Next Article in Journal
Influence of Load Conditions on the Propeller Wake Evolution
Previous Article in Journal
Global Sound Absorption Prediction for a Composite Coating Laid on an Underwater Submersible in Debonding States
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Quantity and Quality of Light on Growth and Pigment Content of Dunaliella sp. and Anabaena sp. Cultures and the Use of Their Absorption Spectra as a Proxy Method for Assessment

Plankton Culture Laboratory, Department of Fisheries and Aquaculture, University of Patras, 30200 Messolonghi, Greece
J. Mar. Sci. Eng. 2023, 11(9), 1673; https://doi.org/10.3390/jmse11091673
Submission received: 9 July 2023 / Revised: 14 August 2023 / Accepted: 23 August 2023 / Published: 25 August 2023
(This article belongs to the Section Marine Biology)

Abstract

:
(1) Background: As microalgae cultures are affected by the quantity and quality of light, I explored this for two species. Additionally, I introduced a novel easy and economical way for the growers to easily and economically ascertain continuously with satisfactory accuracy the quantitative and qualitative status of their culture using absorption spectra. (2) Methods: The locally isolated chlorophyte Dunaliella sp. and the cyanobacterium Anabaena sp. were cultured in small volumes with two intensities of white light (2000 and 8000 lux) and with green, blue and red light, and the increase in their biomass and pigments was studied. Pigment analyses, continuous recordings of absorption spectra and calibration curves were used. (3) Results: The intensity of 8000 lux of white light yielded the highest increase in biomass, chlorophylls and carotenoids in Dunaliella sp., and the same was found for green and blue light, while 2000 lux and green light caused the greatest increase in biomass and phycocyanin in Anabaena sp. From the absorption spectra, the evolution of the pigment content can be estimated, and both pigments and biomass are correlated very strongly with those extracted from the spectra absorption of 750 nm. (4) Conclusions: The use of absorption spectra as an easy, fast and economical method can be a useful tool for a good approximation of the state of the microalgae culture. This is clearly shown when the spectra of the cultures under different light intensities and colors are compared having a catalytic effect on the level of the pigments leading to the increase in carotenoids and phycocyanin of the green light.

1. Introduction

Microalgae are a widespread and rapidly growing branch of primary production, as they offer many and important advantages in terms of biomass production [1,2,3,4]. From an ecological point of view, they can contribute significantly to curbing anthropogenic carbon emissions, becoming a useful tool in the arsenal of climate change mitigation [5,6]. In particular, the cultivation of marine species compares favorably with both freshwater species and grass crops, both because valuable irrigation resources are not lost and because it is possible to use coastal or degraded saline soils for cultivation [7]. In many countries of the world, the cultivation of marine microalgae serves productive purposes in a wide range of applications, from live food in fish hatcheries, feed production, biofuel production, soil remediation and fertilization, water decontamination, chemical production and pharmaceutical and cosmetic substances to direct human consumption and the production of valuable antioxidant pigments [8,9,10,11,12].
Increased productivity during the cultivation of algae may result from lighting modification [13,14]. Chlorophylls, carotenoids and phycobiliproteins are the three main families of microalgal pigments. The latter are only found in some eukaryotic species like glaucophytes, red algae and some cryptomonads, as well as prokaryotic algae (cyanobacteria) [15,16]. Chlorophylls are the most significant group of light-harvesting pigments found in all microalgae [13]. For these pigments that make up the photosynthetic machinery of algae (chlorophylls, carotenoids, phycobiliproteins), a thriving industry has developed, producing ever-increasing quantities of pigments that have been shown to have beneficial effects on human health [17,18,19]. For example, the carotenes and xanthophylls found in all microalgae (eukaryotes and cyanobacteria), as well as the phycocyanin of cyanobacteria, have potent antioxidant and possibly anticancer effects [20]. The content of photosynthetic units of cells in relation to their pigment composition differs between different species of microalgae, and for this reason, growers have selected certain species known to overproduce some of them [19]. Well-known cases are the species of the genus Dunaliella for the production of β-carotene [21,22] and Arthrospira (Spirulina) for phycocyanin [23,24]. However, even for species selected for cultivation, there is much scope for optimizing and maximizing their pigment content, depending on how some critical conditions for cultivation are modified. Much work has examined the effects of conditions (temperature, salinity, pH, nutrients, light) on the growth rate of the culture, the amount of phyco-biomass produced and the change in cellular constituents in various microalgae. If the goal of cultivation is to maximize the production of either the final biomass or selected constituents, or (what makes most sense) to achieve the ideal combination of both, this should be done simultaneously at the lowest possible cost and, of course, under the desired growth conditions. Undoubtedly, according to many researchers, the quantity and quality of light have a catalytic effect on this process [14]. The intensity of white light has the greatest influence on cell growth and pigment content [25,26,27,28]. Too low an intensity results in a slow increase, while too high an intensity has an inhibitory effect [29,30]. At the same time, the content of cells in terms of the proportions of photosynthetic pigments changes drastically depending on the intensity of illumination [31,32]. In addition to light intensity, color has also been found to have a catalytic effect, especially in the synthesis of the pigments of the photosynthetic apparatus of microalgae [27,33]. Minimizing energy costs for illumination is a critical task in microalgae cultivation since these costs heavily influence the price of chemicals derived from microalgae [34]. Light intensity, illumination duration and the utilization of colored light are the key factors that define the lighting conditions. In microalgal cultures, all these parameters can be intentionally altered in different ways [14]. More and more studies employing photobioreactors using artificial light [14,35,36,37,38,39] are focusing on the effect of colored light on changing photosynthetic pigment ratios [13,40,41]. Therefore, a production scheme with a suitable arrangement of white and colored light is of utmost importance to produce the maximum algal biomass with the maximum yield of desired pigments in the shortest time and with the lowest financial cost. In this sense, any monitoring technique that allows growers to assess the condition of the developing phyco-culture can be a useful tool with predictive value. The absorbance spectrum of a live culture sample can provide valuable information about both the density of the culture and the pigments it contains. However, the absorption spectrum has not been discussed for this purpose in the literature, despite the fact that in practice and under production circumstances, it can offer valuable information about the state of the culture in a straightforward and affordable manner, if not with the accuracy needed for laboratory analysis, at least with a method that meets the general needs of the grower who wants to know the condition of the culture. In the present work, I tried to combine the evaluation of the use of the absorption spectrum as a predictive tool for the density of the culture and the content of the cell in photosynthetic pigments and at the same time to study the effect of the intensity and color of light on the increase in the biomass and cellular pigment composition. For this purpose, locally isolated marine microalgae [42,43], the chlorophyte Dunaliella sp. and the filamentous cyanobacterium Anabaena sp., were chosen for the experiments. These microalgae are either established species in algae cultures (Dunaliella) or species with promising cultivation potential (Anabaena) in the way the well-known cyanobacterium Spirulina is cultivated [44]. In the current work, I examined their absorption spectra under various lighting scenarios, and I combined them with their measured biomass and pigment content in order to, on the one hand, determine the effect of the quantity and quality of light on the culture’s growth and pigment content and, on the other, using appropriately the absorption (Optical Density-OD) values at 750 nm and those corresponding to each of the various pigment peaks extracted from the spectra, in combination with parallel cell density calculation and pigment concentration analyses, to provide growers with a quick and effective method to evaluate culture condition and predict biomass and pigment content with a reasonable degree of accuracy.

2. Materials and Methods

The chlorophyte Dunaliella sp. and the cyanobacterium Anabaena sp. were the marine microalgae species utilized. Both species were isolated during a survey in the lagoonal salty waters (35–55 ppt) of Messolonghi in Western Greece (38°20′05.16″ N, 21°25′28.51″ E) and were maintained as monocultures in the lab (19–20 °C, salinity of 35 ppt, white light of 6000 lux). According to an experimentation protocol, all were batch-cultured indoors (Figure 1) in air-conditioned room at 19–20 °C, at salinity of 35 ppt and at white light intensities of 2000 and 8000 lux. The culture vessels consisted of 1 L conical glass Erlenmeyer flasks, filled to the 1 L mark with previously sterilized sea water enriched with Walne’s medium. The three final stock solutions A, B and C that make up Walne’s medium formula were each used at a ratio of 1 mL per liter of culture water. For essential nutrients N, P and K, 300 g of NaNO3, 20 g of NH4Cl and 30 g of KH2PO4 (Merck, Darmstadt, Germany) were diluted in 1 L of distilled water to create solution A. ZnSO4∙H2O (30 g), CuSO4∙5H2O (25 g), CoSO4∙7H2O (30 g) and MnSO4∙H2O (20 g) are the trace elements (Merck, Darmstadt, Germany) dissolved in 1 L of distilled water to make solution B. Solution C contains 100 mg of vitamin B12, 100 mg of biotin and 10 mg of thiamine (Merck, Darmstadt, Germany) diluted in 1 L of distilled water.
White light emitted by a series of 20 watt 1600 lm LED lamps was used. Intensities of 40 and 160 μmol photons/m2/s (2000 and 8000 lux, respectively) were obtained by placing the vessels at the correct distance from the lamps. Intensity was measured at the center of the outer surface of the vessels using a luminometer (BIOBLOCK LX-101, Panasonic, Osaka, Japan). The illumination period of 16 hL:8 hD was controlled with an electric timer that switched the lamps on and off accordingly. For the experimentation using colored light, the vessels were covered with different color (green, blue and red) cellophane (Innovia, Cambridge, UK) wrappers and placed at the appropriate distance of the LED lamps receiving 8000 lux. The spikes of spectral wavelengths were 638 nm for red light, 445 nm for blue and 528 nm for green. Cultures were maintained in suspension by injecting air (with its natural CO2 content) through 2 mL glass pipettes (one in each vessel) at a rate of half the culture volume per minute. The pipettes were connected via sterilized plastic tubing to the 0.45 μm filtered central air supply system, which was fed by a blower.
Daily cell counts using a Fuchs-Rosenthal hematocytometer for unicellular species and drying and weighing a sample of the filamentous cyanobacterium’s filtrate every 2–4 days were used to record algal growth, which was measured either as cells/mL for the unicellular Dunaliella or as dry weight (g/L) for the filamentous Anabaena. Simultaneously, optical density was recorded at 750 nm in the spectrophotometer (for all species). Dry weight was calculated by filtering a known amount of culture through 0.45 μm GF/C filters in a vacuum pump (Heto-SUE-3Q). The filters were next washed with ammonium formate to remove salts and then placed in an oven at 100 °C for 2 h [45,46,47].
Untreated culture samples were used to measure the absorbance spectra of the cultures at different stages of maturation. The spectra were recorded in a Shimadzu UV-1800 (Kyoto, Japan) spectrophotometer, and the raw data were transformed to Excel format using its UVprobe 3.2 software.
After a series of spectra had been collected at regular intervals from the course of the culture, the values of absorbance at 750 nm and at the wavelengths of the peaks that characterize chlorophyll-a, chlorophyll-b, carotenoids and phycocyanin of each microalgae were recorded. In parallel, on the same day of each spectrum, biomass density in triplicates was calculated as cells/mL in Dunaliella using the hematocytometer and as g d.w./L for Anabaena. Additionally, chemical analyses of samples were performed in triplicate for the above-mentioned pigments in order to record their actual concentration. Then, from the bulk of data collected, linear regression equations were constructed between pairs of absorbances of the appropriate values extracted from the spectra and the actual values of calculated biomass and pigments, in order to record the strength of each correlation.
Chlorophyll-a and total carotenoids in the case of the cyanobacteria were extracted with absolute methanol from centrifuged culture samples, and their concentrations (μg/mL) were determined spectrophotometrically in a Shimadzu Uvmini-1240 UV-visible (Kyoto, Japan) spectrophotometer using the following equations [46]:
chl-a = 12.9447 ( A 665 A 720 ) T o t a l   c a r o t . = 1000 A 470 A 720 2.86 c h l o r . a 221
where (A) stands for the absorbance (or optical density (OD)) of the processed sample at the indicated wavelength.
In the case of the chlorophyte Dunaliella sp., chlorophyll-a, chlorophyll-b and total carotenoids were extracted with DMSO from centrifuged culture samples, and their concentrations (μg/mL) were calculated spectrophotometrically using the following equations [48]:
chl-a = 12.47 ( A 665 ) 3.62 ( A 649 ) chl-b = 25.06 ( A 649 ) 6.5 ( A 665 ) T o t a l   c a r o t . = 1000 A 480 ) 1.29 ( c h l o r . a 53.78 c h l o r . b 220
For the estimation of β-carotene [49], 1 mL of algal cells was harvested and centrifuged for 10 min at 3000 rpm to remove the pellet, and then 3 mL of a hexane/ethanol (1:2) mixture was added to the vortex. After that, the mixture was centrifuged at 3000 rpm for 10 min. After two phases had formed, the upper phase, which contained the β-carotene, was collected, and its optical density at 450 nm was assessed. β-carotene in μg/mL was calculated according to the following equation [49]:
β-carotene (μg/mL) = 25 × A450
By freezing (−20 °C) for 24 h a concentrated known amount of cyanobacterial culture in 0.1 M sodium phosphate buffer (pH 7.1) as solvent at a ratio of 1:10 (algal mass: solvent) and then thawing at 4 °C in the dark, the phycocyanin (PC) content was extracted [46]. Over the course of two days, the process of freezing and thawing was repeated. The slurry of the sample was then centrifuged at 3000 rpm for 5 min to determine the concentration of phycocyanin (PC, measured in mg/mL) in the supernatant using spectrophotometry and the following equation [50]:
P C = A 615 0.474   A 652 5.34
From the above equation, the yield in phycocyanin (PC) in mg PC/g dry weight was calculated using the following equation [50]:
P C y i e l d = P C m g m L × V ( m L ) D . W . ( g )
where
  • PCyield = mg of phycocyanin per g algal dry weight
  • V = volume of solvent used (mL)
  • D.W. = grams of dry weight of the algal mass used
Using the free PAST3 program, the various variables were statistically treated using ANOVA and Tukey’s test for comparison of means at the 0.05 level of significance. Statistical calculations of regression lines, Pearson’s correlation coefficient, standard deviation (SD) and standard error (SE) were obtained with Excel software 2019 (Microsoft, Redmond, Washington, DC, USA).

3. Results

3.1. Dunaliella sp.

3.1.1. Effect of Low (2000 lux) and High (8000 lux) White Light Illumination

The cultures lasted 17 days, and their absorption spectra were taken every second day from the 3rd day onward. At the start, the culture vessels were inoculated with a proper amount of algae from another stock culture in the exponential stage and under white light of 6000 lux so as to create an initial cell density of 730,000 ± 55,600 (SE) cells/mL (day1). As seen in Figure 2, on day 3, the cell density in the condition of low light (to be named hereafter L-light) (Figure 2C) was 850,000 ± 35,117 (SE) cells/mL while in the condition of high light (to be named hereafter XL-light) (Figure 2C) on the same day reached 4,600,000 ± 149,332 cells/mL, an indication of rapid growth since the beginning in XL as contrasted to L.
Maximum cell density on day 17 in XL reached 25,150,000 ± 524,309 cells/mL significantly higher (p < 0.05) than the relevant one of the same day in L (18,529,000 ± 265,016 cells/mL). Comparing also the cell densities on previous days (5th–7th–9th–11th–13th–15th), it was found that in XL, the densities of each day were higher (p < 0.05) than their counterparts in L.
In L-light (Figure 2A), until the 11th day, the spectra exhibited weak peaks with only a slight elevation at the wavelength of 680 nm which corresponds to chlorophyll-a. On the 13th day and afterward (15th and 17th days) when cell densities exceeded 11,000,000 cells/mL, all characteristic peaks for chlorophyll-a (680 and 440 nm), chlorophyll-b (650 nm) and total carotenoids (484 nm) became very evident. The situation in XL-light spectra was totally different (Figure 2B) as the above-mentioned peaks became clearly evident as early as the 7th day (at 7,700,000 cells/mL) and onward, reaching much higher peaks than the corresponding ones of L-light at all wavelengths characteristic of each pigment. At the highest cell density of 25,150,000 cells/mL of the 17th day, the peak for total carotenoids (484 nm) was much more pronounced. The depiction of the evolution of the OD values of the wavelengths of 750 nm, 680 nm (chlorophyll-a), 650 nm (chlorophyll-b) and 484 nm (total carotenoids) along the course of the culture (Figure 2D) corroborates the differences between L- and XL-light as generally depicted in their spectra (Figure 2A,B).
Using the values of absorbance (OD) at 750 nm from the spectra of Figure 3, the regression lines of cell density vs. absorbance in both light regimes (L and XL) resulted in perfect fitness with the equations of cells/mL = (2 × 107 × OD 750 nm) − 4 × 106 with R2 = 0.9951 for L-light and cells/mL = (2 × 107 × OD 750 nm) − 9 × 106 with R2 = 0.9971 for XL-light. As the slopes of these regressions were statistically not different (p > 0.05), a common regression using values from both light regimes can be also appropriate: cells/mL = (2 × 107 × OD 750 nm) − 6 × 106 with R2 = 0.9768 (Figure 2E).
Before using as above the corresponding values of OD at 750 nm for examining the correlation between the content of various pigments with their spectrum’s value of OD at 750 nm, their OD values corresponding to the peak at the spectrum for each pigment were examined.
In L-light (Figure 3B), the resulted equations were Chlor.-a (μg/mL) = (6.8971 × OD 680 nm) − 0.1385 with R2 = 0.9939, Chlor.-b (μg/mL) = (3.3745 × OD 650 nm) − 0.0168 with R2 = 0.9748 and Total carot. (μg/mL) = (3.4821 × OD 484 nm) − 0.4589 with R2 = 0.997. In XL-light (Figure 3C), they were Chlor.-a (μg/mL) = (7.2023 × OD 680 nm) − 0.1264 with R2 = 0.9761, Chlor.-b (μg/mL) = (4.5273 × OD 650 nm) -0.215 with R2 = 0.9725 and Total carot. (μg/mL) = (7.6317 × OD 484 nm) − 3.0762 with R2 = 0.965. After the ascertainment of the strong relation between the pigment content and the relevant OD of maximum absorbance, the use of OD at 750 nm was applied (Figure 3E,F). In L-light (Figure 3E), the resulted equations were Chlor.-a (μg/mL) = (9.8992 × OD 750 nm) − 0.9434 with R2 = 0.9896, Chlor.-b (μg/mL) = (4.261 × OD 750 nm) − 0.3334 with R2 = 0.9588 and Total carot. (μg/mL) = (5.0897 × OD 750 nm) -0.095 with R2 = 0.9956. In XL-light (Figure 3F), they were Chlor.-a (μg/mL) = (10.713 × OD 750 nm) − 0.3762 with R2 = 0.9836, Chlor.-b (μg/mL) = (5.9525 × OD 750 nm) − 0.9848 with R2 = 0.9773 and Total carot. (μg/mL) = (12.265 × OD 750 nm) − 5.4663 with R2 = 0.978. Comparing the slopes of the above regressions of each pigment between L- and XL-light, only those of total carotenoids were found to differ (p < 0.05). Based on this, pooled values from both light regimes can be justified producing the following regressions: Chlor.-a (μg/mL) = (7.4464 × OD 680 nm) + 0.2167 with R2 = 0.9654 and Chlor.-b (μg/mL) = (4.214 × OD 650 nm) -0.2763 with R2 = 0.92 (Figure 3A) and Chlor.-a (μg/mL) = (10.846 × OD 750 nm) − 1.0875 with R2 = 0.9668, Chlor.-b (μg/mL) = (5.4006 × OD 750 nm) -0.8116 with R2 = 0.9202 (Figure 3D).
Starting the measurement of pigments on the 3rd day of the cultures, it was found that in XL-light (Figure 4B) at all days (3rd–5th–7th–9th–11th–13th–15th–17th), all pigment concentrations were significantly higher (p < 0.05) than their counterparts in L-light (Figure 4A). Maxima of all pigments (in μg/mL ± SE) were recorded on the 17th day for both light regimes. In L-light, they were chlor.-a: 12.43 ± 0.815, chlor.-b: 5.997 ± 0.204, total carot.: 7.173 ± 0.606 and β-carot: 3.113 ± 0.126. In XL-light, they were chlor.-a: 17.283 ± 1.046,, chlor.-b: 8.290 ± 0.569, total carot.: 15.03 ± 0.977 and β-carot: 7.152 ± 0.318.

3.1.2. Effect of Colored (Green, Blue and Red) Light Illumination

At the start, the culture vessels were inoculated with a proper amount of algae from another stock culture in the exponential stage and under white light of 8000 lux so as to create an initial cell density of 1,760,000 ± 40,800 (SE) cells/mL (day1). The cultures lasted 18 days, and their absorption spectra were taken on the 2nd, 4th, 6th, 12th, 15th and 18th days. As seen in Figure 5, the spectra of green (Figure 5A) and blue light (Figure 5C) were prominently much more elevated in terms of absorption values as compared to red light (Figure 5B) in which a collapse of the culture occurred on the 18th day with its spectrum plummeting. In fact, the signs of collapse in the red light became evident from the 15th day’s spectrum which became almost indistinguishable from the spectrum of the 12th day. The uppermost spectra correspond to the measured highest cell densities of the 18th day which were 18,850,000 ± 287,924 (SE) cells/mL for green light, 20,150,000 ± 504,477 cells/mL for blue light and 11,776,600 ± 103,494 cells/mL for red light (on the 15th day). The density in blue light is significantly higher than that in green light, and both are higher (p < 0.05) than the relevant one in red light. In general, all cell densities of every day in green and blue light are significantly higher than their counterparts in red light. Using the values of absorbance (OD) at 750 nm from the spectra of Figure 5A–C, the regression line of cell density vs. absorbance using data from all colors resulted in a perfect fitness equation: cells/mL = (2 × 107 × OD 750 nm) − 5 × 106 with R2 = 0.9867 (Figure 5D).
Before using as above the corresponding values of OD at 750 nm for examining the correlation between the content of various pigments with their spectrum’s value of OD at 750 nm, their OD values corresponding to the peak at the spectrum for each pigment were examined. This procedure was performed using the sum of data from all colors for each pigment (Figure 6D), using the spectral OD values of 680 nm for chlorophyll-a, 650 nm for chlorophyll-b and 484 nm for total carotenoids. The resulted equations were Chlor.-a (μg/mL) = (7.6573 × OD 684 nm) + 0.6695 with R2 = 0.97, Chlor.-b (μg/mL) = (4.5815 × OD 650 nm) + 0.1873 with R2 = 0.9178 and Total carot. (μg/mL) = (4.0644 × OD 484 nm) + 0.6199 with R2 = 0.9276. After the ascertainment of the strong relation between the pigment content and the relevant OD of maximum absorbance as exhibited above, the use of OD at 750 nm was applied to all (Figure 6H). The resulted equations were Chlor.-a (μg/mL) = (12.15 × OD 750 nm) − 1.2231 with R2 = 0.9454, Chlor.-b (μg/mL) = (6.2648 × OD 750 nm) - 1.007 with R2 = 0.8709 and Total carot. (μg/mL) = (6.6353 × OD 750 nm) − 0.4964 with R2 = 0.931. The above equations can serve as proxies for the pigments as the regression slopes of each pigment between the three colors using their particular wavelengths (Figure 6A–C) or 750 nm (Figure 6E–G) were not significantly different (p > 0.05).
Pigment content (in μg/mL ± SE) was clearly affected by the light color used (Figure 7). All kinds of pigments (chlor.-a, chlor.-b, total carot., β-carot.) were much higher (p < 0.05) in green and blue color compared to red at all relevant days (except the first one between green and red). Although for the first four measurements (except for the first on the 3rd day), chlorophylls, total carotenoids and β-carotene were significantly higher in green light compared with the respective values in blue light (p < 0.05), in the last two measurements on the 15th and 18th days (15.5 × 106 and 18.85 × 106 cells/mL for green light and 16.3 × 106 and 20.15 × 106 cells/mL for blue light, respectively), chlorophyll-a (15.69 ± 0.410 and 17.47 ± 0.274 in green and 15.06 ± 0.163 and 17.41 ± 0.308 in blue light, respectively) and chlorophyll-b (6.97 ± 0.422 and 8.58 ± 0.687 in green and 7.83 ± 0.557 and 9.74.41 ± 0.533 in blue light, respectively) values were similar (p > 0.05). On the same last two days, total carotenoids (7.74 ± 0.475 and 9.11 ± 0.297 in green and 9.02 ± 0.220 and 10.24 ± 0.258 in blue light, respectively) were higher in blue light (p < 0.05), and β-carotene, while higher in blue light on the 15th day (4.82 ± 0.201 vs. 4.20 ± 0.081 in green light, p < 0.05), on the 18th day, both colors had equal values (5.01 ± 0.124 in green and 5.05 ± 0.137 in blue, p > 0.05).

