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Enhancement of lipid productivity by adopting multi-stage continuous cultivation strategy in Nannochloropsis gaditana
Accepted Manuscript Enhancement of Lipid Productivity by Adopting Multi-stage Continuous Cultivation Strategy in Nannochloropsis gaditana Min-Gyu Sung, Bongsoo Lee, Chul Woong Kim, Kibok Nam, Yong Keun Chang PII: DOI: Reference:
S0960-8524(16)31778-3 http://dx.doi.org/10.1016/j.biortech.2016.12.100 BITE 17476
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
28 October 2016 26 December 2016 27 December 2016
Please cite this article as: Sung, M-G., Lee, B., Woong Kim, C., Nam, K., Keun Chang, Y., Enhancement of Lipid Productivity by Adopting Multi-stage Continuous Cultivation Strategy in Nannochloropsis gaditana, Bioresource Technology (2016), doi: http://dx.doi.org/10.1016/j.biortech.2016.12.100
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1
Enhancement of Lipid Productivity by Adopting Multi-stage Continuous Cultivation
2
Strategy in Nannochloropsis gaditana
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Min-Gyu Sung1†, Bongsoo Lee1†, Chul Woong Kim2, Kibok Nam1, Yong Keun Chang1,3*
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gu, Daejeon 305-701, Republic of Korea
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2
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Korea
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3
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Department of Chemical and Biomolecular Engineering, KAIST, 291 Daehak-ro, Yuseong-
Corporate R&D Research Park, LG Chem, 188 Munji-ro, Yeseong-gu, Daejeon, Republic of
Advanced Biomass R&D Center, #2502 Building W1-3, KAIST, 291 Daehak-ro, Yuseong-
gu, Daejeon 305-701, Republic of Korea
11 12
Corresponding Author:
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Yong Keun Chang,
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Tel: +82-42-350-3927, Fax: +82-42-350-3910, [email protected]
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†Min-Gyu Sung and Bongsoo Lee contributed equally to this work
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Keywords: Microalgae, Photobioreactor, Stage Cultivation, Chemostat, Biodiesel
17 18 19 1
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Abstract
21
In the present study, a novel process-based cultivation system was designed to improve lipid
22
productivity of Nannochloropsis gaditana, an oleaginous microalga that has high potential
23
for biofuel production. Specifically, four flat-panel photobioreactors were connected in series,
24
and this system was subjected to continuous chemostat cultivation by feeding fresh medium
25
to the first reactor at dilution rates of 0.028 and 0.056 day-1, which were determined based on
26
Monod kinetics. The results show that the serially connected photobioreactor system
27
achieved 20.0% higher biomass productivity and 46.1% higher fatty acid methyl ester
28
(FAME) productivity than a conventional single photobioreactor with equivalent dilution rate.
29
These results suggest that a process-based approach using serially connected photobioreactors
30
for microalgal cultivation can improve the productivity of lipids that can be used for biofuel
31
production.
32 33 34 35 36 37 38 39 40 2
41 42
1. Introduction There are growing concerns about global warming and climate change because of the
43
continuing use of petroleum-based fuels. In addition, limited oil deposits have increased the
44
energy crisis worldwide (Ho et al., 2014). In these regards, biomass feedstocks for renewable
45
energy production are an important alternative energy source that can replace fossil fuels.
46
Among the various potential alternative energy resources, microalgae have been spotlighted
47
because they have many advantageous traits for biofuel production compared to crop-based
48
biofuels and lignocellulosic biomass. A major advantage is that microalgae grow rapidly and
49
consuming CO2 for photosynthesis. Furthermore, it has been reported that microalgae can
50
produce up to 25-fold more lipids than that of conventional crops or land plants (Ahmad et al.,
51
2011). This suggests microalgae accumulate large amounts of lipids that can be converted
52
into biodiesel (Chen et al., 2011).
53
Microalgae have many advantages as energy resources, but many obstacles must be
54
overcome for commercialization of a microalgae-based biofuel production system. Consistent
55
with this necessity, it has been reported that microalgae being cultivated will ultimately affect
56
every step of the microalgae to biofuels supply chain (National Algal Biofuels Technology
57
Roadmap of US DOE) due to their diverse characteristics. In other words, cultivation of
58
microalgae with high biomass and lipid yields is crucial for successful microalgae-derived
59
biofuel production. One of the major challenges is that microalgae normally accumulate
60
small amounts of lipids under nutrient replete growth conditions, whereas efficient biofuel
61
production requires biomass with high levels of lipids (Gong & Jiang, 2011; Singh & Dhar,
62
2011). To increase the lipid content of microalgae, some researchers have introduced
63
additional strategies such as nitrogen limitation and two-stage cultivation during the 3
64 65
cultivation process (Zheng et al., 2012; Su et al, 2011; Rodolfi et al., 2009; Roessler, 1990). It should be noted that nitrogen starvation sometimes induces starch accumulation in
66
particular species (Ho et al, 2012). However, nitrogen limitation is still one of the most
67
common methods used to induce higher lipid production in many microalgae strains
68
(Griffiths et al., 2014; Liu et al., 2016; Yeh & Chang, 2011). In N. gaditana, when the
69
nitrogen supply is limited, intracellular nitrogen redistribution occurs, and this induces lipid
70
biosynthesis (Carpinelli et al., 2014). Therefore, prolonged exposure to nitrogen-limited
71
conditions results in higher neutral lipid content in N. gaditana (Simionato et al., 2013). This
72
method for lipid induction, however, is achieved by exposing the cells to a stressful condition,
73
and this does not support rapid growth. Consequently, this method leads to decreases in
74
overall biomass productivity, and microalgae lose their inherent advantage as a fast growing
75
source of biomass for biofuel production (Borowitzka, 1992).
76
Many studies have attempted to solve the problem of growth cessation during the
77
lipid induction step. One common solution proposed is the use of a two-stage cultivation
78
system, where an additional lipid induction step is introduced at the later stage of cultivation,
79
so that cells accumulate more lipids than under normal conditions (dos Santos et al., 2016;
80
Suali & Sarbatly, 2012). In the two-stage cultivation process, microalgae are first cultured on
81
a nutrient-rich environment for fast growth. Then, the fully grown cells are subjected to
82
nutrient deprivation to induce lipid accumulation (Martin et al., 2016; Su et al., 2011; Suali &
83
Sarbatly, 2012).
84
Although many studies have applied multi-stage cultivation methods to increase lipid
85
productivity in microalgae, only a few examined this method using continuous cultivation
86
(Klok et al., 2013; Zhang et al., 2014). Continuous cultivation has many benefits compared to 4
87
batch or semi-batch systems. Unlike batch cultivation, continuous cultivation ensures that the
88
operation conditions for growth are maintained at precise levels, determined by the purpose
89
of cultivation, and this provides a stable environment for the microalgae (Tang et al., 2012).
90
In addition, continuous cultivation greatly reduces the labor needed for cleaning and
91
sterilization of the photobioreactors (PBRs) between cultivation batches (Fernandes et al.,
92
2015).
93
In the present study, a new continuous cultivation process was introduced to produce
94
a concentrated microalgal biomass with high lipid content. The process consists of several
95
photobioreactors, with each functioning as an independent environment, that are serially
96
connected so there is simultaneous an accumulation of biomass and lipids in the final reactor.
97
The process is operated in a chemostat, and fresh medium is supplied through the first reactor.
98
In order to investigate the performance of process-based cultivation system, biomass and
99
lipid content were analyzed in each reactor position, and overall lipid productivity was
100
compared to traditional photobioreactor based cultivation systems.
101 102 103 104 105 106 107
5
108
2. Material & Methods
109
2.1. Medium and culture conditions
110
The marine microalga Nannochloropsis gaditana CCMP526 from the National
111
Center for Marine Algae and Microbiota (Maine, USA) was used in this study. The strain was
112
maintained in sterile modified f/2 medium (Guillard & Ryther, 1962) with the following
113
composition: 30 g L-1 sea salts, 375 mg L-1 NaNO3, 5 mg L-1 NaH2PO4·9H2O, 3.15 mg L-1
114
FeCl3·6H2O, 4.36 mg L-1 Na2EDTA·2H2O, 9.8 µg L-1 CuSO4·5H2O, 6.3 µg L-1
115
Na2MoO4·2H2O, 22 µg L-1 ZnSO4·7H2O, 10 µg L-1 CoCl2·6H2O, 180 µg L-1 MnCl2·4H2O, 0.5
116
µg L-1 vitamin B12, 0.5 µg L-1 biotin, and 100 µg L-1 thiamine hydrochloride. The seed culture
117
for photobioreactor cultivation was grown in a culture flask with 300 ml of modified f/2
118
medium at 100 µmol photons m-2 s-1 and 25 °C.
119
2.2. Photobioreactor set-up and determination of dilution rate
120
Four flat-panel PBRs with identical designs were connected in series for cultivation
121
(Fig. S1). PBR frames were made of polyvinyl chloride (PVC) with a width, height and
122
thickness of 220, 335 and 30 mm, respectively, and the working volume was 2.25 L for each
123
reactor. Transparent polycarbonate sheets were used to transmit the LED illumination with a
124
light-path of 30 mm. Gas (3% CO2, v/v) was supplied through a bubble tube at the bottom of
125
each PBR. Sufficient mixing was achieved through the gas bubbles, so the system was
126
assumed to be a continuous stirred-tank reactor. White LED panels supplied 100 µmol
127
photons m-2 s-1 intensity of light to each reactor.
128 129
For a chemostat operation of serially connected PBRs, fresh modified f/2 medium was supplied to the first reactor with a peristaltic pump (Watson-Marlow, UK). The working 6
130
volume in each reactor was inherently maintained through an overflow channel of reactors
131
connected in series (Fig. S1), and this resulted in equivalent feed flow rates in every reactor.
132
Consequently, the dilution rate, which is the feed flow rate divided by the culture volume,
133
became 1/n of the first reactor at the n-th reactor because the same volume of culture was
134
added along the reactor positions where the feed flow rate was constantly maintained.
135
Biomass samples were collected from each bioreactor for the experimental analysis.
136
Dilution rates in chemostat serially connected PBRs were determined by following
137
steps. In a continuous cultivation process with one bioreactor, the specific growth rate (µ) is
138
related to dilution rate (D) by the following mass balance equation (Sung et al., 2014; Tang et
139
al., 2012):
140
= −
(1)
141
where X is biomass concentration and t is time. At steady state, μ = D, so that specific
142
growth can be determined from the dilution rate. In addition, D should not exceed the
143
maximum specific growth rate to prevent washout (Bailey & Ollis, 1976), as described by an
144
equation that follows Monod kinetics (Monod, 1949):
145
=
146
where µmax is the maximum specific growth rate, sf is the substrate concentration at the feed
147
stream, and Ks is a half-saturation constant. Monod kinetics also predicts a dilution rate that
148
produces theoretically maximal cell output (Bailey & Ollis, 1976):
149
= 1 −
<
(2)
(3)
7
150
To determine the dilution rates for the operation of serially connected PBRs, the
151
maximum specific growth rate of N. gaditana strain must be verified. Thus, batch cultivation
152
in a flat-panel PBR, using the same conditions as the serially connected PBR system, was
153
used to determine the maximum specific growth rate.
154
2.3. Growth measurement and specific growth rate calculation
155
In the batch cultivation in a flat-panel PBR, the optical density (OD) of the
156
microalgae suspension was measured at 750 nm with a uv-spectrophotometer (Shimadzu,
157
Japan) to monitor cell growth. Cellulose nitrate membrane filters with a 0.45 µm pore size
158
(Whatman, USA) were used for the dry cell weight measurement in the serially connected
159
PBRs. Filter papers were pre-dried in an oven at 80 ℃, then microalgae suspensions were
160
passed through using a vacuum pump. Filtered cells were dried at 80 ℃ overnight for
161
calculation of dry cell weight.
162
For multiple connected continuous reactors with constant volume, the mass balance
163
of each reactor can be described as (Bailey & Ollis, 1976; Monod, 1949):
164
165
where Xi and µi are biomass concentration and specific growth rate in i-th reactor,
166
respectively. At steady state,
167
estimated from Eq. 2:
168
=
169
2.4. Nitrate concentration measurement
= !" + −
(4)
$% $&
= 0 and the specific growth rate of i-th reactor can be
( ! )*
(5)
8
170
Microalgae suspensions were centrifuged at 7000 rpm for 10 min. (Combi 514 R,
171
Hanil Scientific Inc., Korea). The supernatant was passed through a 0.2 µm syringe filter, and
172
the nitrate concentration was quantified with ion chromatography (883 Basic IC plus,
173
Metrohm, Switzerland). An anion column Metrosep A Supp 5 was used to analyze the nitrate
174
(NO3-) ions remaining in the culture medium. The eluent, which consisted of 3.2 mM Na2CO3
175
and 1 mM NaHCO3, was supplied at a flow rate of 0.7 ml min-1 into the column for the
176
analysis.
177
2.5. Fatty acid methyl ester analysis
178
Microalgae suspensions were centrifuged at 7000 rpm for 10 min. The pellets were
179
washed twice with distilled water, and then stored at -70 ℃ for 24 h. Frozen cells were dried
180
in a freeze dryer (Ilshin, Republic of Korea) for up to 4 days. Dried cells were ground into
181
powder, treated with chloroform/methanol (2:1, v/v), and lipids were determined using the
182
modified Folch method (Folch et al., 1957). Methanol and sulfuric acid were added, and then
183
incubated at 100 ℃ for 20 min for fatty acid methyl ester (FAME) conversion.
184
Heptadecanoic acid was used as an internal standard. The organic phase was separated by 0.3
185
M NaOH, then recovered with centrifugation at 4000 rpm for 10 min. FAMEs were measured
186
by gas chromatography (HP 6890, Agilent, USA) with a flame ionized detector. FAME
187
content was calculated as: FAME content %, w/9 =
;
9:;<ℎ> ?@ ABCD ?E>F;G:H F@>:I >IFGJ:J>:I; 9:;<ℎ> ?@ L;I?FM
K F > ; ? G
× 100 188 9
189
3. Results & Discussion
190
3.1. Determination of dilution rate
191
Initially batch cultivation of N. gaditana was implemented in flat-panel PBRs in
192
duplicate after setting the initial OD750 nm to 0.2, and then, the growth was monitored by
193
continuous measurement at OD750 nm. The cells entered the exponential growth phase after 3
194
days, and a high growth rate was maintained for about 4 days (Fig. 1). The cells subsequently
195
entered the stationary phase on day 8. It is essential to monitor the levels of the limiting
196
nutrient to determine the dilution rate based on Monod kinetics (Monod, 1949). In microalgal
197
cultivation environments, nitrogen is commonly the major limiting nutrient for growth (Zhu
198
et al., 2013). Thus the nitrate concentration was measured during the batch cultivation of N.
199
gaditana in flat-panel PBRs. The results show that the consumption of nitrate closely
200
correlated with cell growth (Fig. 1). In particular, N. gaditana cells consumed most of the
201
nitrate during the exponential growth phase, and the nitrate was completely consumed at day
202
10, when cells were in the stationary phase.
203
Based on these results, the kinetic parameters were calculated using the Monod
204
equation. The maximum specific growth rate of 0.278 day-1 was determined at the
205
exponential growth stage (between day 2 and 6). This value and Eq. (2) was used to
206
determine the dilution rate that should not be exceeded. The sf and Ks values were calculated
207
based on elemental nitrogen. The nitrate concentration in the fresh medium was 375 mg L-1,
208
so the concentration of elemental nitrogen in the feed stream was 273.529 mg L-1. The half-
209
saturation constant (Ks) is 65.141 mg L-1; this is simply the concentration of the limiting
210
nutrient when the specific growth rate is half of the maximum.
211
When the dilution rate (D) exceeds the maximum dilution rate (Dmax), then it exceeds 10
212
the maximum growth rate of the cells. At this point, continuous washout of cells occurs, and
213
the system cannot be maintained (Bailey & Ollis, 1976). Dmax was estimated from the
214
parameters obtained from the preliminary batch experiment, as given in Eq. (2). Based on the
215
maximum growth rate (µ max), Dmax was calculated as 0.224 day-1. Thus, for the continuous
216
operation of serially connected PBRs, the dilution rate should not exceed 0.224 day-1. For the
217
PBR system, this upper limit was only applied to the first reactor, not for all 4 reactors,
218
because fresh medium is only supplied to the first reactor. As the culture passes between
219
reactors, the dilution rate at each reactor decreases, because the flow rate remains consistent
220
as the volume increases. As a consequence, the dilution rate at the fourth reactor is 25% (one-
221
fourth) of that in the first reactor.
222
In addition, the theoretical dilution rate at which the biomass production is
223
maximized (Dmaxoutput) could also be calculated (Bailey & Ollis, 1976) with Eq. (3). Dmaxoutput
224
was calculated as 0.156 day-1, which is approximately half of Dmax. Based on these predicted
225
values, two dilution rates for continuous cultivation of N. gaditana in serially connected
226
PBRs were calculated as 0.028 day-1 and 0.056 day-1, respectively. For each condition, the
227
dilution rates in the first reactor were 0.11 and 0.22 day-1, which are relatively close to
228
Dmaxoutput and Dmax, respectively.
229
3.2. Biomass production in serially connected PBRs
230
For each dilution rate, the change in biomass concentration at each reactor was
231
measured. A single chemostat flat-panel PBR with an equivalent dilution rate was used as a
232
control. For a dilution rate of 0.028 day-1, control data were unavailable because the cultures
233
could not be maintained for a sufficient duration; this system was unstable most likely
234
because the dilution rate was too low. In comparison, the dilution rates in serially connected 11
235
PBRs decreased gradually from one reactor to the next, so that the cells could adapt. In the
236
control reactor, however, an excessively low dilution rate was applied to the whole system
237
from the start. As the fresh medium was only supplied to the first reactor, biomass tended to
238
increase with reactor position (Fig. 2a). At the lower dilution rate of 0.028 day-1, dry cell
239
weight was 0.127 g L-1 at the first reactor and doubled at the second reactor. Dry cell weight
240
increased greatly between second and third reactor to 0.710 g L-1. Finally the biomass at the
241
fourth reactor was 1.110 g L-1 that are 7.74 times higher than at the initial reactor. These
242
changes were nearly identical for the faster dilution rate of 0.056 day-1. Initially, the dry cell
243
weight was 0.251 g L-1, and this increased to 0.309 g L-1 at the second reactor. In this case,
244
the cell mass increase was lower than that for the 0.028 day-1 dilution rate, although the
245
standard errors were rather large. When the dilution rate is greater, cells move more quickly
246
between reactors, and the differences in biomass accumulation become smaller than those at
247
the lower dilution rate. For this reason, the dry cell weight in the latter reactor positions was
248
lower at the greater dilution rate. At reactor 4, the dry cell weight was 29.4% greater for the
249
lower dilution rate. Therefore, a lower dilution rate induced a greater biomass accumulation
250
while remaining within the dilution range for stable operation.
251
Specific growth rates at each reactor position were calculated at low and high
252
dilution rates using Eq. (5) (Table 1). Under these conditions, the specific growth rate (µ) was
253
highest at the first reactor (0.111 and 0.222 day-1) and decreased at the second reactor (0.054
254
and 0.042 day-1). The specific growth rate increased at the third reactor (0.072 and 0.126 day-
255
1
256
specific growth rate is highly dependent on the cells’ ability to consume nutrients, and
257
nitrogen was the limiting nutrient in the present study (Bailey & Ollis, 1976). Thus, nitrate
), and then decreased to minimum values at the fourth reactor (0.040 and 0.038 day-1). The
12
258
concentrations in the medium of each reactor were also measured for both dilution rates (Fig.
259
2b). The results showed similar declines in nitrate concentration with reactor position for both
260
dilution rates. However, the tendency was somewhat different from the prediction based on
261
the calculated specific growth rates, because the specific growth rate at the second reactor
262
decreased significantly for both dilution rates (Table 1). Since nearly all nitrates were
263
consumed by the time the cells reached the third reactor, growth rates at the final reactor were
264
much lower for both dilution rates. This indicates that N. gaditana cells consumed nitrogen
265
actively at the second and third reactors, and corresponds to the greater cell division and
266
growth at these stages.
267
The performance of the serially connected PBR system was also compared to that of
268
a single PBR with the same dilution rate as the control (0.056 day-1). For the control reactor,
269
the dry cell weight was 0.718 g L-1, similar to that of the third reactor in the serially
270
connected PBR system. However, the dry cell weight was 0.858 g L-1 at the fourth reactor in
271
the serially connected PBR, 19.5 % higher than that of the control reactor. This result shows
272
enhancement of productivity through the serially connected system. All of the PBRs used in
273
this study have the characteristics of continuous stirred-tank reactors (CSTRs), with the
274
assumption of almost perfect mixing. It is known that a series of mixed reactors achieves a
275
performance closer to that of plug-flow reactors, which have a high volumetric unit
276
conversion (Schmidt, 1998). Although as an entire system, the serially connected PBRs in
277
this study had the same working volumes and feed flow rates, it was verified that the division
278
of reactor volumes into four compartments led to increased overall biomass, probably
279
because the division made the system closer to the plug-flow reactors.
280 13
281 282
3.3. Lipid production in serially connected PBRs N. gaditana typically accumulates high levels of lipids, making it a promising
283
candidate for biodiesel production (Ren & Ogden, 2014). More specifically, N. gaditana
284
accumulates neutral lipids under nitrogen limitation, and up to 38% triacylglycerol content
285
(Simionato et al., 2013). Triacylglycerols are the preferred substrate for conversion into
286
biodiesel, so their amount indicates the potential of N. gaditana as a feedstock for biodiesel
287
production (Gong & Jiang, 2011).
288
For quantification, all lipids were esterified with methanol into FAMEs, and the lipid
289
content was reported as FAMEs (Fig. 2c). The results show that FAME content tended to
290
increase with reactor position, similar to that of biomass accumulation. For the lower dilution
291
rate (0.028 day-1), the FAME content was 14.360 % of dry biomass at the first reactor, and it
292
steadily increased with reactor position. The third reactor had a FAME content of 23.127 %,
293
and the fourth reactor had a level of 27.972 %. The pattern of lipid accumulation was similar
294
at the dilution rate of 0.056 day-1; the FAME content increased from 13.056 % (first reactor),
295
to 20.383 % (second reactor), and then to 25.056 % (fourth reactor). Lipid biosynthesis in
296
microalgae is related to the ability to absorb nitrogen from the external environment
297
(Lourenco et al., 1998). A lack of nitrogen limits protein synthesis and reduces cell growth.
298
This requires cells to convert the surplus energy from light and fixed carbon into long-term
299
energy storage (lipids), rather than growth (Carpinelli et al., 2014). Many studies have
300
reported lipid accumulation under nitrogen deprivation (Griffiths et al., 2014; Liu et al., 2016;
301
Yeh & Chang, 2011). Thus, the decrease of nitrate concentration of the medium with reactor
302
position (Fig. 2b), corresponds with the increase of FAME content with reactor position. This
303
is especially so at the final reactor, in which nitrate was nearly depleted for both dilution rates, 14
304
but massive accumulation of FAMEs. In addition, as the cells did not undergo complete
305
nitrogen starvation at either dilution, further induction of lipid synthesis at the final reactor
306
can be anticipated when the dilution rate is lowered or if additional reactors are added to the
307
series.
308
The lipid content in the serially connected PBR system was also compared with that
309
of a single reactor at a dilution rate of 0.056 day-1 (Fig. 2c). In a single reactor, the FAME
310
content was 20.490 % of dry biomass, substantially lower than the 25.056 % in the fourth
311
reactor of the serially connected PBR system at the same dilution rate. This demonstrates that
312
the serially connected PBR system has further benefits in terms of lipid production, in
313
addition to increased biomass.
314
3.4. Biomass and FAME productivities in serially connected PBRs
315
Next, the biomass and FAME productivities of N. gaditana were calculated based on
316
the results acquired for different dilution rates to verify the overall performance of the serially
317
connected PBR system (Fig. S2). Biomass productivity was calculated as dry cell weight
318
multiplied by dilution rate. In the serially connected PBRs, a high dilution rate (0.056 day-1 )
319
led to 54.8 % greater biomass productivity than a low dilution rate (0.028 day-1). The two
320
factors that affect biomass productivity are cell density and dilution rate. Cell density is
321
dependent on biological factors, but dilution rate is an engineering factor. As shown in Fig. 2a,
322
an increased dilution rate led to a decreased cell density. This indicates that the dilution rate
323
was a more important factor in determining the biomass productivity. Compared to the
324
control reactor, the serially connected PBR system had 20.0 % greater biomass productivity
325
(0.048 g L-1 day-1 vs. 0.040 g L-1 day-1) indicating that the serially connected PBR system has
326
a better overall performance in biomass productivity. 15
327
The FAME content is a ratio of esterifiable lipids within the cells. Thus, FAME
328
productivity can be calculated by multiplying FAME content and biomass productivity.
329
FAME productivity is a direct measure of the system’s ability to produce biodiesel, and is the
330
most important measure in microalgal cultivation for biofuels (Griffiths & Harrison, 2009).
331
Similar to biomass productivity, the dilution rate was also a major factor affecting FAME
332
productivity (Fig. S2b). The results showed that the FAME content at high dilution was
333
25.056 %, lower than that at low dilution (27.972 %) (Fig. 2c). However, FAME productivity
334
at a dilution rate of 0.056 day-1 was 11.940 mg L-1 day-1, but it was only 8.625 mg L-1 day-1 at
335
a dilution rate of 0.028 day-1. This result clearly shows that dilution rate has a substantial
336
influence on FAME productivity. Consequently when an microalgal cultivation system is
337
operated in continuous mode, it is critical to identify the proper dilution rate to improve
338
overall production quality.
339
The advantages of a serially connected PBR system were further highlighted by
340
comparing with a single reactor system. The serially connected PBRs had 46.1 % greater
341
FAME productivity than the control reactor at a dilution rate of 0.056 day-1 (Fig. S2b). This
342
difference could be attributed to the increased cell mass and FAME content; the dry cell
343
weight in the serially connected system was 19.5 % higher, and FAME content was 22.3 %
344
higher than that of the single reactor system. This significant improvement in biodiesel
345
productivity, following a simple modification of a more traditional operation, is highly
346
encouraging.
347
In addition to producing greater biomass and lipid productivities, the chemostat
348
serially connected PBR system has several additional advantages over the conventional single
349
reactor PBR in terms of process operation. In particular, the serially connected system is 16
350
divided into several independent environments (4 in this study), so it is possible to manage a
351
sudden culture crash without losing the entire culture volume. Thus, when a crash occurs in
352
one of the units, the operator can protect the other units by simply detaching the affected unit.
353
This allows the unaffected units to operate normally, namely, saves a tremendous amount of
354
effort and cost (Smith & Crews, 2014; Yun et al., 2016). Another unique feature of the
355
serially connected PBR system is its wide adaptability. It is possible to independently control
356
every unit, so different culture conditions can be applied to different units. Thus, it may be
357
possible, for example, to enhance overall productivity by using different illumination
358
regimens for different reactors (Imaizumi et al., 2016). The novel serially connected PBR
359
system has special characteristics. Each unit functions as an independent environment, but the
360
overall performance of the system is affected by their interdependence. Thus it can be
361
anticipated that the serially connected PBR system has great potential for improving the
362
overall quality of microalgal cultivation processes.
363 364 365 366 367 368 369 370
17
371 372
4. Conclusions In this study, a novel microalgal cultivation process was developed by serially
373
connecting four PBRs. The cultivation with the low dilution rate (0.028 day-1) led to 1.110 g
374
L-1 of biomass and 27.972 % of FAME production that were 29.4 % and 11.6 % greater than
375
those produced with a high dilution rate (0.056 day-1), respectively. Moreover, cells grown
376
under the serially connected PBRs showed 46.1 % increased lipid productivity compared to a
377
conventional PBR. These results suggest that process based cultivation system combined with
378
the serially connected PBR can be applied for effective biodiesel production in microalgal
379
cultivation field.
