Characterization of Rugulopteryx okamurae algae: A source of bioactive peptides, omega-3 fatty acids, and volatile compounds

Characterization of Rugulopteryx okamurae algae: A source of bioactive peptides, omega-3 fatty acids, and volatile compounds Fernando Rivero-Pino a,b , Teresa Gonzalez-de la Rosa a,b , Maria Torrecillas-Lopez a,b , Luna Barrera-Chamorro a,b , Jose Luis del Rio-Vazquez a , Elvira Marquez-Paradas a,b , Africa Fernandez-Prior a,b , Marco Garcia-Vaquero c , Jose Carlos Garcia-Gomez d , Sergio Montserrat-de la Paz a,b,* , Carmen Maria Claro-Cala b,e a Department of Medical Biochemistry, Molecular Biology, and Immunology, School of Medicine, University of Seville, Spain b Instituto de Biomedicina de Sevilla, IBiS/Hospital Universitario Virgen del Rocio/CSIC/Universidad de Sevilla, Seville 41013, Spain c School of Agriculture and Food Science, University College Dublin, Belfield, D04V1W8 Dublin, Ireland d Department of Zoology, Faculty of Biology, University of Seville, Spain e Department of Pharmacology, Pediatrics, and Radiology, School of Medicine, University of Seville, Spain ARTICLE INFO Keywords: Algae Bioactive peptides Molecular docking Vitamin A ABSTRACT This study provides a detailed characterization of the invasive algae Rugulopteryx okamurae, highlighting its nutritional composition, mineral content, and potential bioactive compounds. This biomass contains 14.18 % protein, 21.29 % lipids (with a high omega-3 content), fibre (31.32 %), and significant amounts of minerals like calcium, sodium, potassium, sulphur, and iron. Phenolic compounds (0.74 %) and volatile compounds, such as retinol, were also identified. Peptidome analysis revealed 626 unique peptides, with 21 low molecular weight peptides showing potential activity against angiotensin converting enzyme and dipeptidyl peptidase IV when assessed using in silico tools and using molecular docking. Additionally, the antioxidant capacity of the alga was demonstrated with a significant free radical inhibition (EC 50 : 2.09 mg/mL). Overall, this study provides initial evidence on the nutritional potential of R. okamurae, which may have potential for future applications in food and biotechnology fields. 1. Introduction The invasion of Rugulopteryx okamurae (R. okamurae), a brown macroalgae species, into European waters and the Strait of Gibraltar presents a pressing concern (Marletta et al., 2024). However, considering the huge amount of this algae which is being collected, and with the purpose of adding new research lines aligned with the new policies of promoting an environmentally friendly food system, recent research is focusing on characterization of this multicellular algae, which could be employed as source of macroand micronutrients. There lies a potential opportunity for its utilization as a valuable food and feed resource (Kammler et al., 2024). Efforts to harness its biomass for these purposes could not only mitigate the ecological threats posed by its presence but also contribute to addressing food security concerns and reducing dependency on traditional sources of protein (Barcellos et al., 2023; Gordalina et al., 2021). It must be noted that the composition of brown algae depends on various factors, including environmental conditions, such as water temperature, light intensity, nutrient availability, and salinity. On top of that, genetic factors and the species-specific metabolic pathways of brown algae can influence their biochemical composition. Algae synthesize a diverse array of compounds including polysaccharides (such as alginate, laminarin, and fucoidan), polyphenols, pigments (like fucoxanthin), proteins, and lipids. The relative proportions of these constituents can vary significantly between different species of brown algae and even within the same species under different environmental conditions, including season and place of growth, as per other marine organisms (Deepika et al., 2022; Gordalina et al., 2021; Morales-Medina et al., 2016). The potential for exploring new species offers a huge opportunity to discover novel compounds—structures never identified * Corresponding author at: Department of Medical Biochemistry, Molecular Biology, and Immunology. School of Medicine, Universidad de Sevilla, Av. Dr. Fedriani s/n, 41009 Seville, Spain. E-mail address: [email protected] (S. Montserrat-de la Paz). Contents lists available at ScienceDirect Food Chemistry journal homepage: www.elsevier.com/locate/foodchem https://doi.org/10.1016/j.foodchem.2025.143084 Received 20 December 2024; Received in revised form 14 January 2025; Accepted 24 January 2025 Food Chemistry 473 (2025) 143084 Available online 25 January 2025 0308-8146/© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). before—with potential applications across various industries, if biological or techno-functional activities are demonstrated. The potential of R. okamurae in food applications has been scarcely explored, highlighting the potential of terpenes, reducing sugars, pigments, fibres, with potential anti-inflammatory, α -glucosidase inhibitory or antibacterial activity, among others, but mostly through in vitro studies. On the other hand, it has been reported the high toxicity of this species attributed to their high content of sesquiterpenes, not found on other algae (Barcellos et al., 2023). If intended to be used for human consumption, a proper risk assessment should be performed, ensuring that no safety concerns arise from its consumption. Utilizing invasive macroalgae for producing high-value products presents a promising strategy to mitigate the negative environmental effects of these species. Macroalgae offer distinct economic advantages as they do not require freshwater or arable land for cultivation, thus avoiding competition with conventional food sources (Agustín et al., 2023). However, determination of how season and place of growth of the marine organisms is affecting its composition is still in a very early stage for R. okamurae, as scarce literature is available. In addition, the processing of the samples collected highly affects the products in the extracts (De la Lama-Calvente et al., 2024). The content of specific peptides or phenolic compounds, in other sources, has been associated with antioxidant and anti-inflammatory properties, due to the structure of these molecules. In the case of R. okamurae, to the authors’ knowledge, little has been described about the bioactive potential of its compounds. This work provides a complete characterization of freeze-dried R. okamurae collected from the coast of Spain during Spring 2024. The characterization of the biomass included macronutrients, fatty acids profile, phenolic and volatile compounds, amino acids, and mineral contents. The in vitro antioxidant activity and ultrastructural characterization was also performed together with peptidome identification, in silico analyses and molecular docking of the identified bioactive peptides. 