Treatment of Swine Wastewater Using the Domestic Microalga Halochlorella rubescens KNUA214 for Bioenergy Production and Carotenoid Extraction

Abstract

The management of swine wastewater (SW) presents significant environmental challenges, requiring solutions that combine effective treatment with resource recovery. This study highlights the dual role of microalgae in wastewater remediation and bioenergy production. H. rubescens KNUA214 was cultivated in media containing varying concentrations of diluted swine wastewater (DSW; 0%, 25%, 50%, and 100%). Cultivating with Blue Green-11 (BG-11) medium + 50% DSW maximized biomass growth, the chlorophyll content, and carotenoid production. Nutrient removal efficiency in 100% DSW over 8 days demonstrated reductions of 59.3% in total nitrogen, 67.7% in ammonia nitrogen, and 40.7% in total phosphorus, confirming the species’ capacity for effective wastewater treatment. The carotenoid analysis using HPLC revealed that astaxanthin, lutein, canthaxanthin, and beta-carotene exhibited the highest levels in BG-11 + 50% DSW. Furthermore, the biomass analyses confirmed its potential for bioenergy applications, with high calorific values and significant polyunsaturated fatty acid concentrations, enhancing its utility for bioenergy and biolubricant production. These findings position H. rubescens KNUA214 as an effective resource for integrating SW management with the sustainable production of high-value biochemicals, offering environmental and economic benefits.

1. Introduction

Amidst escalating global challenges such as energy security, climate change, and the pursuit of sustainable development, the strategic role of biomass and biorefinery technologies has become increasingly pivotal [1,2]. A heightened global awareness of environmental challenges, such as waste accumulation and resource depletion, drives this strategy, urgently calling for innovative and eco-friendly solutions. One such promising approach is the utilization of biological materials, which not only supports a reduction in waste, but also offers a plethora of benefits from renewable energy production to natural resource conservation, contributing to the growing trend toward more sustainable environmental practices [3,4,5].

Microalgae have risen as one of the promising eco-friendly solutions capable of addressing the diverse environmental challenges outlined above. These simple, photosynthetic organisms excel in several key areas: they can sequester significant amounts of carbon dioxide, thereby mitigating greenhouse gas emissions; their rapid growth rates and ability to thrive in diverse aquatic environments make them a sustainable alternative to terrestrial bioenergy crops; and they require less land and water resources, avoiding competition with food production [6,7,8,9]. Furthermore, microalgae can be harnessed for bioremediation—removing pollutants from wastewater and converting them into valuable biomass, which can then be used for producing biofuels, high-value biochemicals, and nutraceuticals, demonstrating their multifaceted utility in sustainable industrial applications [10,11,12,13].

Efforts to utilize microalgae in wastewater treatment have demonstrated their potential, not only for purifying water, but also for producing valuable biomass. Researchers have used microalgae to treat municipal, agricultural, and industrial wastewater [14,15]. Microalgae utilize nutrients such as nitrogen (N) and phosphorus (P) from wastewater to grow, simultaneously reducing the pollutant load and recovering resources [16,17,18]. This dual functionality underscores the role of microalgae as a cornerstone in the sustainable management of water resources.

Furthermore, the biomass generated from these systems has diverse applications, thereby increasing its utility and effectiveness across various sectors [19,20,21,22] Microalgal biomass, which is rich in proteins, lipids, and carbohydrates, not only provides energy, but also serves as a valuable source for animal feed, dietary supplements, and the production of high-value compounds such as antioxidants, pigments, and essential fatty acids [23,24,25,26]. Each application not only represents a step toward more sustainable production processes, but also aligns with the principles of a circular economy by turning waste into wealth.

The diversity among microalgal species necessitates the continuous discovery and study of species-specific strains to match specific environmental or industrial needs. While some strains may be effective in nutrient removal or biomass production in lab-scale experiments using standard media, transitioning to real-world applications such as wastewater treatment introduces variables that can impact efficacy [27,28]. Factors such as fluctuating nutrient concentrations and the presence of toxins in actual wastewater challenge the reproducibility observed in controlled environments [29]. This highlights the need for rigorous pilot and field testing to optimize algal strains, not just in laboratories, but also under practical conditions. This research is essential to ensure the reliability and scalability of microalgal applications in wastewater treatment, effectively adapting them to meet real-world demands.

In this study, microalgae were isolated from Dokdo, an island far from the Korean Peninsula that maintains a unique ecosystem. Morphological and molecular identification of the species was conducted. The growth of the microalgae and its efficacy in pollutant removal were examined using media ranging from BG-11 to diluted swine wastewater (DSW). Additionally, the potential of the microalgal biomass for producing high-value substances was explored, and its viability as a bioenergy source was assessed through proximate analysis, elemental analysis, and fatty acid profiling. These investigations highlight the various industrial uses of the indigenous Korean microalga Halochlorella rubescens KNUA214, which was identified through a pre-screening test of 16 microalgal species cultivated in swine wastewater (SW). This strain demonstrated the highest survival rate and resistance to DSW toxicity, underscoring its potential to support the circular economy and contribute to sustainable, eco-friendly solutions.

2. Materials and Methods

2.1. Microalgal Cultivation in Swine Wastewater (SW)

2.1.1. Characteristics of SW

SW was collected from a livestock farm in Dalseong County, Daegu, Republic of Korea. While SW serves as an appropriate substrate for microalgae cultivation due to its rich nutrient content, its high concentrations of pollutants, such as heavy metals, can adversely affect microalgal growth rate and biomass production [2]. To enhance light penetration and ensure an adequate nutrient supply, the SW was filtered through a 0.22 μm bottle-top vacuum filter (Sartolab RF, Sartorius Stedim Biotech, Göttingen, Germany) and subsequently diluted with distilled water at a ratio of 1:20. The nutrient concentrations in the DSW were quantified, including total nitrogen (TN), ammonia nitrogen (NH₃-N), nitrate (NO₃-N), and total phosphorus (TP), using a water analysis kit (Humas, Daejeon, Republic of Korea). Additionally, concentrations of heavy metal ions were measured using an inductively coupled plasma spectrometer (Optima 7300DV, PerkinElmer, Waltham, MA, USA).

2.1.2. Microalgal Isolation and Identification

H. rubescens KNUA214 was isolated from Dokdo Island (37°14′22.2″ N, 131°52′11.2″ E) in the East Sea of the Republic of Korea. Samples were transported to the laboratory and inoculated into 100 mL of BG-11 medium supplemented with 100 μg mL⁻¹ imipenem (JW Pharmaceutical, Seoul, Republic of Korea). The cultures were incubated on an orbital shaker (Vision Scientific, Bucheon, Republic of Korea) at 160 rpm and 25 °C under approximately 130 μmol m⁻² s⁻¹ with a 16:8 light/dark cycle. Upon visible microalgal growth, 1.5 mL of the culture was centrifuged at 3000× g for 5 min to obtain an algal pellet. A BG-11 agar plate supplemented with 30 μL of 100 μg mL⁻¹ imipenem was inoculated with the microalgal pellet and incubated under similar conditions. Single colonies were isolated from the agar plate and successively re-streaked onto BG-11 agar plates without antibiotics to establish pure colonies.

Genomic DNA was extracted from approximately 200 mg of algal cells using a DNA extraction buffer (100 mM Tris-HCl, pH 9.0–9.5; 1 M KCl; and 10 mM EDTA, pH 8.0) supplemented with RNase A and sterile glass beads. The lysate was vortexed, heated at 65 °C, and centrifuged at 13,523× g to remove the cellular debris. DNA was purified from the resulting supernatant using the Wizard^® DNA Clean-Up System (Promega, Madison, WI, USA), yielding high-purity DNA suitable for downstream molecular analysis.

PCR amplification was performed to target the 18S ribosomal RNA (rRNA) region using the primers NS1 (5′-GTA GTC ATA TGC TTG TCT C-3′) and NS8 (5′-TCC GCA GGT TCA CCT ACG GA-3′) (1). The internal transcribed spacer (ITS) region was also amplified using the primers ITS1 (5′-TCC GTA GGT GAA CCT GCG G-3′) and ITS4 (5′-TCC TCC GCT TAT TGA TAT GC-3′) [30].

The 18S rRNA and ITS sequences obtained, along with closely related sequences retrieved from the National Center for Biotechnology Information (NCBI) database, were analyzed using MEGA X (Molecular Evolutionary Genetics Analysis) software version 10.1.6. [31]. The Kimura 2-parameter (K2) model was determined as the best-fit nucleotide substitution model based on the Bayesian Information Criterion. This model was employed to construct a maximum likelihood (ML) phylogenetic tree with 500 bootstrap replicates to evaluate the robustness of the inferred tree topology [32].

2.1.3. Cultivation of Microalgae

H. rubescens KNUA214 was subsequently inoculated into 100 mL of BG-11 medium and cultivated at 25 °C under dim light (55 μmol m⁻² s⁻¹) with a 16:8 light/dark cycle until the stationary phase was reached. The cultures were harvested by centrifugation at 1516× g for 10 min at 25 °C. The supernatant was discarded, and the algal cell pellets were washed with distilled water to eliminate any residual medium. Furthermore, the effect of SW concentration on the growth of H. rubescens KNUA214 was evaluated using four different media: 100% BG-11 (0% DSW), 75% BG-11 + 25% DSW, 50% BG-11 + 50% DSW, and 100% DSW. The inoculated flasks were incubated for 8 days under light conditions of 130 µmol m⁻² s⁻¹.

2.2. Growth Characteristics and Biomass Productivity

The microalgal growth rate was estimated by measuring the optical density (OD) and dry weight (DW) at 2-day intervals over an 8-day period. Culture samples were collected, and the OD at 680 nm was measured using a spectrophotometer (Optimizer 2120 UV spectrophotometer, Mecasys, Daejeon, Republic of Korea). For determining DW, a sheet of GF/C Whatman™ filter paper (0.7 µm pore size, Thermo Fisher Scientific, Leicestershire, UK) was initially weighed, and 5 mL of the culture was filtered through it. The filter papers were then dried in an oven at 105 °C for 24 h, allowed to cool to room temperature, and reweighed. The microalgal DW was calculated by subtracting the initial weight of the filter paper from its final weight after drying.

