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Article

Enzymatic Process for Cystoseira barbata Valorization: Ethanol Production and Additional By-Products

by
Doinita-Roxana Cioroiu Tirpan
1,2,
Ancaelena Eliza Sterpu
2,*,
Claudia Irina Koncsag
2,
Alina Georgiana Ciufu
1 and
Tănase Dobre
1
1
Chemical and Biochemical Engineering Department, University “Politehnica” of Bucharest, 1-7 Gheorghe Polizu Str., 011061 Bucharest, Romania
2
Chemistry and Chemical Engineering Department, Ovidius University of Constanta, 124 Mamaia Blvd., 900527 Constanta, Romania
*
Author to whom correspondence should be addressed.
Processes 2021, 9(5), 741; https://doi.org/10.3390/pr9050741
Submission received: 26 March 2021 / Revised: 14 April 2021 / Accepted: 20 April 2021 / Published: 22 April 2021
(This article belongs to the Special Issue Bioethanol Production Processes)
Browse Figures
Versions Notes

Abstract

:
The aim of this study is to evaluate the potential of dried Cystoseira barbata alga for ethanol production through alcoholic fermentation. The influence of the main factors affecting the fermentation are studied in the frame of a 23 factorial experimental plan. The main factors influencing the process are the fermentation temperature (t from 25 °C to 35 °C), the solid to liquid ratio (S/L from 0.040 g/g to 0.080 g/g), and the cellulase ratio (R from 8 U/g d.m to 16 U/g d.m.). The maximum volatile compounds yield of 0.2808 g/g d.m and ethanol yield of 0.0158 g/g d.m were favored by the following experimental conditions: process temperature of 35 °C, solid to liquid ratio of 0.0415, and enzyme ratio of 16 U/g d.m. A statistical model was used to correlate the product yield with the process factors. Additionally, 19 interesting bioactive compounds were found in the enzymatic hydrolysis and alcoholic fermentation broths which seem likely to maintain natural defence mechanisms against diseases and physical disorders.

1. Introduction

Nowadays, the main concern in industry is the depletion of fossil fuels and the excessive pollution of the environment they bring about; thus, the use of the planet’s renewable resources has become a challenge. However, the production of biofuels such as biodiesel, bioethanol, and biogas has certain limitations. In the case of first-generation feedstocks, there are moral issues regarding the food versus fuel debate in the context of the worldwide alimentary crisis. For second-generation feedstocks, there is intense discussion regarding the high costs of biomass pre-treatment in the production process [1]. In this regard, the transition was made to third-generation biomass consisting of microalgae, cyanobacteria, and macroalgae, which have multiple advantages, such as their low requirements in terms of cultivation area and water quality (they may grow in seawater, freshwater, or wastewater), as well as their resistance to unfavorable climatic conditions. Additionally, algae have a high growth rate, up to 20 times faster than that of terrestrial plants, and they absorb carbon dioxide from the atmosphere. Seaweeds are recognized as a source of bioethanol [1,2,3,4,5,6], particularly as the absence of lignin makes polysaccharides saccharification easier [4].
On the other hand, macroalgae are known for their yield of bioactive products, which can be extracted through different methods [7,8,9,10,11] and used as food supplements or pharmaceutical products [12,13,14,15].
Brown algae are a phylum of macrophytes with a high content of carbohydrates, contributing up to 60% of their dry matter (d.m.) [16,17], but this depends on the species [18], place, harvest time, water temperature, availability of light during the day, salinity, nutrients concentration, and pre-treatment and extraction methods used. The high content of sugars makes them a promising feedstock for bioethanol production by aquaculture [19,20,21].
Cystoseira barbata (class Phaeophyaceae, order Fucales, family Sargassaceae) is a species that is spread along the Romanian southern coast of the Black Sea [22]. The alginate is the main polysaccharide found in C. barbata in the Black Sea, accounting for 19 ± 1.5% (w/w) of the dry mass [8]. Other polysaccharides present in brown algae are laminaran, mannitol, fucoidan, and cellulose. Selimi et al. [23] demonstrated that the carbohydrate fraction is sulphated (13.81%) and conjugated with proteins (9.86%) and phenolic compounds (4.98%). This is an indication that, in the enzymatic processes leading to bioethanol production, other products are formed, some of them possibly bioactive [24,25,26]. Additionally, the Cystoseira barbata species is known for its biomedical and pharmaceutical potential, because it contains a variety of bioactive natural substances with antimicrobial, antifungal, antiviral, and antitumor activity [27].
This study focuses on evaluating the potential of the edible brown macroalga Cystoseira barbata for bioethanol production in parallel with identifying bioactive compounds with therapeutic properties released during enzymatic processes.

