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Use of magnetic fields and nitrate concentration to optimize the growth and lipid yield of Nannochloropsis oculata
Journal of Environmental Management 253 (2020) 109680
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Journal of Environmental Management journal homepage: http://www.elsevier.com/locate/jenvman
Research article
Use of magnetic fields and nitrate concentration to optimize the growth and lipid yield of Nannochloropsis oculata Feng-Jen Chu a, Terng-Jou Wan b, *, Tzu-Yi Pai c, Hsiao-Wen Lin b, Shang-Hao Liu d, Chung-Fu Huang e a
Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, Douliou, 64002, Yunlin, Taiwan Department of Safety, Health and Environment Engineering, National Yunlin University of Science and Technology, Douliou, 64002, Yunlin, Taiwan Master Program of Environmental Education and Management, Department of Science Education and Application, National Taichung University of Education, Taichung, 40306, Taiwan d Department of Chemical Engineering, Anhui University of Science and Technology, Huainan, 232001, Anhui, China e School of Environmental and Chemical Engineering, Zhaoqing University, Zhaoqing, 526061, Guangdong, China b c
A R T I C L E I N F O
A B S T R A C T
Keywords: Nannochloropsis oculata Lipid productivity Magnetic fields Sodium nitrate Response surface methodology
Microalgae produce increased lipid content accompanied by a significant decrease in cell density with decreasing nitrate concentration. Magnetic fields (MF) have been reported as a factor that could accelerate metabolism and growth in microalgae culture. Thus, this study aimed to optimize the influence of MF and nitrate concentration (sodium nitrate, N) on the growth and lipid productivity of Nannochloropsis oculata. A single-factor experiment integrated with response surface methodology (RSM) via central composite design (CCD) was performed. The results showed that the maximum specific growth rate (0.24 d 1) and maximum lipid productivity (38 mg L 1 d 1) obtained in this study were higher than those of the control culture (by 166% and 103%, respectively). This study also found that the two-way interaction term MF � N had a significant effect on cell growth but not on lipid production. It was concluded that to design appropriate MF for enhanced lipid productivity due to cell growth, further research must focus on developing an understanding of the relationship between the bioeffects of the magnetic field and the proteomic changes involved in lipid accumulation strategies. This approach would enable the design of conditions to obtain inexpensive high-value products from N. oculata.
1. Introduction Despite the many applications and properties of microalgae as feedstock for the production of biofuels, the main interest is in reducing the cost of producing oil-rich microalgae using a modern production strategy that results in an increased growth rate and lipid content of upstream processes (Qv et al., 2014; Geada et al., 2018; Haberkorn et al., 2019). Microalgae cultivation requirements and harvesting steps play key roles in reducing the environmental impact and limiting the cost of microalgae biofuel production (Romero-Villegas et al., 2018; Sajjadi et al., 2018). Thus, effective techniques with low energy consumption, such as electromagnetic biostimulation (Hunt et al., 2009; Haberkorn et al., 2019), and static or modulated magnetic fields (MF) (Nezamma halleh et al., 2016; Santos et al., 2017; Deamici et al., 2019), have received increased attention in recent years. Nitrate concentration significantly affects both the growth rate and
lipid production of microalgae. Gaude et al. (2007) reported that the supply of a nitrate source affects galactolipid composition in microalgae. Kim et al. (2016) also reported the impacts of nitrate concentration on structural and functional components in peptides, enzymes and chlo rophylls. Recently, a small number of studies have cultivated N. oculata in nitrate-depleted medium for the synthesis of lipid accumulation during growth; however, reduced growth rates have been observed (Tran et al., 2016; Araujo et al., 2019). The glycolytic pathway is a major contributor to pyruvate production in fatty acid biosynthesis for tri acylglyceride (TAG) accumulation in N. oculata (Ma et al., 2016). In general, carbon partitioning from storage carbohydrates into the glycolysis pathway occurs under nitrogen-rich conditions (Han et al., 2017). Tran et al. (2016) observed that the shift in metabolic flux is activated to compensate for energy deficits since the glycolytic pathways of N. oculata are impaired under nitrogen-depleted conditions. Metsoviti et al. (2019) demonstrated that when C. vulgaris was grown at initial
* Corresponding author. E-mail address: [email protected] (T.-J. Wan). https://doi.org/10.1016/j.jenvman.2019.109680 Received 14 June 2019; Received in revised form 28 September 2019; Accepted 5 October 2019 Available online 18 October 2019 0301-4797/© 2019 Elsevier Ltd. All rights reserved.
F.-J. Chu et al.
Journal of Environmental Management 253 (2020) 109680
Table 1 The experimental design and results of central composite design using RSM. Runs
Independent Variables (factor values) X1
1 2 3 4 5 6 7 8 9 10 11 12 13
Specific growth rate (μ, d X2
Magnetic Field, mT
Coded levels
Nitrate, g L
1 1
30 30 10 10 20 20 20 20 20 20 34 20 6
1
200 100 100 200 150 150 150 150 150 220 150 80 150
1 1
0 0 0 0 0 0 1.4142 0 1.4142
1 0 0 0 0 0 1.4142 0 1.4142 0
Lipid Productivity (mg L 1)
)
Y1
Coded levels
1 1
1
1
nitrate concentrations of 0–800 mg L 1 KNO3, not only the growth rate but also the protein and lipid contents were inhibited above 400 mg L 1. The results showed that as the nitrogen concentration in the culture medium increased, the protein content also increased, while the lipid content decreased. In conclusion, the metabolic responses under different nitrogen stress conditions had different results based on different aims. Therefore, developing strategies to achieve higher algal biomass and lipid productivity with environmentally friendly factors should be investigated. The use of MF has received increased attention as a nontoxic, wideranging and economical alternative to biocompounds (Tu et al., 2015). Additionally, MF can affect the bioelectrocatalytic transformations of several enzymes by enhancing electron transfer because enzyme activity can be increased under MF (Li et al., 2011; Santos et al., 2017; Wasak et al., 2019). For several aquaculture microalga species, MF has been successfully combined with available nitrate media to produce changes in enzyme levels (Deamici et al., 2016a). Some studies applied MF of different strengths to cultivate and assess the resulting cell growth of algae, such as Chlorella fusca (Deamici et al., 2019), Chlorella kessleri (Small et al., 2012; Bauer et al., 2017), Spirulina sp. (Deamici et al., 2016b; Piazzi et al., 2019) and Nannochloropsis oculata (Oliveira, 2017). However, the effects of optimized MF on N. oculata have not yet been considered. Hence, the aim of this study was to investigate the optimized growth rate and lipid productivity of N. oculata under different MF strengths and N concentration conditions.