Chlorophyll a (Chl-a) and chlorophyll b (Chl-b) were quantified on days 4 and 8 of microalgal cultivation in varying concentrations of DSW. Microalgal cultures were collected in 2 mL tubes and centrifuged at 16,022× g at 4 °C for 5 min. After discarding the supernatant, the centrifugation step was repeated to ensure complete collection of the microalgae pellets from the 2 mL of culture. The pellets were then resuspended in 1 mL of methanol (MeOH) and disrupted by ultrasonication (550 Sonic Dismembrator, Fisher Scientific, Hampton, NH, USA) at 40 Hz for 1 min to extract pigments. The extracted pigment solution was incubated at 4 °C for 24 h in the dark to stabilize it and then it was centrifuged at 16,022× g at 4 °C for 20 min to separate the supernatant. The absorbances of the supernatant at 649 nm and 664 nm were measured using a spectrophotometer to quantify the Chl-a and Chl-b concentrations, respectively. The concentrations were calculated using appropriate equations [33].

Chl-a = 13.36A₆₆₄ − 5.19A₆₄₉(1)

Chl-b = 27.43A₆₄₉ − 8.12A₆₆₄(2)

2.3. Nutrient Removal Efficacy

The concentrations of nutrients in the DSW without microalgae at day 0 were compared to those in microalgal cultures in 100% DSW on day 8. Specifically, TN, TP, NH₃-N, and sulfate (SO₄²⁻) concentrations were measured. These measurements were performed using HS-TN-L, HS-TP-L, HS-NH3(N)-L, and SO4-L test kits, respectively (Humas, Daejeon, Republic of Korea).

2.4. Pigment Productivity

Microalgal cells were collected after cultivation for 4 and 8 days, and the harvested biomass was freeze-dried using a freeze dryer (PVTFD20R, Ilshin Lab, Suwon, Republic of Korea). For carotenoid extraction, 10 mg of the freeze-dried biomass was weighed and suspended in 1.5 mL of MeOH. The mixture was sonicated for 90 min at a resonance frequency of 40 Hz in an ultrasonic bath (Bransonic CPX5800H-E, Danbury, CT, USA). After sonication, the samples were centrifuged at 16,022× g for 20 min at 4 °C, and the supernatant was carefully collected. This supernatant was dried using a rotary evaporator (IKA RV, Staufen, Germany), and the resulting residue was dissolved in 1.5 mL of acetone before being filtered through a 0.2 μm membrane filter (Minisart syringe filter, Sartorius Stedim Biotech, Göttingen, Germany) in preparation for high-performance liquid chromatography (HPLC) analysis. Carotenoid quantification was performed using an Agilent 1200 series gradient HPLC system (Agilent Technologies, Palo Alto, CA, USA) equipped with a diode array detector and a YMC C30 carotenoid column (250 mm × 4.6 mm × 5 μm; YMC, Kyoto, Japan). The mobile phase consisted of 92% MeOH with 10 mM ammonium acetate (solvent A) and pure methyl tert-butyl ether (solvent B). The system operated at a flow rate of 1 mL min⁻¹, with the column temperature maintained at 45 °C. A 10 μL aliquot of each sample was injected, and carotenoid absorbance was measured at 450 nm. The carotenoid content was quantified by comparing the chromatographic peak areas with those of standard solutions, including astaxanthin, lutein, canthaxanthin, zeaxanthin, and beta-carotene, which were obtained from Sigma-Aldrich (St. Louis, MO, USA).

2.5. Proximate and Ultimate Analyses

Proximate analysis was conducted using thermogravimetric analysis (TGA) on a thermal analyzer (DTG-60A, Shimadzu, Kyoto, Japan). Lyophilized samples weighing 5–10 mg were placed in a platinum pan and subjected to TGA under an atmosphere of N at a flow rate of 25 mL min⁻¹. The heating rate was set to 10 °C min⁻¹ until a final temperature of 900 °C was reached. The moisture content was determined as the mass loss occurring prior to reaching 105 °C. Volatile matter was defined as the mass loss observed between 105 °C and 900 °C, resulting from thermal decomposition. The residue remaining after reaching 900 °C contained fixed carbon and ash.

Ultimate analysis for elemental composition was performed using a Flash 2000 elemental analyzer (Thermo Fisher Scientific, Milan, Italy). This analysis determined the content of carbon (C), hydrogen (H), oxygen (O), nitrogen (N), and sulfur (S). The calorific value (CV) of the samples was calculated using the equation provided by [34].

CV (MJ kg⁻¹) = 0.3278C + 1.419H + 0.09257S − 0.1379O + 0.637(3)

2.6. Fatty Acid Methyl Ester (FAME) Analysis and Biodiesel Quality Assessment

2.6.1. FAME Analysis

FAMEs were extracted following a modified version of Breuer’s method (Breuer et al., 2013 [35]). Lyophilized biomass (30 mg) was disrupted using a Micromixer E-36 (Taitec, Saitama, Japan), Vortex-Genie (Scientific Industries, Bohemia, NY, USA), and a sonicator bath (Branson-5210, Branson Inc., Danbury, CT, USA) in the presence of glass beads and a 4:5 (v/v) mixture of chloroform (CHCl₃) and MeOH. Phase separation was achieved by adding 2.5 mL of water containing 50 mM Tris and 1 M NaCl. Lipids were extracted through the repeated addition of CHCl₃ and sonication. The extracted lipids were then concentrated by evaporating CHCl₃ under reduced pressure using a rotary evaporator. The concentrated lipids were subsequently transesterified into FAMEs using 3 mL of MeOH containing 5% (v/v) sulfuric acid. The resulting hexane phase was filtered through a 0.2 μm polyvinylidene fluoride syringe filter (Chromdisc, Hwaseong, Republic of Korea). The FAME components were analyzed by gas chromatography using an Agilent 7890 B system (Santa Clara, CA, USA) equipped with a mass selective detector (MSD, 5977 B, Agilent) and a DB-FFAP column (30 m × 250 μm × 0.25 μm; Agilent). Additionally, compound identification was based on comparing the mass spectra with those in the Wiley/NBS library, with matches over 90% considered valid.

2.6.2. Biodiesel Quality Assessment Based on FAMEs

The quality of biodiesel was assessed by determining various parameters based on the FAME profile. These parameters included the cetane number (CN), degree of unsaturation (DU), saponification value (SV), iodine value (IV), oxidative stability (OS), long-chain saturation factor (LCSF), cold filter plugging point (CFPP), kinematic viscosity (υ), and density (ρ). Prior studies documented the use of an established equation for fuel quality assessment in microalgae to evaluate the biodiesel quality based on its fatty acid composition [36,37].

$$\begin{gathered} \mathrm{SV}=\sum {\displaystyle \frac{560\times \mathrm{F}}{\mathrm{M}\mathrm{W}}}, \\ \mathrm{IV}=\sum {\displaystyle \frac{254\times \mathrm{F}\times \mathrm{N}}{\mathrm{M}\mathrm{W}}}, \\ \mathrm{CN}=\sum \left(-7.8+0.302\times \mathrm{M}\mathrm{W}-20\times \mathrm{N}\right)\times \mathrm{m}\mathrm{a}\mathrm{s}\mathrm{s} \mathrm{f}\mathrm{r}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \\ \mathrm{LCSF}=(0.1 \times \mathrm{C}16)+(0.5 \times \mathrm{C}18)+(1 \times \mathrm{C}20)+(1.5 \times \mathrm{C}22)+(2 \times \mathrm{C}24), \\ \mathrm{CFPP}=(3.1417 \times \mathrm{LCSF}) - \left(16.477\right), \\ \mathrm{DU}=\sum \mathrm{M}\mathrm{U}\mathrm{F}\mathrm{A}+ (2 \times \mathrm{PUFA}), \\ \ln (\upsilon )=\sum -12.503+2.496\times \ln \left(\mathrm{M}\mathrm{W}\right)-0.178\times \mathrm{N}, \\ \rho =\sum 0.8463+{\displaystyle \frac{4.9}{\mathrm{M}\mathrm{W}}}+0.0118\times \mathrm{N}, \mathrm{and} \\ \mathrm{OS}={\displaystyle \frac{117.9295}{\mathrm{X}}}+2.5905 (0<100) \end{gathered}$$

In this Equation, N represents the percentage content of each fatty acid, MW is the molecular weight, D is the number of double bonds, and X represents the content of linoleic and linolenic acid at each FAME value.

2.7. Statistical Analysis

All experiments were conducted in triplicate, and the data are presented as the mean of the triplicate measurements. The error bars in the figures represent the standard deviation. Statistical analyses were performed using GraphPad Prism (version 10.4.1; GraphPad Software, San Diego, CA, USA). Data normality was assessed using the Shapiro–Wilk test. For paired data comparisons, a paired t-test was applied when the data followed a normal distribution, while the Wilcoxon signed-rank test was used for non-normally distributed data. For comparisons between independent groups, an unpaired t-test was conducted for normally distributed data, and the Mann–Whitney U test was employed when normality was not satisfied. Statistical significance was determined at a threshold of p < 0.05.

3. Results

3.1. Microalgal Cultivation in SW

3.1.1. Characteristics of DSW

Table S1 details the nutrient and metal ion concentrations of the DSW used in this experiment. The DSW was found to provide a nutrient-rich environment conducive to microalgal growth, corroborating the findings from previous research [38,39]. Essential metal ions such as Cu, Mn, Ni, and Zn, which are vital for microalgal metabolic processes, were adequately present in the DSW. Conversely, potentially toxic metal ions, including Cd, Cr, Pb, Ti, and Sn, were absent, indicating its suitability for microalgal cultivation. Notably, some metal ions were detected at higher concentrations than those reported in previous studies [40,41]. Despite these elevated levels, the microalga H. rubescens KNUA214 demonstrated robust growth, highlighting its resilience and adaptability to the DSW environment. This contrasted with other species screened in parallel, which showed poor growth under similar conditions, further underscoring H. rubescens KNUA214’s suitability for growth in nutrient-rich wastewater settings.

