Impact of Housing and Management on Production, Behavior, and Welfare of Dairy Cows in Automatic Milking Systems
Why this work is in the frame
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Bibliographic record
Abstract
The overall objective of this research was to determine the impact of Automatic Milking System (AMS) housing and management practices on cow production, behavior, and welfare of Holstein dairy cows. The first objective was to identify factors at the farm and cow level associated with lameness on AMS farms through decision tree analysis to allocate probabilities to each input. Results indicated this novel multifactorial approach of data analysis enabled us to highlight critical points that can be focused on to lessen cow-level complications or enhance farm-level housing and management practices to reduce the incidence and severity of lameness in AMS farms. Classifiers were identified based on the decision tree classification model of 1378 data points from 36 AMS farms across Michigan and Canada. The primary classifier was identified as the type of stall base, specifically sand, rubber, or geotextile mat with the highest class membership (CM=976). The secondary classifier was the quantity of bedding, divided by the cows standing on 2 cm (CM=456) or(CM=520) of bedding. The body condition score (BCS) cow fit stall width were identified as the tertiary classifier. Cows with BCS of 3.25 to 4.5 (CM=307) were defined as non-lame with an estimated probability (EP) of 0.59, while cows with BCS of 2 to 2.5 (CM=213) were further divided by the presence of hock lesions. Cows without lesions were defined as non-lame (EP = 0.93) and cows with lesions were defined as lame (EP=0.07). Cows that fit the stall width were defined as non-lame (EP=0.66), and cows that did not fit were further divided by the width of the feed alley. Farms with ≥430 cm feed alley were defined as non-lame (EP=0.89), whereas farms with(EP=0.11). These findings suggest various cow and farm-level factors can influence the incidence of lameness in AMS farms, with specific factors, having a larger impact than others.\nThus, leads to the second study that evaluates the impact of changes in milking permission permits on dairy cow production, behavior, and welfare as an indicator of stress. The objective of this study was to determine the impact of a decrease in milking permission from milking every 4 h to every 6 h on DIM 100 on cow performance and behavior. Twenty-four Holstein dairy cows were separated into two groups balanced for the lactation stage. Six cows were randomly assigned to one of four treatment groups: PC (primiparous control: cows in 1st lactation with no change in milking permission), PT (primiparous treatment: cows in 1st lactation and milk permission transitioned on DIM 100), MC (multiparous control: cows in ³2nd lactation with no change in milking permission), MT (multiparous treatment: cows in ³2nd lactation and milk permission transitioned on DIM 100). We discovered an impact of milking transition on tail swishing (P = 0.049), displacement behavior (P = 0.041), and total time spent inside the CP (P = 0.009). The change in milking permission also revealed longer AMS time (P = 0.041), higher stepping frequencies (P = 0.031), and extended AMS exit durations (P = 0.001) while cows were inside the milking robot. Heart rate variability (HRV) parameters showed elevated stress levels while waiting in the CP and inside the milking stall. Milking transition also influenced daily lying times (P = 0.030), lying bout durations (P = 0.010), lying frequencies (P = 0.010), and inactive standing time (P = 0.029). However, no effect of change in milking permission was observed in daily milk production, but multiparous (MU) cows produced more milk/day than primiparous (PR) cows (P = 0.021). These results suggest that a decrease in milking permission and cow parity affected various cow behaviors, HRV parameters, and overall cow activity, thus demonstrating increased stress in cows after the milking transition. In conclusion, mapping of risk factors associated with lameness can allow AMS farmers to make appropriate housing and management adjustments and mitigate cow level factors to reduce risk of lameness and maximize AMS efficiency. While changes in milking permission can impact cow behavior and welfare in farms with AMS. Therefore, this thesis focused on AMS farm management and housing factors that influence the prevalence of lameness, cow performance, behavior, and welfare.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it