Y2
Experimental
Model Prediction
Experimental
Model Prediction
0.140 0.119 0.196 0.090 0.266 0.241 0.254 0.230 0.217 0.096 0.038 0.174 0.182
0.107 0.092 0.213 0.101 0.241 0.241 0.241 0.241 0.241 0.109 0.078 0.177 0.158
20.27 26.79 32.05 23.88 39.32 40.53 35.43 37.88 36.67 20.17 18.39 26.02 32.57
18.79 23.75 31.82 25.22 37.95 37.95 37.95 37.95 37.95 19.92 21.27 28.01 31.43
(Magtech Magnetic Products Co., Taiwan) of differing strengths were applied for the duration of each batch of experiments (7 days). To choose the range of response surface methodology (RSM) design, ferrite magnets with intensities of 20 mT, 30 mT and 40 mT were utilized for preliminary optimal range studies. The intensity of the magnetic field was adjusted with ferrite magnets of different sizes for confirmatory experiments. Each ferrite magnet was positioned 10 cm above the reactor base and at one side of the reactor, and the intensity of the magnetic field was measured in the center of the ferrite magnets using a tesla meter (TM-601, Kanetec, Japan). 2.3. Analysis of biomass concentration and lipid extraction The biomass optical density was measured at a wavelength of 682 nm using a UV/VIS spectrophotometer (DR 4000U, Hach, USA). The dry biomass was centrifuged (CN-820, Hsiangtai, Taiwan) at 2500 rpm for 5 min, washed with distilled water 3 times, and dried in an oven (DO45, Dengyng, Taiwan) at 105 � C for 24 h. The microalga biomass concentration was estimated using Eq. (1): Biomass conc: ¼ 200:17 � OD682 þ 81:089 R2 ¼ 0:9858
(1)
1
The specific growth rate (μ, d ) was obtained from the increased microalgae concentration at various times using Eq. (2): � � D ln D0f μ¼ (2) t1 t0
2. Materials and methods
where Df is the final dry weight density (g L 1), D0 is the initial dry weight density (g L 1), and t1–t0 is the experimental time (d). In this study, lipid extraction was performed using the modified solvent extraction method proposed by Bligh and Dyer (1959) and � �stari�c et al., 2012. The lipid was extrac pulverizing pretreatment by So ted from 100 mL of algal suspension and centrifuged at 6000 rpm for 15 min, the supernatant was discarded, and the dried biomass was frozen (FDU-506, EYELA, Japan) at 20 � C for 72 h, then ground in a mortar. The lipids were extracted by 3 mL of chloroform/methanol (2/1, v/v) with dried biomass in a glass tube (weight determined). The mix tures were vortexed (ZX4, Velp Scientifica, Italy) for 1 min and centri fuged at 3600 rpm for 1 min. After phase separation, the supernatant was discarded again, and the process was repeated 3 times until the color turned from green to transparent. The heavier phase (the crude lipid fraction) was dried in a fume cupboard. The extracted lipid was obtained gravimetrically in this study. The lipid content was obtained by conversion according to Eq. (3):
2.1. Microalgae and culture media Nannochloropsis oculata was obtained from Tungkang Biotechnology Research Center, Fisheries Research Institute (FRI), Taiwan and culti vated in modified Walne’s medium (Surendhiran et al., 2014). The medium was adjusted to a pH of 8 and autoclaved (TM-321, Hoyu Inc., Taiwan) at 1.2 kg cm 2 (15 psi) and 121 � C for 20 min. Microalgae were cultivated in a 1 L reactor at room temperature (25 � 1 � C) with an illumination of 67.5 μmol protons m 2 s 1 using a fluorescent lamp (26 W) with a light/dark cycle of 12/12 h. Cultures were used for ex periments when the algal concentration reached 120 mg L 1 with the use of an aeration pump (Ep-12000, Rambo, Taiwan) at a rate of 0.25 vvm (air without CO2 enrichment) and agitation. The composition of the modified Walne’s medium is provided in the Supplementary Material (Table S1). 2.2. Analytical methods for magnetic fields
Y ð%Þ ¼
For experiments with MF, commercial customized ferrite magnets 2
LW � 100% DW
(3)
F.-J. Chu et al.
Journal of Environmental Management 253 (2020) 109680
Table 2 Parameters of N. oculata growth under different nitrate concentrations and magnetic fields. 1
Parameters
Nitrate concentration, mg L 100 (control)
150
200
20
30
40
μ (d 1) τ (d)
0.09 � 0.02b 1.1 � 0.2a 131 � 9a 41 � 5a 18.7 � 1.3a
0.10 < 0.01b 1.04 < 0.01a 167 � 10b 37.1 � 2.2a 23.9 � 1.4b,c
0.10 � 0.02b 0.99 � 0.02a 165 � 13b 37.3 � 3.0a 23.6 � 1.9b,c
0.11 � 0.02b 0.9 � 0.1a 216 � 18c 42.4 � 4.7a 30.9 � 2.6d
0.08 < 0.01a 1.2 � 0.06a 171 � 13b 41.8 � 4.7a 24.4 � 1.9c
0.05 � 0.01a 1.9 � 0.2b 148 � 5a,b 39.8 � 2.4a 21.1 � 0.7a,b
CL concentration (mg L 1) CL contents (% w w 1) CL productivity (mg L 1 d 1)
Magnetic field, mT
Means � standard deviations. Different lowercase letters in the same line correspond to significant differences between all assays (p < 0.05) by Tukey’s test.
3. Results and discussion
where Y is the extracted lipid yield (%); Lw is the extracted lipid weight, and Dw is the dry biomass weight. The lipid productivity was estimated by Eq. (4): Lipid productivity mg L
1
�
¼
Df � Yf
D0 � Y0 T
3.1. Influence of different factors on growth rate and crude lipid concentration
(4)
The effects of different MF strengths and initial nitrate concentra tions on the growth of N. oculata are summarized in Table 2. The specific growth rate and crude lipid productivity of N. oculata reached maximum values of 0.11 d 1 (22% higher than the control of 0.09 d 1) and 30.9 mg L 1 d 1 (65% higher than the control of 18.7 mg L 1 d 1) at 20 mT, respectively. The specific growth rate decreased significantly when the MF intensity was 30 mT (0.08 d 1) or 40 mT (0.05 d 1). This result indicates that an intensity of 20 mT stimulated the growth of N. oculata, whereas intensities of 30 mT and 40 mT inhibited the growth rate. Nezammahalleh et al. (2016) demonstrated that MF effects on cell growth which was attributed to enhancement of algae membrane permeability, resulting in transportation of substrate into cytoplasm of cell, could be classified as a stimulatory function. However, the potential damage of algae cell was observed at high magnetic field intensities and high treatment times due to an increase in the free radicals of media (Small et al., 2012; Wang et al., 2008). The appropriate MF could in fluence the cell metabolism of algae, and there was a possible conse quence on the growth rate of cells. When the initial nitrate concentration was varied from 100 mg L 1 (control) to 200 mg L 1, the growth rate and crude lipid productivity of N. oculata reached maximum values of 0.1 d 1 and 23.9 mg L 1 d 1, respectively, with no significant changes occurring with a further in crease in the initial nitrate concentration, but the crude lipid produc tivity decreased when the growth rate decreased. Nitrogen concentration was also a significant limiting condition for lipid content (Shen et al., 2014; Rasdi et al., 2015). This is due to nitrate must first be reduced to ammonium that can be use directly assimilated into the cells. However, high concentration of ammonium would be toxic to micro algae (Metsoviti et al., 2019). Converti et al. (2009) reported that a reduced nitrate concentration of 300 mg L 1 – 75 mg L 1 in the growth medium of N. oculata resulted in an almost constant growth rate but increased lipid production by protein biosynthesis. Shen et al. (2014) compare the adhesion biomass and lipid yield of N. oculata at different concentration levels of the nitrogen source (6 mM–24 mM); the biomass productivity and the lipid yield decreased from 3.43 g m 2d 1 to 1.77 g m 2d 1 and 0.46 g m 2d 1 to 0.28 g m 2d 1, respectively. Additionally, the CL concentration and productivity in the MF (20 mT) and N concentration (150 mg L 1, 200 mg L 1) conditions were significantly higher (p < 0.05) than in the control. When a MF of 40 mT was applied throughout cultivation, the CL concentration and produc tivity were statistically similar to those of the control culture. The gen eration time for the 20 mT condition that accelerated the growth of N. oculata was 0.9 d. The lower generation time makes cultivation more economically viable. Based on these results, it is possible to study MF application in combination with different nitrate concentrations, since those conditions increased growth rate and lipid productivity.
