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    Animal factors affecting enteric methane production in late lactation pasture based dairy cows in Ireland : a thesis presented in partial fulfilment of the requirements for the degree of Master of Animal Science at Massey University, Palmerston North, New Zealand
    (Massey University, 2022) Starsmore, Katie
    Ireland currently has a national commitment to reduce 51% of total greenhouse gas emissions by 2030. In order to achieve these reductions, factors that affect enteric methane production in a pasture-based system need to be further investigated. The objectives of this study were to 1) investigate the repeatability on enteric methane emissions in grazing dairy cows, 2) assess the relationship between enteric methane and other animal traits at grass and 3) investigate the potential of a new trait called residual enteric methane emission (RME) to select for lower enteric methane emitting cows without impacting productivity. Enteric methane emissions were measured on forty-five late lactation grazing dairy cows using the GreenFeed monitoring system at Teagasc, Moorepark, County Cork, Ireland. The average enteric methane produced was 351.8 g per day with a daily coefficient of variation of 13%. The cows were averaging 16.6 kg dry matter intake (DMI) while producing 1.62 kg milk solids (MS; fat plus protein) per day. The repeatability of the enteric methane measurements was 0.67 indicating that the enteric methane measurement is reliable. Through the partial correlations conducted, it showed that milk, MS, fat and protein yields, milk urea, live weight and DMI all have positive correlations with daily CH4 production. Therefore, it is expected that an increase in any of these traits would lead to an increase in enteric methane production. While body condition score (BCS) had a significant negative correlation with enteric methane production. This could be due to higher energy demands at a lower BCS for an animal to increase their body condition score leading to an increase in DMI. Residual enteric methane emissions were estimated through two methods: multiple regression and Irish national inventory calculations. For each method, animals were split into three groups with high, medium and low ranking of RME with 15 animals per group. The rank correlation between the two methods was 0.79 (P<0.001) showing that the two methods are able to rank animals to a similar level as each other. The low ranked animals produced between 16.2% and 6.9% less enteric methane per day than both the high and medium ranked animals. Despite this reduction in enteric methane production, there was no effect on the milk production, composition, live weight, BCS or DMI. Therefore, these low ranked animals produced less enteric methane per kg of milk solids, live weight and DMI indicating that the RME has potential be used in future strategies to reduce methane through for example breeding for lower enteric methane producing animals while not affecting the production and income of farmers.
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    Genetic and genomic studies on milk production and composition, and longevity in New Zealand dairy goats : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Animal Science at Massey University, Manawatu, New Zealand
    (Massey University, 2020) Scholtens, Megan
    The New Zealand dairy goat industry is important for producing and exporting high-quality specialised dairy products aimed at niche markets. Efforts to increase the quantity and composition of goat milk will improve profits for farmers and deliver significant economic benefits to New Zealand. However, no formal program exists for the genetic improvement of dairy goats. Therefore, the general aim of this thesis was to perform genetic and genomic studies that contribute to the design of the breeding program for New Zealand dairy goats. The first studies estimated variance components and genetic parameters of total lactation yields of milk, fat and protein, somatic cell score and longevity. The main findings suggest sufficient variation and favourable genetic correlations between these traits, supporting their inclusion into a selection index that predicts profit per animal. A random regression test-day model was then used to predict lactation curves of milk, fat, protein and somatic cell score. Using this model for genetic evaluation will enable the dairy goat industry to move from total yields into the prediction of lactation curves, enabling more accurate predictions and the opportunity of selecting for extended lactations. The first genome-wide association study of dairy goats in New Zealand was conducted using 3,732 animals genotyped with the Caprine 50K SNP chip. A highly significant region on chromosome 19 was associated with yields of milk, fat and protein, and somatic cell score, and a region on chromosome 29 was associated with somatic cell score. A prototype single-step BayesC model was developed to predict genomic breeding values and demonstrated that including genomic information into the evaluation can increase the accuracy of predictions compared to the traditional methods based on pedigrees alone, which is currently implemented in the New Zealand dairy goat industry. This thesis demonstrates that a single-step prediction model that uses genomic information would put the New Zealand dairy goat industry in a very good position to implement a genomic selection scheme. Further studies are required to define clearer breeding objectives and to systematically design a breeding program for the genetic improvement of New Zealand dairy goats.
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    Behavior changes in grazing dairy cows during the transition period are associated with risk of disease : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Animal Science at Massey University, Manawatū, New Zealand
    (Massey University, 2020) Hendriks, Stacey
    There is growing interest in the use of behavior data derived from accelerometers as a potential measure of animal health, however, research determining the optimal use of these devices and the interpretation of data derived from them, is lacking, particularly in grazing systems. The aims of this thesis were to understand: 1) data management considerations that need to be taken into account when using accelerometer devices to measure behavior in a research setting; 2) environmental and other potentially-confounding variables that can influence cow behavior and, therefore, the interpretation of behavior data; 3) ‘normal’ behavior of clinically-healthy grazing dairy cows during the transition period, and; 4) changes to behavior of grazing dairy cows experiencing varying degrees of hypocalcemia and hyperketonemia. To do this, data from 4 separate parent experiments were collated to generate a database containing detailed phenotype data, including, but not limited to, measures of cow performance (e.g., milk production and composition, body weight and body condition score), cow health (e.g., energy and protein metabolites, minerals, liver enzymes, and immune markers in blood), and cow behavior (e.g., lying behavior and activity derived from triaxial accelerometers). My review of the appropriate use of leg-mounted accelerometers to monitor lying behaviors of dairy cows indicated that applying editing criteria to remove errors in lying behavior data caused by erroneous movements of the leg (e.g., scratching and kicking) can improve the accuracy of data derived from accelerometers for recording daily lying bouts (LB); however, has little to no impact on the accuracy of lying time. Lying behavior data must be edited using a suitable LB criterion where the interest is in studying both lying time and LB. My results indicated that inclement weather, parity, and physiological state are important variables that influence behavior in their own right and must be considered in subsequent analyses. Interestingly, when comparing my results with lying behaviors previously reported in housed cows, my results indicated that grazing dairy cows engage in similar lying behaviors to housed cows before and at the time of calving, while postcalving, grazing cows spend less time lying. Furthermore, grazing dairy cows displayed greater behavioral synchrony (i.e., cows engaged in the same behaviors simultaneously) compared with reports in housed cows. These postcalving differences highlight the importance of assessing behavior within the farming system of interest. My results also indicated that cows alter their behavior in response to ill health, whereby grazing dairy cows experiencing clinical hypocalcemia (without paresis) and hyperketonemia [with severe negative energy balance (NEB)] altered their behavior before, at the time of, and after disease diagnosis compared with healthy cows. My results indicated that behavioral differences between cows classified into 3 blood calcium groups [clinically-hypocalcemic (without paresis), subclinically-hypocalcemic, and normocalcemic] were transient. On the day of calving, clinically-hypocalcemic cows (without paresis), were less active, spent more time lying, and had more frequent LB compared with subclinically-hypocalcemic and normocalcemic cows; however, changes in behavior were short lived and were no longer present by 2 d postcalving. My results indicate that observed differences in behavior associated with hypocalcemia are small and may not be biologically significant as a metric to discriminate between hypocalcemic and normocalcemic cows. On the contrary, changes in behavior over time and within cow may allow differences between hypocalcemic and normocalcemic cows to be more easily discerned than using mean values of lying behavior and activity at a specific time point. My findings indicated that a relative increase in the number of steps taken within cow compared with a baseline period 2 wk precalving was positively associated with blood calcium concentrations postcalving. Further, my results indicated the behavioral differences between cows classified into 3 energy status groups [Hi–Hi = high non-esterified fatty acids (NEFA) and high β-hydroxybutyrate (BHB); Hi–Lo = high NEFA and low BHB, and; Lo–Lo = low NEFA and low BHB] occurred up to 2 wk before calving. During the 2 wk before calving, cows identified as Hi–Hi were more active, spent less time lying, and had fewer LB than the other 2 energy status groups. Interestingly, similar to the hypocalcemia work, my results indicated that a relative increase in the number of steps taken within cow during the 2 wk before calving was associated with lower odds of developing hyperketonemia with NEB; therefore, greater increases in activity before calving were associated with improved health outcomes postcalving in both studies. My results suggest that relative changes in behavior, in particular, step activity, might be an improved metric to discriminate between clinically-healthy grazing cows and cows experiencing a subclinical metabolic disease. My research provides an improved understanding of the associations between cow behavior and health, particularly for grazing dairy cows. This information provides a base for further exploring the potential for behavior and activity measures to identify cows experiencing ill health during the transition period. Future work should focus on continuing to improve our understanding of associations between behavior and disease, particularly in grazing dairy cows. Using within-cow behavior measures and determining how these data could be interpreted so that farmers could be alerted to sick animals and make actionable decisions on farm, should be the focus of future studies.