Effects of Hemp ( <i>Cannabis sativa</i> L.) Seed Oil Press‐Cake and Decaffeinated Green Tea Leaves ( <i>Camellia sinensis</i> ) on Functional Characteristics of Gluten‐Free Crackers
Bibliographic record
Abstract
UNLABELLED: A mixture, simplex centroid, 2 components experimental design was used to evaluate the addition of hemp seed oil press-cake and decaffeinated green tea leaves, as functional ingredients to assess nutritional characteristics and antioxidant properties of gluten-free crackers. All samples with added hemp flour had much better nutritional qualities than the brown rice flour crackers in terms of higher protein, crude fibers, minerals, and essential fatty acids content. Likewise, all samples with added decaffeinated green tea leaves had much better antioxidant properties than crackers with no added green tea leaves. All crackers with added hemp flour had a significantly increased fiber content (39% to 249%) and decreased carbohydrate content (8.4% to 42.3%), compared to the brown rice flour crackers. All samples had antioxidant properties, even without the addition of green tea leaves. Optimization of the responses was conducted based on the maximized values for protein, fibers, omega-3 fatty acids content, as well as for the antioxidant activity and overall score. The suggested values for the addition of the hemp oil press-cake was 20% (total flour weight) with 4 g of decaffeinated green tea leaves that would provide protein content of 14.1 g/100 g; fibers content of 8.4 g/100 g; omega-3 fatty acids content of 3.2 g/100 g; antioxidant activity measured via 2,2-diphenyl-1-picrylhydrazyl value of 30.3 μmol TE/g d.w.; and an overall score of 8.9. This formulation has demonstrated potential application in the baking industry and marketing of these gluten-free crackers as a value-added functional product. PRACTICAL APPLICATION: Hemp seed oil press-cake as a by-product of cold-pressed oil processing and brown rice flour were used to design a functional gluten-free snack-type product-savory crackers. All crackers were high in minerals, fibers, and omega-3 fatty acids with a desirable omega-6/omega-3 fatty acids ratio. Green tea leaves were added to improve antioxidant activity, which greatly contributed to their functional properties. This qualified the crackers as a healthy snack with a minimal content saturated fatty acids and an abundance of polyunsaturated and monounsaturated fatty acids that originated from chia seeds residual oil present in the hemp flour.
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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 | 0.000 | 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) | 0.001 | 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".