2. Materials and methods 2.1. Biomass and chemical reagents Fresh R. okamurae was collected in Tarifa (Cadiz, Spain) on the 11th April 2024. The samples were stored (−20 ◦C) and freeze-dried (Cryodos −80 ◦C, Telstar), resulting in yields of dried biomass of 18.10 %. The biomass was milled using a commercial cutter mill (HR-2172/00; Philips, the Netherlands), and stored in polypropylene tubes under refrigeration (4 ◦C) for further analyses. 2.2. Chemical characterization All chemical measurements were performed in triplicate except in the case of total phenolic content that were performed in quadruplicate. 2.2.1. Macronutrient composition Protein concentration was analysed by elemental microanalysis, using a LECO TRUSPEC MICRO analyser (Leco Corporation, St. Joseph, MI, USA), multiplying the nitrogen content by a conversion factor of 5 (Cebri´ an-Lloret et al., 2024). The fat content of the samples was determined after extraction with a solvent mixture hexane/isopropanol (1:1; v:v) (Drusch et al., 2012). Total dietary fibre (predominantly hemicellulose, cellulose, and lignin) was determined by digestion in a detergent solution with a neutral detergent solution, heat-stable bacterial α -amylase, and sodium sulfite using ANKOM 2000 technology similarly to Coblentz et al. (2019). Moisture and ash were calculated following the UNE-EN14774–3 and UNE-EN14775 methods. 2.2.2. Determination of total amino acids Total amino acids (TAA) were determined as described by Gonzalezde la Rosa et al. (2024). Samples were hydrolysed with 6 N HCl (110 ◦C, one day). The analyses were performed using a Thermo Scientific liquid chromatography system consisting of a binary UHPLC Dionex Ultimate 3000 RS, connected to a quadrupole-Orbitrap QExactive hybrid mass spectrometer (ThermoFisher Scientific, USA) with heated electrospray ionization (HESI) probe. Separation was carried out using an Acquity UPLC BEH Amide column (1.7 μ m particle size, 100 ×2.1 mm) (Waters) at 35 ◦C at a flow rate of 0.4 mL/min. A binary gradient, consisting of (A) ACN:H2O (85:15, v/v) and (B) H2O both containing 10 mM ammonium formate and 0.15 % formic acid, was used with the following elution profile: 0 % B (6 min), linear gradient from 5.9 % B to 17.6 % B (4 min), linear gradient to 29.4 %B (2 min) and finally 0 % B (6 min). The injection volume was 5 μ L. Total essential amino acid (EAA) values were calculated by adding the concentrations of histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, and valine; non-essential amino acids (NEAA) values were calculated by adding the concentrations of aspartic and glutamic acid, serine, glycine, arginine, alanine, tyrosine, and proline in the samples. The ratio EAA/TAA (%) refers to the proportion of essential amino acids to total amino acids. 2.2.3. Determination of fatty acid profile Fatty acid methyl esters (FAME) were analysed using the method as described by Sukhija & Palmquist, 1988; Gonzalez-de la Rosa et al., 2024. FAME were prepared according to Ju´ arez et al. (2008). Shortly, 1 mL of n-hexane and 3 mL of methanolic HCl were added to samples and heated for 90 min at 70 ◦C; when the samples returned to room temperature, 5 mL K 2 CO 3 and 2 mL of n-hexane were added, followed by a centrifugation, and the upper organic phase was collected and dissolved in 1 mL of n-hexane. FAME were analysed using an Agilent 6890 N gas chromatograph equipped with a flame ionization detector, and a HP-88 capillary column (Agilent Technologies Spain, S.L., Madrid, Spain) (100 m length, 0.25 mm internal diameter, and 0.2 μ m phase thickness). The initial oven temperature was 100 ◦C, with an increase of 3 ◦C per minute until 158 ◦C was reached, then the increase was 1.5 ◦C to 190 ◦C, and this temperature was maintained for 15 min. The temperature was then raised to 200 ◦C with an increase of 2 ◦C per minute. Finally, a rapid rise was made at 10 ◦C per minute to 240 ◦C. This temperature was maintained for 10 min. This temperature was maintained for 10 min. The injector temperature was set at 300 ◦C and the detector temperature was set at 320 ◦C. Split mode was used for the injection. The identification of the fatty acids was carried out by comparison of their retention times with the retention times in a mixture of standards. Results of the fatty acid profile are expressed as a percentage of total identified fatty acids and are shown as mean ±SD. 2.2.4. Determination of the total phenolic content and identification Total phenolic content was determined as described by Singleton et al. (1965). Briefly, 20 μ L of sample (10 mg/mL) previously dissolved in a methanol:water solution to extract the phenols, and standard (gallic acid, from to 25 to 250 mg/L) were mixed with 80 μ L of 0.7 M Na 2 CO 3 and 100 μ L of Folin−Ciocalteu phenol reagent (0.2 M). The mixtures were incubated for 10 min and he absorbance of the reaction was read at 655 nm using a Infinity M-NANO spectrophotometer (Tecan, Untersbergstr, Austria). The results were expressed as mg of gallic acid equivalent (GAE) per 100 mg of sample. Phenolic compounds were then identified by UHPLC Dionex Ultimate 3000 RS, connected to a quadrupole-Orbitrap QExactive hybrid mass spectrometer (ThermoFisher Scientific, San Jose, CA, USA) equipped with heated electrospray ionization source (HESI-II) operated in negative ionization mode. Separation was carried out using an Acquity BEH C18 column (1.7 μ m particle size, 100 ×2.1 mm) (Waters, MA, USA) kept at 40 ◦C using a flow rate of 0.5 mL/min. A binary gradient consisting of (A) water and (B) methanol both containing 0.1 % formic acid was used with the following elution profile: 5 % B (1 min), linear gradient to 100 % B (9 min), 100 % B (2 min) and finally 5 % B (3 min). F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 2 The injection volume was 5 μ L. Xcalibur software was used for instrument control and data acquisition. A data dependent acquisition method (Top5) was used in negative mode at resolution 70,000 and 17,500 at m/ z 200 FWHM for Full Scan and Product Ion Scan, respectively. HESI source parameters were: spray voltage, −3.0 kV; S-lens RF level, 50; capillary temperature, 320 ◦C; sheath and auxiliary gas flow, 60 and 25 respectively (arbitrary units); and probe heater temperature, 400 ◦C. Trace Finder 5.1 software was used for data treatment. The identification was made by comparing retention time, the exact masses of the pseudomolecular ion, and their fragment ions (maximum deviation of 5 ppm) with the data contained in a phenolic compounds database with 87 compounds. Isotopic pattern scores higher than 80 % were also required. 