3.2. Anabaena sp.

3.2.1. Effect of Low (2000 lux) and High (8000 lux) White Light Illumination

At the start, the culture vessels were inoculated with a proper amount of algae from another stock culture in the exponential stage kept at white light of 6000 lux so as to create an initial cell density of 0.32 ± 0.06 (SE) g d.w./L (day1). The two sets of absorption spectra during the culture period of Anabaena sp. in both L-light and XL-light regimes taken every 3 days starting from the 3rd and ending on the 15th day were quite similar (Figure 8) in terms of recorded biomass (g d.w./L). The most remarkable difference between the two light intensities was the more prominent peak at 630 nm that characterizes phycocyanin in all spectra of L-light (Figure 8A) compared to the relevant ones of XL-light (Figure 8B) from the 9th until the 15th day.
Biomass expressed as g d.w./L ± SE while presented significantly higher (p < 0.05) values from the 3rd day until the 12th in XL-light compared to L, finally, on the 15th day, both recorded densities were equal (p > 0.05) with 1.748 ± 0.101 in L and 1.727 ± 0.078 in XL.
Using the values of absorbance (OD) at 750 nm from the spectra of Figure 8, the regression line of cell density vs. absorbance from both light regimes (L and XL) resulted in perfect fitness (Figure 8C) with the equation of g d.w./L = (1.2134 × OD 750 nm) + 0.0812 with R2 = 0.9974.
Before using as above the corresponding values of OD at 750 nm for examining the correlation between the content of chlorophyll-a and total carotenoids with their spectrum’s value of OD at 750 nm, their OD values corresponding to the peak at the spectrum for chlor.-a (682 nm) and total carot. (490 nm) were examined (Figure 9C). A strong relation was recorded for both pigments: Chlor.-a (μg/mL) = (5.3105 × OD 682 nm) − 1.0738 (R2 = 0.9721) and Total carot. (μg/mL) = (2.6585 × OD 490 nm) − 1.0684 (R2 = 0.9816). After the ascertainment of the above strong relation between the pigment content and their relevant OD of maximum absorbance, the use of OD at 750 nm was applied (Figure 9F), resulting in Chlor.-a (μg/mL) = (7.9347 × OD 750 nm) − 1.3155 (R2 = 0.9769) and Total carot. (μg/mL) = (4.3358 × OD 750 nm) − 1.1666 (R2 = 0.9907). These equations can serve as proxies for the pigments as the regression slopes of each pigment between L- and XL-light using their particular wavelengths (Figure 9A,B) or 750 nm (Figure 9D,E) were not significantly different (p > 0.05).
A similar procedure to chlorophyll-a and total carotenoids as above was applied to the correlations of phycocyanin concentrations to its OD value of maximum absorbance and to OD at 750 nm separately for each light regime (Figure 10). Using cumulatively values from both L- and XL-light, the relation between phycocyanin (in mg/mL ± SE) and its OD peak on the spectra (630 nm) resulted in (Figure 10A) Phycoc. L+XL (mg/mL) = (0.9178 × OD 630 nm) − 0.1906 and (R2 = 0.8094) and using OD values of 750 nm (Figure 10B) in Phycoc. L+XL (mg/mL) = (1.1724 × OD 750 nm) − 0.056, (R2 = 0.6389).
Next, using separately the values of 630 nm from each light regime resulted in Phycoc. L (mg/mL) = (1.1176 × OD 630 nm) − 0.2267 and (R2 = 0.985) and Phycoc. XL (mg/mL) = (0.5562 × OD 630 nm)-0.0253 with R2 = 0.98 (Figure 10C) and using 750 nm (Figure 10D) in Phycoc. L (mg/mL) = (1.7797 × OD 750 nm) − 0.2299, (R2 = 0.9687) and Phycoc. XL (mg/mL) = (0.6984 × OD 750 nm) − 0.0765, (R2 = 0.9717). So, a much stronger relation is produced using OD values for each light regime separately than using values pooled from both light regimes. As the slopes of the regressions between L- and XL-light were significantly different (p < 0.05), they serve much more accurately as proxies for phycocyanin separately in L- or XL-light compared to the relevant regressions using pooled values from both light regimes.
In Figure 11A,B are depicted the measured concentrations of chlorophyll-a and total carotenoids in μg/mL ± SE, phycocyanin in mg/mL ± SE and phycocyanin yield in mg/g d.w. ± SE, for every light regime. Chlorophyll-a presented its highest concentration of 9.713 ± 0.533 on the 15th day in L-light significantly higher (p < 0.05) than the respective value in XL-light (8.750 ± 0.323). On the contrary, on the previous days (6th, 9th and 12th), chlorophyll exhibited significantly higher values in XL-light. Almost the same pattern was found for total carotenoids with higher values in XL-light, but finally, on the 15th day, the concentrations were statistically (p > 0.05) equal (4.939 ± 0.411 in L-light, 4.792 ± 0.325 in XL-light).
Concerning phycocyanin, a clear trend was found with equal concentrations (p > 0.05) on the 3rd, 6th and 9th days of culture, but significantly higher values were found in L-light (maximum 2.125 ± 0.078 on the 15th day) vs. 0.943 ± 0.108 in XL-light for the same day. Similarly, the phycocyanin yield was higher (p < 0.05) in L-light (Figure 11C) on the 15th day (29.785 ± 1.687) compared to 24.697 ± 0.366 in XL-light (Figure 11D) on the same day.

3.2.2. Effect of Colored (Green, Blue and red) Light Illumination

At the start, the culture vessels were inoculated with the proper amount of algae from another stock culture in the exponential stage at white light of 8000 lux so as to create an initial cell density of 0.35 ± 0.05 (SE) g d.w./L (day1). In all three colors used, the spectra (Figure 12) presented a remarkable similarity for the first 3 days of measurement (2nd, 3rd and 6th) with almost identical peaks for chlorophyll-a (682 and 440 nm), total carotenoids (490 nm) and phycocyanin (630 nm) between green and red. From the 10th day until the 16th day, the spectra in green and red were more elevated compared to the respective ones in blue, but on the 19th day, the spectrum in red collapsed (Figure 12C), while in blue (Figure 12B), it just barely increased from that of the previous measurement (16th day), and in green (Figure 12A), it kept rising. Phycocyanin peaks (630 nm) became evident from the 6th day onward in all colors with almost identical height until the 10th day. From the 12th day, the phycocyanin peaks subsided in green until the last measurement of the 19th day while the respective ones in blue and red (with the exception of the 19th day) kept rising even above the peak of chlorophyll-a (682 nm), especially in blue color.
At all days of the culture (2nd–3rd–6th–10th–12th–16th–19th), the recorded biomass densities were significantly higher (p < 0.05) in green light compared to blue light, reaching on the 19th day 2.053 ± 0.056 (SE) g d.w./L in green vs. 1.498 ± 0.137 (SE) g d.w./L in blue. The relevant values in red light were significantly higher (p < 0.05) than their relevant ones of the same days in blue light and equal (p > 0.05) to those of the green light, but on the 19th day, the culture obviously collapsed to 1.15 ± 0.07 (SE) g d.w./L from 1.737 ± 0.071 (SE) g d.w./L on its 16th day’s recording.
A perfect fit (R2 = 0.9948) of the regression line of the relation between the OD at 750 nm of the pooled data from all light colors and the culture density (in g d.w./L) was found described by the following equation: Dry Weight = 1.2687 × OD 750 nm + 0.0031 with R2 = 0.9848 (Figure 12D).
A very good fit was also found relating chlorophyll-a content from all colored lights and either OD at 682 or 750 nm (Figure 13D,H with R2 = 0.9071 and 0.9214, respectively) and an even better fit when considering the relevant relations of chlorophyll-a vs. OD of 682 (Figure 13A–C) or 750 nm (Figure 13E–G) for each color separately. In that case, the first-order equations for green, blue and red illumination gave R2 = 0.9411, R2 = 0.9816 and R2 = 0.9477, respectively, using the OD of 682 nm and R2 = 0.9598, R2 = 0.9664 and R2 = 0.9757, respectively, using the OD of 750 nm. As the slopes of the relevant regressions for each color were not significantly different (p > 0.05), the regressions using pooled data from all colors chlor.-a = 4.0604 (OD 682 nm)-1.3082 and chlor.-a = 5.6447 (OD 750 nm)- 1.4814 (Figure 13D,H, respectively) can be used as proxies for chlorophyll-a.
Excellent fits were found considering total carotenoids vs. OD of 490 nm (Figure 14D) or 750 nm (Figure 14H) using pooled data from all colors. The resulted regression equations were Total carot. = 2.4789 (OD 490 nm) − 1.2097, (R2 = 0.9056), and Total carot. = 3.6122 (OD 750 nm) − 1.2859, (R2 = 0.918). The same or even better fits were found when considering the relevant relations of total carotenoids vs. OD of 490 or 750 nm for each color separately. In that case, the first-order equations for green, blue and red illumination gave R2 = 0.944, R2 = 0.9863 and R2 = 0.9462, respectively, using the OD of 490 nm (Figure 14A–C, respectively) and R2 = 0.9433, R2 = 0.9824 and R2 = 0.9577, respectively, using the OD of 750 nm (Figure 14E–G, respectively).
As the slopes of the relevant regressions for each color were not significantly different (p > 0.05), the regressions using pooled data from all colors can be used as proxies for total carotenoids.
Considering phycocyanin using data for each colored light separately (Figure 15), the first-order equations for green, blue and red illumination gave R2 = 0.944, R2 = 0.9863 and R2 = 0.9462, respectively, using the OD of 630 nm (Figure 15A–C, respectively) and R2 = 0.9433, R2 = 0.9824 and R2 = 0.9577, respectively, using the OD of 750 nm (Figure 15E–G, respectively). As the slopes of their regressions did not differ significantly (p > 0.05) and in contrast to the case of using pooled data from both white light intensities (Figure 10), the use of pooled data from all color lights using either the wavelength of 630 nm with equation phycoc. = 1.4678 (OD 630 nm)-0.4086 (Figure 15D) or that of 750 nm phycoc. = 1.9692 (OD 750 nm) − 0.4036 (Figure 15H), which gave also very high correlation coefficients (R2 = 0.9332 and R2 = 0.9358, respectively), can be justified.
The overall picture of pigment content among the colors of illumination along the culture growth (Figure 16) revealed significant differences between colors and between stages of culture density. Green light induced significantly higher (p < 0.05) content of chlorophyll-a and total carotenoids after the 3rd day compared to either blue or red light. Its highest values of 8.859 μg/mL ± 0.532 for chlorophyll-a and 5.766 μg/mL ± 0.472 for total carotenoids on the 19th day (Figure 16A) were significantly higher (p < 0.05) than the relevant ones of blue light (4.301 μg/mL ± 0.122 and 2.322 μg/mL ± 0.176, respectively) and red light (7.16 μg/mL ± 0.383 and 4.04 μg/mL ± 0.122 on the 16th day, respectively, and 1.862 μg/mL ± 0.112 and 0.765 μg/mL ± 0.123 on the 19th day, respectively, when the culture obviously collapsed).
In green light, phycocyanin also presented its highest values either as concentration (Figure 16B) or yield (Figure 16C) on the 19th day (2.922 mg/mL ± 0.207 and 61.467 mg/g d.w. ± 1.126, respectively) significantly higher than the relevant values of the same day in blue (2.323 mg/mL ± 0.122 and 51.294 mg/g d.w. ± 3.954, respectively) and red light (2.291 mg/mL ± 0.139 and 50.23 mg/g d.w. ± 5.19 on the 16th day, respectively, and 0.565 mg/mL ± 0.065 and 10.458 mg/g d.w. ± 0.489 on the 19th day, respectively, when the culture obviously collapsed).

