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Original article
07 2022
:15;
103920
doi:
10.1016/j.arabjc.2022.103920

Design and optimization of lipids extraction process based on supercritical C O 2 using Dunaliella Tertiolecta microalga for biodiesel production

Department of Chemical Engineering, Islamic Azad University, North Tehran Branch, Tehran, Iran
Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Peer review under responsibility of King Saud University.

Abstract

Extraction of oil with supercritical C O 2 solution to produce biofuels from Dunaliella tertiolecta microalga was investigated. 8 treatments during two light periods of light and dark with different shocks of acidity, salinity and nutrients were studied individually and in pairs. As the amount of Dunaliella Tertiolecta microalga produced biomass increased (more than 2.5 g L - 1 after 12 day), C O 2 consumption rate increased (629.97 ± 34.62 m g L - 1 d - 1 ). A more diverse fatty acid content was observed in the present study in Dunaliella Tertiolecta microalga, include: palmitic acid (C16:0), stearic acid (C18:0), erucic acid (C22:1n9), nervonic acid (C24:1n9), docosahexaenoic acid (C22:6n3) and eicosadienoic acid (C20:3n3). The measured iodine value (IV) and saponification value (SV) showed no significant differences between the experimental samples (P < 0.05). The cetane number and degree of saturation in the biofuel produced by microalga were high, therefore, the biofuel was of high quality. The amount of oil extracted in the control and optimal treatments showed that increasing the pressure has a positive effect on the extraction and the best temperature was 40 °C with a pressure of 370 b a r .

Keywords

Supercritical
Carbon dioxide
Microalga
Biodiesel
Dunaliella Tertiolecta
PubMed
1

1 Introduction

Scientists predict that the world will face a crisis of shortage of oil, gas and coal resources in the not-too-distant future (Andreo-Martínez et al., 2020; Tan et al., 2020). Extensive studies have been conducted today on sustainable and renewable fuels such as microalga-derived oils (Halim et al., 2012). Biodiesel is the product of a transesterification reaction between lipids and alcohol, and its required fatty acids can be obtained from a wide range of sources such as food waste, animal fats, vegetable oils, cooking oil wastes, algae and other sources (Qadeer et al., 2021).

Based on stoichiometric ratios, one mole of triglyceride or three moles of alcohol reacts, producing three moles of ester and one mole of glycerol (Koyande et al., 2019). Methanol is the most widely used alcohol because of its low cost, but other alcohols can also be used. for example ethanol, isopropanol and, ethanol. Although the use of these alcohols can improve fuel properties, they will be costly on an industrial scale and not feasible. Biodiesel can be produced from a variety of raw materials, including edible oils (soy, palm, sunflower, coconut) (Nguyen et al., 2020). But, the non-edible oils (Jatropha, Camellia, rice bran, Pongamia, Telotia) are preferred. Therefore, the supply of raw materials is one of the most important challenges in biodiesel production, which accounts for 85% of the cost of biodiesel production (Kadir et al., 2021).

Among the various sources for biodiesel production; microalga is the best option because, unlike agricultural and animal resources, they are more efficient, have a less direct effect on the human food cycle, and can be produced in large quantities in a small space (Tan et al., 2018). By providing light, nutrients, C O 2 and water, microalga can be doubly grown (Islam et al., 2017). The photosynthetic cycle of microalga is shown in Fig. 1.

Schematic of the photosynthesis cycle of microalga.
Fig. 1
Schematic of the photosynthesis cycle of microalga.

Dunaliella Tertiolecta is a green and marine microalga. This microalga has two protozoan parts and has been widely used in ecological, industrial and agricultural studies (Iyer, 2016). In the first stage of its reproduction, this microalga requires super-saline and marine habitats, but the results of studies showed that this microalga is able to grow in a wide range of salinity (Faried et al., 2017). C O 2 capture is a metabolic capability of this microalga, thus receiving and stabilizing insoluble and inorganic carbon from the environment (González-González et al., 2018). Production of glycerol, beta-carotene carotenoids, single-cell proteins and minerals in the aquatic diet are among the industrial and agricultural applications of Dunaliella Tertiolecta microalga (Santana et al., 2012). These microalga are also used in the biological recycling of heavy metals from the environment because it is able to bind heavy metals to peptides and phytochelatins, which plays an important role in detoxification from the environment and the accumulation of heavy metals (Beni and Esmaeili, 2020). Extraction of biodiesel from algae faces many problems such as high energy consumption, environmental pollution and low extraction capacity, which are the main obstacles to the production of this type of fuel on a large scale (Fazal et al., 2018). In traditional extraction methods such as pyrolysis, flammable and soluble solvents are used (Mathimani and Mallick, 2018).

Today, the production of biodiesel using alkaline homogenized catalysts is more commercializable than other methods. This reaction takes place by the addition of a nucleus of the oxide anion to the carbonyl (Leone et al., 2019). The catalysts used are sodium, potassium methoxide and hydroxide. In the alkaline catalyst process, the raw materials must be water-free to prevent hydrolysis of volatile fatty acids (Keddar et al., 2020). Volatile fatty acids are not converted to esters but to soap (Saleem et al., 2018).

In the transesterification method and acidic esterification, the transesterification can be performed in the presence of strong acid catalysts such as sulfuric acid (Liu et al., 2017; Rangabhashiyam and Selvaraju, 2015). The use of this method to produce biodiesel from frying oils and palm oil waste has been reported. Acid catalysts are slower than alkaline catalysts during the acid transesterification process. Due to the low reaction speed, it requires high temperatures and high pressure (Di Caprio et al., 2020). During acidic esterification, water is formed which causes the hydrolysis of triglycerides in small amounts (Tabernero et al., 2012). Most acidic catalysts are highly corrosive and cause contamination and turbidity of biodiesel (Vasistha et al., 2021).

One method of extracting biodiesel from microalgae is the microwave method. Reports have shown that this method is effective but requires a lot of energy (Chang et al., 2020). The biological cell breakdown method is another method of extracting biodiesel from algae that is able to increase biodiesel production (Goh et al., 2019). Nowadays, the extraction method by supercritical C O 2 solution is one of the best methods for producing biofuels, because it has significant yields and by optimizing parameters such as temperature and pressure, production can be increased (Muhammad et al., 2021). This extraction method has many advantages: no toxicity, stable extraction rate, simple process and more biodiesel extraction compared to other methods (Ortiz-Martínez et al., 2019).

Various shocks can affect the production of biomass and dry microalga and change the amount of oil extracted from the algae. Also, different shock conditions can affect the composition and amount of fatty acids in algae, and as a result, this quality of biofuels is effective. In this study, the effect of changes in culture conditions (different shocks in the microalga breeding stage) was studied quantitatively and qualitatively in biofuel extraction by C O 2 supercritical fluid method.

2

2 Experiment

2.1

2.1 Material

A sample of Dunaliella Tertiolecta was purchased from the microalga pilot plant facility of arian gostar research company (TAG BIOTEK CO), Tehran, Iran. BBM Medium 50X (Bold's Basal Medium + soil extract + vitamins) (50X), NaCl, Hcl, and NaOH was purchased from the Sigma-Aldrich. Double distillation water was used in all experiments.