2. Materials and Methods

2.1. Materials

The Cystoseira barbata species was collected on Mangalia beach (N 43°48′36″ E 28°35′13″), Romania, immediately after a storm in June 2019.
Cellulase from Aspergillus niger, 0.8 U/mg off-white powder, was produced by Sigma Aldrich.
Commercial Saccharomyces cerevisiae yeast was procured from SC ROMPACK SRL.

2.2. Equipment and Analysis Methods

The determination of water content in the fresh and dried alga was performed with the OHAUS thermo-balance, model MB45. The drying took place in three steps: 7 min at 200 °C, 1 min at 150 °C, and 12 min at 105 °C.
For the IR spectrum, the apparatus Nicolet 6700- Thermo Scientific (manufacturer: IKA, location: Watertown, Massachusettes, USA) with the technique ATR-Attenuator Total Reflectance was used. The sample was introduced in the apparatus on a GeSe crystal, and the spectrum was performed in the range of 4000 to 600 cm−1. The final spectrum was the average of 135 scans.
The chemical composition of the algae was determined by adapting the separation scheme inspired from [28,29] for the extraction of cellulose: approx. 17 g of dried and ground raw material was placed in a Soxlet apparatus and ethanol extraction of lipids and pigments was performed, then the dry powder was recovered. From this powder, the recovery of alginates in a hydrosoluble form was performed by digestion in ammonium oxalate solution 0.05% (w/w) at boiling point for 1 h. The following step consisted of bleaching the remaining powder in a 2:1 mixture of acetic acid 5% solution and sodium chlorite 2% solution for 3 h at 60 °C. Water rinsing was conducted until a neutral pH was reached. After filtration, the cake was soaked in 0.5 M NaOH solution for 12 h at 60 °C. After washing and drying, the resulting powder was boiled in 5% (v/v) hydrochloric acid solution for 3 h. This suspension was then filtered, washed to neutral, and dried to obtain the cellulose fibers.
The volatile compound concentration in the distillate was determined by adapting the Standard Romanian method SR 184-2/2010 on the oenological apparatus Class-CHEM, Italy, model OH-1. The method was originally intended for the determination of the ethanol concentration in beverages. The relative density of the solution to water was measured with the pycnometer. A total of 200 mL of sample + 60 mL added water was distilled in the apparatus, obtaining 200 mL distillate, then the relative density d 20 20 was correlated with the alcoholic concentration (g/L). Due to the complex composition of the distillate, in this case the measured concentration was expressed as the volatile compounds concentration equivalent to ethanol ( d 20 20 = 0.79 ) .
LC-MS analyses were performed on an ultra-precision liquid chromatograph coupled with a liquid-gas (nitrogen) mass spectrometer from Agilent Technologies 6540 UHD Accurate- Mass Q-TOF. The mobile phase was 0.1% (v/v) formic acid. The analysis was performed at 30 °C with positive and negative ionization.

2.3. Pre-Treatment Process

The algae were washed with seawater in an attempt to remove sand and epiphytes, cleaned from scraps from other algae species such as Ulva lactuca and Cladophora vagabunda, then transported to the laboratory in plastic containers and washed again with distilled water to remove salt.
The humidity of a fresh alga sample was measured with the thermo-balance, as described in point 2.2, resulting in 81.36 ± 0.9% (w/w). Then, the fresh algal material was dried in a hot air dehydrator at 45 °C until reaching a constant weight and the remaining humidity was determined with the thermo-balance with the same method. The aim of the drying was to preserve the material for a longer time. At 25 °C and a relative air humidity of 55%, the remaining humidity in the dry plant was 12.48 ± 0.4% wt.
The dried material was milled in a grinder and passed through a certified granulometric sieve with a mesh size of 630 μm, thus reducing the raw material size for the more efficient further saccharification of polysaccharides [5].

