With increasing demand for meat and dairy products, the volume of wastewater generated from the livestock industry has become a significant environmental concern. The treatment of livestock wastewater (LWW) is a challenging process that involves removing nutrients, organic matter, pathogens, and other pollutants from livestock manure and urine. In response to this challenge, researchers have developed and investigated different biological, physical, and chemical treatment technologies that perform better upon optimization. Optimization of LWW handling processes can help improve the efficacy and sustainability of treatment systems as well as minimize environmental impacts and associated costs. Response surface methodology (RSM) as an optimization approach can effectively optimize operational parameters that affect process performance. This review article summarizes the main steps of RSM, recent applications of RSM in LWW treatment, highlights the advantages and limitations of this technique, and provides recommendations for future research and practice, including its cost-effectiveness, accuracy, and ability to improve treatment efficiency.

Water contamination by pesticides is increasing dramatically due to population growth and the extensive use of pesticides in agriculture, leading to grave environmental and health concerns. Thus, efficient processes and the design and development of effective treatment technologies are required due to the enormous demand for fresh water. The adsorption approach has been widely used to remove organic contaminants such as pesticides because of its performance, less expense, high selectivity, and simplicity of operation compared to other treatment technologies. Among alternative adsorbents, biomaterials abundantly available for pesticide sorption from water resources have attracted the attention of researchers worldwide. The main objective of this review article is to (i) present studies on a wide range of raw or chemically modified biomaterials potentially effective in removing pesticides from aqueous media; (ii) indicating the effectiveness of biosorbents as green and low-cost materials for removing pesticides from wastewater; and (iii) furthermore, report the application of response surface methodology (RSM) for modeling and optimizing adsorption.

Pesticides are known to be threats to the environment and human health. Excessive use of pesticides in agricultural practice can contaminate water bodies, leading to cancer, asthma, neurological disorders, reproductive defects, and hormonal disruption. Electrochemical methods such as electrocoagulation and electrooxidation can be used for pesticide removal due to their numerous advantages such as high efficiency, less sludge production, and low operational cost. During electrocoagulation, dissolution of anode metals results in metal hydroxide complexes, which precipitate with the contaminant present in the reactor. Simultaneously, electro-flotation occurs at the cathode and results in the evolution of hydrogen gas bubbles, leading to flotation of floc to the top surface of the reactor. This review focuses on the removal mechanisms, kinetics, modeling, effects of influencing factors, and sludge characterization of pesticide removal using electrocoagulation and electrooxidation. Major influencing factors include cell configuration, electrode material, current density, pH, supporting electrolyte concentration. In general, aluminum and iron are the most common electrodes used for pesticide removal using electrocoagulation, while boron-doped diamond was used to a far greater extent as the electrode in electrooxidation studies. Greater than 99% removal efficiency was observed in both processes. Overall, this review summarizes the use of electrochemical methods for pesticide removal and offers valuable information to researchers in this area of study.

A large section of the human population relies on legumes as a staple food. Legumes are a rich source of nutrients and possess several health-related beneficial properties. However, the nutritional quality of legumes is challenged by the presence of a considerable amount of antinutrients. Consumption of inadequately processed legumes might affect normal metabolism and cause adverse human health-related effects. Effective processing becomes necessary to reduce these antinutritional factors before consumption. Optimizing the processing variables during preparation of legume-based traditional foods by using response surface methodology could be a valuable option to reduce antinutrients. The present review focuses on the efficacy of traditional household-scale processing unit operations vis-à-vis the reduction of antinutrients. Optimally prepared products should ensure meeting the consumer demand of improved, healthy, and more nutritious and safe foods. Modeling-based optimization approach will be helpful to define best practices at the small-, medium-, and large scale production alike. It should contribute towards effective utilization of legume resources, and to alleviate malnutrition and associated diseases world-wide.

Natural polysaccharides are well-known biomaterials because of their availability and low-cost, with applications in diverse fields. Cellulose, a renowned polysaccharide, can be obtained from different sources including plants, algae, and bacteria, but recently much attention has been paid to the microorganisms due to their potential of producing renewable compounds. In this regard, bacterial nanocellulose (BNC) is a novel type of nanocellulose material that is commercially synthesized mainly by Komagataeibacter spp. Characteristics such as purity, porosity, and remarkable mechanical properties made BNC a superior green biopolymer with applications in pharmacology, biomedicine, bioprocessing, and food. Genetic manipulation of BNC-producing strains and in situ modifications of the culturing conditions can lead to BNC with enhanced yield/productivity and properties. This review mainly highlights the role of genetic engineering of Komagataeibacter strains and co-culturing of bacterial strains with additives such as microorganisms and nanomaterials to synthesize BNC with improved functionality and productivity rate.

