Exploration of Microalgae Biorefinery by Optimizing Sequential

Article pubs.acs.org/IECR

Exploration of Microalgae Biorefinery by Optimizing Sequential Extraction of Major Metabolites from Scenedesmus obliquus Faiz Ahmad Ansari,† Amritanshu Shriwastav,†,‡ Sanjay Kumar Gupta,§ Ismail Rawat, and Faizal Bux* Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa ABSTRACT: The effects of six different sequential extractions of proteins, lipids, and carbohydrates on their yields and subsequent biomass recoveries was investigated. The maximum yields of lipids, proteins, and carbohydrates were 26.50 ± 1.32%, 28.14 ± 1.97%, and 16.40 ± 0.43%, respectively, in primary extraction of biomass. Compared to the primary extractions, lipid yields were significantly lowered by 20−22% in secondary extractions. The maximum loss of proteins in secondary (post lipid extraction) and tertiary extractions was 34.79% and 56%, respectively. The most significant loss (38− 44.5%) in carbohydrates was recorded after tertiary extractions. Among all of the extraction sequences, the sequence of proteins−lipids−carbohydrates extracted algae (PLCEA) showed optimum recovery of individual metabolite. For this extraction sequence, the yields of proteins, lipids, and carbohydrates were found to be 28.14%, 22%, and 10.17%, respectively. It was also characterized by the highest residual biomass available for second (80%) and third (61%) steps of extraction. Finally, the cumulative yields of these metabolites were converted into net value gains. The extraction sequence PLCEA could result in 66.5% net value gain overcoming the cost of biomass generation. 2003).15 Therefore, major metabolites targeted for extraction from algae are proteins, lipids, and carbohydrates based on their relative abundance in algal cell and their market value.9,10 The microalgae biorefinery concept has continuously been explored in recent years; however, there are still several challenges. High efficiency extraction of proteins, lipids, and carbohydrates in a sequential extraction process remains one of the challenges yet to be addressed. As the metabolite extraction processes differ in nature, their sequential use affects the extraction potential of the successive metabolites differently.16 Efforts have been made to use alternative low to medium energy consuming processes for extraction such as pulse electric field, ionic liquids, and surfactants.8,11 However, these techniques are still under development and subject to further research before they could be optimized for commercial implementation for all target metabolites.16 Undeniably, reports on extraction of individual metabolites are available in abundance. However, studies on identification and optimization of an extraction sequence are rare and scattered for individual metabolites. To overcome these inadequacies, we have investigated the effect of various sequential extraction processes on the yields of proteins, lipids and carbohydrates in detail. The metabolite yields, biomass recovery potentials and the value extractions of individual

1. INTRODUCTION Microalgae biofuels are a sustainable and renewable alternative to fossil fuels.1,2 Though the microalgae biodiesel production remains the most sought after alternative for transport fuels, several challenges remain.1,3 Generation of biodiesel (fatty acid alkyl esters) from microalgae lipid is a multistep process which includes cultivation, biomass harvesting, lipid extraction, transesterification, and product purification. Many of these processes demand high input cost which makes the process uneconomical which is the major challenge to commercial microalgae biodiesel production.4 However, shifting the focus from a single product strategy (biodiesel production only) to integrated biomass processing for the extraction of major metabolites alongside lipids may help to develop a profitable microalgae biofuel and biorefinery in the near future.5 Since the conceptualization of microalgae biorefinery, various researchers have investigated its feasibility for extracting different metabolites from many algal species.5−10 Nobre et al.11 studied the extraction of lipids, carotenoids, fatty acids, and biohydrogen from Nannochloropsis sp. Similarly, biorefineries for Chlorella vulgaris were analyzed for different compounds, such as lipids and methane (Amon),12 various pigments, and bioelectricity.13 Olguiń 14 also investigated the production of hydrogen, biodiesel, biogas, and other valuable products from Arthrospira. However, earlier studies reported that the production of high value compounds rather than additional forms of energy (biogas or hydrogen) will be more economically sustainable for biofuel production from algae (Central Pollution Control Board (CPCB), New Delhi © 2017 American Chemical Society