3.1.2. Strain Isolation

Molecular identification was conducted on the strain using the 18S rDNA (Figure 1) and tufA genes (Table S2). The sequences obtained from these analyses closely matched those of Scenedesmus rubescens strains, including KNUA042, IPPAS D-292, and KMMCC263, confirming the classification of the studied strain as Scenedesmus rubescens. Notably, the earliest described strain, Scenedesmus rubescens CCAP 232/1, was initially identified as Chlorella fusca var. rubescens before reclassification through phylogenetic analysis [42]. AlgaeBase lists this nomenclature as a synonym for Halochlorella rubescens P.J.L. Dangeard [43]. Morphologically, the strain exhibited the characteristic red pigmentation around the cell wall, a feature commonly observed in cultured colonies of H. rubescens [44]. Therefore, this phenotypic trait further supported its identification as H. rubescens, aligning with both the genetic and morphological evidence.

3.2. Growth Characteristics and Biomass Productivity

Based on the OD and DW measurements, BG-11 medium supplemented with 50% DSW demonstrated the highest growth rates, achieving an OD₆₈₀ of 2.456 (Figure 2a) and a DW of 1.23 g L⁻¹ (Figure 2b). The Chl-a and Chl-b concentrations, measured on days 4 and 8, revealed that the mixture of BG-11 and 50% DSW yielded the highest levels of Chl-a (10.64 μg mL⁻¹) and b (3.70 μg mL⁻¹) on day 4 (Figure 2c,d). In trials using 100% DSW, elevated nutrient and heavy metal concentrations were found to inhibit growth. The microscopic observations on day 8 illustrated significant morphological differences; the cultures in BG-11 maintained a uniform green coloration with well-defined internal structures, presumably chloroplasts (Figure 2e). In contrast, the 100% DSW cultures displayed clumped cells with large vacuoles and a lack of visible internal organelles (Figure 2f).

3.3. Nutrient Removal Efficacy

The nutrient removal capabilities of H. rubescens KNUA214 were assessed in 100% DSW. The study focused on key water pollution indicators, including TN, NH₃-N, TP, and SO₄²⁻. The nutrient concentrations were measured at the start of the experiment and after 8 days of treatment (Figure 3a). The analysis revealed significant reductions in nutrient levels, with TN reduced by 59.3%, NH₃-N by 67.7%, TP by 40.7%, and SO₄²⁻ by 1.9% (Figure 3b). These results demonstrated the effectiveness of H. rubescens KNUA214 in mitigating nutrient pollution in SW over an 8-day period.

3.4. Pigment Productivity

The carotenoid composition of H. rubescens KNUA214, cultivated in the DSW, was analyzed, focusing on astaxanthin, lutein, zeaxanthin, canthaxanthin, and beta-carotene (Figure 4). On day 4, the highest concentrations of astaxanthin, canthaxanthin, and beta-carotene were observed in BG-11 medium, with values of 0.147 mg g⁻¹, 0.039 mg g⁻¹, and 0.171 mg g⁻¹, respectively. A notable decrease in these concentrations was observed as the DSW level increased. By day 8, an overall increase in the carotenoid content was evident in the media supplemented with the DSW, except for beta-carotene in the BG-11 + 25% DSW mixture. Notably, the BG-11 + 50% DSW mixture showed the most significant increase, with concentrations reaching 0.190 mg g⁻¹ for astaxanthin, 0.064 mg g⁻¹ for canthaxanthin, and 0.260 mg g⁻¹ for beta-carotene. The lutein concentration was relatively stable across all conditions on day 4, ranging from 0.71 mg g⁻¹ to 0.85 mg g⁻¹; however, by day 8, the lutein content had doubled to 1.54 mg g⁻¹ under the BG-11 + 50% DSW condition. Zeaxanthin showed the highest concentration in 100% DSW on day 4, with a remarkable fivefold increase observed in the BG-11 + 25% DSW mixture by day 8. On day 8, the other carotenoids, except for zeaxanthin, reached their peak concentrations under the BG-11 + 50% DSW condition. The astaxanthin concentration increased 2.71-fold, from 0.07 mg g⁻¹ to 0.19 mg g⁻¹, while lutein showed a 2.09-fold increase, from 0.74 mg g⁻¹ to 1.54 mg g⁻¹. The canthaxanthin concentration increased 2.56-fold, from 0.03 mg g⁻¹ to 0.06 mg g⁻¹, and beta-carotene doubled, increasing from 0.13 mg g⁻¹ to 0.26 mg g⁻¹. These results indicated that 50% DSW supplementation offers an optimal environment for enhancing the production of carotenoids in H. rubescens KNUA214, suggesting a potential for scaled bioproduction under controlled dilution conditions.

3.5. Proximate and Ultimate Analyses

Across all the cultivation conditions, the biomass consistently exhibited a moisture content below 6%, volatile matter above 83%, and ash content below 12% (Table 1). Notably, as the concentration of the DSW increased, a corresponding increase in the percentage of volatile matter and a decrease in the ash content were observed. However, the ultimate analysis revealed no distinct trends attributable to the varying DSW concentrations, with the CV of the samples remaining relatively stable, ranging between 20 and 21 MJ kg⁻¹.

