Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Multi-applications and Aquaculture of Seaweeds: Environmental Improvement, Health Benefit, and Sustainable Valorization with Integrated Artificial Intelligence.

Created on 14 Jul 2026

Authors

Shiqi Yin, Monika Sharma, Shaden H Foudah, Sedky H A Hassan, Adel I Alalawy, Ahmed Abdullah Al Zahrani, Yuanzhang Zheng, Aman Khan, El-Sayed Salama

Published in

Applied biochemistry and biotechnology. Jul 14, 2026. Epub Jul 14, 2026.

Abstract

Environmental and human health applications of seaweeds (SWs) have received attention in recent years. However, previous reviews lack of covering SWs from cultivation to their various applications, along with the integration of artificial intelligence (AI). Thus, this review introduces SWs identification and aquaculture techniques, including onshore, nearshore, offshore, and integrated multi-trophic aquaculture (IMTA) to promote sustainable knowledge in SWs. Composition, properties, and applications are discussed to improve resource availability for various purposes (such as wound dressings, biofilms, and cosmetics). The development of AI (such as SWs classification and identification, nutrient determination, growth prediction, and ecological restoration) is discussed. Green (e.g., Ulva) and red SWs (e.g., Gracilaria) were widely reported in IMTA systems, achieving nitrogen and phosphorus removal rates of 74% and 72%, respectively. SWs extracts for animals and plants promoted the physiological functions (stress resistance, antioxidant, and metabolic activity). Genetic engineering shows potential in improving SWs traits. CRISPR technology exhibited a mutation efficiency of nearly 70% (Ectocarpus sp.). AI, based on computer vision and machine learning, is a useful technique that can provide profound insights for futuristic approaches. The safe transformation of SWs from potential value to practical applications also requires effective technologies to remove contaminants and establish relevant limit standards.

PMID:
42446774
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 3
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement