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
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Date
2020
DOI
Open Access Location
Authors
Hendriks, Stacey
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Massey University
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Abstract
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.
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Keywords
Dairy cattle, Behavior, Monitoring, Parturition, Health, Grazing, Accelerometers