4. Discussion

In the present study, the influence of light intensity, on the one hand, and the color of the light, on the other, were studied in a well-known eukaryotic microalga (Dunaliella sp.) and in an also well-known cyanobacterium (Anabaena sp.). The first objective of the study was to investigate if the quantity and quality of light have an intense influence on the biomass growth and the content of the algal pigments, and the second objective was to investigate if there is a simple and reliable method using absorption spectra to infer about the status of these variables. In a continuously growing industry of extracting valuable bioactive compounds from microalgae [51,52,53], every method facilitating the rapid estimation of their pigment content is welcomed. In this perspective and before anything else, it should be clarified that the present work aims primarily to help growers to estimate culture density and photosynthetic pigments, if not with the precision of an analytical method, then at least by exploiting a clear trend in the development of a culture of a certain species of microalgae. As a tool for this purpose, it is shown that the absorption spectrum can give a reliable picture of the state of biomass and pigments from a qualitative and quantitative point of view, on the one hand, and, on the other hand, supply the observer with the values of the optical density of the peaks of the wavelengths that characterize each pigment type as well as the value at 750 nm where no algae pigment absorbs. Key to the applicability of the findings of the present study is the use of the 750 nm wavelength as a predictor of both algal density and photosynthetic pigments [45,46,47,54,55,56]. It is well known that the optical density (OD), also known as absorbance or turbidity, of several unicellular algae species and other unicellular microbes, is widely employed as a quick and non-destructive assessment of biomass [48,57], as the relationship between the amount of light absorbed by a suspension of cells and their mass or number is dependent on the size, shape and refractive index of the particles [58]. Thus, the mass or number of cells in a suspension can directly affect how much light is absorbed by the suspension, but the relationship between particle number and OD in order to construct a standard curve is intricate. That is because microalgae have a disproportionately high pigment content, primarily made up of carotenoids and chlorophylls and additionally phycobiliproteins in cyanobacteria that are subjected to variation not only among species but also depending on culture conditions [59,60,61]. Thus, constructing a calibration curve correlating algal biomass to a wavelength at which certain pigment peaks can produce great error if the pigment content changes. Such wavelengths are those of 400–460 nm or 650–680 nm where the absorbance of chlorophylls is maximized and are frequently encountered in the literature. Although these wavelengths can be used by means of standard curves as predictors of chlorophyll content, and the same is true for other wavelengths assigned to other pigment peaks [62,63,64], they are not the best predictors of biomass as found in the present study. Instead, the wavelength of 750 nm can reliably predict with sufficient accuracy algal density [54,56,65,66,67,68,69,70] because this wavelength avoids the light absorption by photosynthetic pigments which might affect its absorbance value created by turbidity alone [48,56,71]. In both species of microalgae studied, its correlation with the algal density gave very high correlation coefficients and, as this was found also in my previous studies [45,46,47,55,56], leaves me with no doubt for its usefulness in the daily monitoring routine of an algal culture. Further on, when I correlated 750 nm with each pigment content, again, strong correlations ensued, and as I did not find any mention of such a relation in the literature, the present findings add novel knowledge. But in this case (correlation of 750 nm with pigment content), some precautions must be taken. First, such a correlation should be assigned uniquely only for a certain species and for the set of culture conditions prevailing (light intensity, light color, etc.). Second, a lot of pigment measurements should have been made in advance, and then, a correlation analysis of them with their respective absorbance at the relevant wavelength peak for the examined pigment should lead to a calibration curve. Only if the correlation is strong, the next step, namely the correlation of the pigment with 750 nm, can be useful. In the present study, having done all of the above and using the 750 nm values from the series of absorption spectra during the course of each culture, a very strong predictive ability was found for chlorophyll and carotenoid content using pooled data for both low (2000 lux) and high (8000 lux) illumination of white light in both microalgae but not for phycocyanin, in which case, correlations are much stronger when examined separately for each light intensity.
A prerequisite for the success of the above procedure is the regular recording of the absorption spectrum of each particular culture in order to extract from it and use for the correlations the values of absorbance of 750 nm and those of the peaks for the various pigments. To the best of my knowledge, this is a novel method of using the absorption spectrum, expanding its application for the prediction of the cultured phyco-biomass and pigment content and not only as a simple image of the culture’s condition [72].
Since light provides the energy source for autotrophic growth, it is essential for the majority of microalgae. Irradiance and light quality both influence the growth of cultured microalgae through photosynthesis [14,73,74]. From an ecological and physiological perspective, the various pigments found in microalgae show differences in the capacity of algae to use light with various spectral compositions for photosynthesis and to adapt to various lighting regimes [14,75,76,77,78,79]. As a result, the spectrum makeup of light is a crucial growth parameter for producing microalgae [80,81,82]. In the present study, substantial differences were recorded in maximum biomass, the content of pigments and pigment ratios among the intensities of white light and among the three light colors used in both microalgae examined. In both microalgae, the maximum biomass was induced by the higher intensity (8000 lux) of white light when compared to all other light regimes (white 2000 lux or the 8000 lux of green, blue and red light). Considering that in the present study the range of illumination used of 2000–8000 lux (40–160 μmol photons m−2 s−1) is included within the range of 26–400 μmol photons m−2 s−1, which according to [14] are the ideal light intensities at which the maximum growth rate is seen for various taxonomic groups and species of algae, I feel confident about my results.
The response of the two examined algae to the quantity and quality of light presented generally similarities and differences. This was, of course, to be expected as the composition of the photosynthetic pigments in their photosynthetic centers are different between eukaryotic and cyanobacterial microalgae, and in addition, there are differences in their physiological mechanisms in response to various environmental conditions. In the present study, as the temperature was similar (19–20 °C) for both species, I hypothesize that at other higher temperatures where, according to other studies, microalgae in general show faster growth and biomass yield [77,79,83], their response will be greater in terms of growth rate and density as well and possibly in terms of their pigment content.
Both species grew faster and attained higher densities at the light intensity of 8000 lux compared to 2000 lux. This was more prominent in Dunaliella while in Anabaena, the differences were minimal. Presumably, these differences arise from the amount of energy that the photosynthetic apparatus of each species can absorb to carry out photosynthesis. When the maximum rate of photosynthesis is attained, the extra light flux is still absorbed by the cell, which causes photosynthesis to reach a condition of light saturation. As a result, the rate of photosynthesis and algal growth both decline concurrently [84,85,86,87].
Contrary to the biomass increase either as growth rate or biomass yield in both species under the higher white light intensity, the opposite was found to occur when phycocyanin in Anabaena was examined. In this case, the low light intensity (2000 lux) induced far more phycocyanin content compared to the high intensity of 8000 lux in accordance with various findings in the literature for cyanobacteria in general. In most studies on cyanobacteria, the phycobiliprotein synthesis increases under limiting light conditions [88] with the light intensity of 25 μmol photons m−2 s−1 (quite close to the 40 μmol photons m−2 s−1 of the present study) reported as the most suitable for phycocyanin production [89,90,91]. Cyanobacteria produce reactive oxygen species (ROS), which severely photodamage biological components when exposed to high light intensities. This is due to an excess energy balance between the energy needed by various cellular processes and the quantity of light energy that is absorbed by light-harvesting complexes [92].
The influence of white or colored light on growth and pigment content in the genus Dunaliella is rather limited [93,94,95,96,97,98,99] without a certain pattern of response of this genus in general to the various light regimes studied so far. In the present study, two white light intensities were used, low light (L) of 2000 lux (40 μmol photons m−2 s−1) and high light (XL) of 8000 lux (160 μmol photons m−2 s−1). The high-light regime resulted in far more biomass produced (expressed as cells/mL), and this is in accordance with some relevant studies on various Dunaliella species [98,100,101], while in other studies using quite comparable to my study light intensities (40–250 μmol photons m−2 s−1), the opposite was recorded (lower light for every set of intensities used), i.e., the lower intensity resulted in higher growth and biomass [95,96,97,99]. Opposite to the above contradictory findings from the literature concerning the growth of Dunaliella cultures under low and high irradiance, there seems to exist unanimity concerning the enhancement of carotenoid production at higher light intensities [54,95,96,100,102,103] in accordance with what was found in the present study. However, the values of either total carotenoids or β-carotene found in all these studies are very difficult to compare to each other or with mine (μg/mL) because of the different units used (μg/g d.w., pg/cell, mg/106 cells, etc.), so, in the present study, the recorded values for carotenoids, β-carotene and chlorophylls expressed in μg/mL stand as unique to the particular Messolonghi lagoon’s strain of Dunaliella sp.
Among the light colors used in algae cultures, green is recorded as the least effective in enhancing biomass growth among white, red, blue and yellow in the majority of eukaryotic microalgae [14] and in the cyanobacterium Arthrospira platensis [104]. In the present study, the effect of green light on growth in Dunaliella was equal to that of low white light, inferior to high white light and blue and superior to red. Nevertheless, green light along with blue effected equally greater production of chlorophylls and carotenoids compared to low white light and blue in Dunaliella, while in Anabaena, it was superior to blue and red and equal to white light.
The existing information on the effect of colored light on growth and pigment content in the genus Anabaena is very limited [26,91], and no clear response pattern can be deduced not only for Anabaena but for other studied species of cyanobacteria as well from what is available in the literature. The impact of light quality on the growth of cyanobacteria appears to vary depending on the species [32]. In the present study, green and red light had a far greater effect on the production of more chlorophyll and carotenoids over blue light (Figure 16A), but considering phycocyanin, the differences among light colors were more pronounced as green light effected statistically more phycocyanin content than white light and either blue or red light (Figure 11 and Figure 16), in contrast to [26]. Green light in the present study enhanced also more biomass production as g d.w./L compared to blue and equally to red and almost the same compared to white light of high intensity (1.727 ± 0.078 (SE) and 1.856 ± 0.058 (SE), respectively). Only the blue light was found inferior to white light in biomass production in the Anabaena strain used in the present study in accordance with the findings of [91].
Based on the above and especially for the Anabaena culture, the perspective of using green light in photobioreactors seems very promising in maximizing along with growth the cell content in phycocyanin and carotenoids, justifying thus its quite ignored beneficial potential for the photosynthetic organisms [13,105].
In summary, the local strains of Dunaliella sp. and Anabaena sp. from the salt waters of the Messolonghi lagoon can be grown effectively in easily attainable conditions of 35 ppt salinity, ~20 °C and white light intensities of 2000–8000 lux producing biomass and pigments that can be collected at the proper time of the culture by using the absorption spectra of their cultures as the predictor. The same holds true when employing colored light in the case of using photobioreactors. The recording of the absorption spectrum is an easy, cost-free and noninvasive valuable practice that if performed regularly can offer the grower much useful information about the status of the culture. To fully exploit the prediction (for biomass and pigments) capabilities of the absorption spectrum, the following prerequisites must be fulfilled:
  • Enough absorption spectra should be recorded along the course of the culture of a certain microalga at a more or less certain set of culture conditions.
  • On the same day of recording, a certain absorption spectrum and biomass density should be properly calculated, and various pigments’ concentration analyses must be meticulously performed. Additionally, the absorbance values of 750 nm and of the peaks for each pigment should be recorded.
  • The above procedure should be repeated for each spectrum recorded along the culture course. After getting at regular intervals a number of absorption spectra and data on biomass density and pigment concentrations for a particular culture, the data should be processed.
  • Regression equations for the pairs of biomass density and absorbance at 750 nm should be constructed using the above bulk of data in order to see if there is a strong correlation (i.e., R2 > 0.85). If so, then the equation can be used for predicting biomass using the OD value of 750 nm. The same procedure should be executed for the pairs of each pigment concentration and OD at 750 nm in order to predict in the future each pigment’s concentration based on the constructed equations.
  • The above painstaking procedure should be performed once in the beginning in order to construct the calibration equations for the certain culture. Then, for future cultures of the same species in the same conditions, the grower can use the constructed equations to get fairly accurate estimates for biomass and pigments.

