In this review, collected information related to Moringa Oleifera seeds was evaluated, such as their properties and the main active components involved in their processes, as well as their dual efficiency as both antimicrobials and natural coagulants for treating contaminated effluents. Furthermore, discussions were completed about perspectives on progress related to this field of research to understand the bioactive properties of these seed compounds, including their antibacterial, antifungal, and antiviral activity. In addition to the coagulant properties that have been quantitatively assessed, studies have examined the underlying coagulating mechanism, and seed processing techniques. In addition, the challenges associated with the use of conventional coagulants (metals or polymers) have led to numerous research efforts towards the development of natural plant-based coagulants that are eco-friendly to treat wastewater and offer a large variety of other advantages, such as their wide availability, the reduction of by-product generation, the reduction of costs, and greater biodegradability. Based on the results of different researchers, and regarding the appraisals using Moringa Oleifera seeds for wastewater treatment processes, many studies encourage their use for those operations. Due to their extensive and potent properties as an antibacterial and a coagulant, Moringa Oleifera seeds are still used today as a promising wastewater treatment method. Finally, this paper provides suggestions and comments, as well as identifies the knowledge gaps, and makes recommendations for future research development strategies, such as studying the contents of Moringa Oleifera seeds, their interactions with colloids present in wastewater, understanding their stability and behavior, assessing the performance of seed-derived flocculants according to pH values, isolating and characterizing the active compounds to determine the toxicity and optimum dose to be used as effective antimicrobials, and removing heavy metals.

Membrane fouling remains a major obstacle to the performance of the reverse osmosis (RO) desalination processes. Artificial intelligence (AI) is now a promising approach for the reliable modeling of these complex systems. This study evaluates three modeling techniques—multiple linear regression (MLR), artificial neural networks (ANNs), and support vector regression (SVR)—for predicting transmembrane pressure (TMP) at the Boujdour desalination plant, based on five input parameters: temperature, turbidity, pH, conductivity, and feedflow. The analysis is based on an original dataset of 195 daily measurements, and due to the absence of timestamps, the study focuses on state-to-TMP prediction rather than chronological forecasting, with no temporal generalization claimed. Approximately 2000 augmented training samples generated using a conservative SMOGN approach were used for model development, while performance evaluation relied exclusively on 39 independent real test observations. Two modeling strategies were adopted: (i) a minimalist approach based on significant variables identified by an ordinary least squares (OLS) model (pH and conductivity), and (ii) a multivariate approach integrating all parameters to capture non-linear interactions. A rigorous validation framework was put in place to avoid information leakage and ensure the robustness and generalizability of the models. Performance was evaluated using R², RMSE, and MAE metrics, supplemented by robustness and significance analyses including bootstrap confidence intervals, paired statistical comparisons, and interpretability analyses based on permutation importance, partial dependence plots (PDPs), and individual conditional expectation (ICE) curves. The results indicate that the SVR model achieves the best average predictive accuracy among the tested models, albeit with moderate explanatory power.

The aim of this work is to determine the effect of the extraction method on the yield, the chemical composition, and the antifungal activity of cedarwood essential oils (EOs) from sawdust of Moroccan Cedrus atlantica (C. atlantica). EOs were extracted by different methods: hydrodistillation, soxhlet, maceration, and ultrasound. The chemical composition was determined using gas chromatography mass spectrometry (GC-MS) analysis. The yields of EOs were 5.60%, 11.68%, 4.82% and 9.33% for hydrodistillation, soxhlet, maceration and ultrasound, respectively. GC-MS revealed a diversity of chemical compounds depending on extraction methods. Indeed, the main compound of EOs obtained by soxhlet, maceration, and ultrasound was copalic acid methyl ester by a rate of 28.41%, 20.24%, and 24.17%, respectively. However, -himachalene (21.32%) followed by -himachalene (9.40%), β-Copaen-4α-ol (7.71%) and longifolene (6.74%) are the main compounds of EO extracted by hydrodistillation. The antifungal activity of cedarwood EO was tested in vitro on two pathogenic fungi: Fusarium culmorum (F. Culmorum) and Botrytis cineria (B. Cinerea). The minimum inhibitory concentration (MIC) was determined by successive dilutions of the stock solutions. The extracted EOs by soxhlet, maceration and ultrasound showed the important inhibitory effect against B. cinerea (MIC=1.25 mL/L). However, F. culmorum showed resistance towards all tested EOs. The finding of this study showed clearly that the volatile composition of EOs can be variable according to extraction. methods. Moreover, antifungal effects are depending on chemical composition of EOs but also to tested staris.

The contamination of water systems by heavy metals, particularly hexavalent chromium (Cr(VI)), represents a major environmental and public health challenge. Chromium is extensively used in various industries, making its removal from wastewater crucial. This study investigates the potential of...