339 Effect of varieties and tannin levels (low and normal) on the physicochemical and nutritional characterization of faba bean grown in western Canada.
Bibliographic record
Abstract
The aim of this study was to evaluate the impact of varieties and tannin levels on physicochemical and nutritional characteristics of faba beans as alternative protein and energy source for ruminants. Eight varieties with 2 tannin levels (low vs. normal) grown in 3 locations in western Canada were analyzed. Chemical analyses were performed following the Association of Official Analytical Chemists (AOAC) standard methods, bioenergy values at maintenance and production levels were determined using NRC-2001. The experimental design was RCBD (varieties as fixed effect and locations as random block). MIXED model procedure of SAS 9.4 was used for statistical analyses with significance declared at P < 0.05. SAS contrast was used to compare low tannin and normal tannin varieties. Results showed there were no different in dry matter (DM), protein (CP), carbohydrates (CHO), and fiber content (NDF) with averages 93, 28, 68 and 18% DM, respectively. Ash, starch, and non-structural carbohydrates (NSC) were higher (P < 0.05) in low tannin varieties (LT) while organic matter (OM) and lignin were greater (P < 0.05) in normal tannin varieties (NT). Soluble crude protein (SCP) was highly significant different (P < 0.01) in LT compared to NT (21% vs. 18%). The rapidly degradable protein fraction (PA2) showed high significant difference (P < 0.01) in LT compared to NT (74% vs. 62%) while the later showed a higher mean (P < 0.01) on slowly degradable protein fraction (PB2) compared to LT (8% vs. 5%); the mean value of intermediately degradable protein fraction (CB1) was significantly higher (P < 0.05) on LT. No significant difference (P>0.10) was observed on total digestible nutrients (TDN1x), metabolizable protein (MP), rumen degraded protein balance (DPB), and feed milk value (FMV). Even when results showed difference on physicochemical characteristics among seeds, the predicted animal performance and production was not different. These outcomes suggest that faba beans can be use as nutritive ingredient for ruminant diets without a significant tannin level effect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".