380 381
Acknowledgements
382
This work was supported by the Advanced Biomass R&D Center (ABC) of Global Frontier
383
Project funded by the Ministry of Science, ICT, and Future Planning (ABC- 2010-0029728)
384
18
385
5. References
386
1. Ahmad, A., Yasin, N.M., Derek, C., Lim, J. 2011. Microalgae as a sustainable energy
387 388 389 390 391
source for biodiesel production: a review. Renew. Sust. Energ. Rev. 15, 584-593. 2. Bailey, J.E., Ollis, D.F. 1976. Biochemical engineering fundamentals. Chemical Engineering Education. 3. Borowitzka, M.A. 1992. Algal biotechnology products and processes—matching science and economics. J. Appl. Phycol. 4, 267-279.
392
4. Carpinelli, E.C., Telatin, A., Vitulo, N., Forcato, C., D’Angelo, M., Schiavon, R., Vezzi, A.,
393
Giacometti, G.M., Morosinotto, T., Valle, G. 2014. Chromosome scale genome
394
assembly and transcriptome profiling of Nannochloropsis gaditana in nitrogen
395
depletion. Mol. Plant. 7, 323-335.
396
5. Chen, C.Y., Yeh, K.L., Aisyah, R., Lee, D.J., Chang, J.S. 2011. Cultivation,
397
photobioreactor design and harvesting of microalgae for biodiesel production: A
398
critical review. Bioresource Technol. 102, 71-81.
399
6. dos Santos, R.R., Kunigami, C.N., Aranda, D.A.G., Teixeira, C. 2016. Assessment of
400
triacylglycerol content in Chlorella vulgaris cultivated in a two-stage process.
401
Biomass. Bioenerg. 92, 55-60.
402
7. Fernandes, B.D., Mota, A., Teixeira, J.A., Vicente, A.A. 2015. Continuous cultivation of
403
photosynthetic microorganisms: Approaches, applications and future trends.
404
Biotechnol. Adv. 33, 1228-1245.
405 406 407
8. Folch, J., Lees, M., Sloane-Stanley, G. 1957. A simple method for the isolation and purification of total lipids from animal tissues. J. Biol. Chem. 226, 497-509. 9. Gong, Y.M., Jiang, M.L. 2011. Biodiesel production with microalgae as feedstock: from 19
408 409 410
strains to biodiesel. Biotechnol. Lett. 33, 1269-1284. 10. Griffiths, M.J., Harrison, S.T.L. 2009. Lipid productivity as a key characteristic for choosing algal species for biodiesel production. J. Appl. Phycol. 21, 493-507.
411
11. Griffiths, M.J., van Hille, R.P., Harrison, S.T.L. 2014. The effect of nitrogen limitation on
412
lipid productivity and cell composition in Chlorella vulgaris. Appl. Microbiol. Biot.
413
98, 2345-2356.
414 415
12. Guillard, R., Ryther, J. 1962. Studies of marine planktonic diatoms. Cyclotella nana, 229239.
416
13. Ho, S.H., Chen, C.Y., Chang, J.S. 2012. Effect of light intensity and nitrogen starvation
417
on CO2 fixation and lipid/carbohydrate production of an indigenous microalga
418
Scenedesmus obliquus CNW-N. Bioresource Technol. 113, 244-252.
419
14. Ho, S.-H., Ye, X., Hasunuma, T., Chang, J.-S., Kondo, A. 2014. Perspectives on
420
engineering strategies for improving biofuel production from microalgae—a critical
421
review. Biotechnol. Adv. 32, 1448-1459.
422
15. Imaizumi, Y., Nagao, N., Yusoff, F.M., Kurosawa, N., Kawasaki, N., Toda, T. 2016.
423
Lumostatic operation controlled by the optimum light intensity per dry weight for the
424
effective production of Chlorella zofingiensis in the high cell density continuous
425
culture. Algal Res. 20, 110-117.
426 427
16. Klok, A.J., Martens, D.E., Wijffels, R.H., Lamers, P.P. 2013. Simultaneous growth and neutral lipid accumulation in microalgae. Bioresource technol. 134, 233-243.
428
17. Liu, T., Li, Y., Liu, F., Wang, C. 2016. The enhanced lipid accumulation in oleaginous
429
microalga by the potential continuous nitrogen-limitation (CNL) strategy. Bioresource
430
Technol. 203, 150-159.
431 20
432
18. Martin, L.A., Popovich, C.A., Martinez, A.M., Damiani, M.C., Leonardi, P.I. 2016. Oil
433
assessment of Halamphora coffeaeformis diatom growing in a hybrid two-stage
434
system for biodiesel production. Renew. Energ. 92, 127-135.
435
19. Monod, J. 1949. The Growth of Bacterial Cultures.
436
20. Ren, M., Ogden, K. 2014. Cultivation of Nannochloropsis gaditana on Mixtures of
437
Nitrogen Sources. Environ. Prog. Sustain. Energy. 33, 551-555.
438
21. Rodolfi, L., Zittelli, G.C., Bassi, N., Padovani, G., Biondi, N., Bonini, G., Tredici, M.R.
439
2009. Microalgae for Oil: Strain Selection, Induction of Lipid Synthesis and Outdoor
440
Mass Cultivation in a Low-Cost Photobioreactor. Biotechnol. Bioeng. 102, 100-112.
441
22. Roessler, P.G. 1990. Environmental control of glycerolipid metabolism in microalgae:
442
commercial implications and future research directions. J. Phycol. 26, 393-399.
443
23. Schmidt, L.D. 1998. The engineering of chemical reactions. Oxford University Press,
444
USA.
445
24. Simionato, D., Block, M.A., La Rocca, N., Jouhet, J., Maréchal, E., Finazzi, G.,
446
Morosinotto, T. 2013. The response of Nannochloropsis gaditana to nitrogen
447
starvation includes de novo biosynthesis of triacylglycerols, a decrease of chloroplast
448
galactolipids, and reorganization of the photosynthetic apparatus. Eukaryot. Cell. 12,
449
665-676.
450 451 452 453
25. Singh, N.K., Dhar, D.W. 2011. Microalgae as second generation biofuel. A review. Agron. Sustain. Dev. 31, 605-629. 26. Smith, V.H., Crews, T. 2014. Applying ecological principles of crop cultivation in largescale algal biomass production. Algal Res. 4, 23-34.
454
27. Su, C.-H., Chien, L.-J., Gomes, J., Lin, Y.-S., Yu, Y.-K., Liou, J.-S., Syu, R.-J. 2011.
455
Factors affecting lipid accumulation by Nannochloropsis oculata in a two-stage 21
456 457 458
cultivation process. J. Appl. Phycol. 23, 903-908. 28. Suali, E., Sarbatly, R. 2012. Conversion of microalgae to biofuel. Renew. Sust. Energ. Rev. 16, 4316-4342.
459
29. Sung, M.G., Shin, W.S., Kim, W., Kwon, J.H., Yang, J.W. 2014. Effect of shear stress on
460
the growth of continuous culture of Synechocystis PCC 6803 in a flat-panel
461
photobioreactor. Korean J. Chem. Eng. 31, 1233-1236.
462 463
30. Tang, H.Y., Chen, M., Ng, K.Y.S., Salley, S.O. 2012. Continuous microalgae cultivation in a photobioreactor. Biotechnol. Bioeng. 109, 2468-2474.
464
31. Yeh, K.L., Chang, J.S. 2011. Nitrogen starvation strategies and photobioreactor design for
465
enhancing lipid production of a newly isolated microalga Chlorella vulgaris ESP-31:
466
Implications for biofuels. Biotechnol. J. 6, 1358-1366.
467
32. Yun, J.-H., Smith, V.H., La, H.-J., Keun Chang, Y. 2016. Towards managing food-web
468
structure and algal crop diversity in industrial-scale algal biomass production. Curr.
469
Biotechnol. 5, 118-129.
470
33. Zhang, D., Xue, S., Sun, Z., Liang, K., Wang, L., Zhang, Q., Cong, W. 2014.
471
Investigation of continuous-batch mode of two-stage culture of Nannochloropsis sp
472
for lipid production. Bioproc. Biosyst. Eng. 37, 2073-2082.
473 474
34. Zhu, J., Rong, J., Zong, B. 2013. Factors in mass cultivation of microalgae for biodiesel. Chinese J. Catal. 34, 80-100.
475 476
22
477
Figure legends
478 479
Figure 1. Changes in N. gaditana biomass (OD750nm) and nitrate concentration in a single
480
flat-panel photobioreactor over 10 days.
481 482
Figure 2. Dry weight of N. gaditana (a), nitrate concentration in the medium (b), and fatty
483
acid methyl ester content of N. gaditana (c) at each photobioreactor position. Control
484
indicates a single chemostat photobioreactor with the same dilution rate.
485 486 487 488 489 490 491 492
23
493
Figures
494
Figure 1.
495 496 497 498 499 500 501 502 24
503
Figure 2.
504 505
25
506
Tables
507 508
Table 1. Specific growth rate (µ, day-1) in each reactor at 2 different dilution rates. Control represents a single reactor at the designated dilution rate. Dilution rate
Control
Reactor 1
Reactor 2
Reactor 3
Reactor 4
0.028 (day-1)
N/A
0.111
0.054
0.072
0.040
0.056 (day-1)
0.056
0.222
0.042
0.126
0.038
509 510 511 512 513 514
26
515
GRAPHICAL ABSTRACT
516
517 518 519 520 521
27
522
Highlights
523
Microalgae were cultivated with four photobioreactors connected in series.