2.2.5. Quantification of mineral contents The analysis was performed using inductively coupled plasma optical emission spectroscopy (ICP-OES), after a microwave-assisted digestion procedure with HNO 3 and H 2 O 2 at 200 ◦C (Santos et al., 2019). 2.2.6. Quantification of volatile compounds Volatile compounds were quantified according to Guzm´ an et al. (2020). The extraction of the volatile compounds of the seaweed was carried out by headspace solid-phase microextraction (SPME). A fibre of divinylbenzene/carboxene/polydimethylsiloxane (DVB-CAR-PDMS; 1 cm long ×110 μ m diameter; Supelco, Bellefonte, PA, USA) was set in the headspace of the vial for 10 min at 40 ◦C while shaking the sample. The adsorbed compounds were desorbed into the split-splitless injector of a gas chromatograph (GC) at 250 ◦C for 5 min. The analysis was conducted using a Thermo Scientific Trace 1300 GC (Milan, Italy) system coupled to an ion trap mass spectrometer (ThermoScientific ISQ QD Single Quadrupole Mass Spectrometer (MS), Milan, Italy) using a VF-42 WAXms column (30 m ×250 μ m i.d. ×0.50 μ m film thickness, Agilent Technologies, Inc.2012, Santa Clara, CA, USA) where helium was the carrier gas. The conditions were an initial hold at 45 ◦C for 4 min, then increased to 150 ◦C at 5 ◦C/min and maintained for 3 min, a subsequent ramp to 250 ◦C at 6 ◦C/min, and remained at 250 ◦C for 5 min. The transfer line was at 280 ◦C. The MS operated in electron impact mode with an ionization energy of 70 eV, recording data at a scan rate of 1 scan per second. The relative abundance of volatile compounds was calculated based on peak area integration in the chromatograms. Retention indices (RI) were determined using a series of n-alkanes under identical chromatographic conditions. Tentative compound identification was achieved by comparing the mass spectra with entries in the National Institute of Standards and Technology (NIST; Gaithersburg, MD, USA) library or previously published data. 2.3. Ultrastructural characterization Ultrastructural characterization of the dried R. okamurae was done using scanning electron microscopy (SEM) as described in Montserrat-de la Paz et al. (2023). Images were obtained with a Zeiss Crossbeam 550 scanning electron microscope (Zeiss, Madrid, Spain) at an accelerating voltage of 2.00 kV at different magnifications (50×, 200×, 500×, and 981×). 2.4. Antioxidant activity The 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity of the samples was analysed according to Picot et al. (2010). The samples were thoroughly mixed with 0.1 mM DPPH in methanol (1:1, v/ v), incubated in dark conditions (30 min) and their absorbance was read at 515 nm. Their half-maximum effective concentration (EC 50 ) value was determined as the concentration of sample that reduces the DPPH activity by 50 % (Gonzalez-de la Rosa et al., 2024). 2.5. Peptide extraction, purification, and sequence identification Samples were acidified with 0.5 % trifluoroacetic acid (v/v). The desalting and concentration step was performed with ZipTip C18 (Merck Millipore, Darmstadt, Germany) and the samples were dried in a speedvacuum. LC-TIMS-MS/MS was performed with a nanoElute nanoflow ultra-high pressure LC system (Bruker Daltonics, Bremen, Germany) coupled to a timsTOF Pro 2 mass spectrometer, equipped with a CaptiveSpray nanoelectrospray ion source (Bruker Daltonics) according to the procedure described in the patent P202230873. Further details on the methodology can be found in Montserrat-de la Paz et al. (2023). In this case, the reference library was acquired from the taxonomic level Phaephyaceae_2024-05-10. Unique protein peptides were set to larger than 1 and a high confidence score of −10lgP >20 was applied to indicate a protein accurately identified. 2.6. Bioactivity prediction in silico analysis All the peptides below 1000 Da were subjected to in silico analyses (prediction tools aiming to characterize different properties): a) ToxinPred software for physio-chemical properties (Gupta et al., 2013); b) PeptideRanker, AHT-Pin, Stack-DPPIV, PreAIP, AnOxPePred-1.0, for general bioactivity, inhibition of angiotensin converting enzyme (ACE) and dipeptidyl peptidase IV (DPP-IV), anti-inflammatory and antioxidant activity, respectively; (Charoenkwan et al., 2022; Khatun et al., 2019; Kumar et al., 2015; Mooney et al., 2012; Olsen et al., 2020; c) PASTA 2.0 to estimate secondary structure (Walsh et al., 2014); d) The tool BIOPEP, was employed to carry out an in silico simulated gastrointestinal digestion (SGID) of the peptides (using pepsin, chymotrypsin, and trypsin), aiming to predict the potential new sequences produced after digestive degradation and their potential bioactivity (Minkiewicz et al., 2019). 2.7. Molecular docking Molecular docking was carried out to determine the binding affinity energy of three selected peptides with different receptors, including, DPP-IV, ACE, and TLR4/MD2. The X-ray crystal structures of DPP-IV (PDB: 5Y7H), ACE (PDB: 1O8A), and TLR4/MD2 (PDB: 3FXI) were obtained from the RCSB PDB database (Protein Data Bank, http://www. rcsb.org/). Ligands and all the water molecules were removed from the receptor PDB file, while polar hydrogen atoms were added using UCSF Chimera software (San Francisco, California, USA). The 3D structures of the peptides were obtained, and their structure was minimized, by USCF Chimera. The molecular structures of the receptors and the peptides were then converted to PDBQT format with AutoDock Tools. For each receptor, the AGFR program was used in a different way to calculate the specific grid boxes for the selected peptides. For the DPPIV enzyme, its three active site pockets (S1, S2, S3) were selected from the A-chain for the peptides docking box. S1 includes Tyr547, Ser630, Tyr631, Val656, Trp659, Tyr662, Tyr666, Asn710, Val711 and His740; S2 has the residues Glu205, Glu206 and Tyr662, and S3 consists of Ser209, Phe357, and Arg358 (Gui et al., 2022). For the ACE, a grid box coordinate X =37.89, Y =37.57, and Z =47.93 with dimensions 31.5 × 52.5 ×29.25 was generated with AGFR, computing pockets with AutoSite 1.1, specific for peptides. For the TLR4/MD2, AGFR program was used to calculate the positions and sizes of the specific docking boxes for each peptide. AutoDock Crank Pep was employed to perform docking analysis. Finally, the potential best docking score determined was selected for each receptor and visualized via Biovia Discovery Studio Visualizer visualized via Biovia Discovery Studio Visualizer, as well as the 2-dimensional (2D) and surface annotation of both ligand interactions with the protein. F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 3 3. Results and discussion 3.1. Chemical characterization 3.1.1. Proximate composition The composition and properties of the macroalgae R. okamurae have been scarcely reported in literature, and only recently, their full characterization has been described (Cebri´ an-Lloret et al., 2024) for the first time, according to these authors. In Table 1, the proximate analysis of the sample collected for this study is depicted. The protein content was 14.18 %, whereas the fat content was 21.29 %, and the neutral fibre was 31.32 %. On top of that, the moisture was 4.90 % and the ashes corresponded to the highest fraction, 31.90 %. It must be noted that the protein content might be not exactly estimated, since the nitrogen-toprotein factor employed for the calculations was 5, as recently done by other authors (Cebri´ an-Lloret et al., 2024) for other brown seaweeds, so the contents of protein reported here may be underestimated when compared to others using the conventional conversion factor of 6.25. The variability in the composition described for this alga in the literature is huge, as for protein and lipids content values range from 12.20 to 49.05 % and 4.02–17.30 %, respectively. Previous research explored the influence of the environmental conditions on the composition of brown macroalgae (Garcia-Vaquero et al., 2021; Konstantin et al., 2023) and thus, these are likely to play a strong influence on the concentrations of all the compounds reported in this study, even if the samples were collected from similar geographical locations. Thereby, Ferreira-Anta et al. (2023) reported a similar protein content that the one reported for the hereby assessed sample, with a value of 16.43 %, whereas the lipid fraction was lower, with a content of 6.17 %. The sample evaluated by these authors (Ferreira-Anta et al., 2023) was collected in July 2021 – when temperature was ranging from 19 ◦C to 27 ◦C approximately - in the same area as the one reported in this study. A mean protein content of 18.7 % was reported by Nunes et al. (2024) with a neutral detergent fibre of 54.00 % and acid detergent fibre of 41.96 %, for three samples collected in December 2023 from three different areas within the Prainha bathing area. According to Cebri´ an-Lloret et al. (2024), their sample (collected in Granada, Spain, although no information about the season), showed as well as content of carbohydrates of 60.4 % and 4.5 % of polyphenols. In addition to that, Agustín et al. (2023) reported that soluble dietary fibre, insoluble dietary fibre without lignin, Klason lignin, and total dietary fibre without lignin in dry basis (% w/w) of R. okamurae was 27.3, 13.6, 13.7, and 4.5 %, respectively. In fact, Miyashita et al. (2013) indicated that brown seaweeds can contain a fat fraction ranging from 10 to 20 % per dry weight, in line with the results obtained for R. okamurae in this study. It must be noted, in the analysis of fibre, that the detergent methods do not account for the whole fraction of soluble fibres, and consequently, the value reported is underestimated (Jensen et al., 2010). The irradiation and high oxygen concentrations can lead to the formation of free radicals and other strong oxidizing agents. Consequently, marine species might produce essential antioxidant compounds, such as vitamin C and phenolics, to protect themselves against oxidative stress, including UV radiation. Additionally, and similarly to other parameters related to seaweed composition, it has been reported that the vitamin composition of seaweed varies and is influenced by the algal species, growth stage, geographic location, salinity, season, availability of light, and seawater temperature (Praiboon et al., 2018). Overall, the R. okamurae sample contains a balanced composition including proteins, fats, and fibre, which seems promising to be used as food or feed ingredients. However, further characterization studies shall be done in order to provide a more detailed identification of the sample. 3.1.2. Amino acid composition The amino acid profile of R. okamurae is reported in Table 2, together the quantification of essential and non-essential amino acids, and a comparison with the nutritional recommendations in adults proposed by the FAO/WHO/UNU. Notably, valine was the amino acid present at the highest concentration (254.29 ±5.26 mg/g), followed by leucine (157.86 ±2.07 mg/ g) and phenylalanine (119.76 ±1.16 mg/g). These levels are significantly higher than the other essential amino acids measured, and both are relevant for protein synthesis and muscle metabolism. Thus, these values suggest that the unique profile of amino acid composition of this macroalgae could be of nutritional relevance. Cebri´ an-Lloret et al. (2024) reported that essential amino acids (mainly leucine, phenylalanine, and valine) constituted 32 % of the total amino acids in R. okamurae, comparable to traditional food sources, such as eggs or casein. However, the digestibility of these proteins should be addressed in order to account for the protein quality of this biomass. In this case, the limiting amino acids are histidine (1.46 ±0.09 mg/ g) and lysine (1.43 ±0.11 mg/g). However, given that the use of this algae as food would not imply that it is the sole dietary protein source of humans, but instead is incorporated into a diverse and balanced diet, its consumption is unlikely to adversely affect protein nutrition. 