5. Conclusions

As a result of the calibration dependences, I have discovered that it is possible to quickly, easily and fairly accurately estimate biomass and pigment content in the commercially important chlorophyte Dunaliella sp. and the cyanobacterium Anabaena sp. using their absorption spectra in their culture’s course. High correlation coefficients attest to this method’s accuracy. This novel method, which can facilitate the prediction of the culture state by the growers, used values of absorbance extracted from a series of absorption spectra at 750 nm and from the peaks characterizing the chlorophylls, carotenoids and phycocyanin. Additionally, biomass production in both species is enhanced by white light of 8000 lux compared to 2000 lux, and this also applies to chlorophyll and carotenoids in Dunaliella sp. while 2000 lux enhances phycocyanin production over 8000 lux in Anabaena sp. Using colored light, it was found that green light enhances phycocyanin in the cyanobacterium Anabaena sp. and carotenoids and chlorophyll in Dunaliella along with blue over red light. Overall, the findings of the present study can contribute to an effective culture of both species using the appropriate light intensity of white light or green light in photobioreactors and enhance the ability of culture’s control by the growers using data from absorption spectra for the proper construction of calibration equations.

Funding

This research was financially supported by the research program “ALGAVISION: Isolation and culture of local phytoplankton species aiming to mass production of antibacterial substances, fatty acids, pigments and antioxidants” (MIS 5048496), funded by the General Secretariat of Research and Technology of the Greek Government.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The author thanks the technical staff of the laboratory Despoina Avramidou for her help in the experimentation.