524
The final reactor has resulted in a 7.74-fold increased biomass.
525
Lipids accumulated along the reactor positions and doubled at the final reactor.
526
Connected PBR system led to 46 % increased lipid productivity compared to control.
527
28
S0960-8524(16)31778-3 http://dx.doi.org/10.1016/j.biortech.2016.12.100 BITE 17476
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
28 October 2016 26 December 2016 27 December 2016
Please cite this article as: Sung, M-G., Lee, B., Woong Kim, C., Nam, K., Keun Chang, Y., Enhancement of Lipid Productivity by Adopting Multi-stage Continuous Cultivation Strategy in Nannochloropsis gaditana, Bioresource Technology (2016), doi: http://dx.doi.org/10.1016/j.biortech.2016.12.100
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1
Enhancement of Lipid Productivity by Adopting Multi-stage Continuous Cultivation
2
Strategy in Nannochloropsis gaditana
3
4
Min-Gyu Sung1†, Bongsoo Lee1†, Chul Woong Kim2, Kibok Nam1, Yong Keun Chang1,3*
5
1
6
gu, Daejeon 305-701, Republic of Korea
7
2
8
Korea
9
3
10
Department of Chemical and Biomolecular Engineering, KAIST, 291 Daehak-ro, Yuseong-
Corporate R&D Research Park, LG Chem, 188 Munji-ro, Yeseong-gu, Daejeon, Republic of
Advanced Biomass R&D Center, #2502 Building W1-3, KAIST, 291 Daehak-ro, Yuseong-
gu, Daejeon 305-701, Republic of Korea
11 12
Corresponding Author:
13
Yong Keun Chang,
14
Tel: +82-42-350-3927, Fax: +82-42-350-3910, [email protected]
15
†Min-Gyu Sung and Bongsoo Lee contributed equally to this work
16
Keywords: Microalgae, Photobioreactor, Stage Cultivation, Chemostat, Biodiesel
17 18 19 1
20
Abstract
21
In the present study, a novel process-based cultivation system was designed to improve lipid
22
productivity of Nannochloropsis gaditana, an oleaginous microalga that has high potential
23
for biofuel production. Specifically, four flat-panel photobioreactors were connected in series,
24
and this system was subjected to continuous chemostat cultivation by feeding fresh medium
25
to the first reactor at dilution rates of 0.028 and 0.056 day-1, which were determined based on
26
Monod kinetics. The results show that the serially connected photobioreactor system
27
achieved 20.0% higher biomass productivity and 46.1% higher fatty acid methyl ester
28
(FAME) productivity than a conventional single photobioreactor with equivalent dilution rate.
29
These results suggest that a process-based approach using serially connected photobioreactors
30
for microalgal cultivation can improve the productivity of lipids that can be used for biofuel
31
production.
32 33 34 35 36 37 38 39 40 2
41 42
1. Introduction There are growing concerns about global warming and climate change because of the
43
continuing use of petroleum-based fuels. In addition, limited oil deposits have increased the
44
energy crisis worldwide (Ho et al., 2014). In these regards, biomass feedstocks for renewable
45
energy production are an important alternative energy source that can replace fossil fuels.
46
Among the various potential alternative energy resources, microalgae have been spotlighted
47
because they have many advantageous traits for biofuel production compared to crop-based
48
biofuels and lignocellulosic biomass. A major advantage is that microalgae grow rapidly and
49
consuming CO2 for photosynthesis. Furthermore, it has been reported that microalgae can
50
produce up to 25-fold more lipids than that of conventional crops or land plants (Ahmad et al.,
51
2011). This suggests microalgae accumulate large amounts of lipids that can be converted
52
into biodiesel (Chen et al., 2011).
53
Microalgae have many advantages as energy resources, but many obstacles must be
54
overcome for commercialization of a microalgae-based biofuel production system. Consistent
55
with this necessity, it has been reported that microalgae being cultivated will ultimately affect
56
every step of the microalgae to biofuels supply chain (National Algal Biofuels Technology
57
Roadmap of US DOE) due to their diverse characteristics. In other words, cultivation of
58
microalgae with high biomass and lipid yields is crucial for successful microalgae-derived
59
biofuel production. One of the major challenges is that microalgae normally accumulate
60
small amounts of lipids under nutrient replete growth conditions, whereas efficient biofuel
61
production requires biomass with high levels of lipids (Gong & Jiang, 2011; Singh & Dhar,
62
2011). To increase the lipid content of microalgae, some researchers have introduced
63
additional strategies such as nitrogen limitation and two-stage cultivation during the 3
64 65
cultivation process (Zheng et al., 2012; Su et al, 2011; Rodolfi et al., 2009; Roessler, 1990). It should be noted that nitrogen starvation sometimes induces starch accumulation in
66
particular species (Ho et al, 2012). However, nitrogen limitation is still one of the most
67
common methods used to induce higher lipid production in many microalgae strains
68
(Griffiths et al., 2014; Liu et al., 2016; Yeh & Chang, 2011). In N. gaditana, when the
69
nitrogen supply is limited, intracellular nitrogen redistribution occurs, and this induces lipid
70
biosynthesis (Carpinelli et al., 2014). Therefore, prolonged exposure to nitrogen-limited
71
conditions results in higher neutral lipid content in N. gaditana (Simionato et al., 2013). This
72
method for lipid induction, however, is achieved by exposing the cells to a stressful condition,
73
and this does not support rapid growth. Consequently, this method leads to decreases in
74
overall biomass productivity, and microalgae lose their inherent advantage as a fast growing
75
source of biomass for biofuel production (Borowitzka, 1992).
76
Many studies have attempted to solve the problem of growth cessation during the
77
lipid induction step. One common solution proposed is the use of a two-stage cultivation
78
system, where an additional lipid induction step is introduced at the later stage of cultivation,
79
so that cells accumulate more lipids than under normal conditions (dos Santos et al., 2016;
80
Suali & Sarbatly, 2012). In the two-stage cultivation process, microalgae are first cultured on
81
a nutrient-rich environment for fast growth. Then, the fully grown cells are subjected to
82
nutrient deprivation to induce lipid accumulation (Martin et al., 2016; Su et al., 2011; Suali &
83
Sarbatly, 2012).
84
Although many studies have applied multi-stage cultivation methods to increase lipid
85
productivity in microalgae, only a few examined this method using continuous cultivation
86
(Klok et al., 2013; Zhang et al., 2014). Continuous cultivation has many benefits compared to 4
87
batch or semi-batch systems. Unlike batch cultivation, continuous cultivation ensures that the
88
operation conditions for growth are maintained at precise levels, determined by the purpose
89
of cultivation, and this provides a stable environment for the microalgae (Tang et al., 2012).
90
In addition, continuous cultivation greatly reduces the labor needed for cleaning and
91
sterilization of the photobioreactors (PBRs) between cultivation batches (Fernandes et al.,
92
2015).
93
In the present study, a new continuous cultivation process was introduced to produce
94
a concentrated microalgal biomass with high lipid content. The process consists of several
95
photobioreactors, with each functioning as an independent environment, that are serially
96
connected so there is simultaneous an accumulation of biomass and lipids in the final reactor.
97
The process is operated in a chemostat, and fresh medium is supplied through the first reactor.
98
In order to investigate the performance of process-based cultivation system, biomass and
99
lipid content were analyzed in each reactor position, and overall lipid productivity was
100
compared to traditional photobioreactor based cultivation systems.
101 102 103 104 105 106 107
5
108
2. Material & Methods
109
2.1. Medium and culture conditions
110
The marine microalga Nannochloropsis gaditana CCMP526 from the National
111
Center for Marine Algae and Microbiota (Maine, USA) was used in this study. The strain was
112
maintained in sterile modified f/2 medium (Guillard & Ryther, 1962) with the following
113
composition: 30 g L-1 sea salts, 375 mg L-1 NaNO3, 5 mg L-1 NaH2PO4·9H2O, 3.15 mg L-1
114
FeCl3·6H2O, 4.36 mg L-1 Na2EDTA·2H2O, 9.8 µg L-1 CuSO4·5H2O, 6.3 µg L-1
115
Na2MoO4·2H2O, 22 µg L-1 ZnSO4·7H2O, 10 µg L-1 CoCl2·6H2O, 180 µg L-1 MnCl2·4H2O, 0.5
116
µg L-1 vitamin B12, 0.5 µg L-1 biotin, and 100 µg L-1 thiamine hydrochloride. The seed culture
117
for photobioreactor cultivation was grown in a culture flask with 300 ml of modified f/2
118
medium at 100 µmol photons m-2 s-1 and 25 °C.
119
2.2. Photobioreactor set-up and determination of dilution rate
120
Four flat-panel PBRs with identical designs were connected in series for cultivation
121
(Fig. S1). PBR frames were made of polyvinyl chloride (PVC) with a width, height and
122
thickness of 220, 335 and 30 mm, respectively, and the working volume was 2.25 L for each
123
reactor. Transparent polycarbonate sheets were used to transmit the LED illumination with a
124
light-path of 30 mm. Gas (3% CO2, v/v) was supplied through a bubble tube at the bottom of
125
each PBR. Sufficient mixing was achieved through the gas bubbles, so the system was
126
assumed to be a continuous stirred-tank reactor. White LED panels supplied 100 µmol
127
photons m-2 s-1 intensity of light to each reactor.
128 129
For a chemostat operation of serially connected PBRs, fresh modified f/2 medium was supplied to the first reactor with a peristaltic pump (Watson-Marlow, UK). The working 6
130
volume in each reactor was inherently maintained through an overflow channel of reactors
131
connected in series (Fig. S1), and this resulted in equivalent feed flow rates in every reactor.