where lipid productivity is in units of milligrams per liter per day (mg L 1 d 1), and T is the cultivation time (d); Df and D0 are the final and initial lipid content (%) during the cultivation time, and Yf and Yi are the final and initial biomass concentration (mg L 1), respectively. 2.4. Single-factor experimental design Single-factor experimental design was used to define the ranges of the nitrate concentration (100 mg L 1 – 200 mg L 1) and the magnetic field (20 mT–40 mT) to examine the effects on the growth of N. oculata in a preliminary investigation (Figs. S1 and S2). Table S2 shows the quantitative values of the factor levels from the primary investigation with optimization by RSM. 2.5. Experimental design and optimization Full-factorial central composite design (CCD) was used to develop response surface models and to perform a factorial 22 design for the twofactor optimization of the growth rate (Y1, d 1) and lipid productivity (Y2, mg L 1) (Table 1). The magnetic field (X1, mT) and nitrate con centration (X2, mg L 1) were selected as independent variables. Statis tica 6.0 software (StatSoft Inc., USA) was used to develop the response model. The experiment included 14 runs performed under the condi tions shown in Table 1. Five duplicate runs were given four degrees of freedom for pure experimental uncertainties (pure error), while the axial pffiffiffi points were determined to be � 2. The acquired data were fit to a second-order polynomial model as shown in Eq. (5) (Montgomery and Runger, 2006): k X
Y ¼ β0 þ
k X
β i XI þ i¼1
βii X 2i þ
i¼1
XX βij Xi Xj þ ε
(5)
i
where Y is the response (growth rate (d 1) or lipid concentration (mg L 1)); X1 is the magnetic field strength (mT); X2 is the nitrate concen tration (mg L 1); β terms are the parameters or regression coefficients whose values are to be determined (βij is the response interaction be tween two individual factors, and βii represents pure second-order quadratic effects); k denotes the number of experimentally studied fac tors; and ε is the random error of the experiment. 2.6. Statistical analysis The results of the single-factor experiment were performed in three replicates and calculated as the mean � standard deviation. Statistical analyses were carried out by SPSS v20 (IBM Corporation, USA) using analysis of variance (ANOVA) followed by Tukey’s test at a probability level of p < 0.05. The full-factorial CCD of each factor was determined using Student’s t-test. 3
F.-J. Chu et al.
Journal of Environmental Management 253 (2020) 109680
Table 3 Analysis of variance for the experimental design results of specific growth rate and lipid productivity of N. oculata. Factors
SS
Specific growth rate (μ) MF 0.007 MF2 0.027 NN 0.005 N2 0.017 MF � N 0.004 Lack of fit 0.005 Pure error 0.001 Total SS 0.061 2 R 0.900 2 0.829 Adj. R Lipid Productivity (mg L 1 d MF 104.16 MF2 236.86 N 66.10 N2 344.24 MF � N 0.68 Lack of fit Pure error Total SS R2 Adj–R2
26.93 16.53 734.31 0.941 0.899
1
)
df
MS
F
p
1 1 1 1 1
0.007 0.027 0.005 0.017 0.004
17.72 71.94 12.79 45.74 10.83
0.01* 0.00* 0.02* 0.00* 0.03*
3 4 12
0.002 0.000
4.08
0.10
1 1 1 1 1
104.16 236.86 66.10 344.24 0.68
25.21 57.33 16.00 83.32 0.16
0.01* 0.00* 0.02* 0.00* 0.71
3 4 12
8.98 4.13
2.17
0.23
Fig. 1. Response surfaces and contour plots of specific growth rate as calcu lated from the nitrate concentration and magnetic field. The highest specific growth rate (0.24 d 1) reached 16.8 mT and 132.2 mg L 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
SS: Sum of square; df: Degree of freedom (df); MS: Mean square F: F-value; p: Probability; MF: Magnetic field; N: Nitrate concentration; MF � N: Interaction term of magnetic field and nitrate concentration; R2: Coefficient of determina tion; Adj–R2: Adjusted R square. Alpha (α): 0.05; Confidence interval: 95%, *P < 0.05.
approximately 0.1 and 0.23, respectively. Since these values are larger than 0.05, it is inferred that there is no significant difference between the central points. Table 4 summarizes the regression parameters in the growth rate and lipid production model. The data show that linear terms (MF and N), square terms (MF2 and N2), and the two–way interaction term (MF � N) for growth factor but not for lipid production are the major factors with p–values below 0.05, which significantly affect the growth rate and lipid production regression model. The second-order polynomial equations fitted to the experimental data of the CCD for predicting growth rate and lipid production are given in Eq. (6) and Eq. (7), respectively:
3.2. Response surface modeling analysis Table 1 outlines the selection of MF intensities and nitrate concen trations for CCD and the resulting 7-day growth rate and crude lipid productivity of N. oculata. The ANOVA results for the predictive model are summarized in Table 3. The linear terms (MF and N) and square terms (MF2 and N2) have significant effects on growth rate and lipid production responses with p–values below 0.05. Furthermore, the twoway interaction term (MF � N) with a p–value of 0.03 also has a sig nificant effect on the response of growth rate. However, the interaction term (MF � N) of lipid production is approximately 0.71, which in dicates that its contribution is smaller than that of the other terms. The p–values of the lack of fit of the growth rate and lipid production are Table 4 Results of regression analysis for specific growth rate and lipid productivity of N. oculata. Factors
Regression coefficients
Specific growth rate (μ) Intercept 0.1403 MF 0.0128 2 0.0006 MF N 0.0043 2 N 0.00002 MF � N 0.00006
R2 0.900 Adj–R2 0.829 Lipid Production (mg L 1) Intercept 34.037 MF 2.005 MF2 0.059 N 0.799 2 N 0.003 R2 0.940 2 Adj–R 0.910
Student’s t–test (t)
Probability (p)
1.489 3.038 8.418 4.349 6.763 3.291
0.211 0.038* 0.001* 0.012* 0.003* 0.030*
4.346 6.248 7.572 8.413 9.128
0.012* 0.003* 0.002* 0.001* 0.001*
Fig. 2. Response surfaces and contour plots of lipid productivity as calculated from the nitrate concentration and magnetic field. The highest lipid produc tivity (38.8 mg L 1 d 1) reached 16.9 mT and 139.8 mg L 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
MF: Magnetic field; N: Nitrate concentration; MF � N: Interaction term of magnetic field and nitrate concentration; R2: Coefficient of determination; Adj–R2: Adjusted R square. Alpha (α): 0.05; Confidence interval: 95%, *P < 0.05. 4
F.-J. Chu et al.
Journal of Environmental Management 253 (2020) 109680
Table 5 Comparison of the growth parameters of lipid production of N. Oculata. Microalgae
Growth parameter 2
μ
(d 1)
CL productivity (mg L d 1)
1
References
Temp. (oC)
N conc. (mg L 1)
Medium
Irradiances (μmol m s 1)
N. oculata H.a
20
75 (NaNO3)
f/2 Guillard
70c
0.1
16
N. oculatb N. oculata UTEX 2164b
25 26
75 (KNO3) 606.6 (KNO3)
260 150
0.59 –
35 5
N. oculataa N. sp. MUR 267 N. oculata UTEX 2164b þ 10 mT N. oculataa þ 16.8 mT N. oculataa þ 16.9 mT
25 25 23.5
200 (NaNO3) 0 1870 (NaNO3)
f/2 enriched f/2 without vitamin Walne enriched Seawater Modified seawater
Converti et al. (2009) Wu et al. (2013) Shen et al. (2014)
54 150 600c
0.13 – –
– 10.2 38
Wang et al. (2015) Ishika et al., 2018 Oliveira (2017)
25 25
132.2 (NaNO3) 139.8 (NaNO3)
Walne Walne
67.5 67.5
0.24 0.21
34 38
This study This study
Temp.: Temperature; N. conc.: Initial nitrogen source concentration; CL: Crude lipid. a Aeration by Air. b Aeration by 2% CO2. c Measured by photo flux density (μE m 2s 1).
