Central Composite Design Model Research Articles

Simultaneous removal of Pb(II) and Cr(VI) from a steel company wastewater using various green adsorbents: Material characterization and numerical optimization

ABSTRACT This study focuses on the simultaneous uptake of Pb(II) and Cr(VI) from industrial wastewater by walnut shell (WS), almond shell (AS), peanut shell (PS), and coconut shell (CS) adsorbents. Among the used adsorbents, the CS adsorbent exhibited the greatest BET surface area of 18.97 m2/g and porosity of 63.17% and the WS adsorbent also had the highest pore volume of 0.3536 m3/g. Lead and chromium removal were optimized using response surface methodology via a central composite design (CCD) approach. The efficiency of lead and chromium uptake from the wastewater was enhanced by increasing the concentration of WS, AS, PS, and CS adsorbents (Cads.) and decreasing the flow rate (Q) of the wastewater. Under the optimal conditions (Cads. = 0.85 g/L and Q = 2.5 mL/min), the maximum lead and chromium uptake from steel company wastewater was achieved using CS (92%) and WS (97.2%) adsorbents, respectively. The actual lead and chromium removal values were well-fitted based on a high Rpred2, confirming the validity of the CCD model. The acceptable performance of these green adsorbents in the simultaneous removal of chromium and lead from the wastewater introduces the WS, AS, PS, and CS adsorbents as inexpensive and available candidates for industrial wastewater treatment containing heavy metals.

GREEN SYNTHESIS OF CaO–PdNps FROM LAWSONIA INERMIS LEAF EXTRACT: CATALYTIC REDUCTION OF METHYLENE BLUE WITH CENTRAL COMPOSITE DESIGN-ENHANCED NEURAL NETWORK PREDICTION

In this work, small-sized CaO–PdNps nanocomposites were synthesized using Lawsonia inermis leaf extract as a reducing and capping agent. X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR) were used to analyze the produced nanocomposites. Based on these investigations, the average particle size was found to be [Formula: see text][Formula: see text]nm, with a predominantly spherical morphology. The resulting nanocomposite was then tested for catalytic activity in methylene blue reduction. The mass of the catalyst and dye, the concentration of sodium borohydride ([NaBH4]), and the reaction time were all optimized using a central composite design (CCD). A significant correlation between predicted and experimental degradation percentages was shown by the CCD model ([Formula: see text]), which also proved statistically significant (p-[Formula: see text]). Furthermore, a deep learning neural network (DLNN) was used to improve the prediction accuracy over and beyond CCD. There was a good connection between the two models as a result of using the CCD output as DLNN validation data. Mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and [Formula: see text] were used to assess the performance of the DLNN. The results ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]) validated that all four metrics were successful in forecasting the percentage of degradation.

Utilization of water chestnut waste for biohydrogen production and enhanced power generation by stacked microbial fuel cell

A novel two-stage approach combining dark fermentation with microbial fuel cell (MFC) technology is proposed which enable biohydrogen production and bioelectricity generation from residual substrate energy. In the present study, batch fermentation of water chestnut waste using Enterobacter aerogenes (MTCC 2822) resulted in the production of biohydrogen. In the batch process, the highest production was 3.2 L/L. Further, single-parameter optimization and multi-parameter optimization were conducted via Response Surface Methodology (RSM) using the Central Composite Design (CCD) model. The maximum biohydrogen reached 3.44 g/L with 55% COD removal. The biohydrogen yield was 7.163 g H2/kg CODreduced with a maximum production rate of 712 mL/L/h. Further, the waste fermentation medium or spent media was used as a substrate in a Microbial Fuel Cell (MFC) to produce power using Pseudomonas aeruginosa PA1_NCHU as inoculum. MFCs were operated with various concentrations of phosphate buffer in the anolyte. As the output is limited in a single MFC, MFCs were operated in parallel stacks to increase power output. A maximum of 28% increase in the power density was observed in stacked MFCs. The energy recovered from the dark fermentation process was around 10.39% and a single MFC was around 10.67%. Hence, this study highlights the innovative use of agricultural waste and the effective combination of dark fermentation with stacked MFC, presenting a sustainable method of maximizing biohydrogen production and bioelectricity from spent media. By leveraging stacked MFC configuration, the potential of higher power output is demonstrated, underscoring the significance of this integrated system for energy recovery.

Optimization of ultrasound-assisted extraction of bioactive compounds from Carthamus caeruleus L. rhizome: Integrating central composite design, Gaussian process regression, and multi-objective Grey Wolf optimization approaches

The prediction of ultrasound-assisted extraction (UAE) for total phenolic content (TPC) and total flavonoid content (TFC) from Carthamus caeruleus L. rhizomes was conducted using a Gaussian process regression model (GPR) with a multi-objective Grey Wolf optimization approach (MOGWO). A central composite design (CCD) was employed first, examining ethanol concentration, temperature, time, and solvent-to-solid ratio as independent variables. TPC and TFC responses were analyzed under various conditions, revealing significant quadratic and interaction effects (p < 0.05). The GPR was then utilized to predict TPC and TFC, showing high accuracy with correlation coefficients near 1 and minimal root mean square error (RMSE) values. To simultaneously maximize TPC and TFC, the MOGWO was used in a multi-objective framework. Validation through CCD and GPR highlighted GPR's superior predictive accuracy. Optimal conditions (10% ethanol, 40°C, 20minutes sonication, and 50mLg-1 solvent to solid ratio) showed significant discrepancies in CCD predictions but high accuracy in GPR predictions. An interactive tool predicts TPC and TFC using CCD and GPR models. Users input extraction parameters and receive predictions, with a GWO-based optimization module for optimal conditions. The interface enables model comparison, improves process understanding, and optimizes bioactive compound extraction.

Synthesis of N-alkyl azoles carrying metal complexes for catalytic and medicinal applications

Drastic increase in water pollution due to industrial waste specifically dyeing reagents that are disturbing the water cycle ultimately may vanish the aquatic and human life. The current study focused on the synthesis of N-alkylated imidazole’s derivatives and their complexes; tetrakis(3-propyl-2,3-dihydro-1H-imidazol-1-yl)cerium(III) nitrate/C1 and tetrakis(3-butyl-2,3-dihydro-1H-imidazol-1-yl)cerium(III) nitrate/C2 with cerium(III) hexahydrate nitrate. Structural confirmation and chemical environment of synthesized products were confirmed by using FT-IR, FT-Raman, and NMR spectroscopic techniques. Synthesized complexes were evaluated as catalyst by using various independent variables like contact time, dose of catalyst and concentration of catalyst for degradation of Methyl Orange (MO) and Murexide (MX). RSM analyses via Central Composite Design (CCD) model of all these variables were designed and average degradation efficiencies were calculated in the range of 80–90 % that made the synthesized complexes fantastically fit for catalytic applications. Moreover, the ligands used in syntheses of complexes possessed characteristics to inhibit the growth of mutated cells of prostate and HeLa cell lines. Their IC50 values L1, L2, C1 and C2 were observed in the range of 21.3–23.6 µl for PC3 cell line and 12.72–19.51 µl for HeLa cell lines and compared with reported drug called Doxorubicin (Control). Thus, the syntheses of L1, L2, C1, and C2 successfully encountered the need of the concerned issues. They possessed extra-ordinary catalytic (about 84–94 % degradation of textile dyes) and pharmacological (anticancer activity against HeLa cell line and PC3 cell line) potential.

Central composite design for optimizing istamycin production by Streptomyces tenjimariensis.

Istamycins (ISMs) are 2-deoxyfortamine-containing aminoglycoside antibiotics (AGAs) produced by Streptomyces tenjimariensis ATCC 31603 with broad-spectrum bactericidal activities against most of the clinically relevant pathogens. Therefore, this study aimed to statistically optimize the environmental conditions affecting ISMs production using the central composite design (CCD). Both the effect of culture media composition and incubation time and agitation rate were studied as one factor at the time (OFAT). The results showed that both the aminoglycoside production medium and the protoplast regeneration medium gave the highest specific productivity. Results also showed that 6days incubation time and 200rpm agitation were optimum for their production. A CCD quadratic model of 17 runs was employed to test three key variables: initial pH, incubation temperature, and concentration of calcium carbonate. A significant statistical model was obtained including, an initial pH of 6.38, incubation temperature of 30 ˚C, and 5.3% CaCO3 concentration. This model was verified experimentally in the lab and resulted in a 31-fold increase as compared to the unoptimized conditions and a threefold increase to that generated by using the optimized culture media. To our knowledge, this is the first report about studying environmental conditions affecting ISM production as OFAT and through CCD design of the response surface methodology (RSM) employed for statistical optimization. In conclusion, the CCD design is an effective tool for optimizing ISMs at the shake flask level. However, the optimized conditions generated using the CCD model in this study should be scaled up in a fermenter for industrial production of ISMs by S. tenjimariensis ATCC 31603 considering the studied environmental conditions that significantly influence the production proces.

Optimization investigation of parameters for spot-welding of AA2014 and AISI316 dissimilar alloys

The objective of the research was to determine the exact process parameters required for spot-welding AA2014 and AISI316 alloys. The main focus was on achieving particular welding results, including nugget diameter, hardness, and tensile shear fracture load (TSFL). The central composite rotatable design model within the framework of a Response Surface Methodology (RSM) optimization approach, the study sought to intensify key spot weld process factors. The mechanical characteristics and nugget diameter of the welded joints were analyzed by carefully examining these factors to determine their significant effects. The investigation yielded crucial insights, revealing that the highest strength of welded joints, characterized by a nugget diameter of 5.982 mm, hardness of 149.6 VHN, and TSFL of 2.355 KN, was achieved at 3.4 kgf, when accompanied by 60 W power and a 2.5s duration. Notably, power emerged as the predominant factor driving the spot-welding process. Furthermore, microhardness and TSFL displayed direct correlations with power, while nugget diameter exhibited an inverse relationship. Moreover, rigorous statistical analyses, including F-tests and ANOVA, provided robust validation, indicating that the observed values fell comfortably within a 99.5% confidence interval for hardness, nugget diameter, and TSFL. These meticulously derived conclusions represent a significant stride towards establishing more standardized and efficient spot-welding protocols, particularly beneficial for the manufacturing sectors dealing with mild steel and aluminium materials.

Poly(allyl alcohol-co-vinyl acetate)-grafted concrete waste for adsorptive removal of As(III)

This study focused on the synthesis of concrete waste grafted with a polymer of allyl alcohol and vinyl acetate as a novel nano adsorbent and the investigation of its ability in the adsorptive removal of Arsenic (As(III)) from aqueous solutions. The prepared nano adsorbent was characterized using X-ray diffraction, thermogravimetric analysis, field-emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Fourier-transform infrared spectroscopy. Various parameters were optimized by response surface methodology and central composite design model to achieve the highest As(III) removal efficiency, including the solution's temperature, contact time, and pH. The model predicted a maximum removal efficiency of 92 % under the optimal conditions (temperature = 25 °C, contact time = 24 min, and pH = 7), resulting in a sorption capacity of 6.81 mg g−1. The zero point of charge for the nano adsorbent was obtained at about 6.5. The experimental data for As(III) sorption onto the nano adsorbent was well-fitted by the Freundlich isotherm and pseudo-1st-order kinetic models. This suggests that the adsorption process involves the formation of a multilayer of As(III) on the adsorbent surface, and it occurs through physical interactions rather than chemical reactions. The reusability of the nano adsorbent was evaluated, demonstrating a removal efficiency exceeding 72 % even after seven recycling cycles. The presence of interfering cations influenced the removal efficiency in the following order: Pb2+>Mn2+>Cu2+>Zn2+>Ni2+. The prepared nano adsorbent showed significant efficiency in removing As(III) from well water and river water samples, with a repeatability range of 1.09–2.51 %.

Statistical modeling and optimization of heavy metals (Pb and Cd) adsorption from aqueous solution by synthesis of Fe3O4/SiO2/PAM: isotherm, kinetics, and thermodynamic

In this study, magnetic material was synthesized using iron salts, then silicon-specific material was used to gain porosity, straight-chain polyacrylamide (PAM) was modified to give the surface functional properties, and the final product synthesized Fe3O4/SiO2/PAM nanocomposite material. Heavy metal (Pb and Cd) removal studies were carried out with the synthesized composite material, considering the central composite design and response surface methodology (CCD-RSM) optimization model. The effects of various parameters, for example, the initial concentration, pH, adsorbent dose, temperature and contact time, were investigated as a part of this study. To optimize these parameters, the CCD-RSM model was applied to design the experiments. Analysis of variance (ANOVA) was applied to evaluate statistical parameters and investigate interactions of variables. In the designed experimental set, the amount of adsorbent (30 mg), pH 7.0 value, temperature (40 °C), initial concentration of Pb (80 mg/L) and Cd (20 mg/L) and 90 min contact time were determined as the optimum conditions. The high coefficient of determination of both metals showed good agreement between experimental results and predicted values (R2 0.99; 0.95). TEM, SEM, XRD, FTIR, BET and Zeta potential analyses were performed to characterize the structure and morphology of the adsorbent. In Pb2+ and Cd2+ heavy metal removal studies, maximum adsorption capacities were determined as 66.54 and 13.22 mg/g, respectively. Additionally, adsorption isotherms, adsorption kinetics and thermodynamic modeling studies were conducted. Features such as large surface area and high adsorption capacity of the synthesized nanoparticles were observed. In this study, Fe3O4/SiO2/PAM demonstrated its potential as an effective adsorbent for the removal of heavy metal ions present in simulated wastewater samples. In particular, we can say that the material has a strong selectivity, as well as a high affinity for Pb(II) ions.

Joining of Al-Alloy Tubes by Carbon Steel Tubes using MPW Technique

Background/ Objectives: Joining aluminum alloys with low carbon steel (DC01) through fusion welding is a challenging task due to the occurrence of solidification defects like porosity, alloy segregation, and hot cracking. However, these issues can be addressed by employing solid-state welding techniques like explosive welding and MPW (magnetic pulse welding). MPW is a cost-effective and high-speed solid state welding method that involves creating joints in an overlap configuration. Methods: The MPW technique was employed to join dissimilar aluminum alloy AL 7075T6 hollow tube and DC01 steel rod in this study. A central composite design model was created to analyze the relationship between key MPW process parameters, including stand-off distance (SoD), overlap length, and discharge energy, and the bonding strength of the joints. Experimental setups were established and correlate with tensile-shear fracture load and interface hardness of the joints with the MPW process parameters. Findings: It is understood that the maximum TSFL of 2.404 kN was obtained under the welding condition of 23kJ discharge energy, 2.25 mm Stand-off distance, 8.5 mm overlap length, which is the optimum MP welding state for AA 7075 T6 with DC01 and confirmed by RSM. In addition, the cultivated connection can be aptly leveraged to anticipate the TSFL of MPW joints with a 95% confidence level. Novelty: The parametric mathematic samples were developed for forecasting TSFL of joints. The MPW parameters were optimized to enhance TSFL of joints. Aluminium alloys with low carbon steel joints were developed using MPW for cars and ships applications without fusion welding defects. Keywords: Magnetic Pulse Welding, Dissimilar Joint, (RSM) Response Surface Methodology, Tensile Shear-Fracture Load

Enhanced low-cost lipopeptide biosurfactant production by Bacillus velezensis from residual glycerin.

Biosurfactants (BSFs) are molecules produced by microorganisms from various carbon sources, with applications in bioremediation and petroleum recovery. However, the production cost limits large-scale applications. This study optimized BSFs production by Bacillus velezensis (strain MO13) using residual glycerin as a substrate. The spherical quadratic central composite design (CCD) model was used to standardize carbon source concentration (30g/L), temperature (34°C), pH (7.2), stirring (239rpm), and aeration (0.775vvm) in a 5-L bioreactor. Maximum BSFs production reached 1527.6mg/L of surfactins and 176.88mg/L of iturins, a threefold increase through optimization. Microbial development, substrate consumption, concentration of BSFs, and surface tension were also evaluated on the bioprocess dynamics. Mass spectrometry Q-TOF-MS identified five surfactin and two iturin isoforms produced by B. velezensis MO13. This study demonstrates significant progress on BSF production using industrial waste as a microbial substrate, surpassing reported concentrations in the literature.

Application of central composite design (CCD)-response surface methodology (RSM) for optimization of heat transfer in dusty nanofluid flow with velocity slip

Background and Purpose The consequence of thermal radiation is scrutinized on the heat transport of Nano-diamond/silicon oil and silver/silicon oil nanofluids through a stretching endless plate. The single phase (Tiwari and Das) model is employed for nanofluid. The major objective of this study is to optimize the RSM-based Central composite design modeling to optimization of the heat transfer in dusty Oldroyd-B nanofluid across stretching surface. Additionally the velocity slip effect is considered. The dust particle phase is also taken into account. The significance of viscous dissipation, joule heating, inclined magnetic field with convective condition is investigated. Methodology The partial differential equations are developed under consideration, then transform to ODE’s by utilizing similarity tools. The transformed model of ODE’s is tackled numerically via bvp4c MATLAB tool with shooting algorithm. The effect of magnetic parameter, fluid interaction parameter, nanoparticle volume fraction, slip parameter and temperature interaction parameter on velocity field and temperature distribution of fluid phase and dust phase is investigated. Furthermore the Nusselt number on the wall is observed for interactive parameters of mass concentration of dust particles, fluid particles interaction parameter for velocity and unsteady parameters utilizing the face-centered Central Composite design (CCD) of the Response Surface Methodology (RSM). Additionally, Analysis of Variance (ANOVA) algorithm and 3D plots are utilized to examine the consequence of experimental design parameters via the response. The recommended model significance has been analyzed in conditions of correlation coefficient ( R 2 ), mean square error (MSE), root means square error (RMSE), prediction standard error to acknowledge the most excellent strong. Results The difference between the Predicted R2 of 0.9467 and the Adjusted R2 of 0.9867 is less than 0.2, which is assumed to be a reasonable concurrence. Furthermore results of the current analysis indicate that velocity gradient for nanofluid is diminishes for larger fluid particle interaction parameter for velocity, while the dust phase velocity is improved. The increment in Temperature gradients is observed via increasing values of the nanoparticle fraction and temperature base fluid particle interaction parameter. From the results it is concluded that skin friction coefficient is reduced with larger magnetic parameter for both mono nanofluids. Furthermore the heat transfer rate is increased by increasing the thermal radiation parameter for both mono nanofluids. It is concluded that silver/silicon oil nanofluid play a higher role in heat transportation as compare to Nano-diamond/silicon oil.

Optimization of experimental conditions using central composite design for rifampicin removal

This research aims to optimize the impact of parametric conditions on the adsorption process of rifampicin, a drug used in tuberculosis treatment. The study specifically focuses on activated carbon derived from waste generated by a food processing facility, namely cacao shells (CS). Referred to as ACAFW (Activated Carbon Alimentary Factory Waste), the study utilizes a three-factor central composite design (CCD) experimental approach. The investigation is further connected to a parametric study aimed at verifying the effectiveness of the CCD model. Optimal treatment conditions were identified, including a pH of 6, an adsorbent dose of 0.3 g, and an antituberculosis concentration of 10 mg/L. These conditions demonstrated a close alignment between the obtained results (pH of 5.96, ACAFW dose of 0.328 g, and rifampicin concentration of 11.64 mg/L). The study employs a combination of the density functional theory (DFT) approach and infrared (IR) analysis to unravel the structure of rifampicin. Additionally, differential thermal analysis/thermogravimetry (DTA/TG) and Brunauer–Emmett–Teller (BET) analyses were conducted on the material. ACAFW showcased surface areas exceeding 1394 m2/g, and a microporous volume of 0.400 cm³/g. The results from the kinetic study imply that the adsorption process is influenced by competition between internal and external diffusion.

Highly stable reinforced nanostructure of silver-decorated on graphene oxide phytosynthesized through central composite design for antibacterial activity: Green and eco-friendly method

In this study, the simultaneous effects of reaction time, reaction temperature, and ratio of AgNO3 and Curcuma longa extract on the nanoparticle size in the silver nanoparticles@graphene oxide (Ag@GO) nanocomposite were thoroughly investigated via the central composite design model (CCD). The obtained results showed that all parameters played a crucial role in the change in the AgNPs size. Indeed, the synthesis conditions were determined to be 31.9 min, 60.22 °C, and volume ratio between AgNO3 and extract of 0.96 (mL/mL) according to the simulated model, while these were determined at 32 min, 60 °C, and 1.0 (mL/mL) of AgNO3:extract volume ratio in empirical experiments. Under these conditions, the average particle size of the AgNPs was determined to be 22.19 nm, which showed a negligible deviation as compared to the experimental result (23.47 nm). Furthermore, the characterization of the Ag@GO was also assessed, in which the AgNPs affirmed the presence of spherical shapes evenly distributed on the GO sheets through XPS spectra, XRD pattern, TEM, and AFM images results. In addition, the as-prepared material also shows a great antibacterial performance against both Escherichia coli and Staphylococcus aureus strains with the IC50 values of 2.70 and 2.86 μg/mL at the bacteria density of 108 CFU/mL. Besides, the stability of the Ag@GO material in the form of suspension after 3 months was also evaluated, in which insignificant changes in the morphological structure were observed as compared to the initial sample. The aforementioned results exerted the great potential of the as-prepared material as an antibacterial agent in medicinal applications.

Gaussian process regression with levy flight optimization: Advanced AR66 adsorption studies

The coal fly ash (CFA), which is the residue generated by coal-fired power plants, was converted into a valuable zeolite material known as zeolite P (ZNa-P) through thermal and acid pretreatments followed by microwave radiation. Various analytical techniques were utilized to analyze the resulting zeolite, including X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, BET analysis, and zeta potential measurement. The efficiency of ZNa-P in eliminating anionic dyes from aqueous solutions was exhibited by successfully removing acid red dye 66 (AR66) from a solution composed of water. To optimize the removal process, Central Composite Design (CCD) was applied to investigate the impact of four main parameters: solution pH, initial dye concentration, adsorbent mass, and contact time. The generated CCD database was modeled using Gaussian process regression (GPR) with the Lévy flight distribution (LFD) optimization algorithm. The GPR model was then used to determine optimal conditions for maximum AR66 absorption (3405.3 mg/g), with a pH of 2, initial dye concentration of 1000 mg/L, adsorbent mass of 0.2 g/L, and contact time of 11 minutes. Furthermore, the GPR model exhibited significantly lower error (32.58 mg/g) in predicting the experimental values compared to the CCD model (204.92 mg/g), highlighting the efficiency and superiority of the GPR model in this study.

Development and characterization of topical ethosomal gel for improved antifungal therapeutics

The present study aimed to develop Eberconazole nitrate (EBZ)-loaded ethosomes using Central Composite Design (CCD) by the cold method. The three-factor CCD model was implemented to investigate the effect of variables on ethosome characteristics and performance. For CCD modelling, dependent and independent variables were chosen. The percentage of soy phosphatidylcholine (PC) (X1; % w/v), ethanol (X2; % v/v), and Propylene glycol (PG) (X3; % v/v) were designated as independent variables. However, the dependent variables were particle size (Y1; nm), polydispersity index (PDI) (Y2), and encapsulation efficiency (EE) (Y3; %). The level of independent variables was changed to produce a total of 17 batches (F1-F17). Formulation code F2 with particle size; 227.9 nm, PDI; 0.160 and % EE; 90 ± 0.34 % was selected as the optimized batch. The optimized batch was further incorporated into the hydrogel matrix and investigated for several physicochemical parameters. When compared to the free drug-loaded hydrogel, the ethosomes-loaded hydrogel demonstrated controlled EBZ release with higher skin permeation and skin retention of EBZ. The assessment of antifungal efficacy of the developed formulation was carried out by in vivo animal model method. In vivo studies demonstrated that EBZ-loaded ethosomal gel may alleviate fungal infection caused by a resistant strain of Candida albicans. The study showed satisfactory results, which suggest the suitability of the developed formulation for the effective treatment of fungal infection.

Optimization of culture conditions for keratinase production of Bacillus tropicus KRKJVR 5 by using RSM (Response Surface Methodology)

This study aimed to optimize the production of keratinase by Bacillus tropicus KRKJVR 5 using response surface methodology (RSM). The factors considered were temperature (20 to 40°C), pH (5 to 9), inoculum size (0.5 to 2.5%), incubation period (24 to 120 hours) and agitation speed (RPM) (50 to 350). A total of 32 experimental runs were conducted based on the central composite design (CCD) model, with observed keratinase activity ranging from 2.00 to 13.33 U/mL. The highest keratinase activity (13.33 U/mL) was observed under the conditions of 30°C temperature, pH 7.0, 1.5% inoculum size, 72 hours incubation period and 150 RPM. The lowest activity (2.00 U/mL) was recorded at extreme conditions of low pH (3.0) and high temperature (50°C), highlighting the sensitivity of keratinase production to these factors. The regression analysis revealed a significant model with an R-squared value of 93.78%, indicating a strong fit to the data. The ANOVA results further supported the significance of these factors, with the overall model being highly significant (F-Value = 8.30, P-Value = 0.000). The contour plots demonstrated the optimal conditions for maximizing keratinase activity. The study effectively identified the optimal conditions for keratinase production by Bacillus tropicus KRKJVR 5 using response surface methodology. The results indicate that a temperature of 30°C, pH of 7.0, inoculum size of 1.5%, incubation period of 72 hours, and agitation speed of 150 RPM are ideal for producing high levels of keratinase. These findings provide valuable insights for scaling up the process for industrial applications, emphasizing the importance of precise control over culture conditions to achieve high enzyme yields.

Optimisation of POME biodiesel with isobutanol additive to cater UN sustainable development goal on affordable and clean energy

Biodiesel is a suitable alternative to solve global pollution and declining non-renewable resources. This aligns with the sustainable climate goals and policies to cater to SDG 7. Sustainable technology and solutions have to be fostered. The higher blends of biodiesel will result in engine performance and emissions degradation. Therefore, this research aims to improve the engine performance and emissions of diesel engines operating with B20 POME biodiesel and isobutanol. The Central Composite Design (CCD) model was used to construct the RSM model to determine the optimised condition of the engine testing. Engine performance and emissions of diesel engines were tested on the Yanmar TF120M at 50 % load. Six fuel samples, diesel, B20 Palm Oil Methyl Ester (POME) biodiesel blended fuel, and another four B20 POME biodiesel blends added with 5–20 % in volume percentage of isobutanol, were tested. The optimised RSM obtained a desirability of 0.7. The optimal conditions for the engine testing were at 1868 rpm and a 10 % isobutanol additive percentage. The brake power, BSFC, and BTE of the B95IBU5 and B90IBU10 show an improvement compared to the B20. The exhaust emission shows the lowest CO emission for B90IBU10 at 50 % load. The lowest NOx emission was obtained by B95IBU5 and B90IBU10, with an improvement of 1.8 % and 2.4 %, respectively. Therefore, from this study, it can be concluded that a lower percentage of isobutanol additive of 5–10 % is a promising additive for biodiesel blended fuels.

Optimization of Combined Microwave and Ultrasound Extractions of Cannabinoids Compounds from Cannabis indica L. (Blueberry Cultivar) Using Response Surface Methodology

Microwave and ultrasound are novel technologies that are widely used for extracting bioactive compounds from plant materials. In this study, combined extraction techniques, microwave and ultrasound, were applied to extract cannabinoids, cannabidiol (CBD) and delta-9-tetrahydrocannabinol (THC), from Cannabis indica L. (Blueberry cultivar). Three independent variables including solid to liquid ratio (X1, A: 1:10-1:30 w/v), microwave extraction time (X2, B: 5-20 min), and ultrasound extraction time (X3, C: 10-30 min) were optimized using central composite design (CCD). The experimental data obtained was fitted to a second-order polynomial equation using multiple regression analysis and additionally analyzed using appropriate statistical methods (analysis of variance, ANOVA). The optimum conditions were determined according to the solid to liquid ratio (X1, A) of 1:22 (w/v), microwave extraction time (X2, B) of 5 min and ultrasound extraction time (X3, C) of 14 min. Under these conditions, the experimental CBD and THC content was 0.298±0.001 mg/g dry weight and 91.35±0.35 mg/g dry weight, respectively. The experimentally-achieved values were in accordance with those estimated by the CCD model, suggesting the applicability of the utilized model and the favorable result of CCD’s application in the optimization of the combined microwave and ultrasound extraction.

Enzymatic Hydrolysis of Protein Hydrolysate from Pangasius sp. by-Product using Bromelain

Fish protein hydrolysate (FPH) is a product resulting from the degradation of fish protein into simple peptides and amino acids through hydrolysis. This study aims to optimise the enzymatic hydrolysis conditions of Pangasius sp. by-products to produce high-quality fish protein hydrolysate. Bromelain enzyme was used as the catalyst for hydrolysis. The degree of hydrolysis (DH), pH and antioxidant activity of FPH were used as response parameters. The optimisation was done using response surface methodology (RSM) by applying two factors (enzyme concentration and incubation time) with a 3-level Central Composite Design (CCD) model. The result showed that the bromelain concentration and incubation time of catfish protein hydrolysate gave significantly different effects (p&lt;0.05) on the response parameters of Pangasius protein hydrolysate. Hydrolysis of Pangasius protein with 0.04% bromelain enzyme and incubation time of 2.8 hours resulted in DH, pH and DPPH antioxidant activity of 35.88%, 7.07 and 29.86%, respectively. The response value of Pangasius protein hydrolysate was within the range of the predicted value of hydrolysate. Therefore, the optimum conditions suggested by RSM can be used in the future production of Pangasius FPH. In addition, amino acid profiles of Pangasius protein hydrolysate showed high concentrations of Glycine, L-glutamic acid and L-aspartic Acid.