Effect of lentil flour incorporation on the sensory, nutritional, and functional properties of noodles
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This study focuses on the development and evaluation of lentil-infused noodles as a nutritious and functional food alternative for health-conscious consumers. Various formulations of lentil flour (10%, 20%, 30%, and 40%) were combined with wheat flour to produce lentil-enriched noodles. The sensory attributes, nutritional composition, functional properties, and storage stability of these noodles were assessed. Sensory evaluation revealed that the formulation with 30% lentil flour (LIN-30) had the highest acceptability, particularly in terms of flavor and texture. Proximate composition analysis showed that LIN-30 had significantly higher protein (15.84 g/100 g) and fiber (3.14 g/100 g) content compared to control wheat noodles. Additionally, LIN-30 exhibited a moderate glycemic index of 60.57 ± 0.07, making it suitable for individuals looking to manage blood sugar levels. In vitro protein digestibility was also favorable, with a digestibility rate of 72.59 ± 1.12%. The mineral content of LIN-30 was enriched, showing higher levels of iron, zinc, and manganese than the control noodles. Texture profile analysis revealed that LIN-30 had good firmness and elasticity, although slightly lower than that of control noodles. Furthermore, LIN-30 demonstrated good storage stability, maintaining its nutritional and sensory properties over a three-month period. Overall, lentil-infused noodles, especially the LIN-30 formulation, offer a promising, affordable, and nutritious option for individuals seeking healthier noodle alternatives.
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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 | 0.000 |
| 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 it