132
Consequently, the dilution rate, which is the feed flow rate divided by the culture volume,
133
became 1/n of the first reactor at the n-th reactor because the same volume of culture was
134
added along the reactor positions where the feed flow rate was constantly maintained.
135
Biomass samples were collected from each bioreactor for the experimental analysis.
136
Dilution rates in chemostat serially connected PBRs were determined by following
137
steps. In a continuous cultivation process with one bioreactor, the specific growth rate (µ) is
138
related to dilution rate (D) by the following mass balance equation (Sung et al., 2014; Tang et
139
al., 2012):
140
= −
(1)
141
where X is biomass concentration and t is time. At steady state, μ = D, so that specific
142
growth can be determined from the dilution rate. In addition, D should not exceed the
143
maximum specific growth rate to prevent washout (Bailey & Ollis, 1976), as described by an
144
equation that follows Monod kinetics (Monod, 1949):
145
=
146
where µmax is the maximum specific growth rate, sf is the substrate concentration at the feed
147
stream, and Ks is a half-saturation constant. Monod kinetics also predicts a dilution rate that
148
produces theoretically maximal cell output (Bailey & Ollis, 1976):
149
= 1 −
<
(2)
(3)
7
150
To determine the dilution rates for the operation of serially connected PBRs, the
151
maximum specific growth rate of N. gaditana strain must be verified. Thus, batch cultivation
152
in a flat-panel PBR, using the same conditions as the serially connected PBR system, was
153
used to determine the maximum specific growth rate.
154
2.3. Growth measurement and specific growth rate calculation
155
In the batch cultivation in a flat-panel PBR, the optical density (OD) of the
156
microalgae suspension was measured at 750 nm with a uv-spectrophotometer (Shimadzu,
157
Japan) to monitor cell growth. Cellulose nitrate membrane filters with a 0.45 µm pore size
158
(Whatman, USA) were used for the dry cell weight measurement in the serially connected
159
PBRs. Filter papers were pre-dried in an oven at 80 ℃, then microalgae suspensions were
160
passed through using a vacuum pump. Filtered cells were dried at 80 ℃ overnight for
161
calculation of dry cell weight.
162
For multiple connected continuous reactors with constant volume, the mass balance
163
of each reactor can be described as (Bailey & Ollis, 1976; Monod, 1949):
164
165
where Xi and µi are biomass concentration and specific growth rate in i-th reactor,
166
respectively. At steady state,
167
estimated from Eq. 2:
168
=
169
2.4. Nitrate concentration measurement
= !" + −
(4)
$% $&
= 0 and the specific growth rate of i-th reactor can be
( ! )*
(5)
8
170
Microalgae suspensions were centrifuged at 7000 rpm for 10 min. (Combi 514 R,
171
Hanil Scientific Inc., Korea). The supernatant was passed through a 0.2 µm syringe filter, and
172
the nitrate concentration was quantified with ion chromatography (883 Basic IC plus,
173
Metrohm, Switzerland). An anion column Metrosep A Supp 5 was used to analyze the nitrate
174
(NO3-) ions remaining in the culture medium. The eluent, which consisted of 3.2 mM Na2CO3
175
and 1 mM NaHCO3, was supplied at a flow rate of 0.7 ml min-1 into the column for the
176
analysis.
177
2.5. Fatty acid methyl ester analysis
178
Microalgae suspensions were centrifuged at 7000 rpm for 10 min. The pellets were
179
washed twice with distilled water, and then stored at -70 ℃ for 24 h. Frozen cells were dried
180
in a freeze dryer (Ilshin, Republic of Korea) for up to 4 days. Dried cells were ground into
181
powder, treated with chloroform/methanol (2:1, v/v), and lipids were determined using the
182
modified Folch method (Folch et al., 1957). Methanol and sulfuric acid were added, and then
183
incubated at 100 ℃ for 20 min for fatty acid methyl ester (FAME) conversion.
184
Heptadecanoic acid was used as an internal standard. The organic phase was separated by 0.3
185
M NaOH, then recovered with centrifugation at 4000 rpm for 10 min. FAMEs were measured
186
by gas chromatography (HP 6890, Agilent, USA) with a flame ionized detector. FAME
187
content was calculated as: FAME content %, w/9 =
;
9:;<ℎ> ?@ ABCD ?E>F;G:H F@>:I >IFGJ:J>:I; 9:;<ℎ> ?@ L;I?FM
K F > ; ? G
× 100 188 9
189
3. Results & Discussion
190
3.1. Determination of dilution rate
191
Initially batch cultivation of N. gaditana was implemented in flat-panel PBRs in
192
duplicate after setting the initial OD750 nm to 0.2, and then, the growth was monitored by
193
continuous measurement at OD750 nm. The cells entered the exponential growth phase after 3
194
days, and a high growth rate was maintained for about 4 days (Fig. 1). The cells subsequently
195
entered the stationary phase on day 8. It is essential to monitor the levels of the limiting
196
nutrient to determine the dilution rate based on Monod kinetics (Monod, 1949). In microalgal
197
cultivation environments, nitrogen is commonly the major limiting nutrient for growth (Zhu
198
et al., 2013). Thus the nitrate concentration was measured during the batch cultivation of N.
199
gaditana in flat-panel PBRs. The results show that the consumption of nitrate closely
200
correlated with cell growth (Fig. 1). In particular, N. gaditana cells consumed most of the
201
nitrate during the exponential growth phase, and the nitrate was completely consumed at day
202
10, when cells were in the stationary phase.
203
Based on these results, the kinetic parameters were calculated using the Monod
204
equation. The maximum specific growth rate of 0.278 day-1 was determined at the
205
exponential growth stage (between day 2 and 6). This value and Eq. (2) was used to
206
determine the dilution rate that should not be exceeded. The sf and Ks values were calculated
207
based on elemental nitrogen. The nitrate concentration in the fresh medium was 375 mg L-1,
208
so the concentration of elemental nitrogen in the feed stream was 273.529 mg L-1. The half-
209
saturation constant (Ks) is 65.141 mg L-1; this is simply the concentration of the limiting
210
nutrient when the specific growth rate is half of the maximum.
211
When the dilution rate (D) exceeds the maximum dilution rate (Dmax), then it exceeds 10
212
the maximum growth rate of the cells. At this point, continuous washout of cells occurs, and
213
the system cannot be maintained (Bailey & Ollis, 1976). Dmax was estimated from the
214
parameters obtained from the preliminary batch experiment, as given in Eq. (2). Based on the
215
maximum growth rate (µ max), Dmax was calculated as 0.224 day-1. Thus, for the continuous
216
operation of serially connected PBRs, the dilution rate should not exceed 0.224 day-1. For the
217
PBR system, this upper limit was only applied to the first reactor, not for all 4 reactors,
218
because fresh medium is only supplied to the first reactor. As the culture passes between
219
reactors, the dilution rate at each reactor decreases, because the flow rate remains consistent
220
as the volume increases. As a consequence, the dilution rate at the fourth reactor is 25% (one-
221
fourth) of that in the first reactor.
222
In addition, the theoretical dilution rate at which the biomass production is
223
maximized (Dmaxoutput) could also be calculated (Bailey & Ollis, 1976) with Eq. (3). Dmaxoutput
224
was calculated as 0.156 day-1, which is approximately half of Dmax. Based on these predicted
225
values, two dilution rates for continuous cultivation of N. gaditana in serially connected
226
PBRs were calculated as 0.028 day-1 and 0.056 day-1, respectively. For each condition, the
227
dilution rates in the first reactor were 0.11 and 0.22 day-1, which are relatively close to
228
Dmaxoutput and Dmax, respectively.
229
3.2. Biomass production in serially connected PBRs
230
For each dilution rate, the change in biomass concentration at each reactor was
231
measured. A single chemostat flat-panel PBR with an equivalent dilution rate was used as a
232
control. For a dilution rate of 0.028 day-1, control data were unavailable because the cultures
233
could not be maintained for a sufficient duration; this system was unstable most likely
234
because the dilution rate was too low. In comparison, the dilution rates in serially connected 11
235
PBRs decreased gradually from one reactor to the next, so that the cells could adapt. In the
236
control reactor, however, an excessively low dilution rate was applied to the whole system
237
from the start. As the fresh medium was only supplied to the first reactor, biomass tended to
238
increase with reactor position (Fig. 2a). At the lower dilution rate of 0.028 day-1, dry cell
239
weight was 0.127 g L-1 at the first reactor and doubled at the second reactor. Dry cell weight
240
increased greatly between second and third reactor to 0.710 g L-1. Finally the biomass at the
241
fourth reactor was 1.110 g L-1 that are 7.74 times higher than at the initial reactor. These
242
changes were nearly identical for the faster dilution rate of 0.056 day-1. Initially, the dry cell
243
weight was 0.251 g L-1, and this increased to 0.309 g L-1 at the second reactor. In this case,
244
the cell mass increase was lower than that for the 0.028 day-1 dilution rate, although the
245
standard errors were rather large. When the dilution rate is greater, cells move more quickly
246
between reactors, and the differences in biomass accumulation become smaller than those at
247
the lower dilution rate. For this reason, the dry cell weight in the latter reactor positions was
248
lower at the greater dilution rate. At reactor 4, the dry cell weight was 29.4% greater for the
249
lower dilution rate. Therefore, a lower dilution rate induced a greater biomass accumulation
250
while remaining within the dilution range for stable operation.