Received: Revised: Accepted: Published: 3407

December 13, 2016 February 12, 2017 March 10, 2017 March 10, 2017 DOI: 10.1021/acs.iecr.6b04814 Ind. Eng. Chem. Res. 2017, 56, 3407−3412

Article

Industrial & Engineering Chemistry Research

for 10 min. Solvent containing extracted lipids was centrifuged and vacuum filtered. Solvent was evaporated to dryness in an oven at 60 °C. Total lipids were quantified gravimetrically and expressed as percentage dry cell weight. 2.4. Protein Extraction from Biomass. 2.4.1. Protein Extraction. Protein extraction was done according to Barbarino and Lourenco.18 In brief 50 mg of dried microalgal biomass was mixed with 4 mL of ultrapure water and incubated for 12 h at 4 °C. Before 1 h of incubation period the algal mixture was ground for 5 min by mortar and pestle. To recover all of the ground sample, 4 mL of ultrapure was added to rinse the mortar pestle. After grinding, the mixture was centrifuged (at 4 °C, 15000g) for 20 min. Supernatant was collected and microalgal pellets were re-extracted with 1 mL of 0.1N NaOH with 0.5% β-mercaptoethanol (v/v). The mixture of algal extract and NaOH solution kept at room temperature for 1 h with occasional manual shaking. Then the mixture was centrifuged for 20 min at 21 °C, 15000g. The supernatant was pooled with the first one. 2.4.2. Protein Analysis. In a tube, 25% of trichloroacetic acid (TCA) was mixed with the extract in a 2.5:1 ratio. The mixture were kept on ice bath for 30 min and then centrifuged for 20 min at 4 °C, 15000g. The supernatant was discarded and the pellets were washed with cold (4 °C) 10% TCA and centrifuged. Pellets formed after the second centrifugation were suspended in 5% TCA at room temperature in proportion of 5:1 (5% TCA: precipitate v/v) and centrifuged again at 21 °C (15000g) for 20 min. The supernatant was discarded and the pellets were used for protein estimation Lowry’s et al.19 Calibration curve was made using bovine albumin serum (BSA) to calculate the percentage protein.20 2.5. Carbohydrate Extraction from Biomass. 2.5.1. Carbohydrates Extraction. Carbohydrates extraction was done by a slightly modified method of Karemore and Sen.21 In brief 50 mg of microalgal biomass was placed in a 100 mL flask and mixed with 50 mL of 2% H2SO4 (v/v). The mixture was autoclaved at 121 °C and 15 psi for 30 min. The autoclave mixture pH was maintained at 7 by using 1 M NaOH or H2SO4. To separate to microalgal pellets, the mixture was centrifuged at 4 °C, 1509g for 10 min. The supernatant was used for carbohydrates analysis. 2.5.2. Carbohydrates Analysis. Total carbohydrates were quantified using the phenol-sulfuric acid method.22 In brief, 0.1 mL of supernatant was diluted to 1 mL, and then mixed with 1 mL of phenol (5% w/v) and 5 mL of 96% H2SO4. After cooling to 25−30 °C, the absorbance of this solution was measured at 490 nm using a spectrophotometer (SpectroquantPharo 300, Merck). Total carbohydrates were quantified referring to a calibration curve prepared using glucose as a standard.23 2.6. Chemicals and Reagents. Ultrapure water (Aqua MAX Ultra 370, Younglin, Korea) was used to prepare all solutions. Most of the chemicals and reagents (analytical/ HPLC grade) were purchased from Sigma-Aldrich, Germany 2.7. Statistical Analysis. All of the experimental analyses were carried out in triplicate. Statistical analysis was conducted using one-way ANOVA at 95% confidence level. Posthoc analysis of the results was performed with Tukey’s honestly significant differences (HSD) test.

extraction sequences were carried out and compared to each other to ascertain the highest value yielding sequence.

2. MATERIAL AND METHODS 2.1. Microalgae Strain, Growth Conditions, and Biomass Generation. Scenedesmus obliquus (genbank accession number: FR751179.1) was isolated and purified from a pond located at Kwa-Zulu Natal province of Durban, South Africa. This alga was cultivated in domestic wastewater (Table 1) in a 25 L reactor with 16:8 h of light-dark cycle using GroTable 1. Characteristics of Wastewater (Screened Raw Sewage) Used for Algal Cultivation parameter

unit

pH alkalinity total dissolved solids total suspended solids BOD5 COD N-NH3 N-NO2− N-NO3− P-PO43−

mg mg mg mg mg mg mg mg mg

L−1 L−1 L−1 L−1 L−1 L−1 L−1 L−1 L−1

value 6.93 ± 0.28 240.00 ± 2.35 523.02 ± 45.75 1034 ± 93.82 136.60 ± 3.64 320.07 ± 3.78 52.23 ± 1.21 0.00 ± 0.00 0.40 ± 0.13 8.47 ± 0.23

Lux lamps (80 μmol m−2 s−1) and a temperature of 25 ± 2 °C. Biomass was harvested by gravitational settling and then centrifuged to obtain a thick algal slurry. Thickened slurry was then sun dried. Dried algal biomass was pulverized using mortar and pestle and stored in desiccator for further use. 2.2. Sequential Extraction of Major Metabolites. Dried biomass of S. obliquus was utilized for sequential extraction of lipids, proteins, and carbohydrates. The extraction processes were chosen on the basis of their wide applicability and acceptability as the most effective method for each of these metabolites, respectively. A total of 3−5 g of dried biomass was utilized for initial extraction of each selected metabolite. Residual biomass after each extraction was collected by vacuum filtration and then air-dried. Table 2 provides the details of Table 2. Extracted Metabolites during Different Steps of Sequential Extraction from Algae metabolite extracted legend

first step

second step

third step

LPCEA LCPEA PLCEA PCLEA CPLEA CLPEA

lipid lipid protein protein carbohydrate carbohydrate

protein carbohydrate lipid carbohydrate protein lipid

carbohydrate protein carbohydrate lipid lipid protein

various sequential extraction schemes investigated. The percentage yields of the extracted metabolites along with the percentage recovery of processed biomass in each individual step were quantified. 2.3. Lipid Extraction from Biomass. Total lipids were extracted using 2:1 (v/v) mixture of chloroform and methanol as per the method of Folch et al.17 with microwave assisted cell disruption. A total of 20 mL of solvent was added to 1g of dried biomass and digested in a microwave digester (Milestone S.R.L., Italy; 1200 W of output power) at 1000 W and 100 °C

3. RESULTS AND DISCUSSION 3.1. Effects of Sequential Extraction on Extraction Yields of Metabolites. The yields obtained for lipids, proteins, and carbohydrates after primary extraction from 3408

DOI: 10.1021/acs.iecr.6b04814 Ind. Eng. Chem. Res. 2017, 56, 3407−3412

Article

Industrial & Engineering Chemistry Research biomass were found to be 26.25 ± 0.64%, 27.79 ± 1.41%, and 16.53 ± 0.20%, respectively (Figure 1). This also correspond to

and secondary extraction following protein (PCLEA) were comparable. The yields of proteins, lipids, and carbohydrates obtained in this study were comparable to the earlier reports. Our results are similar to the previous findings of Toyubet al.,25 who reported 28.30 ± 1.17% protein content in S. obliquus. For the same microalga, Ji et al.26 and Ryckebos et al.27 have reported the lipid content in the range of 21.9−24.3% and 29.7%, respectively. Recently, Trzcinski et al.28 have also reported the carbohydrate content of various microalgae strains in the range of 12−15%. Therefore, these results also confirm the appropriateness of the extraction methods used in this study. In addition, the extraction sequence PLCEA, where proteins were extracted first, lipids in subsequent step, and finally carbohydrates was found be the best for value extraction (detailed in next sections) corroborates with the earlier studies. Gottel et al.29 have observed with A. prothothecoides that the lipid droplets remained intact inside the cell even after the extraction of soluble proteins. Therefore, the study opined that the proteins must be extracted prior to lipids in an extraction sequence. In support to this principal, Gerde et al.30 have observed that some proteins could be lost during lipid extraction from biomass which cross-confirms the PLCEA schemes superiority. Interestingly, Munoz et al.7 have observed that carbohydrates were concentrated in a spent biomass (of B. braunii) after the extraction of proteins and lipids. These recent findings from various researchers confirm that the protein extraction must be prioritised in a biorefinery process. 3.2. Effects of Sequential Extraction on Residual Biomass. The extraction processes for all three metabolites viz. proteins, carbohydrates, and lipids concomitantly causes some loss of algal biomass. We have also observed subsequent reduction in residual biomass after each extraction step which can be attributed to the lower extraction yields of next metabolite. These results are summarized in Figure 2 as a residual biomass yield (% of initial algal mass).

