Characterization of teff straw fibers and optimization of soda-anthraquinone delignification of the teff straw for pulp production using response surface methodology in view of agricultural waste valorization

The present study evaluated first the characterization of Teff straw and then Box–Behnken design (BBD), and response surface methodology was adopted to optimize the parameters (hydrolysis temperature, dilute sulfuric acid concentration, solid to liquid ratio, and hydrolysis time) of dilute sulfuric acid hydrolysis of Teff straw in order to get a maximum yield of total reducing sugar (TRS). The chemical analysis of Teff straw revealed high amounts of cellulose (41.8 wt%), hemicellulose (38 wt%), and lignin (17 wt%). The morphological analysis using SEM showed that hydrolyzed Teff straw with dilute sulfuric acid has more pores and distorted bundles than those of raw Teff straw. XRD analysis also indicated that hydrolyzed Teff straw has higher crystallinity index and smaller crystallite size than raw Teff straw, which might be due to removal of hemicellulose, amorphous cellulose, and lignin components. Under the optimized conditions for dilute sulfuric acid hydrolysis of Teff straw (120°C, 4% v/v H2SO4 concentration, 1 : 20 solid to liquid ratio, and 55 min hydrolysis time), we have found a total reducing sugar yield of 26.65 mg/g. The results of validation experiment under the optimum conditions agreed well with model predictions.

Microwave vacuum drying of pomegranate peel was studied through this work and the drying process was modeled with the aid of response surface methodology (RSM) and artificial neural network (ANN) method. The drying experimental runs were performed on varied ranges of microwave power (175, 330, and 485 W) and vacuum pressure (10, 15, and 20 kPa) using a face-centered composite design. The influence of process parameters on five target responses, namely: total hydrolysable tannin (THT), color change (ΔE), maximum temperature evolved (Tmax), effective moisture diffusivity (Deff), and specific energy consumption (SEC) were analyzed. For microwave power and vacuum, the optimal conditions attained with aid of RSM and ANN were 260 W, 15.59 kPa, and 287 W, 19 kPa, respectively. The THT retention, ΔE, Tmax, Deff, SEC determined with RSM and ANN optimized values were 78.51 mg TAE/g of DW, 13.48, 67.02°C, 3.38 × 10−6 m2/s, 20.02 kWh/kg and 90.32 ± 0.35 mg TAE/g of DW, 12.488, 64.83°C, 5.64 × 10−6 m2/s, 20.01 ± 0.33 kWh/kg, respectively. The influence analysis explained that pomegranate peel dried at optimized ANN conditions of microwave power 287 W and vacuum 19 kPa possessed improved physicochemical properties and was efficient in terms of energy consumption compared to peel dried using RSM suggested conditions. Furthermore, the major criterion for evaluation between RSM and ANN tools in this study was the goodness of fit. The value for R2 produced via RSM varied between 0.8354 and 0.9870, whereas subsequent R2 in the case of ANN was considerably greater, varying between 0.9213 and 0.9956. The mean square error value displayed the minimum value in the case of ANN compared to the RSM model. These signified rather greater exactness and predictive capability of the ANN tool. Fourier transform infrared analysis established the existence of peaks between 3,308.92 and 908.89 cm−1 and high-performance liquid chromatography showed that pomegranate peel produced using microwave vacuum drying contains a good amount of gallic acid and tannic acid derivative compounds. Scanning electron microscopy elucidated that the combined microwave vacuum effect resulted in the formation of bigger pores on the peel surface ensuing in elevated extraction of THT at reduced energy consumption. Practical applications Shifting into a bio-economy is unrealistic with no proficient use of agricultural by-products and food waste. Microwave vacuum drying is a novel technique that would be applied to preserve the product bioactive components while drying. This study has established that drying of waste pomegranate peel using microwave vacuum dryer aided in excellent recovery rate of bioactive compounds particularly hydrolysable tannin (strong antioxidant and antimicrobial agent). This promises pomegranate peel powder obtained using microwave vacuum drying to be utilized in functional and nutraceutical food processing industries as a prospective resource of antimicrobial and antioxidant compounds. The findings also identified that the ANN-GA (artificial neural network–genetic algorithm) model would be effective for modeling the microwave vacuum drying method of pomegranate peel with preservation of peel quality. The optimal process values attained using coupled ANN-GA tool could be applied with respect to microwave vacuum-based industrial dryers to achieve the objective of drying at a considerably quicker rate.

Agricultural sorbents have received attention for their effectiveness in oil removal. In Malaysia, oil palm’s empty fruit bunch (EFB) spikelets are an abundant agricultural waste that provides a non-toxic, renewable resource of cellulosic materials. In this study, the effectiveness of EFB spikelets to remove oil spills from seawater pollution in a filter system was investigated and the best optimisation approach for filtering conditions was determined. Experiments for oil spill clean-up were performed using a filter-based oil sorption system with a series of conditions such as temperature, time, packing density, and oil concentration to evaluate sorption capacity, oil and water absorbed efficiency. Fourier transform infrared spectroscopy (FTIR) was used to characterise the physicochemical properties of untreated and treated EFB fibres. Based on one-factor-at -a-time (OFAT) analysis conducted at 160 °C for 30 min on 0.1 g/cm3 of packing density containing 25% diesel, 8.667 mL of oil and 5 mL of water was absorbed. In response surface methodology (RSM), the three parameters of temperature, packing density and diesel concentration were observed as significant. From RSM fitting model analysis, the predicted value obtained for both oil and water absorbed were 8.805 and 5.213 mL, respectively. The experimental RSM values of 9 and 5 mL of oil and water absorbed were obtained. The result demonstrated the validity of the model as the experimental RSM values were close to the RSM model’s prediction. As compared to OFAT, the RSM method is more efficient in oil removal. This research contributes to a better knowledge of the usage of a natural sorbent as a method of diesel pollution remediation.

Comparative study of flexural properties prediction of Washingtonia filifera rachis biochar bio-mortar by ANN and RSM models

In this research, the production of exo-pectinase by Bacillus pumilus using different agricultural wastes was studied. Agricultural wastes containing pectin such as wheat bran, sugar beet pulp, sunflower plate, orange peel, banana peel, apple pomace and grape pomace were tested as substrates, and activity of exo-pectinase was determined only in the mediums containing sugar beet pulp and wheat bran. Then, effects of parameters such as concentrations of solid substrate (wheat bran and sugar beet pulp) (A), ammonium sulphate (B) and yeast extract (C) on the production of exo-pectinase were investigated by response surface methodology. First, wheat bran was used as solid substrate, and it was determined that exo-pectinase activity increased when relatively low concentrations of ammonium sulphate (0.12-0.21% w/v) and yeast extract (0.12-0.3% w/v) and relatively high wheat bran (~5-6% w/v) were used. Then, exo-pectinase production was optimized by response surface methodology using sugar beet pulp as a solid substrate. In comparison to P values of the coefficients, values of not greater than 0.05 of A and B (2) showed that the effect of these process variables in exo-pectinase production was important and that changes done in these variables will alter the enzyme activity.

Potentials of algae-based activated carbon for the treatment of M.orange in wastewater

The research covered the entire process, from collecting the Areca nut leaves to purifying the produced bioethanol. Materials and Methods: The Areca nut leaves were pre-treated with sulfuric acid and sodium hydroxide, followed by enzymatic hydrolysis using cellulose enzymes. The hydrolyzed biomass was then fermented by Saccharomyces cerevisiae for 12–72 h to produce bioethanol. The produced bioethanol was purified through distillation using a rotary flask evaporator. To optimize the fermentation process and bioethanol production, the researchers employed two modeling approaches: Artificial neural networks (ANN) and response surface methodology (RSM). Variables such as pH, fermentation time, and disodium hydrogen phosphate (Na2HPO4) concentration, identified from the Plackett- Burman design, were optimized using the central composite design of RSM. Results and Discussion: The R² value for the RSM model was 91.72%, and the adjusted R² was 84.72%. In addition, an ANN algorithm model with 3 input neurons, 10 hidden layer neurons, and 1 output neuron was developed to investigate the relationship between bioethanol production and fermentation parameters. The ANN model achieved an R² of 99.78%, indicating higher accuracy and reliability compared to the RSM approach. The optimal conditions for bioethanol production were identified as pH 5.5, 60 h fermentation time, and 0.45 g of Na2HPO4. Under these conditions, the experimental bioethanol concentration reached 36.54 g/L. Conclusion: This study demonstrates the effective utilization of Areca nut leaves, a readily available agricultural waste, to produce bioethanol. The combination of statistical and machine learning techniques, such as ANN and RSM, allowed for the optimization of the fermentation process and the enhancement of bioethanol yield, showcasing the potential of this approach for sustainable biofuel production.

