibility of an automated livestock detection system, MelFrequency Cepstral Coefficients (MFCCs) were used as input features for an SVM model to accurately classify sheep vocalisations. To improve on the preliminary results obtained, compact DWT-based acoustic features were proposed. The developed features were compared to MFCCs, both in terms of classification performance and computational timing. It was found that DWT-based features provided similar discriminatory ability to MFCCs, but a marked difference in computational timing was observed. DWT-based features were consistently faster to compute, and less variable in computational time, make them an ideal candidate for real-time vocalisation detection applications. To test the algorithm’s ability to be rapidly applied to different livestock-related vocalisations, 3 datasets were used for performance evaluation, targeting sheep, cattle, and Mareema Sheepdog vocalisations. The high classification results obtained indicated that the algorithm is multi-purpose in nature and can be successfully retrained to detect different vocalisation types.

With the successful development of an accurate classification component, functionality was extended into automated segmentation using an energy-based thresholding approach to acoustic event identification. A sophisticated codebase was developed in the C-programming language, capable of operating in an offline capacity. 700 hours of field recorded audio data underwent automated segmentation to identify the periods of highest acoustic activity. A test dataset containing sound events temporally dissimilar to the training data was created, allowing for the evaluation of the algorithm’s ability to operate in a changing acoustic environment. Results obtained from the test dataset revealed a highly accurate vocalisation detection algorithm, capable of successfully extracting and identifying sheep vocalisations. Although the algorithm performed well at classifying negative acoustic events, it was found to struggle with sounds possessing a similar spectral content and envelope to the target class (e.g., crow vocalisations). Following the successful development of the automated detection algorithm, all field recorded data was processed to classify segmented sound events, revealing the ratio of sheep vocalisations contained within each period.

The codebase developed for offline operation was extended to real-time deployment using the Advanced Linux Sound Architecture (ALSA). Prototype real-time livestock vocalisation detection hardware was produced and tested using pre-recorded audio data playback at varying distances from the capture sensor. During experimentation, the real-time system demonstrated high performance in detecting sheep vocalisations, and correctly rejected the majority of non-vocalisation acoustic events. The system experienced no data losses and did not enter any error states, indicating that the developed algorithm is computationally efficient enough to run on lowresource SBC hardware.

Context. The third Australian national survey on control practices for internal and external parasites of sheep, following similar surveys in 2003 and 2011.
Aims. To document current parasite control practices and attitudes, measure change and to provide a benchmark against which to assess future practices and attitudes.

Methods. An online survey emailed to 6460 sheep producers, with a paper version supplied on request. A follow up short survey was conducted to assess non-response bias. Analysis by region and key sheep enterprise.

Key results. There were 354 and 250 useable responses to the main and short surveys respectively. Mean reported rainfall of 407 mm in 2018 was 27% lower than the average for respondents and >200 mm lower than mean reported rainfall in the previous surveys. The top three methods for worm control over the past 5 years were preventative treatments (74%), preparing clean pastures by spelling paddocks (62%) and treatment on the basis of faecal worm egg count (WEC, 54%). The proportion of respondents using WEC monitoring in 2018 was 40.4%, with a mean frequency of 3.1/year, and this was unaffected by sheep class. The frequency of anthelmintic treatment for ewes and lambs and weaners was 2.1/year. Of the respondents, 36.7% had performed an anthelmintic resistance test in the previous 5 years. The most popular flystrike control methods were timing of crutching (76.4%), preventative chemical treatment (75.9%), timing of shearing (63.1%), mulesing (46.8%) and genetic selection (46.4%). Pain relief was widely used for mulesing ewes (86.6%) and wethers (90.9%). Only 17.3% used Australian Sheep Breeding Values for traits in rams. Most respondents reported 'evidence of lice' in the past 5 years (55.8%) and had treated for lice off shears (50.1%), short wool (16.6%) or long wool (6.6%), with only 26.7% having not treated at all in the period. Web-based sources of information on parasite control have become increasingly important.

Conclusions. Notable changes since the earlier surveys were high rates of pain relief when mulesing, an increase in the use of Australian Sheep Breeding Values for parasite-related traits, an increase in WEC monitoring since 2011 and an increased use of web-based resources.

Implications. Parasite control remains important for sheep producers and continues to evolve with new drugs and approaches. The surveys highlight the effectiveness of extension networks and identify where more attention is required.

