Economic feasibility of incorporating pea coproducts in a Manitoba cow-calf operation
Bibliographic record
Abstract
Low-cost feeds that fulfill the nutritional needs of cattle are critical to the profitability of livestock operations. Feed, accounting for 50-60% of total production costs, is the primary expense associated with most livestock operations. Byproducts can be an inexpensive addition to livestock feeds, often possessing nutritional value comparable to the original feed source. The Roquette Pea Protein plant in Portage La Prairie, Manitoba produces 500 tons of pea protein per day, generating three different byproducts with potential for incorporation into cattle diets: pea hulls, pea cream and pea screenings. This research developed and evaluated six different over-winter cow-calf feeding systems incorporating pea screenings. The objectives of this research were to: (1) compare the quantity of pea screenings or barley needed to meet the energy requirements of a 1300lb cow in the third trimester of pregnancy, feeding grass legume hay, grass, or straw-based diets during the 90 day over-winter period; (2) compare the cost of the three forage-based rations when supplemented with either barley or pea screenings; and (3) determine the price at which rations containing pea screenings are equivalent in cost to (i.e. break-even with) the three conventional barley-based rations. Price data on the traditional feed ingredients were approximate ten-year averages while pea screenings price was assumed to be 75% of the long-term average price for field peas. All six rations were nutritionally balanced by the Beef Cattle Nutrient Requirements Model 2016 (NRC 2016). Results demonstrate that pea screenings are slightly lower in TDN than barley (80% vs 84%) and can be incorporated as an energy supplement at a slightly higher inclusion rate in Manitoba cow-calf winter rations during the third trimester of pregnancy. Breakeven analysis revealed nine separate pea screening prices where the cost of each alternative ration was comparable with each conventional ration. Findings further suggest that pea screenings price may need to decrease from $176.46/ton to as low as $58.17/ton to incentivize cow-calf producers currently feeding a ration of barley straw supplemented with barley grain to switch to a ration of grass legume hay supplemented with pea screenings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".