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Article

Bioprocess Integration of Candida ethanolica and Chlorella vulgaris for Sustainable Treatment of Organic Effluents in the Honey Industry

by
Juan Gabriel Sánchez Novoa
1,*,
Natalia Rodriguez
2,
Tomás Debandi
3,
Juana María Navarro Llorens
4,
Laura Isabel de Cabo
2 and
Patricia Laura Marconi
1
1
CONICET, CEBBAD-University Maimónides, Hidalgo 775, Ciudad, Autónoma de Buenos Aires C1405, Argentina
2
Museo Argentino de Ciencias Naturales B. Rivadavia-CONICET, Av. Patricias Argentinas 480, Ciudad, Autónoma de Buenos Aire C1405, Argentina
3
Instituto de Investigación en Ingeniería Ambiental 3iA, Universidad Nacional de San Martin, Francia 34, Villa Lynch B1650, Argentina
4
Departamento de Bioquímica y Biología Molecular, Facultad de Biología, Universidad Complutense de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(15), 6809; https://doi.org/10.3390/su17156809 (registering DOI)
Submission received: 19 June 2025 / Revised: 9 July 2025 / Accepted: 11 July 2025 / Published: 27 July 2025
(This article belongs to the Special Issue Research on Sustainable Wastewater Treatment)
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Abstract

Honey processing is closely linked to water pollution due to the lack of a specific wastewater treatment. This study proposes a sustainable and innovative solution based on two sequential bioprocesses using a real effluent from an Argentine honey-exporting facility. In the initial stage, the honey wastewater was enriched with a non-Saccharomyces yeast (Candida ethanolica), isolated from the same effluent. Treatment with this yeast in a bioreactor nearly doubled the total sugar removal efficiency compared to the control (native flora). Subsequent clarification with diatomaceous earth reduced the optical density (91.6%) and COD (30.9%). In the second stage, secondary sewage effluent was added to the clarified effluent and inoculated with Chlorella vulgaris under different culture conditions. The best microalgae performance was observed under high light intensity and high inoculum concentration, achieving a fivefold increase in cell density, a specific growth rate of 0.752 d−1, and a doubling time of 0.921 d. Although total sugar removal in this stage remained below 28%, cumulative COD removal reached 90% after nine days under both lighting conditions. This study presents the first integrated treatment approach for honey industry effluents using a native yeast–microalgae system, incorporating in situ effluent recycling and the potential for dual waste valorization.