Y1 ¼
0:1403 þ 0:0128 MF
0:0006 MF2 þ 0:0043 N
(6)
þ 0:00006 MF � N Y2 ¼
34:037 þ 2:005 MF
crude lipid productivity of N. oculata (38 mg L 1 d 1) is much higher than that of N. oculata H. in f/2 Guillard’s medium with 75 mg L 1 NaNO3 at 70 μE m 2 s 1 (10 mg L 1 d 1), N. oculata. in f/2 enriched medium with 75 mg L 1 KNO3 at 260 μmol m 2 s 1 (35 mg L 1 d 1), N. oculata UTEX 2164 in f/2 medium without vitamin at 150 μmol m 2 s 1 (5 mg L 1 d 1), N. sp in sea water at 150 μmol m 2 s 1 (10.2 mg L 1 d 1) and N. oculata UTEX 2164 under MF strength of 16.9 mT in modified seawater with 1870 mg L 1 NaNO3 at 600 μE m 2 s 1 (38 mg L 1 d 1). N. oculata is a candidate for growth in seawater. Future work will focus on the relationship between the bioeffect of the magnetic field and proteomic changes in lipid accumulation. Moreover, this result can promote the development an MF microalgae reactor to solve nitrogenrich piggery wastewater.
0:00002 N 2
0:059 MF 2 þ 0:799 N
0:003 N 2
(7)
where Y1 is the growth rate (d 1), Y2 is the crude lipid production (mg L 1 d 1), MF is the magnetic field strength (6 mT–34 mT), and N is the initial nitrate concentration (80 mg L 1 – 220 mg L 1). Table 1 summarizes both observations from experimental results and the predicted values calculated from the model (Table 3) using Statistica 6.0. The quality of fit of the regression equations was tested by exam ining the adjusted determination coefficient adj–R2. The values of adj–R2 (0.829 and 0.91 for Eqs. (6) and (7), respectively) indicate a high degree of agreement between the observed and predicted values for all of the response studies (Table 4). Within the tested ranges of MF (6 mT–34 mT) and N concentration (80 mg L 1 – 220 mg L 1), the growth rate of N. oculata is estimated to reach a maximum of 0.24 d 1 at a cultivation time of 7 days, MF of 16.8 mT and N concentration of 132.2 mg L 1 according to the regres sion model in Eq. (6). Furthermore, the crude lipid productivity of N. oculata is estimated to reach a maximum of 38.8 mg L 1 d 1 at a cultivation time of 7 days, MF strength of 16.9 mT and N concentration of 139.8 mg L 1 according to the regression model in Eq. (7). The response surface plots showing the mutual effect of MF and N as a functional pair of controlled factors on the N. oculata growth rate (Fig. 1) and crude lipid productivity (Fig. 2) indicate that these variables substantially affect the response. Additionally, the two–way interaction between MF and N is an important term for the growth rate; however, with a p–value of 0.71 (Table 3), the interaction does not appear to affect lipid production.
4. Conclusions The effects of MF and nitrate concentration on the specific growth rate and crude lipid productivity of N. oculata were investigated. The optimization results show that appropriate MF and nitrate concentra tions are important factors that significantly accelerate the growth rate and lipid production because the interaction term MF � N affects the specific growth rate. This low-cost approach would enable the design of industrial processes. The relationship between the bioeffect of the magnetic field and the proteomic change in lipid accumulation in N. oculata will be investigated in future studies. Acknowledgments This work was supported by the Ministry of Science and Technology, Taiwan, R.O.C. [grant no. MOST 108-2218-E-224-001].
3.3. Confirmatory experiments
Appendix A. Supplementary data
N. oculata was cultivated under optimized conditions with no lag phase (Fig. S3). The specific growth rate (μ) reached 0.24 < 0.01 d 1, which differed by 4% from the computed value. Crude lipid productivity reached 38 mg L 1 d 1 under conditions of 16.9 mT MF strength and 139.8 mg L 1 N concentration at a cultivation temperature of 25 � C, which differed by 2% from the computed value (Table S2). These results indicate that the established model is reliable. As reported in Table 5, the lipid productivity of N. oculata from media with different N sources and environmental conditions was equal to the productivity of crude lipid produced from N. oculata UTEX 2164 under MF strength of 10 mT by modified seawater medium with 1870 mg L 1 NaNO3 at 600 μE m 2 s 1 (38 mg L 1 d 1). However, the
Supplementary data to this article can be found online at https://doi. org/10.1016/j.jenvman.2019.109680. References Araujo, G.S., Silva, J.W., Viana, C.A., Fernandes, F.A., 2019. Effect of sodium nitrate concentration on biomass and oil production of four microalgae species. Int. J. Sustain. Energy 1–10. https://doi.org/10.1080/14786451.2019.1634568. Bauer, L.M., Costa, J.A.V., Da Rosa, A.P.C., Santos, L.O., 2017. Growth stimulation and synthesis of lipids, pigments and antioxidants with magnetic fields in Chlorella kessleri cultivations. Bioresour. Technol. 244, 1425–1432. https://doi.org/10.1016/ j.biortech.2017.06.036. Bligh, E.G., Dyer, W.J., 1959. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917. https://doi.org/10.1139/o59-099.
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Journal of Environmental Management 253 (2020) 109680
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Piazzi, A.C.F., Veiga, M.C., Santos, L.O., Costa, J.A.V., Kuhn, R.C., Salau, N.P.G., 2019. Modeling the growth of microalgae Spirulina sp. with application of illuminance and magnetic field. J. Chem. Technol. Biotechnol. 94, 1770–1776. https://doi.org/ 10.1002/jctb.5942. Qv, X.Y., Guo, Y.Y., Jiang, J.G., 2014. Assessment of the effects of nutrients on biomass and lipid accumulation in Dunaliella tertiolecta using a response surface methodology. RSC Adv. 4, 42202–42210. https://doi.org/10.1039/C4RA04192E. Rasdi, N.W., Qin, J.G., 2015. Effect of N: P ratio on growth and chemical composition of Nannochloropsis oculata and Tisochrysis lutea. J. Appl. Phycol. 27, 2221–2230. https://doi.org/10.1007/s10811-014-0495-z. Romero-Villegas, G.I., Fiamengo, M., Aci� en-Fern� andez, F.G., Molina-Grima, E., 2018. Utilization of centrate for the outdoor production of marine microalgae at the pilotscale in raceway photobioreactors. J. Environ. Manag. 228, 506–516. https://doi. org/10.1016/j.jenvman.2018.01.043. Sajjadi, B., Chen, W.Y., Raman, A.A.A., Ibrahim, S., 2018. Microalgae lipid and biomass for biofuel production: a comprehensive review on lipid enhancement strategies and their effects on fatty acid composition. Renew. Sustain. Energy Rev. 97, 200–232. https://doi.org/10.1016/j.rser.2018.07.050. Santos, L.O., Deamici, K.M., Menestrino, B.C., Garda-Buffon, J., Costa, J.A.V., 2017. Magnetic treatment of microalgae for enhanced product formation. World J. Microbiol. Biotechnol. 33, 169. https://doi.org/10.1007/s11274-017-2332-4. Shen, Y., Chen, C., Chen, W., Xu, X., 2014. Attached culture of Nannochloropsis oculata for lipid production. Bioproc. Biosyst. Eng. 37, 1743–1748. https://doi.org/10.1007/ s00449-014-1147-z. Small, D.P., Hüner, N.P.A., Wan, W., 2012. Effect of static magnetic fields on the growth, photosynthesis and ultrastructure of Chlorella kessleri microalgae. Bioelectromagnetics 33, 298–308. https://doi.org/10.1002/bem.20706. � stari�c, M., Klinar, D., Bricelj, M., Golob, J., Berovi�c, M., Likozar, B., 2012. Growth, So� lipid extraction and thermal degradation of the microalga Chlorella vulgaris. N. Biotech. 29, 325–331. https://doi.org/10.1016/j.nbt.2011.12.002. Surendhiran, D., Vijay, M., Razack, A., Subramaniyan, T., Shellomith, A.S., Tamilselvam, K., 2014. A green synthesis of antimicrobial compounds from marine microalgae Nannochloropsis oculata. J. Coast. Life Med. 2 https://doi.org/10.12980/ JCLM.2.2014APJTB-2014-0138, 862–859. Tran, N.A.T., Padula, M.P., Evenhuis, C.R., Commault, A.S., Ralph, P.J., Tamburic, B., 2016. Proteomic and biophysical analyses reveal a metabolic shift in nitrogen deprived Nannochloropsis oculata. Algal Res. 19, 1–11. https://doi.org/10.1016/j. algal.2016.07.009. Tu, R., Jin, W., Xi, T., Yang, Q., Han, S.F., Abomohra, A.E.F., 2015. Effect of static magnetic field on the oxygen production of Scenedesmus obliquus cultivated in municipal wastewater. Water Res. 86, 132–138. https://doi.org/10.1016/j. watres.2015.07.039. Wang, H.Y., Zeng, X.B., Guo, S.Y., Li, Z.T., 2008. Effects of magnetic field on the antioxidant defense system of recirculation cultured Chlorella vulgaris. Bioelectromagnetics 29, 39–46. https://doi.org/10.1002/bem.20360. Wang, T.H., Chu, S.H., Tsai, Y.Y., Lin, F.C., Lee, W.C., 2015. Influence of inoculum cell density and carbon dioxide concentration on fed-batch cultivation of Nannochloropsis oculata. Biomass Bioenergy 77, 9–15. https://doi.org/10.1016/j. biombioe.2015.03.014. Wasak, A., Drozd, R., Jankowiak, D., Rakoczy, R., 2019. Rotating magnetic field as tool for enhancing enzymes properties-laccase case study. Sci. Rep. 9, 3707. https://doi. org/10.1038/s41598-019-39198-y. Wu, P.F., Teng, J.C., Lin, Y.H., Hwang, S.C.J., 2013. Increasing algal biofuel production using Nannocholropsis oculata cultivated with anaerobically and aerobically treated swine wastewater. Bioresour. Technol. 133, 102–108. https://doi.org/10.1016/j. biortech.2013.01.109.
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Research article
Use of magnetic fields and nitrate concentration to optimize the growth and lipid yield of Nannochloropsis oculata Feng-Jen Chu a, Terng-Jou Wan b, *, Tzu-Yi Pai c, Hsiao-Wen Lin b, Shang-Hao Liu d, Chung-Fu Huang e a
Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, Douliou, 64002, Yunlin, Taiwan Department of Safety, Health and Environment Engineering, National Yunlin University of Science and Technology, Douliou, 64002, Yunlin, Taiwan Master Program of Environmental Education and Management, Department of Science Education and Application, National Taichung University of Education, Taichung, 40306, Taiwan d Department of Chemical Engineering, Anhui University of Science and Technology, Huainan, 232001, Anhui, China e School of Environmental and Chemical Engineering, Zhaoqing University, Zhaoqing, 526061, Guangdong, China b c
A R T I C L E I N F O
A B S T R A C T
Keywords: Nannochloropsis oculata Lipid productivity Magnetic fields Sodium nitrate Response surface methodology
Microalgae produce increased lipid content accompanied by a significant decrease in cell density with decreasing nitrate concentration. Magnetic fields (MF) have been reported as a factor that could accelerate metabolism and growth in microalgae culture. Thus, this study aimed to optimize the influence of MF and nitrate concentration (sodium nitrate, N) on the growth and lipid productivity of Nannochloropsis oculata. A single-factor experiment integrated with response surface methodology (RSM) via central composite design (CCD) was performed. The results showed that the maximum specific growth rate (0.24 d 1) and maximum lipid productivity (38 mg L 1 d 1) obtained in this study were higher than those of the control culture (by 166% and 103%, respectively). This study also found that the two-way interaction term MF � N had a significant effect on cell growth but not on lipid production. It was concluded that to design appropriate MF for enhanced lipid productivity due to cell growth, further research must focus on developing an understanding of the relationship between the bioeffects of the magnetic field and the proteomic changes involved in lipid accumulation strategies. This approach would enable the design of conditions to obtain inexpensive high-value products from N. oculata.
1. Introduction Despite the many applications and properties of microalgae as feedstock for the production of biofuels, the main interest is in reducing the cost of producing oil-rich microalgae using a modern production strategy that results in an increased growth rate and lipid content of upstream processes (Qv et al., 2014; Geada et al., 2018; Haberkorn et al., 2019). Microalgae cultivation requirements and harvesting steps play key roles in reducing the environmental impact and limiting the cost of microalgae biofuel production (Romero-Villegas et al., 2018; Sajjadi et al., 2018). Thus, effective techniques with low energy consumption, such as electromagnetic biostimulation (Hunt et al., 2009; Haberkorn et al., 2019), and static or modulated magnetic fields (MF) (Nezamma halleh et al., 2016; Santos et al., 2017; Deamici et al., 2019), have received increased attention in recent years. Nitrate concentration significantly affects both the growth rate and
lipid production of microalgae. Gaude et al. (2007) reported that the supply of a nitrate source affects galactolipid composition in microalgae. Kim et al. (2016) also reported the impacts of nitrate concentration on structural and functional components in peptides, enzymes and chlo rophylls. Recently, a small number of studies have cultivated N. oculata in nitrate-depleted medium for the synthesis of lipid accumulation during growth; however, reduced growth rates have been observed (Tran et al., 2016; Araujo et al., 2019). The glycolytic pathway is a major contributor to pyruvate production in fatty acid biosynthesis for tri acylglyceride (TAG) accumulation in N. oculata (Ma et al., 2016). In general, carbon partitioning from storage carbohydrates into the glycolysis pathway occurs under nitrogen-rich conditions (Han et al., 2017). Tran et al. (2016) observed that the shift in metabolic flux is activated to compensate for energy deficits since the glycolytic pathways of N. oculata are impaired under nitrogen-depleted conditions. Metsoviti et al. (2019) demonstrated that when C. vulgaris was grown at initial
* Corresponding author. E-mail address: [email protected] (T.-J. Wan). https://doi.org/10.1016/j.jenvman.2019.109680 Received 14 June 2019; Received in revised form 28 September 2019; Accepted 5 October 2019 Available online 18 October 2019 0301-4797/© 2019 Elsevier Ltd. All rights reserved.