3.1.3. Fatty acid composition The fatty acid profile of R. okamurae is reported in Table 3, and accounts for the total amount of fat of the biomass of 22.3 % as mentioned Table 1 Chemical composition of R. okamurae. Data are expressed as a percentage of dry weight and are shown as mean ±SD (n =3). Proximate composition (g/100 g of dry weight) R. okamurae Protein content 14.18 ±0.06 Fat content 21.29 ±0.93 Fibre 31.32 ±0.31 Phenols 0.74 ±0.98 Moisture 4.90 ±0.28 Ash 31.90 ±0.28 Table 2 Amino acid composition of R. okamurae. Data are expressed as mg amino acids per g total protein and are shown as mean ±SD (n =3). Amino acids (mg/g of protein) R. okamurae 2013 FAO/WHO/UNU a Essential amino acids  Histidine 1.46 ±0.09 15 Isoleucine 98.11 ±1.22 30 Leucine 157.86 ±2.07 59 Lysine 1.43 ±0.11 45 Methionine 19.22 ±0.56 16 Cystine n.d. 6 Phenylalanine 119.76 ±1.16 38 Threonine 20.75 ±0.31 23 Valine 254.29 ±5.26 39  Non-essential amino acids  Aspartic acid 53.19 ±0.25 – Glutamic acid 93.21 ±1.84 – Serine 20.37 ±0.43 – Glycine 22.81 ±0.36 – Arginine 10.23 ±0.15 – Alanine 99.26 ±1.07 – Tyrosine 11.46 ±1.24  Glutamine n.d.  Proline 16.59 ±0.38 – Total essential amino acids 672.87 ±4.56  Total non-essential amino acids 327.13 ±3.15  EAA/TAA b (%) 67.29 %  NEAA/TAA b (%) 32.71 %  a FAO/WHO/UNU 2013. Dietary protein quality evaluation in human nutrition. FAO FOOD and Nutrition Document NO. 92. Scoring pattern mg/g protein requirements for adults. n.d.; no detected. b EAA: total essential amino acids; TAA: total amino acids; NEAA: total nonessential amino acids. F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 4 previously. The main fatty acids detected were C16:0, C18:0, and C14:0, all of them saturated fatty acids, representing around 62 % of the sample. Then, oleic acid (C18:1n-9c) represented 8.43 % of the sample. Moreover, the sample was also high in C20:5n-3 (eicosapentaenoic acid, EPA) with values of around 7.7 %, as well as of C20:4n-6 (arachidonic acid, ARA) and C18:3n-3 ( α -linolenic acid) that represented approximately 5.1 and 3.4 %, respectively. Monounsaturated fatty acids represented 13.3 % of the total fatty acids. In the case of polyunsaturated fatty acids, omega-3 were 12.1 % and omega-6 represented a 9 % of the total fatty acids, making an omega-6/omega-3 ratio of 0.74:1. This ratio indicates that the R. okamurae-derived lipid fraction contains more omega-3 than omega-6 fatty acids, which is positive since it is generally recommended to maintain a balance where omega-3 is at least equal to or greater than omega-6 (Karageorgou et al., 2023). This result in highly comparable to the results obtained by Cebri´ an-Lloret et al. (2024), which reported saturated fatty acids as the most abundant fraction (around 61 %), followed by polyunsaturated fatty acids, around 24 % and monounsaturated fatty acids, around 15 %. However, these authors reported different content of specific fatty acids compared to this study, such as lower content of C16:0 and C18:0, and more of C14:0 and C18:1n-9. In relation to EPA, ARA, and α -linolenic acid, R. okamurae from this study had higher content of all of them compared to other food sources such as olive oil, fishes such as Tilapia (Chepkirui et al., 2021) or some legume seeds (Khrisanapant et al., 2019). These differences might be attributed to both the location where the raw material was collected from, and the season, since for instance, for other sources of lipids, it has been demonstrated that the content of unsaturated fatty acids could be higher in winter. According to Aussant et al. (2018), the temperature is one of the key factors in determining the content of EPA and docosahexaenoic acid (DHA) in microalgae, in relation to the fluidity of cell membranes. The introduction of these polyunsaturated fatty acids into the membranes is reduced when temperatures rise, and consequently, the proportion of polyunsaturated fatty acids in algae is reported to increase in winter. The samples hereby analysed were collected in Tarifa (Spain) during the spring in 2024. The average temperature recorded by the Tarifa station in April 2024 was 16.96 ◦C, ranging between a minimum of 9.1 ◦C and a maximum of 28.3 ◦C. In order to understand seasonal variation, samples taken in different months should be analysed. In the same line, the R. okamurae sample collected in summer, as mentioned above (FerreiraAnta et al., 2023) contained palmitic acid (50.1 %), myristic acid (22 %), 9-hexadecenoic acid (11 %), 9-octadecenoic (12 %), stearic acid (2.6 %), and eicosanoic acid (2.3 %), different from the current results. The fatty acid profile of an ingredient should be also assessed in terms of the regioTable 3 Fatty acid composition of R. okamurae. Data are expressed as a percentage of total identified fatty acids and are shown as mean ±SD (n =3). Fatty acid (relative amount, %) R. okamurae Capric acid (C10:0) 0.08 ±0.01 Lauric acid (C12:0) 0.21 ±0.02 Tridecylic acid (C13:0) 0.10 ±0.01 Myristic acid (C14:0) 8.74 ±0.08 Myristoleic acid (C14:1n-9) 0.17 ±0.04 Pentadecylic acid (C15:0) 0.95 ±0.02 10-Pentadecenoic acid (C15:1n-5) 0.26 ±0.07 Palmitic acid (C16:0) 40.03 ±0.28 Palmitoleic acid (C16:1n-9c) 3.14 ±0.00 Margaric acid (C17:0) 0.35 ±0.13 Margaroleic acid (C17:1n-9c) 0.13 ±0.04 Stearic acid (C18:0) 13.37 ±0.08 Elaidic acid (C18:1n-9 t) 0.12 ±0.01 Oleic acid (C18:1n-9c) 8.43 ±0.04 Linoelaidic acid (C18:2n-6 t) 0.10 ±0.02 Linoleic acid (C18:2n-6c) 2.38 ±0.07 γ-Linolenic acid (C18:3n-6 g) 0.61 ±0.05 α -Linolenic acid (C18:3n-3 α )3.41 ±0.01 Arachidic acid (C20:0) 0.54 ±0.05 Gondoic acid (C20:1n-9) 0.62 ±0.17 Eicosadienoic acid (C20:2n-6) 0.14 ±0.05 Dihomo γ-linolenic acid (C20:3n-6) 0.48 ±0.08 Arachidonic acid (C20:4n-6) 5.06 ±0.07 Eicosapentaenoic acid (C20:5n-3) 7.75 ±0.31 Eicosatrienoic acid (20:3n-3) 0.16 ±0.02 Heneicosanoic acid (C21:0) 0.42 ±0.04 Behenic acid (C22:0) 0.42 ±0.13 Erucic acid (C22:1n-9) 0.18 ±0.07 Docosadienoic acid (C22:2n-6) 0.24 ±0.11 Clupanodonic acid (C22:5n-3) 0.50 ±0.04 Docosahexaenoic acid (C22:6n-3) 0.24 ±0.03 Tricosanoic acid (C23:0) 0.19 ±0.06 Lignoceric acid (C24:0) 0.27 ±0.14 Nervonic acid (C24:1n-9) 0.26 ±0.03 Total saturated fatty acids 65.6 % Total monounsaturated fatty acids 13.3 % Total polyunsaturated fatty acids 21.1 % Omega-3 12.1 % Omega-6 9 % Omega-6/omega-3 ratio 0.74:1 Table 4 Characterization of the phenolic profile of R. okamurae. Data are expressed as ppb and are shown as mean ±SD (n =4). Phenol (Conf.) a (ppb) b Formula R. okamurae 3-hydroxytyrosol (1/3) C 8 H 10 O 3 2.51 ±0.04 2,4-dihydroxybenzoic acid (1/3) C 7 H 6 O 4 7.97 ±0.11 4-hydroxybenzoic acid (2/3) C 7 H 6 O 3 11.88 ±0.25 Benzoic acid (1/3) C 7 H 6 O 2 83.28 ±0.96 Caffeic acid (1/3) C 9 H 8 O 4 5.19 ±0.09 Dihydrocaffeic acid (2/3) C 9 H 10 O 4 8.19 ±0.12 Ellagic acid (3/3) C 14 H 6 O 8 15.61 ±0.15 Floretic acid (1/3) C 9 H 10 O 3 41.50 ±0.20 Gentisic acid (1/3) C 7 H 6 O 4 7.97 ±0.07 Homovanillic acid (1/3) C 9 H 10 O 4 8.19 ±0.09 Indoleacetic acid (2/3) C 10 H 9 NO 2 12.02 ±0.10 Indolactic acid (2/3) C 11 H 11 NO 3 2.91 ±0.00 P-coumaric acid (1/3) C 9 H 8 O 3 91.87 ±0.84 Protocatechic acid (1/3) C 7 H 6 O 4 7.97 ±0.07 Quinic acid (1/3) C 7 H 12 O 6 2.99 ±0.01 Salicylic acid (3/3) C 7 H 6 O 3 11.88 ±0.04 Trans-cinnamic acid (1/3) C 9 H 8 O 2 2.65 ±0.02 Catechol (2-hydroxyphenol) (1/3) C 6 H 6 O 2 5.30 ±0.06 Kaempferol-3-O-Glc (0/3) C 21 H 20 O 11 3.81 ±0.04 Luteolin-4’-O-Glc (0/3) C 21 H 20 O 11 3.81 ±0.03 Luteolin-7-O-Glc (0/3) C 21 H 20 O 11 3.81 ±0.03 Quercitrin (Quercetin-3-O-rhamnoside) (0/3) C 21 H 20 O 11 3.81 ±0.03 Taxifolin (0/3) C 15 H 12 O 7 16.03 ±0.11 Vanillin (2/3) C 8 H 8 O 3 31.74 ±0.18 3,4-Dihydroxyxyphenylglycol (1/3) C 8 H 10 O 4 3.26 ±0.03 4-O-Caffeoylquinic acid (3/3) C 16 H 18 O 9 5.93 ±0.06 Abscisic acid (1/3) C 15 H 20 O 4 15.92 ±0.12 Chlorogenic Acid (3-O-Caffeoylquinic Acid) (2/3) C 16 H 18 O 9 5.93 ±0.02 Gibberellic Acid (GA3) (1/3) C 19 H 22 O 6 18.04 ±0.19 Isovanillic acid (1/3) C 8 H 8 O 4 4.02 ±0.06 Jasmonic acid (1/3) C 12 H 18 O 3 4.14 ±0.05 Syringic acid (1/3) C 9 H 10 O 5 2.84 ±0.03 Vanillic acid (1/3) C 8 H 8 O 4 4.02 ±0.03 Aromadendrin (0/3) C 15 H 12 O 6 9.31 ±0.10 Brevifolin (1/3) C 10 H 12 O 4 2.72 ±0.04 Catechin (0/3) C 15 H 14 O 6 3.69 ±0.04 Epicatechin (0/3) C 15 H 14 O 6 3.69 ±0.04 Eriodictyol (0/3) C 15 H 12 O 6 9.31 ±0.11 Ethyl gallate (1/3) C 9 H 10 O 5 2.84 ±0.02 Gibberellin A12 (2/3) C 20 H 28 O 4 265.55 ±1.21 Gibberellin A19 (2/3) C 20 H 26 O 6 67.60 ±0.51 Gibberellin A20 (1/3) C 19 H 24 O 5 15.80 ±0.14 Gibberellin A44 (2/3) C 20 H 26 O 5 76.57 ±0.48 Gibberellin A53 (1/3) C 20 H 28 O 5 23.67 ±0.21 Oleuropein (1/3) C 25 H 32 O 13 9.55 ±0.12 Pinoresinol (1/3) C 20 H 22 O 6 2.60 ±0.03 a Conf: Confidence based on retention time, ionic fragmentation, and isotopes; b ppb has been estimated with the area and concentration of the internal standard for 2,4-dihydroxybenzoic acid. F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 5 distribution of the fatty acid, as the bioavailability of the fatty acids in a triacylglyceride depends on its position on the backbone, so further studies should go towards that direction. 3.1.4. Phenolic compounds Overall, the total polyphenol contents of this macroalgae were 0.0074 ±0.0010 mg gallic acid/mg of sample. In Table 4, the phenolic compounds identified by mass spectrometry are shown. When analysing the type of compounds identified, it was observed that some of these phenols are common components in other plant-derived sources, such as olive, berries, tree bark, vanilla pods, and various plants, aligning with the profiles reported in similar studies (Rivero-Pino et al., 2024; Tanase et al., 2019; Zhang et al., 2023). It has been reported that, for example, extraction with ethanol increases polyphenol yields by 4.59–10.78 times when compared with water, whereas on the contrary, with water, the content of reduced sugar is higher (doi:https://doi.org/10.1016/j. jenvman.2024.122504). Consequently, processing of raw materials is a key step in order to concentrate specific compounds which may be of interest. Cebrian-Lloret et al., (2024) reported a content of 4.5 % of total phenols, employing the same methodology as the one in this study, but no further identification of phenolic compounds was performed by these authors. However, phlorotannins have been reported to be the most important class of polyphenols present in brown seaweeds. Numerous studies have demonstrated that the potent antioxidant qualities of phlorotannins derived from different species of brown seaweeds may be attributed to their distinct molecular structure (Duan et al., 2023). 3.1.5. Mineral contents The content of minerals of R. okamurae are reported in Table 5. In this study, the ash contents were higher than 30 %, whereas other authors reported lower values (e.g., 11 % by Cebri´ an-Lloret et al., 2024). The minerals found at the highest concentrations were potassium, sodium, calcium, and sulphur, with values over 19 g/kg. The content of salt is high, thus, potentially limiting the use levels of this sample as food when used as ingredient. Cebrian et al., (2024) reported high content of magnesium (around 7 g/kg), calcium (5.5 g/kg), potassium and sodium (2.5 g/kg), strontium (1.5 g/kg), chlorine (1.1 g/kg), and aluminium (1 g/kg). However, other authors did not detect magnesium or calcium, for instance, while finding a high content of sodium (Agabo-García et al., 2023). Similarly to other composition parameters analysed in this study, the variability in the concentrations reported between studiues can be explained by the differences in the environment in which the algae grow. The high content of sodium and calcium has also been reported for other brown algae (Meng et al., 2022), and even when not being among the most abundant ones, the iron content of R. okamurae (463.6 mg/kg) was substantial, as has been also highlighted in other species. The high Table 5 Mineral content of R. okamurae. Data are expressed as mg/kg and are shown as mean ±SD (n =3). Mineral (mg/kg) R. okamurae Ca 20,482.11 ±11.30 Co n.d. Cr 0.35 ±0.00 Cu 7.02 ±0.00 Fe 463.62 ±0.00 K45,696.54 ±426.42 Mg 7985.80 ±0.12 Mn 15.38 ±0.00 Na 36,157.94 ±0.00 Ni 5.55 ±0.00 P2011.24 ±0.14 S19,816.62 ±1.82 Se n.d. V2.58 ±0.00 Zn 31.13 ±0.00 n.d., not detected. Table 6 Volatile compounds identified in R. okamurae. Data are expressed as relative value and are shown as mean ±SD (n =3). Compounds (relative amount, %) R. okamurae Carboxylic acids 7.26 ±0.01 Acetic acid 6.00 ±0.33 Butanoic acid 0.02 ±0.00 Butanoic acid, 3-methyl-(Isovaleric acid) 0.19 ±0.01 2-pentenoic acid 0.16 ±0.04 Hexanoic acid 0.11 ±0.01 Octanoic acid 0.64 ±0.04 Nonanoic acid 0.08 ±0.00 Decanoic acid 0.11 ±0.01 Dodecanoic acid 0.06 ±0.00 Hexadecanoic acid 0.05 ±0.00 Octadecanoic acid 0.04 ±0.00 Alcohols 12.33 ±0.01 Ethanol 1.37 ±0.06 2-butyl-1-octanol 0.05 ±0.00 3-buten-2-ol-2-methyl ( α , α -dimethyl-allylalcohol) 0.10 ±0.02 Pinacol (2,3butanediiol-2,3-dimethyl) 0.01 ±0.00 1-pentanol 0.13 ±0.01 1-penten-3-ol 1.02 ±0.06 2-penten-1-ol, (E)- 0.23 ±0.01 2-penten-1-ol, (Z)- 1.29 ±0.07 1-hexanol 0.10 ±0.01 Phenol 0.04 ±0.00 Benzenemethanol 0.04 ±0.00 Benzeneethanol 0.06 ±0.00 3-hexen-1-ol 0.08 ±0.00 3-methyl-1-hexen-1-ol/1-methylcyclohexanol 0.56 ±0.03 2,4-hexadien-1-ol 0.34 ±0.02 2-ethylhexanol 3.73 ±0.21 Cyclohexanol, 2,4-dimethyl0.10 ±0.01 2,4-diethyl-1-heptanol/ Caranol 0.04 ±0.00 2-butyl-1-octanol 0.04 ±0.00 Citronellol-dihydro (1-octanol,3,7-dimethyl) 