Figure 1. Effects of extraction sequence on the extraction yields of primary metabolites from algae. Different letters on bars for each metabolite indicate significant difference among them (ANOVA, Tukey’s test, P < 0.05).

the maximum content of these metabolites in the biomass for the current study. Further, when these metabolites were extracted individually as a secondary or tertiary extraction product, their yields were significantly lower. In case of lipids yield, when the lipids were extracted followed by the extraction of proteins (PLCEA) and carbohydrates (CLPEA), the yields were significantly lower and noted to be 23.00 ± 0.78% and 20.00 ± 0.89%, respectively. When compared to the maximum lipid yields of 26.25 ± 0.64% (obtained by primary extraction), lipid yields of secondary extraction have decreased by ∼12% for PLCEA and ∼24% for CLPEA. Interestingly, no considerable difference was observed between the lipid yields of these two secondary extractions with CLPEA resulting in ∼9% lesser lipid yield than the PLCEA extraction scheme. Nonetheless, tertiary extraction further resulted in the significant reduction in lipid yields by 28−43% lipid content (for PCLEA, 19.00 ± 0.92%, and for CPLEA, 15.00 ± 0.95%). In the case of proteins, the highest yield of 27.79 ± 1.41% was obtained with primary extraction. Secondary extraction of proteins following carbohydrate extraction (CPLEA, 24.98 ± 1.57%) or lipid extraction (LPCEA, 23.21 ± 4.77%) provided similar yields to primary extraction. Tertiary protein extraction resulted in the yields of 12.29 ± 2.01% for LCPEA and 8.00 ± 0.83% for CLPEA. No significant difference was observed in protein yield for LCPEA and CLPEA scheme of extraction. It is also reported that the protein yield decreases significantly when performed after lipid extraction. In a previously reported study, protein yields of Navicula sp. when extracted after lipids were found to decrease from 19.4% to 13.3% which corresponds to ∼31.5% decreased yield.24 In the case of carbohydrates, the maximum yield (16.53 ± 0.20%) was obtained by primary extraction. Secondary extractions of carbohydrates followed by lipids (LCPEA, yield of 13.53 ± 0.35%) did not result in significant reduction in yield, while extraction after proteins (PCLEA, yield of 10.41 ± 3.69%) significantly decreased it. The most significant loss in carbohydrates was as a result of tertiary extractions (LPCEA and PLCEA) and was noted to be 45−53% lower when compared to the yields of primary extraction. Moreover, carbohydrates yield as a result of tertiary extraction (PLCEA)

Figure 2. Effects of extraction sequence on the residual algal biomass in each step of metabolite extraction. Different letters on bars for each step indicate significant difference among them (ANOVA, Tukey’s test, P < 0.05).

When proteins were extracted primarily from the whole cell algae biomass (PCLEA and PLCEA extraction sequence), it resulted in the highest residual mass available for second step (80.00 ± 3.00% for PLCEA and 80.00 ± 6.00% for PCLEA) with the concomitant biomass loss of only 20%. The next best primary extraction was found to be of lipids wherein it had resulted in 30% loss of initial biomass and 70% residual biomass was available for the next extraction. However, when carbohydrates were extracted first, the residual biomass was 3409

DOI: 10.1021/acs.iecr.6b04814 Ind. Eng. Chem. Res. 2017, 56, 3407−3412

Article

Industrial & Engineering Chemistry Research reduced to 64.00 ± 7.00% for CPLEA and 64.00 ± 2.00% for CLPEA. These residual biomass values were significantly lower (ANOVA, P < 0.05) when compared with biomass left after initial protein extraction. After secondary extraction, the highest residual biomass was 60.80 ± 2.00% for PLCEA while the lowest residual biomass was 18.88 ± 5.00% for CPLEA (Figure 3). Despite the

extraction sequence and summarized in Figure 4. Their individual yields per kg of algae biomass (in primary extraction)