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Journal of Environmental Management 253 (2020) 109680
Table 1 The experimental design and results of central composite design using RSM. Runs
Independent Variables (factor values) X1
1 2 3 4 5 6 7 8 9 10 11 12 13
Specific growth rate (μ, d X2
Magnetic Field, mT
Coded levels
Nitrate, g L
1 1
30 30 10 10 20 20 20 20 20 20 34 20 6
1
200 100 100 200 150 150 150 150 150 220 150 80 150
1 1
0 0 0 0 0 0 1.4142 0 1.4142
1 0 0 0 0 0 1.4142 0 1.4142 0
Lipid Productivity (mg L 1)
)
Y1
Coded levels
1 1
1
1
nitrate concentrations of 0–800 mg L 1 KNO3, not only the growth rate but also the protein and lipid contents were inhibited above 400 mg L 1. The results showed that as the nitrogen concentration in the culture medium increased, the protein content also increased, while the lipid content decreased. In conclusion, the metabolic responses under different nitrogen stress conditions had different results based on different aims. Therefore, developing strategies to achieve higher algal biomass and lipid productivity with environmentally friendly factors should be investigated. The use of MF has received increased attention as a nontoxic, wideranging and economical alternative to biocompounds (Tu et al., 2015). Additionally, MF can affect the bioelectrocatalytic transformations of several enzymes by enhancing electron transfer because enzyme activity can be increased under MF (Li et al., 2011; Santos et al., 2017; Wasak et al., 2019). For several aquaculture microalga species, MF has been successfully combined with available nitrate media to produce changes in enzyme levels (Deamici et al., 2016a). Some studies applied MF of different strengths to cultivate and assess the resulting cell growth of algae, such as Chlorella fusca (Deamici et al., 2019), Chlorella kessleri (Small et al., 2012; Bauer et al., 2017), Spirulina sp. (Deamici et al., 2016b; Piazzi et al., 2019) and Nannochloropsis oculata (Oliveira, 2017). However, the effects of optimized MF on N. oculata have not yet been considered. Hence, the aim of this study was to investigate the optimized growth rate and lipid productivity of N. oculata under different MF strengths and N concentration conditions.
Y2
Experimental
Model Prediction
Experimental
Model Prediction
0.140 0.119 0.196 0.090 0.266 0.241 0.254 0.230 0.217 0.096 0.038 0.174 0.182
0.107 0.092 0.213 0.101 0.241 0.241 0.241 0.241 0.241 0.109 0.078 0.177 0.158
20.27 26.79 32.05 23.88 39.32 40.53 35.43 37.88 36.67 20.17 18.39 26.02 32.57
18.79 23.75 31.82 25.22 37.95 37.95 37.95 37.95 37.95 19.92 21.27 28.01 31.43
(Magtech Magnetic Products Co., Taiwan) of differing strengths were applied for the duration of each batch of experiments (7 days). To choose the range of response surface methodology (RSM) design, ferrite magnets with intensities of 20 mT, 30 mT and 40 mT were utilized for preliminary optimal range studies. The intensity of the magnetic field was adjusted with ferrite magnets of different sizes for confirmatory experiments. Each ferrite magnet was positioned 10 cm above the reactor base and at one side of the reactor, and the intensity of the magnetic field was measured in the center of the ferrite magnets using a tesla meter (TM-601, Kanetec, Japan). 2.3. Analysis of biomass concentration and lipid extraction The biomass optical density was measured at a wavelength of 682 nm using a UV/VIS spectrophotometer (DR 4000U, Hach, USA). The dry biomass was centrifuged (CN-820, Hsiangtai, Taiwan) at 2500 rpm for 5 min, washed with distilled water 3 times, and dried in an oven (DO45, Dengyng, Taiwan) at 105 � C for 24 h. The microalga biomass concentration was estimated using Eq. (1): Biomass conc: ¼ 200:17 � OD682 þ 81:089 R2 ¼ 0:9858
(1)
1
The specific growth rate (μ, d ) was obtained from the increased microalgae concentration at various times using Eq. (2): � � D ln D0f μ¼ (2) t1 t0
2. Materials and methods
where Df is the final dry weight density (g L 1), D0 is the initial dry weight density (g L 1), and t1–t0 is the experimental time (d). In this study, lipid extraction was performed using the modified solvent extraction method proposed by Bligh and Dyer (1959) and � �stari�c et al., 2012. The lipid was extrac pulverizing pretreatment by So ted from 100 mL of algal suspension and centrifuged at 6000 rpm for 15 min, the supernatant was discarded, and the dried biomass was frozen (FDU-506, EYELA, Japan) at 20 � C for 72 h, then ground in a mortar. The lipids were extracted by 3 mL of chloroform/methanol (2/1, v/v) with dried biomass in a glass tube (weight determined). The mix tures were vortexed (ZX4, Velp Scientifica, Italy) for 1 min and centri fuged at 3600 rpm for 1 min. After phase separation, the supernatant was discarded again, and the process was repeated 3 times until the color turned from green to transparent. The heavier phase (the crude lipid fraction) was dried in a fume cupboard. The extracted lipid was obtained gravimetrically in this study. The lipid content was obtained by conversion according to Eq. (3):
2.1. Microalgae and culture media Nannochloropsis oculata was obtained from Tungkang Biotechnology Research Center, Fisheries Research Institute (FRI), Taiwan and culti vated in modified Walne’s medium (Surendhiran et al., 2014). The medium was adjusted to a pH of 8 and autoclaved (TM-321, Hoyu Inc., Taiwan) at 1.2 kg cm 2 (15 psi) and 121 � C for 20 min. Microalgae were cultivated in a 1 L reactor at room temperature (25 � 1 � C) with an illumination of 67.5 μmol protons m 2 s 1 using a fluorescent lamp (26 W) with a light/dark cycle of 12/12 h. Cultures were used for ex periments when the algal concentration reached 120 mg L 1 with the use of an aeration pump (Ep-12000, Rambo, Taiwan) at a rate of 0.25 vvm (air without CO2 enrichment) and agitation. The composition of the modified Walne’s medium is provided in the Supplementary Material (Table S1). 2.2. Analytical methods for magnetic fields
Y ð%Þ ¼
For experiments with MF, commercial customized ferrite magnets 2
LW � 100% DW
(3)
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Journal of Environmental Management 253 (2020) 109680
Table 2 Parameters of N. oculata growth under different nitrate concentrations and magnetic fields. 1
Parameters
Nitrate concentration, mg L 100 (control)
150
200
20
30
40
μ (d 1) τ (d)
0.09 � 0.02b 1.1 � 0.2a 131 � 9a 41 � 5a 18.7 � 1.3a
0.10 < 0.01b 1.04 < 0.01a 167 � 10b 37.1 � 2.2a 23.9 � 1.4b,c
0.10 � 0.02b 0.99 � 0.02a 165 � 13b 37.3 � 3.0a 23.6 � 1.9b,c
0.11 � 0.02b 0.9 � 0.1a 216 � 18c 42.4 � 4.7a 30.9 � 2.6d
0.08 < 0.01a 1.2 � 0.06a 171 � 13b 41.8 � 4.7a 24.4 � 1.9c
0.05 � 0.01a 1.9 � 0.2b 148 � 5a,b 39.8 � 2.4a 21.1 � 0.7a,b
CL concentration (mg L 1) CL contents (% w w 1) CL productivity (mg L 1 d 1)
Magnetic field, mT
Means � standard deviations. Different lowercase letters in the same line correspond to significant differences between all assays (p < 0.05) by Tukey’s test.
