Associations between on-farm cow welfare indicators and productivity and profitability on Canadian dairies: II. On tiestall farms
Bibliographic record
Abstract
The use of tiestall housing for dairy cows is often criticized due to the reduced freedom of movement it offers for the animals. Maximizing comfort is especially important in tiestall farms to ensure an acceptable level of cow welfare. Motivating dairy producers to make financial investments directly aimed toward the improvement of their animals' welfare can be challenging, especially when financial returns are uncertain. The aim of this study was to evaluate the existence of associations between on-farm animal welfare and indicators of farm productivity and profitability in tiestall farms. The prevalence of animal-, resource-, and management-based welfare indicators was collected on 100 Canadian tiestall farms during a cow comfort study. Records from the dairy herd improvement agency were retrieved and used to calculate the farms' productivity and profitability measures. Univariable and multivariable linear regressions were used to assess the associations between welfare indicators and milk production, milk quality, cow longevity, and economic margins calculated over replacement costs. Increased yearly average corrected milk production was associated with longer average lying time [β = 272; 95% confidence interval (CI): 94, 450] and a higher proportion of cows fitting the tie-rail height (β = 6; 95% CI: 1, 11). Lower yearly average somatic cell count was associated with lower percentages of stalls mostly soiled with manure (β = -3.7; 95% CI: -1.9, -5.4) and a lower proportion of cows with body condition score ≤2 (β = -5.1; 95% CI: -2.3, -8.3). The average margin per cow over replacement costs was positively associated with average lying time (β = 147; 95% CI: 27, 267), percent of stall not soiled with manure (β = 7.2; 95% CI: 3.0, 11.3), and the frequency of scheduled hoof trimming per year. Some of the relationships found included interactions between animal- and management-based welfare measures. For example, the relationship between lameness prevalence and average milk production was modified through the milk production genetic index. Overall, the results show that improved cow comfort and welfare on tiestall farms is associated with increased productivity, cow longevity, and profitability when estimated through margins calculated over the replacement costs. Producers should aim to optimize all aspects of stall comfort to enhance their cows' productivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".