Seaweed farming: A perspectives of genetic engineering and nano-technology application

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TL;DR

This review examines how nanotechnology and genetic engineering can address key challenges in large-scale seaweed cultivation, including disease control, biofouling, and low yields. Nanomaterials offer potential for water purification, pathogen detection, and improved nutrient delivery, while genetic techniques like selective breeding, mutagenesis, protoplast fusion, and transformation could enhance growth rates and stress tolerance. The authors call for coordinated multidisciplinary research combining computational tools, remote sensing, and biotechnological innovations to make seaweed farming economically and environmentally sustainable.

Full summary

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**Background:** Seaweed (macroalgae) cultivation has grown significantly and now accounts for 51.3% (34.7 MMT wet weight) of all marine aquaculture worldwide, with China and eight other Asian nations producing 99.6% of the total. Seaweed is more productive (1600 g C m⁻² year⁻¹) than terrestrial plants (470 g C m⁻² year⁻¹) and can contribute to multiple UN Sustainable Development Goals including zero hunger (SDG2), good health (SDG3), affordable clean energy (SDG7), climate action (SDG13), and life below water (SDG14). However, large-scale sustainable cultivation faces persistent challenges including disease susceptibility, seed mortality from extreme weather and pollution, biofouling, and logistical difficulties in site selection. This review explores how nanotechnology and genetic engineering can address these barriers.

**Methods:** The authors conducted a narrative review of the literature on innovative technologies in aquaculture, focusing on nanotechnology applications and genetic engineering strategies for macroalgae. They examined published studies on nanoparticle use in seaweed systems, breeding techniques (selective breeding, mutagenesis, protoplast fusion, genetic transformation), and emerging computational tools (remote sensing, computational fluid dynamics, numerical modeling).

**Key Results:** Nanotechnology applications in seaweed farming include nanosensors for detecting pathogens and pollutants, nanoparticles for water purification and biofouling control, and nanomaterials for nutrient and medication delivery. Specific examples include: Ni–Cu/TiO2/Ti electrodes as nanostructure sensors for glucose in Ulva lactuca; magnetic nanoparticles (Fe2O3, zero-valent nano iron) that significantly increase growth and biochemical composition at adequate doses; and Ag and Au nanoparticles showing antibiofilm activity against marine bacteria like A. hydrophila, Salmonella sp., and S. liquefaciens. However, adverse effects are documented: nAl₂O₃ inhibited Dunaliella salina growth with decreased chlorophyll and carotenoid levels; ZnO nanoparticles are highly cytotoxic at low concentrations; and water-soluble NPs can accumulate in aquatic food chains.

In genetic engineering, selective breeding has been successfully applied to Porphyra (Rhodophyta), Laminaria (Phaeophyceae), Saccharina, and Undaria, but not yet to agarophytes, carragenophytes, or green seaweeds. Since 1949, only 30 Porphyra cultivars have been created. Chemical mutagens (e.g., EMS) have been used in Gracilaria tikvahiae, and physical mutagens (gamma rays) in Ectocarpus siliculosus and Ulva compressa. Protoplast fusion between Gracilaria tikvahiae and G. chilensis produced bicolor chimera seedlings, and fusion between Gayralia oxysperma and Ulva reticulata generated variants with superior agronomic traits. Genetic transformation has been achieved via electroporation (Neopyropia yezoensis with CaMV 35S promoter and GUS marker), microparticle bombardment (Gracilaria changii with SV40 promoter and lacZ), glass bead agitation (NeoPorphyra haitanensis), and particle bombardment (Undaria pinnatifida, Ulva australis). The CaMV 35S promoter has shown functionality in Chondrus, Gracilaria changii, Kappaphycus alvarezii, and Wildemania miniata.

Emerging methods include remote sensing using multispectral Landsat data, MODIS imagery, and Google Earth Engine for monitoring kelp canopies and tracking Ulva prolifera blooms. Computational fluid dynamics (CFD) models have been used to predict nutrient flow and optimize farm designs. Numerical models like MACMODS (Macroalgal Cultivation Modeling System) evaluate within-farm fluctuations in sunlight, salinity, flow, and nutrients.

**Clinical Implications:** This is not a clinical study; it is a narrative review focused on aquaculture and biotechnology. The implications are primarily agricultural, environmental, and economic rather than clinical. The authors emphasize that genetically engineered algae research is largely restricted to accredited labs, with regulatory oversight from bodies like the US EPA under the Toxic Substances Control Act. Public acceptance remains uncertain due to limited awareness. The review concludes that continuous innovation in seaweed farming is needed to address global climate change and rising demand for food, fuel, and bio-products.