3. Results and discussion
where Y is the extracted lipid yield (%); Lw is the extracted lipid weight, and Dw is the dry biomass weight. The lipid productivity was estimated by Eq. (4): Lipid productivity mg L
1
�
¼
Df � Yf
D0 � Y0 T
3.1. Influence of different factors on growth rate and crude lipid concentration
(4)
The effects of different MF strengths and initial nitrate concentra tions on the growth of N. oculata are summarized in Table 2. The specific growth rate and crude lipid productivity of N. oculata reached maximum values of 0.11 d 1 (22% higher than the control of 0.09 d 1) and 30.9 mg L 1 d 1 (65% higher than the control of 18.7 mg L 1 d 1) at 20 mT, respectively. The specific growth rate decreased significantly when the MF intensity was 30 mT (0.08 d 1) or 40 mT (0.05 d 1). This result indicates that an intensity of 20 mT stimulated the growth of N. oculata, whereas intensities of 30 mT and 40 mT inhibited the growth rate. Nezammahalleh et al. (2016) demonstrated that MF effects on cell growth which was attributed to enhancement of algae membrane permeability, resulting in transportation of substrate into cytoplasm of cell, could be classified as a stimulatory function. However, the potential damage of algae cell was observed at high magnetic field intensities and high treatment times due to an increase in the free radicals of media (Small et al., 2012; Wang et al., 2008). The appropriate MF could in fluence the cell metabolism of algae, and there was a possible conse quence on the growth rate of cells. When the initial nitrate concentration was varied from 100 mg L 1 (control) to 200 mg L 1, the growth rate and crude lipid productivity of N. oculata reached maximum values of 0.1 d 1 and 23.9 mg L 1 d 1, respectively, with no significant changes occurring with a further in crease in the initial nitrate concentration, but the crude lipid produc tivity decreased when the growth rate decreased. Nitrogen concentration was also a significant limiting condition for lipid content (Shen et al., 2014; Rasdi et al., 2015). This is due to nitrate must first be reduced to ammonium that can be use directly assimilated into the cells. However, high concentration of ammonium would be toxic to micro algae (Metsoviti et al., 2019). Converti et al. (2009) reported that a reduced nitrate concentration of 300 mg L 1 – 75 mg L 1 in the growth medium of N. oculata resulted in an almost constant growth rate but increased lipid production by protein biosynthesis. Shen et al. (2014) compare the adhesion biomass and lipid yield of N. oculata at different concentration levels of the nitrogen source (6 mM–24 mM); the biomass productivity and the lipid yield decreased from 3.43 g m 2d 1 to 1.77 g m 2d 1 and 0.46 g m 2d 1 to 0.28 g m 2d 1, respectively. Additionally, the CL concentration and productivity in the MF (20 mT) and N concentration (150 mg L 1, 200 mg L 1) conditions were significantly higher (p < 0.05) than in the control. When a MF of 40 mT was applied throughout cultivation, the CL concentration and produc tivity were statistically similar to those of the control culture. The gen eration time for the 20 mT condition that accelerated the growth of N. oculata was 0.9 d. The lower generation time makes cultivation more economically viable. Based on these results, it is possible to study MF application in combination with different nitrate concentrations, since those conditions increased growth rate and lipid productivity.
where lipid productivity is in units of milligrams per liter per day (mg L 1 d 1), and T is the cultivation time (d); Df and D0 are the final and initial lipid content (%) during the cultivation time, and Yf and Yi are the final and initial biomass concentration (mg L 1), respectively. 2.4. Single-factor experimental design Single-factor experimental design was used to define the ranges of the nitrate concentration (100 mg L 1 – 200 mg L 1) and the magnetic field (20 mT–40 mT) to examine the effects on the growth of N. oculata in a preliminary investigation (Figs. S1 and S2). Table S2 shows the quantitative values of the factor levels from the primary investigation with optimization by RSM. 2.5. Experimental design and optimization Full-factorial central composite design (CCD) was used to develop response surface models and to perform a factorial 22 design for the twofactor optimization of the growth rate (Y1, d 1) and lipid productivity (Y2, mg L 1) (Table 1). The magnetic field (X1, mT) and nitrate con centration (X2, mg L 1) were selected as independent variables. Statis tica 6.0 software (StatSoft Inc., USA) was used to develop the response model. The experiment included 14 runs performed under the condi tions shown in Table 1. Five duplicate runs were given four degrees of freedom for pure experimental uncertainties (pure error), while the axial pffiffiffi points were determined to be � 2. The acquired data were fit to a second-order polynomial model as shown in Eq. (5) (Montgomery and Runger, 2006): k X
Y ¼ β0 þ
k X
β i XI þ i¼1
βii X 2i þ
i¼1
XX βij Xi Xj þ ε
(5)
i
where Y is the response (growth rate (d 1) or lipid concentration (mg L 1)); X1 is the magnetic field strength (mT); X2 is the nitrate concen tration (mg L 1); β terms are the parameters or regression coefficients whose values are to be determined (βij is the response interaction be tween two individual factors, and βii represents pure second-order quadratic effects); k denotes the number of experimentally studied fac tors; and ε is the random error of the experiment. 2.6. Statistical analysis The results of the single-factor experiment were performed in three replicates and calculated as the mean � standard deviation. Statistical analyses were carried out by SPSS v20 (IBM Corporation, USA) using analysis of variance (ANOVA) followed by Tukey’s test at a probability level of p < 0.05. The full-factorial CCD of each factor was determined using Student’s t-test. 3
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Journal of Environmental Management 253 (2020) 109680
Table 3 Analysis of variance for the experimental design results of specific growth rate and lipid productivity of N. oculata. Factors
SS
Specific growth rate (μ) MF 0.007 MF2 0.027 NN 0.005 N2 0.017 MF � N 0.004 Lack of fit 0.005 Pure error 0.001 Total SS 0.061 2 R 0.900 2 0.829 Adj. R Lipid Productivity (mg L 1 d MF 104.16 MF2 236.86 N 66.10 N2 344.24 MF � N 0.68 Lack of fit Pure error Total SS R2 Adj–R2
26.93 16.53 734.31 0.941 0.899
1
)
df
MS
F
p
1 1 1 1 1
0.007 0.027 0.005 0.017 0.004
17.72 71.94 12.79 45.74 10.83
0.01* 0.00* 0.02* 0.00* 0.03*
3 4 12
0.002 0.000
4.08
0.10
1 1 1 1 1
104.16 236.86 66.10 344.24 0.68
25.21 57.33 16.00 83.32 0.16
0.01* 0.00* 0.02* 0.00* 0.71
3 4 12
8.98 4.13
2.17
0.23
Fig. 1. Response surfaces and contour plots of specific growth rate as calcu lated from the nitrate concentration and magnetic field. The highest specific growth rate (0.24 d 1) reached 16.8 mT and 132.2 mg L 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
SS: Sum of square; df: Degree of freedom (df); MS: Mean square F: F-value; p: Probability; MF: Magnetic field; N: Nitrate concentration; MF � N: Interaction term of magnetic field and nitrate concentration; R2: Coefficient of determina tion; Adj–R2: Adjusted R square. Alpha (α): 0.05; Confidence interval: 95%, *P < 0.05.