2.2

2.2 Cultivation of microalga

Microalga were cultured in clear polyethylene terephthalate flasks with a volume of 10 L . The initial density of culture cells was diluted to 4.25 c e l l L - 1 at pH 8 and 21 °C in the BBM Medium (Bold's Basal Medium + soil extract + vitamins). The microalga were cultured under cold light at 3000–3500 L u x and continuous aeration at 800 m l m i n - 1 l for 12 days. After stabilizing the cell density, the solution containing the microalga was centrifuged at 3500 r p m for 5 m i n . The obtained biomass ( 0.2713 g ) was suspended in 1 L of deionized water. The solution was evenly distributed and inoculated into 32 flasks according to the instructions in Table 1, including 8 treatments.

Table 1 Instructions for creating shock in different cultures of Dunaliella Tertiolecta microalga.
Treatments Instructions for creating shock
1 Creating severe alkaline conditions (pH 11)
2 Creating severe salinity conditions by increasing salt (1 M NaCl)
3 Creating nutrient deficiency conditions (Substrate reduction)
4 pH 11 + 1 M NaCl
5 pH 11 + Substrate reduction
6 1 M NaCl + Substrate reduction
7 1 M NaCl + Substrate reduction + pH 11
8 No shock (control sample)

2.3

2.3 Extraction with supercritical carbon dioxide

In this method, extraction was performed with the help of liquid carbon dioxide on dry algae, which extracts all the fat of the microalga cell (McKennedy et al., 2016). In this method, 30 g of microalga under temperature conditions of 40-80 °C, pressure of 200–370 bar, mixture of hexane: ethanol solvents (1:1), duration 60 min, carbon dioxide flow rate of 200–100 g m i n - 1 was underwent of oil extraction. According to Fig. 2 three outlet pipes was considered for oil: one for high pressure (CS1) and one for low pressure (CS2) and the third outlet for standard conditions from which other remaining fats was removed. The oil was then centrifuged and the pure oil was mixed with hexane to remove pigments and polar fats, and after passing through sodium sulfate, neutral fats were extracted, which had to be chromatographed to determine the fatty acid profile (Saranya and Ramachandra, 2020).

The process of extracting biodiesel fuel from microalga using supercritical C O 2 .
Fig. 2
The process of extracting biodiesel fuel from microalga using supercritical C O 2 .

According to Paolo Leone et al. (Leone et al., 2019) reports, in terms of purity, the lower the pressure, the higher the purity, because the highest lipid purity was found at 75 °C and 100 bar with a C O 2 flow rate of 14.48 g m i n - 1 . The literature reports that fat recovery increases with increasing temperature and pressure. But, higher temperatures can increase extraction performance, leading to higher impurity content.

2.4

2.4 Measurement of cell growth

Cell density was determined by measuring the optimal density at a wavelength of 750 nm. The optimal density was checked daily and the number of cells was counted daily. The biomass productivity ( g L - 1 d - 1 ) was calculated based on the change in biomass concentration ( g L - 1 ) in the desired time period ( d ) and using Eq. (1) (Iyer, 2016):

(1)
P s = ( X 1 - X 0 ) ( t 1 - t 0 )

The specific growth rate ( d - 1 ) was calculated based on the following equation:

(2)
μ = ( ln X 1 - ln X 0 ) ( t 1 - t 0 )

X 1 and X 0 are biomass concentrations ( g L - 1 ) on days t 1 and t 0 , respectively.

Division time ( d - 1 ) and production time ( h - 1 ) were obtained using the following equation:

(3)
D i v i s i o n t i m e = μ 0.9631
(4)
P r o d u c t i o n t i m e = 0.9631 μ

C O 2 stabilization efficiency ( g L - 1 d - 1 ) was obtained by measuring the carbon dioxide index in microalga:

(5)
P C O 2 = 1.88 P s

2.5

2.5 Chlorophyll a, b and total carotene measurements

96% methanol solvent will be used for extraction. For this purpose, a certain amount of culture medium was taken and after separating the algae from the water, 50 m l of solvent was added to each gram of algal sample. The solution is homogenized by mixing 1000 r p m for one minute. The homogenized solution was filtered using Whatman paper and then centrifuged using a centrifuge at 2500 r p m for 10 min.

The adsorption of chlorophyll a ( C a ) will be read at 662 nm, chlorophyll b ( C b ) at 646 nm and total carotene ( C X + C ) at 470 nm. The relationships used to calculate the amount of chlorophyll a, chlorophyll b and total carotene are given below (Naito et al., 2007):

(6)
C a = 15.65 A 666 - 7.340 A 653
(7)
C b = 27.05 A 653 - 11.21 A 666
(8)
C X + C = 1000 A 470 - 2.860 C a - 81.4 C b 245

2.6

2.6 Approximate composition

2.6.1

2.6.1 Lipid and ash content analysis

Soxhlet method was used to measure the amount of total fat and burning the weighed samples in an electric oven at 550 °C for 6 h was used for the amount of ash (Faried et al., 2017).

2.6.2

2.6.2 Protein content measurement

To measure the protein content, 5 m g of the dry sample was mixed with 2 m l of 24% (w/v) trichloroacetic acid, then the mixture was incubated at 95 °C for 15 min. The homogenized samples were centrifuged for 4 m i n at 4 °C and the supernatant was separated. The resulting mass was suspended again in 0.5 m l of Lowry reagent and incubated for 20 m i n , then the supernatant was placed in Lowry reagent for 30 m i n . Finally, the wavelength was read at 600 n m .

2.6.3

2.6.3 Total carbohydrate content measurement

The prepared samples were centrifuged at 5000 r p m at 4 °C for 30 m i n . The supernatant was collected and 1 m l of each sample/standard glucose was poured into a test tube and then 1 ml of 5% phenol and 5 ml of 96% sulfuric acid were added to each tube. After 10 m i n , the mixture was vertexed in tubes and kept at 25 °C for 20 m i n . The absorbance was assessed at 400 nm (Leone et al., 2019; Tan et al., 2020).

2.6.4

2.6.4 Fatty acid profiles

200 m g of Dunaliella Tertiolecta was added to 1 m l of H 2 S O 4 (2.5%) and 98% methanol mixture solution 1:40 (v/v) was poured into each sample and incubated for 1 h at 80 °C. 500 μl of hexane was mixed with 1.5 m l of 90% (w/v) NaCl and added to mixtures to extract fatty acid methyl ester (FAME). The prepared samples were centrifuged at 10,000 r p m for 10 m i n and the supernatant was collected in three replications. Samples were injected into the GC-FID apparatus to evaluate the fatty acid profile (Tobar and Núñez, 2018). FAME was analyzed using GC-FID (Shimadzu GC-2010). GC-FID was equipped with a BPXBD20 column and helium was used as the carrier gas. The initial column temperature was set at 150 °C and gradually increased to 240 °C at 15 °C m i n - 1 rate, while the injector and FID were set at 250 °C. The injection volume was 1 μ l with a split ratio of 10:1. Methyl heptadecanoate was used as the internal standard for quantitative analysis (Nguyen et al., 2020).

2.7

2.7 Measuring of biodiesel quality

The quality of biodiesel extracted from Dunaliella Tertiolecta oil was determined by evaluating the degree of unsaturation (DU) (Tobar and Núñez, 2018), saponification value (SV) (Keddar et al., 2020), cetane number (CN) (Islam et al., 2017) and, iodine value (IV) (Islam et al., 2017). These values were calculated by following equations:

(9)
SV = 560 × F M
(10)
IV = 254 × F × D M
(11)
CN = 46.3 + 5458 SV - ( 0.225 × I V )
(12)
DU = M U F A + ( 2 × P U F A )
where F is the percentage of each fatty acid, M is the molecular mass of fatty acid, D is the number of double bonds, MUFA (wt%) is monounsaturated fatty acids and PUFA (wt%) is a polyunsaturated fatty acid.

2.8

2.8 Statistical analysis

All measurements were repeated three times and the error of values was considered in the report. All statistical analysis was performed using SPSSSPSS Statistics V.17.01 (SPSS Inc., Chicago, USA). The P-value less than 0.05 was considered as significant.

3

3 Results and discussion

3.1

3.1 Growth factors in Dunaliella Tertiolecta microalga

The Dunaliella Tertiolecta microalga biomass production and cell number during 12 days was shown in Fig. 3 a and b. The properties of Dunaliella Tertiolecta microalga growth were as follows: SGR = 0.17 μ , Biomass productivity = 0.34 ± 0.05 g L - 1 d - 1 and, C O 2 consumption rate = 629.97 ± 34.62 m g L - 1 d - 1 . As shown in Fig. 3 c, pH changes were recorded at 12 days of growth. From the first day of microalga growth, the pH increased and at the end of day 12, the growth medium was alkaline. Also, the highest pH value was recorded on the tenth day (see Fig. 4).

Dunaliella Tertiolecta microalga biomass produced (a), cell number (b) and, pH change (c) during 12 days of culture.
Fig. 3
Dunaliella Tertiolecta microalga biomass produced (a), cell number (b) and, pH change (c) during 12 days of culture.
Dunaliella Tertiolecta microalga biomass produced (a), cell number (b) and, pH change (c) during 12 days of culture.
Fig. 3
Dunaliella Tertiolecta microalga biomass produced (a), cell number (b) and, pH change (c) during 12 days of culture.
Overview of fatty acids of Dunaliella Tertiolecta microalga.
Fig. 4
Overview of fatty acids of Dunaliella Tertiolecta microalga.

3.2

3.2 Approximate composition of Dunaliella Tertiolecta microalga

The results obtained for the microalga Dunaliella teriolecta are given in Table 2. According to the results, the amount of lipid in the dark period 7 treatment was the highest (54.83 ± 1.02) and the lowest value was related to the light period of treatment 4 (10.93 ± 0.97). On the other hand, lipid levels in treatments 5, 6 and 8 did not differ significantly between dark and light periods (P < 0.05). The results obtained for ash also showed the highest value in the light and dark period of treatment 4, the light period was slightly higher (9.60 ± 0.44) and the lowest value was related to the light period of treatment 4 (16.4 ± 0.85).

Table 2 Analysis of chemical compounds of Dunaliella Tertiolecta microalga.
Treatments Lipid (%) Ash (%) Protein (%) Carbohydrate (%)
1 Dark Time 23.18 ± 0.44d 9.00 ± 0.10b 17.02 ± 0.18ab 50.24 ± 0.47bc
Light Time 13.73 ± 0.44ab 8.08 ± 0.49b 17.07 ± 0.22ab 60.41 ± 0.38 cd
2 Dark Time 18.05 ± 0.61c 4.78 ± 0.71a 16.21 ± 0.209ab 60.0 ± 2.21 cd
Light Time 17.95 ± 0.56c 5.23 ± 1.19a 16.71 ± 0.23ab 59.64 ± 1.72c
3 Dark Time 20.08 ± 0.72d 9.24 ± 0.68b 14.07 ± 2.50a 56.5 ± 1.30c
Light Time 12.84 ± 0.41ab 9.60 ± 0.44b 20.08 ± 0.86b 57.19 ± 0.72c
4 Dark Time 22.50 ± 0.94d 7.68 ± 0.96b 12.02 ± 1.63a 57.03 ± 1.43c
Light Time 33.89 ± 0.84f 6.88 ± 0.25ab 17.39 ± 1.54ab 41.38 ± 0.02b
5 Dark Time 27.40 ± 1.18e 5.54 ± 0.20a 17.66 ± 0.45ab 49.16 ± 1.57b
Light Time 10.93 ± 0.97a 4.16 ± 0.85a 19.16 ± 1.95b 65.32 ± 3.52e
6 Dark Time 27.53 ± 1.52e 7.62 ± 0.79b 14.30 ± 0.09a 50.27 ± 0.85bc
Light Time 11.63 ± 0.44a 7.68 ± 0.94b 21.75 ± 1.90bc 58.72 ± 2.88c
7 Dark Time 54.83 ± 1.02 g 5.04 ± 0.96a 13.16 ± 1.40a 26.01 ± 1.30a
Light Time 10.21 ± 0.09a 5.14 ± 0.63a 19.11 ± 0.54b 65.45 ± 1.04e
8 Dark Time 28.88 ± 0.16e 6.75 ± 0.91ab 13.70 ± 0.77a 50.27 ± 0.14bc
Light Time 11.20 ± 0.25a 7.81 ± 0.66b 17.25 ± 0.68ab 63.38 ± 1.15d

Non-identical letters in each column indicate significance between treatments (P < 0.05).

The amount of protein in the results obtained in the light period of treatment 6 (21.75 ± 1.90) was the highest and the lowest value in the dark period of treatment 4 (12.02 ± 1.63) and also between the dark and light periods of the treatments. No significant differences were observed in 1, 2, 4, 5 and 8 (P < 0.05). The highest and lowest carbohydrates were observed in light (65.45 ± 1.04) and dark (26.01 ± 1.30) treatments, respectively, and treatments 1, 2, 3 and 6 in dark and their brightness was not significantly different from each other (P < 0.05).

3.3

3.3 Measurement of chlorophyll a, b and total carotene

The results for chlorophyll a, b and total carotene of Dunaliella teriolecta are shown in Table 3. Based on the results, it was determined that the amount of chlorophyll a had the highest value during the light period of treatments 1 (28.18 ± 0.22), 2 (28.78 ± 0.36) and 3 (29.74 ± 0.19) and between there was no significant difference between the dark and light periods of treatments 4 and 5 (P < 0.05). The lowest amount of chlorophyll a was observed in the dark period of treatment 3 (2.14 ± 0.16). The highest amount of chlorophyll b in the light period of treatments 1 (16.71 ± 0.07), 2 (16.40 ± 0.12) and 3 (16.87 ± 0.21) The highest amount and dark periods of treatments 3 (143.44 ± 0.02), 6 (2.53 ± 0.17), 7 (2.31 ± 0.21) and 8 (2.52 ± 0.04) showed the lowest values. However, there was no significant difference between the dark and light periods of treatments 3, 2 and 6 (P < 0.05). Treatments 4, 5, 6, 7 and 8 did not show a significant difference in the amount of chlorophyll b (P < 0.05).

Table 3 Amounts of chlorophyll a, b and total carotene of Dunaliella Tertiolecta microalga.
Treatments Chlorophyll a ( μ g g - 1 ) Chlorophyll b ( μ g g - 1 ) Total Carotene ( μ g g - 1 )
1 Dark Time 4.68 ± 0.28b 3.76 ± 0.1.52a 322.44 ± 31.10a
Light Time 28.18 ± 0.22e 16.71 ± 0.07c 797.27 ± 30.81c
2 Dark Time 7.05 ± 0.02b 3.93 ± 0.00a 1238.59 ± 70.00f
Light Time 28.78 ± 0.36e 16.40 ± 0.12c 833.23 ± 21.88d
3 Dark Time 2.14 ± 0.16a 2.47 ± 0.143a 852.95 ± 13.00d
Light Time 29.74 ± 0.19e 16.87 ± 0.21c 906.22 ± 16.30d
4 Dark Time 4.01 ± 1.46b 3.21 ± 0.07a 1892.19 ± 31.27 g
Light Time 22.87 ± 0.21c 14.22 ± 0.02b 498.87 ± 16.72b
5 Dark Time 5.57 ± 0.01b 3.36 ± 0.01a 1111.62 ± 14.61e
Light Time 23.11 ± 0.84c 13.68 ± 0.45b 439.48 ± 106.83b
6 Dark Time 2.45 ± 0.29a 2.53 ± 0.17a 879.52 ± 21.04d
Light Time 24.19 ± 0.26 cd 14.67 ± 0.47b 482.83 ± 32.04b
7 Dark Time 2.32 ± 0.15a 2.31 ± 0.21a 872.45 ± 5.17d
Light Time 22.40 ± 0.38c 13.32 ± 0.47b 441.24 ± 28.61b
8 Dark Time 2.54 ± 0.01a 2.52 ± 0.04a 900.79 ± 44.35d
Light Time 24.87 ± 1.99 cd 14.11 ± 0.62b 439.20 ± 84.25b

Non-identical letters in each column indicate significance between treatments (P < 0.05).

Based on the results obtained for total carotene, it was found that the highest amount of carotene is present in the dark period of treatment 4 (1892.19 ± 31.27) and the lowest amount is in the light period of treatment 1 (322.44 ± 31.10) and between No significant differences were observed in treatments 6, 7 and 8 (P < 0.05).

3.4

3.4 Profiles of fatty acids

The profile results of Dunaliella teriolecta microalga fatty acids are given in Table 4. Based on the results, it was found that the amount of myristic acid (C14) in the dark period was higher than the light period and the highest and lowest values ​​in the dark period (15.57 ± 0.12) in the dark period of treatment 7 (0.01 ± 0.00) was observed. The amount of palmitic acid (C16:0) had the highest value between dark and light periods in treatment 5 (25.95 ± 0.14) and 8 (24.58 ± 0.12) in the dark period and the lowest value in the light period. Treatment 2 (10.31 ± 2.12) was observed.

Table 4 Dunaliella Tertiolecta microalga saturated fatty acid profile.
Fatty acid profiles Time Treatments ( μ g g - 1 )
1 2 3 4 5 6 7 8
C14 Dark Time 9.74 ± 0.52c 8.72 ± 0.52c ND 15.57 ± 0.12d ND ND 0.01 ± 0.00a 1.09 ± 0.02b
Light Time 0.50 ± 0.12a 3.59 ± 1.05c 3.53 ± 0.01c 0.51 ± 0.12a 0.39 ± 0.11a 0.79 ± 0.07a 1.46 ± 0.13b 0.87 ± 0.04a
C16:0 Dark Time 20.94 ± 1.06b 17.89 ± 1.05a 17.36 ± 0.82a 21.70 ± 0.69b 25.95 ± 0.14c 20.53 ± 0.09b 21.17 ± 0.69b 24.58 ± 0.12c
Light Time 24.19 ± 0.74c 10.31 ± 2.12a 17.28 ± 0.72b 23.96 ± 0.73c 15.88 ± 0.83b 23.82 ± 0.38c 17.54 ± 0.53b 21.29 ± 0.20c
C18:0 Dark Time 12.91 ± 0.53bc 6.70 ± 0.53a 11.91 ± 0.51bc 4.40 ± 0.28a 18.58 ± 0.10c 8.06 ± 0.04b 16.76 ± 0.55c 11.12 ± 0.09bc
Light Time 7.09 ± 0.41a 8.65 ± 0.29a 22.12 ± 0.14d 24.28 ± 0.12d 10.67 ± 0.01ab 14.12 ± 0.53bc 13.98 ± 0.21b 29.28 ± 0.09f
C20:0 Dark Time 7.73 ± 0.41c 7.71 ± 0.41c ND 0.45 ± 0.09ab ND ND 0.01 ± 0.00c 0.87 ± 0.19b
Light Time 0.40 ± 0.09a ND 0.42 ± 0.07a 0.40 ± 0.09a 0.31 ± 0.09a 0.63 ± 0.05ab 1.16 ± 0.10a 0.99 ± 0.03ab
C22:0 Dark Time 0.61 ± 0.20a 0.55 ± 0.25a 0.78 ± 0.07a 0.88 ± 0.03a 3.56 ± 0.24b 2.43 ± 0.05b 0.73 ± 0.02b 0.62 ± 0.00a
Light Time 0.40 ± 0.11a 0.26 ± 0.00a 0.91 ± 0.02a 1.09 ± 0.04b 3.76 ± 0.25c 2.12 ± 0.08c 1.33 ± 0.00b 0.90 ± 0.14a
C24:0 Dark Time 0.80 ± 0.03a 1.11 ± 0.00ab 0.81 ± 0.00a 0.37 ± 0.05a 1.17 ± 0.05b 0.67 ± 0.14a 0.24 ± 0.00a 0.27 ± 0.000a
Light Time 7.65 ± 0.05c 0.19 ± 0.00a 0.24 ± 0.00a 0.54 ± 0.16a 0.71 ± 0.04a 0.22 ± 0.00a 0.45 ± 0.02a 2.93 ± 0.05b

Non-identical letters in each column indicate significance between treatments (P < 0.05).

Stearic acid (C18:0) showed the highest value during the light period in treatment 8 (29.28 ± 0.09) and the lowest value during the dark period in treatment 4 (4.40 ± 0.28). In the dark period, no significant differences were observed between treatments 1, 3, 8 and also during the light period between treatments 1, 2 and 5 (P < 0.05). The amount of arachidic acid (C20: 0) was also highest in treatments 1 (7.73 ± 0.41) and 2 (7.71 ± 0.41) during the dark period and in treatment 7 (0.01 ± 0.00) darkness. Showed the lowest value. During the dark period, treatments 3, 5 and 6 did not contain arachidonic acid and during the light period, treatment 2 did not contain this fatty acid. Based on the results, the amount of benic acid (C22:0) during the light period in treatment 5 (3.76 ± 0.25) showed the highest value and in treatment 2 (0.26 ± 0.00) showed the lowest value and between treatments 1 no significant differences were observed in 2, 3, 4 and 8 dark periods (P < 0.05). Finally, the amount of lignosic acid (C24:0) in the first treatment of light period (7.65 ± 0.05) was the highest and the lowest value in treatment 2 (0.19 ± 0.00) of the light period. In the dark period, except for treatment 5, no significant difference was observed between any of the treatments (P < 0.05). In general, according to these results, the amount of saturated fatty acids in Dunaliella teriolecta was higher during the dark period than during the light period.