3.6. FAME Analysis and Biodiesel Quality Assessment

The fatty acid profiles derived from the microalgal biomass cultivated under the various conditions were analyzed to assess the impact of these conditions on lipid metabolism. The analysis revealed significant variations in the fatty acid composition, indicating the activation of differential biosynthetic pathways in response to environmental stress or nutrient availability. Among the saturated fatty acids (SFAs), palmitic acid (C16:0) was prominent, with percentages varying across the different cultivation conditions (Table 2). In all the cultivation conditions analyzed, oleic acid (C18:1) was the only monounsaturated fatty acid (MUFA) identified. Polyunsaturated fatty acids (PUFAs) showed a consistently high presence. Notably, α-linolenic acid (C18:3) was a significant component, highlighting its substantial contribution to the total fatty acid content.

In all the cultivation conditions, parameters such as the CFPP, υ, and ρ met EN14214 (European) [45] and ASTM D6751 (American) [46] standard (Table 3). However, due to the high content of PUFAs, parameters such as the IV and CN did not meet the standards. As the DSW proportion that was mixed with the control BG-11 medium increased, the IV increased and the CN decreased. At 100% DSW, the values were observed to return to levels similar to those seen with the BG-11 control.

4. Discussion

Enhanced microalgal growth was observed when it was cultivated in BG-11 medium supplemented with 50% DSW, corroborating previous studies that highlighted the benefits of combining SW with BG-11 for microalgal cultivation [47]. The utilization of 50% DSW not only capitalizes on the nutrient richness of wastewater but also mitigates the inhibitory effects associated with higher concentrations of heavy metals and other toxins found in less diluted wastewater. The high concentrations of Chl-a and Chl-b on day 4 indicated that the 50% DSW mixture provides an optimal balance of nutrients, which is crucial during the exponential growth phase of algae. However, a decline in chlorophyll levels by day 8, observed across all the conditions, likely indicated a transition to the stationary phase, where nutrient depletion or metabolic shifts lead to reduced chlorophyll synthesis [48]. In contrast, the cultures grown in 100% DSW displayed significant morphological stress, characterized by clumped cells and the formation of large vacuoles, which are typical indicators of toxic stress. These conditions confirmed the adverse effects of high metal ion concentrations in less diluted DSW that surpass the microalgae’s tolerance thresholds, leading to inhibited growth and cellular damage [49]. The notable morphological differences between the cultures grown in BG-11 with 50% DSW and those grown in 100% DSW emphasize the critical need for optimizing wastewater dilution. Proper dilution harnesses the benefits of nutrient availability while preventing the detrimental impacts of metal toxicity. Achieving this balance is vital not only for maximizing biomass yield but also for maintaining the physiological health of the algae, which is essential for sustainable bioenergy production.

The nutrient removal efficiency of H. rubescens KNUA214 in 100% DSW within 8 days—59.3% of TN, 67.7% of NH₃-N, 40.7% of TP, and 1.9% of SO₄²⁻—highlight its potential in wastewater treatment [50,51]. Mixed cultures can achieve enhanced performance by improving removal rates through synergistic effects. For instance, mixed cultures involving Chlorella vulgaris and Scenedesmus obliquus have shown superior nutrient reduction abilities compared to monocultures [52]. Additionally, employing rotating algae biofilm reactors that include bacteria can increase the SO₄²⁻ removal efficiency by up to 46% [53]. Research also suggests that DSW can significantly boost nutrient removal, reducing toxicity and enabling more effective management of TN and TP [54]. Incorporating these advanced strategies can significantly enhance the capability of H. rubescens KNUA214, making it a more robust option for sustainable wastewater treatment.

During the pigment analysis, the initial results revealed the highest concentrations of astaxanthin, canthaxanthin, and beta-carotene in BG-11 medium on day 4. By day 8, however, the addition of diluted swine wastewater (DSW) significantly enhanced the carotenoid yields, particularly under the BG-11 + 50% DSW condition. In this setup, most carotenoids, except for zeaxanthin, reached their peak concentrations. Specifically, astaxanthin increased 2.71-fold, lutein increased 2.09-fold, canthaxanthin increased 2.56-fold, and beta-carotene doubled compared to the initial levels. These findings suggest that components in the DSW, such as nitrogen and organic matter, acted as stressors that effectively promoted carotenogenesis. Stress-induced carotenoid synthesis is a well-documented phenomenon in microalgae. For instance, Haematococcus pluvialis produces astaxanthin under nutrient deprivation and light stress, primarily through the upregulation of carotenogenic genes such as phytoene synthase (PSY). Nitrogen depletion combined with varying light intensities has been shown to significantly influence astaxanthin accumulation, with optimal synthesis observed under low nitrogen levels and moderate light intensity to minimize cell mortality [55,56]. Similarly, Chlorella vulgaris demonstrated enhanced carotenoid synthesis, including lutein and beta-carotene synthesis, under nitrogen depletion stress. Stepwise nitrogen depletion has been found to facilitate carotenoid accumulation, while simultaneously affecting photosynthetic efficiency and proliferative activity, emphasizing the role of nitrogen stress as a critical driver of carotenogenesis in this species [57]. These results underscore the pivotal role of stress conditions, such as those induced by DSW, in enhancing carotenoid production. The BG-11 + 50% DSW condition effectively replicated such stressors, offering a promising strategy for maximizing carotenoid yields in H. rubescens KNUA214. This highlights the broader importance of stress physiology in microalgae not only for improving production efficiency but also for advancing sustainable and eco-friendly biotechnological applications. Further research to optimize these conditions is essential for scalable carotenoid bioproduction and sustainable industry practices.

