Biosorption as a method of biowaste valorization to feed additives: RSM optimization

WITHDRAWN: Unlimited possibilities to use Сladophora (Chlorophyta, Ulvophyceae, Cladophorales) biomass in agriculture and aquaculture with profit for the environment and humanity

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal). This article has been withdrawn at the request of the Publisher for legal reasons related to Elsevier's policy on Geographic Sanctions (https://www.elsevier.com/about/policies/trade-sanctions).

Using chemometric models to predict the biosorption of low levels of dysprosium by Euglena gracilis

The critical rare earth element dysprosium (Dy) is integral for sustainable technologies. What is concerning is that Dy is in imminent short supply and no current replacements yet exist, coupled with increasing environmental Dy levels influenced by anthropogenic activities. This study applies chemometric methods such as response surface methodology and artificial neural networks to predict low Dy removal levels using the biosorbent Euglena gracilis. A three-factor Box-Behnken experimental design was conducted with initial concentration (1 to 100 µg L^-1), contact time (30 to 180 min), and pH (3 to 8) as the three independent variables, and percentage removal and sorption capacity (q) as dependent variables. Using Dy percentage removal as response, for the worst and best conditions ranged from 0 to 92% respectively, with an average removal of 66 ± 4%. Using sorption capacity (q) as a different response variable, q varied from 0 to 93 µg/g with 27 ± 4 µg/g capacity as average. Maximum removal was 92% (q = 93 µg/g) was at pH 3, a contact time of 105 min and at a concentration of 100 µg/L. Using sorption capacity as the response variable for ANOVA, pH and metal concentrations were statistically significant factors, with lower pH and higher metal concentration having improved Dy removal, with a desirability near 1. Statistical tests such as analysis of variance, lack-of-fit, and coefficient of determination (R²) confirmed model validity. A 3-10-1 ANN network array was used to model experimental responses (q). RSM and ANN effectively modeled Dy biosorption. E. gracilis proved to be a cheap and effective biosorbent for Dy biosorption and has the potential to remediate acid mine drainage areas exhibiting low Dy concentrations.

Recovery of Citric Acid from Citrus Peels: Ultrasound-Assisted Extraction Optimized by Response Surface Methodology

The production of citrus juice generates a large quantity of by-products, which are often discarded or used for animal feed. However, several studies have shown its richness in valuable compounds, namely organic acids. Thus, this work intended to valorize orange and lime peels as renewable sources of citric acid. An experimental design combining five levels of the independent variables time (2–45 min), ultrasonic power (50–500 W), and ethanol proportion (0–100%) was implemented and response surface methodology (RSM) was applied to optimize the extraction process. The UPLC-PDA analysis showed that orange peel presented a higher citric acid content than lime. For lime and orange peels, the extraction yield was maximized by sonicating at low power for 5.8 or 35.5 min, using a low ethanol proportion or only water as a solvent, respectively. Overall, optimal UAE conditions were defined for the sustainable extraction of citric acid from citrus by-products, thus contributing to its valorization and upcycling into natural food ingredients.

A generic input-output approach in developing and optimizing an Aspen plus steam-gasification model for biomass

Steam-gasification is drawing great interests as it yields higher H₂ in syngas than any other gasification process. In this article, an equilibrium steam-gasification model developed in Aspen plus has been presented. The effect of the major input variables along with their synchronized effects on the response variables i.e., cold gas efficiency (CGE) and lower heating value (LHV) have been performed. Steam-gasification process optimization has been carried out employing response surface methodology (RSM) considering wide variety of biomass to get the best possible outcomes. The generic relations for both CGE and LHV as response variables have also been framed from obtained individual relations to estimate the response variables for considered biomass feeds at optimum operating conditions. The analysis reveals that the optimum response is obtained having almost 100% desirability (D) at the optimum operating condition (steam to biomass ratio of 0.7 and gasification temperature between 780 and 790 °C) of the steam-gasification model.

Aflatoxin Detoxification Using Microorganisms and Enzymes

Mycotoxin contamination causes significant economic loss to food and feed industries and seriously threatens human health. Aflatoxins (AFs) are one of the most harmful mycotoxins, which are produced by Aspergillus flavus, Aspergillus parasiticus, and other fungi that are commonly found in the production and preservation of grain and feed. AFs can cause harm to animal and human health due to their toxic (carcinogenic, teratogenic, and mutagenic) effects. How to remove AF has become a major problem: biological methods cause no contamination, have high specificity, and work at high temperature, affording environmental protection. In the present research, microorganisms with detoxification effects researched in recent years are reviewed, the detoxification mechanism of microbes on AFs, the safety of degrading enzymes and reaction products formed in the degradation process, and the application of microorganisms as detoxification strategies for AFs were investigated. One of the main aims of the work is to provide a reliable reference strategy for biological detoxification of AFs.