The profile of monounsaturated fatty acids of Dunaliella teriolecta is given in Table 5. Based on the results, Myristoleic acid (C14:1n5) in the dark period had the highest value in treatments 1 (5.13 ± 0.40) and 2 (5.14 ± 0.41) and the lowest value in treatments 6. (1.44 ± 0.00) and 8 (1.18 ± 0.00) were in Drara. There was no significant difference between treatments 3, 4, 5, 6, 7 and 8 (P < 0.05). During the light period, the highest and lowest values ​​were observed in treatments 1 (11.18 ± 0.02) and 5 (1.01 ± 0.02), respectively, and treatments 4 to 8 showed no significant differences (P < 0.05).

Table 5 Profile of monounsaturated fatty acids of Dunaliella Tertiolecta microalga.
Fatty acid profiles Time Treatments ( μ g g - 1 )
1 2 3 4 5 6 7 8
C14:1n5 Dark Time 5.13 ± 0.40c 5.14 ± 0.41c 2.17 ± 0.07ab 1.27 ± 0.34a 2.51 ± 0.01ab 1.44 ± 0.00a 2.36 ± 0.07ab 1.18 ± 0.00a
Light Time 11.18 ± 0.02c 5.61 ± 0.00b 5.99 ± 0.01b 1.41 ± 0.04a 1.01 ± 0.02a 1.02 ± 0.01a 1.26 ± 0.0.02a 1.29 ± 0.11a
C16:1n7 Dark Time 1.81 ± 0.10a 1.81 ± 0.10a 4.40 ± 0.17c 1.95 ± 0.06a 2.17 ± 0.00ab 2.04 ± 0.00ab 1.66 ± 0.02a 1.42 ± 0.00a
Light Time 1.48 ± 0.04a 5.62 ± 0.00c 1.86 ± 0.05a 1.86 ± 0.07a 1.49 ± 0.04a 1.66 ± 0.02a 1.39 ± 0.03a 2.28 ± 0.02b
C18:1n9 Dark Time 8.07 ± 0.54d 1.97 ± 0.11a 1.67 ± 0.04a 1.92 ± 0.06a 1.67 ± 0.02a 5.70 ± 0.19c 1.68 ± 0.00a 2.02 ± 0.02ab
Light Time ND ND ND ND ND 3.89 ± 0.13b ND 1.66 ± 0.00a
C18:1n7 Dark Time 16.30 ± 0.33c 16.28 ± 0.33c 12.54 ± 0.90b 11.56 ± 0.42ab 9.11 ± 0.40a 11.81 ± 0.53ab 8.31 ± 0.19a 15.20 ± 0.07c
Light Time 11.94 ± 0.06b 5.64 ± 0.00a 12.54 ± 0.09b 11.66 ± 0.05b 22.22 ± 0.00d 18.64 ± 0.08c 24.79 ± 0.17d 4.72 ± 0.06a
C20:1n9 Dark Time 1.84 ± 0.40b 1.85 ± 0.41b 1.34 ± 0.15b 0.91 ± 0.15a 1.21 ± 0.01ab 1.20 ± 0.02ab 1.04 ± 0.03ab 1.14 ± 0.13ab
Light Time 1.19 ± 0.00ab 4.48 ± 0.04c 1.15 ± 0.04ab ND ND 0.85 ± 0.00a ND ND
C22:1n9 Dark Time 1.72 ± 0.02b 1.75 ± 0.00b 1.44 ± 0.05b 1.15 ± 0.28b 1.35 ± 0.06b 1.44 ± 0.05b 1.19 ± 0.19b 0.80 ± 0.00a
Light Time ND ND ND ND ND ND ND ND
C24:1n9 Dark Time 0.69 ± 0.00a 1.16 ± 0.033ab 0.76 ± 0.00a 1.35 ± 0.01b 1.29 ± 0.09ab 3.47 ± 0.05b 1.40 ± 0.01b 1.36 ± 0.16b
Light Time ND ND ND ND ND ND ND ND

Non-identical letters in each column indicate significance between treatments (P < 0.05).

Palmitoleic acid (C16: 1n7) showed the highest value in treatment 3 (4.40 ± 0.17) and the lowest in treatment 8 (1.42 ± 0.00) during the dark period, except for treatment 3. There were no significant differences between the treatments (P < 0.05). During the lighting period, it had the highest value in treatment 2 (5.62 ± 0.00) and the lowest value in treatment 7 (1.39 ± 0.03). There was no significant difference between treatments 1, 3, 4, 5, 6 and 8 (P < 0.05).

Oleic acid had the highest value during the dark period in treatment 1 (8.07 ± 0.54) and the lowest values ​​in treatments 3 (1.67 ± 0.04) and 5 (1.67 02 0.02). Oleic acid levels in treatments 2, 3, 4, 5, 7 and 8 were not significantly different during the dark period (P < 0.05). During the light period, the highest value was observed in treatment 6 (3.89 ± 0.13) and the lowest value in treatment 8 (1.66 ± 0.00) and the rest of the treatments lacked this fatty acid. Cis-Vaccenic acid monounsaturated fatty acid (C18:1n7) had the highest value during the dark period in treatments 1 (16.30 ± 0.33) and 2 (16.28 ± 0.33) and in treatment 7 (8.31 ± 0.19) had the lowest value and no significant difference was observed between treatments 3, 4, 5, 6 and 7 (P < 0.05). During the lighting period, the highest value was observed in treatment 7 (24.79 ± 0.17) and the lowest value was observed in treatment 8 (4.72 ± 0.06) and no significant difference was observed between treatments 1, 3 and 4 (P < 0.05).

Paullinic acid (C20:1n9) had the highest value during the dark period in treatments 1 (1.84 ± 0.04) and 2 (1.85 ± 0.41) and in treatment 4 (0.91 ± 0.15) It had the lowest value. There was no significant difference between treatments 1, 2, 3, 5, 6, 7 and 8 (P < 0.05). During the light period, the highest value was observed in treatment 4 (4.48 ± 0.04) and the lowest value was observed in treatment 6 (0.85 ± 0.00) that the other treatments lacked this fatty acid. Erucic acid (C22:1n9) had the highest value during the dark period in treatments 1 (1.72 ± 0.02) and 2 (1.75 ± 0.00) and in treatment 8 (0.80 ± 0.00) Had the lowest value. Also, no significant difference was observed between other treatments (P < 0.05). This fatty acid was not observed at all during the light period. Finally, Nervonic acid (C24:1n9) had the highest value during the dark period in treatment 6 (3.47 ± 0.05) and in treatments 1 (0.69 ± 0.00) and 3 (0.76 ± 0.00) showed the lowest value and no significant difference was observed between treatments 1, 2, 3 and 5 (P < 0.05). This fatty acid was not observed at all during light shock. Finally, it can be concluded that the amount of monounsaturated fatty acids in Dunaliella tertiolecta was higher during light shock.

The profile results of Dunaliella tertiolecta polyunsaturated fatty acids are given in Table 6. According to the results, the amount of linoleic acid (C18: 2n6) during the dark period had the highest value in treatment 2 (3.60 ± 2.23) and the lowest value in treatment 6 (1.15 ± 1.14). Also, treatments 1, 4, 5 and 8 did not contain this fatty acid. During the light period, the highest value was observed in treatment 8 (2.86 ± 2.15) and the lowest value was observed in treatment 1 (0.66 ± 0.66). Also, treatments 5, 6 and 7 did not contain this fatty acid.