The proximate and ultimate analyses provided key insights into the composition and energy content of the microalgal biomass, affirming its potential as a bioenergy feedstock. As shown in Table 1, the uniform moisture content across all the samples indicated that the drying methods after harvest were effective. The high levels of volatile matter suggested that the biomass largely consisted of compounds advantageous for combustion, enhancing burning efficiency [58,59]. The variations in the ash content, reflecting differences in mineral uptake by the algae, indicated that lower ash values, which minimize slagging and fouling during combustion, make these microalgal strains suitable for bioenergy applications without the need for extensive ash removal [60,61] l C and O levels, typical for organic biomasses, which support its conversion into bioenergy through biochemical or thermochemical processes. The favorable H:C ratios indicated potential for high energy yields [62], while the low S content across the samples implied fewer sulfur oxide emissions, aiding in compliance with environmental standards [63,64]. Therefore, the analyzed biomass, characterized by high C and low S levels, represents a viable candidate for sustainable biofuel production. This biomass can effectively be converted into high-energy biofuel with reduced environmental impacts, especially in terms of NOx emissions during combustion [63].

The analysis of the fatty acid profiles of the microalgal biomass cultivated under diverse conditions demonstrated significant variability, reflecting the adaptability of the microalgae to different environmental and nutritional contexts. Table 2 reveals that palmitic acid (C16:0) was consistently found across all the conditions, with concentrations ranging from 17.0% to 24.4%, indicating its importance in maintaining the structural integrity of cell membranes and suggesting robust membrane stability, which is essential for algae to thrive in different environments [65,66]. The concentration of oleic acid (C18:1), the only detected MUFA, varied between 10.5% and 18.5%. Its presence is beneficial for biodiesel production, reducing fuel viscosity and improving its cold flow properties, with its variability likely due to the different environmental stresses impacting algal metabolism [67,68]. PUFAs, especially α-linolenic acid (C18:3), were prominent, ranging from 36.6% to 44.9%. These PUFAs are crucial for cellular membrane fluidity and overall physiological processes, although their high concentrations pose challenges for biodiesel stability due to their oxidation susceptibility [69]. The diverse fatty acid profiles underscore the impact of cultivation conditions on lipid metabolism, suggesting that targeted adjustments can optimize biomass for specific uses, such as biofuel production or dietary supplementation. For instance, enhancing the MUFA content can improve biofuel properties, while boosting PUFAs can increase the nutritional value of supplements [70,71]. This strategic modulation of fatty acid profiles enhances our understanding of algal lipid biology and underscores the potential for commercial exploitation of microalgal biomass in various industries through aligning the growth conditions with the desired lipid outcomes to meet specific industry standards.

The IV serves as a critical indicator of unsaturation levels in biodiesel, significantly influencing its stability and performance [72,73]. The measurements in Table 3 show that the IV ranged from 134 to 173, reflecting a substantial presence of UFAs. This high unsaturation level enhances biodiesel’s cold flow properties, as unsaturated fats have lower melting points that improve performance in colder climates [74,75]. However, the high levels of PUFAs and their corresponding high IV values result in a low CN, which does not meet the standard requirements. Despite this, the high unsaturation level offers considerable advantages for biolubricant applications where reduced viscosity and high fluidity are beneficial [76,77]. Biolubricants that leverage the high unsaturation level can undergo chemical modifications to enhance properties such as lubricity and viscosity, making them suitable for a range of specialized applications. Oils can be classified based on their IV into drying (IV > 130), semi-drying (100 < IV < 130), or non-drying (IV < 100) oils, with higher unsaturation levels facilitating greater chemical adaptability for biolubricant applications [78]. This adaptability is not only useful in traditional fuel applications but also extends to high-performance lubricants, where specific performance characteristics are required. Modifying fatty acid profiles linked to high IV values enhances biodiesel’s lubricity and viscosity index, broadening its applications into markets requiring specialized lubricant performance.

5. Conclusions

The study demonstrated that employing Halochlorella rubescens KNUA214 in the treatment of DSW can lead to effective nutrient removal while concurrently enhancing carotenoid production. Additionally, the robust adaptability of H. rubescens KNUA214 to the nutrient-rich but potentially toxic environment of swine wastewater highlights its exceptional capabilities in bioremediation. This dual functionality underscores the potential of H. rubescens KNUA214 as a sustainable bioresource for both environmental management and high-value biochemical production, presenting a viable strategy for integrated waste treatment and resource recovery in agricultural settings. This approach leverages advanced biotechnological methods to enhance the economic viability and environmental sustainability of using microalgae in bioremediation and bioconversion processes.

