A Sustainable Alternative: Violet Pigment from Streptomyces DP6 for Textile Applications
Bibliographic record
Abstract
Introduction: The environmental impact of synthetic dyes have sparked interest in eco-friendly, biodegradable, non-toxic natural colorants. Microbial pigments hold considerable potential for applications in industries such as textile, food, and pharmaceuticals. In this study, a violet pigment producing Streptomyces violaceoruber strain DP6 was isolated, characterized and explored for its use in fabric dyeing. Materials and Methods: Strain DP6 was isolated from a soil sample collected from Dalhousie, Himachal Pradesh, India. The strain producing a violet pigment was characterized using morphological, cultural, chemotaxonomic, and 16S rRNA sequencing methods. Various physical parameters were studied to obtain the maximum yield of the extracellular pigment. Dyeing potential of the pigment was evaluated on silk and wood fabrics. Further, pigment was purified and characterized. Results: Optimum pigment production was achieved when DP6 was cultivated for 10 days in ISP5 medium (International Streptomyces Project), at an initial pH of 5.0-5.5, with 2% inoculum, and incubated at 30oC under shaking conditions (160 rpm). The violet pigment was extracted using ethyl acetate and was found to be highly sensitive to changes in pH and sunlight. The dyeing ability of the violet pigment, produced under optimized conditions was evaluated on wool and silk fabrics. The color yield was observed to be better on wool as compared to silk. Additionally, mutagenicity tests confirmed the non-mutagenic nature of the pigment. Purification and preliminary characterization suggested that the pigment may possess an anthraquinone type structure with a methoxy group. Conclusions: The study results indicate that the violet pigment from Streptomyces DP6 hold potential to be exploited as a safe dye for use in the textile industry.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".