251
Specific growth rates at each reactor position were calculated at low and high
252
dilution rates using Eq. (5) (Table 1). Under these conditions, the specific growth rate (µ) was
253
highest at the first reactor (0.111 and 0.222 day-1) and decreased at the second reactor (0.054
254
and 0.042 day-1). The specific growth rate increased at the third reactor (0.072 and 0.126 day-
255
1
256
specific growth rate is highly dependent on the cells’ ability to consume nutrients, and
257
nitrogen was the limiting nutrient in the present study (Bailey & Ollis, 1976). Thus, nitrate
), and then decreased to minimum values at the fourth reactor (0.040 and 0.038 day-1). The
12
258
concentrations in the medium of each reactor were also measured for both dilution rates (Fig.
259
2b). The results showed similar declines in nitrate concentration with reactor position for both
260
dilution rates. However, the tendency was somewhat different from the prediction based on
261
the calculated specific growth rates, because the specific growth rate at the second reactor
262
decreased significantly for both dilution rates (Table 1). Since nearly all nitrates were
263
consumed by the time the cells reached the third reactor, growth rates at the final reactor were
264
much lower for both dilution rates. This indicates that N. gaditana cells consumed nitrogen
265
actively at the second and third reactors, and corresponds to the greater cell division and
266
growth at these stages.
267
The performance of the serially connected PBR system was also compared to that of
268
a single PBR with the same dilution rate as the control (0.056 day-1). For the control reactor,
269
the dry cell weight was 0.718 g L-1, similar to that of the third reactor in the serially
270
connected PBR system. However, the dry cell weight was 0.858 g L-1 at the fourth reactor in
271
the serially connected PBR, 19.5 % higher than that of the control reactor. This result shows
272
enhancement of productivity through the serially connected system. All of the PBRs used in
273
this study have the characteristics of continuous stirred-tank reactors (CSTRs), with the
274
assumption of almost perfect mixing. It is known that a series of mixed reactors achieves a
275
performance closer to that of plug-flow reactors, which have a high volumetric unit
276
conversion (Schmidt, 1998). Although as an entire system, the serially connected PBRs in
277
this study had the same working volumes and feed flow rates, it was verified that the division
278
of reactor volumes into four compartments led to increased overall biomass, probably
279
because the division made the system closer to the plug-flow reactors.
280 13
281 282
3.3. Lipid production in serially connected PBRs N. gaditana typically accumulates high levels of lipids, making it a promising
283
candidate for biodiesel production (Ren & Ogden, 2014). More specifically, N. gaditana
284
accumulates neutral lipids under nitrogen limitation, and up to 38% triacylglycerol content
285
(Simionato et al., 2013). Triacylglycerols are the preferred substrate for conversion into
286
biodiesel, so their amount indicates the potential of N. gaditana as a feedstock for biodiesel
287
production (Gong & Jiang, 2011).
288
For quantification, all lipids were esterified with methanol into FAMEs, and the lipid
289
content was reported as FAMEs (Fig. 2c). The results show that FAME content tended to
290
increase with reactor position, similar to that of biomass accumulation. For the lower dilution
291
rate (0.028 day-1), the FAME content was 14.360 % of dry biomass at the first reactor, and it
292
steadily increased with reactor position. The third reactor had a FAME content of 23.127 %,
293
and the fourth reactor had a level of 27.972 %. The pattern of lipid accumulation was similar
294
at the dilution rate of 0.056 day-1; the FAME content increased from 13.056 % (first reactor),
295
to 20.383 % (second reactor), and then to 25.056 % (fourth reactor). Lipid biosynthesis in
296
microalgae is related to the ability to absorb nitrogen from the external environment
297
(Lourenco et al., 1998). A lack of nitrogen limits protein synthesis and reduces cell growth.
298
This requires cells to convert the surplus energy from light and fixed carbon into long-term
299
energy storage (lipids), rather than growth (Carpinelli et al., 2014). Many studies have
300
reported lipid accumulation under nitrogen deprivation (Griffiths et al., 2014; Liu et al., 2016;
301
Yeh & Chang, 2011). Thus, the decrease of nitrate concentration of the medium with reactor
302
position (Fig. 2b), corresponds with the increase of FAME content with reactor position. This
303
is especially so at the final reactor, in which nitrate was nearly depleted for both dilution rates, 14
304
but massive accumulation of FAMEs. In addition, as the cells did not undergo complete
305
nitrogen starvation at either dilution, further induction of lipid synthesis at the final reactor
306
can be anticipated when the dilution rate is lowered or if additional reactors are added to the
307
series.
308
The lipid content in the serially connected PBR system was also compared with that
309
of a single reactor at a dilution rate of 0.056 day-1 (Fig. 2c). In a single reactor, the FAME
310
content was 20.490 % of dry biomass, substantially lower than the 25.056 % in the fourth
311
reactor of the serially connected PBR system at the same dilution rate. This demonstrates that
312
the serially connected PBR system has further benefits in terms of lipid production, in
313
addition to increased biomass.
314
3.4. Biomass and FAME productivities in serially connected PBRs
315
Next, the biomass and FAME productivities of N. gaditana were calculated based on
316
the results acquired for different dilution rates to verify the overall performance of the serially
317
connected PBR system (Fig. S2). Biomass productivity was calculated as dry cell weight
318
multiplied by dilution rate. In the serially connected PBRs, a high dilution rate (0.056 day-1 )
319
led to 54.8 % greater biomass productivity than a low dilution rate (0.028 day-1). The two
320
factors that affect biomass productivity are cell density and dilution rate. Cell density is
321
dependent on biological factors, but dilution rate is an engineering factor. As shown in Fig. 2a,
322
an increased dilution rate led to a decreased cell density. This indicates that the dilution rate
323
was a more important factor in determining the biomass productivity. Compared to the
324
control reactor, the serially connected PBR system had 20.0 % greater biomass productivity
325
(0.048 g L-1 day-1 vs. 0.040 g L-1 day-1) indicating that the serially connected PBR system has
326
a better overall performance in biomass productivity. 15
327
The FAME content is a ratio of esterifiable lipids within the cells. Thus, FAME
328
productivity can be calculated by multiplying FAME content and biomass productivity.
329
FAME productivity is a direct measure of the system’s ability to produce biodiesel, and is the
330
most important measure in microalgal cultivation for biofuels (Griffiths & Harrison, 2009).
331
Similar to biomass productivity, the dilution rate was also a major factor affecting FAME
332
productivity (Fig. S2b). The results showed that the FAME content at high dilution was
333
25.056 %, lower than that at low dilution (27.972 %) (Fig. 2c). However, FAME productivity
334
at a dilution rate of 0.056 day-1 was 11.940 mg L-1 day-1, but it was only 8.625 mg L-1 day-1 at
335
a dilution rate of 0.028 day-1. This result clearly shows that dilution rate has a substantial
336
influence on FAME productivity. Consequently when an microalgal cultivation system is
337
operated in continuous mode, it is critical to identify the proper dilution rate to improve
338
overall production quality.
339
The advantages of a serially connected PBR system were further highlighted by
340
comparing with a single reactor system. The serially connected PBRs had 46.1 % greater
341
FAME productivity than the control reactor at a dilution rate of 0.056 day-1 (Fig. S2b). This
342
difference could be attributed to the increased cell mass and FAME content; the dry cell
343
weight in the serially connected system was 19.5 % higher, and FAME content was 22.3 %
344
higher than that of the single reactor system. This significant improvement in biodiesel
345
productivity, following a simple modification of a more traditional operation, is highly
346
encouraging.
347
In addition to producing greater biomass and lipid productivities, the chemostat
348
serially connected PBR system has several additional advantages over the conventional single
349
reactor PBR in terms of process operation. In particular, the serially connected system is 16
350
divided into several independent environments (4 in this study), so it is possible to manage a
351
sudden culture crash without losing the entire culture volume. Thus, when a crash occurs in
352
one of the units, the operator can protect the other units by simply detaching the affected unit.
353
This allows the unaffected units to operate normally, namely, saves a tremendous amount of
354
effort and cost (Smith & Crews, 2014; Yun et al., 2016). Another unique feature of the
355
serially connected PBR system is its wide adaptability. It is possible to independently control
356
every unit, so different culture conditions can be applied to different units. Thus, it may be
357
possible, for example, to enhance overall productivity by using different illumination
358
regimens for different reactors (Imaizumi et al., 2016). The novel serially connected PBR
359
system has special characteristics. Each unit functions as an independent environment, but the
360
overall performance of the system is affected by their interdependence. Thus it can be
361
anticipated that the serially connected PBR system has great potential for improving the
362
overall quality of microalgal cultivation processes.
363 364 365 366 367 368 369 370
17
371 372
4. Conclusions In this study, a novel microalgal cultivation process was developed by serially
373
connecting four PBRs. The cultivation with the low dilution rate (0.028 day-1) led to 1.110 g
374
L-1 of biomass and 27.972 % of FAME production that were 29.4 % and 11.6 % greater than
375
those produced with a high dilution rate (0.056 day-1), respectively. Moreover, cells grown
376
under the serially connected PBRs showed 46.1 % increased lipid productivity compared to a
377
conventional PBR. These results suggest that process based cultivation system combined with
378
the serially connected PBR can be applied for effective biodiesel production in microalgal
379
cultivation field.