Author Contributions

Conceptualization, H.-S.Y.; methodology, Y.-H.S., H.-S.S. and S.-B.P.; validation, Y.-H.S. and S.-B.P.; data curation, Y.-H.S. and H.-S.S.; writing—original draft preparation, Y.-H.S. and J.-M.D.; writing—review and editing, J.-M.D. and H.-S.Y.; funding acquisition, H.-S.Y. and S.-B.P. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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.

Figures and Tables

Figure 1. (a) Light microscope image of H. rubescens KNUA214. (b) Phylogenetic relationship of H. rubescens KNUA214 and its closely related species based on 18S rRNA sequence data. Numbers at nodes indicate percentage values derived from 500-bootstrap-analysis samples. The scale bar represents differences in nucleotide sequences.

Figure 2. (a) Optical density, (b) dry weight, and (c) chlorophyll a and (d) chlorophyll b concentrations of H. rubescens KNUA214 under different concentrations of DSW for 8 days. Microscopy images of H. rubescens KNUA214 in (e) BG-11 and (f) 100% DSW over an 8-day period.

Figure 3. (a) Nutrient concentration and (b) percentage of removal efficiency in 100% DSW by H. rubescens KNUA214 over an 8-day period. Statistical significance between groups is denoted as follows: ** p [less than] 0.01, *** p [less than] 0.001.

Figure 4. (a) Astaxanthin, (b) lutein, (c) zeaxanthin, (d) canthaxanthin, and (e) beta-carotene contents of H. rubescens KNUA214 cultivated under different concentrations of DSW on 4 and 8 days. Statistical significance between groups is denoted as follows: * p [less than] 0.05, *** p [less than] 0.001.

Table 1

Proximate and ultimate analyses of H. rubescens KNUA214 biomass over an 8-day period.

	BG-11	BG-11 +25% DSW	BG-11 +50% DSW	100% DSW
Proximate analysis (wt%)
Moisture	4.59	4.36	5.76	4.58
Volatile matter	83.66	83.96	84.21	86.52
Ash	11.81	11.82	10.03	8.89
Ultimate analysis (wt%)
Carbon (C)	45.4	44.9	45.4	45.3
Hydrogen (H)	6.51	6.64	6.73	6.44
Oxygen (O)	28.4	27.5	27.0	28.4
Nitrogen (N)	5.24	6.10	6.55	6.12
Sulfur (S)	0.49	0.56	0.57	0.37
CV 1 (MJ kg−1)	20.9	21.0	21.4	20.74

¹ Calorific value.

Table 2

Relative abundance of FAMEs in H. rubescens KNUA214 biomass under different concentrations of DSW over an 8-day period.

Fatty Acid	BG-11	BG-11 +25% DSW	BG-11 +50% DSW	100% DSW
C14:0	-	-	0.3	0.4
C16:0	20.2	18.2	17.0	24.4
C16:2 (ω6)	-	1.5	1.5	1.9
C16:3 (ω3)	-	4.2	-	-
C16:4 (ω3)	11.6	12.5	13.9	11.1
C18:0	-	1.5	0.9	1.7
C18:1	18.5	14.5	10.5	14.5
C18:2 (ω6)	10.4	8.4	8.7	9.2
C18:3 (ω3)	39.3	39.1	44.9	36.6
C18:4	-	-	2.2	-
Saturated fatty acids (%)	20.2	19.7	18.2	26.6
Monounsaturated fatty acids (%)	18.5	14.5	10.5	14.5
Polyunsaturated fatty acids (%)	61.3	65.8	71.3	58.9
Total	100	100	100	100

Table 3

Biodiesel quality analysis of H. rubescens KNUA214 biomass under different concentrations of DSW after 8 days.

	BG-11	BG-11 +25% DSW	BG-11 +50% DSW	100% DSW	EN14214Standard	ASTM D6751Standard
SV	145	178	167	165
IV	134	173	173	141	≤120
CN	37.8	35.3	32.3	40.3	≥51	≥47
DU	104	131	129	109
CFPP	−11.8	−9.3	−10.7	−14.2	≤0	≤−3
OS	5.8	5.3	5.2	5.7	≥8	≥3
υ	3.58	3.48	3.40	3.63	3.5–5.0	1.9–6.0
ρ	0.89	0.89	0.89	0.89	0.86–0.90	0.82–0.90

SV: Saponification value (mg KOH g⁻¹), IV: Iodine value (g I₂ 100 g⁻¹ fat), CN: Cetane number, DU: Degree of unsaturation, CFPP: Cold filter plugging point (°C), OS: Oxidation stability (110 °C), υ: Kinematic viscosity (mm² s⁻¹), ρ: Density (15 °C) g cm⁻³.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app142411650/s1, Table S1: Characteristics of the DSW used in this study; Table S2. Results from BLAST searches using the 18S rRNA and tufA sequences of H. rubescens KNUA214.

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