Figure 3. Effects of extraction sequence on total extraction of primary metabolites. Different letters on bars for each metabolite indicate significant difference among them (ANOVA, Tukey’s test, P < 0.05).

relatively low carbohydrate content (Figure 1), extraction of carbohydrates resulted in the highest loss of biomass when compared to the other two extraction processes irrespective of the extraction sequence (Figure 3). On the contrary, the loss of biomass during protein or lipid extractions depended on the extraction sequence. Though the primary extraction of proteins and lipids had comparable losses of biomass, secondary extraction of lipids resulted in significantly lower loss of biomass when compared to secondary extraction of proteins. PLCEA had a 24% loss of primary extracted biomass (initial biomass for secondary extraction) whereas CLPEA had lost 31% of it. However, when proteins were extracted in secondary extraction after lipids, the loss in biomass was noted to be 57.5%, and when it was followed by carbohydrates extraction, the biomass loss was maximum and was found to be 70.5%. This suggested that proteins have a higher tendency than lipids to be affected by the preceding extraction process. Proteins are likely to become progressively unbound from the algal biomass after each extraction process and increased loss of biomass. Furthermore, these insights help us in determining an extraction sequence where loss of biomass in each step could be minimized so that the comprehensive extraction sequence is developed for extraction of a reasonable yield of the target metabolites. Therefore, in order to minimize the loss of the biomass, the extraction of the metabolites can follow a sequence as proteins−lipids−carbohydrate. This further requires an investigation into the total extraction of all three metabolites while accounting for the effects of extraction sequence on both extraction yields and biomass recovery. 3.3. Comparison of Metabolite Extracts Based on Market Value using Various Extraction Sequences. A primary objective in achieving a sustainable algal biorefinery is to obtain sufficient extractions of major metabolites from harvested algal biomass. However, extraction processes for individual metabolites and the sequence of extraction not only affects their extraction yield from biomass but also lowers the residual biomass available for next extraction. In the current study, the extracted metabolites were quantified for each

Figure 4. Effects of extraction sequence on value of extracted primary metabolites from 1 kg of dried algal biomass after accounting for extraction cost, (a) value of individual primary metabolites extracted, (b) cumulative value extraction. Values are compared with the production cost of 1 kg of dried algal biomass for net gain or loss obtained in that extraction sequence. Different letters on bars for each metabolite indicate significant difference among them (ANOVA, Tukey’s test, P < 0.05).

were found to be 0.27 ± 0.01 kg for lipids, 0.28 ± 0.02 kg for proteins, and 0.16 ± 0.01 kg for carbohydrates. The secondary extraction of these metabolites has greatly reduced their yields which was a function of the type of metabolite extracted and the % loss of biomass in preceding extraction. When lipids were extracted after protein (PLCEA), it resulted in a yield of 0.18 ± 0.02 kg kg−1 algae, while after carbohydrates extraction, lipids yield were significantly lowered to 0.13 ± 0.01 kg kg−1 algae. The facts of individual metabolites yield and the concomitant loss of processed biomass marks the importance of choosing an appropriate extraction sequence to enhance the value extraction of products. In this study, we have attempted to convert the yields of individual metabolites to their market cost so as to investigate the overall value of the products from an extraction sequence.The values of these extracted metabolites for their unit mass and the production cost of dried algae while accounting for the costs involved in extraction of individual metabolite were referred from the available literature.31 These values are summarized in Table 3. Based on these, the cost of extracted metabolites from 1 kg of dried biomass (Figure 4) was calculated. Figure 4a presents the values of individual metabolites for each extraction sequence. Significant effects of extraction sequences were observed on the value extraction for each metabolite. As observed, none of the extraction sequence could recover the current production cost of algae (∼4 € kg−1 of dried algae). However, with the potential of lowering these production costs to ∼0.4 € kg−1 of dried algae 3410