Concrete mix design and the determination of concrete performance are not merely engineering studies, but also mathematical and statistical endeavors. The study of concrete mechanical properties involves a myriad of factors, including, but not limited to, the amount of each constituent material and its proportion, the type and dosage of chemical additives, and the inclusion of different waste materials. The number of factors and combinations make it difficult, or outright impossible, to formulate an expression of concrete performance through sheer experimentation. Hence, design of experiment has become a part of studies, involving concrete with material addition or replacement. This paper reviewed common design of experimental methods, implemented by past studies, which looked into the analysis of concrete performance. Several analysis methods were employed to optimize data collection and data analysis, such as analysis of variance (ANOVA), regression, Taguchi method, Response Surface Methodology, and Artificial Neural Network. It can be concluded that the use of statistical analysis is helpful for concrete material research, and all the reviewed designs of experimental methods are helpful in simplifying the work and saving time, while providing accurate prediction of concrete mechanical performance.

Phenolic compounds from plant sources have significant health-promoting properties and are known to be an integral part of folk and herbal medicines. Consumption of phenolics is known to alleviate the risk of various lifestyle diseases including cancer, cardiovascular, diabetes, and Alzheimer\'s. In this context, numerous plant crops have been explored and characterized based on phenolic compounds for their use as supplements, nutraceutical, and pharmaceuticals. The present review highlights some important source of bioactive phenolic compounds and novel technologies for their efficient extraction. These techniques include the use of microwave, ultrasound, and supercritical methods. Besides, the review will also highlight the use of response surface methodology (RSM) as a statistical tool for optimizing the recoveries of the phenolic bioactives from plant-based matrices.

The sample extraction process is considered as the essential step in the pesticide residue analysis, as it provides the base for the detection of the pesticides in trace level. Various factors need to be optimized during the extraction of pesticides due to the complexity of the matrix which is time-consuming and tedious. Therefore, the use of experimental design in the optimization process proves to be effective with minimum experiments and cost. This paper is aimed to overview the experimental designs that are frequently used for screening (full factorial, fractional factorial, Plackett-Burman Design) and optimizing (central composite design, Box-Behnken design, Taguchi design, Doehlert design, D-optimal design) the most influential factors to provide a sequential understanding of the linear and complex interactions in the pesticide extraction methods. Further, a systematic approach has been discussed about the use of experimental designs in pesticide extraction and also the softwares used for application-oriented readers.

The production of high yields of soluble recombinant protein is one of the main objectives of protein biotechnology. Several factors, such as expression system, vector, host, media composition and induction conditions can influence recombinant protein yield. Identifying the most important factors for optimum protein expression may involve significant investment of time and considerable cost. To address this problem, statistical models such as Design of Experiments (DoE) have been used to optimise recombinant protein production. This review examines the application of DoE in the production of recombinant proteins in prokaryotic expression systems with specific emphasis on media composition and culture conditions. The review examines the most commonly used DoE screening and optimisation designs. It provides examples of DoE applied to optimisation of media and culture conditions.

Xylanases are hydrolytic enzymes which cleave the β-1, 4 backbone of the complex plant cell wall polysaccharide xylan. Xylan is the major hemicellulosic constituent found in soft and hard food. It is the next most abundant renewable polysaccharide after cellulose. Xylanases and associated debranching enzymes produced by a variety of microorganisms including bacteria, actinomycetes, yeast and fungi bring hydrolysis of hemicelluloses. Despite thorough knowledge of microbial xylanolytic systems, further studies are required to achieve a complete understanding of the mechanism of xylan degradation by xylanases produced by microorganisms and their promising use in pulp biobleaching. Cellulase-free xylanases are important in pulp biobleaching as alternatives to the use of toxic chlorinated compounds because of the environmental hazards and diseases caused by the release of the adsorbable organic halogens. In this review, we have focused on the studies of structural composition of xylan in plants, their classification, sources of xylanases, extremophilic xylanases, modes of fermentation for the production of xylanases, factors affecting xylanase production, statistical approaches such as Plackett Burman, Response Surface Methodology to enhance xylanase production, purification, characterization, molecular cloning and expression. Besides this, review has focused on the microbial enzyme complex involved in the complete breakdown of xylan and the studies on xylanase regulation and their potential industrial applications with special reference to pulp biobleaching, which is directly related to increasing pulp brightness and reduction in environmental pollution.