Evaluation of the Physicochemical, Nutritional, Textural, and Sensory Characteristics of Extrudates From Sorghum and Orange‐Fleshed Sweet Potato Flour Blends
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study is aimed at producing extrudates using sorghum and orange‐fleshed sweet potato (OFSP) flour in varying ratios (90:10, 80:20, 70:30, 60:40, 50:50, 40:60, 30:70, and 20:80), with extrudates made from 100% sorghum serving as the control. The puffed snacks’ physicochemical, nutritional, textural, and sensory qualities were assessed, and the obtained data were analyzed through ANOVA. Our findings revealed notable variations in the physicochemical properties of the puffed snacks, showing a decrease in moisture, fat, protein, and crude fibre content as the percentage of OFSP flour increased. Furthermore, increased substitution of sorghum flour with OFSP in the extrudates led to a corresponding rise in vitamin A, B 1 , and C levels from 0.24, 0.15 and 0.21 mg/100 g in the control to 1.30, 0.19, and 1.82 mg/100 g in the extrudates made from 20% sorghum. More so, samples with increased OFSP content were preferred regarding springiness, chewiness, gumminess, and cohesiveness, whereas those with elevated percentages of sorghum received higher likeness for adhesiveness and stringiness. Extruded samples containing 80% and 90% sorghum levels received the highest overall acceptance ratings of 7.15 and 7.18, respectively. The research results are essential for the food industry to produce nutritious extrudates with appealing sensory characteristics and textures.
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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 | 0.001 | 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 | 0.001 |
| 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 it