NRMJ_10_3_331-352

Introduction

Pectinases are a heterogeneous group of enzymes of technological interest that degrade pectic polysaccharides in the plant cell walls (de Souza and Kawaguti, 2021; Jin et al., 2024). Their classification is based on their mode of action on pectin. Thus, these enzymes are classified into three groups (Murad and Azzaz, 2011). First, the protopectinases, or pectinases, which hydrolyze the insoluble protopectin into a highly polymerized soluble pectin. On the other hand, the enzymes that modify the structure of pectin include both the pectin methylesterases that demethylate the methoxyl groups, and the depolymerization enzymes, such as pectin lyases, pectate lyases, polygalacturonases and polymethylgalacturonases, which catalyze the trans-elimination lysis and hydrolytic cleavage of the glycosidic bonds in the pectic substances (Murad and Azzaz, 2011). These enzymes are present in plants, microorganisms, nematodes, and insects and express broad substrate specificity (de Souza and Kawaguti, 2021). They are therefore considered promising biocatalysts for all processes that require pectin hydrolysis (Hailé and Ayele, 2022). In the fruit and vegetable juice industry, these pectinases improve clarification, stability, and extraction yield, reduce viscosity, and enhance organoleptic qualities (Sharma et al., 2017; Alqahtani et al., 2022; Haile and Ayele, 2022; Sheladiya et al., 2022). They also play a role in the processing of coffee, tea, cocoa, and tobacco by facilitating fermentation, mucilage removal, and release of bioactive compounds and aromas (Oumer and Abate, 2017; Samanta, 2019; Mulluye and Atnafu, 2022). Their applications also extend to the extraction of oils and plant compounds, animal feed, valorization of agri-food waste, bioethanol production, paper processing and the textile industry, where they used in combination with cellulase to improve the cotton fibers (Anand et al., 2020; Ruchika et al., 2020; de Souza and Kawaguti, 2021; Shrestha et al., 2021; Khan et al., 2025). A previous study demonstrated antitumor effects of pectinases on colorectal and endothelial cells (Cho et al., 2019). These enzymes account for approximately 25% of food enzymes sold and used worldwide, and their demand continues to increase (Jayani et al., 2005; Amin et al., 2019). Most commercially available pectinases are of fungal origin and industrial production began in 1970 (Haile and Ayele, 2022). Although fungal pectinases are the most studied and the main source of these enzymes, their production can present challenges, including relatively slow growth, sometimes complex nutritional requirements, and, in some cases, the co-production of undesirable secondary metabolites such as mycotoxins and allergenic compounds, which may complicate the purification and increase the production costs (Geris et al., 2024). These challenges, combined with the growing demand for industrial pectinases, justify exploring the new microbial sources. In this context, bacteria represent a promising alternative because they exhibit rapid growth and extracellular enzyme secretion, thereby simplifying recovery and reducing production costs (Ramin and Allison, 2019). Furthermore, they can adapt to a wide range of conditions, covering a broad spectrum of pH and temperatures. Furthermore, bacteria are biological systems that are generally more amenable to strain improvement approaches, particularly through selection, mutagenesis, or genetic engineering, thereby increasing enzyme production. Their tolerance to phenolic inhibitors, combined with their shorter generation time compared to fungi, also allows for faster evaluation of the effects of multiple culture parameters (Sui et al., 2025). This speed offers advantages in the application of multifactorial optimization methods, such as response surface methodology (RSM), to evaluate the influence of the interactions between several factors and identify the optimal production conditions. Available studies focused primarily on the enzymatic activity and optimization of pectinase production conditions (Jalil and Ibrahim, 2021; Alqahtani et al., 2022; Blanco Crivelli et al., 2024; Satpathy et al., 2025; Panchal et al., 2026). However, these studies rarely addressed the preliminary safety assessment of the producing strains, particularly through investigating their hemolytic activity, even though this aspect is important for considering their use in food applications. The decaying tropical fruits, such as cashew apples, remain relatively unexplored as potential niches for pectinase-producing bacteria. The cashew apples natural state of decomposition could be exploited to isolate microorganisms capable of degrading cell-wall polysaccharides, especially pectin. In this context, this study aimed to explore the decomposition of cashew apples as a potential local source of the pectinolytic bacteria. It combined screening for enzymatic activity, preliminary safety assessment of isolates, and statistical optimization of pectinase production conditions in a high-performing, non-hemolytic strain. This approach could help identify the bacterial strains of interest for future biotechnological applications.

Materials and Methods

Isolation and screening of the pectinolytic bacteria

Bananas, mangoes, oranges, cashew apples, and soumbala, a condiment made from fermented Parkia biglobosa seeds, served as matrices for isolating the pectinolytic bacteria. For each type of fruit, a single composite sample was created from healthy fruit randomly collected from 5 to 7 vendors in different markets in Ouagadougou, the capital of Burkina Faso (Figure 1). The fruit was then stored for 21 d at room temperature until visible signs of spoilage appeared, before being used for the isolation of pectinolytic bacteria. Soumbala, being a fermented product, was used directly after its random collection from 5 vendors. Stock solutions were prepared by mixing 10 g of each sample into 90 ml of 0.9% (w/v) NaCl, followed by performing serial dilutions. A 100 μl volume of each dilution was inoculated onto a reconstituted culture medium containing pectin as the sole carbon source, according to the method described by Priyanka and Prajna (2019). The reconstituted culture medium, MGR medium (Medium growth receptor) solution was composed of 10 g pectin, 0.1 g MgSO4, 3 g K2HPO4, 2 g KH2PO4, 5 g NaCl, 3 g (NH4)2HPO4, and 25 g agar per 1 l of dist. water, and the pH was adjusted to 6. The plates were incubated at 37 °C for 96 h (Priyanka and Prajna, 2019). After incubation, all the developed bacterial colonies were purified by successive sub-culturing onto a pectin agar medium. The purified isolates were stored at 4°C in nutrient broth (NB) supplemented with 15% glycerol for further studies. To detect the pectinase activity, pure bacterial isolates were inoculated by spot deposition on the surface of MGR agar and incubated at 37 °C for 24 h. After incubation, the plates were covered with iodine/ potassium iodide (I2/KI) solution (0.1% w/v) to identify the development of transparent halo around the colonies, indicating that the bacteria hydrolysed the pectin (Mercimek Takcı and Turkmen, 2016). The pectin degradation index (PDI) (Equation 1) was calculated as described by Haile and Kang (2019). Bacterial isolates exhibiting a halo around the colonies were noted for the haemolysis test.

Haemolysis test

Columbia agar (OXOID Ltd, PB pH 7.5 ± 0.2, Wesel, Germany) supplemented with 5% (V/V) sheep blood (CA-SB) was used to evaluate the haemolytic capacity of the isolates. Spot inoculation was performed, and incubation was carried out at 37°C for 48 h (Lee et al., 2023). The formation of a clear or green halo around the bacterial colonies indicated β-haemolytic or α-hemolytic activity, respectively. Isolates without a halo around the colonies were regarded as γ-hemolytic (Kavitha et al., 2018) and were considered non-haemolytic.

