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Spirulina (Spirulina platensis) Production in Different Photobioreactors on Rooftop

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INTERNATIONAL JOURNAL OF BUSINESS, SOCIAL AND SCIENTIFIC RESEARCH ISSN: 2309-7892 (Online), 2519-5530 (Print), Volume: 8, Issue: 1, Page: 15–19, January-June 2020

Review Paper SPIRULINA (Spirulina platensis) PRODUCTION IN DIFFERENT PHOTOBIOREACTORS ON ROOFTOP

*AFM Jamal Uddin;1O. Gani; A.K. Mahato; I. Sakib and M. Rakibuzzaman

[Citation: AFM Jamal Uddin; O. Gani; A.K. Mahato; I. Sakib and M. Rakibuzzaman (2020). Spirulina (Spirulina platensis) Production in Different Photobioreactors on Rooftop. Int. J. Bus. Soc. Sci. Res. 8(1): 15–19. Retrieve from http://www.ijbssr.com/currentissueview/14013346] Received Date: 05/02/2020 Acceptance Date: 15/02/2020 Published Date: 15/02/2020

Abstract An experiment was accomplished on the rooftop of Faculty of Agriculture, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh to screen some Photobioreactors for finding out more economically convenient and easily available one for spirulina production in Bangladesh. Four types of photobioreactors, viz., Rectangular shaped 5L photobioreactor (PBR1), Cuboidal shaped 3L Photobioreactor (PBR2), Cylindrical shaped 15L Photobioreactor (PBR3), Rectangular shaped 15L Photobioreactor (PBR4) were used in this experiment following Completely Randomized Design (CRD) with three replications. Fifteen days of production was carried out in the selected photobioreactors to determine the performance of the PBRs where culture condition were kept the same and data on different growth and yield parameters were taken throughout the experiment to which all the PBRs showed significant variations. Among photobioreactors, growth doubling require (3.41 days), maximum productivity (0.90 gL-1day-1) and the highest marketable yield (3.34 kg/kl) - were found in PBR4 while maximum doubling time (10.63 days) with lower productivity (0.40gL 1 -1 day ) and minimum marketable yield (1.64 kg/kl) in PBR2. So, 15L rectangular shaped Photobioreactor will be the promising photobioreactor for spirulina cultivation in Bangladesh. Key words: Photobioreactor, Super food, Rooftop,Spirulina production Introduction Spirulina (Spirulina platensis) belongs to the family Spirulinaceae is a free floating filamentous microalgae belonging to the class Cyanobacteria (Komarek and Hauer 2009). Spirulina is an ecologically sound, nutrient rich super food that is grown all around the world as a dietary supplement. Spirulina is considered as the “food of the future” that will effectively tackle the existing malnutrition problem (Jamal uddin et al., 2018) and it is high time to give most priority to produce spirulina for consumption. The main barriers of quality spirulina production are contamination, PH maintenance, growth rate, productivity and photosynthetic efficiency with the cost of growth chamber. Spirulina is a phototrophic organism that’s why it is mainly cultivated in different photobioreactors such as Vertical, Horizontal and Flat Plane photobioreactor. A photobioreactor is a bioreactor that utilizes a light source to cultivate phototrophic microorganisms. These organisms use photosynthesis to generate biomass from light and carbon dioxide and include plants, mosses, macro algae, cyanobacteria and purple bacteria. Photobioreactor enables the consumer to cultivate and consume fresh spirulina, minimizes the loss of nutrients after drying process, and leads to high-grade nourishing health foods (Li et al., 2004). The cylindrical photobioreactors are widely used because their design is simple and easy to scale for large volumes of several hundred liters (Tsygankov, 2001). Quality spirulinaproduction depends on photobioreactor types and designs both for large as well as small scale production. Therefore the present study is to evaluate the suitable and cost effective photobioreactors for growth, productivity and yield of quality spirulina production. Methods and materials Installation of the photobioreactors Thirty photobioreactors were vertically placed on an iron made bench, food grade silicon tubes were coming out from a central PVC pipe which was directly connected with a motor (RESUN ACO 006) and were linked to photobioreactors for air circulation and agitation. The air circulation was continued at one our interval automatically by using timer. Chlorination and dechlorination of photobioreactor

