Characterization of ruminal degradation, intestinal digestion and total true nutrient supply to dairy cows from feedstocks and coproducts from Canola bio‐oil processing: Impact by source origin
Bibliographic record
Abstract
The objective of this study was to characterize ruminal degradation, intestinal digestion and total true nutrient supply to dairy cows from canola feedstock (canola seeds) and coproducts (meal and pellets) from bio-oil processing which were impacted by source origin. The feedstocks and coproducts (mash, pellet) were randomly collected from five different bio-oil processing plants with five different batches of samples in each bio-processing plant in Canada (CA) and China (CH). In situ rumen degradation kinetics were determined using four fistulated Holstein cows with incubation times at 0, 2, 4, 8, 12, 24 and 48 h. Intestinal digestions were determined using the three-step in vitro method with preincubation at 12 h. The DVE/OEB and National Research Council systems were applied to evaluate the truly absorbable nutrient supply to dairy cows and feed milk values (FMVs). The results showed that in situ undegradable fractions (U) (p = 0.025) were higher in CA meals, and potentially degradable fraction of D was higher (p = 0.016) in CH meals. CH meals had higher total digestible dry matter (TDDM, p = 0.018) and intestinal digestibility of protein (dIDP, p = 0.016). Canola meals from CA had lower MREE (microbial protein synthesized in the rumen based on available rumen degradable protein; p = 0.011) and DVME (rumen synthesized microbial protein digested in the small intestine; p = 0.011) and had higher ECP (endogenous protein in the small intestine, p = 0.001) and absorbed endogenous crude protein (truly absorbed ECP in the small intestine) than CH (p = 0.001). The FMV evaluated based on the metabolic protein and net energy showed no differences between CA and CH in both coproducts and feedstocks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".