Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1016/j.jclepro.2026.149382 |
Lizenz  |
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| Titel (primär) | Machine learning-based integration of plant growth regulators and overcompensation enhances microalgal protein production from wastewater |
| Autor | Li, G.; Gong, J.; Xiao, W.; Zhang, W.; Huang, Z.; Yao, X.; Yang, Y.; Gontard, N.; Lyu, T.; Pan, M. |
| Quelle | Journal of Cleaner Production |
| Erscheinungsjahr | 2026 |
| Department | MIBITECH |
| Band/Volume | 576 |
| Seite von | art. 149382 |
| Sprache | englisch |
| Topic | T7 Bioeconomy |
| Supplements | Supplement 1 |
| Keywords | Microalgal protein; Overcompensation; Plant growth regulator; Machine learning; Wastewater valorization |
| Abstract | Photoautotrophic
wastewater valorization represents a sustainable route for
carbon-neutral nutrient upcycling into bioproducts. However, its
practical implementation is often constrained by wastewater-induced
growth inhibition. Besides, the distribution of metabolic flux across
competing pathways may further restrict nutrient allocation towards
target product. In this study, we propose a combined strategy
integrating plant growth regulators (PGRs) with a nitrogen
overcompensation strategy to enhance microalgal performance during
potato starch wastewater treatment. Gibberellic acid (GA3) and naphthaleneacetic acid (NAA) both alleviated wastewater inhibition and enhanced nutrient recovery in Chlorella pyrenoidosa, achieving up to 79.9% total nitrogen removal. Notably, supplementation with 10 mg L−1 GA3
resulted in a 26.2% increase in biomass compared to controls. The
random forest model identified candidate high-response concentrations of
approximately 10.5 ± 1 mg L−1 for GA3 and 10.2 ± 1 mg L−1 for NAA and suggested declining biomass responses at higher NAA concentrations, whereas GA3
showed a broader model-predicted growth-promoting range. Under the
nitrogen starvation–repletion condition, PGR-supplemented cultures
achieved maximum biomass and protein concentrations of up to 1.58 g L−1 and 594.82 mg L−1,
respectively, together with over 90% removal of COD, total phosphorus,
and ammonium. Transcriptomic profiling indicated that GA3
induced significant upregulation of genes involved in photosynthetic
apparatus function, ribosomal biogenesis, and transmembrane transport
processes compared to NAA. This work establishes a strategy that
integrates PGRs with nitrogen overcompensation to overcome
wastewater-induced stress. The proposed approach provides a practical
strategy for improving microalgal productivity and nutrient recovery
from high-strength wastewater, advancing the development of
carbon-neutral biorefinery systems. |
| Li, G., Gong, J., Xiao, W., Zhang, W., Huang, Z., Yao, X., Yang, Y., Gontard, N., Lyu, T., Pan, M. (2026): Machine learning-based integration of plant growth regulators and overcompensation enhances microalgal protein production from wastewater J. Clean Prod. 576 , art. 149382 10.1016/j.jclepro.2026.149382 |
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