Table 6 Dunaliella Tertiolecta microalga polyunsaturated fatty acid profiles.
Fatty acid profiles Time Treatments ( μ g g - 1 )
1 2 3 4 5 6 7 8
C18:2n6 Dark Time ND 3.60 ± 2.23c 0.21 ± 0.03a ND ND 1.15 ± 1.14b 2.39 ± 5.27bc ND
Light Time 0.66 ± 0.66a 0.69 ± 0.68a 2.47 ± 1.12c 1.60 ± 1.59b ND ND ND 2.86 ± 2.15c
C18:3n3 Dark Time ND ND 27.27 ± 0.80b 24.78 ± 1.16b 26.26 ± 0.13b 22.90 ± 0.10b 13.42 ± 0.97a 23.70 ± 0.14b
Light Time 22.92 ± 1.07a 21.85 ± 0.08a 20.86 ± 0.79a 21.34 ± 1.00a 27.30 ± 1.11b 22.37 ± 0.55a 25.16 ± 0.91b 20.94 ± 0.36a
C20:2n6 Dark Time 11.09 ± 0.93c 11.07 ± 0.93c 14.51 ± 0.36 cd 11.20 ± 0.52c 5.12 ±.02b 16.95 ± 0.03d 1.29 ± 0.33a 14.13 ± 0.07 cd
Light Time 10.28 ± 0.48b 0.85 ± 0.04a 10.35 ± 0.39b 10.93 ± 0.51b 15.89 ± 0.47d 9.35 ± 0.23b 10.67 ± 0.39bc 8.50 ± 0.16b
C20:3n3 Dark Time ND 0.14 ± 0.03b ND 0.06 ± 0.00a ND ND ND ND
Light Time ND 1.73 ± 0.08c ND 0.09 ± 0.00a ND 0.18 ± 0.00ab ND ND
C20:3n5 Dark Time ND ND 2.55 ± 0.11c ND ND ND 0.18 ± 0.00b 0.08 ± 0.03a
Light Time ND ND 0.04 ± 0.00a ND ND ND 0.08 ± 0.00a ND

Non-identical letters in each column indicate significance between treatments (P < 0.05).

Linolenic acid (C18: 3n3) had the highest value during the dark period in treatments 3 (27.27 ± 0.80) and 5 (26.26 ± 0.13) and in treatment 7 (13.42 ± 0.97) Had the lowest value and no significant difference was observed between any of the treatments except treatment 7 (p < 0.05). Treatments 1 and 2 were completely free of these fatty acids. During the lighting period, the highest value was observed in treatment 5 (20.86 ± 0.79) and the lowest value was observed in treatment 3 (27.30 ± 1.11). Also, differences between treatments 1, 2, 3, 4, 6 and 8 were observed, no significance was observed (P < 0.05).

Eicosadienoic acid (C20: 2n6) had the highest and lowest values ​​in treatment 6 (16.95 ± 0.03) and treatment 7 (1.29 ± 0.33), respectively, during the dark period. No significant differences were observed in 1, 2, 3, 4 and 8 (P < 0.05). During the lighting period, the highest value was observed in treatment 5 (15.89 ± 0.47) and the lowest value in treatment 2 (0.85 ± 0.04), also between treatments 1, 3, 4, 6, 7 and 8. No significant difference was observed (P < 0.05).

Eicosatrienoic acid (C20: 3n3) had the highest amount in treatment 2 (0.14 ± 0.03) and the lowest in treatment 4 (0.06 ± 0.00) during the dark period and between treatments 1, 3, 5, 6, 7 and 8 no significant differences were observed (P < 0.05). During the light period in treatments 2 (1.73 ± 0.08) and 4 (0.09 ± 0.00) had the highest and lowest values, respectively, and treatments 1, 3, 5, 7 and 8 lacked this acid. Fats were polyunsaturated.

Finally, Eicosapentanoic acid (EPA) (C20: 3n5) was not observed in treatments 1, 2, 4, 5 and 6 of the dark shock period. The highest EPA was observed in treatment 3 (2.55 ± 0.11) and the lowest in treatment 8 (0.08 ± 0.03) during dark shock. On the other hand, during light shock, the highest value of EPA was the highest in treatment 3 (0.04 ± 0.00) and the lowest in treatment 7 (0.08 ± 0.00), also in treatments 1, 2, 4, 5, 6 and 8 of this fatty acid were not observed. According to the results observed in Dunaliella tertiolecta, the amount of fatty acids in the dark shock was higher than the light shock.

3.5

3.5 Quality of fat and biofuels produced

The results obtained on the quality characteristics of fats and biofuels extracted from the microalga Dunaliella tertiolecta are given in Table 7. According to the results regarding the number of sapnification value, no significant difference was observed between different treatments during dark shock (P < 0.05), but slightly treatment 5 (31.25 ± 1.06) was the highest and treatment 1 (62.00 ± 30.95) had the lowest value. The number of saponification during light shock did not show a significant difference between different treatments (P < 0.05), but slightly the highest value in treatment 3 (31.95 ± 0.85) and the lowest value in treatment 8 (95.30 ± 1.06) was observed. The results obtained for iodine value during dark shock showed the highest value in treatment 5 (125.00 ± 14.35) and the lowest value in treatment 2 (124.18 ± 12.32), Also, no significant differences were observed between treatments 2, 3, 4, 6, 7 and 8 (P < 0.05). Iodine number during light shock did not show a significant difference between different treatments (P < 0.05), but slightly 1 (124.90 ± 2.15) and 8 (123.82 ± 11.24) treatments were the most and They had the lowest values.

Table 7 Quality of fat and biofuels obtained from Dunaliella Tertiolecta microalga.
Time Treatments ( μ g g - 1 )
1 2 3 4 5 6 7 8
Saponification value Dark Time 30.95 ± 0.62a 31.04 ± 0.35b 31.18 ± 2.01b 31.11 ± 1.02b 31.25 ± 1.06b 31.20 ± 0.35b 31.23 ± 0.14b 31.13 ± 1.02b
Light Time 31.28 ± 0.28b 31.09 ± 1.02b 31.95 ± 0.85b 31.16 ± 2.30b 31.15 ± 0.61b 31.15 ± 0.04b 31.03 ± 0.25b 30.95 ± 1.06a
Iodine value Dark Time 123.83 ± 1.20a 124.18 ± 12.32b 124.71 ± 11.05b 124.46 ± 11.08b 125.00 ± 14.35c 124.79 ± 9.58b 124.94 ± 10.35b 124.54 ± 9.62b
Light Time 124.90 ± 2.15b 124.39 ± 21.32b 124.65 ± 10.14b 124.65 ± 13.00b 124.59 ± 9.68b 124.63 ± 10.25b 124.14 ± 10.20b 123.82 ± 11.24a
Cetane number Dark Time 2509.40 ± 36.54d 1701.52 ± 23.65a 1786.26 ± 34.05a 1865.86 ± 26.51b 1925.50 ± 30.14c 1731.63 ± 22.02a 1969.03 ± 24.15c 1779.26 ± 24.65a
Light Time 1701.52 ± 26.51a 1952.88 ± 26.34c 1831.26 ± 12.65b 2137.92 ± 24.68 cd 1771.58 ± 16.85a 1746.60 ± 30.01a 1719.28 ± 36.52a 2713.52 ± 46.25d
Degree of unsaturation Dark Time 57.74 ± 1.62a 97.28 ± 6.21d 113.40 ± 2.63e 92.19 ± 3.14c 82.07 ± 2.65c 109.10 ± 2.65e 78.26 ± 3.17b 99.94 ± 3.52d
Light Time 93.51 ± 2.62d 71.59 ± 2.15a 88.98 ± 1.65bc 82.85 ± 3.12b 111.10 ± 3.14f 89.86 ± 3.51bc 99.26 ± 2.58e 74.55 ± 3.51a

Non-identical letters in each column indicate significance between treatments (P < 0.05).

