Optimization of Xanthan Gum Production by Demerara Sugar Using Response Surface Methodology

Abstract

Xanthan gum (XG) production using three Xanthomonas sp. strains (290, 472, and S6) was evaluated by applying a 2³ full factorial central composite design response to study the interactive effects of the fermentation medium component concentrations as parameters to determine the efficiency of the gum production in batch experiments. The experimental variables were the carbon source (demerara sugar or sucrose), potassium phosphate dibasic, and magnesium sulfate. Experimental results showed the K₂HPO₄ concentration as the important parameter for XG production by using Xanthomonas axonopodis pv. manihotis IBSBF 290 and X. campestris pv. campestris IBSBF 472, while for the Xanthomonas sp. S6 strain, the MgSO₄∙7H₂O concentration was the determining factor in XG production using demerara sugar or sucrose as a carbon source. The strains of Xanthomonas 472 and S6, using demerara sugar and higher concentrations of salts, exhibited a higher yield of XG (36 and 32%) than when using sucrose and the same concentration of salts. The experimental outcomes highlighted demerara sugar as a suitable and efficient alternative carbon and micronutrient source for XG production. Despite the bacterial strain influence, the medium composition is crucial for this fermentation process. Therefore, the evaluated salts are important factors for XG production, and the demerara sugar can partially replace this mineral salt requirement as indicated by the face-centered composite experimental design due to its chemical composition. Overall, demerara sugar provides promising properties for XG production.

1. Introduction

Xanthan gum (XG) is a water-soluble microbial exopolysaccharide (EPS) produced by bacteria of the genus Xanthomonas [1]. The monomeric structure of the XG is formed by two units of glucose (cellobiose) bonded in the main chain (the backbone) with a branch formed by two units of mannose and one unit of glucuronic acid (Figure 1) [2,3]. The XG is an EPS, and a biopolymer, chemically characterized by a structural chain with a molar mass ranging between 2 × 10⁶ and 20 × 10⁶ Da [4,5]. Furthermore, its molecular weight is influenced both by bacterium strains and fermentation conditions, producing a variety of gums of industrial interest [6]. These aspects are important since the XG molecular structure and conformational state are closely related to its rheology, stability, and function [7,8]. These properties allow its application as a thickening, dispersant, emulsifier, and viscous aqueous solution at low concentrations (0.05–1%), and are stable over a wide range of pH values and temperatures. Moreover, XG is a dry, tasteless, white-to-cream, and biodegradable powder, and is less expensive compared to synthetic polymers [9].

These properties add industrial value and explain the wide commercial acceptance of this polysaccharide, whereby the xanthan market is constantly expanding to meet its global demand [7,10]. The global XG market grows at a significant rate of 5.6% since 2019, predicting that its market value will reach USD 1.2 billion by 2030 [11]. Its demand increase is due to the growth in processed food consumption, and applications in the agrochemical, cosmetics, driller fluid, and foam stabilizer segments [7]. This commercial demand is a key factor that stimulates studies to increase xanthan production on an industrial scale by sustainable processes to exploit the micro-organism potential [12,13].

Therefore, studies have been carried out analyzing the variables involved in XG production to obtain efficient results, since this productivity can be affected by biotic and abiotic factors [4,7]. Fermentation depends on many parameters and variables, including micronutrients (e.g., potassium, iron, and calcium salts), macronutrients such as carbon and nitrogen sources, oxygen transfers, agitation rate, pH, temperature, and fermentation duration beyond the Xanthomonas strain production efficiency [14,15]. These conditions represent a pivotal point in XG production by affecting the fermentative medium cost, further promoting changes in the gum characteristics, downstream processes, and, consequently, in its productivity [7,16]. In addition, the adjustment of the strains with the conditions applied in the fermentation are important as they directly influence the characteristics, techniques, yields, compositions, and structures [7,10] of the XG produced. The different strains present different productivity levels depending on the factors implemented during the fermentation [17] The Xanthomonas strains used to produce XG that are most reported in the literature are X. campestris pv. campestris 629, X. campestris pv. campestris 1078, X. campestris pv. campestris S6, X. campestris pv. campestris 254, X. sp. 1537, X. campestris pv. campestris 729, X. campestris pv. campestris 607, X. campestris pv. campestris 1167, X. campestris pv. mangiferaeindicae 1230, X. campestris pv. arracia 1198, X. axonopodis pv. manihotis 1182, and X. melonis 68 [18,19].

On an industrial scale, glucose and sucrose are the usual carbon sources for XG production. Considering that the raw material cost is a factor which burdens its production, alternative carbon sources have been evaluated to obtain this polysaccharide [20,21,22]. Regarding Brazil, sucrose as a carbon source is a favorable point for its production since its soil and climate allow an intense development of sugarcane cultivation [23]. Therefore, the binomial XG–sugarcane exhibits a positive effect on profitable income for the agro-industrial market.

In this regard, sugarcane juice is a raw material option for this gum production due to the high content of sucrose, minerals, and vitamins [24]. This broth is used to produce demerara sugar, which, after a brief refinement process, still maintains its rich chemical composition compared to refined sugar [25]. Considering its cost of production in Brazil [26], demerara sugar is an alternative carbon source for XG production due to its nutritional profile and little processing [27]. In addition, as it is an abundant, low-cost, and little-processed product, it can be considered an economical solution and a possible low-cost approach to the production of XG, which can contribute to a sustainable bioeconomy [28].

Nonetheless, several variables affect xanthan production, including technical, biochemical, and microbiological aspects, whose evaluation is crucial for potential industrial implementation [12]. Hence, experimental designs and related statistical methods have been applied systematically to investigate different problems correlating to development and production [15,29,30]. These designs include blocking and factorial experiments to determine the steepest climb ascent path to identify the individual factor effect and approach the neighborhood of the optimal response [17,31,32].

Screening research on alternative or conventional fermentation media for this polymer synthesis has previously been reported [7,33], for example, agricultural residues and biomass with lignocellulosic content [20] (such as tapioca pulp [34], sugarcane bagasse [35], orange peel [36], kitchen waste [37], rice bran [38], chicken feathers [39], coconut shell, cocoa husk [20], potato crop [40], cellar wastewater [41], and corncob [19]); however, these studies found some limitations in the pre-treatments and production yields. Furthermore, there are no studies reporting and describing the use of demerara sugar in XG production. This raw sugar appears to be a promising source since its chemical composition displays adequate nutritional requirements for a fermentative medium, allowing it to be an excellent substrate alternative for the industrial production of XG.

Therefore, the objective of the research was to design and compare XG production processes and thus maximize its yield through a full central factorial composite design (2³). Furthermore, the interactive effects of MgSO₄, K₂HPO₄, and the carbon source (camera sugar or sucrose) as variable parameters of the fermentation medium using three strains of Xanthomonas will be evaluated, thus finding ideal conditions for the biosynthesis of XG, with a greater yield and using an alternative carbon source to obtain the most effective operating conditions, and being able to contribute to a bioeconomy sustainable.

2. Materials and Methods

2.1. Strains

Xanthomonas axonopodis pv. manihotis IBSBF 290, X. campestris pv. campestris IBSBF 472, and Xanthomonas sp. S6 from the Cultures Collection of the Biomaterials Laboratory (Institute of Technology and Research, Aracaju, SE, Brazil) were used as xanthan-producing micro-organisms. Bacteria were grown on MY-agar medium with the following composition (g∙L⁻¹)—yeast extract, 3.0; malt extract, 3.0; peptone, 5.0; glucose, 10.0; and agar, 20.0—and subcultured every three weeks. After incubation (25 °C/48 h), cultures were stored at 4 °C [42]. Inoculum cultures were prepared in MY liquid medium in 125 mL Erlenmeyer flasks containing 14 mL of culture medium at 28 °C, at 100 rpm for 24 h until reaching a log growth of 10¹¹ CFU/mL [43].

2.2. Xanthan Gum Production

The xanthan production was performed in 250 mL Erlenmeyer flasks containing 85 mL of the culture medium under experimental conditions of 28 °C, 96 h, and 180 rpm. The fermentation medium was constituted by the carbon source (demerara sugar or sucrose) ranging from 30 to 70 g∙L⁻¹, supplemented with MgSO₄∙7H₂O (ranging from 0.2 to 1.0 g∙L⁻¹), K₂HPO₄ (ranging from 0.01 to 1.0 g∙L⁻¹), (NH₄)₂SO₄ (2.2 g∙L⁻¹), H₃BO₃ (0.0066 g∙L⁻¹, FeCl₃ (0.0026 g∙L⁻¹), CaCl₂ (0.0022 g∙L⁻¹), and ZnSO₄ (0.0022 g∙L⁻¹). Fermentation started with an inoculum concentration of 15% (v/v), according to medium composition conditions established by experimental design.

2.3. Xanthan Gum Recovery

After fermentation, the samples were subjected to centrifugation (9626× g/5 °C/60 min) to remove cells from the fermented broth. Then, the cell-free supernatant was precipitated with 98% ethanol at a 3:1 (v/v) ratio for biopolymer recovery. After recovery, the precipitated gum was collected and dried at 30 ± 2 °C for 72 h. Its production was expressed as g∙L⁻¹ (grams of XG per liter of fermentation broth) [42].

2.4. Experimental Design and Data Analysis

For each Xanthomonas strain used experimentally, a 2³ full factorial central composite design was used to optimize XG production, with variable concentrations of MgSO₄∙7H₂O (0.2–1 g∙L⁻¹), K₂HPO₄ (0.01–1 g∙L⁻¹), and demerara sugar or sucrose (30–70 g∙L⁻¹).

Table 1. Real and coded values of independent variables according to each 2³ full factorial design, for all strains of Xanthomonas (X. axonopodis pv. manihotis IBSBF 290, X. campestris pv. campestris IBSBF 472, and Xanthomonas sp. S6).

Independent Variable (Concentration on g∙L−1)	Symbol	Range and Levels
		−1	0	+1
Sucrose or demerara sugar	X1	30	50	70
MgSO4∙7H2O	X2	0.2	0.6	1.0
K2HPO4	X3	0.01	0.50	1.00

shows the conditions of the performed experiments. All experiments were conducted in triplicate. For statistical calculation, factor levels (in coded values) were −1, 0, and +1, where 0 corresponded to the central point. The range and levels of the variables investigated in this study are depicted in Table 1. The variables were coded using Equation (1):

xi = (X_i − X₀)/∆X_i

(1)

where xi is the independent variable coded value, X_i is the independent variable real value, X₀ is the independent variable real value on the center point, and ∆X_i is the step change value.

The individual and interactive effects of carbon source (demerara sugar or sucrose), and MgSO₄∙7H₂O and K₂HPO₄ concentrations on the xanthan production (Y) as response variables were studied. Thereby, a second-order polynomial model using a least-squares method was fitted to evaluate the production (Y), resulting in Equation (2):

Y = b₀ + b_1×1 + b_2×2 + b_3×3 + b_11×1² + b_22×2² + b_3×3² + b_12×1×2 + b_13×1×3 + b_23×2×3

(2)

where (Y) is the calculated response function; X₁, X₂, and X₃ represent the coded variables (carbon source, MgSO₄∙7H₂O, and K₂HPO₄, respectively); and b₀, b_i, and b_ij (I, j = 1, 2, 3) are the coefficient estimates.

The software “Statistic” (version 8.0) was applied for regression and graphical analysis of experimental data. The statistical significance of the regression coefficients was determined by the Student t-test, while second-order model equations were determined by the F test, and the proportions of variance explained by the obtained models were given by the multiple coefficients of determination, R².

3. Results and Discussion

The xanthan production by the three selected strains (X. axonopodis pv. manihotis IBSBF 290, X. campestris pv. campestris IBSBF 472, and Xanthomonas sp. S6) was developed using six experimental designs (two for each strain). Thus, the 2³ full factorial central composite design with five replicates at the center point comprised a set of 78 experiments. The design matrix of the variables in coded units is depicted in

Table 2. 2³ full factorial central composite design with five replicates at the center point along with the experimental values of xanthan gum production.

Runs	X1	X2	X3	Production of Xanthan Gum (g∙L−1)
				Strain 290		Strain 472		Strain S6
				Sucrose	Demerara Sugar	Sucrose	Demerara Sugar	Sucrose	Demerara Sugar
1	−1	−1	−1	0.2993	0.3192	0.2857	0.3931	0.1528	0.4533
2	−1	−1	+1	0.5166	0.2465	0.7171	1.2739	0.0200	0.0600
3	−1	+1	+1	0.5992	0.2070	0.8308	1.3075	0.9382	1.3839
4	−1	+1	−1	0.2847	0.2317	0.2585	0.3619	0.5968	0.4644
5	+1	+1	+1	0.2784	0.3924	0.5254	0.3750	0.0712	0.3219
6	+1	−1	+1	0.6840	0.2741	1.0034	0.6109	0.0920	0.3996
7	+1	−1	−1	0.1127	0.2263	0.3713	0.1373	0.0619	0.4166
8	+1	+1	−1	0.1454	0.1811	0.4683	0.8674	0.9255	0.3644
9	0	0	0	0.4926	0.3761	0.3480	0.7854	0.4634	0.7212
10	0	0	0	0.2859	0.4738	0.3436	0.6200	0.5775	0.7488
11	0	0	0	0.4182	0.4273	0.2495	0.4562	0.6876	0.6121
12	0	0	0	0.2750	0.3885	0.2326	0.6213	0.4677	0.6193
13	0	0	0	0.3010	0.4708	0.2875	0.6315	0.7182	0.6533

, as well as the predicted and experimental values of the response factor (xanthan production).

The concentration of demerara or sucrose sugar, and the concentration of MgSO₄∙7H₂O and and K₂HPO₄ are important factors that influence the efficiency of the fermentation process for XG production. The conditions of these experiments and the results obtained are listed in Table 2.

As seen in Table 1, the lowest XG production was achieved with the Xanthomonas S6 strains in experiment 2 (0.0600 g∙L⁻¹), where lower concentrations of demerara sugar and MgSO₄∙7H₂O were used, and higher concentrations of K₂HPO₄. Silva et al. [16] also did not find significant effects in relation to the concentration of MgSO₄∙7H₂O; in addition, the presence of K₂HPO₄ improved the yield of XG production. The improvement in extraction was observed when the MgSO₄∙7H₂O concentration increased up to 1 g∙L⁻¹ in experiment 3, where the highest XG production in this study was obtained for strains 472 and S6 (1.3075 and 1.3839 g∙L⁻¹, respectively). These results agree with Jesus et al. [19], which achieved higher yields of XG production using the S6 strain supplemented with salts and a hemicellulose fraction obtained by the alkaline hydrolysis of corncob. Furthermore, MgSO₄∙7H₂O at lower concentrations 0.2 g∙L⁻¹and 30 g∙L⁻¹ of demerara sugar showed similar results for strain 472. It was verified that the highest productions of XG for strains Xanthomonas 290 and 472, when using sucrose as the main source of carbon, were obtained in the tests containing higher levels of K₂HPO₄ and sucrose (experiment 6, 0.6840 and 1.0034 g∙L⁻¹, respectively). However, for strain 290, the best results were obtained in the conditions applied in the central points (50, 0.6, and 0.50 g∙L⁻¹ of demerara sugar, MgSO₄∙7H₂O, and K₂HPO₄, respectively). In addition, the lowest concentration of XG produced by this strain using demerara sugar was obtained in experiment 8 or more; there were no significant differences between the other experiments. Other authors [44] state in the literature that the most promising culture medium for producing XG is sucrose supplemented with salts. On the other hand, in this study, it is observed that demerara sugar has a higher XG production compared to the experiments with the same conditions using sucrose as a carbon source, making it a very important factor for producing XG.

The quadratic regression models in terms of a coded factor expressed by Equations (3)–(5) represent the XG productions (Y) as a function of the sucrose (X₁), MgSO₄∙7H₂O (X₂), and K₂HPO₄ (X₃) concentrations reached by each of the Xanthomonas strains (290, 472, and S6), respectively.

Y = 0.0105 X₁² − 0.0599 X₁ − 0.0381 X₂ + 0.1545 X₃ − 0.0551 X₁X₂ + 0.0215 X₁X₃ − 0.0426 X₂X₃ + 0.3545

(3)

Y = 0.2653 X₁² + 0.0345 X₁ − 0.0368 X₂ + 0.2116 X₃ − 0.0584 X₁X₂ − 0.0393 X₁X₃ − 0.0543 X₂X₃ + 0.2922

(4)

Y = −0.2256 X₁² − 0.0696 X₁ + 0.2756 X₂ − 0.0769 X₃ − 0.0649 X₁X₂ − 0.1291 X₁X₃ − 0.0513 X₂X₃ + 0.5823

(5)

Regarding the carbon source alteration in fermentation, the quadratic regression models in terms of a coded factor indicating the gum production (Y) as a function of demerara sugar (X₁), MgSO₄∙7H₂O (X₂), and K₂HPO₄ (X₃) concentrations are expressed by Equations (6)–(8), also achieved with each studied strain (290, 472, and S6), respectively.

Y = −0.1675 X₁² + 0.0087 X₁ − 0.0067 X₂ + 0.0202 X₃ + 0.0250 X₁X₂ + 0.0446 X₁X₃ + 0.2064 X₂X₃ + 0.4273

(6)

Y = 0.0430 X₁² − 0.1682 X₁ + 0.0621 X₂ + 0.2260 X₃ + 0.0615 X₁X₂ − 0.2306 X₁X₃ − 0.1126 X₂X₃ + 0.6229

(7)

Y = −0.1879 X₁² − 0.1074 X₁ + 0.1506 X₂ + 0.0583 X₃ − 0.1831 X₁X₂ − 0.0732 X₁X₃ + 0.1609 X₂X₃ + 0.6709

(8)

3.1. Analysis of Variance (ANOVA)

The statistical significance of the main interaction effects of the factors on the dependent variable was assessed by the F test of the analysis of variance (ANOVA).

Table 3. Analysis of variance (ANOVA) for the model regression representing xanthan gum production (Y) using sucrose by X. axonopodis pv. manihotis 290, X. campestris pv. campestris 472, and Xanthomonas sp. S6, respectively.

	SS	dF	MS	F	p-Value
Strain 290
(1) sucrose (L)	0.028716	1	0.028716	1.97056	0.219346
sucrose (Q)	0.000339	1	0.000339	0.02327	0.884727
(2) MgSO4∙7H2O (L)	0.011621	1	0.011621	0.79742	0.412776
(3) K2HPO4 (L)	0.190993	1	0.190993	13.10634	0.015215
1L by 2L	0.024299	1	0.024299	1.66746	0.253072
1L by 3L	0.003720	1	0.003720	0.25524	0.634884
2L by 3L	0.014544	1	0.014544	0.99802	0.363654
Error	0.072863	5	0.014573
Total SS	0.347094	12
Strain 472
(1) sucrose (L)	0.009543	1	0.009543	0.63434	0.461891
sucrose (Q)	0.216603	1	0.216603	14.39851	0.012699
(2) MgSO4∙7H2O (L)	0.010841	1	0.010841	0.72066	0.434676
(3) K2HPO4 (L)	0.358239	1	0.358239	23.81361	0.004553
1L by 2L	0.027320	1	0.027320	1.81604	0.235625
1L by 3L	0.012364	1	0.012364	0.82187	0.406201
2L by 3L	0.023555	1	0.023555	1.56582	0.266171
Error	0.075217	5	0.015043
Total SS	0.733682	12
Strain S6
(1) sucrose (L)	0.038809	1	0.038809	0.67477	0.448775
sucrose (Q)	0.156573	1	0.156573	2.72232	0.159867
(2) MgSO4∙7H2O (L)	0.607753	1	0.607753	10.56694	0.022679
(3) K2HPO4 (L)	0.047370	1	0.047370	0.82362	0.405737
1L by 2L	0.033722	1	0.033722	0.58632	0.478413
1L by 3L	0.133334	1	0.133334	2.31827	0.188357
2L by 3L	0.021033	1	0.021033	0.36570	0.571750
Error	0.287573	5	0.057515
Total SS	1.326168	12

SS: sum of squares; DF: degrees of freedom; MS: mean square.

and

Table 4. Analysis of variance (ANOVA) for the model regression representing xanthan gum production (Y) using demerara sugar by X. axonopodis pv. manihotis 290, X. campestris pv. campestris 472, and Xanthomonas sp. S6, respectively.

	SS	dF	MS	F	p-Value
Strain 290
(1) Demerara sugar (L)	0.000604	1	0.000604	0.30652	0.604
Demerara sugar (Q)	0.086340	1	0.086340	43.83216	0.001
(2) MgSO4∙7H2O (L)	0.000363	1	0.000363	0.18436	0.685
(3) K2HPO4 (L)	0.003268	1	0.003268	1.65925	0.254
1L by 2L	0.005005	1	0.005005	2.54089	0.172
1L by 3L	0.015887	1	0.015887	8.06512	0.036
2L by 3L	0.005592	1	0.005592	2.83865	0.153
Error	0.009849	5	0.001970
Total SS	0.126907	12
Strain 472
(1) Demerara sugar (L)	0.226397	1	0.226397	6.05021	0.057
Demerara sugar (Q)	0.005688	1	0.005688	0.15200	0.713
(2) MgSO4∙7H2O (L)	0.030826	1	0.030826	0.82380	0.406
(3) K2HPO4 (L)	0.408427	1	0.408427	10.91476	0.021
1L by 2L	0.030233	1	0.030233	0.80795	0.410
1L by 3L	0.425595	1	0.425595	11.37356	0.020
2L by 3L	0.101520	1	0.101520	2.71301	0.160
Error	0.187099	5	0.037420
Total SS	1.415786	12
Strain S6
(1) Demerara sugar (L)	0.092257	1	0.092257	1.930789	0.223
Demerara sugar (Q)	0.108667	1	0.108667	2.274231	0.192
(2) MgSO4∙7H2O (L)	0.181533	1	0.181533	3.799212	0.109
(3) K2HPO4 (L)	0.027226	1	0.027226	0.569801	0.484
1L by 2L	0.268242	1	0.268242	5.613882	0.064
1L by 3L	0.042881	1	0.042881	0.897424	0.387
2L by 3L	0.207143	1	0.207143	4.335177	0.092
Error	0.238909	5	0.047782
Total SS	1.166857	12

SS: sum of squares; DF: degrees of freedom; MS: mean square.

depict the experiments with sucrose and demerara sugar, respectively, showing significant results at a 95% confidence level.

The Xanthomonas growth time can vary according to the fermentation conditions. Xanthan production is closely related to the carbon source consumption up to its maximum concentration. Afterward, the enzymatic polysaccharide hydrolysis starts to restore the carbon source in the culture medium as an attempt to maintain bacterial viability [45]. Therefore, the carbon source is a critical factor in any bioproduct formation, including XG [46]. Thereby, it is noteworthy to evaluate each carbon source interaction with respect to the other variables in the medium composition independently, to establish the carbon-source–micronutrient interactions, such as MgSO₄∙7H₂O and K₂HPO₄ [14].

The statistical study using an ANOVA-linked Fisher (F) test was applied to determine the significant variables, whose significance degree was ranked based on the F-ratio value. In fact, the greater the magnitude of the F value and the lower the “Prob < F” value, the more significantly displayed the corresponding model and individual coefficient. The p-value serves as a tool to check the significance of each of the coefficients, also indicating the interaction strength between the parameters. Low p-values (<0.05) denote a greater correlation of the significance between corresponding coefficients [32,47].

Hence, in the study using sucrose as a carbon source (Table 3), a significant linear effect (p < 0.05) of K₂HPO₄ was observed with strain 290 (p = 0.015) and strain 472 (p = 0.004), and of MgSO₄∙7H₂O with strain S6 (p = 0.023). Silva et al. [16] and Niknezhad et al. [47] also reported potassium as a significant factor in fermentations using cheese whey, K₂HPO₄, and MgSO₄ for xanthan production. Notwithstanding, Umashankar et al. [48] observed the nutrient influence on X. campestris growth under a high phosphate concentration, which inhibited gum production. Nonetheless, the sucrose quadratic term coefficients (p = 0.013) were significant for strain 472, indicating that both the concentration and carbon source type are important for the cells during the fermentation process for xanthan production. This result is consistent with that reported by Demirci et al. [21], verifying the significant glucose effect on polymer production.

The demerara sugar concentration evaluation depicted in Table 4 shows the ANOVA statistical analysis concerning the influence of this sugar concentration, K₂HPO₄, and MgSO₄∙7H₂O on xanthan production. The effects of MgSO₄∙7H₂O associated with the demerara sugar rate displayed no statistical significance for the strains tested. However, the significant effect (p < 0.05) on the response for strain 290 was the demerara sugar concentration quadratic term (p = 0.001), while the linear term of the K₂HPO₄ concentration (p = 0.021) was significant for strain 472. Furthermore, the interaction between demerara sugar and the K₂HPO₄ concentration exhibited a significant effect (p = 0.036 and p = 0.020) for the 290 and 472 strains, respectively.

The measures of the models’ goodness-of-fit were confirmed by the determination coefficients (R²), with R² values of 0.79008, 0.89748, and 0.78316 by the 290, 472, and S6 strains, respectively, for the sucrose experiments, while for the demerara sugar experiments, the R² values for the 290, 472, and S6 strains were 0.92239, 0.86785, and 0.79525, respectively. The R² value provides a variability measure in the observed response values, which can be explained by the experimental parameters and their interactions. R² values close to 1 indicate the best correlation between the experimental and predicted values and the better predictive response model [32]. Therefore, the R² predicted values > 0.78 for all strains pointed to a reasonable agreement between the experimental and predicted values for xanthan production.

3.2. Response Surface Methodology (RSM)

The response surface methodology (RSM) is often applied in order to provide effective tools for optimization since it involves many critical factors for determining high accuracy [32,49]. Figure 2 and Figure 3 represent the response surfaces of the regression study using sucrose.

Figure 2a,b show the response surface plots for xanthan production at different concentrations of sucrose and K₂HPO₄ for the Xanthomonas 290 and 472 strains, respectively. Likewise, Figure 2 depicts the relationship between the MgSO₄∙7H₂O concentrations with sucrose for the S6 strain. According to the response surface plots, the xanthan production yield rises with the increased K₂HPO₄ concentration relative to the 290 and 472 strains, while an increased MgSO₄∙7H₂O concentration promoted a higher yield by the S6 strain. In both cases, the independent variables MgSO₄∙7H₂O and K₂HPO₄ significantly affected xanthan production in each Xanthomonas strain.

The results show the importance of screening the Xanthomonas strains in association with a fermentation variable study since the culture medium composition can promote different behaviors on the strains used for production. Therefore, the response surface methodology aimed to detect the experimental parameters responsible for signals superior to those caused by noise. The phosphate addition to the medium can increase xanthan gum production by acting as a buffering agent, minimizing pH fluctuations [50].

Concerning Figure 4a,b, the response surface displays the relationship between the K₂HPO₄ concentrations and demerara sugar for the Xanthomonas 290 and 472 strains, respectively. High K₂HPO₄ concentrations provided a significant xanthan production increase, previously observed in fermentations using sucrose. Moreover, it was observed that the Xanthomonas strain 290 grown in demerara sugar, even with a low K₂HPO₄ content, kept gum production close to its highest level when grown in demerara sugar at the central point level. The data suggest that the demerara sugar and K₂HPO₄ use provided a high potassium content, affecting gum production. The experiment performed with maximum values of demerara sugar and MgSO₄∙7H₂O and a minimum value of K₂HPO₄ displayed the third-largest gum production by the Xanthomonas 472 strain. Therefore, demerara sugar could supply the potassium amount required for gum production.

Overall, these results are supported by Faria et al. [51] on the influence of the initial sucrose concentration on xanthan production, and by García-Ochoa et al. [4] on the effects of nitrogen, phosphorus, and magnesium on bacterial growth and polymer production. Micronutrients may be required for pyruvilation, although the literature reports several results regarding its effect on the pyruvilation degree in the xanthan molecular structure [14]. Pyruvate influences the polymer–polymer interaction increase related to the affinity with the neighboring xanthan molecules, promoting more viscous aqueous solutions [52].

The significant effects of K₂HPO₄ were similar to those described by Silva et al. [16] and Mesomo et al. [53] These authors evaluated the combined effects of K₂HPO₄ and MgSO₄∙7H₂O with the cheese whey addition, observing the higher xanthan production with the maximum K₂HPO₄ supplementation by X. campestris pv. mangiferaeindicae 1230 and X. campestris pv. manihotis 1182. Kalogiannis et al. [50] also reported the maximal production using pretreated beet molasses (carbon source), supplemented with K₂HPO₄, yeast extract, and Triton 80. Moreover, potassium can significantly increase the xanthan viscosity [54] which, in the form of K₂HPO₄ and KH₂PO₄, are significant medium components, acting as buffering agents as well as nutrients for Xanthomonas growth [55].

Despite evidence showing the influence of the microbial strain, time, and fermentation medium composition on XG production, no alternative medium has even replaced the use of sucrose or glucose with a significant effect on the polysaccharide quality and productivity. Nevertheless, the results with demerara sugar showed its efficiency as a carbon source in gum production due to its nutritional richness, which can partially replace the evaluated salt addition. Even so, further studies with demerara sugar or other potential substrates are required, whose nutrient content can provide operational and economic advantages for a xanthan production process since the analyzed variables are significant for the polymer-producing strains.

4. Conclusions

This study evaluated the possibility of supplementing the fermentation medium with mineral salts, using demerara sugar or sucrose as substrates, in XG production. Thereby, the sucrose or demerara sugar, K₂HPO₄, and MgSO₄∙7H₂O concentration effects on its production were explored by an experimental design and a response surface analysis. The proposed model studies pointed out a reasonable experimental agreement for xanthan production, indicating specific nutritional requirements for each Xanthomonas strain. The three selected strains displayed a different influence from the fermented conditions for xanthan production. Statistical significance values suggested that the sugar concentration and K₂HPO₄ played an important role for this production by the Xanthomonas 472 strain, using sucrose or demerara sugar as a carbon source. Regarding the S6 strain, MgSO₄∙7H₂O played a significant role in gum synthesis with sucrose but not with demerara as a carbon source. With strain 290, the demerara sugar concentration increases the XG but with sucrose as the carbon source, the production is higher with K₂HPO₄. The evaluated salts are important factors for XG production, and the demerara sugar can partially replace this mineral salt requirement. Economically, the experimental data show the relevance of demerara sugar as an efficient and low-cost alternative source of carbon in the production of XG compared to a carbon source used industrially. These results contribute to the production of XG through sustainable biotechnology, efficient in the context of the circular bioeconomy.