Evidence mapPaperPMID 42446774Full record

ReviewApplied biochemistry and biotechnology2026

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

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

Abstract readReview
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In one paragraph

Review in Applied biochemistry and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Shiqi YinDepartment of Occupational and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China.
Monika SharmaDepartment of Occupational and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China.
Shaden H FoudahHospitality Management Department, College of Tourism, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Sedky H A HassanDepartment of Biology, College of Science, Sultan Qaboos University, Muscat, 123, Oman.
Adel I AlalawyDepartment of Biochemistry, Faculty of Science, University of Tabuk, Tabuk, 71491, Saudi Arabia.
Ahmed Abdullah Al ZahraniMicrobiology Department, King Fahd Military Medical Complex, Dhahran, Saudi Arabia.
Yuanzhang ZhengDiscovery Biology, Curia Global Inc., Albany, NY, USA.
Aman KhanDepartment of Occupational and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China.
El-Sayed SalamaDepartment of Occupational and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China. salama@lzu.edu.cn.ORCID http://orcid.org/0000-0002-8446-0033

Funding

Fundamental Research Funds for the Central Universities lzujbky-2024-ey12
6 · The paper itself

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.

Indexed as

ApplicationAquacultureArtificial intelligenceProductionSeaweeds

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.