Cetane number had the highest value during dark shock in treatment 5 (2509.40 ± 36.54) and the lowest value in treatment 2 (1701.52 ± 65.23) and between treatments 2, 3, 6 And 8 no significant differences were observed (P < 0.05). During light shock, the value of cetane number in treatment 8 (2713.52 ± 00) had the highest value and in treatment 1 (1701.52 ± 52.26) had the lowest value and a significant difference was observed between treatments 1, 5, 6 and 8.

Degree of unsaturation was highest during dark shock in treatment 3 (113.40 ± 2.63) and lowest in treatment 1 (57.74 ± 1.62) and between treatments 2 and 8. No significant difference was observed (P < 0.05). During light shock, the degree of unsaturation was the highest in treatment 5 (111.10 ± 3.14) and the lowest in treatment 2 (71.59 ± 2.15). Also, no significant difference was observed between treatments 3, 4 and 6 (P < 0.05).

3.6

3.6 Effect of pressure and temperature on extracted oil by C O 2 supercritical fluid method

According to Table 8, the amount of fatty acids extracted from Dunaliella tertiolecta microalga using supercritical C O 2 solution under different temperatures and pressures showed the best results in the optimal treatment at 370 b a r and 40 °C, as well as the weakest and lowest amount of fat and fuel under A pressure of 200 b a r and a temperature of 80 °C were obtained. Andrich et al. (Andrich et al., 2005) use of Nannochloropsis sp. with extraction pressure of 400 bar, 40 °C and, C O 2 flow rate 0.17 k g m i n - 1 , their results showed: at constant temperature, lipid extraction rate increased with pressure; at constant pressure, lipid extraction rate slightly increased with temperature, final total lipid yield was the same at any temperature and pressure (25 w t . % of dried microalgal biomass). A comparison of the results of using different microalga is presented in Table 9.

Table 8 Quality of fat and biofuels obtained from Dunaliella Tertiolecta microalga.
Fatty Acid (w/w %) Control Optimal treatment
200 bar
40 °C
285 bar
40 °C
370 bar
40 °C
200 bar
80 °C
285 bar
80 °C
370 bar
80 °C
200 bar
40 °C
285 bar
40 °C
370 bar
40 °C
200 bar
80 °C
285 bar
80 °C
370 bar
80 °C
C12:0
Lauric acid
1.56 1.70 2.17 0.93 1.21 1.38 3.15 3.29 3.76 2.52 2.81 2.98
C14:0
Myristic acid
3.32 3.42 3.59 2.23 2.27 2.60 4.92 5.01 5.18 3.82 3.86 4.20
C16:0
Palmitic acid
26.99 27.39 28.51 25.12 26.01 26.51 28.59 28.99 30.10 26.71 27.60 28.11
C18:0
Stearic acid
28.11 29.24 30.73 24.83 25.37 27.32 29.70 30.84 32.32 26.42 26.97 28.91
C20:0
Arachidic acid
1.00 1.27 1.60 0.14 0.37 0.45 2.59 2.86 3.19 1.74 1.97 2.04
C16:1n7
Palmitoleic acid
0.88 1.20 1.49 0.37 0.63 1.18 2.47 2.79 3.09 1.97 2.22 2.77
C18:1n9Oleic acid
(Trance)
1.30 1.61 2.02 0.68 0.75 1.13 2.90 3.21 3.61 2.28 2.35 2.72
C18:2n6Linoleic acid
(LA)
0.22 0.45 0.61 0.10 0.15 0.17 1.82 2.04 2.20 1.69 1.74 1.77
C20:5n3
Eicosapentaenoic acid (EPA)
2.28 2.44 2.66 1.70 1.81 1.90 3.87 4.04 4.25 3.30 3.40 3.50
C22:6n3Docosahexaenoic acid
(DHA)
0.46 0.55 0.85 0.12 0.19 0.26 2.05 2.15 2.44 1.72 1.79 1.85
Table 9 Comparison of process conditions and results of using different microalga (Halim et al., 2012).
Microalgal species P (bar) T (°C) C O 2 flow rate; extraction duration ( m i n ) Polar modifier; quantity of polar modifier Results Final total lipid yield ( w t . % )
Spirulina platensis 316 40 0.71 k g m i n - 1 ; 60 Ethanol; 9.64, 11, 13, 15, 16.36 ml Total lipid yield increased with P. Optimum condition was found at 400 bar, 60 min, and 13.7 ml ethanol. 8.6
Spirulina maxima 250 50 Ethanol; 10 mol% of C O 2 At constant T, total lipid yield increased with P.At constant P, total lipid yield decreased with
T.At
constant T and P, polar modifier addition significantly increased total lipid yield.
Optimum condition was found at 350 bar, 60 °C with ethanol addition (10 mol%).
3.1
Hypnea charoides 310 50 1 l m i n - 1 ; 120 At constant T, total lipid yield increased with P.At low P
(241 bar), total lipid yield decreased with T.At medium to high P
(310 and 379 bar), total lipid yield increased with T.
Optimum condition was found at 379 bar and 50 °C.
6.7
Chlorella vulgaris 350 55 0.4 l m i n - 1 ; 500 At constant T, total lipid yield increased with P.At low P
(200 bar), total lipid yield decreased with T.At high P
(350 bar), total lipid yield increased with T.
Optimum condition was found at 350 bar and 55 °C.
13

