Abstract: The hydrolysis of lactose using β-galactosidase is one of the most promising biotechnological applications, which has wide range of potential applications in food processing industries. However, due to intracellular location of the yeast enzyme, and expensive extraction methods, the industrial applications of enzymatic hydrolysis processes are being hampered. The use of permeabilization technique can help to overcome the problems associated with enzyme extraction and purification of yeast cells and to develop the economically viable process for the utilization of whole cell biocatalysts in food industries. In the present investigation, standardization of permeabilization process of novel yeast isolate was carried out using a statistical model approach known as Response Surface Methodology (RSM) to achieve maximal b-galactosidase activity. The optimum operating conditions for permeabilization process for optimal β-galactosidase activity obtained by RSM were 1:1 ratio of toluene (25%, v/v) and ethanol (50%, v/v), 25.0 oC temperature and treatment time of 12 min, which displayed enzyme activity of 1.71 IU /mg DW.
Abstract: In this work the concentration of steepwater from corn starch industry is monitored using ultrafiltration membrane. The aim was to examine the conditions of ultrafiltration of steepwater by applying the membrane of 2.5nm. The parameters that vary during the course of ultrafiltration, were the transmembrane pressure, flow rate, while the permeate flux and the dry matter content of permeate and retentate were the dependent parameter constantly monitored during the process. Experiments of ultrafiltration are conducted on the samples of steepwater, which were obtained from the starch wet milling plant „Jabuka“ Pancevo. The procedure of ultrafiltration on a single-channel 250mm lenght, with inner diameter of 6.8mm and outer diameter of 10mm membrane were carried on. The membrane is made of a-Al2O3 with TiO2 layer obtained from GEA (Germany). The experiments are carried out at a flow rate ranging from 100 to 200lh-1 and transmembrane pressure of 1-3 bars. During the experiments of steepwater ultrafiltration, the change of permeate flux, dry matter content of permeate and retentate, as well as the absorbance changes of the permeate and retentate were monitored. The experimental results showed that the maximum flux reaches about 40lm-2h-1. For responses obtained after experiments, a polynomial model of the second degree is established to evaluate and quantify the influence of the variables. The quadratic equitation fits with the experimental values, where the coefficient of determination for flux is 0.96. The dry matter content of the retentate is increased for about 6%, while the dry matter content of permeate was reduced for about 35-40%, respectively. During steepwater ultrafiltration in permeate stays 40% less dry matter compared to the feed.
Abstract: Humic acids (HA) were produced by a Trichoderma
viride strain under submerged fermentation in a medium based on the
oil palm empty fruit bunch (EFB) and the main variables of the
process were optimized by using response surface methodology. A
temperature of 40°C and concentrations of 50g/L EFB, 5.7g/L potato
peptone and 0.11g/L (NH4)2SO4 were the optimum levels of the
variables that maximize the HA production, within the
physicochemical and biological limits of the process. The optimized
conditions led to an experimental HA concentration of 428.4±17.5
mg/L, which validated the prediction from the statistical model of
412.0mg/L. This optimization increased about 7–fold the HA
production previously reported in the literature. Additionally, the
time profiles of HA production and fungal growth confirmed our
previous findings that HA production preferably occurs during fungal
sporulation. The present study demonstrated that T. viride
successfully produced HA via the submerged fermentation of EFB
and the process parameters were successfully optimized using a
statistics-based response surface model. To the best of our
knowledge, the present work is the first report on the optimization of
HA production from EFB by a biotechnological process, whose
feasibility was only pointed out in previous works.
Abstract: The aim of this study was to obtain the optimal conditions for biogas production from anaerobic digestion of organic fraction of municipal solid waste (OFMSW) using response surface methodology (RSM). The parameters studied were initial pH, substrate concentration and total organic carbon (TOC). The experimental results showed that the linear model terms of initial pH and substrate concentration and the quadratic model terms of the substrate concentration and TOC had significant individual effect (p < 0.05) on biogas yield. However, there was no interactive effect between these variables (p > 0.05). The highest level of biogas produced was 53.4 L/Kg VS at optimum pH, substrate concentration and total organic carbon of 6.5, 99gTS/L and 20.32 g/L respectively.