Conflicts of Interest

The author declares no conflict of interest. The funders had no role in the design of the study; in the collection, analyses or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Moreno-Garcia, L.; Adjallé, K.; Barnabé, S.; Raghavan, G.S.V. Microalgae Biomass Production for a Biorefinery System: Recent Advances and the Way towards Sustainability. Renew. Sustain. Energy Rev. 2017, 76, 493–506. [Google Scholar] [CrossRef]
  2. Benedetti, M.; Vecchi, V.; Barera, S.; Dall’Osto, L. Biomass from Microalgae: The Potential of Domestication towards Sustainable Biofactories. Microb. Cell Fact. 2018, 17, 173. [Google Scholar] [CrossRef] [PubMed]
  3. Sun, H.; Zhao, W.; Mao, X.; Li, Y.; Wu, T.; Chen, F. High-Value Biomass from Microalgae Production Platforms: Strategies and Progress Based on Carbon Metabolism and Energy Conversion. Biotechnol. Biofuels 2018, 11, 227. [Google Scholar] [CrossRef]
  4. Subramanian, S.; Sayre, R.T. The Right Stuff; Realizing the Potential for Enhanced Biomass Production in Microalgae. Front. Energy Res. 2022, 10, 979747. [Google Scholar] [CrossRef]
  5. Wang, B.; Li, Y.; Wu, N.; Lan, C.Q. CO2 Bio-Mitigation Using Microalgae. Appl. Microbiol. Biotechnol. 2008, 79, 707–718. [Google Scholar] [CrossRef]
  6. Zhou, W.; Wang, J.; Chen, P.; Ji, C.; Kang, Q.; Lu, B.; Li, K.; Liu, J.; Ruan, R. Bio-Mitigation of Carbon Dioxide Using Microalgal Systems: Advances and Perspectives. Renew. Sustain. Energy Rev. 2017, 76, 1163–1175. [Google Scholar] [CrossRef]
  7. Awal, S.; Christie, A. Suitability of Inland Saline Ground Water for the Growth of Marine Microalgae for Industrial Purposes. J. Aquac. Mar. Biol. 2015, 3, 00063. [Google Scholar] [CrossRef]
  8. Muhammad, G.; Alam, M.A.; Xiong, W.; Lv, Y.; Xu, J.-L. Microalgae Biomass Production: An Overview of Dynamic Operational Methods. In Microalgae Biotechnology for Food, Health and High Value Products; Springer: Singapore, 2020; pp. 415–432. [Google Scholar]
  9. Farooq, W. Sustainable Production of Microalgae Biomass for Biofuel and Chemicals through Recycling of Water and Nutrient within the Biorefinery Context: A Review. GCB Bioenergy 2021, 13, 914–940. [Google Scholar] [CrossRef]
  10. Ahmad, A.; Hassan, S.W.; Banat, F. An Overview of Microalgae Biomass as a Sustainable Aquaculture Feed Ingredient: Food Security and Circular Economy. Bioengineered 2022, 13, 9521–9547. [Google Scholar] [CrossRef] [PubMed]
  11. Ummalyma, S.B.; Sirohi, R.; Udayan, A.; Yadav, P.; Raj, A.; Sim, S.J.; Pandey, A. Sustainable Microalgal Biomass Production in Food Industry Wastewater for Low-Cost Biorefinery Products: A Review. Phytochem. Rev. 2022. [Google Scholar] [CrossRef] [PubMed]
  12. Yu, K.L.; Ong, H.C.; Zaman, H.B. Microalgae Biomass as Biofuel and the Green Applications. Energies 2022, 15, 7280. [Google Scholar] [CrossRef]
  13. Paper, M.; Glemser, M.; Haack, M.; Lorenzen, J.; Mehlmer, N.; Fuchs, T.; Schenk, G.; Garbe, D.; Weuster-Botz, D.; Eisenreich, W.; et al. Efficient Green Light Acclimation of the Green Algae Picochlorum Sp. Triggering Geranylgeranylated Chlorophylls. Front. Bioeng. Biotechnol. 2022, 10, 885977. [Google Scholar] [CrossRef]
  14. Maltsev, Y.; Maltseva, K.; Kulikovskiy, M.; Maltseva, S. Influence of Light Conditions on Microalgae Growth and Content of Lipids, Carotenoids, and Fatty Acid Composition. Biology 2021, 10, 1060. [Google Scholar] [CrossRef] [PubMed]
  15. Toole, C.M.; Allnutt, F.C.T. Red, Cryptomonad and Glaucocystophyte Algal Phycobiliproteins. In Photosynthesis in Algae; Springer: Dordrecht, The Netherlands, 2003; pp. 305–334. [Google Scholar]
  16. MacColl, R. Cyanobacterial Phycobilisomes. J. Struct. Biol. 1998, 124, 311–334. [Google Scholar] [CrossRef] [PubMed]
  17. Maroneze, M.M.; Dias, R.R.; Severo, I.A.; Queiroz, M.I. Microalgae-Based Processes for Pigments Production. In Pigments from Microalgae Handbook; Springer International Publishing: Cham, Switzerland, 2020; pp. 241–264. [Google Scholar]
  18. Jeevanandam, J.; Choudhary, V.; Selvam, J.D.; Danquah, M.K. The Bioeconomy of Production of Microalgal Pigments. In Pigments from Microalgae Handbook; Springer International Publishing: Cham, Switzerland, 2020; pp. 325–362. [Google Scholar]
  19. Silva, S.C.; Ferreira, I.C.F.R.; Dias, M.M.; Barreiro, M.F. Microalgae-Derived Pigments: A 10-Year Bibliometric Review and Industry and Market Trend Analysis. Molecules 2020, 25, 3406. [Google Scholar] [CrossRef]
  20. Coulombier, N.; Jauffrais, T.; Lebouvier, N. Antioxidant Compounds from Microalgae: A Review. Mar. Drugs 2021, 19, 549. [Google Scholar] [CrossRef] [PubMed]
  21. Pourkarimi, S.; Hallajisani, A.; Alizadehdakhel, A.; Nouralishahi, A.; Golzary, A. Factors Affecting Production of Beta-Carotene from Dunaliella Salina Microalgae. Biocatal. Agric. Biotechnol. 2020, 29, 101771. [Google Scholar] [CrossRef]
  22. Wolf, L.; Cummings, T.; Müller, K.; Reppke, M.; Volkmar, M.; Weuster-Botz, D. Production of Β-carotene with Dunaliella Salina CCAP19/18 at Physically Simulated Outdoor Conditions. Eng. Life Sci. 2021, 21, 115–125. [Google Scholar] [CrossRef]
  23. Khandual, S.; Sanchez, E.O.L.; Andrews, H.E.; de la Rosa, J.D.P. Phycocyanin Content and Nutritional Profile of Arthrospira Platensis from Mexico: Efficient Extraction Process and Stability Evaluation of Phycocyanin. BMC Chem. 2021, 15, 24. [Google Scholar] [CrossRef] [PubMed]
  24. Yao, T.; Huang, J.; Su, B.; Wei, L.; Zhang, A.-H.; Zhang, D.-F.; Zhou, Y.; Ma, G. Enhanced Phycocyanin Production of Arthrospira Maxima by Addition of Mineral Elements and Polypeptides Using Response Surface Methodology. Front. Mar. Sci. 2022, 9, 1057201. [Google Scholar] [CrossRef]
  25. Grant, C.; Louda, J. Microalgal Pigment Ratios in Relation to Light Intensity: Implications for Chemotaxonomy. Aquat. Biol. 2010, 11, 127–138. [Google Scholar] [CrossRef]
  26. Vijaya, V.; Anand, N. Blue Light Enhance the Pigment Synthesis in Cyanobacterium Anabaena Ambigua Rao (Nostacales). J. Agric. Biol. Sci. 2009, 4, 36–43. [Google Scholar]
  27. Mohsenpour, S.F.; Richards, B.; Willoughby, N. Spectral Conversion of Light for Enhanced Microalgae Growth Rates and Photosynthetic Pigment Production. Bioresour. Technol. 2012, 125, 75–81. [Google Scholar] [CrossRef]
  28. Eriksen, N.T. Production of Phycocyanin—A Pigment with Applications in Biology, Biotechnology, Foods and Medicine. Appl. Microbiol. Biotechnol. 2008, 80, 1–14. [Google Scholar] [CrossRef] [PubMed]
  29. Barsanti, L.; Gualtieri, P. Algae: Anatomy, Biochemistry, and Biotechnology, 2nd ed.; CRC Press: Boca Raton, FL, USA, 2014; ISBN 9781439867334. [Google Scholar]
  30. Wang, C.-Y.; Fu, C.-C.; Liu, Y.-C. Effects of Using Light-Emitting Diodes on the Cultivation of Spirulina Platensis. Biochem. Eng. J. 2007, 37, 21–25. [Google Scholar] [CrossRef]
  31. Singh, S.P.; Singh, P. Effect of Temperature and Light on the Growth of Algae Species: A Review. Renew. Sustain. Energy Rev. 2015, 50, 431–444. [Google Scholar] [CrossRef]
  32. Khattar, J.I.S.; Kaur, S.; Kaushal, S.; Singh, Y.; Singh, D.P.; Rana, S.; Gulati, A. Hyperproduction of Phycobiliproteins by the Cyanobacterium Anabaena Fertilissima PUPCCC 410.5 under Optimized Culture Conditions. Algal Res. 2015, 12, 463–469. [Google Scholar] [CrossRef]
  33. del Pilar Sánchez-Saavedra, M.; Maeda-Martínez, A.N.; Acosta-Galindo, S. Effect of Different Light Spectra on the Growth and Biochemical Composition of Tisochrysis Lutea. J. Appl. Phycol. 2016, 28, 839–847. [Google Scholar] [CrossRef]
  34. Liyanaarachchi, V.C.; Nishshanka, G.K.S.H.; Premaratne, R.G.M.M.; Ariyadasa, T.U.; Nimarshana, P.H.V.; Malik, A. Astaxanthin Accumulation in the Green Microalga Haematococcus Pluvialis: Effect of Initial Phosphate Concentration and Stepwise/Continuous Light Stress. Biotechnol. Rep. 2020, 28, e00538. [Google Scholar] [CrossRef] [PubMed]
  35. Reichert, C.C.; Reinehr, C.O.; Costa, J.A.V. Semicontinuous Cultivation of the Cyanobacterium Spirulina Platensis in a Closed Photobioreactor. Braz. J. Chem. Eng. 2006, 23, 23–28. [Google Scholar] [CrossRef]
  36. Chronakis, I.S.; Galatanu, A.N.; Nylander, T.; Lindman, B. The Behaviour of Protein Preparations from Blue-Green Algae (Spirulina Platensis Strain Pacifica) at the Air/Water Interface. Colloids Surf. A Physicochem. Eng. Asp. 2000, 173, 181–192. [Google Scholar] [CrossRef]
  37. Bergmann, P.; Trösch, W. Repeated Fed-Batch Cultivation of Thermosynechococcus Elongatus BP-1 in Flat-Panel Airlift Photobioreactors with Static Mixers for Improved Light Utilization: Influence of Nitrate, Carbon Supply and Photobioreactor Design. Algal Res. 2016, 17, 79–86. [Google Scholar] [CrossRef]
  38. Ho, S.-H.; Liao, J.-F.; Chen, C.-Y.; Chang, J.-S. Combining Light Strategies with Recycled Medium to Enhance the Economic Feasibility of Phycocyanin Production with Spirulina Platensis. Bioresour. Technol. 2018, 247, 669–675. [Google Scholar] [CrossRef]
  39. Zeng, X.; Danquah, M.K.; Zhang, S.; Zhang, X.; Wu, M.; Chen, X.D.; Ng, I.-S.; Jing, K.; Lu, Y. Autotrophic Cultivation of Spirulina Platensis for CO2 Fixation and Phycocyanin Production. Chem. Eng. J. 2012, 183, 192–197. [Google Scholar] [CrossRef]
  40. Tamary, E.; Kiss, V.; Nevo, R.; Adam, Z.; Bernát, G.; Rexroth, S.; Rögner, M.; Reich, Z. Structural and Functional Alterations of Cyanobacterial Phycobilisomes Induced by High-Light Stress. Biochim. Et. Biophys. Acta BBA-Bioenerg. 2012, 1817, 319–327. [Google Scholar] [CrossRef]
  41. Klepacz-Smółka, A.; Pietrzyk, D.; Szeląg, R.; Głuszcz, P.; Daroch, M.; Tang, J.; Ledakowicz, S. Effect of Light Colour and Photoperiod on Biomass Growth and Phycocyanin Production by Synechococcus PCC 6715. Bioresour. Technol. 2020, 313, 123700. [Google Scholar] [CrossRef] [PubMed]
  42. Hotos, G.N. A Preliminary Survey on the Planktonic Biota in a Hypersaline Pond of Messolonghi Saltworks (W. Greece). Diversity 2021, 13, 270. [Google Scholar] [CrossRef]
  43. Hotos, G.; Avramidou, D.; Mastropetros, S.G.; Tsigkou, K.; Kouvara, K.; Makridis, P.; Kornaros, M. Isolation, Identification, and Chemical Composition Analysis of Nine Microalgal and Cyanobacterial Species Isolated in Lagoons of Western Greece. Algal Res. 2023, 69, 102935. [Google Scholar] [CrossRef]
  44. Markou, G. Effect of Various Colors of Light-Emitting Diodes (LEDs) on the Biomass Composition of Arthrospira Platensis Cultivated in Semi-Continuous Mode. Appl. Biochem. Biotechnol. 2014, 172, 2758–2768. [Google Scholar] [CrossRef] [PubMed]
  45. Hotos, G.N. Culture Growth of the Cyanobacterium Phormidium Sp. in Various Salinity and Light Regimes and Their Influence on Its Phycocyanin and Other Pigments Content. J. Mar. Sci. Eng. 2021, 9, 798. [Google Scholar] [CrossRef]
  46. Hotos, G.N.; Antoniadis, T.I. The Effect of Colored and White Light on Growth and Phycobiliproteins, Chlorophyll and Carotenoids Content of the Marine Cyanobacteria Phormidium Sp. and Cyanothece Sp. in Batch Cultures. Life 2022, 12, 837. [Google Scholar] [CrossRef]
  47. Hotos, G.N.; Avramidou, D.; Samara, A. The Effect of Salinity and Light Intensity on the Batch Cultured Cyanobacteria Anabaena sp. and Cyanothece sp. Hydrobiology 2022, 1, 278–287. [Google Scholar] [CrossRef]
  48. Griffiths, M.J.; Garcin, C.; van Hille, R.P.; Harrison, S.T.L. Interference by Pigment in the Estimation of Microalgal Biomass Concentration by Optical Density. J. Microbiol. Methods 2011, 85, 119–123. [Google Scholar] [CrossRef] [PubMed]
  49. Morowvat, M.H.; Ghasemi, Y. Culture Medium Optimization for Enhanced β-Carotene and Biomass Production by Dunaliella Salina in Mixotrophic Culture. Biocatal. Agric. Biotechnol. 2016, 7, 217–223. [Google Scholar] [CrossRef]
  50. Arashiro, L.T.; Boto-Ordóñez, M.; Van Hulle, S.W.H.; Ferrer, I.; Garfí, M.; Rousseau, D.P.L. Natural Pigments from Microalgae Grown in Industrial Wastewater. Bioresour. Technol. 2020, 303, 122894. [Google Scholar] [CrossRef]
  51. Novoveská, L.; Ross, M.E.; Stanley, M.S.; Pradelles, R.; Wasiolek, V.; Sassi, J.-F. Microalgal Carotenoids: A Review of Production, Current Markets, Regulations, and Future Direction. Mar. Drugs 2019, 17, 640. [Google Scholar] [CrossRef] [PubMed]
  52. Patel, A.K.; Albarico, F.P.J.B.; Perumal, P.K.; Vadrale, A.P.; Nian, C.T.; Chau, H.T.B.; Anwar, C.; Wani, H.M.; Pal, A.; Saini, R.; et al. Algae as an Emerging Source of Bioactive Pigments. Bioresour. Technol. 2022, 351, 126910. [Google Scholar] [CrossRef] [PubMed]
  53. Wan, X.; Zhou, X.-R.; Moncalian, G.; Su, L.; Chen, W.-C.; Zhu, H.-Z.; Chen, D.; Gong, Y.-M.; Huang, F.-H.; Deng, Q.-C. Reprogramming Microorganisms for the Biosynthesis of Astaxanthin via Metabolic Engineering. Prog. Lipid Res. 2021, 81, 101083. [Google Scholar] [CrossRef]