Cross-sectional surveys of sheep parasite control practices in Australia were conducted in 2004, 2012 and 2019 to document parasite problems, control practices and measure change over time. This article reports the results pertaining to gastrointestinal nematode infection; comparisons between years are mostly descriptive and not based on statistical inference. There was a general increase in the use of grazing management to prepare clean pastures for sheep to control gastrointestinal nematode infections with the largest increases in the use of: cropping, long acting anthelmintics to prepare clean pastures, feeding strategies, selecting rams for resistance to nematodes, and leaving some sheep untreated. The proportion of respondents using faecal worm egg count monitoring (WEC) and the number of WEC monitors per year were similar in 2003 (weaners: 3.0 WEC/year, adult ewes: 2.6 WEC/year) and 2018 (lambs and weaners and adult ewes both 3.1 WEC/year) but lower in 2011 (lambs and weaners: 2.0 WEC/year, adult ewes: 2.9 WEC/year), whilst there was a higher number of anthelmintic treatments given in 2011 than 2003 and 2018 which were similar. There was an increase in the proportion of respondents carrying out WEC monitors themselves from 2011 (21%) to 2018 (30%) and a corresponding reduction in the use of private laboratories, government laboratories and veterinarians with regional differences in who carried out WECs. The top three anthelmintic groups used did not differ between the three survey years with macrocyclic lactones the most used followed by benzimidazoles (BZ) and levamisole (LEV) although the percentage of MLs used in 2011 and 2018 was lower than in 2003 with higher proportions of respondents using BZ and LEV groups in the latter two survey years. Moxidectin was in the most commonly used active in all survey years. There was an increase in the use of combination of anthelmintics from different groups, especially for a combination of three anthelmintics (2003: 4.4%, 2011: 19.1%, 2018: 21.5%), with lower use of single anthelmintics in 2011 (57.0%) and 2018 (55.4%) compared with 2003 (74.5%). The use of testing for anthelmintic resistance was generally low across the survey years with a lower proportion of respondents using tests in 2011 and 2018 than in 2003 (2003:48%, 2011: 29%, 2018: 37%). Time of year, results from WEC and seasonal weather condition were the most important factors when deciding when to apply anthelmintic treatment.

This thesis aimed to define a suitable definition of ewe longevity for the Australian sheep industry and determine the merit of incorporating the trait into the Australian sheep breeding objectives. Therefore, the fundamental requirements for incorporating ewe longevity in the Australian sheep breeding objectives, the genetic parameters and economic values were estimated for ewe longevity and stayability traits followed by an estimation of response to selection.

The first part of this thesis deals with the data exploration of the MERINOSELECT and LAMBPLAN maternal databases within the Sheep Genetics and the estimation of genetic parameters for the ewe longevity and stay ability traits in Merino and maternal breeds. The majority of the flocks submitting data to the MERINOSELECT and LAMBPLAN maternal databases do not have sufficient recording patterns to derive longevity. However, the contemporary groups with regular recording patterns were selected. The contemporary groups were defined as the site × flock × year of birth. These contemporary groups of ewes with regular recording patterns within the MERINOSELECT database were; 1) born since the year 2000, 2) had spent a minimum of 3 years in the flock, 3) had their own annual weight (weaning, postweaning or yearling) or wool record and reproduction record (from 2 yrs) up to 6 years of age, 4) contained at least 30 ewes, and 5) at least 70% of the animals were assigned a sire (chapter 3).The ewe longevity or time in flock (TIF) was defined as the period between birth and the last available production record. The stay ability traits were defined as the presence of a ewe in flock up to certain periods of time. The heritability estimates of the ewe's longevity and stayability traits were moderate if not corrected for the ewes’ production and reproductive performance. However, after correcting for these traits, the ewe's longevity and stayability traits were lowly heritable. The correlation between the ewes’ longevity and stayability traits was strong.

The correlation between ewe longevity and production and reproduction traits was estimated via a series of bivariate analyses. The analysed production traits were weaning weight (wwt), post-weaning weight (pwt), post-weaning C-site fat (pcf), post-weaning eye muscle depth (pemd), post-weaning faecal egg count (pfec), yearling weight (ywt), yearling Csite fat (ycf), yearling eye muscle depth (yemd), yearling faecal egg count (yfec), yearling greasy fleece weight (ygfw), yearling fibre diameter (yfd), adult greasy fleece weight (agfw) and adult fibre diameter (afd). The reproductive traits analysed were fertility (fert), litter size (ls), number of lambs born (nlb), ewe rearing ability (era) and number of lambs weaned (nlw). The ewes’ TIF was lowly heritable and correlated to the production and reproduction traits. Therefore, a breeding objective was to be formulated that considers longevity as an objective trait, which requires calculating the economic value of the ewes’ TIF trait.

The second part of this thesis deals with the estimation of economic value and response to selection. The economic value of the ewes’ TIF was large across the fine wool Merino, dual purpose Merino and maternal production systems. Ewe longevity has a positive correlation with the current breeding objectives suggesting that selection on the current breeding objectives will improve ewe longevity across the three production systems within the Australian sheep industry. However, including longevity trait in the breeding objectives will further increase the overall genetic gain, and particularly improve genetic gain for longevity. In the maternal production system, the genetic gain of the growth and carcase traits slows down a little after including the longevity trait in the breeding scenarios. The results showed a 2 to 3% increase in the total dollar response across the three production systems after incorporating the ewes’ TIF trait into the breeding objectives. However, incorporating genomic information of TIF into breeding objectives increased the overall response by 13 to 16% across three production systems. The results suggest that selection based on the current breeding objectives will improve ewe longevity within the Merino and maternal production systems but noticeably higher genetic gain can be attained if the genomic information of ewes’ TIF is incorporated into the breeding objectives.

The final chapter discusses the research findings and concludes with recommendations for future research areas. These recommendations include important encouragements like improving the data quality, the importance of recording culling reasons, estimating accurate genetic parameters of ewe longevity and the potential of incorporating the ewe longevity as a trait in the Australian sheep breeding objectives to achieve higher genetic gain. This thesis contributes significantly to define ewe longevity and using the genetic parameters in the Australian sheep breeding objectives.