approximately 0.1 and 0.23, respectively. Since these values are larger than 0.05, it is inferred that there is no significant difference between the central points. Table 4 summarizes the regression parameters in the growth rate and lipid production model. The data show that linear terms (MF and N), square terms (MF2 and N2), and the two–way interaction term (MF � N) for growth factor but not for lipid production are the major factors with p–values below 0.05, which significantly affect the growth rate and lipid production regression model. The second-order polynomial equations fitted to the experimental data of the CCD for predicting growth rate and lipid production are given in Eq. (6) and Eq. (7), respectively:
3.2. Response surface modeling analysis Table 1 outlines the selection of MF intensities and nitrate concen trations for CCD and the resulting 7-day growth rate and crude lipid productivity of N. oculata. The ANOVA results for the predictive model are summarized in Table 3. The linear terms (MF and N) and square terms (MF2 and N2) have significant effects on growth rate and lipid production responses with p–values below 0.05. Furthermore, the twoway interaction term (MF � N) with a p–value of 0.03 also has a sig nificant effect on the response of growth rate. However, the interaction term (MF � N) of lipid production is approximately 0.71, which in dicates that its contribution is smaller than that of the other terms. The p–values of the lack of fit of the growth rate and lipid production are Table 4 Results of regression analysis for specific growth rate and lipid productivity of N. oculata. Factors
Regression coefficients
Specific growth rate (μ) Intercept 0.1403 MF 0.0128 2 0.0006 MF N 0.0043 2 N 0.00002 MF � N 0.00006
R2 0.900 Adj–R2 0.829 Lipid Production (mg L 1) Intercept 34.037 MF 2.005 MF2 0.059 N 0.799 2 N 0.003 R2 0.940 2 Adj–R 0.910
Student’s t–test (t)
Probability (p)
1.489 3.038 8.418 4.349 6.763 3.291
0.211 0.038* 0.001* 0.012* 0.003* 0.030*
4.346 6.248 7.572 8.413 9.128
0.012* 0.003* 0.002* 0.001* 0.001*
Fig. 2. Response surfaces and contour plots of lipid productivity as calculated from the nitrate concentration and magnetic field. The highest lipid produc tivity (38.8 mg L 1 d 1) reached 16.9 mT and 139.8 mg L 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
MF: Magnetic field; N: Nitrate concentration; MF � N: Interaction term of magnetic field and nitrate concentration; R2: Coefficient of determination; Adj–R2: Adjusted R square. Alpha (α): 0.05; Confidence interval: 95%, *P < 0.05. 4
F.-J. Chu et al.
Journal of Environmental Management 253 (2020) 109680
Table 5 Comparison of the growth parameters of lipid production of N. Oculata. Microalgae
Growth parameter 2
μ
(d 1)
CL productivity (mg L d 1)
1
References
Temp. (oC)
N conc. (mg L 1)
Medium
Irradiances (μmol m s 1)
N. oculata H.a
20
75 (NaNO3)
f/2 Guillard
70c
0.1
16
N. oculatb N. oculata UTEX 2164b
25 26
75 (KNO3) 606.6 (KNO3)
260 150
0.59 –
35 5
N. oculataa N. sp. MUR 267 N. oculata UTEX 2164b þ 10 mT N. oculataa þ 16.8 mT N. oculataa þ 16.9 mT
25 25 23.5
200 (NaNO3) 0 1870 (NaNO3)
f/2 enriched f/2 without vitamin Walne enriched Seawater Modified seawater
Converti et al. (2009) Wu et al. (2013) Shen et al. (2014)
54 150 600c
0.13 – –
– 10.2 38
Wang et al. (2015) Ishika et al., 2018 Oliveira (2017)
25 25
132.2 (NaNO3) 139.8 (NaNO3)
Walne Walne
67.5 67.5
0.24 0.21
34 38
This study This study
Temp.: Temperature; N. conc.: Initial nitrogen source concentration; CL: Crude lipid. a Aeration by Air. b Aeration by 2% CO2. c Measured by photo flux density (μE m 2s 1).
Y1 ¼
0:1403 þ 0:0128 MF
0:0006 MF2 þ 0:0043 N
(6)
þ 0:00006 MF � N Y2 ¼
34:037 þ 2:005 MF
crude lipid productivity of N. oculata (38 mg L 1 d 1) is much higher than that of N. oculata H. in f/2 Guillard’s medium with 75 mg L 1 NaNO3 at 70 μE m 2 s 1 (10 mg L 1 d 1), N. oculata. in f/2 enriched medium with 75 mg L 1 KNO3 at 260 μmol m 2 s 1 (35 mg L 1 d 1), N. oculata UTEX 2164 in f/2 medium without vitamin at 150 μmol m 2 s 1 (5 mg L 1 d 1), N. sp in sea water at 150 μmol m 2 s 1 (10.2 mg L 1 d 1) and N. oculata UTEX 2164 under MF strength of 16.9 mT in modified seawater with 1870 mg L 1 NaNO3 at 600 μE m 2 s 1 (38 mg L 1 d 1). N. oculata is a candidate for growth in seawater. Future work will focus on the relationship between the bioeffect of the magnetic field and proteomic changes in lipid accumulation. Moreover, this result can promote the development an MF microalgae reactor to solve nitrogenrich piggery wastewater.
0:00002 N 2
0:059 MF 2 þ 0:799 N
0:003 N 2
(7)
where Y1 is the growth rate (d 1), Y2 is the crude lipid production (mg L 1 d 1), MF is the magnetic field strength (6 mT–34 mT), and N is the initial nitrate concentration (80 mg L 1 – 220 mg L 1). Table 1 summarizes both observations from experimental results and the predicted values calculated from the model (Table 3) using Statistica 6.0. The quality of fit of the regression equations was tested by exam ining the adjusted determination coefficient adj–R2. The values of adj–R2 (0.829 and 0.91 for Eqs. (6) and (7), respectively) indicate a high degree of agreement between the observed and predicted values for all of the response studies (Table 4). Within the tested ranges of MF (6 mT–34 mT) and N concentration (80 mg L 1 – 220 mg L 1), the growth rate of N. oculata is estimated to reach a maximum of 0.24 d 1 at a cultivation time of 7 days, MF of 16.8 mT and N concentration of 132.2 mg L 1 according to the regres sion model in Eq. (6). Furthermore, the crude lipid productivity of N. oculata is estimated to reach a maximum of 38.8 mg L 1 d 1 at a cultivation time of 7 days, MF strength of 16.9 mT and N concentration of 139.8 mg L 1 according to the regression model in Eq. (7). The response surface plots showing the mutual effect of MF and N as a functional pair of controlled factors on the N. oculata growth rate (Fig. 1) and crude lipid productivity (Fig. 2) indicate that these variables substantially affect the response. Additionally, the two–way interaction between MF and N is an important term for the growth rate; however, with a p–value of 0.71 (Table 3), the interaction does not appear to affect lipid production.
4. Conclusions The effects of MF and nitrate concentration on the specific growth rate and crude lipid productivity of N. oculata were investigated. The optimization results show that appropriate MF and nitrate concentra tions are important factors that significantly accelerate the growth rate and lipid production because the interaction term MF � N affects the specific growth rate. This low-cost approach would enable the design of industrial processes. The relationship between the bioeffect of the magnetic field and the proteomic change in lipid accumulation in N. oculata will be investigated in future studies. Acknowledgments This work was supported by the Ministry of Science and Technology, Taiwan, R.O.C. [grant no. MOST 108-2218-E-224-001].
3.3. Confirmatory experiments
Appendix A. Supplementary data
N. oculata was cultivated under optimized conditions with no lag phase (Fig. S3). The specific growth rate (μ) reached 0.24 < 0.01 d 1, which differed by 4% from the computed value. Crude lipid productivity reached 38 mg L 1 d 1 under conditions of 16.9 mT MF strength and 139.8 mg L 1 N concentration at a cultivation temperature of 25 � C, which differed by 2% from the computed value (Table S2). These results indicate that the established model is reliable. As reported in Table 5, the lipid productivity of N. oculata from media with different N sources and environmental conditions was equal to the productivity of crude lipid produced from N. oculata UTEX 2164 under MF strength of 10 mT by modified seawater medium with 1870 mg L 1 NaNO3 at 600 μE m 2 s 1 (38 mg L 1 d 1). However, the
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