Natural Carotenoid Pigments of 6 Chlorophyta Freshwater Green Algae Species
Bibliographic record
Abstract
Nowadays, halal products are gaining wider recognition as a new benchmark for safety and quality assurance. As a consequence the commercial development of microalgae is established due to their high value chemicals, for examples, β-carotene, astaxanthin, phycobilin pigments and algal extracts for cosmaceutical products. Therefore, many researchers have gained interest to study the potential of microalgae as new valuable chemicals and other product sources. The aim of the research is to explore new sources of pigments to be used as halal food colorants. This quest is not only directed in finding natural alternatives for synthetic dyes, but also to discover new taxons for the carotenoid production. Thus, there is a solid need to investigate the potential of natural pigments, particularly carotenoids in microalgae to be fully utilised and commercialised especially in halal market, health advantages, food products and dye technology. A total of 6 species was evaluated for quantitative and qualitative carotenoid composition, namely, Chlorella fusca, Chlorella vulgaris, Selenastrum capricornutum, Pandorina morum, Botryococcus sudeticus and Chlorococcum sp. The main carotenoids identified in all species through HPLC analysis were lutein, β-cryptoxanthin and β-carotene. The ratio of these carotenoids varies between species. Lutein was detected substantially higher in Chlorella fusca(69.54±11.29 μg/g DW);β-cryptoxanthin in Pandorina morum species (1.24±0.33 μg/g DW) whereas β-carotene in Chlorella vulgaris (18.42±9.2 ug/g DW). The significant outcome of the research will be new findings of new natural carotenoid pigment sources as potential food colorants and bioactive compounds which can be beneficial to halal health promoting products industry.
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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 | 0.000 | 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 | 0.001 |
| 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".