2.4. Enzymatic Hydrolysis for Polysaccharides Saccharification

Enzymatic hydrolysis has a higher potential compared to acid hydrolysis, because it uses less energy to break the walls of cells, gives higher yields in ethanol, and no residual products are formed [30,31,32,33].
For the enzymatic hydrolysis, 40 g of algal powder (approximately 35 g d.m.) was boiled in a certain quantity of distilled water (420 mL or 840 mL) for 25 min for sterilization. After the cooling the mixture to approx. 40 °C, cellulase was added at different ratios (8 or 16 U/g d.m.) and pH was regulated at 5.5–6 from a natural one of 6.8 with a few drops of 20% (w/w) citric acid solution. It is preferable to use commercial cellulase because traces of other enzymes present in the major enzyme of interest (in this case, cellulase enzyme) will give added advantages during processing [34,35], such as a higher yield in saccharification. Enzymatic hydrolysis was performed at 40 °C in a shaking incubator cabinet for 24 h. After hydrolysis, a sample was collected and filtered for the LC-MS analysis. The results and discussion are presented in Section 3.4.

2.5. Bioethanol Production through Alcoholic Fermentation

After the release of the fermentable sugars during the enzymatic hydrolysis, the algal broth was filtered and the solution was used for the next step. The alcoholic fermentation started after adding 1 g of commercial yeast Saccharomyces cerevisiae to the filtrate, proceeding from 420 mL or 840 mL initial distilled water, as explained above; anaerobic conditions were secured. Saccharomyces cerevisiae is the most commonly used yeast because it has a high tolerance to unwanted inhibitory compounds and a high glucose fermentation capacity [33,35]. Further, the solution was kept in the dark and at afixed temperature, under mild agitation, providing ethanol formation and carbon dioxide accumulation. The amount of CO2 produced was measured at room temperature (25 °C) with a gasometer during fermentation and related to the bioethanol production.
The total concentration of volatile compounds was determined after the distillation of the fermented broth, by correlating the density of the distillate with the content of Organic Matter (OM, equivalent to g/L ethanol).

2.6. Experiment Design

A statistical model according to a 23 factorial plan (3 process factors at 2 levels each) was designed. Based on previous experimental studies [5,32], the main factors affecting the products yields in case of enzymatic hydrolysis followed by ethanolic fermentation are: the proportion between dry alga and water in weight, namely solid- to- liquid ratio (S/L, g/g), the cellulase ratio (number of enzyme units per gram of dry matter, (R, U/g d.m.) and the temperature of the alcoholic fermentation (t, °C).
The independent variables were set at two levels: S/L = 0.0415 or 0.083 g/g, R = 8 or 16 U/g d.m., and t = 25 or 35 °C. The dependent variables were the volatile compounds yield (V, g/g d.m.) and ethanol yield (E, g/g d.m.) which were considered the process responses.

3. Results and Discussion

The results of the experiment are presented and discussed in the following.

3.1. FT-IR Spectrum of Cystoseira Barbata Powder

In interpretation of the results, the group frequencies characteristic of the main organic substances were considered.
The FT-IR spectrum of Cystoseira barbata powder, presented in Figure 1, highlights several characteristic bands—intense, average, or slight—specific for particular functional groups. Their identification was conducted in comparison with bands specified in the literature [36].
The signal at 3353.25 cm−1 corresponds to the -OH group (υOH = 3200–3600 cm−1), but in the same broad band the presence of the amine group is also detected (υNH = 3300–3500 cm−1). The width of the 3353.25 cm−1 band denotes the association of molecules with hydrogen bonds. The presence of -NH bending at 1608.62 cm−1 also confirms the presence of amine groups. A band of medium intensity at 2925.72 cm−1 shows the valence vibration of C-H bonds in alkane chains (υCH = 2850–2960 cm−1); there is a fairly broad band which may indicate the presence of a carboxylic acid with molecules strongly associated with hydroxyl groups with hydrogen bonds (υ-OH = 2500–3200 cm−1). Some valence vibration at 1031.28 cm−1 may indicate the simple bond C-O in ethers and esters (νC-O = 1050–1250 cm−1). Alkane chains and ester groups denote the lipids, since C=0, C-O, and carboxy groups are present in polysaccharides such as alginates (containing units of mannuronic and guluronic acid) and cellulose. The functional groups -NH2 and -COOH indicate the presence of amino acids, constituents of proteins; the amino acids found in dry alga samples will boost the alcoholic fermentation and influence the product range found in the fermentation broth.
In conclusion, from the FT-IR spectrum the prevalence of polysaccharides in the composition of algae can be observed, with some of the polysaccharides constituting the raw for alcoholic fermentation. Additionally, lipids and proteins in the composition of algae are a source of other compounds produced in the hydrolysis and fermentation processes.

3.2. Fiber Analysis Results

A chemical analysis of the algae was performed as described in Section 2.2, and the results are presented in Table 1. The main aim was to determine the cellulose content as the raw material for the ethanolic fermentation.

3.3. Statistical Model for the Alcoholic Fermentation

The experiment design is described in point 2.6. The experiment aimed to obtain a statistical model for the correlation of the product yield with the process factors.
As seen in Figure 2, in all runs, the alcoholic fermentation started almost immediately after adding the yeast; the CO2 volume (and the corresponding ethanol quantity) increased steadily over time. Most of the batches ceased fermentation after 7 h, as CO2 did not form anymore. The final quantity (g) of CO2 was then calculated with the ideal gas law and correlated with the ethanol quantity through stoechiometric calculations. Additionally, from Figure 2 corroborated in Table 1, the efficiency of the ethanol production can be deduced. The poorest efficiency is reached at t = 25 °C, S/L = 0.083, and U = 8 U/g d.m, and the highest at t = 35 °C, S/L = 0.0415, and U = 16 U/g d.m. From Table 1, one can observe that the bioethanol yield increases with increasing fermentation temperature and enzyme ratio and decreases with the decrease in the solid to liquid ratio, thus confirming the observations of a previous study carried out on dried Ulva lactuca species [5]. The same tendency was observed for the volatile compounds yield.
These observations can be quantified by a mathematical correlation.
The yields of volatile compounds and ethanol obtained in enzymatic hydrolysis followed by ethanolic fermentation of dry brown algae are summarized in Table 2.
The maximum volatile compounds yield was 0.2808 g/g d.m, while the ethanol maximum yield was 0.0158 g/g d.m or 0.102 g/g cellulose, compared with the theoretical yield of 0.51 g ethanol/g cellulose. In the same conditions, from Ulva lactuca the maximum ethanol yield was 0.0234 g/g DM [37], so the potential for ethanol production is 32.4% lower for Cystoseira barbata. This can be explained by chemical composition differences between the algae. U. lactuca has a higher content in polysaccharides readily saccharificable, such as cellulose, while C. barbata contains a lower content of such polysaccharides, such as laminaran, mannitol, and cellulose. Few studies on bioethanol production from brown algae class Phaeophyaceae have been published. Khan and Noreen [38] reported an ethanol production between 0.0065 and 0.017 g/g d.m for Cystoseira indica and 0.013 and 0.035 g/g d.m for Sargassum tenerrimum, while Hamouda et al. [39] reported an ethanol production from Cystoseira compressa between 0.045 and 0.050 g/g d/m. Alginate from C. barbata is more difficult to destroy with cellulase to obtain fermentable sugars [40]. Metabolically engineered microbes would be more efficiently utilized for the transformation of alginate in fermentable sugars [20].
For the model describing the volatile compounds yield (V) (Equation (1)) and ethanol yield (E) (Equation (2)), linear regression analysis was used to evaluate the correlation between the independent variables and the dependent ones.
V = 0.00453 U + 0.01065 t − 0.71566 S − 0.13425,
E = 0.00030 U+ 0.00052 t − 0.03313 S − 0.00696.
The coefficients’ significance was tested using the statistical technique ANOVA (Analysis of Variance). In Table 3 and Table 4, the results of this analysis are presented for the coefficients of Equation (1) and Equation (2), respectively. The ANOVA test shows that all the equation coefficients are significant and indicates that there is strong evidence against the null hypothesis (p < 0.05).
In conclusion, the statistical model is accurate in the customary range of process factors. Additionally, the model reflects the tendency of the products yields to increase with increasing fermentation temperatures and cellulase ratios, and to decrease with increasing solid to liquid ratio.

3.4. Bioactive Compounds Identification

As it is known, brown seaweeds are a significant source of bioactive compounds such as vitamins, minerals, polysaccharides, polyphenols, and fatty acids, which are beneficial in herbivore food [8,41]. In the present study, other compounds were searched for, possibly to be released in the enzymatic processes intended for ethanol production from C. barbata.
A batch was processed with the parameters corresponding to Run#8 in Table 1, because this run gave the highest yields of volatiles and ethanol, so it was probable we would find more compounds in the broth. A sample (10 mL) was collected after hydrolysis for analysis. Then, the remaining hydrolysate was filtered and submitted to alcoholic fermentation. Afterwards, the broth was distilled, collecting up to 100 mL and aiming not to exceed the temperature of 100 °C. The distillate was also analyzed by LC-MS.
The chromatogram for the hydrolysate is presented in Figure 3. The main peaks were identified at retention times in the range of 2.372 to 4.612 min, with another important peak being situated at RT = 21.358 min.
The MS spectra were found with negative and then positive ionization, and, for each important peak, the MS spectra were interpreted. The apparatus holds a library of compounds, but some of the compounds were still unidentified and the researchers had to propose structures in accordance with the molar weight, with the aid of NIST Chemistry Webbook, SRD 69 [42], PubChem [43], and taking into account the possible transformations of polysaccharides. In the enzymatic hydrolysate, over 43 ions were identified, most of them with a mass-to-charge under 200 Da, but, as seen in Figure 4, in the MS spectrum (negative ionization) corresponding to the peak at RT = 2.372 there are also larger ions such as m/z = 827.30 or 1151.42.
The most abundant bioactive compounds from the hydrolysate, identified in the MS spectra with a negative ionization are listed in Table 5.
The potential benefits of the compounds are presented further:
Malonic acid (m/z = 103.00) is a basis substance for the synthesis of drugs with anti-inflammatory and antimicrobial activity [44] or for synthesis of valproate, which is used to treat epilepsy [45] and bipolar disorder. β-hydroxybutyric acid (m/z = 113.00), one of the most abundant compounds in the broth, was obtained in the fragmentation of alginate macromolecules in a fragment shorter than guluronic acid; β-Hydroxybutyrate can be used as an energy source in the brain when blood glucose is low [46], and it is able to cross the blood–brain barrier into the central nervous system [47]. Maltol (m/z = 125.02) is a protective agent for oxidative stress related to ocular diseases, including glaucoma [48]. Phloroglucinol is another possible compound with m/z = 125.02; it is a commercial drug with antispasmodic properties. Thiophenecarboxilic acid (m/z = 127.00) is an intermediate compound for the synthesis of thiourides: antihistaminic, tuberculostatic, sedative drugs, etc. [49]. Diallyl disulphide (m/z = 145.01) is an organosulfur compound with anti-inflammatory and antioxidative activity in emphysema [50]. Phenyl Iminoacetate (m/z = 147.03) could be an intermediary in the synthesis of isatin derivatives, with potential antibacterial activity [51], or in N-Mannich bases with mitodepressive properties [52]. Ligands of Asparagusic acid (m/z = 149.1) with Pt (II) showed interesting anticancer results in cisplatin-resistant cell lines [53]. S-Propyl 2- propene-1-sulfinothioate (m/z = 165.04) is also a constituent of garlic oil, with anti-neoplasic and antifungal activity. Derivatives of 3-Acetylcoumarin (m/z = 187.11) were tested in vitro for anticancer activity, some of them with good results [54]. Semustine (m/z = 247.00) is a drug used in chemotherapy to treat various types of cancer [55]. The imidazole moiety of 2-Undecyl-1H-imidazole-carbothioic acid (m/z = 265.16) has antifungal activity, and imidazole derivatives synthesized in recent years are drugs used to treat a broad spectrum of diseases [56]. Estazolam (m/z = 293.2) is a benzodiazepine with anticonvulsant, hypnotic, and muscle relaxant activity [57].
Additionally, in the negative ion spectra, at RT = 4.348 and 4.612 min, reducing sugars with m/z = 193,1: Guluronic acid (C6H10O7) and 3-O-methyl-α-D-glucopyranose (C7H14O6) were found, as monomers in the structure of alginate. Their relative abundance was high: 30% and 43%, respectively. In alcoholic fermentation, they are precursors of ethanol. The same compounds were detected also in the MS spectrum, with positive ionization at RT = 4.369 min and a relative abundance of 39.3%. However, in general different compounds were identified in positive ionization spectra, as seen in Table 6.
These are bioactive compounds or bases for other bioactive compounds, as follows:
3-Mercaptopropionic acid (m/z = 107.09) is a building block for glycopeptide synthesis. Nicotinyl alcohol (Piconol) (m/z = 110.2) serves as an intermediate in the synthesis of ibuprofen piconol, a nonsteroidal anti-inflammatory agent [58]. Furoic acid (m/z = 127.06) was also found in the positive spectrum of the peak RT = 3.247 min (relative abundance, 27.6%), and its alkyl esters have an anesthetic activity [59]. The bioactivity of compounds Maltol/Phloroglucinol (m/z = 127.06) was explained before; they were also identified in the spectrum of peak RT = 3.142, with negative ionization. 5-Aminobarbituric acid (m/z = 144.02) in a hydantoin rearrangement results in an anticonvulsant agent [60]. Glycerol triformate (Triformin) (m/z = 177.17) is an anti-hyperglycemic agent for the treatment of patients with type 2 diabetes [61]. D-Gluconic acid (m/z = 197.13), C6H12O7, proceeds from glucose under the action of cellulase; it is used to maintain the cation–anion balance in electrolyte solutions [62]; the calcium salt of gluconic acid is used in calcium therapy and iron salt in the treatment of anemia [63]. Methoxalen (m/z = 217.13) is sold under the name Oxsoralen [64] and is used to treat severe psoriasis, eczema, and vitiligo.
Additionally, Glucose (m/z = 181.15) was identified in the spectrum, corresponding to peak RT = 10.306 min (relative abundance, 38.6%), and is a fermentable sugar raw for ethanol.
After the alcoholic fermentation and distillation, the distillate was sampled and analyzed. The LC-MS chromatogram of the distillate is presented in Figure 5.
Most of the compounds detected in the hydrolyzed sample remained in the fermentation broth, and 16 ions were identified in MS spectra of the distillate with negative ionization, at retention times ranging from 2.525 to 10.922 min, but only two had significant abundance. β-hydroxybutyric acid (m/z = 103.00) was detected at RT: 2.525, 2.822, 6.399, 8.584, and 10.922, with a relative abundance between 50.5% and 61.3%, but its absolute abundance decreased to 1.8 × 104–5.4 × 104 compared with the values in the hydrolysate: 7.8·104–1.6·105. This is an indication that the substance was consumed in alcoholic fermentation. N,N-dimethyl glycine (m/z = 103.04) C4H9NO2, at RT = 3.114 min, with a relative abundance of 47.1% is an α-amino acid [65], a nutritional supplement, and a modulator of ketamine in drugs with antidepressant effects [66]. Additionally, Ethanol (m/z = 45.02) was identified in all the peaks, as a low-mass compound with an absolute abundance up to 1.65 × 105. It was differentiated from the solvent, Formic acid (m/z = 45.00), with an abundance of 5.01–5.48 × 105.
In the positive ionization spectra, 17 ions were identified, but only two of them had significant abundance (over 104). Leucine (m/z = 217.13), C6H13O2N (RT = 2.789, 3.141, 3.328, 4.511, 10.322, 19.049, 29.949 min), had a relative abundance between 20% and 33.8% and is an essential amino acid important for hemoglobin formation [67]. Curzene (Isogermafurene) (m/z = 217,13), C15H20O, RT = 10.322, with a relative abundance of 33.1% has cytostatic and antitumor activity with limited toxicity and side effects [68]. Unfermented Glucose(m/z = 181.15) was also detected at RT = 10.322 min.
It is easy to notice that few volatile compounds were detected in the distillate, among them two amino acids, and the β-hydroxybutyric acid was the most abundant. All these bioactive compounds have molecular weights very different from that of ethanol, so it is possible for to be separated from it by membrane filtration.

4. Conclusions

The ethanol was produced from Cystoseira barbata by the enzymatic hydrolysis of polysaccharides with Aspergillus niger cellulase, followed by alcoholic fermentation with Saccharomyces cerevisiae yeast. An experimental plan according to a 23 factorial was designed. The factors of the process were alcoholic fermentation temperature t, solid to liquid ratio S/L, and cellulase ratio R. Correlations between the three factors and the final process responses, including volatile compounds yield V and ethanol yield E, were established in a statistically sound mathematical model. The optimal working parameters (process temperature of 35 °C, solid to liquid ratio of 0.0415, and enzyme ratio of 16 U/g d.m) led to the maximum performance (volatile compounds yield V = 0.2808 g/g d.m. and ethanol yield E = 0.0158 g/g d.m.). The disadvantage of this method in producing ethanol and volatile compounds is the low biomass stock, which makes it impossible to capitalize on this species, but aquaculture under controlled growing conditions can be used.
The enzymatic hydrolysate and the distilled fraction from the ethanolic fermentation were analyzed with an ultra-precision liquid chromatograph coupled with a liquid-gas mass spectrometer (LC/MS). A total of 19 active compounds identified in the samples could be used as drugs or as bases for drug synthesis. The challenge is to validate and quantify these compounds, which are presumed to be in significant concentrations, since the yield of volatile compounds is high (between 0.12 and 0.28 g/g d.m.), and to find an efficient separation scheme.
The use of an edible alga for bioethanol production and additional by-products seems to be in conflict with the need for food security, but as it represents a dietary supplement and not a base food for animals, the alga could serve for both purposes, provided that it is naturally abundant or cultivated.

Author Contributions

Conceptualization, D.-R.C.T., C.I.K. and T.D.; methodology, D.-R.C.T., A.E.S. and A.G.C.; validation, C.I.K. and T.D.; investigation, D.-R.C.T., A.E.S. and A.G.C.; resources, D.-R.C.T., C.I.K. and T.D.; data curation, D.-R.C.T. and C.I.K.; writing—original draft: D.-R.C.T. and A.G.C.; writing—review and editing: C.I.K., A.E.S. and T.D.; supervision, T.D.; project administration, T.D.; funding acquisition, D.-R.C.T. All authors have read and agreed to the published version of the manuscript.

Funding

The work has been funded by the Operational Programme Human Capital of the Ministry of European Funds through the Financial Agreement 51668/09.07.2019, SMIS code 124705.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data used to support the funding of this study are included within the article.

Acknowledgments

The chromatograph Agilent Technologies 6540 UHD Accurate-Mass Q-TOF LC/MS has been purchased by University Politehnica of Bucharest, through the Operational Programme POSSCEA2-O2.2.1.-2013-1 contract No 1970, Code SMIS-CSNR 48652 (2014–2016).

Conflicts of Interest

The authors declare no conflict of interest.

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Processes 09 00741 g001 550
Figure 1. The FT-IR spectrum of Cystoseira barbata powder.
Figure 1. The FT-IR spectrum of Cystoseira barbata powder.
Processes 09 00741 g001
Processes 09 00741 g002 550
Figure 2. The CO2 volume released and accumulated during fermentation vs. time. (run#1, run#2, …, run#8 represent the 8 samples from experimental matrix, Table 2).
Figure 2. The CO2 volume released and accumulated during fermentation vs. time. (run#1, run#2, …, run#8 represent the 8 samples from experimental matrix, Table 2).
Processes 09 00741 g002
Processes 09 00741 g003 550
Figure 3. LC-MS chromatogram of the hydrolysate.
Figure 3. LC-MS chromatogram of the hydrolysate.
Processes 09 00741 g003
Processes 09 00741 g004 550
Figure 4. MS spectrum related to the chromatogram in Figure 2, peak at RT = 2.372.
Figure 4. MS spectrum related to the chromatogram in Figure 2, peak at RT = 2.372.
Processes 09 00741 g004
Processes 09 00741 g005 550
Figure 5. LC-MS chromatogram of the distilled sample.
Figure 5. LC-MS chromatogram of the distilled sample.
Processes 09 00741 g005
Table
Table 1. Composition of Cystoseira barbata powder.
Table 1. Composition of Cystoseira barbata powder.
ComponentsConcentration, % (wt/wt)
Lipids8.20
Alginates14.93
Extractibles in NaOH sol. 0.5M32.08
Extractibles in HCl sol 5% (v/v)28.97
Cellulose fibers15.82
Table
Table 2. Experimental matrix.
Table 2. Experimental matrix.
Run #ParameterV (g/g d.m.)E (g/g d.m.)
t
(°C)		S/L
ratio		U/mg
d.m.		ExperimentalPredictedExperimentalPredicted
1250.08380.11520.10890.00610.0058
2250.083160.14760.14520.00820.0083
3250.041580.13920.13860.00760.0072
4250.0415160.16560.17490.00910.0096
5350.08380.19920.21540.01110.0110
6350.083160.25920.25170.01330.0135
7350.041580.25440.24510.01170.0124
8350.0415160.28080.28140.01580.0149
Table
Table 3. ANOVA analysis for the coefficients of Equation (1).
Table 3. ANOVA analysis for the coefficients of Equation (1).
CoefficientsStandard Errorp-ValueLower 95%Upper 95%
Intercept−0.134250.030400.01155−0.21866−0.04983
Variable x1 (t) 0.010650.000810.000200.008370.01292
Variable x2 (S)−0.715660.197570.02231−1.26422−0.16710
Variable x3 (U)0.004530.001020.011440.001690.00738
Multiple R = 0.9902; R square = 0.9805; adjusted R square = 0.9659; standard error = 0.0115.
Table
Table 4. ANOVA analysis for the coefficients of Equation (2).
Table 4. ANOVA analysis for the coefficients of Equation (2).
CoefficientsStandard Errorp-ValueLower 95%Upper 95%
Intercept−0.006960.001830.01929−0.01206−0.00186
Variable x1 (t) 0.000524 × 10−50.000450.000380.00066
Variable x2 (S)−0.033130.011940.05010−0.066282 × 10−5
Variable x3 (U)0.000306 × 10−50.007520.000130.00048
Multiple R = 0.9863; R square = 0.9729; adjusted R square = 0.9526; standard error = 0.0007.
Table
Table 5. Possible bioactive compounds identified in the hydrolyzed sample in MS spectra with negative ionization.
Table 5. Possible bioactive compounds identified in the hydrolyzed sample in MS spectra with negative ionization.
Nr.Namem/zChemical FormulaRetention Time (min)Relative Abundance, %
1.Malonic acid103.00C3H4O42.62529.3
2.80732.0
2.β-hydroxybutyric acid113.00C4H2O40.06130.6
2.62529.3
2.80732.0
2.90647.1
3.14229.0
3.24716.0
3.90723.9
4.34826.0
16.81262.2
21.35838.8
3.Maltol/Phloroglucinol125.02C6H6O33.14229.6
4.Thiophenecarboxilic acid127.0C5H4O2S3.24715.2
5.Diallyl disulphide145.01C6H10S22.8078.7
6.Phenyliminoacetate147.02C8H6NO22.90619.5
7.Asparagusic acid149.1C4H6O2S23.24717.7
4.34848.0
8.S-Propyl 2- propene-1-sulfinothioate163.02C6H12OS22.80711.7
9.3-Acetylcoumarin187.11C11H8O33.90735.4
10.Semustine247.00C10H18ClN3O23.14211.5
3.24734.8
11.2-Undecyl-1H-imidazole-
carbothioic acid		265.16C15H26N2S221.35840.4
12.Estazolam293.2C6H11ClN40.06139.9
Table
Table 6. Possible bioactive compounds identified in the hydrolyzed sample in MS spectra with positive ionization.
Table 6. Possible bioactive compounds identified in the hydrolyzed sample in MS spectra with positive ionization.
Nr.Namem/zChemical FormulaRetention Time (min)Relative Abundance, %
1.3-Mercaptopropionic acid107.09C6H6O2S4.47321.6
2.Nicotinyl alcohol110.2C6H7NO2.66833.3
58.8
3.Furoic acid113.0C5H4O32.66825.6
4.Maltol/ Phloroglucinol127.06C6H6O33.60932.3
5.5-Aminobarbituric acid144.02C4H5N3O34.08817.8
4.36918.0
4.47323.5
4.91325.4
5.49124.0
6.Glycerol triformate177.17C6H8O63.60932.3
7. Gluconic acid197.13C6H12O64.08852.8
8.Methoxalen217.13C12H8O44.91319.5
5.49122.7
10.30621.8
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Cioroiu Tirpan, D.-R.; Sterpu, A.E.; Koncsag, C.I.; Ciufu, A.G.; Dobre, T. Enzymatic Process for Cystoseira barbata Valorization: Ethanol Production and Additional By-Products. Processes 2021, 9, 741. https://doi.org/10.3390/pr9050741

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Cioroiu Tirpan D-R, Sterpu AE, Koncsag CI, Ciufu AG, Dobre T. Enzymatic Process for Cystoseira barbata Valorization: Ethanol Production and Additional By-Products. Processes. 2021; 9(5):741. https://doi.org/10.3390/pr9050741

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Cioroiu Tirpan, Doinita-Roxana, Ancaelena Eliza Sterpu, Claudia Irina Koncsag, Alina Georgiana Ciufu, and Tănase Dobre. 2021. "Enzymatic Process for Cystoseira barbata Valorization: Ethanol Production and Additional By-Products" Processes 9, no. 5: 741. https://doi.org/10.3390/pr9050741

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