Multi-scale modeling of intensive macroalgae cultivation and marine nitrogen sequestration

Effects of season, depth and pre-cultivation fertilizing on Ulva growth dynamics offshore the Eastern Mediterranean Sea

Offshore macroalgae production could provide an alternative source of biomass for food, materials and energy. However, the offshore environment in general, specifically the Eastern Mediterranean Sea (EMS) offshore, is a high energy and low nutrients environment, thus challenging for macroalgae farming. In this study, we experimentally investigated the impact of season, depth, and pre-cultivation fertilization duration on the growth rates and chemical composition of offshore Ulva biomass, and developed a predictive model tailored to offshore conditions, capable of estimating both biomass growth rate and nitrogen content. Specifically, we measured Ulva biomass growth rate and internal nitrogen in the nitrogen-poor EMS a few kilometers offshore the Israeli coast at various depths and on-shore pre-cultivation fertilization schedules. Based on these data, we constructed a predictive cultivation model of Ulva offshore growth, which allows for the optimization of fertilization requirements for offshore cultivation. This study provides new insights on the effects of seasonality, depth, and pre-cultivation fertilization duration on growth rates and chemical composition of offshore Ulva sp. biomass production.

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

In order to meet the growing demand for resources, there is a rising interest in macroalgae cultivation worldwide due to their potential as a source of food, fuel, and bio-products. However, large-scale and sustainable seaweed cultivation has been a persistent challenge. Specific fundamental issues need to be addressed to maximize the benefits of seaweed production. This article reviews a plan for transitioning to an environmentally sustainable aquaculture system incorporating non-toxic nanoparticles. It also provides an overview of genetic enhancement techniques for macroalgae species to realize their potential fully. Additionally, the article discusses the need for advanced tools and concepts to overcome the challenges in seaweed identification and cultivation and emphasizes the importance of a coordinated effort in fundamental and applied research using emerging technologies to ensure long-term practicality.

From model organism to application: Bacteria-induced growth and development of the green seaweed Ulva and the potential of microbe leveraging in algal aquaculture

The marine green macroalga Ulva (Chlorophyta, Ulvales), also known as sea lettuce, coexists with a diverse microbiome. Many Ulva species proliferate in nature and form green algal blooms ("green tides"), which can occur when nutrient-rich wastewater from agricultural or densely populated areas is flushed into the sea. Bacteria are necessary for the adhesion of Ulva to its substrate, its growth, and the development of its blade morphology. In the absence of certain bacteria, Ulva mutabilis develops into a callus-like morphotype. However, with the addition of the necessary marine bacteria, the entire morphogenesis can be restored. Surprisingly, just two bacteria isolated from U. mutabilis are sufficient for inducing morphogenesis and establishing the reductionist system of a tripartite community. While one bacterial strain causes algal blade cell division, another causes the differentiation of basal cells into a rhizoid and supports cell wall formation because of a low concentration of the morphogen thallusin (below 10^-10 mol/L). This review focuses on the research conducted on this topic since 2015, discusses how U. mutabilis has developed into a model organism in chemical ecology, and explores the questions that have already been addressed and the perspectives that a reductionist model system allows. In particular, the field of systems biology will achieve a comprehensive, quantitative understanding of the dynamic interactions between Ulva and its associated bacteria to better predict the behavior of the system as a whole. The reductionist approach has enabled the study of the bacteria-induced morphogenesis of Ulva. Specific questions regarding the optimization of cultivation conditions as well as the yield of raw materials for the food and animal feed industries can be answered in the laboratory and through applied science. Genome sequencing, the improvement of genetic engineering tools, and the first promising attempts to leverage macroalgae-microbe interactions in aquaculture make this model organism, which has a comparatively short parthenogenetic life cycle, attractive for both fundamental and applied research. The reviewed research paves the way for the synthetic biology of macroalgae-associated microbiomes in sustainable aquacultures.