Abstract: Artificial neural networks (ANN) are used in distinct researching fields and professions, and are prepared by cooperation of scientists in different fields such as computer engineering, electronic, structure, biology and so many different branches of science. Many models are built correlating the parameters and the outputs in electrical discharge machining (EDM) concern for different types of materials. Up till now model for Ti-5Al-2.5Sn alloy in the case of electrical discharge machining performance characteristics has not been developed. Therefore, in the present work, it is attempted to generate a model of material removal rate (MRR) for Ti-5Al-2.5Sn material by means of Artificial Neural Network. The experimentation is performed according to the design of experiment (DOE) of response surface methodology (RSM). To generate the DOE four parameters such as peak current, pulse on time, pulse off time and servo voltage and one output as MRR are considered. Ti-5Al-2.5Sn alloy is machined with positive polarity of copper electrode. Finally the developed model is tested with confirmation test. The confirmation test yields an error as within the agreeable limit. To investigate the effect of the parameters on performance sensitivity analysis is also carried out which reveals that the peak current having more effect on EDM performance.
Abstract: Electrical discharge machining (EDM) is a relatively modern machining process having distinct advantages over other machining processes and can machine Ti-alloys effectively. The present study emphasizes the features of the development of regression equation based on response surface methodology (RSM) for correlating the interactive and higher-order influences of machining parameters on surface finish of Titanium alloy Ti-6Al-4V. The process parameters selected in this study are discharge current, pulse on time, pulse off time and servo voltage. Machining has been accomplished using negative polarity of Graphite electrode. Analysis of variance is employed to ascertain the adequacy of the developed regression model. Experiments based on central composite of response surface method are carried out. Scanning electron microscopy (SEM) analysis was performed to investigate the surface topography of the EDMed job. The results evidence that the proposed regression equation can predict the surface roughness effectively. The lower ampere and short pulse on time yield better surface finish.
Abstract: In the present study, effect of critical medium components (a total of fifteen components) on ethanol production from waste cashew apple juice (CAJ) using yeast Saccharomyces diasticus was studied. A statistical response surface methodology
(RSM) based Plackett-Burman Design (PBD) was used for the design of experiments. The design contains a total of 32 experimental trails. The effect of medium components on ethanol was studied at two different levels such as low concentration level (-) and high concentration levels (+). The dependent variables selected in this study were ethanol concentration (g/L) and cellmass concentration (g/L). Data obtained from RSM on ethanol production were subjected to analysis of variance (ANOVA). In general, initial substrate concentration significantly influenced the microbial growth and product formation. Of the medium components evaluated, CAJ concentration, yeast extract, (NH4)2SO4, and malt extract showed significant effect on ethanol fermentation. A second-order polynomial model was used to predict the experimental data and the model fitted the data with a high correlation coefficient (R2 > 0.98).
Maximum ethanol (15.3 g/L) and biomass (6.4 g/L) concentrations
were obtained at the optimum medium composition and at optimum
condition (temperature-30°C; initial pH-6.8) after 72 h fermentation
using S.diasticus.
Abstract: The process parameters, starch-water ratio (A, (w/v) %), pH of suspension (B), Temperature(C, °C) and Time (D, hrs.)., were optimized for the preparation of starch-lysine conjugate and studying their effect on stability of emulsions by calculating emulsion stability index using response surface methodology. The optimized conditions are pH 9.0, temperature 60oC, reaction time 6 hrs, starch:water ratio 1:2.5, having emulsion stability index was 0.72.
Abstract: A total of 6 isolates of Bacillus subtilis were isolated from oil mill waste collected in Namakkal district, Tamilnadu, India. The isolated bacteria were screened using lipase screening medium containing Tween 80. BS-3 isolate exhibited a greater clear zone than the others, indicating higher lipase activity. Therefore, this isolate was selected for media optimization studies. Ten process variables were screened using Plackett–Burman design and were further optimized by central composite design of response surface methodology for lipase production in submerged fermentation. Maximum lipase production of 16.627 U/min/ml were predicted in medium containing yeast extract (9.3636g), CaCl2 (0.8986g) and incubation periods (1.813 days). A mean value of 16.98 ± 0.2286 U/min/ml of lipase was acquired from real experiments.
Abstract: In this study, statistical optimization design was used to study the optimum disinfection parameters using defatted crude Moringa oleifera seed extracts against Escherichia coli (E. coli) bacterial cells. The classical one-factor-at-a-time (OFAT) and response surface methodology (RSM) was used. The possible optimum range of dosage, contact time and mixing rate from the OFAT study were 25mg/l to 200mg/l, 30minutes to 240 minutes and 100rpm to 160rpm respectively. Analysis of variance (ANOVA) of the statistical optimization using faced centered central composite design showed that dosage, contact time and mixing rate were highly significant. The optimum disinfection range was 125mg/l, at contact time of 30 minutes with mixing rate of 120 rpm.
Abstract: Optimization of a microwave-assisted extraction of cherry laurel (Prunus laurocerasus) fruit using methanol was studied. The influence of process parameters (microwave power, plant material-to-solvent ratio and the extraction time) on the extraction efficiency were optimized by using response surface methodology. The predicted maximum yield of extractive substances (41.85 g/100 g fresh plant material) was obtained at microwave power of 600 W and plant material to solvent ratio of 0.2 g/cm3 after 26 minutes of extraction, while a mean value of 40.80±0.41 g/100 g fresh plant material was obtained from laboratory experiments. This proves applicability of the model in predicting optimal extraction conditions with minimal laborious and time consuming. The results indicated that all process parameters were effective on the extraction efficiency, while the most important factor was extraction time. In order to rationalize production the optimal economical condition which gave a large total extract yield with minimal energy and solvent consumption was found.
Abstract: In this work, sorption of nickel from aqueous solution on hypnea valentiae, red macro algae, was investigated. Batch experiments have been carried out to find the effect of various parameters such as pH, temperature, sorbent dosage, metal concentration and contact time on the sorption of nickel using hypnea valentiae. Response surface methodology (RSM) is employed to optimize the process parameters. Based on the central composite design, quadratic model was developed to correlate the process variables to the response. The most influential factor on each experimental design response was identified from the analysis of variance (ANOVA). The optimum conditions for the sorption of nickel were found to be: pH – 5.1, temperature – 36.8oC, sorbent dosage – 5.1 g/L, metal concentration – 100 mg/L and contact time – 30 min. At these optimized conditions the maximum removal of nickel was found to be 91.97%. A coefficient of determination R2 value 0.9548 shows the fitness of response surface methodology in this work.
Abstract: A statistical optimization of the saccharification
process of EFB was studied. The statistical analysis was done by
applying faced centered central composite design (FCCCD) under
response surface methodology (RSM). In this investigation, EFB
dose, enzyme dose and saccharification period was examined, and the
maximum 53.45% (w/w) yield of reducing sugar was found with 4%
(w/v) of EFB, 10% (v/v) of enzyme after 120 hours of incubation. It
can be calculated that the conversion rate of cellulose content of the
substrate is more than 75% (w/w) which can be considered as a
remarkable achievement. All the variables, linear, quadratic and
interaction coefficient, were found to be highly significant, other than
two coefficients, one quadratic and another interaction coefficient.
The coefficient of determination (R2) is 0.9898 that confirms a
satisfactory data and indicated that approximately 98.98% of the
variability in the dependent variable, saccharification of EFB, could
be explained by this model.
Abstract: An attempt has been made to investigate the
machinability of zirconia toughened alumina (ZTA) inserts while
turning AISI 4340 steel. The insert was prepared by powder
metallurgy process route and the machining experiments were
performed based on Response Surface Methodology (RSM) design
called Central Composite Design (CCD). The mathematical model of
flank wear, cutting force and surface roughness have been developed
using second order regression analysis. The adequacy of model has
been carried out based on Analysis of variance (ANOVA) techniques.
It can be concluded that cutting speed and feed rate are the two most
influential factor for flank wear and cutting force prediction. For
surface roughness determination, the cutting speed & depth of cut
both have significant contribution. Key parameters effect on each
response has also been presented in graphical contours for choosing
the operating parameter preciously. 83% desirability level has been
achieved using this optimized condition.
Abstract: In recent years, response surface methodology (RSM) has
brought many attentions of many quality engineers in different
industries. Most of the published literature on robust design
methodology is basically concerned with optimization of a single
response or quality characteristic which is often most critical to
consumers. For most products, however, quality is multidimensional,
so it is common to observe multiple responses in an experimental
situation. Through this paper interested person will be familiarize
with this methodology via surveying of the most cited technical
papers.
It is believed that the proposed procedure in this study can resolve
a complex parameter design problem with more than two responses.
It can be applied to those areas where there are large data sets and a
number of responses are to be optimized simultaneously. In addition,
the proposed procedure is relatively simple and can be implemented
easily by using ready-made standard statistical packages.