0.36 ±0.02 Citranellol (6-octen-1-ol) 0.25 ±0.01 (Z)-oct-2-en-1-ol 0.06 ±0.00 (E)-2-nonen-1-ol 0.19 ±0.01 2-ethyl-2-methyl-tridecanol 0.03 ±0.00 1-octadecanol 0.04 ±0.00 1-octen-3-ol 0.15 ±0.01 2,4-decadien-1-ol 0.04 ±0.00 1-hexadecanol 0.05 ±0.00 Ethyl-linalool 0.05 ±0.00 Lonol 0.04 ±0.00 Linalool 1.12 ±0.06 Aldehydes 5.43 ±0.01 Butanal, 3-methyl0.12 ±0.01 2-butenal 0.01 ±0.00 2-pentenal, € -0.42 ±0.02 Hexanal 0.07 ±0.00 2-hexenal, € -0.07 ±0.00 Sarbaldehyde (2,4-hexadienal) 0.04 ±0.00 Benzaldehyde 0.75 ±0.04 Benzaldehyde,2-methyl 0.17 ±0.01 € -2-heptenal 0.10 ±0.01 (Z)-4-heptenal 0.07 ±0.00 2,4-heptadienal, (E,Z)- 0.44 ±0.02 2,4-Heptadienal, (E,E)- 0.71 ±0.04 2,4-octadienal 0.02 ±0.00 Citronellal (6-octenal-3,7-dimethyl) 0.07 ±0.00 € -oct-2-enal 0.12 ±0.01 Nonanal 0.06 ±0.00 (E,E)-2,4-nonadienal 1.67 ±0.09 € -2-decenal 0.13 ±0.01 (E,Z)-2,4-decadienal 0.02 ±0.00 2-dodecenal 0.09 ±0.00 (E,Z)-2,4-dodecadienal 0.44 ±0.00 Photocitral 0.04 ±0.00 Ketones 7.57 ±0.04 2-propanone 4.21 ±0.18 Acetoin (2-butanone,3hydroxy) 0.13 ±0.01 2-pentanone 0.52 ±0.02 4-hydroxy-4-methyl-2-pentanone 0.02 ±0.00 (continued on next page) F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 6 Table 6 (continued) Compounds (relative amount, %) R. okamurae 5-hepten-2-one, 6-methyl0.50 ±0.03 3,5-heptadien-2-ona, 6-methyl1.82 ±0.10 6-octen-2-one 0.02 ±0.00 2-octanone 0.07 ±0.00 3-octen-2-one 0.03 ±0.00 3,5-octadien-2-one (E,E)- 0.08 ±0.00 3-hexen-2-one/4-methyl-4-octenal 0.05 ±0.00 (E,E)-2,4-dodecadienal 0.30 ±0.02 Valerophenone 0.02 ±0.00 Aliphatic hydrocarbons 34.66 ±0.02 2-hexene-3,5,5-trimethyl0.11 ±0.01 Heptane 0.38 ±0.02 Heptane, 2-methyl0.35 ±0.02 Heptane, 2,3-dimethyl0.84 ±0.04 1,6-dimethylhepta-1,3,5-triene 0.18 ±0.01 7-hexyl-eicosane 0.08 ±0.00 3-ethyl-1,5-Octadiene 0.51 ±0.02 Decane 1.01 ±0.04 Dodecane 0.54 ±0.03 Tridecane 0.13 ±0.01 Tetradecane 0.48 ±0.03 Pentadecane 29.28 ±1.62 Heptadecane 0.56 ±0.03 8-Heptadecene 0.40 ±0.02 9-nonadecene 0.26 ±0.01 1,4,6,9-nonadecatetraene 0.03 ±0.00 Farnesan (Dodecane,2,6,10-trimethyl) 0.03 ±0.00 Phytone/Phytol 0.06 ±0.00 Tricosane 0.14 ±0.01 Tetracosane 0.03 ±0.00 Pentacosane 0.04 ±0.00 Heptacosane 0.06 ±0.00 Octacosane 0.06 ±0.00 Aromatic hydrocarbons 1.20 ±0.00 p-xilene (1,4-dimethyl-benzene) 0.25 ±0.01 o-xilene (1,2-dimethyl-benzene) 0.06 ±0.00 1,3,5-trimethyl-Benzene 0.03 ±0.00 Styrene 0.65 ±0.04 o-cymene (benzene,1-methyl-2-(1-methylethyl) 0.05 ±0.00 Cumene (benzene 1-methylethyl-) 0.01 ±0.00 p-cymene (benzene,1-methyl-4-(1-methylethyl) 0.01 ±0.00 Dimethylstyrene 0.04 ±0.00 Benzene, 1,3-bis(1,1-dimethylethyl)- 0.13 ±0.01 Lactones 0.13 ±0.00 δ-decalactone 0.07 ±0.00 γ-dodecalactone 0.07 ±0.00 Esters 2.00 ±0.00 Linalyl formate 0.85 ±0.05 butanoic acid, butylester/Isopropyl myristate 0.09 ±0.01 Butanoic acid, decylester 0.05 ±0.00 (2Z)-2-pentenylacetate 0.09 ±0.00 Hexanoic acid, hexylester 0.02 ±0.00 2-ethylbutylhexanoate 0.03 ±0.00 Valeric anhydride (pentanoic acid,1,1-anhydride)/ 4-heptanone, 3,5-dimethyl 0.03 ±0.00 Heptadecanoic acid ethyl ester 0.07 ±0.00 Methyl oleate 0.56 ±0.03 Methyl palmitate 0.07 ±0.00 Ethyl oleate 0.03 ±0.00 Ethyl palmitate 0.16 ±0.01 Terpenes 27.71 ±0.04 Limonene 0.63 ±0.04 Eucalyptol 0.58 ±0.03 Cymen-7-ol 0.05 ±0.00 ß-thujone 0.02 ±0.00 Trans-3-caren-2-ol 0.02 ±0.00 Germacrene 0.17 ±0.18 Bourbonene 1.86 ±0.10 Selinene/Elemene 1.14 ±0.06 β-copaene/ α -cubebene/Germacrene 0.37 ±0.02 α -cubebene/Ylangene 0.33 ±0.02 α -cubebene/Armorphene/Cadina-3-5-diene 0.05 ±0.00 ß-cyclocitral 0.12 ±0.01 1-epi-cubenol 0.02 ±0.00 β-caryophyllene 0.64 ±0.04 Table 6 (continued) Compounds (relative amount, %) R. okamurae Seychellene/β-chamigrene 0.04 ±0.00 Gurjunene/Guaiene/Guaia-1(5),11-diene 0.25 ±0.01 Acoradiene/Copaene/Cubenene/amorphene 0.19 ±0.01 acoradiene/ acorenol 0.31 ±0.02 Acorenol/Elemene/Neocalitropsene 0.36 ±0.02 Borneol 0.04 ±0.00 Germacrene-D/Copaene/Cubenene/amorphene 2.25 ±0.12 Bisabolene 0.19 ±0.01 α -farnesene 0.03 ±0.00 Guaia-1(5),7(1)-diene 0.04 ±0.00 delta-cardinene/Cadina-1(10),4diene 0.06 ±0.00 Chrysanthenone 0.08 ±0.00 2-pien-10-ol 0.07 ±0.00 Cumene/Benzene,1,3,5 trimethyl/ o-ethyl-toluene 0.06 ±0.00 Calamenene/Cadina-1,3,5-triene 0.03 ±0.00 α -Ionone 0.11 ±0.01 Bisabolone, oxide 0.07 ±0.00 Caryophyllene,oxide 0.09 ±0.01 Elemene/Hinesol 0.19 ±0.01 Borneol 0.04 ±0.00 cis-β-terpineol/pinocamphone 0.04 ±0.00 Geijeren/Pregeijerene 0.02 ±0.00 Santalol 0.29 ±0.02 β-ionone 0.25 ±0.01 Cembrene 0.15 ±0.01 β-humulene 0.15 ±0.01 Elemene/Isogermacrene/Valencene 0.08 ±0.00 Thujopsene 0.10 ±0.01 β-ionone, 5,6-epoxy 2.26 ±0.01 Humulene/Verticiol 0.48 ±0.03 Caryophyllene/Khusimene 3.96 ±0.22 Guaia-5-11-diene 0.21 ±0.01 Cubebene 0.81 ±0.98 Elenene 0.29 ±0.02 Guaia-5-11-diene/Elemene 0.16 ±0.01 Verticiol/Rimuen/Rosa-5,15-diene 0.05 ±0.00 Bulnesene 0.19 ±0.01 Muurolene/ Copaene 0.03 ±0.00 Retinol 6.68 ±0.37 Retinol acetate 0.37 ±0.02 Retinal 0.22 ±0.25 Cubitene 0.21 ±0.01 Pregeijerene 0.06 ±0.00 FoKienol 0.06 ±0.00 Retinol acetate 0.75 ±0.36 Cedranediol 0.02 ±0.00 Bacdanol 0.27 ±0.01 Cedr-8-en-13-ol 0.23 ±0.01 Cuprenene 0.52 ±0.03 Methandrostenolone 0.14 ±0.01 Retinoic acic methylester 0.15 ±0.01 Nitrogen compounds 0.004 ±0.00 Indane 0.01 ±0.00 Sulphur compounds 0.10 ±0.01 Dimethyl sulfoxide 0.10 ±0.01 Furan compounds 0.72 ±0.00 Furan, 2-pentyl0.16 ±0.01 trans-2-(2-pentenylfuran) 0.09 ±0.00 2(5H)-furanone,5,5-dimethyl 0.07 ±0.00 Benzenothiofuran 0.34 ±0.02 2(4H)-benzofuranone,5,6,7,7atetrahydro-4,4,7a-trimethyl 0.07 ±0.01 Naphthalene derivatives 0.37 ±0.02 1,4-dimethyltetralin 0.19 ±0.01 2,7-dimethyltetralin 0.21 ±0.01 Others 0.52 ±0.00 Dibromomethane 0.10 ±0.01 Bromoform 0.37 ±0.02 Biphenyloxide 0.03 ±0.00 Dibuthylphatale 0.02 ±0.00 Unknows 0.81 ±0.02 F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 7 content of sulphur, in spite of the sulphur-containing amino acids lack, might be due to sulphated polysaccharides like fucoidan and alginate. These compounds have sulphur atoms attached to their sugar units, contributing significantly to the overall sulphur content (Usov et al., 2022). The variability of mineral content, in terms of total concentration, but also in the specific contribution of each of them, has to be comprehensively addressed in the assessment of novel sources, and it is important to know the main factors affecting this compositional data. As the presence of specific heavy metals may pose a risk if intended to be used as food ingredient, research is being done to reduce their content by using innovative strategies such as ultrasounds technologies (NoriegaFern´ andez et al., 2021). 