Chemical Characterization of Hemp (<i>Cannabis sativa</i> L.)-Derived Products and Potential for Animal Feed
Why this work is in the frame
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Bibliographic record
Abstract
Hemp ( Cannabis sativa L.)-derived products are not approved as feed ingredients in Canada. This study aims to provide detailed chemical characterization of hemp seed (HS)-processing products to support regulatory approval of their potential use as animal feed. Eight cold-pressed derivatives of HS including HS hulls (HH), dehulled HS, HS oil (HO), and HS cake/meal (HC/HM) were analyzed for nutritional, antinutritional, and cannabinoid contents. Although crude protein (CP) was lower ( P < 0.0001) in HH (15.7 ± 2.96%) compared to other proteinous derivatives (>20%), all fractions were rich in amino acids. Neutral detergent fiber was highest ( P < 0.0001) in HH (58.8 ± 4.77%) and lowest in dehulled HS (2.99 ± 4.77%). However, their energy values in poultry and swine were comparable to HC/HM and coarse HS protein. All fractions, except HO, are rich in macro- and microminerals. Antinutritional factors including heavy metals, nitrate, and Δ9-tetrahydrocannabinol were below the maximum allowable residual levels in food/feed [ CFIA Canadian Food Inspection Agency. Rg-8 Regulatory Guidance: Contaminants in Feed (Formerly Rg-1, Chapter 7), 2017 . https://inspection.canada.ca/animal-health/livestock-feeds/regulatory-guidance/rg-8/eng/1347383943203/1347384015909?chap=0 (Accessed October 20, 2023), Commission Regulation EC Setting Maximum Levels for Certain Contaminants in Foodstuffs, 2006, https://extwprlegs1.fao.org/docs/pdf/eur68134.pdf (Accessed October 11, 2020), and EFSA EFSA J. 2015, 13 (6), 4141 ]. In summary, all HS-derived fractions are nutritionally favorable to serve as potential animal feed ingredients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| 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 it