Physicochemical compositions, nutritional and functional properties, and color qualities of sorghum–orange‐fleshed sweet potato composite flour
Bibliographic record
Abstract
Abstract Sorghum and orange‐fleshed sweet potato (OFSP) flours were blended to produce composite flours at eight different ratios of 90:10, 80:20, 70:30, 60:40, 50:50, 40:60, 30:70, and 20:80, respectively, whereas 100% sorghumflour was used as control. The physicochemical compositions, nutritional and functional properties, as well as color attributes of the composite flour blends were evaluated. The acquired data were analyzed using ANOVA, and the means were separated using the Duncan multiple range test. Significant differences ( p < .05) were observed in the physicochemical and nutritional properties of the flour blends. The protein levels in the composite flour decreased as the proportion of OFSP flour increased. However, the levels of vitamins, particularly vitamins A and C contents of the composite flours increased with higher proportions of OFSP, ranging from 0.27 and 1.74 mg/100 g in sample S 100 to 2.13 and 2.12 mg/100 g in sample S 20 O 80 , respectively. In contrast, an increase in the percentage of OFSP flour resulted in a decrease in the contents of vitamin B‐complex, particularly vitamins B 2 and B 6 . These values decreased slightly from 0.19 and 1.98 mg/100 g in sample S 100 to 0.16 and 0.03 mg/100 g in sample S 20 O 80 , respectively. Furthermore, as the proportion of OFSP flour increased, there was a reduction in the calcium levels from 17.39 mg/100 g in the 100% sorghum sample to 13.52 mg/100 g in the S 20 O 80 sample. However, no particular trend was observed in, magnesium, iron, and phosphorus levels. Sample S 50 O 50 had the highest percentage of essential and conditional amino acids, except for cysteine, valine, and phenylalanine. The findings also revealed significant variations ( p < .05) in the composite flour samples' functional properties and color measurements. Substituting sorghum with OFSP in sorghum‐based food products would significantly increase their vitamin A content.
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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 | 0.001 | 0.001 |
| 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".