  54. Borovkov, A.B.; Gudvilovich, I.N.; Avsiyan, A.L. Scale-up of Dunaliella Salina Cultivation: From Strain Selection to Open Ponds. J. Appl. Phycol. 2020, 32, 1545–1558. [Google Scholar] [CrossRef]
  55. Hotos, G.N.; Avramidou, D. The Effect of Various Salinities and Light Intensities on the Growth Performance of Five Locally Isolated Microalgae [Amphidinium Carterae, Nephroselmis Sp., Tetraselmis Sp. (Var. Red Pappas), Asteromonas gracilis and Dunaliella Sp.] in Laboratory Batch Cultures. J. Mar. Sci. Eng. 2021, 9, 1275. [Google Scholar] [CrossRef]
  56. Hotos, G.N.; Avramidou, D.; Bekiari, V. Calibration Curves of Culture Density Assessed by Spectrophotometer for Three Microalgae (Nephroselmis Sp., Amphidinium carterae and Phormidium Sp.). Eur. J. Biol. Biotechnol. 2020, 1, 1–7. [Google Scholar] [CrossRef]
  57. Toennies, G.; Gallant, D.L. The Relation between Photometric Turbidity and Bacterial Concentration. Growth 1949, 13, 7–20. [Google Scholar]
  58. Clesceri, L.S.; Greenberg, A.E.; Eaton, A.D. Standard Methods for the Examination of Water and Wastewater, 20th ed.; American Public Health Association: Washington, DC, USA, 1998. [Google Scholar]
  59. Nicholls, K.H.; Dillon, P.J. An Evaluation of Phosphorus-Chlorophyll-Phytoplankton Relationships for Lakes. Int. Rev. Gesamten Hydrobiol. Hydrogr. 1978, 63, 141–154. [Google Scholar] [CrossRef]
  60. Begum, H.; Yusoff, F.M.; Banerjee, S.; Khatoon, H.; Shariff, M. Availability and Utilization of Pigments from Microalgae. Crit. Rev. Food Sci. Nutr. 2016, 56, 2209–2222. [Google Scholar] [CrossRef]
  61. Pagels, F.; Salvaterra, D.; Amaro, H.M.; Guedes, A.C. Pigments from Microalgae. In Handbook of Microalgae-Based Processes and Products; Elsevier: Amsterdam, The Netherlands, 2020; pp. 465–492. [Google Scholar]
  62. An, J.-Y.; Sim, S.-J.; Lee, J.S.; Kim, B.W. Hydrocarbon Production from Secondarily Treated Piggery Wastewater by the Green Alga Botryococcus Braunii. J. Appl. Phycol. 2003, 15, 185–191. [Google Scholar] [CrossRef]
  63. Chiu, S.-Y.; Kao, C.-Y.; Chen, C.-H.; Kuan, T.-C.; Ong, S.-C.; Lin, C.-S. Reduction of CO2 by a High-Density Culture of Chlorella Sp. in a Semicontinuous Photobioreactor. Bioresour. Technol. 2008, 99, 3389–3396. [Google Scholar] [CrossRef] [PubMed]
  64. Hsieh, C.-H.; Wu, W.-T. Cultivation of Microalgae for Oil Production with a Cultivation Strategy of Urea Limitation. Bioresour. Technol. 2009, 100, 3921–3926. [Google Scholar] [CrossRef] [PubMed]
  65. Detweiler, A.M.; Mioni, C.E.; Hellier, K.L.; Allen, J.J.; Carter, S.A.; Bebout, B.M.; Fleming, E.E.; Corrado, C.; Prufert-Bebout, L.E. Evaluation of Wavelength Selective Photovoltaic Panels on Microalgae Growth and Photosynthetic Efficiency. Algal Res. 2015, 9, 170–177. [Google Scholar] [CrossRef]
  66. Gao, F.; Sá, M.; Teles, I.; Wijffels, R.H.; Barbosa, M.J. Production and Monitoring of Biomass and Fucoxanthin with Brown Microalgae under Outdoor Conditions. Biotechnol. Bioeng. 2021, 118, 1355–1365. [Google Scholar] [CrossRef] [PubMed]
  67. Hirooka, S.; Tomita, R.; Fujiwara, T.; Ohnuma, M.; Kuroiwa, H.; Kuroiwa, T.; Miyagishima, S. Efficient Open Cultivation of Cyanidialean Red Algae in Acidified Seawater. Sci. Rep. 2020, 10, 13794. [Google Scholar] [CrossRef]
  68. Plöhn, M.; Escudero-Oñate, C.; Funk, C. Biosorption of Cd(II) by Nordic Microalgae: Tolerance, Kinetics and Equilibrium Studies. Algal Res. 2021, 59, 102471. [Google Scholar] [CrossRef]
  69. Yoshitomi, T.; Karita, H.; Mori-Moriyama, N.; Sato, N.; Yoshimoto, K. Reduced Cytotoxicity of Polyethyleneimine by Covalent Modification of Antioxidant and Its Application to Microalgal Transformation. Sci. Technol. Adv. Mater. 2021, 22, 864–874. [Google Scholar] [CrossRef]
  70. Markina, Z.V.; Maslennikov, S.I.; Botsun, L.A. Application of the Spectrophotometric Method for Determination of the Cell Numbers of Microalgae in the Genus Tetraselmis (Chlorophyta): Calibration Curves and Equations for Calculation. Russ. J. Mar. Biol. 2022, 48, 525–528. [Google Scholar] [CrossRef]
  71. Chioccioli, M.; Hankamer, B.; Ross, I.L. Flow Cytometry Pulse Width Data Enables Rapid and Sensitive Estimation of Biomass Dry Weight in the Microalgae Chlamydomonas Reinhardtii and Chlorella Vulgaris. PLoS ONE 2014, 9, e97269. [Google Scholar] [CrossRef] [PubMed]
  72. Al-Hasan, R.H.; Ghannoum, M.A.; Sallal, A.-K.; Abu-Elteen, K.H.; Radwan, S.S. Correlative Changes of Growth, Pigmentation and Lipid Composition of Dunaliella Salina in Response to Halostress. J. Gen. Microbiol. 1987, 133, 2607–2616. [Google Scholar] [CrossRef]
  73. Wagner, I.; Steinweg, C.; Posten, C. Mono- and Dichromatic LED Illumination Leads to Enhanced Growth and Energy Conversion for High-Efficiency Cultivation of Microalgae for Application in Space. Biotechnol. J. 2016, 11, 1060–1071. [Google Scholar] [CrossRef] [PubMed]
  74. Li, Y.; Liu, J. Analysis of Light Absorption and Photosynthetic Activity by Isochrysis galbana under Different Light Qualities. Aquac. Res. 2020, 51, 2893–2902. [Google Scholar] [CrossRef]
  75. Remias, D.; Lütz-Meindl, U.; Lütz, C. Photosynthesis, Pigments and Ultrastructure of the Alpine Snow Alga Chlamydomonas nivalis. Eur. J. Phycol. 2005, 40, 259–268. [Google Scholar] [CrossRef]
  76. Mayer, D.; Dubinsky, Z.; Iluz, D. Light as a Limiting Factor for Epilithic Algae in the Supralittoral Zone of Littoral Caves. Front. Mar. Sci. 2016, 3, 18. [Google Scholar] [CrossRef]
  77. Metsoviti, M.N.; Papapolymerou, G.; Karapanagiotidis, I.T.; Katsoulas, N. Effect of Light Intensity and Quality on Growth Rate and Composition of Chlorella Vulgaris. Plants 2019, 9, 31. [Google Scholar] [CrossRef] [PubMed]
  78. Fisher, N.L.; Campbell, D.A.; Hughes, D.J.; Kuzhiumparambil, U.; Halsey, K.H.; Ralph, P.J.; Suggett, D.J. Divergence of Photosynthetic Strategies amongst Marine Diatoms. PLoS ONE 2020, 15, e0244252. [Google Scholar] [CrossRef] [PubMed]
  79. Abiusi, F.; Sampietro, G.; Marturano, G.; Biondi, N.; Rodolfi, L.; D’Ottavio, M.; Tredici, M.R. Growth, Photosynthetic Efficiency, and Biochemical Composition of Tetraselmis suecica F&M-M33 Grown with LEDs of Different Colors. Biotechnol. Bioeng. 2014, 111, 956–964. [Google Scholar] [CrossRef] [PubMed]
  80. Teo, C.L.; Atta, M.; Bukhari, A.; Taisir, M.; Yusuf, A.M.; Idris, A. Enhancing Growth and Lipid Production of Marine Microalgae for Biodiesel Production via the Use of Different LED Wavelengths. Bioresour. Technol. 2014, 162, 38–44. [Google Scholar] [CrossRef]
  81. Sharma, N.; Fleurent, G.; Awwad, F.; Cheng, M.; Meddeb-Mouelhi, F.; Budge, S.M.; Germain, H.; Desgagné-Penix, I. Red Light Variation an Effective Alternative to Regulate Biomass and Lipid Profiles in Phaeodactylum Tricornutum. Appl. Sci. 2020, 10, 2531. [Google Scholar] [CrossRef]
  82. Diamantopoulou, C.; Christoforou, E.; Dominoni, D.M.; Kaiserli, E.; Czyzewski, J.; Mirzai, N.; Spatharis, S. Wavelength-Dependent Effects of Artificial Light at Night on Phytoplankton Growth and Community Structure. Proc. R. Soc. B Biol. Sci. 2021, 288, 20210525. [Google Scholar] [CrossRef]
  83. Lubián, L.M.; Montero, O.; Moreno-Garrido, I.; Huertas, I.E.; Sobrino, C.; González-del Valle, M.; Parés, G. Nannochloropsis (Eustigmatophyceae) as Source of Commercially Valuable Pigments. J. Appl. Phycol. 2000, 12, 249–255. [Google Scholar] [CrossRef]
  84. Fan, J.; Zheng, L. Acclimation to NaCl and Light Stress of Heterotrophic Chlamydomonas Reinhardtii for Lipid Accumulation. J. Biosci. Bioeng. 2017, 124, 302–308. [Google Scholar] [CrossRef]
  85. Wu, M.; Zhu, R.; Lu, J.; Lei, A.; Zhu, H.; Hu, Z.; Wang, J. Effects of Different Abiotic Stresses on Carotenoid and Fatty Acid Metabolism in the Green Microalga Dunaliella Salina Y6. Ann. Microbiol. 2020, 70, 48. [Google Scholar] [CrossRef]
  86. Nzayisenga, J.C.; Farge, X.; Groll, S.L.; Sellstedt, A. Effects of Light Intensity on Growth and Lipid Production in Microalgae Grown in Wastewater. Biotechnol. Biofuels 2020, 13, 4. [Google Scholar] [CrossRef]
  87. Cointet, E.; Wielgosz-Collin, G.; Bougaran, G.; Rabesaotra, V.; Gonçalves, O.; Méléder, V. Effects of Light and Nitrogen Availability on Photosynthetic Efficiency and Fatty Acid Content of Three Original Benthic Diatom Strains. PLoS ONE 2019, 14, e0224701. [Google Scholar] [CrossRef]
  88. Bermejo Román, R.; Alvárez-Pez, J.M.; Acién Fernández, F.G.; Molina Grima, E. Recovery of Pure B-Phycoerythrin from the Microalga Porphyridium Cruentum. J. Biotechnol. 2002, 93, 73–85. [Google Scholar] [CrossRef] [PubMed]
  89. Takano, H.; Arai, T.; Hirano, M.; Matsunaga, T. Effects of Intensity and Quality of Light on Phycocyanin Production by a Marine Cyanobacterium Synechococcus Sp. NKBG 042902. Appl. Microbiol. Biotechnol. 1995, 43, 1014–1018. [Google Scholar] [CrossRef]
  90. Hong, S.-J.; Lee, C.-G. Statistical Optimization of Culture Media for Production of Phycobiliprotein by Synechocystis Sp. PCC 6701. Biotechnol. Bioprocess Eng. 2008, 13, 491–498. [Google Scholar] [CrossRef]
  91. Hemlata; Fatma, T. Screening of Cyanobacteria for Phycobiliproteins and Effect of Different Environmental Stress on Its Yield. Bull. Environ. Contam. Toxicol. 2009, 83, 509–515. [Google Scholar] [CrossRef] [PubMed]
  92. Singh, N.K.; Parmar, A.; Sonani, R.R.; Madamwar, D. Isolation, Identification and Characterization of Novel Thermotolerant Oscillatoria Sp. N9DM: Change in Pigmentation Profile in Response to Temperature. Process Biochem. 2012, 47, 2472–2479. [Google Scholar] [CrossRef]
  93. Xu, Y.; Harvey, P.J. Carotenoid Production by Dunaliella Salina under Red Light. Antioxidants 2019, 8, 123. [Google Scholar] [CrossRef]
  94. Li, Y.; Li, L.; Liu, J.; Qin, R. Light Absorption and Growth Response of Dunaliella under Different Light Qualities. J. Appl. Phycol. 2020, 32, 1041–1052. [Google Scholar] [CrossRef]
  95. Wu, Z.; Duangmanee, P.; Zhao, P.; Juntawong, N.; Ma, C. The Effects of Light, Temperature, and Nutrition on Growth and Pigment Accumulation of Three Dunaliella Salina Strains Isolated from Saline Soil. Jundishapur J. Microbiol. 2016, 9, e26732. [Google Scholar] [CrossRef]
  96. Park, S.; Lee, Y.; Jin, E. Comparison of the Responses of Two Dunaliella Strains, Dunaliella Salina CCAP 19/18 and Dunaliella Bardawil to Light Intensity with Special Emphasis on Carotenogenesis. ALGAE 2013, 28, 203–211. [Google Scholar] [CrossRef]
  97. Vo, T.; Tran, D. Effects of Salinity and Light on Growth of Dunaliella Isolates. J. Appl. Environ. Microbiol. 2014, 2, 208–211. [Google Scholar]
  98. Gaur, S.; Adholeya, A. Influence of Light Intensity, Photoperiod and Culture Medium on the Dunaliella Tertiolecta and Nannochloropsis Oculata Pigment Production, Lipid Yields and Fatty Acid Composition. SSRN Electron. J. 2022, 9, e12801. [Google Scholar] [CrossRef]
  99. Ak, I.; Cirik, S.; Goksan, T. Effects of Light Intensity, Salinity and Temperature on Growth in Camalti Strain of Dunaliella Viridis Teodoresco from Turkey. J. Biol. Sci. 2008, 8, 1356–1359. [Google Scholar] [CrossRef]
  100. Xu, Y.; Ibrahim, I.; Wosu, C.; Ben-Amotz, A.; Harvey, P. Potential of New Isolates of Dunaliella Salina for Natural β-Carotene Production. Biology 2018, 7, 14. [Google Scholar] [CrossRef]
  101. Chang, F.H.; Wear, R.G.; Reynolds, J. Effects of Salinity, Temperature, and Light Intensity on the Growth Rates of Two Halophilic Phytoflagellates in Mixed Culture. N. Z. J. Mar. Freshw. Res. 1986, 20, 467–478. [Google Scholar] [CrossRef]
  102. Hermawan, J.; Masithah, E.D.; Tjahjaningsih, W.; Abdillah, A.A. Increasing β-Carotene Content of Phytoplankton Dunaliella Salina Using Different Salinity Media. In IOP Conference Series: Earth and Environmental Science; IOP Publishing: Bristol, UK, 2018; Volume 137, p. 012034. [Google Scholar] [CrossRef]
  103. Nguyen, A.; Tran, D.; Ho, M.; Louime, C.; Tran, H.; Tran, D. High Light Stress Regimen on Dunaliella Salina Strains For Carotenoids Induction. Integr. Food Nutr. Metab. 2016, 3, 347–350. [Google Scholar] [CrossRef]
  104. Raqiba, H.; Sibi, G. Light Emitting Diode (LED) Illumination For Enhanced Growth And Cellular Composition In Three Microalgae. Adv. Microbiol. Res. 2019, 3, 1–6. [Google Scholar] [CrossRef]
  105. Smith, H.L.; McAusland, L.; Murchie, E.H. Don’t Ignore the Green Light: Exploring Diverse Roles in Plant Processes. J. Exp. Bot. 2017, 68, 2099–2110. [Google Scholar] [CrossRef] [PubMed]
Figure 1. (A) Dunaliella sp. (B) Anabaena sp. (C) Bottles with Dunaliella on 5th day of culture at two different distances from light sources so as to create L-light (2000 lux) and XL-light (8000 lux). (D) Bottles with Anabaena on 2nd day of culture at two different distances from light sources.
