Prediction of textural properties of 3D-printed food using response surface methodology.

3D printing has enabled modifying internal structures of the food affecting textural properties, but predicting desired texture remains challenging. To overcome this challenge, the use of response surface methodology (RSM) was demonstrated to develop empirical models relating 3D printing parameters to textural properties using aqueous inks containing cricket powders as a model system. Regression models were established for our key textural properties (i.e., hardness (H), adhesiveness (A), cohesiveness (C), and springiness (S)) in response to three 3D printing parameters: infill percentage (i), layer height (h), and print speed (s). Our developed model successfully predicted the 3D printing parameters to achieve the intended textural properties using a multi-objective optimization framework. The predicted limits for H, A, C, and S were 0.66-5.39 N, 0.01-12.43 mJ, 0.01-1.05, and 0-19.20 mm, respectively. To validate our models, we simulated the texture of other food using our model ink and achieved high accuracy for H (99%), C (82%), and S (87%). This work highlights a simple way to 3D-print foods with spatially different textures and materials, unlocking the full potential of 3D printing technology for manufacturing a range of customized foods.

Energizing tomorrow: unleashing spirulina's potential in engine performance optimization and emission reduction.

Dwindling of fossil fuels and the global climate change has prompted civilization to look into alternate energy sources. This has led to explore inexhaustible and sustainable resources in the domain of renewable energy. Among all sources renewable energy, biofuel produced from biomass has great prospect for energy security as well as environmental safety over fossil fuels. The present work tries to explore the performance attributes and emission characteristics of a CI engine utilizing spirulina microalgae biodiesel blend comprising of 20% algae biodiesel blended with 80% diesel. This blend is tested in a diesel engine at varying engine load conditions of 20%, 40%, 60%, 80%, and 100% at variable injection timing of 20°, 23°, 25°, and 28° bTDC, respectively at compression ratio of 18. Based on experimental results, the peak brake thermal efficiency for injection timing of 20°, 23°, 25°, and 28° bTDC at 100% engine load were observed to be 26.79%, 23.77%, 24.77%, and 25.09%, respectively for the biodiesel blend in comparison to 27.76% of diesel mode whereas the emissions levels were found to minimum at 20° bTDC. On the part of emission, the average drop in CO emissions for injection timing of 20°, 23°, 25°, and 28° bTDC were found to be 53.46%, 43.71%, 44.34%, and 50.31%, respectively for biodiesel blend as compared to diesel mode. For the same setting, in comparison diesel mode, the average fall in HC emissions were found to be 42.32%, 34.13%, 30.37%, and 37.54%, respectively, and the rise of NOx emissions were found to be 8.06%, 5.55%, 3.51%, and 3.04%, respectively. Response surface methodology was applied for optimization of operating parameters of the algae biodiesel blend run diesel engine. The desirability based study revealed that at 85.19% engine load and injection timing of 20° bTDC were optimal operation settings which resulted in engine performance of 25.44% brake thermal efficiency. The emission level at this setting was observed to be reduced to 27.68 ppm CO, 1.60% CO2, 24.65 ppm HC, and 182.15 ppm NOx.

Optimized combination of zero-valent iron and oxygen-releasing biochar as cathodes of microbial fuel cells to enhance copper migration in sediment.

Membrane-less single-medium sediment microbial fuel cells (single-SMFC) can remove Cu2+ from sediment through electromigration. However, the high mass transfer resistance of the sediment and amount of oxygen at the cathode of the SMFC limit its Cu2+ removal ability. Therefore, this study used an oxygen-releasing bead (ORB) for slow oxygen release to increase oxygen at the SMFC cathode and improve the mass transfer property of the sediment. Resultantly, the copper removal efficiency of SMFC increased significantly. Response surface methodology was used to optimize the nano zero-valent iron (nZVI)-modified biochar as the catalyst to enhance the ability of the modified ORB (ORBm) to remove Cu2+ and slow release of O2. The maximum Cu2+ removal (95 %) and the slowest O2 release rate (0.41 mg O2/d·g ORBm) were obtained when the CaO2 content and ratio of nZVI-modified biochar to unmodified biochar were 0.99 g and 4.95, respectively. When the optimized ORBm was placed at the single-SMFC cathode, the voltage output and copper removal increased by 4.6 and 2.1 times, respectively, compared with the system without ORBm. This shows that the ORBm can improve the migration of Cu2+ in the sediment, providing a promising remediation method for Cu-contaminated sediments.

Optimizing preparation of low-NaCl protein gels from goose meat and understanding synergistic effects of pH/NaCl in improving gel characteristics.

This study explored the feasibility of partially substituting NaCl with MgCl2 in preparing gel products from goose meat. Furthermore, the effects of synergistic interaction between different pH levels and NaCl concentrations on the structure and characteristics of the gels were explored by analyzing their secondary structure, microstructure, and water-distribution properties. The results showed that NaCl could be partially substituted by MgCl2, with the optimal preparation conditions: NaCl (0.83 mol/L), pH (7.3), MgCl2 (0.04 mol/L), heating temperature (79 °C), heating time (20 min), and solid-liquid ratio (1:3). Furthermore, the pH had a more significant impact on the gels' structure and characteristics than did NaCl concentration. Thus, our optimized method can reduce the usage of NaCl in the gel products while at the same time improving the characteristics of gel products under low-NaCl conditions by lowering pH, laying a solid theoretical foundation for producing low-NaCl protein gel products from goose meat.

Early properties of magnesium phosphate cement repairing material used in slab track.

Magnesium phosphate cement (MPC) is a high-performance repairing material suitable for the interfacial disease of slab track. In this study, the early properties of MPC were optimized using central composite design (CCD) approach based on response surface methodology (RSM). Three factors with five levels and three responses were considered. The significance of the factors and their interactions were verified by using analysis of variance (ANOVA). The result show that the mass ratio of water-to-binder (W/b) affects fluidity, while the mass ratio of magnesia-to-phosphate (M/P) and borax-to-magnesia (B/M) impact the setting time of MPC. Higher W/b results in higher fluidity, while an increase in M/P reduces the setting time by increasing the neutralization reaction. Borax addition retards the reaction, prolonging the setting time. The three factors significantly affect the early compressive strength of MPC. At M/P = 3.5, the interweaving of MgO and K-struvite (MKP) forms a dense network structure, enhancing the strength. Borax and W/b interact to affect compressive strength, with borax retarding MKP crystal growth and higher W/b reducing compactness. Combined with microscopic property test, the strength generation mechanism of MPC with optimized mixing ratio was revealed, And the feasibility of field application of MPC was verified by strength test.

Optimization of fermentation conditions and medium components for chrysomycin a production by Streptomyces sp. 891-B6.

BACKGROUND: Chrysomycin A (CA) is a promising antibiotic for treatment of Gram-positive bacterial infections and cancers. In order to enhance CA yield, optimization of fermentation conditions and medium components was carried out on strain Streptomyces sp. 891-B6, an UV-induced mutant with improved CA titer compared with its wide-type marine strain 891. RESULTS: Using one-way experiment, the optimal fermentation conditions for CA production in 1-L shake flask were obtained as follows: 12 days of fermentation time, 5 days of seed age, 5% of inoculum volume ratio, 200 mL of loading volume and 6.5 of initial pH. By response surface methodology, the optimal medium components determined as glucose (39.283 g/L), corn starch (20.662 g/L), soybean meal (15.480 g/L) and CaCO3 (2.000 g/L). CONCLUSION: Validation tests showed that the maximum yield of CA reached 1601.9 ± 56.7 mg/L, which was a 60% increase compared to the initial yield (952.3 ± 53.2 mg/L). These results provided an important basis for scale-up production of CA by strain 891-B6.

Prediction of the Physical-Mechanical Properties of Roller-Compacted Concrete Pavements under Different Service and Mix Conditions Based on Cement and Water Content.

Roller-compacted concrete (RCC) for pavements has experienced problems with its physical-mechanical performance over extended periods due to ambient and in situ curing conditions. Accordingly, this study aimed to present multiple regression equations for calculating the physical-mechanical properties of RCC for pavements under different service and mix conditions. For this purpose, the research included two cement and two water contents, one reduced with admixture, and four combinations of temperature and relative humidity. For model calibration and definition of the equations, cubic and beam samples were fabricated to carry out physical-mechanical tests, such as moisture content, shrinkage, and modulus of rupture. Laboratory-obtained data were studied with the Response Surface Methodology (RSM) to determine the best regression equations. The main findings determined that the behavior of a mixture of RCC at a prolonged ambient exposure time is possible because the surface models and the RSM were consistent with the different service and mix conditions. The models showed an accuracy of 98.99% in detecting shrinkage changes from 12 to 16% cement with 5.65% water in dry to wet ambient conditions. Similarly, moisture content and modulus of rupture had a 98.27 to 98.88% fit. Finally, the drying shrinkage, with mixes of 12% cement and water content variations with water-reducing admixture and superplasticizer effects, had an adjustment of 94.87%.

Optimization of photocatalytic ceramic membrane filtration by response surface methodology: Effects of hydrodynamic conditions on organic fouling and removal efficiency.

The effects of the operating conditions, including the applied pressure, feed organic concentration, and recirculation flowrate along the TiO2-coated ceramic membrane, on the normalized membrane permeability and organic removal efficiency were systematically investigated by operating a photocatalytic membrane reactor (PMR). Response surface methodology (RSM) was conducted to better understand the interactive effect of operational conditions as well as their individual and combined effects to control membrane performance. Our results showed that the applied pressure and feed organic concentration, as single parameter, affected the normalized membrane permeability and organic removal efficiency more dominantly than the recirculation flowrate. The polynomial performance equations generated by RSM successfully predicted the membrane performance of the PMR. The responses to the normalized membrane permeability and organic removal efficiency with respect to the operational conditions were less sensitive to any combination of operational conditions than to their individual impacts. The combined effects of the operating conditions were less pronounced in promoting the catalytic performance of organic contaminants on the TiO2 surface. Our RSM analysis based on experimental observations designed by Box-Behnken Design (BBD) suggested that 1.3 bar of applied pressure, 44 mg/L of feed organic dye concentration and 0.8 L/min as recirculation flowrate as optimum conditions achieved more than 98% of organic removal efficiency and less than 5% of decline in normalized membrane permeability. This research shows that the RSM provides effective tool to optimize operational conditions to determine fouling rate and organic removal in PMR.

Fabrication of cellulose-collagen based biosorbent as eco-friendly scavengers for uranyl ions.

The aim of the present research is to fabricate a biosorbent using agricultural waste for removal of uranium from contaminated water i.e. "waste to wealth" approach. Cellulose extracted from wheat straw was mercerized and a novel semi-interpenetrating polymer network (semi-IPN) was fabricated through graft copolymerization of polyvinyl alcohol onto hybrid mercerized cellulose + collagen backbone. Response surface methodology was used for optimization of different reaction parameters as a function of % grafting (195.1 %) was carried out. Semi-IPN was found to possess higher thermal stability. Adsorption results revealed that the optimum parameters for the elimination of uranium using semi-IPN were: adsorbent dose = 0.15 g, pH = 6.0, contact time = 120 min and initial U (VI) concentration = 100 µg/L. The pseudo-second-order kinetic model gave the best description of the adsorption equilibrium data as the calculated qe value is nearest to the experimental qe for the different initial U(VI) concentrations. Adsorption experiments followed Langmuir isotherm with R2 = 0.999. Furthermore, recyclability and reusability studies showed that the adsorption efficiency of semi-IPN was 82 % after 5 cycles indicating the superior recycling execution of fabricated biosorbent. Thus, the fabricated ecofriendly device can be used effectively for the removal of uranium from contaminated wastewater sources.

Optimization of preparation conditions for Salsola laricifolia protoplasts using response surface methodology and artificial neural network modeling.

BACKGROUND: Salsola laricifolia is a typical C3-C4 typical desert plant, belonging to the family Amaranthaceae. An efficient single-cell system is crucial to study the gene function of this plant. In this study, we optimized the experimental conditions by using Box-Behnken experimental design and Response Surface Methodology (RSM)-Artificial Neural Network (ANN) model based on the previous studies. RESULTS: Among the 17 experiment groups designed by Box-Behnken experimental design, the maximum yield (1.566 × 106/100 mg) and the maximum number of viable cells (1.367 × 106/100 mg) were obtained in group 12, and the maximum viability (90.81%) was obtained in group 5. Based on these results, both the RSM and ANN models were employed for evaluating the impact of experimental factors. By RSM model, cellulase R-10 content was the most influential factor on protoplast yield, followed by macerozyme R-10 content and mannitol concentration. For protoplast viability, the macerozyme R-10 content had the highest influence, followed by cellulase R-10 content and mannitol concentration. The RSM model performed better than the ANN model in predicting yield and viability. However, the ANN model showed significant improvement in predicting the number of viable cells. After comprehensive evaluation of the protoplast yield, the viability and number of viable cells, the optimal results was predicted by ANN yield model and tested. The amount of protoplast yield was 1.550 × 106/100 mg, with viability of 90.65% and the number of viable cells of 1.405 × 106/100 mg. The corresponding conditions were 1.98% cellulase R-10, 1.00% macerozyme R-10, and 0.50 mol L-1 mannitol. Using the obtained protoplasts, the reference genes (18SrRNA, ß-actin and EF1-α) were screened for expression, and transformed with PEG-mediated pBI121-SaNADP-ME2-GFP plasmid vector. There was no significant difference in the expression of ß-actin and EF1-α before and after treatment, suggesting that they can be used as internal reference genes in protoplast experiments. And SaNADP-ME2 localized in chloroplasts. CONCLUSION: The current study validated and evaluated the effectiveness and results of RSM and ANN in optimizing the conditions for protoplast preparation using S. laricifolia as materials. These two methods can be used independently of experimental materials, making them suitable for isolating protoplasts from other plant materials. The selection of the number of viable cells as an evaluation index for protoplast experiments is based on its ability to consider both protoplast yield and viability. The findings of this study provide an efficient single-cell system for future genetic experiments in S. laricifolia and can serve as a reference method for preparing protoplasts from other materials.

Experimental investigation on punch shear strength of poly lactic acid specimens for biomedical applications.

The designed biomedical implants require excellent shear strength primarily for mechanical stability against forces in human body. However, metallic implants undergo stress shielding with release of toxic ions in the body. Thus, Fused Deposition Modeling (FDM) has made significant progress in the biomedical field through the production of customized implants. The mechanical behavior is highly dependent on printing parameters, however, the effect of these parameters on punch shear strength of ASTM D732-02 standard specimens has not been explored. Thus, in the current study, the effect of infill density (IFD), printing speed (PTS), wall thickness (WLT), and layer thickness (LYT) has been investigated on the punch shear strength using Response Surface Methodology. The Analysis of Variance (ANOVA) has been performed for predicting statistical model with 95% confidence interval. During the statistical analysis, the terms with p-value lower than 0.05 were considered significant and the influence of process parameters has been examined using microscopic images. The surface plots have been used for discussing the effect of interactions between printing parameters. The statistical results revealed IFD as the most significant contributing factor, followed by PTS, LYT, and WLT. The study concluded by optimization of printing parameters for obtaining the highest punch shear strength.

Optimization of cassava peel ash concrete using central composite design method.

Cassava peel ash (CPA) is an abundant agricultural byproduct that has shown promise as an additional cementitious material in concrete manufacturing. This research study aims to optimize the incorporation of CPA in concrete blends using the central composite design (CCD) methodology to determine the most effective combination of ingredients for maximizing concrete performance. The investigation involves a physicochemical analysis of CPA to assess its pozzolanic characteristics. Laboratory experiments are then conducted to assess the compressive and flexural strengths of concrete mixtures formulated with varying proportions of CPA, cement, and aggregates. The results show that a mix ratio of 0.2:0.0875:0.3625:0.4625 for cement, CPA, fine, and coarse aggregates, respectively, yields a maximum compressive strength of 28.51 MPa. Additionally, a maximum flexural strength of 10.36 MPa is achieved with a mix ratio of 0.2:0.0875:0.3625:0.525. The experimental data were used to develop quadratic predictive models, followed by statistical analyses. The culmination of the research resulted in the identification of an optimal concrete blend that significantly enhances both compressive and flexural strength. To ensure the reliability of the model, rigorous validation was conducted using student's t-test, revealing a strong correlation between laboratory findings and simulated values, with computed p-values of 0.9987 and 0.9912 for compressive and flexural strength responses, respectively. This study underscores the potential for enhancing concrete properties and reducing waste through the effective utilization of CPA in the construction sector.

Optimizing recombinant production of L-asparaginase 1 from Saccharomyces cerevisiae using response surface methodology.

L-asparaginase is an essential enzyme used in cancer treatment, but its production faces challenges like low yield, high cost, and immunogenicity. Recombinant production is a promising method to overcome these limitations. In this study, response surface methodology (RSM) was used to optimize the production of L-asparaginase 1 from Saccharomyces cerevisiae in Escherichia coli K-12 BW25113. The Box-Behnken design (BBD) was utilized for the RSM modeling, and a total of 29 experiments were conducted. These experiments aimed to examine the impact of different factors, including the concentration of isopropyl-b-LD-thiogalactopyranoside (IPTG), the cell density prior to induction, the duration of induction, and the temperature, on the expression level of L-asparaginase 1. The results revealed that while the post-induction temperature, cell density at induction time, and post-induction time all had a significant influence on the response, the post-induction time exhibited the greatest effect. The optimized conditions (induction at cell density 0.8 with 0.7 mM IPTG for 4 h at 30 °C) resulted in a significant amount of L-asparaginase with a titer of 93.52 µg/mL, which was consistent with the model-based prediction. The study concluded that RSM optimization effectively increased the production of L-asparaginase 1 in E. coli, which could have the potential for large-scale fermentation. Further research can explore using other host cells, optimizing the fermentation process, and examining the effect of other variables to increase production.

Efficient reduction of vanadium (V) with biochar and experimental parameters optimized by response surface methodology.

Water pollution deteriorates ecosystems and has a great threaten to the environment. The environmental benefits of wastewater treatment are extremely important to minimize pollutants. Here, the biochar purchased from the related industry was used to treat the wastewater which contained high concentration of vanadium (V). The concentration of vanadium was measured by the IC-OES and the results showed that 96.1% vanadium (V) was reduced at selected reaction conditions: the mass ratio of biochar to vanadium of 5.4, reaction temperature of 90 °C, reaction time at 60 min and concentration of H2SO4 of 10 g/L, respectively. Response surface methodology confirmed that all the experimental parameters had positive effect on the reduction of vanadium (V), which could improve the reduction efficiency of vanadium (V) as increased. The influence of each parameter on the reduction process followed the order: A (Concentration of H2SO4) > C (mass ratio of biochar to vanadium) > B (mass ratio of biochar to vanadium). Especially, the mass ratio of biochar to vanadium and concentration of H2SO4 had the greatest influence on the reduction process. This paper provides a versatile strategy for the treatment of wastewater containing vanadium (V) and shows a bright tomorrow for wastewater treatment.

Recovery of Cembratrien-Diols from Waste Tobacco (Nicotiana tabacum L.) Flowers by Microwave-Assisted Deep Eutectic Solvent Extraction: Optimization, Separation, and In Vitro Bioactivity.

Deep eutectic solvents (DESs) are novel solvents with physicochemical properties similar to those of ionic liquids, and they have attracted extensive attention for the extraction of bioactive compounds from different plant materials in the context of green chemistry and sustainable development. In this study, seven DESs with different polarities were explored as green extraction solvents for cembratrien-diols (CBT-diols) from waste tobacco flowers. The best solvent, DES-3 (choline chloride: lactic acid (1:3)), which outperformed conventional solvents (methanol, ethanol, and ethyl acetate), was selected and further optimized for microwave-assisted DES extraction using the response surface methodology. The maximum yield of CBT-diols (6.23 ± 0.15 mg/g) was achieved using a microwave power of 425 W, microwave time of 32 min, solid/liquid ratio of 20 mg/mL, and microwave temperature of 40 °C. Additionally, the isolated CBT-diols exhibited strong antimicrobial activity against Salmonella, Staphylococcus aureus, Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa and antitumor activity in the human liver cancer HepG2 and SMMC-7721 cell lines. This study highlights the feasibility of recovering CBT-diols from tobacco flower waste using DESs and provides opportunities for potential waste management using green technologies.

Enhancing biodiesel yield and purification with a recently developed centrifuge machine: A response surface methodology approach.

Biodiesel production processes, such as gravity settling, have limitations in terms of biodiesel yield, purification efficiency, operating time in the separation process, and more extensive equipment. Therefore, this study has focused on using a recently developed centrifuge machine for biodiesel separation to address these challenges due to its compact design, high efficiency, and simplicity. Additionally, this study aimed to optimize the separation efficiency of glycerol from biodiesel using a centrifuge machine, employing response surface methodology (RSM) with central composite design (CCD). The optimum conditions for separating glycerol from biodiesel via centrifuge machine are a rotation speed of 1800 rpm, a mixture flow rate of 192.25 ml/min, and a temperature of 55 °C, respectively. In optimum conditions, 94.52% separation efficiency was achieved. Biodiesel production can be improved, leading to higher yields and greater purity. The utilization of RSM proved valuable in determining the optimum conditions for separation. Furthermore, the machine successfully separated the biodiesel to meet ASTM D6751 and EN 14,214 standards. The results highlight the potential of the centrifuge machine for efficient and reliable biodiesel production, contributing to the advancement of the biodiesel industry.

Application of experimental design as a statistical approach to recover bioactive peptides from different food sources.

Bioactive peptides (BAPs) derived from samples of animals and plants have been widely recommended and consumed for their beneficial properties to human health and to control several diseases. This work presents the applications of experimental designs (DoE) used to perform factor screening and/or optimization focused on finding the ideal hydrolysis condition to obtain BAPs with specific biological activities. The collection and discussion of articles revealed that Box Behnken Desing and Central Composite Design were the most used. The main parameters evaluated were pH, time, temperature and enzyme/substrate ratio. Among vegetable protein sources, soy was the most used in the generation of BAPs, and among animal proteins, milk and shrimp stood out as the most explored sources. The degree of hydrolysis and antioxidant activity were the most investigated responses in obtaining BAPs. This review brings new information that helps researchers apply these DoE to obtain high-quality BAPs with the desired biological activities.

Optimizing heat source distribution in sintering molds: Integrating response surface model with sequential quadratic programming.

The sintering mold imposes strict requirements for temperature uniformity. The mold geometric parameters and the power configuration of heating elements exert substantial influence. In this paper, we introduce an optimization approach that combines response surface models with the sequential quadratic programming algorithm to optimize the geometric parameters and heating power configuration of a heating system for sintering mold. The response surface models of the maximum temperature difference, maximum temperature, and minimum temperature of the sintering area are constructed utilizing the central composite design method. The model's reliability is rigorously confirmed through variance analysis, residual analysis, and generalization capability validation. The models demonstrate remarkable predictive accuracy within the design space. A nonlinear constrained optimization model is established based on the response surface models, and the optimal parameters are obtained after 9 iterations using the sequential quadratic programming algorithm. Under the optimal parameters, the maximum temperature difference is maintained at less than 5 °C, confirming exceptional temperature uniformity. We conduct parameter analysis based on standardized effects to determine the main influencing factors of temperature uniformity, revealing that the distance between adjacent heating rods and the power density of the inner heating rods exert significant influence. Enhanced temperature uniformity can be achieved by adopting a larger distance between heating rods and configuring the power density of the heating rods to a relatively modest level. This work introduces a practical approach to optimize the heating systems for sintering molds, with potential applications in various industrial mold optimization.

Influence of intensity ultrasound on rheological properties and bioactive compounds of araticum (Annona crassiflora) juice.

The use of extracts rich in bioactive compounds is becoming increasingly common in the food, cosmetics, and pharmaceutical industries for the production of functional products. Araticum is a potential fruit to be analyzed due to its content of phenolic compounds, carotenoids and vitamins, with antioxidant properties. Therefore, this study aimed to investigate the effect of ultrasound on total phenolic compounds, total carotenoids, ascorbic acid, color, turbidity and rheology in araticum juice. Response surface methodology based on a central composite design was applied. Araticum juice was subjected to sonication at amplitude levels ranging from 20 to 100 % of the total power (400 W) at a constant frequency of 20 kHz for different durations (2 to 10 min). Morphological analysis was conducted to observe microscopic particles, and viscosity and suitability to rheological models (Newtonian, Power Law, and Herschel-Bulkley) were assessed. The ultrasonic probe extraction method was compared to the control juice. According to the responses, using the desirability function, the optimal conditions for extraction were determined to be low power (low amplitude) applied in a short period of time or low power applied in a prolonged time. These conditions allowed an ultrasonic probe to act on releasing bioactive compounds without degrading them. All three rheological models were suitable, with the Power Law model being the most appropriate, exhibiting non-Newtonian pseudoplastic behavior.

Multiplexed colorimetry collaborated with smartphone-based image analysis for simultaneous and fast visualization of dyes in both environmental and food samples.

In this work, a multiplexed colorimetric strategy was initiated for simultaneous and fast visualization of dyes using low-cost and easy-to-prepare indicator papers as sorbents. Response surface methodology (RSM) was employed to model statistically and optimize the process variables for dyes extraction and colorimetric assays. Multiplexed colorimetry was realized by virtue of synchronous color alignments from different dimensions of multiple dyes co-stained colorimetric cards under RSM-optimized conditions, and smartphone-based image analysis was subsequently performed from different modes to double-check the credibility of colorimetric assays. As concept-to-proof trials, simultaneous visualization of dyes in both beverages and simulated dye effluents was experimentally proved with results highly matched to HPLC or spiked amounts at RSM-predicted staining time as short as 50 s ∼3 min, giving LODs as low as 0.97 ± 0.22/0.18 ± 0.08 µg/mL (tartrazine/brilliant blue) for multiplexed colorimetry, which much lower than those obtained by single colorimetry. Since this is the first case to propose such a RSM-guided multiplexed colorimetric concept, it will provide a reference for engineering of other all-in-one devices which can realize synchronous visualization applications within limited experimental steps.