Graphical Abstract

1. Introduction

Argentina ranks as the world’s third-largest honey producer and the second-largest exporter, with an annual average production of 70,000 tons [1]. This international trade has a significant economic impact at both regional and national levels [2]. However, the close relationship between production and market demand also leads to substantial environmental consequences for the producing country. Like other sectors of the food industry [3], this activity requires substantial volumes of water throughout most plant operations. This is directly related to an increase in the greywater footprint, mainly associated with wastewater generation across the supply chain [4].
Organic effluents generated during honey processing primarily contain honey residues, external contaminants (such as dust and soil particles) from drums used for transporting honey, and by-products from cleaning activities within the facility. The high levels of Chemical Oxygen Demand (COD), together with the low pH levels in the wastewater resulting from the cleaning of drums and the floors of the fractionation plant, require treatment prior to its discharge or infiltration into the ground. Currently, the available information on the management of this type of wastewater is limited, and the literature lacks descriptions of feasible in situ biological treatments. In practice, existing approaches range from highly hazardous and polluting methods (such as the direct discharge of these effluents without prior treatment) to unsustainable strategies, such as outsourced treatment, in which the waste is transported and treated ex situ using conventional technologies. Although this latter alternative ensures a certain level of treatment, it entails significant increases in operational costs and the environmental footprint, mainly associated with the carbon emissions from transport and off-site processing of the effluents.
Bee honey is known not only for its nutritional and therapeutic properties [5,6] but also for its bactericidal activity, attributed to various factors such as its low pH, high sugar concentration, hydrogen peroxide (H2O2) generation, the presence of antimicrobial peptides, and low nitrogen and phosphorus content [7]. These characteristics contribute to the complexity of honey wastewater, significantly limiting the applicability of conventional biological treatment systems, as only a few microorganisms can thrive under these conditions [7]. Therefore, to achieve effective biological treatment, it is essential to select microbial strains adapted and highly tolerant to such complex matrices.
In this context, identifying organisms present in the effluent is the first step in finding a solution to its treatment. Subsequently, evaluating their bioremediation potential will support the development of alternative biological treatments tailored to the effluents from honey processing facilities.
In previous research, a non-Saccharomyces yeast strain, identified as strain H3 of Candida ethanolica, was isolated from an industrial effluent at an Argentine honey-exporting company [8]. Its bioremediation potential was evaluated, positioning this yeast strain as a promising candidate for wastewater treatment in the beekeeping industry. However, due to the high COD levels in these effluents, integrated bioremediation approaches are needed, combining different microorganisms with complementary metabolic capabilities [8].
In this sense, microalgae have been extensively studied as bioremediation agents for effluents with organic and inorganic contamination [9]. Among them, Chlorella vulgaris one of the most frequently used species [10,11] due to its ability to adapt to various types of effluents and to remove nutrients, heavy metals, and organic matter, among other pollutants [12,13,14,15]. Recent studies have explored the synergistic potential of co-cultures involving microalgae and heterotrophic microorganisms, such as yeasts, for bioremediation [16,17]. Through their metabolism, yeasts transform complex sugars and other organic compounds into simpler and less toxic forms than can subsequently be assimilated by other organisms, such as microalgae, either in sequential or combined systems [18]. This approach offers several advantages: (i) mixed microbial cultures reflect dynamics typical of natural ecological systems; (ii) nutrient and metabolite exchange between species enhances co-culture stability and resilience; (iii) it facilitates biomass harvesting; and (iv) functional metabolite production, such as lipids, is enhanced through microbial interactions, contributing to waste valorization [16,19,20]. Furthermore, the co-utilization of microalgae and heterotrophic microorganisms has been shown to improve the overall efficiency of wastewater treatment [21]. Moreover, it has been reported that microalgae can use dissolved sugars in the culture medium as an alternative carbon source when lighting conditions do not allow photosynthesis (mixotrophy) [22,23].
The present study aims to develop a sequential biological treatment that integrates two complementary bioprocesses. In the first stage, the native C. ethanolica H3 strain is inoculated into the effluent for primary conditioning. In the second stage, the microalgae C. vulgaris is added along with a secondary wastewater stream generated in the administrative sector of the company (quite similar to domestic wastewater), which supports algal growth and completes the treatment. Under mixotrophic conditions, the microalgae can also assimilate sugars derived from the yeast metabolism, enhancing treatment efficiency in the absence of light [23].
This strategy, employing a native yeast–microalgae system, is the first reported method for managing all liquid waste generated by the beekeeping industry. It offers a novel, environmentally sustainable, and economically viable solution for the integrated treatment of honey processing wastewater.

2. Materials and Methods

2.1. Wastewater Samples and Microorganisms

2.1.1. Industrial Effluent

Wastewater is generated during honey processing and conditioning for export primarily in the following stages: (i) reception, consisting of the external washing of drums from beekeepers and collectors; (ii) sampling; and (iii) homogenization, where in two stages, tools, equipment, and facilities are cleaned. These liquid wastes present mixed contamination, with a predominant organic load from honey residues, along with a variety of substances such as dust, soil particles, and cleaning agents. Honey residual wastewater (RHW) is collected through a drainage system and conveyed via pipes to a 15 m3 storage tank located outside the facility (Table 1). There, it is stored until its final disposal via ex-situ treatment. RHW samples were obtained from this tank at a honey processing and export plant located in the Canning District of Buenos Aires Province, Argentina, between September 2022 and July 2023.

2.1.2. Sewage Effluent

The administrative activities of the company generate grey- and blackwater with characteristics similar to domestic wastewater (RTW), originating from restrooms and changing rooms, kitchens, and dining areas (Table 1). These effluents are collected in a septic tank and discharged untreated into a soil absorption system. RTW samples were collected directly from this septic tank. The collection of RHW and RTW samples was conducted following appropriate biosafety standards.

