Decorticated and non-decorticated BARI lentil varieties: An ample source of essential nutrients, minerals and bioactive compounds
Bibliographic record
Abstract
• The study highlights the decortication and non-decortication process of BARI lentil varieties. • Non-decorticated (peel) lentil provides an abundant source of bioactive compounds. • People should consume mycotoxin-free non-decorticated lentils. • The non-decorticated lentils were more accepted by the sensory evaluators. BARI lentils play an important role in Bangladesh for providing essential nutrients to combat micronutrient malnutrition. Hence, the objective of the study was to explore the nutritional, mineral, and bioactive compounds analysis of the selected varieties under different milling conditions. Results exhibited that a significant number of bioactive compounds such as ascorbic acid (15.29 mg/100 g), ß-carotene (142.16 mg/100 g), total carotenoid (67.49 mg/100 g), anthocyanin (1.35 mg/100 g), and total phenolic compounds (20.72 mg GAE/100 g) were plentiful in non-decorticated lentil. In contrast, the non-significant amount of ascorbic acid (4.52 mg/100 g), ß-carotene (64.65 mg/100 g), total carotenoid (11.65 mg/100 g), anthocyanin (0.65 mg/100 g), and total phenolic compounds (11.68 mg GAE/100 g) was found in decorticated lentils. Non-decorticated lentils possessed the highest amount of crude protein (29.63 %), crude fiber (14.12 %), Ca (3.55 %), Mg (1.11 %), Fe (219.00 ppm), and Zn (32.62 ppm). A non-significant difference was noted between cooked decorticated and non-decorticated lentils during organoleptic taste by the sensory evaluators. Apart from this, the most instructive findings are, to utilize non-decorticated lentils that will contribute to minimizing the broken loss (cracked loss) and milling cost of the farmers without any presence of ochratoxin and patulin.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".