The use of relatively expensive and nonrenewable precursors such as natural coal is the main reasons for the high cost of commercial activated carbons. Agricultural wastes are considered as promising precursors for low cost and high surface area activated carbons due to their high volatile matter and lignocellulosic contents and their renewable natures. To recycle agricultural wastes and decrease activated carbon(AC) production cost, in this study, AC from sesame stalks were prepared by sodium hydroxide activation. Activation temperature, activation time and impregnation ratio (IR) were optimized by Response surface methodology (RSM) in AC preparation. Results showed that temperature at 640°C, time 1.45h and IR 1.93, methylene blue(MB) adsorption capacity and yield of AC reached 224.11 mg/g and 18.29%, respectively. Furthermore, surface characteristics of AC were studied using BET surface area analysis and scanning electron microscopy (SEM). Keywords-Sesame stalks; Activated carbon; Response surface methodology; Optimization

This study aimed to optimize the preparation condition of activated carbon using Teff straw as a precursor material via evaluating its potential in terms of maximizing the adsorptive removal of Reactive Yellow 145 dye (RY 145) from aqueous solutions. Selective factors, such as activation time, activation temperature, and impregnation ratio on the preparation of Teff Straw-based Activated Carbon (TSAC) were optimized using response surface methodology (RSM). A quadratic regression model with estimated coefficients was developed by RSM and it was observed that model predictions were matched with experimental value with an acceptable R2 value (0.98). Further, the TSAC prepared at optimal condition was characterized using Fourier-transform infrared (FTIR), Scanning electron microscopy (SEM), and X-ray diffraction (XRD) techniques. The TSAC prepared at optimal condition showed anionic nature with a BET surface area of 627.7 m2/g. In addition, important adsorptive parameters (contact time, solution pH, adsorbent dose, and dye concentration) were evaluated through batch experiments. In such a way, it was determined that 2 h for activation time, 539 °C for activation temperature, and impregnation ratio of 5 g of phosphoric acid per 1 g of TSAC were optimal for efficient adsorption with maximum removal of 98.53% for RY 145 dye. In addition, the TSAC was subjected to test in order to determine its adsorptive performance by treating real textile industry effluent for examining its Chemical Oxygen Demand (COD) removal potential. The results showed that 76% COD was removed from the real textile effluent, which met Ethiopian Environmental Protection Authority (EPA) standard. The finding of this paper asserts that this material is a good and low-cost bio-sorbent that can be used for the removal of pollutants from textile wastewater. Nevertheless, additional investigations of the adsorbents including regeneration options are advisable to draw explicit conclusions.

Oil pollution such as diesel poses a significant threat to the environment. Due to this, there is increasing interest in using natural materials mainly from agricultural waste as organic oil spill sorbents. Oil palm’s empty fruit bunch (EFB), a cost-effective material, non-toxic, renewable resource, and abundantly available in Malaysia, contains cellulosic materials that have been proven to show a good result in pollution treatment. This study evaluated the optimum screening part of EFB that efficiently absorbs oil and the physicochemical characterisation of untreated and treated EFB fibre using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM). The treatment conditions were optimised using one-factor-at-a-time (OFAT), which identified optimal treatment conditions of 170 °C, 20 min, 0.1 g/cm3, and 10% diesel, resulting in 23 mL of oil absorbed. The predicted model was highly significant in statistical Response Surface Methodology (RSM) and confirmed that all the parameters (temperature, time, packing density, and diesel concentration) significantly influenced the oil absorbed. The predicted values in RSM were 175 °C, 22.5 min, 0.095 g/cm3, and 10%, which resulted in 24 mL of oil absorbed. Using the experimental values generated by RSM, 175 °C, 22.5 min, 0.095 g/cm3, and 10%, the highest oil absorption achieved was 24.33 mL. This study provides further evidence, as the data suggested that RSM provided a better approach to obtain a high efficiency of oil absorbed.

