Parametric Optimization of Lactic Acid Production by Immobilized Lactobacillus casei Using Box-Behnken Design

Period. Polytech. Chem. Eng. A. Thakur, P. S. Panesar, M. S. Saini Abstract Technological optimization of process parameters posses one of the open challenge for fermentative lactic acid (LA) production. Hence optimization of process parameters viz. sugar concentration, pH, biomass, incubation temperature and incubation time for maximizing fermentative lactic acid production from molasses sugar and corn steep liquor as a low cost carbon and nitrogen source, respectively by immobilized Lactobacillus casei MTCC 1423 cells has been carried out using Box Behnken Design (BBD). By applying multiple regressions on experimental data, quadratic models have been realized, explaining role of each variable and their quadratic interaction on LA production, LA productivity and yield coefficient. Analysis of variance has demonstrated that models are significant. The maximum LA production (132 g/(L fermentor volume) ), LA productivity of 2.36 g/(L×h) and yield coefficient of 0.936 g/(g substrate) have been estimated by the quadratic regression model for optimum process parameters values of sugar concentration (194 g/L), pH (6.85), biomass (310 mg, CDW), incubation temperature (37°C) and incubation time (57 h). The optimization validated experiments had resulted in LA production of 130±2.1 g/(L fermentor volume) ; LA productivity of 2.28±0.037 g/(L×h) and yield coefficient of 0.921±0.003 g/(g substrate) and which are substantially higher than those obtained with free cells of Lb. casei MTCC 1423 (2%, v/v inoculums size) at obtained optimized process parameters values. Thus resulted quadratic models provided an opportunity for scaling up the lactic acid production process and demonstrated the economic potential of using agro industrial waste molasses sugar for lactic acid production by Lb. casei MTCC 1423.


Introduction
Lactic acid (LA) is GRAS (generally recognized as safe) grade one, being declared safe by the United States Food and Drug Administration.Lactic acid, one of the functional, valuable and versatile compounds has been utilized globally for synthesizing various compounds in food, textile, pharmaceutical, cosmetics and chemical industries [1].In recent time, its market demand has been increased manifold since naturally producing lactic acid acts as feedstock for biocompatible and bioabsorbable Poly lactic acid (PLA) which has a widespread variety of applications and is an effective alternative to petrochemical plastics hence ultimately leading to a considerable diminution in carbon dioxide net emission [2,3].
Lactic acid can be produced on industrial scale by fermentation or chemical synthesis method.Fermentative lactic acid production, a green method has attained a remarkable place worldwide attributed to the escalating global energy and environmental issues.In recent years, microbial conversion of renewable raw materials into valuable compounds has become an important objective in industrial biotechnology.Moreover it also offers an advantage in terms of low production temperature, low energy consumption, etc. [2].
Fermentation process using immobilized cells has recently gained a considerable scientific and industrial interest.Cell immobilization is an approach to bring improvements in the fermentation performance because immobilized cells exhibit numerous advantages over free (suspended) cell, like accomplishment of high cell densities in the bioreactors, higher productivities due to cell growth within the immobilizates, feasibility of continuous processing at high dilution rate, ease in product separation, preservation of biosynthetic activity of the cells for longer duration etc [4][5][6][7][8][9].The immobilization also gives an additive advantage of easier removal of biocatalyst from the fermentation media subsequently facilitating their reusability in repeated batch fermentation cycles [10].The relative weakness of adsorptive binding forces poses a major disadvantage [11].However, proper selection of immobilization techniques and supporting materials can minimize the disadvantages of immobilization [12].The price of biological lactic acid is considerably higher in comparison to chemical lactic acid, mainly because of the high cost of the carbohydrate sources [13].The production cost of microbial lactic acid can be significantly reduced by using the cheap raw materials like starchy, cellulosic materials, algal biomass and waste or side stream feed stocks [14,10].But the starch-based substrates compete with food resources as a large part of the earth's population is malnourished, due to poverty and inadequate food production [15].A complicated pretreatment hydrolysis processing is required for cellulosic biomass-derived substrates.The significant reduction in the manufacturing cost of lactic acid must be accomplished by seeking the possible use a waste/by product such as sugarcane molasses containing ''simple sugars'' which is considered to be preferred potential renewable raw material for microbial lactic acid production by sucrose positive biocatalysts [16].
The primary microbial sources of lactic acid are lactic acid bacteria (LAB) and filamentous fungi, although the latter exhibits relatively lower productivity.Homofermentative LAB is an imperative aspect in developing an economical and efficient bioprocess for lactic acid production.Homofermentative LAB genera include Lactobacillus, Lactococcus, Enterococcus, Streptococcus and Pediococcus species [14,17].Lactobacillus is the main gernus which can be employed for lactic acid production as free or immobilized cells [9].The Lactobacillus related strains utilized by various researchers for lactic acid production with immobilized cells are Lactobacillus delbrueckii, Lactobacillus casei, Lactobacillus helveticus, Lactobacillus rhamnosus etc. [9,10,20,40,41].
In the field of fermentation technology, the cell growth and metabolic products accumulation are strongly dependent on the various parameters like temperature, pH, time, carbon sources & its compositions etc. [18].Rational experimental design and optimization of fermentation is required for finding the major factor influencing the fermentation.In comparison to single parameter optimization, the optimization by response surface methodology offers more advantages like saving time, space and raw material [19].
Keeping in view the above, the present study has been carried out to optimize the process parameters for maximizing the production, productivity and yield coefficient during the bioconversion of sugarcane molasses into lactic acid by immobilized Lactobacillus (Lb.) casei MTCC 1423 cells using response surface methodology (Box-Behnken Design).

Materials
Sugarcane molasses (agro industrial waste) obtained from Bhagwanpura Sugar Mill Limited Dhuri was used as substrate, Punjab, India.Corn steep liquor (CSL), waste water as a nitrogen source was procured from Sukhjeet Industries, Phagwara, Punjab, India.Sugarcane molasses and corn steep liquor were stored at 4°C and no pretreatment was applied.Sodium alginate (alginic acid sodium salt from brown algae with medium viscosity) was obtained from Sigma-Aldrich.All other chemicals (analytical grade or HPLC grade for HPLC analysis) have been procured from HiMedia Laboratories Pvt.Limited, Mumbai (India), Merk India Ltd., Mumbai (India), Fluka Goldie Chemika-Biochemica, Mumbai (India).

Fermentation media
The carbon source, molasses was diluted with deionized H 2 O to achieve the required sugar concentration for fermentation.Fermentation media was composed of molasses sugar concentration of (125-225 g/L), MnSO 4 (20 mg/L), CaCO 3 (25%, w/w with respect to sugar content) and CSL (2.5%, v/v).The pH was adjusted with 4.0 N NaOH and conc.H 2 SO 4 .Erlenmeyer flasks containing 50 mL fermentation medium were sterilized (121°C, 15 psi for 20 min) before subjecting to fermentation.

Immobilization of Lb. casei MTCC 1423 cells and bead coating
The cultivation of Lb. casei MTCC 1423 cells for immobilization was carried out in MRS broth for 24 h at 37°C temperature.Cells were harvested aseptically by centrifuging (6700 rpm x 12 min at 4°C) using temperature controlled centrifuge (Eppendorf) and washed twice with phosphate buffer (0.1 M, pH 7.0) and were used for accomplishing the immobilization in sodium alginate (2%, w/v) matrix.The cell dry weight (CDW) equivalent to cell wet weight (CWW) of Lb. casei MTCC 1423 utilized for immobilization in sodium alginate matrix had been determined from the calibration curve.The known amount of harvested cells were placed in an oven at 65°C for 72 h and thereafter the cell dry weights were measured to obtain the calibration curve.
The Lb. casei MTCC 1423 immobilization was accomplished in accordance to the procedure adopted by Idris et al. [20] and Kaleem et al. [21].The known amount (CWW) (equivalent to 200, 300 and 400 mg, CDW) of harvested cells of Lb. casei MTCC 1423 were aseptically transferred into sterilized (121°C for 20 min) sodium alginate (2%, w/v) solution (7.5 mL) and mixed well.Biocatalysts entrapped in beads of 2.5±0.2mm size were thus obtained by the drop wise addition of cells and sodium alginate solution mixture aseptically with the help of sterilized syringe, into a 0.2 [M] sterile solution of calcium chloride.After 30 min beads were sieved out and followed by washing with 0.85% (w/v) sodium chloride solution.Wet weight of beads was determined to account for any material and cell content loss during immobilization process and no appreciable losses were noticed.
For achieving reduction in the cell leakage, alginate beads thus obtained were double layer coated with chitosan and sequentially with alginate.The coating of bead containing Lb. casei cells was accomplished by following the method as described by Klinkenberg et al. [22] at ambient temperature.The sodium alginate beads containing Lb. casei MTCC 1423 were aseptically immersed in sterilized chitosan (0.4%, w/v) solution (pH=5.6) for 45 min.The chitosan coated beads after sieving were immersed and stirred for 15 min in sterilized solution of sodium chloride (0.2 M) and calcium chloride (0.05 M).The beads were then transferred into sterilized sodium alginate solution (0.5%, w/v) and stirred for 10 min before sieving.The beads were again put in the solution of sodium chloride (0.2 M) and calcium chloride (0.05 M) for 15 min after washing with sterilized demineralized water.The double layered coated biocatalysts were stored in peptone solution (0.75%, w/v) at 4°C for further utilization in fermentation broth (within 30 min).The known amount of beads (on the wet basis) containing equivalent amount of Lb. casei MTCC 1423 cells (i.e.200, 300 and 400 mg, CDW) were transferred to the Erlenmeyer flasks containing sterilized 50 mL fermentation medium.

Analytical methods
The lactic acid concentration in fermentation samples was analyzed by the HPLC method [23] using Shimadzu LC 2010 CHT (Shimadzu Corporation, Kyoto, Japan) equipped with low pressure quaternary gradient pump, dual wavelength UV-Visible detector and column oven.The chromatographic data were recorded and processed using LC solution software based on the peak area of the identified lactic acid.The column temperature was maintained constant at 25°C.Phosphate buffer (10 mM, pH 3.0) and acetonitrile at 95:5 % (v/v) ratio as mobile phase were utilized for isocratic elution at the flow rate maintained at 1 mL/min and in each run, the injection volume was 50 μL.The effluent was monitored at a wavelength of 210 nm for detection and quantification of lactic acid.The samples of the fermentation broth were prepared by centrifuging at 6700 rpm for 15 min and were further diluted appropriately using the mobile phase and vacuum filtered through 0.22 μm filter membrane.The phenol sulfuric acid method [24] was followed for the determination of total sugar concentration.Each sample was analyzed in duplicate and the lactic acid as well as sugar concentrations were quantified from the respective calibration curve generated using standard solutions.

Response surface methodology
Response surface methodology has been widely and successfully applied for evaluating the effect of process variables and optimization of various bioprocesses.The optimization of lactic acid production by immobilized Lb. casei MTCC 1423 cells, lactic acid productivity and yield coefficient had been carried out to investigate the positive effect of the nutrients and negative effect of the toxic substances in molasses and other process variables using Box-Behnken design (BBD).

Statistical analysis and optimization
The statistical software Design-Expert 7.16 (Statease Inc., Minneapolis, USA) was used for experimental design, regression analysis of the experimental data, response surface graphs preparation and carrying out the numerical optimization.A suitable approximation for the true functional relationship between independent variables and responses had been obtained in the form of mathematical model by making assumption that the independent variables are continuous and controllable by experiments with negligible errors.The process behavior can be explained by a quadratic equation of the form: Where Y represents the predicted responses i.e LA production, LA productivity and yield coefficient.Whereas b 0 , b i , b ii , b ij and x i are offset term; linear effect; squared effect; interaction effect and ith independent variable, respectively [25] and ε represents random error or allows for discrepancies or uncertainties between predicted and measured values.
The analysis of variance (ANOVA) for the response was utilized for the estimation of significance of the terms in the model through the Fisher's test for P (probability) <5%.The fitting quality of the hence generated second-order polynomial model equation was checked with the help of the coefficient of determination (R 2 ).The interactive relationship between the variables and the responses had been illustrated through the three-dimensional surface plot as an outcome of the 2 nd order polynomial model equation.The maximum LA production, LA productivity as well as yield coefficient along with corresponding optimal level of each independent variable (within the experimental range) were obtained by numerical optimization method [26].

Experimental design
The software of Design-Expert (version 7.16, Stat-Ease, Inc.) has been employed to program a Box-Behnken design (BBD) with five factors at three coded levels (Table 1).Experiments were carried out according to the design generated by the software using the production medium (50 mL) constituted of molasses sugar (125, 175 and 225 g/L), CSL (2.5%, v/v); CaCO 3 (25%, w/w w. r. t. sugar content) and MnSO 4 (20 mg/L).A total of 46 experimental run results obtained for the responses are presented in the Table 2 as average value ± standard deviation.Average value of LA produced, LA productivity and yield coefficient for each run were considered for further analysis.
(1) Experimental combinations obtained through Box-Behnken design had been performed in triplicate for further analysis, obtaining 3D graphs as well as for numerical optimization to obtain the optimized value of the five individual parameters and responses.The plan of experimental design in un-coded form of process variables along with results have been shown in Table 2.

Lactic acid production 3.1.1 Regression model
The regression equation was developed as a result of application the multiple regressions with backward elimination regression (alpha to exit = 0.100) on experimental data.The quadratic model (coded forms) explaining the role of each variable and their quadratic interaction on the lactic acid production, C LA (g/L) thus obtained is as follows: The quadratic model (Eq.( 2)) has fourteen terms comprised of five each of linear and quadratic terms alongwith four twofactorial interactions.The statistical significance of Eq. ( 2) was checked by analysis of variance (ANOVA).The significance of each of the coefficients was checked through probability, P (p > f ) values (Table 3).The terms having p > f values <0.05 are identified as significant terms while the terms having P-value >0.1 indicates that the model term is insignificant [27].Smaller the values of |P|, more significant is the correlation with the corresponding coefficient [28].It can be concluded from Table 3 that all the parameters play a significant role in lactic acid production from molasses by immobilized Lb. casei MTCC 1423 due to the significant first-order main and the square effect of all factors.Significant interactions between and highly significant model has also been demonstrated by the ANOVA (Table 3).
The satisfactory (>0.98) coefficient of determination values (R 2 ) for the LA production (P≤ 0.05) is an indicative of a good agreement between experimental results and predicted values and suggested that only 1.18% of the variation was not explained by the model [27].The significant model best fit has been certified by the "Lack of Fit F-value" of 4.63 for lactic acid production which implies that it is not significant relative to the pure error [25].The sufficiently close in values of adjusted R 2 and predicted R 2 implies that the model values are in good agreement.

Interactive effect of variables on lactic acid production
The response surface graphs (Fig. 1-4) were obtained using the Design-Expert 7.16 software to understand the individual as well as interactive effect of variables on the lactic acid production and for obtaining their optimum levels.
The interactive effect of biomass loading and substrate concentration on the lactic acid production is illustrated in Fig. 1.Regardless of substrate concentration, an increase in the lactic acid production has been registered with the enhancement in the concentration of entrapped Lb. casei MTCC 1423 cells (≤ 300 mg, CDW) and highest biomass loading (≈ 400 mg) has caused a decrease in production.However, at the low substrate concentration, lactic acid production was comparatively lower.This may have been resulted in due to limited availability of substrate for microbial growth and hence it secretes less lactic acid.Moreover at small initial cell density, distinct and large micro colonies formed due to cell growth and their size got increased with decreasing initial cell density [29].At the lower biomass loading, the lactic acid production has been observed to be increased with an increase in the initial sugar concentration and it tends to decrease at higher sugar concentration (225 g/L).The lactic acid production was observed to decrease at the higher cell concentrations and higher sugar concentration.This could be attributed to the depletion of substrate by the high population of microbes for maintenance and growth, repressive effect of molasses as a result of increased viscosity and sugar inhibition [19].
Lactic acid production has been noticed to be enhanced, depending on the sugar concentration and the incubation temperature (Fig. 2).An increase in the LA production with the increase in the incubation temperature and sugar concentration was observed which may be due to the influence of temperature on substrate and product diffusion through the beads [9].A gradual decrease in lactic acid production was obtained towards higher incubation temperature while the enhanced production and significant interactive effect was found at around 37°C.As the incubation temperature was increased towards 42°C, there was a slight decreament in the lactic acid production.
(2) Since Lb. casei being a thermophilic or mesophilic could produce lactic acid within a range of 30 and 44°C and production tends to be got reduced at higher or lower temperature than optimum due to decrement in catalytic activities of the cells [26][27][28][29][30]31].The lactic acid production may have decreased at higher sugar concentration due to the increase in the concentration of metal ions such as calcium, sodium, iron, magnesium, copper etc. and suspended colloids which might be present in molasses causing toxic or inhibitory effect on the cells [25].
Lactic acid production has been observed to be varied extensively and simultaneously by incubation time and sugar concentration (Fig. 3).The increase in lactic acid production was more significant in the early phase of incubation time (≤54 h) for all sugar concentration.At higher sugar concentration the lactic acid production has been noticed to be increased continuously with the incubation time and remained nonetheless significant at 60 h of incubation time because increasing the level of fermentable sugars not only increases availability of sugars to the microbes in the fermentation media but also some other nutritional substances that are suitable for production [25].At low sugar concentration, the lactic acid production did not increase with prolonged incubation time due to early depletion of substrate.
A sharper initial increase was illustrated during the first period (48 h) of fermentation at the low incubation temperature (32-37°C) range (Fig. 4).The increase was followed by a slow reduction that might be because of decrease in the cells' catalytic activity at higher incubation temperature [9].At higher incubation temperature, the lactic acid production tends to stabilized after a shorter incubation time.Higher production of lactic acid by immobilized Lb. casei MTCC 1423 could be obtained in medium with high incubation time at a moderate incubation temperature.Lower production was obtained with lower incubation time and temperature.

Lactic acid productivity 3.2.1 Regression model
The regression equation for LA productivity, P LA (g/(L×h)) was obtained after backward elimination regression (alpha to exit = 0.100) on experimental data.The quadratic model (in coded forms) thus obtained is as follows: The quadratic model (Eq.( 3)) has thirteen terms which comprises of five each linear and quadratic terms along with three two-factorial interactions.The statistical significance of Eq. ( 3) was checked by analysis of variance (ANOVA).
Significant interactions between C s & T f , C s & τ f and T f & τ f have been indicated by the analysis of variance.ANOVA (Table 4) has also demonstrated that the model is highly significant.

Interactive effect of variables on lactic acid productivity
It is evident from the Table 4 that for LA productivity, the interaction among incubation temperature and sugar concentration is significant.Fig. 5 has displayed that with the enhancement in sugar concentration (up to approx.210 g/L) irrespective of incubation temperature, the LA productivity has risen to maximum.This indicates a consistent and promising efficiency of Lb. casei MTCC 1423 cells even at concentrated form of substrate since the byproducts/wastes from sugar manufacturing process are rich in mixed carbohydrates which provides an additive advantage in enhancing LA productivity and process economy [32].
The LA productivity can also be seen achieving maxima on increasing the incubation temperature up to 40°C giving an impression that the Lb.casei MTCC 1423 cells is capable of balancing the first and last biochemical reaction up to this temperature during the conversion of molasses sugar into lactic acid [33].The LA productivity has been found to be consistently decreased as sugar concentration as well as incubation temperature has increased beyond optimal thereafter.This implies that LA productivity has got influenced due to LA accumulation at higher sugar concentration or substrate constituents' complexity and decrement in microbial activity at high temperature.
Both incubation time and sugar concentration has shown significant interactive effect on LA productivity (Table 4).The  lactic acid productivity irrespective of the sugar concentration has gradually increased with the increase in incubation time up to 54 h (Fig. 6).Further enhancement in time has resulted in a decrement in productivity.Similarly irrespective of the incubation time, the LA productivity has been found to be increased with the increase in sugar concentration up to 200 g/L and thereafter decrement has been observed which likely has indicated the onset of the substrate inhibition influence.Hence the LA productivity tends to decrease as the incubation time and sugar concentration simultaneously on approaching towards the high level of each.At low (-1) level of incubation time, with the increase in incubation temperature, levelling off the LA productivity has been observed as the temperature approaches its high (+1) level (Fig. 7).However at high (+1) level of incubation time the LA productivity was found to be decreased with the increase in incubation temperature just after a slight initial increase in it.At low level of incubation temperature the LA productivity has initially increased but no significant enhancement in the lactic acid productivity for incubation temperature of higher than 54 h has been noticed and it has decreased with an increase in the incubation time at high level of incubation temperature once the incubation time has increased beyond 48 h.The quadratic model (Eq.( 4)) has fourteen terms comprises of five each linear and quadratic terms along with four twofactorial interactions.The statistical significance of Eq. ( 4) was checked by analysis of variance (ANOVA).The analysis had shown that there were significant interactions between C S & pH; pH & τ f ; B w & T f and B w & τ f .ANOVA (Table 5) of the regression model demonstrates that the model is significant.

Interactive effect of variables on yield coefficient
The yield coefficient had displayed a parabolic behaviour with the increment in pH as well as sugar concentration with significant shifting towards higher level of both the parameters (Fig. 8).The microbial growth as well as the synthesis of metabolic enzymes which further in turn synthesis new protoplasm has been regulated and limited by pH [34].It has been demonstrated that the yield coefficient maxima could be achieved at optimal conditions of near 6.75 of pH and sugar concentration of 175 g/L (approx.).Further enhancement in pH and sugar concentration had led to a significant decrease in yield coefficient.This indicates that higher pH as well as enhanced sugar concentration has negative effect on the yield coefficient as the shift in pH towards alkanity or (4) acidulous influences the reaction pathways during the conversion of molasses sugar into lactic acid associated with the inhibiting factor of molasses at higher concentration [35].As evident from the Fig. 9 that the yield coefficient has increased with the increase in incubation time up to approx.50 h and 58 h of incubation time at low and high pH levels respectively and further enhancement in incubation time has resulted in decrement in yield coefficient.While the yield coefficient at low and high level of incubation time has been noticed to be increased with the increase in pH (up to 6.65) and thereafter it has shown a decrement.This suggests the negative impact of low and high pH at longer incubation time on yield coefficient as the pH influences the metabolism of the microbes.Low value of yield coefficient has been observed at low pH in comparison to that at high pH irrespective to the incubation time which might be attributed to the low acidogenic bacterial activity at low pH [36] resulting in utilization of more molasses sugar for the maintenance of the cells.Higher incubation temperature and high biomass loading has clearly depicted a negative interactive effect on the yield coefficient (Fig. 10).At low level of incubation time the yield coefficient has consistently decreased with the increase in biomass while at high level of temperature it initially has increased but afterwards a decrement has been noticed with the increase in biomass content.Since each bead contains limited space for the growth as well as maintenance and survival of the biomass entrapped in it hence with the enhancement in biomass content the availability of the substrate transported into the bead matrix becomes limited.Moreover the cell growth inside the beads can have affect on the mass transfer and fermentation efficiency profoundly causing reduction in yield coefficient [37].Low value of yield coefficient at low and high temperature irrespective of the biomass content may be attributed to the low metabolic rate [34].
Yield coefficient maxima could be visualized to be achieved at 55 h (approx.) and between 54 and 56 h of incubation time for low (-1) level and high (+1) level of biomass (CDW), respectively.The yield coefficient has consistently decreased at low level of incubation time with the increase in the biomass (CDW).
However at high level of incubation time, the yield coefficient has initially increased with the enhancement in biomass loaded in beads (up to 350 mg, CDW), but beyond that it has decreased.

Optimization of lactic acid production
Since a higher LA production combined with high LA productivity and high yield is highly desirable from technoeconomic point of view.Hence a numerical optimization using RSM was applied to obtain the optimized conditions for maximizing LA production, LA productivity and yield coefficient.It has been estimated that highest lactic acid production of 132g/L, lactic acid productivity of 2.36 g/(L×h) and yield coefficient of 0.936 g/(g substrate) could be obtained under the optimized conditions.The optimized conditions are sugar concentration: 194 g/L; pH: 6.85; biomass: 310 mg (CDW); incubation temperature: 37°C and incubation time: 57 h which were validated experimentally.In our previous study, it has been observed that the double layer coated beads (alginate) entrapping Lb. casei MTCC 1423 cells has exhibited a potential of elevated immobilization efficiency and consistent reusability performance up to ninth cycle (each of 72 h) with sugarcane molasses as substrate.