The Chlorination of photobioreactor was carried out @ 0.02g/L H2O and dechlorination of photobioreactor was done using ascorbic acid (0.04g/L), with bubbling for 24 hours. Media preparation and strain inoculation The culture medium was prepared by making four types of solution separately in four 1000 ml Erlenmeyer flasks for making 180 liters of culture medium. This volume was diluted with filtrated water to obtain the

*Corresponding Author’s email: [email protected] Department of Horticulture, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh Copyright©IJBSSR, Hello-Teen Society and Agrofoundation, Bangladesh and Authors, This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Spirulina (Spirulina platensis) Production in Rooftop 16 initial intended concentration. The initial concentration of each solution is obtained using the dry biomass weight method. Then the culture medium was prepared in a 500L plastic container by pouring the solution sequentially for 180 liters of culture medium.Spirulina strain selected and the media was inoculated with 0.75g/l fresh weight basis. Growth measurement The efficiency of algae biomass growth was measured due to optical density, defined as the absorption of visible radiation at 560 nm through the spectrophotometer. The specific growth rate (SGR, µ/day) of cultured microalgae was calculated by the following equation (Clesceri et al., 1989).

SGR (µ/day) = ln (X1- X2)/ t2 - t1 Where,

X1 = Biomass concentration at the end of selected time interval, X2 = Biomass concentration at the beginning of selected time interval, And, t2 -t1= Elapsed time between selected time in day.

The biomass doubling time (td, d) was calculated using natural logarithms (ln) as td = ln2/ μmax(Bailey and -1 -1 Ollis, 1986). The maximum productivity (Pmax, gL d ) calculated from the equation,

P = (Xt - X0)/ (t - t0) Where, Xt is the biomass concentration at time t (d) X0 is the initial biomass concentration at t0 (Schmidell et al., 2001). Statistical and Economical Analysis Collected data were tabulated and analyzed using MSTAT-C computer package programme and difference between treatments was assessed by Least Significant Difference (LSD) test at 5% level of significance (Gomez and Gomez, 1989).The cost of production was analyzed in order to find out the most economical solution of production unit means photobioreactor. Current market price of spirulina was considered for the cost and return. Gross return per 1000L Benefit Cost Ratio (BCR) = Total cost of production per 1000L Result and Discussion Optical Density (OD) Significant variation was observed among the photobioreactors in case of optical density at maturity. The highest Optical Density was observed in PBR4 (1.56) followed by PBR1 (1.31) and the lowest was in PBR2 (0.96) (Fig. 1). Similar trend of results was also observed by Saranraj et al. (2013).Light interception, foaming, environmental factors and competition of other algae plays an important role to regulate Optical Density (OD) along with it’s over all performances.

PBR1 PBR2 PBR3 PBR4 1.80 1.60 1.40 1.20 1.00 0.80 0.60 0.40 Optical density at 560 nm 560 at density Optical 0.20 0.00 2 DAI 4 DAI 6 DAI 8 DAI 10 DAI 12 DAI Day after inoculation (DAI)

Fig. 1. Performance of photobioreactors on optical density at different days after inoculation Specific Growth rate Growth rate showed significant variation in different photobioreactors used under study. Highest average growth rate was observed in PBR4 (2.48) and the lowest was observed in PBR2 (0.977) (Fig. 2.a). Suphi et al. (2006) found variation in specific growth rate in integrated type of photobioreactor.

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Doubling time Doubling time showed significant inequality in different photobioreactors under study. Minimum days required for doubling was observed in PBR4 (3.41) and maximum days of doubling time was observed by PBR1 (10.63) followed by PBR2 (8.02) (Fig. 2.b). Doucha and Livansky (2009) also showed similar variation in case of cultivation of spirulina in close and open bioreactor. He found variation in case of doubling time. Light interception may plays an important role doubling time towards the total productivity of spirulina. 3 14 2.5 12 10 2 8 1.5 6 1

4 growth (%) rate growth

0.5 2 Doubling (days) time Doubling 0 0 Specific PBR1 PBR2 PBR3 PBR4 PBR1 PBR2 PBR3 PBR4 Photobioreactors Photobioreactors (a) (b)