Brown Macroalgae (Phaeophyceae): A Valuable Reservoir of Antimicrobial Compounds on Northern Coast of Spain

The search for new sources of antimicrobial compounds has become an urgent need, due to the threat that the spread of bacterial resistance represents for global health and food safety. Brown macroalgae have been proposed as a great reservoir in the search for novel antimicrobial compounds. In this study, mid-polarity extracts were performed with a selection of 20 brown macroalgae species from northern Spain. The total polyphenol, carbohydrate and protein contents were quantified by spectrophotometry. The volatile organic compounds (VOCs) of whole macroalgae were also studied as a biomarker of their metabolic state in the representative species of the tested families by gas chromatography-mass spectrometry (GC-MS). The antimicrobial potential of the extracts was assessed by a disk diffusion assay against 20 target bacteria and further determinations of the minimum inhibitory (MIC) and minimum bactericidal concentrations (MBC) were performed by a microdilution assay for the active extracts. Ericaria selaginoides, Bifurcaria bifurcata and Dictyota dichotoma showed an antimicrobial effect against six Gram-positive strains: Bacillus cereus, Bacillus subtilis, Geobacillus stearothermophilus, Listeria monocytogenes, Staphylococcus aureus and Staphylococcus haemolyticus. The phenolic content was generally higher in the extracts that showed antimicrobial activity, followed by carbohydrates and low contents of proteins. The results obtained in this study reveal the potential of brown macroalgae as a promising alternative source of antimicrobial compounds as functional ingredients for the application in industrial fields.

Photosynthetic Characteristics of Macroalgae Ulva fasciata and Sargassum thunbergii in the Daya Bay of the South China Sea, with Special Reference to the Effects of Light Quality

The changes in underwater light in field usually occur not only in intensity but in spectrum, affecting the photophysiology of marine photoautotrophs. In this study, we comparably examined the photosynthesis of two dominating macroalgae in the Daya Bay, Chlorophyta Ulva fasciata and Phaeophyta Sargassum thunbergii, under white light, as well as under red, green and blue light. The results showed that the net photosynthetic O2 evolution rate (Pn) of U. fasciata under field light increased from 25.2 ± 3.06 to 168 ± 1.2 µmol O2 g FW−1 h−1 from dawn to noon, then decreased to 42.4 ± 0.20 µmol O2 g FW−1 h−1 at dusk. The Pn of S. thunbergii exhibited a similar diel change pattern, but was over 50% lower than that of U. fasciata. The maximal photosynthetic rate (Pmax) of U. fasciata derived from the photosynthesis vs. irradiance curve under white light (i.e., 148 ± 15.8 µmol O2 g FW−1 h−1) was ~30% higher than that under blue light, while the Pmax of S. thunbergii under white light (i.e., 39.2 ± 3.44 µmol O2 g FW−1 h−1) was over 50% lower than that under red, green and blue light. Furthermore, the daily primary production (PP) of U. fasciata was ~20% higher under white than blue light, while that of S. thunbergii was 34% lower, indicating the varied light spectral compositions influence algal photosynthetic ability and thus their primary production in field, and such an influence is species-specific.

Estimation of Seaweed Biomass Based on Multispectral UAV in the Intertidal Zone of Gouqi Island

UAV remote sensing inversion is an efficient and accurate method for obtaining information on vegetation coverage, biomass and other parameters. It is widely used on forest, grassland and other terrestrial vegetation. However, it is rarely used on aquatic vegetation, especially in intertidal zones and other complex environments. Additionally, it is mainly used for inversion of coverage, and there have been few studies thus far on biomass assessment. In this paper, we applied multispectral UAV aerial photography data to evaluate the biomass of seaweed in an intertidal zone. During the ebb tide, UAV aerial photography and in situ sampling data were collected in the study area. After optimizing the spectral index and performing a multiple linearity test, the spectral parameters were selected as the input of the evaluation model. Combined with two machine learning algorithms, namely random forest (RF) and gradient boosting decision tree (GBDT), the biomasses of three species of seaweed (Ulva pertusa, Sargassum thunbergii and Sargassum fusiforme) in the intertidal zone were assessed. In addition, the input parameters of the machine learning algorithms were optimized by one-way ANOVA and Pearson’s correlation analysis. We propose a method to assess the biomass of intertidal seaweed based on multispectral UAV data combined with statistics and machine learning. The results show that the two machine learning algorithms have different accuracies in terms of biomass evaluation using multispectral images; the gradient boosting decision tree can evaluate the biomass of seaweed in the intertidal zone more accurately.