3.1.6. Volatile compounds In Table 6, the volatile compounds identified are indicated, together with the percentage of area. 114 compounds were identified with aliphatic hydrocarbons as predominant representing 34.66 % followed by terpenes with values of 27.71 %, alcohols representing an amount of 12.33 %, and carboxylic acids and ketones around 7 %. As reported in other brown algae, aliphatic compounds (e.g., pentadecane) were the majority as reported for Cladostephus spongiosus (Radman et al., 2023) or Amphiroa rigida (Cikoˇ s et al., 2021). Overall, the analysis revealed that the major volatile components were pentadecane (29.28 %), retinol (6.68 %), acetic acid (6.00 %) and 2-propanone (4.21 %). The content of retinol (6.68 %) could be relevant considering the health benefits of this compound when added to the diet. It must be noted that in food, the term vitamin A comprises all-trans-retinol (also called retinol), naturally occurring molecules associated with the biological activity of retinol, and provitamin A carotenoids that are dietary precursors of retinol. Thus, R. okamurae could be of interest for this industry, since it is a form of vitamin A authorised for foods and food supplements (Carazo et al., 2021). On top of that retinol is an effective anti-aging for the skin, due to its ability to stimulate collagen synthesis, reduce oxidative stress, and modulate gene expression (Quan, 2023), so, the use of this macroalgal species as source of anti-aging compounds deserves further investigation. Acetone (4.21 %) can be found as an ingredient in a variety of consumer products ranging from cosmetics to processed and unprocessed foods, it is generally recognized as safe (GRAS) substance when present in drinks, baked foods, desserts, and preserves at concentrations ranging from 5 to 8 mg/L (Besinis et al., 2016). Then, 2-ethylhexan-1-ol (3.59 %) is a natural product found in Camellia sinensis and Alpinia chinensis, whereas trans,trans-2,4-nonadienal (1.61 %) is a natural product found in Artemisia annua, Prunus avium, and Agaricus bisporus. These compounds have been reported that have a fatty, green aroma quality, according to Hosoglu et al. (2020), after identifying them in the microalgae Crypthecodinium cohnii. Similarly, 3,5-heptadien-2-ona, 6methyl- (1.75 %) was found as well in Arthrospira platensis, while not detected on other microalgae and cyanobacteria (Moran et al., 2022). Special attention has to be given to some of these compounds when using this macroalgal species as food or feed, as a long-term chronic toxicity study in mice and rats showed toxicity due to thujone, and consequently, the proposed uses of R. okamurae as a new ingredient should be assessed carefully to ensure its safety. Essential oils, such as limonene, eucalyptol, retinol, etc., have been evaluated as components for feed or food. Thus, future studies should also evaluate changes in the composition of volatiles when considering adding this biomass into food or feed, aiming to establish safe levels of inclusion. 3.2. Ultrastructural characterization Fig. 1 shows different images obtained by SEM, at different configurations. SEM allows to perform detailed observations of the surface of the sample particles at a nanometric scale, which can help to understand the morphology and surface structures that can influence their functional properties and can also be used to verify the uniformity and consistency of the product between different batches. Fig. 1. Surface characteristics of R. okamurae by SEM. Images were taken at (A) Magnification 50×(scale marks =100 μ m), (B) 200×(scale marks =30 μ m), (C) 500×(scale marks =10 μ m), and (D) 981×(scale marks =10 μ m), and AV =2.0 kV for all. F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 8 3.3. Antioxidant activity The antioxidant activity of R. okamurae was evaluated by the DPPH radical scavenging method. The samples of this study had an EC 50 value of 2.090 ±0.093 mg/mL, which is in line with recent reports evaluating the in vitro antioxidant activity of ethanolic extracts achieved from Fig. 2. Number of sequences (Y-axis) with specific peptide length (from 7 to 26 amino acids length – X axis). Table 7 Characterization of the 20 peptides sequences with a molecular weight below <1000 Da identified in R. okamurae on the basis of in silico analyses. Peptides ToxinPred a Pasta 2.0 b Hydrophobicity Steric hindrance Water Solubility pI Charge Amphipathicity Selfagg c Disorder probability Secondary structure d α -helix β-strand Coil VAPEEHPV −0.06 0.5 Good 4.51 −1.50 0.5 1–4 (NI) 100 – – 100 APILVPVGK 0.17 0.58 Poor 9.11 1.00 0.41 3–7 (NI) 100 –11.11 88.89 FVKGYKY −0.12 0.69 Good 9.55 2.00 1.05 1–7 (NI) 100 – – 100 KEAKEVVE −0.34 0.67 Good 4.79 −1.00 1.39 4–8 (NI) 100 50 –50 KAALDLWK −0.12 0.59 Good 8.94 1.00 0.92 4–7 (NI) 100 50 –50 KAAIDLWK −0.1 0.61 Good 8.94 1.00 0.92 4–7 (NI) 100 37.5 –62.5 TGLFLDPKG −0.01 0.61 Good 6.19 0.00 0.41 1–5 (NI) 100 – – 100 VFTGSPGKY −0.01 0.62 Poor 8.94 1.00 0.41 1–4 (NI) 100 – – 100 TVDAKAGVKA −0.11 0.63 Good 8.94 1.00 0.73 1–4 (NI) 100 – – 100 ITDEDIKQ −0.32 0.69 Good 4.03 −2.00 0.77 4–7 (NI) 100 50 –50 VGDGIARIY 0.01 0.68 Good 6.19 0.00 0.27 5–9 (NI) 100 –22.22 77.78 ETGIKVVDL −0.01 0.66 Good 4.38 −1.00 0.55 4–7 (NI) 100 –33.33 66.67 AGFAGDDAPR −0.16 0.62 Good 4.21 −1.00 0.25 1–4 (NI) 100 – – 100 SHISTGGGASL 0.06 0.54 Poor 7.1 0.50 0.13 2–5 (NI) 100 – – 100 VAPEEHPVL 0.01 0.05 Good 4.51 −1.50 0.44 6–9 (NI) 100 – – 100 SQSEKDWD −0.5 0.64 Good 4.03 −2.00 0.77 2–5 (NI) 100 – – 100 VVIGHVDAGK 0.07 0.61 Good 7.09 0.50 0.51 1–6 (PA) 100 –40 60 EAGGITQHVS −0.03 0.57 Poor 5.25 −0.50 0.4 5–9 (NI) 100 – – 100 VLVGGSTRIP 0.04 0.61 Poor 10.11 1.00 0.25 1–4 (NI) 100 – – 100 TPDLTDPKL −0.22 0.56 Good 4.21 −1.00 0.41 3–6 (NI) 100 – – 100 a Peptides were subjected to calculation via https://webs.iiitd.edu.in/raghava/toxinpred/design.php/. where the hydrophobicity, steric hinderance, solubility, isoelectric point (pI), charge, and amphipathicity were calculated. b The web server PASTA 2.0 (http://protein.bio.unipd.it/pasta2/) computes the tendency of peptide self-aggregation (Self-agg) to the possible region at sequence. The probability of intrinsic disorder and portion of estimated secondary structure that complement the aggregation data were also reported. c Self-aggregation-prone region and amyloids (Parallel aggregation (PA) and Non aggregating residue (NI)); d Probability in secondary structure. F. Rivero-Pino et al. Food Chemistry 473 (2025) 143084 9