Morphological and biochemical characterization of the bacterial isolates

Studies on the colony morphology, biochemical and molecular analyses were conducted on the isolates, which were selected based on their pectinolytic index. Morphological and biochemical analyses were performed according to the approach described by Shrestha et al. (2021), while molecular identification was conducted in accordance with the methodologies used for bacterial identification by 16S rRNA gene analysis (Janda and Abbott, 2007). The color, shape, and size of each colony were recorded. For each selected isolate, various biochemical assays were carried out including the catalase test, the indole and Voges Proskauer (VP), gas production from glucose and mannitol, Ortho Nitro Phenyl Galactopyranoside (ONPG), arginine dihydrolase (ADH), lysine decarboxylase (LDC), ornithine decarboxylase (ODC), tryptophan deaminase (TDA), hydrogen sulphide (H2S) production, use of citrate, and the gelatinase assay, according to Shrestha et al. (2021).

Molecular characterization of the bacterial isolates

Each bacterial isolate was cultured on pectin agar and incubated at 37°C under aerobic conditions for 24 h. Genomic DNA was rapidly extracted from a bacterial colony by heat shock, as described by Dashti et al. (2009). The extracted DNA was amplified by PCR, and the resulting amplicons were subjected to Sanger sequencing using the chain-termination method described by Sanger et al. (1977). This service included PCR amplification of the 16S rRNA gene, targeting the region encoding the 30S subunit of the bacterial ribosome. The variable regions V1 to V5 were specifically targeted to distinguish among the bacterial populations by aligning the sequences against an international reference database. PCR was performed using genomic DNA from each bacterial isolate and two primer pairs. The first pair, composed of P8 (5′-AGAGTTTTGATCCTTGGCTCAG-3′) and P535 (5′-GTATTACCGCGGCTGCTGGCAC-3′), and the second pair, 338-1040F (5′-CTCCTACGGGAGGCAG-3′) and 338-1040R (5′-GACACGAGCTGACGACA-3′), amplified fragments of approximately 550 bp and 750 bp, respectively. These primers targeted the universally conserved regions of the 16S rRNA gene, and the resulting fragments were used to identify each isolate molecularly. The PCR conditions included 40 cycles of denaturation, hybridization, and elongation, with positive and negative controls. Amplicons were verified by agarose gel electrophoresis and QIAxcel analysis (QIAGEN). The molecular weights of the amplified DNA fragments were calculated using size markers ranging from 50 to 1500 bp (QXDNA size marker, QIAGEN). After purification of the PCR products on a membrane (Macherey-Nagel), the amplicons were quantified by a fluorimetry with SYBR Green, using an Infinite® 200 microplate reader (Tecan, Switzerland). Sequencing of the 16S rRNA gene was carried out using a purified PCR product, with a minimum quantity of approximately 50 ng per reaction, corresponding to a concentration of 10-20 ng/µl. Afterward, the amplicons were sequenced in both directions using the same primers, according to an optimized protocol. The resulting sequencing reactions were purified on a Sephadex-G50 gel (GE Healthcare) and loaded onto an ABI 3730XL capillary sequencer.

Analysis and processing of the bioinformatic data

The raw sequences were optimized using Auto Peak Trace 6 RP software (Nucleics, Australia) and assembled into contigs using a Sequencher V4.9 software (Gene Codes Corporation, USA). To determine the phylogenetic affiliation of the isolates, the resulting 16S rRNA genes were compared by BLASTn against those of other bacterial strains available in the GenBank at NCBI, using the BLASTn1 option (Zhang et al., 2000) and the specialized EZbiocloud2 for bacterial 16S rRNA sequences (Yoon et al., 2017). The resulting sequences were manually checked and corrected using a BioEdit version 7.2 software. Sequence alignment was conducted using a MEGAX software with the Muscle algorithm (Kumar et al., 2018).

Unifactorial study of the components of the pectinase production medium

The B. amyloliquefaciens (PC25p) strain isolated from the decomposing cashew apple was selected for the optimization of pectinase production because it had the highest pectinolytic index (3.659) among the tested isolates and showed no haemolytic activity on blood agar. The effect of different growth factors on pectinase production by the selected bacterium was evaluated using the approach described by Satpathy et al. (2025).

Influence of different carbon sources: Pectinase production was carried out in 100 ml of broth medium in 250 mL Erlenmeyer flasks. The base culture medium contained K2HPO4, KH2PO4, MgSO4, and NaCl to which a different carbon source (pectin, glucose, sucrose, or arabinose) was added individually at different concentrations (5.00, 10.00, and 15.00 g/l), as along with (NH4)2HPO4 as a nitrogen source. The pH of the medium was adjusted and maintained at 6. The broth medium was inoculated with 5% (v/v) of a bacterial suspension standardized to an optical density of 0.6 at 600 nm and then incubated under shaking at 200 rpm at 37 ± 2 °C for 3 d. The activity of the pectinases was then determined, where its methodology will be described later under the title “Determination of pectinase activity”, and the carbon source inducing the highest activity was selected for subsequent studies.

Influence of different nitrogen sources: A protocol similar to the previous one was followed to identify the optimal nitrogen source among the various nitrogen compounds. The tested nitrogen sources included yeast extract, peptone, and (NH4)2HPO4 were added individually at different concentrations (2.00, 3.00, and 5.00 g/l) to a basal medium containing pectin as the sole carbon source and buffered at pH 6. The activity was determined after 3 d of incubation with shaking.

Influence of pH: Bacterial cultures were grown individually in culture media adjusted to different pH levels using appropriate buffers: citrate-phosphate buffer for pH 2, 3, 4, 5, and 6; phosphate buffer for pH 7; and Tris-HCl buffer for pH 8 and 9. The culture medium was formulated using the previously determined optimal carbon and nitrogen sources. The cultures were incubated with shaking for 3 d. After incubation, the broth cultures were centrifuged at 4427 g for 30 min. at 4 °C. The resulting supernatant, corresponding to the enzymatic fraction, was used to evaluate the pectinase activity.

Multifactorial optimization of pectinase production

Statistical optimization of the growth factors influencing pectinase production in the selected B. amyloliquefaciens (PC25p) was performed using a centred composite design to increase the enzyme yield (Govindaraji and Vuppu, 2020). This design is a valuable tool in response surface methodology for improving the enzyme yield. This type of experimental design allows modelling of the linear, quadratic, and interaction effects of the factors under study, while reducing the number of trials required. The factors selected for optimization included pectin, (NH4)2HPO4, temperature, and K2HPO4, which were selected based on preliminary trials. Coded levels were assigned to each factor according to the structure of the centred composite design, including factorial, axial, and central points. Design-Expert 7.0 software was used to design the experimental trials. A total of 30 trials combining different values of the four factors were designed and then carried out experimentally in the laboratory as shown in Table 1. Following the trials, the enzyme activity (expressed in IU/ml) was measured and used as a response variable to assess optimization of pectinase production. The experimental response was fitted to a second-order polynomial model to establish the relationship between the pectinase activity and the independent variables studied. The following equation (Equation 2) generated by the Expert Design software version 7.0.0 describes the regression model used in the factorial planning, including the interaction terms:

In this equation, Y represents the response predicted by the model, n corresponds to the number of factors studied, xi and xj represent the independent variables. The term a0, corresponds to the constant of the model; while ai, aii, and aij denote respectively the coefficients of the linear, quadratic, and interaction effects. The significance and goodness of fit were assessed using analysis of variance (ANOVA). All three-dimensional and contour plots, as well as the statistical analysis were performed using Design-Expert 7.0 software.

