Financially Optimal Culling Strategies for Western Canadian Cow-Calf Producers
Bibliographic record
Abstract
Canadian cow-calf producers often experience slim margins and focus on reducing costs to maximize their economic profit. This study aims to identify financially optimal breeding female culling strategies using production and financial data from 16 ‘typical farms’ in the Canadian Cow-Calf Cost of Production Network (COP Network). Managing the breeding herd inventory composition through culling and replacement decisions impacts the future cashflows and the value of the herd. Average values from 16 ‘typical farms’ in the COP Network were used to generate four farms with combinations of high and low costs and productivity. Four culling scenarios were looked at in this thesis; the base scenario does not account for wean weight differences based on dam age. Scenarios 1 through 3 vary wean weight based on dam age using the Beef Improvement Federation (2002) factors and price slide adjustments. Replacements come from home-raised heifer calves (Scenario 1 and 3) or purchased bred heifers (Scenario 2). Using these culling and replacement scenarios a net present value (NPV) model is converted to an equivalent annual annuity (EAA). The enterprise profitability analysis assesses the cash flow and returns on assets (ROA) for the cow-calf and home-raise heifer enterprises and whole farm business in three scenarios (1 through 3). This analysis considers the depreciation of breeding females over their productive life, assessing the cash flow and ROA impact of different culling decision rules. When evaluating the ROA, depreciation is considered when calculating the accrual net income. Depreciation is a significant cost when looking at accrual-based income, which is the proper way to measure financial performance when considering investment alternatives. By reducing breeding stock depreciation through lowering heifer development costs, farms can positively impact the net income of the enterprise. The EAA model shows greater EAA valuation for home-raised bred heifers over open females. The enterprise ROA model found the home-raised heifer enterprise to be profitable for the majority of farms. The whole farm business was the most profitable for these same farms, suggesting home-raised bred heifers are more profitable than purchasing bred heifers priced at the Alberta 5-year average price of $1978/hd (CanFax, unpublished data). These models provide a financial perspective on the optimal culling decision based on a farm's costs and productivity, as well as the source of replacements (home-raised or purchased).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".