DOI: 10.1021/acs.iecr.6b04814 Ind. Eng. Chem. Res. 2017, 56, 3407−3412

Article

Industrial & Engineering Chemistry Research

biomass generation whereas PCLEA could result in 49% net value gain. Comparatively higher value gain in PCLEA than PLCEA was due to the fact that the sequence of extraction had followed their descending order of market costs. This sequence was also characterized by minimum loss of biomass prior to lipids and carbohydrates extraction. Overall upon accounting for the cost of biomass generation that can potentially be achieved, the cumulative cost of individual metabolites extracted from the whole algae biomass could theoretically result in 112.5% net value gain. However, in comparison to this, the best extraction sequence of PLCEA (which has net value of 66.5%) exhibits ∼41% reduction in value. The value of 112.5% corresponds to the maximum recovery of an individual metabolite in one step process without the loss of other metabolites. This value is unrealistic in practice as when only lipids are targeted, the value of proteins and carbohydrates is lost, and when only proteins are targeted the value of lipids and carbohydrates is lost. Therefore, in order to successfully develop an integrated biofuel, food and feed industry from microalgal biomass as a feedstock, biorefining of microalgae must be applied to extract value from all the intracellular (primary and secondary) metabolites in addition to lowering the production cost of algae.

Table 3. Value of Different Primary Metabolites Extracted from Algae after Accounting for Extraction Cost and the Production Cost of Dried Algal Biomass (Wijffels et al.) value of extracted primary metabolite

metabolite lipid

protein

application as feedstock for chemical industry as transport fuel for food for feed

fraction of extracted quantity

value (€ kg−1 metabolite)

0.25

2.00

0.75 0.20 0.80 1.00

0.50 5.00 0.75 1.00

carbohydrate (as polysaccharides) current production cost of dried algae biomass = 4.02 € kg−1 dried algae potential production cost of dried algae biomass = 0.40 € kg−1 dried algae

with certain measures,31 the following observations could be made. Maximum values of these metabolites (0.23 ± 0.01 € for lipids, 0.45 ± 0.03 € for proteins, and 0.16 ± 0.01 € for carbohydrates) were obtained when extracted directly from whole cell algae in the first step. However, these extracted values lowered in their second or tertiary extractions in accordance to their lower extracted amounts. Cumulative value extractions for all of the extraction schemes were also calculated (Figure 4b) which were found to be significantly affected by the sequence of extraction. The total value of these metabolites in 1 kg of dried algae available for extraction was 0.84 ± 0.04 €. However, subsequent losses in sequential extraction significantly reduced the total value extraction in all cases. Such extracted values ranged from 0.65 ± 0.04 € for PLCEA to 0.33 ± 0.03 € for CLPEA. These values were compared with the production cost for 1 kg of dried algae to estimate net gain or loss for a particular extraction sequence. In this study, proteins were categorized as the most costly commodity followed by lipids and then carbohydrates (Table 3).Carbohydrates, though the cheapest of all three metabolites have affected the cumulative value of the products extraction with its processing sequence. The highest loss (57.64%) in market cost of these products was observed when carbohydrates were either extracted as the primary (CLPEA) or secondary extraction (LCPEA) product. This significant loss in value can be attributed to the maximum loss of biomass along with the extraction sequence where the highest value commodity (proteins) was extracted in the end with its yields being drastically reduced. Therefore, the CLPEAand LCPEA schemes could not meet even the potential input cost of biomass generation (0.40 € kg−1 biomass) and can account for an additional dispensation cost of 10%. It corresponds to a classic case of net energy input being more than the net energy which can be harnessed from the biomass. In secondary extraction of proteins, the cases LPCEA and CPLEA, the cumulative cost of products was marginally higher than the potential input cost whereby it resulted in 12.5% cost benefit to the process. It was mainly because the proteins being the highest value commodity were extracted second in the sequence which resulted in minimum loss of product. On the other hand, the maximum gain in value (49−66.5%) was achieved with primary extraction of proteins. The scheme PLCEA resulted in 66.5% benefit overcoming the cost of

4. CONCLUSION This study demonstrated the importance of selecting an extraction sequence to achieve sufficient yields of major metabolites from microalgal biomass. Significant effects of these extraction sequences were observed on the final yields of individual metabolites as well as biomass recovery. The cumulative value extractions were calculated (by subtracting the input cost of biomass production) for each extraction sequence and compared. Based on these comparisons, an optimal sequence for maximum value extraction was determined as protein in the first step, lipid in the second step, and carbohydrate in the tertiary. This PLCEA scheme of extraction could provide a net value gain of 66.5% with the potential production cost of algae.