380 381
Acknowledgements
382
This work was supported by the Advanced Biomass R&D Center (ABC) of Global Frontier
383
Project funded by the Ministry of Science, ICT, and Future Planning (ABC- 2010-0029728)
384
18
385
5. References
386
1. Ahmad, A., Yasin, N.M., Derek, C., Lim, J. 2011. Microalgae as a sustainable energy
387 388 389 390 391
source for biodiesel production: a review. Renew. Sust. Energ. Rev. 15, 584-593. 2. Bailey, J.E., Ollis, D.F. 1976. Biochemical engineering fundamentals. Chemical Engineering Education. 3. Borowitzka, M.A. 1992. Algal biotechnology products and processes—matching science and economics. J. Appl. Phycol. 4, 267-279.
392
4. Carpinelli, E.C., Telatin, A., Vitulo, N., Forcato, C., D’Angelo, M., Schiavon, R., Vezzi, A.,
393
Giacometti, G.M., Morosinotto, T., Valle, G. 2014. Chromosome scale genome
394
assembly and transcriptome profiling of Nannochloropsis gaditana in nitrogen
395
depletion. Mol. Plant. 7, 323-335.
396
5. Chen, C.Y., Yeh, K.L., Aisyah, R., Lee, D.J., Chang, J.S. 2011. Cultivation,
397
photobioreactor design and harvesting of microalgae for biodiesel production: A
398
critical review. Bioresource Technol. 102, 71-81.
399
6. dos Santos, R.R., Kunigami, C.N., Aranda, D.A.G., Teixeira, C. 2016. Assessment of
400
triacylglycerol content in Chlorella vulgaris cultivated in a two-stage process.
401
Biomass. Bioenerg. 92, 55-60.
402
7. Fernandes, B.D., Mota, A., Teixeira, J.A., Vicente, A.A. 2015. Continuous cultivation of
403
photosynthetic microorganisms: Approaches, applications and future trends.
404
Biotechnol. Adv. 33, 1228-1245.
405 406 407
8. Folch, J., Lees, M., Sloane-Stanley, G. 1957. A simple method for the isolation and purification of total lipids from animal tissues. J. Biol. Chem. 226, 497-509. 9. Gong, Y.M., Jiang, M.L. 2011. Biodiesel production with microalgae as feedstock: from 19
408 409 410
strains to biodiesel. Biotechnol. Lett. 33, 1269-1284. 10. Griffiths, M.J., Harrison, S.T.L. 2009. Lipid productivity as a key characteristic for choosing algal species for biodiesel production. J. Appl. Phycol. 21, 493-507.
411
11. Griffiths, M.J., van Hille, R.P., Harrison, S.T.L. 2014. The effect of nitrogen limitation on
412
lipid productivity and cell composition in Chlorella vulgaris. Appl. Microbiol. Biot.
413
98, 2345-2356.
414 415
12. Guillard, R., Ryther, J. 1962. Studies of marine planktonic diatoms. Cyclotella nana, 229239.
416
13. Ho, S.H., Chen, C.Y., Chang, J.S. 2012. Effect of light intensity and nitrogen starvation
417
on CO2 fixation and lipid/carbohydrate production of an indigenous microalga
418
Scenedesmus obliquus CNW-N. Bioresource Technol. 113, 244-252.
419
14. Ho, S.-H., Ye, X., Hasunuma, T., Chang, J.-S., Kondo, A. 2014. Perspectives on
420
engineering strategies for improving biofuel production from microalgae—a critical
421
review. Biotechnol. Adv. 32, 1448-1459.
422
15. Imaizumi, Y., Nagao, N., Yusoff, F.M., Kurosawa, N., Kawasaki, N., Toda, T. 2016.
423
Lumostatic operation controlled by the optimum light intensity per dry weight for the
424
effective production of Chlorella zofingiensis in the high cell density continuous
425
culture. Algal Res. 20, 110-117.
426 427
16. Klok, A.J., Martens, D.E., Wijffels, R.H., Lamers, P.P. 2013. Simultaneous growth and neutral lipid accumulation in microalgae. Bioresource technol. 134, 233-243.
428
17. Liu, T., Li, Y., Liu, F., Wang, C. 2016. The enhanced lipid accumulation in oleaginous
429
microalga by the potential continuous nitrogen-limitation (CNL) strategy. Bioresource
430
Technol. 203, 150-159.
431 20
432
18. Martin, L.A., Popovich, C.A., Martinez, A.M., Damiani, M.C., Leonardi, P.I. 2016. Oil
433
assessment of Halamphora coffeaeformis diatom growing in a hybrid two-stage
434
system for biodiesel production. Renew. Energ. 92, 127-135.
435
19. Monod, J. 1949. The Growth of Bacterial Cultures.
436
20. Ren, M., Ogden, K. 2014. Cultivation of Nannochloropsis gaditana on Mixtures of
437
Nitrogen Sources. Environ. Prog. Sustain. Energy. 33, 551-555.
438
21. Rodolfi, L., Zittelli, G.C., Bassi, N., Padovani, G., Biondi, N., Bonini, G., Tredici, M.R.
439
2009. Microalgae for Oil: Strain Selection, Induction of Lipid Synthesis and Outdoor
440
Mass Cultivation in a Low-Cost Photobioreactor. Biotechnol. Bioeng. 102, 100-112.
441
22. Roessler, P.G. 1990. Environmental control of glycerolipid metabolism in microalgae:
442
commercial implications and future research directions. J. Phycol. 26, 393-399.
443
23. Schmidt, L.D. 1998. The engineering of chemical reactions. Oxford University Press,
444
USA.
445
24. Simionato, D., Block, M.A., La Rocca, N., Jouhet, J., Maréchal, E., Finazzi, G.,
446
Morosinotto, T. 2013. The response of Nannochloropsis gaditana to nitrogen
447
starvation includes de novo biosynthesis of triacylglycerols, a decrease of chloroplast
448
galactolipids, and reorganization of the photosynthetic apparatus. Eukaryot. Cell. 12,
449
665-676.
450 451 452 453
25. Singh, N.K., Dhar, D.W. 2011. Microalgae as second generation biofuel. A review. Agron. Sustain. Dev. 31, 605-629. 26. Smith, V.H., Crews, T. 2014. Applying ecological principles of crop cultivation in largescale algal biomass production. Algal Res. 4, 23-34.
454
27. Su, C.-H., Chien, L.-J., Gomes, J., Lin, Y.-S., Yu, Y.-K., Liou, J.-S., Syu, R.-J. 2011.
455
Factors affecting lipid accumulation by Nannochloropsis oculata in a two-stage 21
456 457 458
cultivation process. J. Appl. Phycol. 23, 903-908. 28. Suali, E., Sarbatly, R. 2012. Conversion of microalgae to biofuel. Renew. Sust. Energ. Rev. 16, 4316-4342.
459
29. Sung, M.G., Shin, W.S., Kim, W., Kwon, J.H., Yang, J.W. 2014. Effect of shear stress on
460
the growth of continuous culture of Synechocystis PCC 6803 in a flat-panel
461
photobioreactor. Korean J. Chem. Eng. 31, 1233-1236.
462 463
30. Tang, H.Y., Chen, M., Ng, K.Y.S., Salley, S.O. 2012. Continuous microalgae cultivation in a photobioreactor. Biotechnol. Bioeng. 109, 2468-2474.
464
31. Yeh, K.L., Chang, J.S. 2011. Nitrogen starvation strategies and photobioreactor design for
465
enhancing lipid production of a newly isolated microalga Chlorella vulgaris ESP-31:
466
Implications for biofuels. Biotechnol. J. 6, 1358-1366.
467
32. Yun, J.-H., Smith, V.H., La, H.-J., Keun Chang, Y. 2016. Towards managing food-web
468
structure and algal crop diversity in industrial-scale algal biomass production. Curr.
469
Biotechnol. 5, 118-129.
470
33. Zhang, D., Xue, S., Sun, Z., Liang, K., Wang, L., Zhang, Q., Cong, W. 2014.
471
Investigation of continuous-batch mode of two-stage culture of Nannochloropsis sp
472
for lipid production. Bioproc. Biosyst. Eng. 37, 2073-2082.
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34. Zhu, J., Rong, J., Zong, B. 2013. Factors in mass cultivation of microalgae for biodiesel. Chinese J. Catal. 34, 80-100.
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22
477
Figure legends
478 479
Figure 1. Changes in N. gaditana biomass (OD750nm) and nitrate concentration in a single
480
flat-panel photobioreactor over 10 days.
481 482
Figure 2. Dry weight of N. gaditana (a), nitrate concentration in the medium (b), and fatty
483
acid methyl ester content of N. gaditana (c) at each photobioreactor position. Control
484
indicates a single chemostat photobioreactor with the same dilution rate.
485 486 487 488 489 490 491 492
23
493
Figures
494
Figure 1.
495 496 497 498 499 500 501 502 24
503
Figure 2.
504 505
25
506
Tables
507 508
Table 1. Specific growth rate (µ, day-1) in each reactor at 2 different dilution rates. Control represents a single reactor at the designated dilution rate. Dilution rate
Control
Reactor 1
Reactor 2
Reactor 3
Reactor 4
0.028 (day-1)
N/A
0.111
0.054
0.072
0.040
0.056 (day-1)
0.056
0.222
0.042
0.126
0.038
509 510 511 512 513 514
26
515
GRAPHICAL ABSTRACT
516
517 518 519 520 521
27
522
Highlights
523
Microalgae were cultivated with four photobioreactors connected in series.
524
The final reactor has resulted in a 7.74-fold increased biomass.
525
Lipids accumulated along the reactor positions and doubled at the final reactor.
526
Connected PBR system led to 46 % increased lipid productivity compared to control.
527
28