Fig. 2. Performances of photobioreactors on (a) specific growth rate, and (b) doubling time

Fresh weight Harvested fresh biomass at three times and every times it varied significantly in different photobioreactors. The highest biomass content collected on fresh weight basis was observed in PBR1 (14.44 g/l), (12.44 g/l) and (9.01 g/l) whereas the lowest weight was observed in PBR2 (5.40 g/l), (5.08 g/l) and (3.97 g/l) successively (Table 1). Richmond et al. (1990) also found the similar kind of variation on biomass production. Dry weight Significant variation was found in case of dry weightamong different photobioreactors). Highest amount of dry weightwas observed in PBR4 (1.19 g/l), (1.22 g/l) and (0.91 g/l) and the lowest was found in PBR2 (0.53 g/l), (0.44 g/l) and (0.40 g/l) respectively (Table 1). Variation in dry weight was also observed in a laboratory scale integrated type of photobioreactorby Suphi et al. (2006). Table 1. Performances of photobioreactors on fresh wt. and dry wt. of Spirulina 1st fresh 2nd fresh 3rd fresh 1st dry wt. 2nd dry 3rd dry wt. Photobioreactors wt. (g/l) wt. (g/l) wt. (g/l) (g/l) wt. (g/l) (g/l) PBR1 9.75 b 8.08 b 6.98 ab 0.72 b 0.82 b 0.77 b PBR2 5.4 d 5.09 d 3.97 c 0.53 c 0.44 d 0.4 d PBR3 7.07 c 6.17 c 5.05 bc 0.65 bc 0.61 c 0.63 c PBR4 14.44 a 12.64 a 9.01 a 1.19 a 1.22 a 0.91 a LSD 0.05 1.51 1.07 1.29 0.16 0.11 0.13 CV% 8.24 6.70 10.32 10.06 7.00 10.20 Table 2. Performance of photobioreactors on productivity of spirulina at different times Ist productivity Ist productivity Ist productivity Photobioreactors (gL-1day-1) (gL-1day-1) (gL-1day-1)

PBR1 0.53 b 0.64 b 0.77 b PBR2 0.41 c 0.4 c 0.4 c PBR3 0.55 b 0.51 bc 0.63 b PBR4 0.9 a 0.87 a 0.91 a LSD 0.05 0.11 0.19 0.09 CV% 0.10 0.15 0.09 Productivity

Different photobioreactors displayed significant non-uniformity in case of productivity. PBR4 showed the highest productivity (0.90), (0.87) and (0.91) and the lowest was observed in PBR2 (0.41), (0.40) and (0.40)successively at each three harvest (Table 2).Similar variation in productivity was observed by

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Reichert et al. (2006) in two-liter Erlenmeyer flasks). Presence of higher productivity and variation in productivity is controlled by photobioreactor quality. Marketable yield/Inoculation Variation in marketable yield was observed among the different photobioreactors used for spirulina cultivation. The highest marketable yield was found in PBR4 (3.34kg) and the lowest was observed in PBR1 (1.64kg) (Fig. 3). Similar result was recorded by a report by Indian Ocean Commission (2016).

4.00 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00

PBR1 PBR2 PBR3 PBR4 Total Total (kg/1000L) marketable yield Photobioreactors

Fig. 3. Photobioreactor performances on marketable yield of spirulina Economic analysis Input cost for materials and non-materialswere recorded as per 1000L inoculation. Price of spirulina was considered as per market rate. The economic analysis is presented under the following heading- Gross return Different photobioreactors showed different values in terms of gross return (Table 3). The highest gross return (Tk.66800.00) was obtained from the PBR4 and the lowest gross return (Tk.32800.00) was obtained from PBR2 in first month. Net return

In case of net return, only PBR4showed positive net returns but others showed losses in first month (Table 5) but the losses could be minimized with the consecutive month’s productionbecause there is no cost in next two consecutive returns in case of small scale culture (Table 3). Benefit cost ratio (BCR)