■

AUTHOR INFORMATION

Corresponding Author

*Tel: +27 31 373 2346. Fax: +27 31 373 2777. E-mail: faizalb@ dut.ac.za. ORCID

Faizal Bux: 0000-0002-8108-0238 Present Addresses ‡

Centre for Environmental Science and Engineering, Indian Institute of Technology, Bombay, Mumbai 400 076, India. § Environmental Engineering, Department of Civil Engineering, Indian Institute of Technology, Delhi, New Delhi 110016, India. Author Contributions †

F.A.A. and A.S. contributed equally to this paper.

Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS The authors hereby acknowledge the National Research Foundation and Durban University of Technology for providing financial assistance. 3411

DOI: 10.1021/acs.iecr.6b04814 Ind. Eng. Chem. Res. 2017, 56, 3407−3412

Article

Industrial & Engineering Chemistry Research

■

holistic approach for biofuel applications. RSC Adv. 2016, 6, 29486− 29496. (22) DuBois, M.; Gilles, K. A.; Hamilton, J. K.; Rebers, P. A.; Smith, F. Colorimetric Method for Determination of Sugars and Related Substances. Anal. Chem. 1956, 28, 350−356. (23) Prajapati, S. K.; Malik, A.; Vijay, V. K. Comparative evaluation of biomass production and bioenergy generation potential of Chlorella spp. through anaerobic digestion. Appl. Energy 2014, 114, 790−797. (24) Patterson, D.; Gatlin, D. M. Evaluation of whole and lipidextracted algae meals in the diets of juvenile red drum (Sciaenopsocellatus). Aquaculture 2013, 416, 92−98. (25) Toyub, M. A.; Miah, M. I.; Habib, M. A. B.; Rahman, M. M. Growth performance and nutritional value of Scenedesmus obliquus cultured in different concentrations of sweetmeat factory waste media. Bangladesh J. Anim. Sci. 2008, 37, 86−93. (26) Ji, M. K.; Yun, H. S.; Park, S.; Lee, H.; Park, Y. T.; Bae, S.; Ham, J.; Choi, J. Effect of food wastewater on biomass production by a green microalga Scendesmus obliquus for bioenergy generation. Bioresour. Technol. 2015, 179, 624−62. (27) Ryckebosh, E.; Muylaert, K.; Foubert, I. Optimization of an analytical procedure for extraction of lipids from microalgae. J. Am. Oil Chem. Soc. 2012, 89 (2), 189−198. (28) Trzcinski, P.; Hernandez, E.; Webb, H. A novel process for enhancing oil producing in algae biorefineries through bioconversion of soilid by-products. Bioresour. Technol. 2012, 116, 295−301. (29) Gottel, M.; Eing, C.; Gusbeth, C.; Straessner, R.; Frey, W. Pulsed electric field assisted extraction of intracellular valuables from microalgae. Algal Res. 2013, 2, 401−408. (30) Gerde, J. A.; Wang, T.; Yao, L.; Jung, S.; Johnson, L. A.; Lamsal, B. Optimizing protein isolation from defatted and non- defatted Nannochloropsis microalga biomass. Algal Res. 2013, 2 (2), 145−153. (31) Wijffels, R. H.; Barbosa, M. J.; Eppink, M. H. M. Microalgae for the production of bulk chemicals and biofuels. Biofuels. Biofuels, Bioprod. Biorefin. 2010, 4, 287−295.

REFERENCES

(1) Griffiths, M. J.; Harrison, T. L. Lipid productivity as a key characteristic for choosing algal species for biodiesel production. J. Appl. Phycol. 2009, 21, 493−507. (2) Chisti, Y. Biodiesel from microalgae. Biotechnol. Adv. 2007, 25, 294−306. (3) Knothe, G. A technical evaluation of biodiesel from vegetable oil vs. algae. Will algae-derived biodiesel perform? Green Chem. 2011, 13, 3048−3065. (4) Slade, R.; Bauen, A. Micro-algae cultivation for biofuels: Cost, energy balance, environmental impacts and future prospects. Biomass Bioenergy 2013, 53, 29−38. (5) Bharatiraj, A.; Chakravarthy, M.; Kumar, R. R.; Yogendra, D.; Yuvaraj, D.; Jayamuthungai, J.; Kumar, P. R.; Palani, S. Aquatic biomass (algae) as a future feed stock for bio- refineries: A revive on cultivation, processing and products. Renewable Sustainable Energy Rev. 2015, 47, 634−653. (6) Yen, H. W.; Hu, I. C.; Chen, C. Y.; Ho, S. H.; Lee, D. J.; Chang, J. S. Microalgae based biorefinery- From biofuels to natural products. Bioresour. Technol. 2013, 135, 166−174. (7) Munoz, R.; Navia, R.; Ciudad, G.; Tessini, C.; Jeison, D.; Mella, R.; Rabert, C.; Azócar, L. Preliminary biorefinery process proposal for protein and biofuels recovery from microalgae. Fuel 2015, 150, 425− 433. (8) Ursu, A. V.; Marcati, A.; Sayd, T.; Lhoutellier, S. V.; Djelveh, G.; Michaud, P. Extraction, fraction and functional properties of proteins from the microalgae chlorella vulgaris. Bioresour. Technol. 2014, 157, 134−139. (9) Vanthoor-Koopmans, M.; Wijffels, R. H.; Barbosa, M. J.; Eppink, M. H. M. Biorefinery of microalgae for food and fuel. Bioresour. Technol. 2013, 135, 142−149. (10) Ansari, F. A.; Shriwastav, A.; Gupta, S. K.; Rawat, I.; Guldhe, A.; Bux, F. Lipid extracted algae as a source for protein and reduced sugar: A step closer to the biorefinery. Bioresour. Technol. 2015, 179, 559− 564. (11) Nobre, B. P.; Villalobos, F.; Barragán, B. E.; Oliveira, A. C.; Batista, A. P.; Marques, P. A. S. S.; Mendes, R. L.; Sovová, H.; Palavra, A. F.; Gouveia, L. A biorefinery from Nannochloropsis sp. microalga − Extraction of oils and pigments. Production of biohydrogen from the leftover biomass. Bioresour. Technol. 2013, 135, 128−136. (12) Arnon, D. I. Copper enzymes in isolated chloroplasts. Polyphenoloxidase in Beta vulgaris. Plant Physiol. 1949, 24, 1. (13) Gouveia, L.; Neves, C.; Sebastião, D.; Nobre, B. P.; Matos, C. T. Effect of light on the production of bioelectricity and added-value microalgae biomass in a Photosynthetic Alga Microbial Fuel Cell. Bioresour. Technol. 2014, 154, 171−177. (14) Olguín, E. J. Dual Purpose Microalgae-Bacteria-Based Systems that Treat Wastewater and Produce Biodiesel and Chemical Products within a Biorefinery. Biotechnol. Adv. 2012, 30, 1031−1046. (15) CPCB. Environmental Management in Selected Industrial Sectors Status and Needs; Central Pollution Control Board, Ministry of Environment and Forest: New Delhi, 2003. (16) Gouveia, L. From Tiny Microalgae to Huge Biorefineries. Oceanography 2014, 2, 120. (17) Folch, J.; Lees, M.; Stanley, G. H. S. A simple method for the isolation and purification of total lipides from animal tissues. J. Biol. Chem. 1957, 226, 497−509. (18) Barbarino, E.; Lourenço, S. O. An evaluation of methods for extraction and quantification of protein from marine macro- and microalgae. J. Appl. Phycol. 2005, 17 (5), 447−460. (19) Lowry, O. H.; Rosebrough, N. J.; Farr, A. L.; Randall, R. J. Protein measurement with the folin phenol reagent. J. Biol. Chem. 1953, 193, 265−275. (20) López, C. V. G.; García, M. D. C. C.; Fernández, F. G. A.; Bustos, C. S.; Chisti, Y.; Sevilla, J. M. F. Protein measurements of microalgal and cyanobacterial biomass. Bioresour. Technol. 2010, 101, 7587. (21) Karemore, A.; Sen, R. Downstream processing of microalgal feedstock for lipid and carbohydrate in a biorefinery concept: A 3412

DOI: 10.1021/acs.iecr.6b04814 Ind. Eng. Chem. Res. 2017, 56, 3407−3412