Table 1: Coded levels and actual values of the independent variables.

Indépendant variable	Levels
Indépendant variable	-1	0	1
Pectin (g /l)	5	9.62	15
(NH4)2HPO4(g/l)	2	3.65	4
Temperature (°C)	25	31.09	40
K2HPO4(g/l)	2	2.83	4

Determination of pectinase activity

At the end of each culture, the different pectinase production broth media used with B. amyloliquefaciens (PC25p), both during single-factor and multi-factor optimization trials, were centrifuged at 4427 g for 30 min. at 4 °C. The supernatants obtained were collected and used as crude enzyme extracts, containing the extracellular pectinases produced by the selected bacteria isolate. The pectinase activity of each crude extract was then determined using the 3,5-dinitrosalic acid (DNS) colorimetric method described by Miller (1959) with minor modifications. This method was based on quantifying the reducing sugars released during hydrolysis of the pectic substrate by the pectinases. The reaction medium consisted of 100 µl of crude enzyme extract and 900 µl of 1% pectin dissolved in 50 mM citrate-phosphate buffer, pH 5. The mixture was incubated with stirring at 30 °C for 5 min. Enzyme activity was stopped by adding 1000 µl of 3,5- dinitrosalicylic acid (DNS). Afterward, the reaction mixture was heated in a water bath at 100 °C for 5 min. Substrate blanks were also prepared under the same conditions as the enzymatic tests, replacing the enzyme extract with the buffer. The absorbance of the colored complex formed after reaction with DNS was measured at 540 nm using a Biotek Instruments Inc. EpochTM spectrophotometer (Highland Park, Winooski, VT 05404-0998, USA). Enzyme activity was estimated from a calibration curve established using galacturonic acid at concentrations ranging from 0 to 0.05 mM. The resulting linear regression equation

y=75.757 X+0.2254; R2=0.9984 ..... (3)

allowed determination of the amount of galacturonic acid equivalents released during pectin hydrolysis. One unit of pectinase activity is defined as the amount of enzyme required to release 1 µmol of galacturonic acid equivalent per minute under the experimental conditions (Qureshi et al., 2012). Enzyme activity (A) in IU/ml of the crude enzyme extract was calculated following this formula (Equation 4) (Shrestha et al., 2021):

Where; A: pectinase activity; C: Concentration of galacturonic acid determined from the standard curve and expressed in µmol/ml; Vr: Reaction volume in ml; Ve: Volume of crude enzyme extract in ml; D: Dilution factor.

Statistical analyses

One-way ANOVA was performed using XLSTAT software version 2016.02.27444 at a significance level of α = 0.05 (p < 0.05). In cases of significant differences between the studied parameters, the means were ranked using the Newman-Keuls method. RSM was used to determine the optimal interactions among the factors and estimate the optimal conditions for pectinase production with the minimum number of experiments (Kottilingal et al., 2026). RSM determines the effects of the independent variables on the processes, either individually or collectively. A central composite design comprising 30 experiments was applied for the statistical analysis. The experiments were performed in biological/experimental triplicate. For determination of the pectinolytic index, each isolate was subcultured independently onto three separate Petri plates. For the broth cultures, the PC26p isolate was cultured in three independent tubes, maintained under the same experimental conditions. A single measurement was performed for each independent culture and the results were expressed as mean ± standard deviation (±SD). For the analysis of variance, RSM, and the determination of the regression equations and the optimal parameters, Expert Design software version 7.0.0 was used.

Results and Discussion

Screening of the pectinase-producing bacterial isolates

Soumbala and four rotten fruits were analyzed to determine the presence of pectinolytic bacteria. A total of 145 different isolates (Table 2) cultured on reconstituted medium were obtained based on their color, elevation, consistency, transparency, and outline. After purification, 55 of these were selected and subjected to a pectin hydrolytic activity test by immersing their culture plates in I2/KI solution. Of the 55 isolates, pectin degradation that was indicated through the formation of a clear halo was observed in approximately 12 bacterial isolates, representing 21.81%. Bananas and cashew apples yielded the most pectinolytic isolates, with 4 isolates each. Oranges yielded three isolates, while rotten mangoes produced the fewest isolates, only one. In contrast, no pectinolytic isolates were obtained from soumbala (Table 2). The variability observed in the distribution of pectinolytic isolates can be explained by the physicochemical differences in the matrices and ecological conditions. The high number of pectinolytic strains observed in bananas and cashew apples could be attributed to their higher levels of pectins and fermentable sugars. The availability of pectic substrates in these two matrices could thus promote the proliferation of the pectinolytic bacteria

Table 2: Origins and morphological characteristics of the isolated pectinase-producing bacterial isolates.

Samples	Strain code	Isolated strains	Isolates with a halo	Clear zone	Shape	Grouping method	Color	Size
Banana	B1 à B25	25 (17.24)	B6p	+	Stick	Isolated	Whitish	Medium
			B16p	+	Shell	Isolated	Whitish	Medium
			B20p	+	Shell	Isolated	Yellowish	Medium
			B24p	+	Shell	Isolated	Whitish	Small
Mango	M1 à M30	30 (20.68)	M29p	+	Oval	Isolated	Whitish	Large
Orange	O1 à O30	30 (20.68)	O5p	+	Stick	Isolated	Yellowish	Small
			O25p	+	Stick	Chain stitch	Whitish	Large
			O30p	+	Shell	Chain stitch	Whitish	Large
Cashew apple	PC1 à PC30	30 (20.68)	PC10p	+	Oval	Isolated	Yellowish	Large
			PC22p	+	Shell	Chain stitch	Whitish	Medium
			PC25p	+	Shell	Chain stitch	Whitish	Small
			PC26p	+	Stick	Isolated	Whitish	Medium
Soumbala	S1 à S30	30 (20.68)	-	-	-	-	-	-
Total	-	145 (100%)	12 (21.81%)	-	-	-	-	-

Where; B, O, M, PC, and S designate bacterial isolates obtained from bananas, oranges, mangoes, cashew apples, and soumbala, respectively. The isolates are numbered B1 to B25, O1 to O30, M1 to M30, PC1 to PC30, and S1 to S30 according to their origin. The letter p placed after the number indicates isolates exhibiting pectinolytic activity.