Abstract: With the aim of improving nutritional profile and antioxidant capacity of gluten-free cookies, blueberry pomace, by-product of juice production, was processed into a new food ingredient by drying and grinding and used for a gluten-free cookie formulation. Since the quality of a baked product is highly influenced by the baking conditions, the objective of this work was to optimize the baking time and thickness of dough pieces, by applying Response Surface Methodology (RSM) in order to obtain the best technological quality of the cookies. The experiments were carried out according to a Central Composite Design (CCD) by selecting the dough thickness and baking time as independent variables, while hardness, color parameters (L*, a* and b* values), water activity, diameter and short/long ratio were response variables. According to the results of RSM analysis, the baking time of 13.74min and dough thickness of 4.08mm was found to be the optimal for the baking temperature of 170°C. As similar optimal parameters were obtained by previously conducted experiment based on sensory analysis, response surface methodology (RSM) can be considered as a suitable approach to optimize the baking process.
Abstract: Response Surface Methodology (RSM) is a powerful
and efficient mathematical approach widely applied in the
optimization of cultivation process. Cellulase enzyme production by
Trichoderma reesei RutC30 using agricultural waste rice straw and
banana fiber as carbon source were investigated. In this work,
sequential optimization strategy based statistical design was
employed to enhance the production of cellulase enzyme through
submerged cultivation. A fractional factorial design (26-2) was applied
to elucidate the process parameters that significantly affect cellulase
production. Temperature, Substrate concentration, Inducer
concentration, pH, inoculum age and agitation speed were identified
as important process parameters effecting cellulase enzyme synthesis.
The concentration of lignocelluloses and lactose (inducer) in the
cultivation medium were found to be most significant factors. The
steepest ascent method was used to locate the optimal domain and a
Central Composite Design (CCD) was used to estimate the quadratic
response surface from which the factor levels for maximum
production of cellulase were determined.
Abstract: Pretreatment is an essential step in the conversion of
lignocellulosic biomass to fermentable sugar that used for biobutanol
production. Among pretreatment processes, microwave is considered
to improve pretreatment efficiency due to its high heating efficiency,
easy operation, and easily to combine with chemical reaction. The
main objectives of this work are to investigate the feasibility of
microwave pretreatment to enhance enzymatic hydrolysis of
corncobs and to determine the optimal conditions using response
surface methodology. Corncobs were pretreated via two-stage
pretreatment in dilute sodium hydroxide (2 %) followed by dilute
sulfuric acid 1 %. Pretreated corncobs were subjected to enzymatic
hydrolysis to produce reducing sugar. Statistical experimental design
was used to optimize pretreatment parameters including temperature,
residence time and solid-to-liquid ratio to achieve the highest amount
of glucose. The results revealed that solid-to-liquid ratio and
temperature had a significant effect on the amount of glucose.
Abstract: Implementation of response surface methodology (RSM) was employed to study the effects of two factor (rubber clearance and round per minute) in brown rice peeling machine of The optimal BROKENS yield (19.02, average of three repeats),.The optimized composition derived from RSM regression was analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level α = 0.05, the values of Regression coefficient, R 2 (adj)were 97.35 % and standard deviation were 1.09513. The independent variables are initial rubber clearance, and round per minute parameters namely. The investigating responses are final rubber clearance, and round per minute (RPM). The restriction of the optimization is the designated.
Abstract: This study deals with a multi-criteria optimization
problem which has been transformed into a single objective
optimization problem using Response Surface Methodology (RSM),
Artificial Neural Network (ANN) and Grey Relational Analyses
(GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques
which can be used for solving multi-criteria optimization problem.
There have been two main purposes of this research as follows.
1. To determine optimum and robust fiber dyeing process
conditions by using RSM and ANN based on GRA,
2. To obtain the best suitable model by comparing models
developed by different methodologies.
The design variables for fiber dyeing process in textile are
temperature, time, softener, anti-static, material quantity, pH,
retarder, and dispergator. The quality characteristics to be evaluated
are nominal color consistency of fiber, maximum strength of fiber,
minimum color of dyeing solution. GRA-RSM with exact level
value, GRA-RSM with interval level value and GRA-ANN models
were compared based on GRA output value and MSE (Mean Square
Error) performance measurement of outputs with each other. As a
result, GRA-ANN with interval value model seems to be suitable
reducing the variation of dyeing process for GRA output value of the
model.