Validation of results
In order to validate the optimized values of the process variables for the maximum production of the lactic acid, experiments were conducted in triplicate using the optimized conditions obtained.A close correspondence between the values of model prediction and experimental data was observed.The optimization validated experiments had resulted in LA production of 130±2.1 g/(L fermentor volume); LA productivity of 2.28±0.037g/(L×h) and yield coefficient of 0.921±0.003g/ (g substrate) at obtained optimized process parameters values.Lactic acid production of 110±1.9g/(Lfermentor volume), LA productivity of 1.93±0.033g/(L×h) and yield coefficient of 0.91±0.002g/(gsubstrate) was obtained, on performing the experiments for LA biosynthesis by free cells of Lb. casei MTCC 1423 under the above optimized conditions i.e. molasses sugar concentration: 194 g/L; pH: 6.85; incubation temperature: 37°C and incubation time: 57 h with inoculums size of 2% (v/v) (observed optimal during our previous study for LA production from molasses by free cells of Lb. casei MTCC 1423) while keeping other fermentation conditions same as mentioned in materials and method section of this study.The high lactic acid productivity observed during the validation experiments by immobilized Lb. casei MTCC 1423 cells is characterized by high cell densities retained in the fermentation media and long term stability.A maximum of 26.6 g/L lactic acid was reported to be synthesised by Lb. casei ssp.Lb. rhamnosus ATCC 11979 cells immobilized in alginate/chitosan complexes with solid and liquid core at optimum temperature of 42°C in 44 h with optimum pH of 6.5 [9].A maximum rate of 2.16 g/(L×h) and a yield of 0.81 g/(g substrate) using food waste as carbon and nitrogen source was reported by Daniel et al. for lactic acid production using Streptococcus sp.Strains [38].
Lactic acid concentration ranging of 120.02-129.45g/L and productivity in the range of 2.5 to 2.69 g/(L×h) during 1-5 batches of repeated fermentation with NVLS as immobilization matrix was obserbed by Sailaja et al. [39].Lactic acid production of 136 g/L from whey by Lactobacillus casei NRRL B-441 cells immobilized in Ca-alginate/chitosan coated beads using yeast extract as nitrogen source has been reported by Goksungur et al. [40].The maximum lactic acid concentration of 42.19 g/L & 47.60 g/L, process productivity of 1.69 g/ (L×h) & 1.41 g/(L×h) and average yield coefficient of 0.96 g/ (g substrate) and 0.96 g/(g substrate) was achieved by Djukic-Vukovic during the LA fermentation of liquid stillage by Lb. rhamnosus ATCC 7469 cells immobilized onto zeolite and Mg modified Zeolite without mineral or nitrogen supplementation, respectively [10,41].Maximum LA preparation of 70 g/L & 93 g/L and average LA productivity of 2.7 g/(L×h) & 4.7 from glucose (100 g/L) by using 7.5 g of dry cells/L of Lb. casei and R. oryzae immobilized in Ca-alginate gel & PVA cryogel, respectively has been reported by Maslova et al. [42].

Conclusion
Homofermentive lactic acid production by immobilized cells of Lactobacillus casei MTCC 1423 was found to be promising value added utilization of agro industrial by-product molasses and industrial waste corn steep liquor as carbon and nitrogen sources, respectively.Lactic acid production of 130±2.1 g/(L fermentor volume), LA productivity of 2.28±0.037g/(L×h) and yield coefficient of 0.921±0.003g/(gsubstrate) has been

Fig. 1 Fig. 2 Fig. 3 Fig. 4
Fig. 1 Lactic acid production by immobilized Lb. casei MTCC as a function of biomass and sugar concentration

Fig. 5 Fig. 6
Fig. 5 Lactic acid productivity as a function of incubation temperature and sugar concentration for LA production by immobilized Lb. casei MTCC 1423

Fig. 7
Fig. 7 Lactic acid productivity as a function of incubation time and incubation temperature for LA production by immobilized Lb. casei MTCC 1423

Fig. 8 Fig. 9
Fig. 8 Yield coefficient as a function of pH and sugar concentration for LA production by immobilized Lb. casei MTCC 1423

Fig. 10 Fig. 11
Fig. 10 Yield coefficient as a function of incubation temperature and biomass for LA production by immobilized Lb. casei MTCC 1423

1
Research Laobratory-III, Department of Chemical Engineering, Sant Longowal Institute of Engineering and Technology, Longowal Punjab-148106, India 2 Biotechnology Research Laboratory, Department of Food Engineering and Technology, Sant Longowal Institute of Engineering and Technology, Longowal Punjab-148106, India 3 Guru Nanak Dev Engineering College, Ludhiana, Punjab, India

Table 1
Process variables range for batch lactic acid production by immobilized Lb. casei MTCC 1423 cells

Table
Experimental design of process variables and values of experimental data for lactic acid production by immobilized Lb. casei MTCC 1423 cells

Table 4
Regression model and ANOVA for lactic acid productivity by immobilized Lb. casei MTCC 1423

Table 5
Regression model and ANOVA for yield coefficient by immobilized Lb. casei MTCC 1423 * non-significant at 5 % level