(Aguila and Huitron, 1987). Conversely, the low number of isolates observed in mangoes and oranges may be linked to the acidic pH of these matrices and/or the presence of inhibitors that inhibit the bacterial growth (Shaik and Chakraborty, 2022; Kučuk et al., 2024). The complete absence of isolates in soumbala can be explained by the nature of this product, which is produced by alkaline fermentation. The pH and substances produced during fermentation are not favourable to the pectinolytic bacteria (Sheladiya et al., 2022). Several recent studies involving the screening of pectinolytic bacteria have reported substantial numbers of these microbial species in the various environments (Oumer and Abate, 2018; Alqahtani et al., 2022; Owusu et al., 2024). The overall rate of 21.81% that we obtained was higher than that reported previously by Umar et al. (2023). However, higher rates than ours have been reported by Aaisha and Barat (2016); Shrestha et al. (2021) for forest soil and coffee pulp samples, with rates reached of 58.6% and 51.4%, respectively. These differences could be assigned to the nature of the isolation matrix, stage of sample decomposition, environmental conditions, or the composition of the isolation medium. The addition of the KI solution highlighted clear areas of varying diameters around the 12 selected isolates, as shown in Figure 2a. The diameters ranged from 5 mm to 14.67 mm. The most extensive hydrolysis zones were observed around isolates PC25p and PC26p obtained from rotten cashew apples. These values are lower than those reported by Ghazala et al. (2016); Shrestha et al. (2021), who reported hydrolysis zones reaching 21 mm and 17 mm in diameter, respectively, for some isolates. However, lower values than ours were reported by Kamalambigeswari et al. (2018). The smallest pectinolytic zone diameters were observed with isolates from bananas. Although this matrix allowed for the isolation of many isolates, the hydrolysis diameters were small, ranging from 5 mm to 5.33 mm. This clearing zone observed around the colonies can be explained by the bacterial pectinases hydrolysing the pectin, thereby preventing the formation of an iodine complex (Shrestha et al., 2021). Regarding the sizes of the different colonies shown in Figure 2b, they varied from 3.16 to 7.66 mm (reflecting different growth rates between the isolates). The greatest bacterial growth was observed in isolate O30p, followed by isolates PC10p and O25p. The smallest colony diameter (3.16 mm) was recorded in isolate B24p. Determining the pectin degradation index is a commonly used approach to assess the ability of the isolates to hydrolyze pectin. In the present study, the analyzed isolates showed pectinolytic indices varying statistically from 0.33 to 3.65 (Figure 2c), reflecting temarkable variability in their pectinolytic activities. The best pectin degradation indices were obtained with isolates PC25p (3.65), PC26p (2.35), and B20p (1.70). The lowest indices were obtained with isolates B6p (0.33), B16p (0.33), and O30p (0.35). This heterogeneity observed among the isolatess can be attributed to the intrinsic differences among them and the affinity of their pectinases for pectin, which was used as the sole carbon source. Furthermore, the degradation index was widely used in the literature to quantify the enzymatic activity due to its simplicity and ability to provide a rapid estimate of bacterial pectinolytic activity. However, it remains a semi-quantitative estimation (Okonji et al., 2019; Mohammed et al., 2021). Thus, the highest pectinolytic indices observed for isolates PC25p and PC26p revealed that these two isolates exhibited the highest pectinase activity. These results suggest that food matrices such as cashew apples, bananas, oranges, and decomposing mangoes could be used to isolate the pectinase-producing bacteria.

Phenotypic characteristics

Biochemical characterization revealed a diversity of metabolic profiles (Table 2). All isolates were Gram-positive and tested positive for citrate, demonstrating their ability to utilize alternative carbon sources. However, all isolates tested negative for hydrogen sulphide, urease reduction, lysine decarboxylase, and indole (Table 3). All isolates tested positive for glucose utilization. Some isolates also tested positive for rhamnose, sucrose, and arabinose. This explains the isolates’ ability to utilize a wide variety of carbohydrates as a carbon source. The study of the assimilation of various carbon sources by different isolates indicated that the pectinolytic iolates had a high capacity to assimilate mono- and disaccharides, as well as complex sugars. Asmaa et al. (2020) found similar results to ours. Their analysis showed that sucrose and fructose were the most frequently used sugars by the bacterial isolates, followed by glucose. All isolates were unable to assimilate lysine, as confirmed by the negative LDC (lysine decarboxylase) test. However, some isolates were positive for ornithine decarboxylase (ODC). Furthermore, all isolates were positive for tryptophan deaminase (TDA). These results indicated that the current isolates can assimilate these amino acids as a nitrogen source. Similar trends were reported by Kaur et al. (2016), who observed positive results for TDA. Some isolates were positive for Gelatinase, indicating that they were capable of hydrolyzing the gelatin and therefore possessed gelatinase enzyme. Furthermore, all isolates were catalase-positive, indicating their ability to tolerate oxidative stress. However, they all showed negative results for ortho-nitrophenyl-β-galactopyranoside (ONPG) and urea. These results indicated the inability of these isolates to hydrolyze these two compounds, which were substrates for urease and β-galactosidase. β-galactosidase is an inducible enzyme and its synthesis depends on the presence of lactose in the medium and its entry into the bacterial cells. Its absence could be explained by an

Table 3: Biochemical and molecular characteristics of the bacterial isolates exhibiting pectinolytic properties.

Tests conducted	Isolated pectinolytic bacteria
	B6p	B16p	B20p	B24p	M29p	O5p		O25p		O30p	PC10p		PC22p		PC25p		PC26p
Gram	+	+	+	+	+	+		+		+	+		+		+		+
Mobility	-	-	+	-	-	+		-		-	+		-		-		-
ONPG	-	-	-	-	-	-		-		-	-		-		-		-
ADH	-	-	-	-	-	-		-		+	-		+		-		-
LDC	-	-	-	-	-	-		-		-	-		-		-		-
ODC	-	-	+	-	+	-		-		-	-		-		-		+
Citrate	+	+	+	+	+	+		+		+	+		+		+		+
H2S	-	-	-	-	-	-		-		-	-		-		-		-
Ureate	-	-	-	-	-	-		-		-	-		-		-		-
TDA	+	+	+	+	+	+		+		+	+		+		+		+
Indole	-	-	-	-	-	-		-		-	-		-		-		-
V-P	+	+	+	+	+	-		+		-	-		+		+		+
Gelatinase	-	+	-	-	+	-		-		+	+		+		+		-
Glucose	+	+	+	+	+	+		+		+	+		+		+		+
Mannitol	-	+	+	-	+	-		+		-	+		+		+		-
Inositol	-	+	-	-	+	-		-		+	+		+		+		-
Sorbitol	-	+	-	-	+	-		-		+	+		+		+		-
Rhamnose	-	-	-	-	+	-		-		-	-		+		-		-
Sucrose	-	+	-	+	+	-		-		+	+		+		-		-
Melibiose	-	-	-	-	+	-		-		+	-		+		+		-
Amygdaline	-	+	-	-	+	-		-		+	+		+		-		-
Arabinose	-	-	+	-	-	-		+		-	-		-		+		+
Catalase	+	+	+	+	+	+		+		+	+		+		+		+
Identified species
Strain	Identified species						GenBank accession number of deposited sequences		Similarity (%)			Top-hit strain		Number base pairs (pb)		Habitat
B20p	Lactiplantibacillus plantarum						PQ845133		99.91			CP103911.1		1069		Banana
O25p	Acetobacter tropicalis						PQ845142		100.00			KJ469773.1		992		Orange
PC25p	Bacillus amyloliquefaciens						PQ845326		99.90			HQ850702.1		1043		Cashew apple
PC26p	Bacillus subtilis						PQ845369		99.71			KP676117.1		1050		Cashew apple

Where; ONPG= Ortho nitrophenylgalactopyranoside; ADH= arginine dihydrolase; LDC= Lysine decarboxylase; ODC= ornithine decarboxylase; H2S= Hydrogen sulfide; TDA= Tryptophan desaminase; V-P= Vogue-Proskauer; B=Banana; O= Orange; PC= Cashew apple.

inability to utilize lactose due to the lack of transport. Contrary to our results, Umar et al. (2023) reported positive results for B. thuringiensis isolated from soil, with the ONPG and urea tests suggesting genetic diversity among the isolates.