Figure 1. (A) Dunaliella sp. (B) Anabaena sp. (C) Bottles with Dunaliella on 5th day of culture at two different distances from light sources so as to create L-light (2000 lux) and XL-light (8000 lux). (D) Bottles with Anabaena on 2nd day of culture at two different distances from light sources.
Jmse 11 01673 g001
Figure 2. The absorption spectra at 8 consecutive days (3rd, 5th, 7th, 9th, 11th, 13th, 15th and 17th with their cell densities indicated in the inserted captions) of the cultures of Dunaliella sp. exposed to low (L) 2000 lux (A) and high (XL) 8000 lux white light illumination (B). (C) The progress of culture density (cells/mL) along the culture course for L- and XL-light regime. (D) OD values of the peaks characterizing the wavelengths of each pigment and of 750 nm along the culture course. (E) Regression (calibration) line of cell density—OD value at 750 nm using pooled data (cells/mL ± SD) from both L- and XL-light.
Figure 2. The absorption spectra at 8 consecutive days (3rd, 5th, 7th, 9th, 11th, 13th, 15th and 17th with their cell densities indicated in the inserted captions) of the cultures of Dunaliella sp. exposed to low (L) 2000 lux (A) and high (XL) 8000 lux white light illumination (B). (C) The progress of culture density (cells/mL) along the culture course for L- and XL-light regime. (D) OD values of the peaks characterizing the wavelengths of each pigment and of 750 nm along the culture course. (E) Regression (calibration) line of cell density—OD value at 750 nm using pooled data (cells/mL ± SD) from both L- and XL-light.
Jmse 11 01673 g002
Figure 3. (A,D) Regression lines using pooled data from L- and XL-light of chlorophyll-a, chlorophyll-b and total carotenoid concentration as μg/mL ± SD vs. OD at each wavelength exhibiting the maximum absorbance for each pigment (A) and versus the OD at the wavelength of 750 nm (D) in Dunaliella culture. (B,E) The same as in (A,D) correspondingly under L-light and (C,F) under XL-light.
Figure 3. (A,D) Regression lines using pooled data from L- and XL-light of chlorophyll-a, chlorophyll-b and total carotenoid concentration as μg/mL ± SD vs. OD at each wavelength exhibiting the maximum absorbance for each pigment (A) and versus the OD at the wavelength of 750 nm (D) in Dunaliella culture. (B,E) The same as in (A,D) correspondingly under L-light and (C,F) under XL-light.
Jmse 11 01673 g003
Figure 4. Pigment content in μg/mL ± SE for chlorophyll-a, chlorophyll-b, total carotenoids and b-carotene at 8 different culture densities of Dunaliella sp. in L-light (A) and XL-light (B). Each successive culture density starting from the 3rd day of culture represents measurements taken every 2 days. Above each bar cluster is indicated the corresponding day of the culture.
Figure 4. Pigment content in μg/mL ± SE for chlorophyll-a, chlorophyll-b, total carotenoids and b-carotene at 8 different culture densities of Dunaliella sp. in L-light (A) and XL-light (B). Each successive culture density starting from the 3rd day of culture represents measurements taken every 2 days. Above each bar cluster is indicated the corresponding day of the culture.
Jmse 11 01673 g004
Figure 5. The absorption spectra at 6 different days (2nd–4th–6th–12th–15th–18th) of the cultures of Dunaliella sp. exposed to green (A), red (B) and blue (C) light. (D) Regression (calibration) line of cell density—OD value at 750 nm using pooled data (cells/mL ± SD) from all colors.
Figure 5. The absorption spectra at 6 different days (2nd–4th–6th–12th–15th–18th) of the cultures of Dunaliella sp. exposed to green (A), red (B) and blue (C) light. (D) Regression (calibration) line of cell density—OD value at 750 nm using pooled data (cells/mL ± SD) from all colors.
Jmse 11 01673 g005
Figure 6. Regression lines of chlorophyll-a, chlorophyll-b and total carotenoid concentration as μg/mL ± SD vs. OD at each wavelength exhibiting the maximum absorbance for each pigment in blue (A), red (B), green (C) and cumulative all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Dunaliella cultures.
Figure 6. Regression lines of chlorophyll-a, chlorophyll-b and total carotenoid concentration as μg/mL ± SD vs. OD at each wavelength exhibiting the maximum absorbance for each pigment in blue (A), red (B), green (C) and cumulative all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Dunaliella cultures.
Jmse 11 01673 g006
Figure 7. Pigment content in μg/mL ± SE for chlorophyll-a, chlorophyll-b, total carotenoids and β-carotene at 6 different culture densities of Dunaliella sp. in each light color used at different cell densities along the culture period starting from the 3rd day and every 3 days until the 18th day. Each set of measurements for each light color is depicted by the appropriate coloration. Above each bar cluster is indicated the day of the culture.
Figure 7. Pigment content in μg/mL ± SE for chlorophyll-a, chlorophyll-b, total carotenoids and β-carotene at 6 different culture densities of Dunaliella sp. in each light color used at different cell densities along the culture period starting from the 3rd day and every 3 days until the 18th day. Each set of measurements for each light color is depicted by the appropriate coloration. Above each bar cluster is indicated the day of the culture.
Jmse 11 01673 g007
Figure 8. The absorption spectra at 5 consecutive days (3rd–6th–9th–12th–15th) with their respective culture density (in g d.w./L) of the cultures of Anabaena sp. exposed to low L-2000 lux (A) and high XL-8000 lux illumination (B). (C) Regression (calibration) line of cell density in (g d.w./L ± SD)—OD value at 750 nm using pooled data from both L- and XL-light.
Figure 8. The absorption spectra at 5 consecutive days (3rd–6th–9th–12th–15th) with their respective culture density (in g d.w./L) of the cultures of Anabaena sp. exposed to low L-2000 lux (A) and high XL-8000 lux illumination (B). (C) Regression (calibration) line of cell density in (g d.w./L ± SD)—OD value at 750 nm using pooled data from both L- and XL-light.
Jmse 11 01673 g008
Figure 9. (A,D) Regression lines of chlorophyll-a and total carotenoid concentration as μg/mL ± SE vs. OD at each wavelength exhibiting the maximum absorbance for each pigment (A) and versus the OD at the wavelength of 750 nm (D) in Anabaena sp. culture in L-light. (B,E) The same correspondingly in XL-light. (C,F) The same correspondingly using values from both light regimes.
Figure 9. (A,D) Regression lines of chlorophyll-a and total carotenoid concentration as μg/mL ± SE vs. OD at each wavelength exhibiting the maximum absorbance for each pigment (A) and versus the OD at the wavelength of 750 nm (D) in Anabaena sp. culture in L-light. (B,E) The same correspondingly in XL-light. (C,F) The same correspondingly using values from both light regimes.
Jmse 11 01673 g009
Figure 10. Regression lines of phycocyanin concentration as mg/mL ± SE vs. OD at its wavelength (630 nm) exhibiting the maximum absorbance in pooled data from L+XL-light (A) and versus the OD at the wavelength of 750 nm (B). The same using data from each light regime for 630 nm (C) and 750 nm (D) in Anabaena sp. culture.
Figure 10. Regression lines of phycocyanin concentration as mg/mL ± SE vs. OD at its wavelength (630 nm) exhibiting the maximum absorbance in pooled data from L+XL-light (A) and versus the OD at the wavelength of 750 nm (B). The same using data from each light regime for 630 nm (C) and 750 nm (D) in Anabaena sp. culture.
Jmse 11 01673 g010
Figure 11. Pigment content in μg/mL ± SE for chlorophyll-a and total carotenoids and in mg/mL ± SE for phycocyanin at 5 different culture densities of Anabaena sp. in L-light (A) and XL-light (B) and additionally for phycocyanin yield in mg/g d.w. ± SE for L-light (C) and XL-light (D). The five biomass densities on “X” axis correspond to 3rd, 6th, 9th, 12th and 15th days of culture indicated above each bar cluster.
Figure 11. Pigment content in μg/mL ± SE for chlorophyll-a and total carotenoids and in mg/mL ± SE for phycocyanin at 5 different culture densities of Anabaena sp. in L-light (A) and XL-light (B) and additionally for phycocyanin yield in mg/g d.w. ± SE for L-light (C) and XL-light (D). The five biomass densities on “X” axis correspond to 3rd, 6th, 9th, 12th and 15th days of culture indicated above each bar cluster.
Jmse 11 01673 g011
Figure 12. The absorption spectra at 7 different days (2nd–3rd–6th–10th–12th–16th–19th) of the cultures of Anabaena sp. exposed to green (A), blue (B) and red (C) light. (D) Regression (calibration) line of cell density—OD value at 750 nm using pooled data from all colors.
Figure 12. The absorption spectra at 7 different days (2nd–3rd–6th–10th–12th–16th–19th) of the cultures of Anabaena sp. exposed to green (A), blue (B) and red (C) light. (D) Regression (calibration) line of cell density—OD value at 750 nm using pooled data from all colors.
Jmse 11 01673 g012
Figure 13. Regression lines of chlorophyll-a concentration as μg/mL ± SD vs. OD at the wavelength of 682 nm exhibiting the maximum absorbance in green (A), blue (B), red (C) and cumulatively all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Anabaena sp. culture.
Figure 13. Regression lines of chlorophyll-a concentration as μg/mL ± SD vs. OD at the wavelength of 682 nm exhibiting the maximum absorbance in green (A), blue (B), red (C) and cumulatively all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Anabaena sp. culture.
Jmse 11 01673 g013
Figure 14. Regression lines of total carotenoid concentration as μg/mL ± SD vs. OD at the wavelength of 490 nm exhibiting the maximum absorbance in green (A), blue (B), red (C) and cumulatively all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Anabaena sp. culture.
Figure 14. Regression lines of total carotenoid concentration as μg/mL ± SD vs. OD at the wavelength of 490 nm exhibiting the maximum absorbance in green (A), blue (B), red (C) and cumulatively all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Anabaena sp. culture.
Jmse 11 01673 g014
Figure 15. Regression lines of phycocyanin concentration as mg/mL ± SD vs. OD at the wavelength of 490 nm exhibiting the maximum absorbance in green (A), blue (B), red (C) and cumulatively all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Anabaena sp. culture.
Figure 15. Regression lines of phycocyanin concentration as mg/mL ± SD vs. OD at the wavelength of 490 nm exhibiting the maximum absorbance in green (A), blue (B), red (C) and cumulatively all colors (D) and versus the OD at the wavelength of 750 nm ((EH), correspondingly) in Anabaena sp. culture.
Jmse 11 01673 g015
Figure 16. (A) Chlorophyll-a and total carotenoids as μg/mL ± SE at each culture density in each colored light regime (indicated by the proper coloration of each bar cluster). (B) Phycocyanin as mg/mL ± SE and (C) phycocyanin yield as mg/g d.w. ± SE in each colored light regime (indicated by the proper coloration of each bar cluster) in Anabaena sp. culture. Above each bar cluster is indicated the day of the culture.
Figure 16. (A) Chlorophyll-a and total carotenoids as μg/mL ± SE at each culture density in each colored light regime (indicated by the proper coloration of each bar cluster). (B) Phycocyanin as mg/mL ± SE and (C) phycocyanin yield as mg/g d.w. ± SE in each colored light regime (indicated by the proper coloration of each bar cluster) in Anabaena sp. culture. Above each bar cluster is indicated the day of the culture.
Jmse 11 01673 g016
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Hotos, G.N. Quantity and Quality of Light on Growth and Pigment Content of Dunaliella sp. and Anabaena sp. Cultures and the Use of Their Absorption Spectra as a Proxy Method for Assessment. J. Mar. Sci. Eng. 2023, 11, 1673. https://doi.org/10.3390/jmse11091673

AMA Style

Hotos GN. Quantity and Quality of Light on Growth and Pigment Content of Dunaliella sp. and Anabaena sp. Cultures and the Use of Their Absorption Spectra as a Proxy Method for Assessment. Journal of Marine Science and Engineering. 2023; 11(9):1673. https://doi.org/10.3390/jmse11091673

Chicago/Turabian Style

Hotos, George N. 2023. "Quantity and Quality of Light on Growth and Pigment Content of Dunaliella sp. and Anabaena sp. Cultures and the Use of Their Absorption Spectra as a Proxy Method for Assessment" Journal of Marine Science and Engineering 11, no. 9: 1673. https://doi.org/10.3390/jmse11091673

APA Style

Hotos, G. N. (2023). Quantity and Quality of Light on Growth and Pigment Content of Dunaliella sp. and Anabaena sp. Cultures and the Use of Their Absorption Spectra as a Proxy Method for Assessment. Journal of Marine Science and Engineering, 11(9), 1673. https://doi.org/10.3390/jmse11091673

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop