Effect of Drying Method and Sugar Type (Sucrose, Glucose, and Fructose) on the Concentration and Stability of Phycocyanin During Storage
Bibliographic record
Abstract
Phycocyanin is a major water-soluble pigment derived from Spirulina, valued for its strong antioxidant activity and potential as a natural food colorant. However, its stability is influenced by factors such as temperature, light intensity, and pH. This study investigated the impact of different drying methods (freeze-drying, oven-drying, and spray-drying) and different sugar concentrations (glucose, fructose, and sucrose) on the stability of phycocyanin extracted from Spirulina platensis. Additionally, the effect of storage duration (up to 120 days in 15-day intervals) on pigment stability was assessed. Results showed that Freeze-drying resulted in significantly higher phycocyanin concentration and stability than oven and spray drying (p<0.05). Among the treatments, freeze-drying with sucrose yielded the highest pigment retention (p< 0.05). Furthermore, sugar-treated samples demonstrated greater pigment preservation than sugar-free samples, with sucrose outperforming glucose and fructose in all drying methods tested. Overall, the stability and concentration of phycocyanin decreased over time during storage. The degradation kinetics followed a second-order model, with thermal degradation constants decreasing as pH and fructose concentration increased but increasing with temperature. Moderate fructose levels extended the pigment half-life, whereas excessive amounts reduced it. These findings suggest that freeze-drying combined with sucrose addition is the most effective strategy for enhancing phycocyanin stability during storage.
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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 | 0.000 |
| 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".