Haemolytic activity

Figure 3a shows the distribution of isolates by haemolytic activity. Among the 12 isolates tested on blood agar, seven isolates namely B6p, B16p, B24p, M29p, O5p, O30p, and PC22p showed a clear halo around the colonies, indicating β-haemolysis, representing 58.33% of the isolates. This reflects the isolate’s ability to lyse the blood cells. Conversely, five isolates specifically B20p, O25p, PC10p, PC25p, and PC26p showed no halo zone; thus, they were considered γ-haemolytic. The absence of a halo around these colonies indicated that they were unable to cause erythrocyte lysis. Haemolytic activity is an essential criterion for assessing the safety of bacteria of interest to the food industry (Nwagu et al., 2020). Haemolysis, whether partial (α) or complete (β), is an indicator of virulence. Indeed, β-haemolysis reveals the presence of cytotoxic phospholipases in the bacteria and indicates that the haemolytic factor reduces the amount of haemoglobin available as an iron source for the host cells (Sorokulova et al., 2008).

Molecular characteristics of the pectinase-producing bacterial isolates

The potential isolates for pectinase production were identified by 16S rRNA gene analysis. The sequencing results were analyzed and compared to probable sequences in NCBI. In the present study, sequencing of the 16S rRNA gene and sequence comparison revealed similarity rates ranging from 99.71% to 100% with the type species in NCBI (Table 4). Isolate B20 exhibited a maximum identity of 99.91% with Lactiplantibacillus plantarum (OZ064365.1). As for isolates O25p, PC25p, and PC26p, they exhibited maximum identity of 100%, 99.90%, and 99.71%, with Acetobacter tropicalis (DQ523494.1), B. amyloliquefaciens (CP054415.1), and B.s subtilis (KF626465.1), respectively (Table 5). Of the molecularly identified isolates, approximately 75% belonged to the genus Bacillus. According to Priest (1977), the pectinolytic activity is widespread in the genus Bacillus. Some studies have also shown that many strains of this genus produce pectinase (Roosdiana et al., 2013; Oumer and Abate, 2018). Furthermore, during the screening, isolates PC25p and PC26p, which secreted the highest amounts of pectinase, were also member of the genus Bacillus. This result is consistent with those of Oumer and Abate (2018), who reported that Bacillus sp. can produce large amounts of extracellular pectinase.

The phylogenetic tree was constructed using the closest sequences from NCBI GenBank with E. coli as the outgroup. The phylogenetic analysis indicated that several isolates exhibited a marked evolutionary proximity to known species. Isolate B20p (PQ845133) was phylogenetically related to Lactiplantibacillus plantarum, O25p (PQ845142) to Acetobacter tropicalis, PC25p (PQ845326) to B. amyloliquefaciens, and PC26p (PQ845369) to B. subtilis. However, species-level identification, particularly for those isolates belonging to the genus Bacillus, should be considered provisional, due to the high similarity of 16S rRNA sequences among the closely related species. These affiliations are presented in Table 3 and illustrated by the phylogenetic tree (Figure 3b). This diversity is consistent with data from the literature, which reports a wide distribution of the pectinolytic microorganisms in the natural environments rich in the organic matter (Haile and Ayele, 2022). These species observed in our isolates differ from those reported by Abdel-Aziz et al. (2019), who identified Klebsiella oxytoca from the soil samples. Similarly, Abdollahzadeh et al. (2020) isolated Enterobacter species from the fields. Furthermore, fruit waste dumps yielded B. tropicus (Thakur et al., 2021). Along the same lines, B. cereus, Streptomyces sp. and Aspergillus niger isolated from fruits, vegetables, and soil samples were reported by Kh et al. (2022). The observed differences between

Table 4: Matrix of the 4-factor central composite design and response function values.

Run	X1	X2	X3	X4	DO	Activity (UI/ml)	Predicted value
1	20	3	32.5	3	0.96	19.3953	11.87
2	10	3	32.5	3	0.7	12.5306	11.74
3	15	2	25	4	0.56	8.8343	11.33
4	5	2	25	2	0.58	9.3623	8.91
5	10	3	32.5	3	0.57	9.0983	11.74
6	0	3	32.5	3	0.33	2.7617	5.89
7	15	4	40	2	0.36	3.5537	4.80
8	10	3	32.5	1	0.75	13.8508	10.64
9	15	2	40	2	0.29	1.7056	4.69
10	10	3	32.5	3	0.72	13.0587	11.74
11	10	5	32.5	3	0.48	6.7221	5.36
12	5	4	25	4	0.46	6.194	6.67
13	10	3	47.5	3	0.23	0.1214	-2.30
14	15	4	25	4	0.79	14.9069	15.40
15	10	3	32.5	5	0.72	13.0587	11.87
16	10	1	32.5	3	0.61	10.1544	7.12
17	10	3	32.5	3	0.79	14.9069	11.74
18	15	4	40	4	0.32	2.4976	6.40
19	15	4	25	2	0.59	9.6264	12.87
20	10	3	32.5	3	0.67	11.7386	11.74
21	15	2	40	4	0.28	1.4415	3.26
22	5	4	25	2	0.41	4.8739	4.00
23	5	2	40	4	0.45	5.93	6.14
24	5	2	40	2	0.49	6.9861	7.44
25	10	3	17.5	3	0.61	10.1544	8.17
26	15	2	25	2	0.55	8.5702	11.84
27	10	3	32.5	3	0.57	9.0983	11.74
28	5	4	40	4	0.44	5.666	3.34
29	5	2	25	4	0.56	8.8343	8.54
30	5	4	40	2	0.25	0.6495	1.61

X1: Pectin (g/l); X2: (NH4)2HPO4) (g/l) (g/l); X3: Temperature (°C); X4: (K2HPO4) (g/l), DO: Optical density

our strains and those reported in the recent studies can be attributed to variations in the ecological niches as well as the physicochemical parameters of the isolation environment. Despite this diversity, these microorganisms share the same ability to degrade pectin. The strain PC25p exhibiting the best pectin degradation index, which was γ-haemolytic, was therefore selected to study the optimal conditions for its pectinase production using a one-factor design and a centred composite design.

Table 5: Analysis of variance (ANOVA) for optimizing the pectinase enzyme production efficiency based on the central composite design source.

	Pectinase activity
Source	Sum of squares	Degree of freedom	Mean square	P > F
Model	473.61	14	33.83	0.0344*
X1-Pectin	53.72	1	53.72	0.0571*
X2- (NH4)2HPO4	4.65	1	4.65	0.5536
X3-Temperature	164.53	1	164.53	0.0026*
X4-K2HPO4	2.28	1	2.28	0.6774
X1 X2	35.29	1	35.29	0.1157
X1 X3	32.22	1	32.22	0.1314
X1 X4	0.017	1	0.017	0.9709
X2 X3	0.85	1	0.85	0.7986
X2 X4	9.22	11	9.22	0.4068
X3 X4	0.85	1	0.85	0.7986
X12	14.02	1	14.02	0.3091
X22	51.87	1	51.87	0.0611
X32	132.78	1	132.78	0.0055*
X42	0.40	1	0.40	0.8610
Residuel	189.81	15	12.65
Lack of fit	163.46	10	16.35	0.1117**
Pure error	26.35	5	5.27
Cor total	663.43	29

Optimization of pectinase production by Bacillus amyloliquefaciens PQ845326 using a single factor design

The effects of different carbon and nitrogen sources and pH on pectinase production were investigated. The results showed a variation in enzyme activity across the different media compositions. As shown in Figure 4a, maximum production was obtained when pectin was used as the sole carbon source, followed by glucose, and then sucrose. Conversely, the lowest activities were obtained with arabinose. These results differed from those recently reported by Sukmawati et al. (2025), who found low activities with pectin and higher activities with sucrose in yeast pectinases. Furthermore, pectinase activity increased with increasing the carbon source concentration. For all the tested four carbon compounds, the highest activities were observed at 15 g/l, which was the maximum concentration evaluated in this study. Also Figure 4b presents the kinetic parameters (Vm and Km) of the pectinase under study with respect to the various substrates, including glucose, sucrose, pectin, and arabinose. Variations were observed depending on the substrate, reflecting the marked enzymatic specificity. Pectin exhibited the highest Vm value (13.31 UI/ml), indicating a higher maximum reaction rate and thus greater catalytic efficiency of the pectinase enzyme on this substrate. Furthermore, its relatively low Km value reflected good enzymatic affinity, confirming that pectin was the enzyme’s preferred substrate. Glucose displayed a high Vm but a very low Km (1.32 mM), suggesting a high apparent affinity, although it was not the primary natural target of the pectinases, reflecting its nonspecific interactions. Sucrose showed intermediate values for Vm (10.46 UI/ml) and Km (25.8 mM), indicating moderate catalytic efficiency and affinity. In contrast, arabinose had the lowest Vm (7.07 UI/ml) along with the highest Km (96 mM), indicating its low catalytic efficiency and very low enzyme affinity for this substrate. Although the activity of pectinase varied depending on the nature of the carbon source used, namely glucose, sucrose, arabinose, and pectin, increasing the concentration of each of these sources in the medium promoted the pectinase activity of the selected strain. The highest activities were observed at the highest tested concentrations. These observations are consistent with those of Mat Jalil et al. (2023), who also reported improved pectinase enzyme activity with increasing the carbon source concentration. However, they differ from those reported by KC et al. (2020), who observed a decrease in pectinase production by Aspergillus niger when the substrate concentration increased. Similarly, Satpathy et al. (2025) showed that a moderate pectin concentration was conducive to pectinase production. On the contrary to the trend observed in the present study, where pectin activity increased up to the highest tested concentration, a previous study reported by Haile and Ayele (2022) indicated that excessive concentrations of pectin can lead to a decrease in pectin activity, probably due to substrate inhibition or catabolite repression. Given that the nitrogen source plays a crucial role in enzymatic activity, various nitrogen compounds were considered to study their influence. The results showed a variation in the enzyme activity depending on the type of nitrogen compound. Among these compounds, (NH4)2HPO4 proved to be the best source with an activity of 13.04 IU/ml (Figure 4c), and was followed by yeast extract. Peptone led to the lowest values. A considerable increase was observed as the concentration of the different compounds increased. The superiority of the observed inorganic nitrogen source suggested a rapid assimilation and an inducing effect on the metabolism, unlike the organic sources, which induced a repressive effect. Contrary to our results, Shet et al. (2022) reported higher activity with peptone, an organic nitrogen source. Furthermore, Satpathy et al. (2025) reported a negative impact of the inorganic nitrogen sources. However, El-Enshasy et al. (2018) reported that (NH4)2HPO4 was the most influential nitrogen source on pectinase production. This difference could be due to the nature of the strain studied.

To determine the optimum pH for pectinase production, the bacterial culture was incubated at different pH levels ranging from 2 to 10. Variations in the pectinase activity were observed at the different tested pH levels. These variations were attributed to changes in the ionization state of the amino acids in the enzyme’s active site, thus affecting its affinity for its substrate. As shown in Figure 4d, the maximum activity (14.29 IU/ml) was obtained at pH 7, followed by pH 6 (12.61 IU/ml). The enzyme retained more than 50% of its activity over a wide pH range from 4 to 8. The optimum pH obtained in this study is consistent with that reported for many other bacterial pectinases. However, a pH of 4.5 was reported by Alqahtani et al. (2022) as optimum for the pectinase of B. siamensis and a pH of 9 was recorded by Abdollahzadeh et al. (2020) on optimum for the pectinase produced by Enterobacter sp. MF84. The observed differences can be assigned to the genetic variability of the tested bacterium.

Optimization of pectinase production using response surface methodology

Based on the results of single-factor optimization design, pectin, (NH4)2HPO4, and pH 7 were selected as optimum components of the culture medium. Data from 30 experiments obtained using a centred composite design were fitted to a second-order polynomial model with Y representing the response (Equation 5).

Where; Y represents the total pectinase activity (UI/ml); X1, X2, X3 and X4 respectively represent the independent variables used for the optimization of the production medium, namely pectin (g/l), (NH4)2HPO4 (g/l), temperature (°C), and K2HPO4 (g/l).

The influence of each factor and its interactions on pectinase production by the bacterium was analyzed using RSM. According to the experimental response, the activity of pectinases produced by B. amyloliquefaciens PQ845326 ranged from 0.1214 to 19.3953 IU/ml (Table 4), demonstrating the influence of the different parameters and an optimization yield of 160 folds. The maximum pectinase activity was observed with pectin (10 g/l), NH4)2HPO4 (3 g/l), a temperature of 32.5°C, and K2HPO4 (3 g/l), corresponding to series number 1. The maximum enzyme activity recorded in this study was remarkably higher than that obtained by Ahmed et al. (2021) in Aspergillus niger, where a maximum production of 0.6173 μmol/ml was recorded. Furthermore, an optimization rate of 9 was reported by Satpathy et al. (2024), which remained lower than that obtained in the present work, thus indicating a better optimization efficiency. However, superior performance was reported by El-Enshasy et al. (2018) for Aspergillus niger pectinase, with activities reaching 101.06 IU/ml in the most optimized medium. ANOVA of the model showed a p-value < 0.05, suggesting that the variables studied significantly influenced the response. Moreover, the linear terms X1 and X3 and the quadratic terms X22 and X23 were highly significant (p < 0.05), indicating a direct effect of the pectin concentration and the incubation temperature on pectin production. The significance of the quadratic terms X22 and X23 highlights a non-linear relationship between these factors and pectinase production, indicating the existence of optimal values for (NH4)2HPO4 concentration and temperature. These values were determined from the response surface model, namely 3 g/l for (NH4)2HPO4 and 32.5 °C. However, the interaction among the different variables was not substantial, indicating the independence between their effects. The considerable effect of pectin suggested that the carbon source played a crucial role in the bacterial pectinase production. These results are consistent with those of El-Enshasy et al. (2018), who reported pectin’s role as an inducer, potentially stimulating the expression of genes encoding for pectinase synthesis. Furthermore, the optimal concentration observed with the nitrogen source could be explained by its limiting effect at low concentrations and its inhibitory effect at high concentrations. On the contrary to the results observed in this study, Umar et al. (2023) did not observe a considerable quadratic effect associated with the nitrogen source. Their study instead showed a remarkable linear effect of this factor on pectinase production. The combined significance of the linear and the quadratic effects of temperature, with a negative quadratic coefficient, was typical to enzymatic systems and corroborates observations reported by Zhang et al. (2025) that temperature exerted a major control over the pectinase enzyme production. At low temperatures, pectinase production was limited by reduced substrate flux across the bacterial membrane. Conversely, above the optimal temperature, enzyme denaturation can occur, leading to reallocation of the energy resources towards growth at the expense of secondary metabolites production such as enzymes. These results are consistent with those reported by Afzia et al. (2024), who also showed that pectinase activity decreased above the optimal temperature.

The coefficient of determination (R²) of the model was 0.7139, indicating that 71.39% of the observed variation in enzyme activity can be assigned to the studied factors. However, the adjusted R² was lower at 0.4469, indicating that the model’s explanatory power decreased after accounting for the number of included terms. This difference between R² and adjusted R² suggested that some model terms may contribute little, or that experimental variability was not fully explained by the model. The predicted R² was 0.7862, suggesting an acceptable predictive power under the experimental conditions studied. Thus, the model can be considered useful for guiding the optimization of pectinase production, but its explanatory power remains only moderate. Furthermore, the goodness-of-fit test was not significant (Table 5). The non-significant lack of fit indicated that no statistically significant difference was observed between the experimental values and those predicted by the model, suggesting that the quadratic model remained acceptable for describing the response in the experimental domain studied. These results are broadly consistent with previous studies conducted on optimizing pectinase production using RSM (Sharif et al., 2023; Kottilingal et al., 2026).

Figure 5 shows 3D response surfaces with enzyme activity (U/ml) on the vertical axis representing the response variable. These three-dimensional response surfaces were generated to assess the combined effect of the two variables and identify the presence and the magnitude of their interactions on the enzyme activity, while the other variables were held constant at their fixed levels. Figure 5a illustrates the evolution of pectinase activity as a function of pectin and (NH4)2HPO4 concentrations. The surface exhibited a parabolic shape with an optimum enzyme activity, which explained the remarkable quadratic effect of the factors X21 and X22. The pectinase activity increased with pectin concentration up to 10 g/l, then decreased. It was also increased with (NH4)2HPO4 concentration up to an optimum of 3 g/l, then decreased. Thus, the most favourable conditions observed on this surface corresponded approximately to 10 g/l pectin and 3 g/l (NH4)2HPO4. However, this apparent optimum range must be attributed to the individual and quadratic effects of the two factors.

Figure 5b shows the combined effect of pectin and temperature on pectinase activity. The response surface shows an upward slope in its initial region, suggesting an increase in activity as both pectin concentration and temperature increase. This trend can be explained by the inductive role of pectin in pectinase production. Similar observations have been reported for Aspergillus niger pectinase, where the addition of citrus pectin to the culture medium remarkably increased the pectinase activity (Mat Jalil et al., 2023). However, this increase was not linear with temperature (X3). Above a certain temperature, the variation became moderate and slightly downward, indicating the presence of an optimum or a quadratic effect. Pectin acts as a factor promoting enzyme production, while temperature modulates this response. The contour lines were elliptical, confirming the presence of an optimum and a substantial interaction between the two independent factors and explaining why the effect of one factor depends on the level of the other. This type of interaction was also reported by Satpathy et al. (2025), where pectin and temperature were among the factors influencing B. siamensis pectinase. The maximum response was obtained with a high pectin concentration within the limits of the experimental range studied, and at a temperature of 32.50 °C. The combined effect of pectin and K2HPO4 is shown in Figure 5c. Unlike the previous figures, it exhibited a nearly flat shape, indicating a small contribution from the quadratic terms X22 and X23, and therefore the absence of a marked optimum pectinase activity as a function of these two factors. The response varied very little when these two factors were modified simultaneously. The broad, slightly constricted contour lines without closed elliptical contours showed a negligible interaction between the two factors. These results suggested that pectin and K2HPO4 exerted a moderate effect on enzyme activity, without a marked combined influence. Figure 5d shows the three-dimensional response surface and its contour lines illustrating the combined effect of (NH4)2HPO4 and temperature on pectinase activity. The curve was convex and slightly upward-sloping as temperature and (NH4)2HPO4 concentration increased, reaching an optimal activity of 15 IU/ml. However, a slight slope was observed, indicating that the activity did not evolve in a strictly linear fashion. Rather, it followed a quadratic trend, suggesting the existence of a favourable range. To maximize the response, an (NH4)2HPO4 concentration of 3 g/l and a temperature of 32.5°C should be selected. The contour lines were concentric, indicating irregular variation in pectinase activity and confirming the existence of a local optimum condition for pectinase production through the combination of the two factors. Furthermore, the oval shape of the contour lines and their slightly more elongated orientation along the X2 axis indicated a weak interaction between the two factors and a more pronounced influence of temperature than (NH4)2HPO4 on the response. This stronger influence of temperature can be explained by its direct impact on the microbial growth and cellular metabolism. In this regard, Kaur and Gupta (2017) showed that temperature is a key factor in pectinase production, while nitrogen sources play a more supportive nutritional role, the effect of which depends on the concentration used and the strain studied. Figure 5e shows the evolution of pectinase activity as a function of the concentrations of (NH4)2HPO4 and K2HPO4, with the other factors held constant. The surface showed a progressive increase in activity up to an optimum, followed by a decrease beyond a certain concentration. This trend primarily reflected the individual and the quadratic effects of the two factors on pectinase production.

The most favourable conditions observed for this response corresponded to a moderate combination of (NH4)2HPO4 and K2HPO4. Despite the apparent joint variation observed on the response surface, the lack of significant interaction in the ANOVA suggested that the effects of (NH4)2HPO4 and K2HPO4 were independent. On the contrary to the results of the present study, El-Enshasy et al. (2018) reported that the joint variation of the mineral nitrogen source and K2HPO4 influenced pectinase production. Figure 5f illustrates the variation of pectin activity as a function of K2HPO4 concentration and temperature, with pectin and (NH4)2HPO4 concentrations held constant at their median values. The response surface showed an increase in enzyme activity up to a maximum, followed by a slight decrease. Increasing the temperature promoted the enzyme activity up to an optimum near 32.50 °C, beyond which the activity decreased slightly. Similarly, a moderate increase in K2HPO4 concentration appeared to improve the activity, whereas higher concentrations tended to be detrimental. The contour lines were nearly parallel, indicating a weak interaction between temperature and K2HPO4 concentration. This observation is consistent with the ANOVA results, which revealed no significant interaction between the factors. Thus, the observed variations in specific surface area appear to be mainly related to the individual and quadratic effects of the variables, rather than to a statistically significant synergy or antagonism between them. Among the variables studied, pectin appeared to be one of the most influential factors on the pectinase activity. This result is consistent with its role as an inducer of pectinase synthesis (Satpathy et al., 2024). However, the beneficial influence of pectin appeared to be limited to a specific concentration range, with a maximum of 10 g/l, as indicated by the curvature of the response surface. Temperature was also an important factor in pectinase production. These results suggested that maximum pectinase activity was achieved at a moderate temperature near 32.5 °C. A lower temperature could limit the bacterial metabolic activity, while a higher temperature may affect the microbial growth, enzyme production, or enzyme stability (Ali et al., 2025). Thus, optimizing pectinase production should consider the simultaneous adjustment of these two factors. In contrast, the other interactions among the factors were not statistically significant. Therefore, the effect of (NH4)2HPO4 and K2HPO4 was primarily attributed to their own or quadratic effects within the experimental range studied, rather than to their interaction effects. (NH4)2HPO4 appeared to promote the enzyme activity at intermediate concentrations, which could be explained by its role as a source of nitrogen and phosphorus, both of which were necessary for microbial metabolism (El-Enshasy et al. 2018; Lu et al., 2025). This observation is consistent with the results of Joshi et al. (2006), who showed that supplementing the medium with 0.2% (NH4)2HPO4 promoted the production of pectin esterase by Aspergillus niger. On the other hand, K2HPO4 exhibited a more moderate effect, indicating that it was not the primary factor governing the response. This trend aligns with the findings of Mohandas et al. (2018), who demonstrated that K2HPO4 had a weaker impact on pectinase production by the B. sonorensis strain. Thus, K2HPO4 appears to have contributed to the enzyme activity, but only secondarily, compared to the other factors such as pectin and temperature. Overall, maximum pectinase activity was observed under conditions combining a relatively high pectin concentration, intermediate concentrations of (NH4)2HPO4 and K2HPO4, and a moderate temperature of approximately 32.5 °C. These results confirmed the importance of optimizing the nutritional and the physical parameters to improve the pectinase production. A recent work has reported that pectinase production by Bacillus strains was highly dependent on medium composition and incubation temperature, with optimal conditions varying with the bacterial strain and the substrate used (Kottilingal et al., 2026). Thus, the optimal conditions for pectinase production by B. velezensis, as determined by this study, were 5.5 g/l pectin, 10 g/l yeast, 1 g/l glucose, pH 7, and 30 °C.

Conclusions and Recommendations

This study allowed the isolation, selection, and characterization of the pectinolytic bacteria from several decaying fruits. Among the isolates obtained, four showed high hydrolytic activity and were identified as: Lactiplantibacillus plantarum, Acetobacter tropicalis, B. amyloliquefaciens, and B. subtilis. Among these isolates, the B. amyloliquefaciens-related strain isolated from a decomposing cashew apple exhibited the highest pectinolytic index. Its γ-haemolytic profile indicated the absence of haemolysis under the tested conditions, supporting its selection for pectinase production optimization trials. Single-factor optimization revealed that pectin and (NH4)2HPO4 were the best carbon and nitrogen sources, respectively, for pectinase production, while pH 7 represented the optimum pH. Furthermore, multifactorial optimization using the centred composite design remarkably improved the production yield, increasing it 160-fold compared to the non-optimized condition. A maximum pectinase activity of 19.3953 IU/ml was obtained at 32.5 °C with 10 g/l of pectin, 3 g/l of (NH4)2HPO4, and 3 g/l of K2HPO4, at pH 7. These obtained results suggested that the selected strain related to Bacillus amyloliquefaciens is a promising candidate for the production of pectinases used for biotechnological applications. In light of these results, further investigations are recommended to more precisely confirm the strain’s taxonomic identification using deeper molecular methods. It is also recommended to further assess the selected strain safety, particularly before any application in the food industry. Furthermore, the enzyme produced should be purified and characterized to determine its biochemical properties, including thermal stability, pH stability, and behaviour in the presence of various ions or chemical agents. Moreover, it would also be relevant to evaluate the effectiveness of this pectinase in the various technological processes, such as clarifying or treating the cashew apple juice.

Acknowledgements

The authors wish to acknowledge Uppsala University for partial support of this research through ISP/IPICS/RABIOTECH, a project of Uppsala University at UJKZ.

Novelty Statement

This study proposes an optimized approach for pectinase production by Bacillus amyloliquefaciens isolated from a locally produced, decomposing food matrix, the cashew apple. It is distinguished by the combined study of four production factors: pectin, (NH4)2HPO4, K2HPO4, and temperature. To our knowledge, few studies have simultaneously evaluated the combined effect of these four factors for optimizing pectinase production by Bacillus sp. The integration of a haemolysis assay further strengthened the assessment of this isolate’s potential for food applications. The results obtained, with a maximum pectinase enzyme activity of 19.39 IU/ml under the optimized conditions, highlight the potential of this strain for pectinase production, particularly in the processing of cashew apple juice.

Author’s Contribution

Tienbnoma Sandrine Ouedraogo, Boureima Kaboré and Iliassou Mogmenga: Conceptualization, methodology, investigation, software, writing original draft.

Mamounata Diao: Conceptualization, data curation, investigation, software, formal analysis, writing review and editing.

Fréderic Anderson Konkobo, Roger Dakuyo and Poussian Raymond Barry: Methodology, writing original draft.

Hemayoro Sama: data curation, formal analysis; writing original draft.

Samson Guenné, Crépin Ibingou Dibala and Kiessoun Konaté: Writing reviewing and editing. Mamoudou Hama Dicko: Funding acquisition, supervision, validation.

The final version of the manuscript was approved by all the authors.

Funding source

This work was partially supported by the Uppsala University, within the framework of the ISP/IPICS/RABIOTECH project no. 172600000, conducted by the Uppsala University in collaboration with the Joseph Ki-Zerbo University.

Ethical approval

This study did not involve human participants, laboratory animals, or sensitive personal data. Therefore, ethical approval was not required.

Generative AI and AI assisted technology statement

The authors declare that no generative AI and AI assisted technology was used in the creation of this manuscript.

Conflict of interests

The authors have declared no conflicts of interest.

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