4

4 Conclusion

Based on the results obtained on growth indices, it was found that with increasing the amount of SGR and C O 2 consumption rate, the amount of biomass production in Dunaliella Tertiolecta microalga increased so that the number of production cells also increased. The pH value also increased during the breeding period and decreased in the last days of breeding. According to the results obtained for approximate compounds, the lipid content was higher in nutrient-free treatments and the results were the opposite for protein. Based on the results obtained for chlorophyll a, b and carotenoids, it was also found that the higher the growth of algae, the higher their amount. The results related to fatty acids also showed that the amount of saturated and monounsaturated fatty acids in microalga was higher and more diverse than PUFAs. According to the results obtained in terms of quality characteristics, the produced fuel has high cetane number and low saturation degree, also provided good combustion quality and oxidative stability.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. Andreo-Martínez, P., Ortiz-Martínez, V.M., García-Martínez, N., de los Ríos, A.P., Hernández-Fernández, F.J., Quesada-Medina, J., 2020. Production of biodiesel under supercritical conditions: State of the art and bibliometric analysis. Appl. Energy 264, 114753. https://doi.org/10.1016/j.apenergy.2020.114753.
  2. , , , , , . Supercritical fluid extraction of bioactive lipids from the microalga Nannochloropsis sp. Eur. J. Lipid Sci. Technol.. 2005;107:381-386.
    [CrossRef] [Google Scholar]
  3. , , . Environmental Technology & Innovation Biosorption, an efficient method for removing heavy metals from industrial effluents : A Review. Environ. Technol. Innov.. 2020;17:100503
    [CrossRef] [Google Scholar]
  4. , , , , . In situ catalyst-free biodiesel production from partially wet microalgae treated with mixed methanol and castor oil containing pressurized CO2. J. Supercrit. Fluids. 2020;157:104702
    [CrossRef] [Google Scholar]
  5. , , , . Sequential extraction of lutein and β-carotene from wet microalgal biomass. J. Chem. Technol. Biotechnol.. 2020;95:3024-3033.
    [CrossRef] [Google Scholar]
  6. , , , , , , . Biodiesel production from microalgae: Processes, technologies and recent advancements. Renew. Sustain. Energy Rev.. 2017;79:893-913.
    [CrossRef] [Google Scholar]
  7. , , , , , , , , . Bioremediation of textile wastewater and successive biodiesel production using microalgae. Renew. Sustain. Energy Rev.. 2018;82:3107-3126.
    [CrossRef] [Google Scholar]
  8. , , , , , , . Sustainability of direct biodiesel synthesis from microalgae biomass: A critical review. Renew. Sustain. Energy Rev.. 2019;107:59-74.
    [CrossRef] [Google Scholar]
  9. , , , , , , . Integrated biodiesel and biogas production from microalgae: Towards a sustainable closed loop through nutrient recycling. Renew. Sustain. Energy Rev.. 2018;82:1137-1148.
    [CrossRef] [Google Scholar]
  10. , , , . Extraction of oil from microalgae for biodiesel production: A review. Biotechnol. Adv.. 2012;30:709-732.
    [CrossRef] [Google Scholar]
  11. , , , . Microalgae biodiesel: Current status and future needs for engine performance and emissions. Renew. Sustain. Energy Rev.. 2017;79:1160-1170.
    [CrossRef] [Google Scholar]
  12. , . The issue of reducing or removing phospholipids from total lipids of a microalgae and an oleaginous fungus for preparing biodiesel. Biofuels. 2016;7:55-72.
    [CrossRef] [Google Scholar]
  13. , , , , , , , , , , . Simultaneous harvesting and cell disruption of microalgae using ozone bubbles: optimization and characterization study for biodiesel production. Front. Chem. Sci. Eng.. 2021;15:1257-1268.
    [CrossRef] [Google Scholar]
  14. , , , , , , , . Efficient extraction of hydrophilic and lipophilic antioxidants from microalgae with supramolecular solvents. Sep. Purif. Technol.. 2020;251:117327
    [CrossRef] [Google Scholar]
  15. , , , , , , . Optimization of protein extraction from Chlorella Vulgaris via novel sugaring-out assisted liquid biphasic electric flotation system. Eng. Life Sci.. 2019;19:968-977.
    [CrossRef] [Google Scholar]
  16. Leone, G.P., Balducchi, R., Mehariya, S., Martino, M., Larocca, V., Sanzo, G. Di, Iovine, A., Casella, P., Marino, T., Karatza, D., Chianese, S., Musmarra, D., Molino, A., 2019. Selective extraction of ω-3 fatty acids from nannochloropsis sp. using supercritical CO2 Extraction. Molecules 24. https://doi.org/10.3390/molecules24132406.
  17. Liu, W. ping, Yin, X. fei, 2017. Recovery of copper from copper slag using a microbial fuel cell and characterization of its electrogenesis. Int. J. Miner. Metall. Mater. 24, 621–626. https://doi.org/10.1007/s12613-017-1444-z.
  18. , , . A comprehensive review on harvesting of microalgae for biodiesel - Key challenges and future directions. Renew. Sustain. Energy Rev.. 2018;91:1103-1120.
    [CrossRef] [Google Scholar]
  19. , , , , . Supercritical carbon dioxide treatment of the microalgae Nannochloropsis oculata for the production of fatty acid methyl esters. J. Supercrit. Fluids. 2016;116:264-270.
    [CrossRef] [Google Scholar]
  20. , , , , , , , , . Modern developmental aspects in the field of economical harvesting and biodiesel production from microalgae biomass. Renew. Sustain. Energy Rev.. 2021;135:110209
    [CrossRef] [Google Scholar]
  21. , , , , , , . Spectrophotometric determination of insuline by ternary complex formation with o-carboxyphenylfluorone-copper(II) complex. Bunseki Kagaku. 2007;56:781-784.
    [CrossRef] [Google Scholar]
  22. , , , , , , , , . High biodiesel yield from wet microalgae paste via in-situ transesterification: Effect of reaction parameters towards the selectivity of fatty acid esters. Fuel. 2020;272:117718
    [CrossRef] [Google Scholar]
  23. Ortiz-Martínez, V.M., Andreo-Martínez, P., García-Martínez, N., Pérez de los Ríos, A., Hernández-Fernández, F.J., Quesada-Medina, J., 2019. Approach to biodiesel production from microalgae under supercritical conditions by the PRISMA method. Fuel Process. Technol. 191, 211–222. https://doi.org/10.1016/j.fuproc.2019.03.031.
  24. , , , , , , , , , , . Review of biodiesel synthesis technologies, current trends, yield influencing factors and economical analysis of supercritical process. J. Clean. Prod.. 2021;309:127388
    [CrossRef] [Google Scholar]
  25. , , . Efficacy of unmodified and chemically modified Swietenia mahagoni shells for the removal of hexavalent chromium from simulated wastewater. J. Mol. Liq.. 2015;209:487-497.
    [CrossRef] [Google Scholar]
  26. , , , . Biological hydrogen production via dark fermentation by using a side-stream dynamic membrane bioreactor: Effect of substrate concentration. Chem. Eng. J.. 2018;349:719-727.
    [CrossRef] [Google Scholar]
  27. , , , , . Supercritical carbon dioxide extraction of algal lipids for the biodiesel production. Procedia Eng.. 2012;42:1755-1761.
    [CrossRef] [Google Scholar]
  28. , , . Life cycle assessment of biodiesel from estuarine microalgae. Energy Convers. Manage.. 2020;X 8:100065
    [CrossRef] [Google Scholar]
  29. , , , . Evaluating the industrial potential of biodiesel from a microalgae heterotrophic culture: Scale-up and economics. Biochem. Eng. J.. 2012;63:104-115.
    [CrossRef] [Google Scholar]
  30. , , , , , , , . A review on microalgae cultivation and harvesting, and their biomass extraction processing using ionic liquids. Bioengineered. 2020;11:116-129.
    [CrossRef] [Google Scholar]
  31. , , , , , , . Cultivation of microalgae for biodiesel production: A review on upstream and downstream processing. Chinese J. Chem. Eng.. 2018;26:17-30.
    [CrossRef] [Google Scholar]
  32. , , . Supercritical transesterification of microalgae triglycerides for biodiesel production: Effect of alcohol type and co-solvent. J. Supercrit. Fluids. 2018;137:50-56.
    [CrossRef] [Google Scholar]
  33. , , , , . Current advances in microalgae harvesting and lipid extraction processes for improved biodiesel production: A review. Renew. Sustain. Energy Rev.. 2021;137:110498
    [CrossRef] [Google Scholar]
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