Xanthan gum is one of the major commercial biopolymers. Due to its excellent rheological properties xanthan gum is used in many applications, mainly in food industry. Commercial production of xanthan gum uses glucose as the carbon substrate; consequently the price of xanthan production is high. One of the ways to decrease xanthan price, is using cheaper substrate like agricultural wastes. Iran is one of the biggest date producer countries. However approximately 50% of date production is wasted annually. The goal of this study is to produce xanthan gum from waste date using Xanthomonas campestris PTCC1473 by submerged fermentation. In this study the effect of three variables including phosphor and nitrogen amount and agitation rate in three levels using response surface methodology (RSM) has been studied. Results achieved from statistical analysis Design Expert 7.0.0 software showed that xanthan increased with increasing level of phosphor. Low level of nitrogen leaded to higher xanthan production. Xanthan amount, increasing agitation had positive influence. The statistical model identified the optimum conditions nitrogen amount=3.15g/l, phosphor amount=5.03 g/l and agitation=394.8 rpm for xanthan. To model validation, experiments in optimum conditions for xanthan gum were carried out. The mean of result for xanthan was 6.72±0.26. The result was closed to the predicted value by using RSM. Keywords—Optimization, RSM, Waste date, Xanthan gum, Xanthomonas Campestris

The agricultural waste sugarcane bagasse (SCB) is a kind of plentiful biomass resource. In this study, different pretreatment methods (NaOH, H2SO4, and sodium percarbonate/glycerol) were utilized and compared. Among the three pretreatment methods, NaOH pretreatment was the most optimal method. Response surface methodology (RSM) was utilized to optimize NaOH pretreatment conditions. After optimization by RSM, the solid yield and lignin removal were 54.60 and 82.30% under the treatment of 1% NaOH, a time of 60 min, and a solid-to-liquid ratio of 1:15, respectively. Then, the enzymolysis conditions of cellulase for NaOH-treated SCB were optimized by RSM. Under the optimal enzymatic hydrolysis conditions (an enzyme dose of 18 FPU/g, a time of 64 h, and a solid-to-liquid ratio of 1:30), the actual yield of reducing sugar in the enzyme-treated hydrolysate was 443.52 mg/g SCB with a cellulose conversion rate of 85.33%. A bacterium, namely, Bacillus sp. EtOH, which produced ethanol and Baijiu aroma substances, was isolated from the high-temperature Daqu of Danquan Baijiu in our previous study. At last, when the strain EtOH was cultured for 36 h in a fermentation medium (reducing sugar from cellulase-treated SCB hydrolysate, yeast extract, and peptone), ethanol concentration reached 2.769 g/L (0.353%, v/v). The sugar-to-ethanol and SCB-to-ethanol yields were 13.85 and 11.81% in this study, respectively. In brief, after NaOH pretreatment, 1 g of original SCB produced 0.5460 g of NaOH-treated SCB. Then, after the enzymatic hydrolysis, reducing sugar yield (443.52 mg/g SCB) was obtained. Our study provided a suitable method for bioethanol production from SCB, which achieved efficient resource utilization of agricultural waste SCB.

Polyphenols have gained significant attention in recent decades due to their protective role against cancer, diabetes, obesity, osteoporosis, neurodegenerative, and cardiovascular diseases. This study explored the influence of radiation time, microwave power, and sample-to-solvent ratio on the microwave-assisted extraction of polyphenols from Pithecellobium dulce fruit peels. Extraction efficiency, antioxidant activity, and anti-cholesterol activity were optimised using both response surface methodology (RSM) and artificial neural networks combined with a genetic algorithm (ANN-GA). The ANN-GA model exhibited higher predictive accuracy (R2 = 0.9805–0.9813) and lower statistical error compared to quadratic RSM models (R2 = 0.9566–0.9767). Under optimised conditions, ANN-GA yielded 244.35 mg/g total polyphenols, 92.51% antioxidant activity, and 73.96% anti-cholesterol activity, outperforming RSM (242.35 mg/g, 92.18%, and 73.26%, respectively). These findings demonstrate the scientific novelty of ANN-GA as a more robust and reliable tool than RSM for process optimisation. Moreover, the study highlights the practical application of utilizing P. dulce fruit peels as a low-cost, natural source of health-promoting bioactives. Importantly, this work presents a broader impact by providing a sustainable strategy for waste valorisation into nutraceutical and pharmaceutical products.

Optimal pretreatment of plantain peel waste valorization for biogas production: Insights into neural network modeling and kinetic analysis

Response surface methodology and artificial neural network-genetic algorithm for modeling and optimization of bioenergy production from biochar-improved anaerobic digestion