The highest benefit cost ratio was noted (1.82) from PBR4 and the lowest benefit cost ratio was observed in PBR2 (0.64) in case of first month (Table 3). The highest benefit cost ratio was noted (5.06) from PBR4 and the lowest benefit cost ratio was observed in PBR2 (2.49) in case of 2nd month (Table 3). Therefore, it is apparent that PBR4 was better than the rest of the photobioreactors from the economic point of view as well. Table 3. Cost and return of spirulinaproduction in photobioreactor for 1stmonth and from 2nd month For 1st month from 2nd month Marketable Gross Benefit Benefit Net Net Photobioreactors yield return Total cost cost Total cost return return (kg/1000L) (tk) (tk) ratio cost (tk) ratio (tk) (tk) (BCR) (BCR) PBR1 1.9 38800.00 49486.00 -10686 0.78 13186.00 25614.00 2.94 PBR2 1.6 32800.00 51386.00 -18586 0.64 13186.00 19614.00 2.49 PBR3 1.9 38200.00 44686.00 -6486 0.85 13186.00 25014.00 2.90 PBR4 3.3 66800.00 36686.00 30114 1.82 13186.00 53614.00 5.06 Conclusion It can be concluded that, Rectangular shaped 15L Photobioreactor has potential productivity and higher marketable yield including quick doubling times for quality spirulina production over rest of photobioreactors. So, Rectangular shaped 15L Photobioreactor has the promise to acquire a core position in the commercial spirulina production market in a very short time.

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Acknowledgement: We gratefully thank University Grant Commission (UGC) of Bangladesh for providing the financial support for the research work (Crop-19/2018/7419) References Bailey, J.E., and Ollis, D.F. (1986),.Biochemical Engineering Fundamentals, 2nd ed. McGraw-Hill, Singapore. Clesceri, L.S., Greenberg A.E. and Trussell R.R. (1989).Standard Methods for the Examination of Water and Wastewater. American Public Health Association, American Water Works Association and Water Pollution Control Federation; New York. USA. 92-1110. Doucha, J. and Livansky, K. (2009). Outdoor open thin-layer microalgalphotobioreactor: potential productivity. J. of Applied Phycol.,21: 111-117. Gomez, K.A. and Gomez, A.A. (1984).Statistical Procedure for Agricultural Research.John Willey and Sons Ltd. New York. 28-192. Indian Ocean Commission. (June /July 2012). Spirulina - A Livelihood and a Business Venture. REPORT/RAPPORT: SF/2012/16. Smart Fish Programme, P43. Jamal Uddin, A.F.M., Mahbuba, S., Rahul, Sk., Ifaz, M.I. and Ahmad, H. (2018). Super Food Spirulina (Spirulinaplatensis): Prospect and Scopes in Bangladesh. Int. J. Bus. Soc. Sci. Res.,6(2): 51-55. Komarek, J. and Hauer, T. (2009).Worldwide electronic publication. Univ. of South Bohemia and Inst of Botany AS CR; CyanoDB.Cz- On-line database of cyanobacterial genera. Li, Hengguang, Hu, Hongjun, Chen and Yinglong.(2004). Methods of cultivating Fresh spirulina at Home and Device Thereof.United States Patent, US 6,698,134. Reichert, C.C., Reinehr, C.O. and CostaJ.A.V. (2006).Semi continuous cultivation of the cyanobacterium Spirulinaplatensis in a closed photobioreactor. Braz. J. Chem. Eng., 23(1): 1678- 4383. Richmond, A., Lichtenberg, E., Stahl, B. and Vonshak, A. (1990). Quantitative assessment of the major limitations on productivity of Spirulinaplatensis in open raceways. J.of Applied Phycol.,2: 195- 206. Saranraj, P., Stella, D., Usharani, G. and Sivasakthi, S. (2013). Effective Recycling of Lignite Fly Ash for the Laboratory Cultivation of Blue Green Algae-Spirulinaplatensis. Intl. J., 4(3):219-226. Schmidell, W., Lima, A.U., Aquarone, E., and Borzani, W. (2001). Biotecnologia Industrial, vol 2. Edgard Blücher, Sao Paulo. Suphi, S., Oncel, S. and Oguz, A. (2006).An integrated photobioreactor system for the production of spirulinaplatensis. Biotechnology, 5(3):365-372. Tsygankov, A.A. (2001). Laboratory Scale Photobioreactors. Applied Biochem.andMicrobiol., 37:333- 341.

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