2.1.3. Microbial Strains and Their Maintenance

C. ethanolica strain H3 was previously isolated by our research group from RHW [8]. This strain is naturally adapted to the complex environmental conditions of this industrial effluent and has demonstrated high bioremediation potential [8]. The strain was deposited and registered under code CoMIM4426 in the genetic bank of the National Institute of Agriculture Technology (INTA), Mendoza, San Juan, Argentina. It was maintained in 50 mL of Yeast Extract Beef (YEB) medium in 250 mL Erlenmeyer flasks at 28° ± 2 °C in a rotary shaker at 100 rpm. The composition of the YEB medium is as follows (g/L): Meat (Beef) Extract (5.00), Yeast Extract (1.00), Peptone from Meat (5.00), sucrose (5.00), and Magnesium Sulphate Anhydrous (0.24).
C. vulgaris native strain LMPA-40 (National Biological Data System, SNDB-173) was obtained from the Faculty of Natural Sciences of the National University of Patagonia San Juan Bosco, Argentina. It was cultured in 50 mL of synthetic wastewater medium (WS) [24] in 250 mL Erlenmeyer flasks. The cultures were incubated at 24° ± 2 °C on a rotary shaker at 100 rpm under a 16 h PAR photoperiod (14,000 kJ, 400 μmol photon/m2 s). The composition of the WS medium is as follows (mg/L): CH3COONH3 (240.88), KH2PO4 (43.94), NaHCO3 (125.00), CaCl2 (10.00), FeCl2 (0.375), MnSO4 (0.038), ZnSO4 (0.035), MgSO4 (25.00), and Yeast Extract (50.00).

2.2. Experimental Design and Measurements

Figure 1 shows the overall strategy for honey-processing wastewater bioremediation using a dual-microorganism system (C. ethanolica and C. vulgaris).
The first stage was conducted in a 1.5 L stirred tank bioreactor (Minifors, Infors, ® Basel, Switzerland). The non-aerated bioreactor was equipped with mechanical agitation provided by a marine propeller at 50 rpm. The temperature was maintained at 28° ± 2 °C [25]. Three treatments were applied: raw effluent RHW; autoclaved RHW (Arcano 80 L® Chamberland, Rosario, Argentina) at 0.1 MPa for 20 min (RHW A); and RHW inoculated with H3 strain (2% v/v, DO 600 nm: 1.36 ± 0.02) (RHW + H3). After 5 days of batch culture, the effluent was filtered through a gravity-flow column (238 cm3) packed with diatomaceous earth, obtaining a filtered effluent (RHWF). The RHWF was collected and mixed with a sewage effluent (RTW) in 1:1 ratio (v/v), pH-adjusted to 7.00 with 1N NaOH and designated as RW.
The second stage involved a factorial experimental design over 4 days (Figure 1). Two factors were tested:
1.
Cell density: RW was inoculated with C. vulgaris to achieve the following initial concentrations:
X1: 2.78 × 105 cells/mL.
X2: 3.97 × 105 cells/mL.
2.
Light intensity:
High light intensity (*): culture under high PAR intensity (14,000 k, 400 μmol photon/m2 s) (autotrophic conditions).
Low light intensity: culture under low PAR intensity (14,000 k, 100 μmol photon/m2 s) (mixotrophic conditions).
Both conditions maintained a photoperiod of 16 h. A control treatment was also included, consisting of RW without C. vulgaris inoculation, cultured under high PAR intensity (14,000 k, 400 μmol photon/m2 s).
All treatments with microalgae were carried out in Erlenmeyer flasks (50 mL working volume; 250 mL total volume) incubated at 24° ± 2 °C on an orbital shaker at 100 rpm.

2.3. Analytical Methods

Cell density (DO) for Candida ethanolica H3 was measured at 600 nm using a spectrophotometer (UV-mini 1240, Shimadzu®, Kyoto, Japan). C. vulgaris cell number was determined by counting in a Neubauer chamber.
Kinetic cell growth was estimated using the following formula:
dx/(dt) = µ*X
where X represents the biomass obtained at time (t) and μ is the specific growth rate.
The duplication time was calculated as
ln(2)/µ
The concentrations of monosaccharides (glucose and fructose), sucrose, and total sugar (glucose, fructose, and sucrose) in the culture medium were determined using the colorimetric phenol–sulfuric acid method, as described in [26,27], with glucose, fructose and sucrose (Sigma-Aldrich®, St. Louis, MO, USA) as the standards.
The Chemical Oxygen Demand (COD), soluble reactive phosphorous (SRP), and ammoniacal nitrogen (N-NH4) were determined according to [28].
Escherichia coli total and fecal coliforms were quantified using Petrifilm systems (3M®, St. Paul, MN, USA).

2.4. Statistical Analysis

All analytical determinations were performed in triplicate. The results were evaluated using ANOVA with Tukey’s post hoc test for multiple comparisons or the Kruskal–Wallis test for non-normally distributed variables using Infostat software v 2020 [29,30].

3. Results and Discussion

Honey is composed of approximately 80% carbohydrates, primarily glucose and fructose (75%), and a smaller proportion of sucrose (less than 5%). In residual honey wastewater, both the content and proportions of these sugars are altered. These modifications are attributed to several factors, such as dilution (approximately 100-fold), the incorporation of other residues present on the honey drum surfaces, and the contribution of by-products derived from equipment and facility cleaning activities [31,32,33,34,35]. The resulting mixture, together with the prolonged storage of the effluent prior to final disposal, promotes microbial metabolic activity, leading to increased biomass and COD levels up to 40 times higher than the discharge limits established by the local environmental authority (700 mg O2/L, ADA Res. 336/03). In addition to a high sugar content, these effluents exhibit a low pH and a deficiency of essential macronutrients, particularly soluble reactive phosphorus and ammonium nitrogen (Table 1).

3.1. Yeast Treatment

During RHW treatment, an increase in biomass corresponding to native microflora was observed, along with a 30% reduction in total sugar content, comprising, approximately, 42% monosaccharides and 58% sucrose (Figure 2). In environments with an excess of carbon sources, such as glucose, fructose, and sucrose, yeasts can rapidly hydrolyze these compounds into simpler forms [31,36]. Furthermore, native microbiota can utilize these compounds as nutrients through high- or low-affinity transport systems, increasing the overall efficiency of the process [18,36]. In contrast, the axenic effluent RHW A, devoid of native microbiota, showed neither yeast growth nor significant substrate consumption, with only an 8% total sugar reduction (Figure 2).
Inoculation with C. ethanolica H3 (2% v/v RHW + H3) significantly enhanced sugar removal, nearly doubling that observed with the native microflora treatment (RHW) (Figure 2). The RHW + H3 system showed a classical batch culture pattern, with peak exponential growth and substrate consumption occurring on day 3. This treatment achieved 53% sugar removal within the first three days (Figure 2), with a specific growth rate (μ) of 0.607 d−1 and a doubling time of 1.14 days.
By the end of the RHW + H3 treatment, the pH decreased to 3.96 ± 0.06, while the COD increased by 8.7% compared to initial values (Table 1 and Table 2). This COD rise could be attributed to oxygen consumption as well as the synthesis, accumulation, and availability of new organic compounds in the aqueous matrix and suspended biomass [37].
Following this stage, the effluent (RHW + H3) was filtered using diatomaceous earth to obtain RHWF. This filtering medium is an inert, naturally derived material composed of rigid, highly porous, and morphologically diverse nanostructures, making it an efficient and environmentally friendly alternative for industrial filtration systems [38,39]. This filtering medium effectively removed turbidity (91.6%) and reduced the COD by 30.9% (Figure 3, Table 2). In addition to acting as a physical barrier for the removal of suspended solids and microorganisms, the vertical flow column likely improved dissolved oxygen levels in the filtered water, improving the oxidative conditions of the system [40]. The total residence time for this stage (including RHW + H3 treatment and filtration) was five days.

3.2. C. vulgaris Treatment

The low pH and severe nutrient deficiency of RHWF, primarily soluble reactive phosphorus and ammonium nitrogen, create hostile environmental conditions for the development of C. vulgaris strain LMPA-40 during the initial treatment stage. Previous experiments confirmed that these conditions significantly inhibit microalgal growth. The addition of RTW (Table 1) to RHWF as a second source of organic nutrients enriched the clarified effluent with essential nutrients and eliminated the need for synthetic chemical additives commonly used in microalgae cultivation. This step was key to improving the ecological sustainability and technological feasibility of the treatment process.
The nutrient contribution of RTW (Table 2) (RHWF:RTW) created favorable conditions for the development of microalgae and other beneficial microorganisms during the following treatment stage [41,42,43] but also helped regulate the pH and dilute the pollutant load. The resulting mixture (RW) showed a 44.4% decrease in COD and a 38.1% reduction in total sugars (Figure 3 and Figure 4; Table 2), representing a cumulative COD removal of 61.6% up to this point in the process. Also, Table 1 shows the concentrations of E. coli, fecal coliforms, and total coliforms at the start of the RTW treatment. As previously mentioned, all treatments involving C. vulgaris led to the complete elimination of pathogenic microorganisms by the end of the second treatment stage, with a population reduction of approximately 100% [12]. However, the same result was observed in the RW control (no C. vulgaris), suggesting that the complex chemical nature of the mixed effluent may itself prevent the survival of these pathogens [7]. This highlights the microbial safety of the treated effluent and may reduce the need for additional disinfection steps.
During the microalgae treatment stage, the highest biomass production of C. vulgaris occurred in cultures under high PAR light intensity conditions and with double inoculum density (RW + CHL* X2; Figure 5). In this condition, C. vulgaris achieved a fivefold increase in biomass over 4 days, with a specific growth rate (µ) of 0.752 d−1 and a doubling time (dt) of 0.921 days. At the end of the experiment, total sugar reduction reached 20.5%, along with 92.7% ammonium removal and 79.3% soluble reactive phosphorus (SRP) removal (Table 2, Figure 4). In contrast, under the same inoculum density but with low PAR light intensity (RW + CHL X2), no significant biomass growth was observed. However, this condition resulted in the highest sugar removal (25.4%), indicating the microalgae’s mixotrophic behavior and increased reliance on organic carbon when light is limited (Figure 4 and Figure 5). Nutrient removal in this treatment did not differ significantly from the high-light-intensity condition, reaching 89.6% ammonium and 61.3% SRP removal (Table 2). This behavior has been reported previously, indicating that microalgae can adapt to unfavorable lighting by metabolizing sugars to sustain growth and survival [37,44,45].
Treatments with lower cell density inoculum (X1) showed limited performance: no biomass growth was observed, and sugar removal efficiency was below 17% and below 11% for RW + CHL* X1 and for RW + CHL X1, respectively. However, nutrient removal over four days reached 80.1% ammonium and 51.3% SRP under the high-light condition and 72.6% ammonium and 36.5% SRP under the low-light condition.
All C. vulgaris treatments significantly reduced COD compared to the RW control (Figure 3). Although the native microbiota in the RW effluent contributed to the COD reduction, the most pronounced reductions occurred with a high initial cell density (X2) under both light conditions, likely due to the strain’s ability to alternate between autotrophic and heterotrophic metabolism (Table 2; Figure 5). This allowed C. vulgaris to assimilate CO2 during photosynthesis and to use organic carbon (e.g., sugars, acetate, and glycerol) under mixotrophic or dark conditions [42,44,46,47,48]. Higher initial inoculum densities (X2) also enabled more rapid biomass accumulation, with cell growth evident after just 2 days compared to 3 days in the lower-density treatments.
The complete integrated bioprocess, which included inoculation with the C. ethanolica H3 yeast strain, clarification, enrichment with RTW, and subsequent high-density C. vulgaris LMPA-40 inoculation (X2), resulted in a cumulative COD reduction of 90.6% under high-light conditions and 90.8% under low-light conditions (Figure 3). Treatments with C. vulgaris at lower initial inoculum densities (X1) reached 77.5% and 79.8% COD removal under high and low light, respectively. In all cases, removals of both COD and total sugar were achieved within a 9-day period (Figure 3 and Figure 4). Also, RTW revalorization as a nutrient source offers a circular, low-cost strategy to support microalgal growth [49].
Fida et al. (2025) [50] lists the results of treatment methods for sugar industry wastewater and distiller’s grain wastewater. Although the COD levels of honey wastewater are much higher than those from sugar and distiller grain industries, the treatment efficiencies reported here are comparable to the best biological methods documented for those sectors. Aerobic bioprocesses used in the sugar industry are generally more cost effective than physicochemical methods, while still achieving high efficiency in the removal of organic material. However, there is currently no published information on the treatment of residual honey wastewater that would allow for a more comprehensive comparison. The integrated bioprocess, combining yeast isolated from RHW and microalgae, represents an efficient, sustainable, and low-cost alternative to conventional physicochemical approaches.

4. Conclusions

The integrated bioprocess, which combines sequential treatments with a yeast (C. ethanolica) and microalgae (C. vulgaris), proved highly effective in reducing the primary pollutants found in industrial effluent from honey processing within a total residence time of just 9 days. This approach is based on the synergy between respiratory metabolism (from yeast) and either autotrophic or heterotrophic pathways (from microalgae), enabling the progressive biotransformation of complex organic compounds into simpler, bioavailable forms. Large-scale honey fractionation activity requires large volumes of water and generates highly polluted effluents that require an efficient treatment to ensure safe discharge or potential reuse. The proposed method demonstrated substantial potential for treating complex effluents with high levels of COD and sugars, achieving values near those permitted by Argentine national discharge regulations. Moreover, this system allows the integration of domestic effluents (such as greywater and blackwater from the other facility sectors), promoting a comprehensive and decentralized solution for managing all liquid waste produced by honey industry operations. This feature reinforces its value as a nature-based solution, characterized by low cost, low energy consumption, adaptability, and alignment with circular economy principles. Ultimately, the process contributes to reducing both the greywater footprint and the carbon footprint of the generating facility while promoting environmental sustainability.

Author Contributions

J.G.S.N.: conceptualization, investigation, formal analysis, writing—original draft, writing—review and editing, visualization. N.R.: data curation, writing—review and editing. T.D.: data curation, writing—review and editing. L.I.d.C.: writing—review and editing, supervision, funding acquisition. J.M.N.L.: writing—review and editing. P.L.M.: conceptualization, investigation, formal analysis, supervision, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Agencia Nacional de Promoción Científica y Tecnológica (PICT 2020-2681), CONICET (PIP 1122021 0100641) and Fund. Científica Felipe Fiorellino, U. Maimónides, Argentina (to J.G.S.N. and P.L.M.). The APC was funded by Fund. Científica Felipe Fiorellino, U. Maimónides, Argentina.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to it being “Not applicable” for studies not involving humans or animals.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data is available in the paper.

Acknowledgments

The authors are grateful to the “Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo (CYTED)” through RED RENUWAL 320rt0005.

Conflicts of Interest

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

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Figure 1. Schematic representation of the sequential treatment of honey-processing effluents using C. ethanolica strain H3 and C. vulgaris strain LMPA-40 based on complementary metabolic pathways for integrated bioremediation and water quality improvement.
Figure 1. Schematic representation of the sequential treatment of honey-processing effluents using C. ethanolica strain H3 and C. vulgaris strain LMPA-40 based on complementary metabolic pathways for integrated bioremediation and water quality improvement.
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Figure 2. Growth kinetics of C. ethanolica, measured by biomass (Abs at 600 nm), and total sugar concentration (mg/L), over 5 days under the following treatments: RHW, residual honey water; RHW + H3, RHW inoculated with C. ethanolica strain H3; RHWA, autoclaved RHW. Bars represent standard deviation (s.d.) of triplicate samples. Significant differences between treatments at the same time point (p < 0.05) are indicated by black stars (biomass) and clear stars (substrate).
Figure 2. Growth kinetics of C. ethanolica, measured by biomass (Abs at 600 nm), and total sugar concentration (mg/L), over 5 days under the following treatments: RHW, residual honey water; RHW + H3, RHW inoculated with C. ethanolica strain H3; RHWA, autoclaved RHW. Bars represent standard deviation (s.d.) of triplicate samples. Significant differences between treatments at the same time point (p < 0.05) are indicated by black stars (biomass) and clear stars (substrate).
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Figure 3. COD levels (mg O2/L) during a 9-day integrated bioprocess using C. ethanolica and C. vulgaris for the remediation of the honey industry effluent across various treatment stages. RHW: residual honey water; RHWF: filtered residual honey water; RW: RHWF mixed with septic tank effluent (RTW) in a 1:1 (v/v) ratio; RW + CHL (X1): C. vulgaris at low-light condition, standard inoculum density; RW + CHL* (X2): C. vulgaris at high-light condition, double inoculum density; RW + CHL (X2): C. vulgaris at low-light condition, double inoculum density; CTRL: control treatment containing RW. Note: CHL* denotes high-light condition, while CHL indicates low-light condition. Bars represent s.d. of triplicates. Stars indicate significant differences between treatments RW + CHL (X2), RW + CHL* (X2), and RW final (p < 0.05).
Figure 3. COD levels (mg O2/L) during a 9-day integrated bioprocess using C. ethanolica and C. vulgaris for the remediation of the honey industry effluent across various treatment stages. RHW: residual honey water; RHWF: filtered residual honey water; RW: RHWF mixed with septic tank effluent (RTW) in a 1:1 (v/v) ratio; RW + CHL (X1): C. vulgaris at low-light condition, standard inoculum density; RW + CHL* (X2): C. vulgaris at high-light condition, double inoculum density; RW + CHL (X2): C. vulgaris at low-light condition, double inoculum density; CTRL: control treatment containing RW. Note: CHL* denotes high-light condition, while CHL indicates low-light condition. Bars represent s.d. of triplicates. Stars indicate significant differences between treatments RW + CHL (X2), RW + CHL* (X2), and RW final (p < 0.05).
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Figure 4. Total sugar concentration (mg/L) over a 9-day integrated bioprocess using C. ethanolica and C. vulgaris for honey industry effluent remediation. Treatments: RHW + H3: RHW inoculated with C. ethanolica H3 strain; RHWF: filtered RHW; RW + CHL* (X2): C. vulgaris at high-light condition with doubled cell density inoculum; RW + CHL (X2): C. vulgaris at low-light condition with doubled cell density inoculum; RW final: control treatment containing untreated RW after 4 days of treatment; RTW addition: sewage addition (v:v). Bars represent s.d. of triplicates.
Figure 4. Total sugar concentration (mg/L) over a 9-day integrated bioprocess using C. ethanolica and C. vulgaris for honey industry effluent remediation. Treatments: RHW + H3: RHW inoculated with C. ethanolica H3 strain; RHWF: filtered RHW; RW + CHL* (X2): C. vulgaris at high-light condition with doubled cell density inoculum; RW + CHL (X2): C. vulgaris at low-light condition with doubled cell density inoculum; RW final: control treatment containing untreated RW after 4 days of treatment; RTW addition: sewage addition (v:v). Bars represent s.d. of triplicates.
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Figure 5. Growth kinetics of C. vulgaris in RW medium over 4 days measured by cell density (cells/mL). The growth conditions are as follows: RW + CHL* (X1): high-light condition with standard inoculum density; RW + CHL (X1): low-light condition with standard inoculum density; RW + CHL* (X2): high-light condition with double inoculum density; RW + CHL (X2): low-light condition with double inoculum density. Note: CHL* denotes high-light condition, while CHL indicates low-light condition. Bars represent s.d. of triplicates. Stars indicate significant differences between treatments at the same time point (p < 0.05).
