Sunroot snack bar: Optimization, characterization, consumer perception, and storage stability assessment
Bibliographic record
Abstract
Abstract This study reports the evolution of phenolics, inulin content, proximate composition, hardness, and sensory characteristics of an inulin‐rich healthy snack bar (The Sunroot Snack Bar) over 90 days of storage in refrigerated and room temperature storage. A response surface methodology (RSM) with a central composite rotatable design was first employed for optimizing the concentrations of sunroot, potato, and oats. The optimum selected concentrations of sunroot, potato, and oat were 53.99, 37.88, and 5 g, respectively, and a quadratic model was found to yield the best fit. Analysis of variance revealed that a higher sunroot content resulted in more firmness of the bar and higher overall acceptability in sensory trials. Sunroot snack bar samples without flavor (control), sunroot snack bar with cheese flavor (S1), and sunroot snack bar with olive flavor (S2) were then tested for sensory, chemical, phytochemicals, and microbial contents among control, S1, and S2 samples over a 90‐day shelf‐life study. Results showed no significant ( p < .05) changes in these contents on addition of flavor. An increase in microbial load and the appearance of a bitter taste after 30 days of fresh sunroot storage were observed. No microbial growth was observed in all sunroot snack bar samples during storage at 4°C, while some microbial growth was observed at 25°C for 90 days. It was inferred that the high‐quality shelf life of the sunroot bar was 90 days at 4°C, which was shortened to a month if the bars were preserved at 25°C. There was a significant phenolic and inulin content loss at 25°C compared with 4°C in total phenolic component. Based on the results of sensory evaluation, online questionnaire of customer experience, and cost analysis, this study successfully used sunroot tubers for the production of snack bars as a promising new raw material, which was introduced healthily with a suitable price for such product compared with other products in the market.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".