Evaluation of sheep genetic resources in North America: Milk production and composition of purebred, crossbred and synthetic populations
Bibliographic record
Abstract
Purebreds, crossbreds and synthetic populations of sheep in North America of divergent genetic types produced 47–103 litres of milk for 121–144 d, consistent with "non dairy-type" breeds; however, this was substantially less than the 200–330 kg of milk per lactation characteristic of "dairy" type breeds in Europe and the Middle East countries. Among established breeds, the Suffolk (Su) breed produced significantly more total and daily milk yield, respectively, for a longer lactation (79 litres and 589 mL for 139 d), followed by the Rambouillet (Ra), Targhee (T) and Dorset (D) breeds (60–62 litres and 422–542 mL for 120–132 d), while the Lincoln (L) breed produced significantly less (48 litres and 285 mL for 128 d). Among fecund-type breeds and their crosses, Finnsheep (F) and Romanov (Ro) breeds produced significantly less (50–55 litres and 425–463 mL, for 122–129 d), while Ro × F produced significantly more milk (91 litres and 744 mL for 126 d), followed by F × Ro (60 litres and 505 mL for 128 d). Among other crossbreds, F × Ra produced significantly more milk (66 litres and 434 mL for 136 d) followed by L × Ra, L × D, F × L, F × Ra (49–60 litres and 296–385 mL for 123–136 d), while Ra × D produced significantly less (47 litres and 245 mL for 121 d). Among multiple breed composite populations, the Outaouais (O) and Rideau (R) Arcott breeds and their crosses had the highest milk production, e.g., R and R × O produced significantly more milk (95–103 litres and 754–820 mL for 131–144 d) than O and O × R (74–80 litres and 621–693 mL for 124–142 d). Concurrently, Synthetic I (½ F, ½ L) produced significantly less (58 litres and 494 mL for 134 d), while Synthetic III (¼ F, ¼ L, ¼ D, ¼ Ra) produced significantly more milk (91 litres and 673 mL, P > 0.05, for 130 d), and Synthetic II (½ D, ½ Ra) was intermediate (74.8 litres and 621 mL for 129 d); however, lactation length was consistent. Sheep breeds in North America exhibited diversity that was substantial for milk yield, but negligible for lactation length, as well as fat, protein, lactose and solid-not-fat content. Lack of inherent potential for milk production continues to be a serious constraint towards development of commercial dairy sheep industry. In the absence of "dairy-type" breeds, superior milk production in the Rideau Arcott breed (with East Friesian lineage) and their crosses demonstrates considerable promise for further improvement, thus increasing the efficiency of sheep production. Key words: Milk yield and composition, sheep breeds, synthetic sheep, Arcott breeds
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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 | 0.000 | 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 | 0.000 | 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 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".