Figure 5. Growth kinetics of C. vulgaris in RW medium over 4 days measured by cell density (cells/mL). The growth conditions are as follows: RW + CHL* (X1): high-light condition with standard inoculum density; RW + CHL (X1): low-light condition with standard inoculum density; RW + CHL* (X2): high-light condition with double inoculum density; RW + CHL (X2): low-light condition with double inoculum density. Note: CHL* denotes high-light condition, while CHL indicates low-light condition. Bars represent s.d. of triplicates. Stars indicate significant differences between treatments at the same time point (p < 0.05).
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Table 1. Physicochemical parameters of residual honey water (RHW) and sewage effluent (RTW) at the beginning of the assay.
Table 1. Physicochemical parameters of residual honey water (RHW) and sewage effluent (RTW) at the beginning of the assay.
Untreated Samples
ParameterRHWRTW
pH4.33 ± 0.036.57 ± 0.16
COD (mg O2/L) 27,167 ± 192731 ± 33
Total sugar (mg/L) 3690 ± 27510 ± 0.02
NH4-N (mg/L) 0.02 ± 0.0032.9 ± 2.8
Soluble reactive phosphorous (mg/L) 0.03 ± 0.002.50 ± 0.39
Escherichia coli (CFU/100 mL)051,200 ± 2550
Total coliforms (CFU/100 mL)074,800 ± 4580
Fecal coliforms (CFU/100 mL)0126,000 ± 5820
Table 2. Physicochemical parameters across different stages and treatment conditions. RHW + H3: raw honey wastewater (RHW, see Table 1) inoculated with C. ethanolica after 5 days of yeast-based treatment; RHWF: effluent obtained after filtration of RHW + H3 through diatomaceous earth; RW: dilution of RHWF with sewage effluent (RTW, see Table 1); RW + CHL (X1): RW inoculated with Chlorella vulgaris at 2.78 × 105 cells/mL under heterotrophic conditions; RW + CHL (X1)*: RW inoculated with C. vulgaris at 2.78 × 105 cells/mL under high-light condition; RW + CHL (X2): RW inoculated with C. vulgaris at 3.97 × 105 cells/mL under low-light condition; RW + CHL (X2)*: RW inoculated with C. vulgaris at 3.97 × 105 cells/mL under high-light condition. Microalgal treatments were evaluated after 4 days of cultivation.
Table 2. Physicochemical parameters across different stages and treatment conditions. RHW + H3: raw honey wastewater (RHW, see Table 1) inoculated with C. ethanolica after 5 days of yeast-based treatment; RHWF: effluent obtained after filtration of RHW + H3 through diatomaceous earth; RW: dilution of RHWF with sewage effluent (RTW, see Table 1); RW + CHL (X1): RW inoculated with Chlorella vulgaris at 2.78 × 105 cells/mL under heterotrophic conditions; RW + CHL (X1)*: RW inoculated with C. vulgaris at 2.78 × 105 cells/mL under high-light condition; RW + CHL (X2): RW inoculated with C. vulgaris at 3.97 × 105 cells/mL under low-light condition; RW + CHL (X2)*: RW inoculated with C. vulgaris at 3.97 × 105 cells/mL under high-light condition. Microalgal treatments were evaluated after 4 days of cultivation.
Yeast TreatmentFiltrationSewage AdditionMicroalgae Treatment
ParameterRHW + H3RHWFRWRW + CHL (X1)RW + CHL * (X1)RW + CHL (X2)RW + CHL * (X2)
pH 3.96 ± 0.063.98 ± 0.067.23 ± 0.005.83 ± 0.298.00 ± 0.007.30 ± 0.297.50 ± 0.00
COD (mg O2/L) 29,533 ± 88218,766 ± 18910,433 ± 6395486 ± 3556120 ± 2402486 ± 1582553 ± 124
Total sugar (mg/L) 1672 ± 6.151539 ± 57.0953 ± 17.0893 ± 10.8810 ± 30.8602 ± 5.31774 ± 15.4
NH4-N (mg/L) 0.03 ± 0.010.02 ± 0.0019.1 ± 1.925.22 ± 0.163.79 ± 0.151.99 ± 0.181.39 ± 0.05
Soluble reactive phosphorous (mg/L) 0.03 ± 0.010.03 ± 0.001.31 ± 0.120.84 ± 0.080.64 ± 0.190.51 ± 0.190.27 ± 0.07
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Sánchez Novoa, J.G.; Rodriguez, N.; Debandi, T.; Navarro Llorens, J.M.; de Cabo, L.I.; Marconi, P.L. Bioprocess Integration of Candida ethanolica and Chlorella vulgaris for Sustainable Treatment of Organic Effluents in the Honey Industry. Sustainability 2025, 17, 6809. https://doi.org/10.3390/su17156809

AMA Style

Sánchez Novoa JG, Rodriguez N, Debandi T, Navarro Llorens JM, de Cabo LI, Marconi PL. Bioprocess Integration of Candida ethanolica and Chlorella vulgaris for Sustainable Treatment of Organic Effluents in the Honey Industry. Sustainability. 2025; 17(15):6809. https://doi.org/10.3390/su17156809

Chicago/Turabian Style

Sánchez Novoa, Juan Gabriel, Natalia Rodriguez, Tomás Debandi, Juana María Navarro Llorens, Laura Isabel de Cabo, and Patricia Laura Marconi. 2025. "Bioprocess Integration of Candida ethanolica and Chlorella vulgaris for Sustainable Treatment of Organic Effluents in the Honey Industry" Sustainability 17, no. 15: 6809. https://doi.org/10.3390/su17156809

APA Style

Sánchez Novoa, J. G., Rodriguez, N., Debandi, T., Navarro Llorens, J. M., de Cabo, L. I., & Marconi, P. L. (2025). Bioprocess Integration of Candida ethanolica and Chlorella vulgaris for Sustainable Treatment of Organic Effluents in the Honey Industry. Sustainability, 17(15), 6809. https://doi.org/10.3390/su17156809

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