In the present research work, the use of agro-industrial waste such as agave bagasse from the tequila industry was carried out. The agave bagasse was treated to obtain biosorbent and hydrochar materials. Direct Blue 86 was used as an adsorbate model to evaluate the performance of both materials. The adsorption studies showed an adsorption capacity of 6.49 mg g⁻¹ in static and 17.7 mg g⁻¹ in dynamic, associated with a physisorption process between functional groups of the material and the dye. The characterization of the biosorbent showed that the material was mainly composed of macroporous fibers with a surface area <5.0 m² g⁻¹. Elemental analysis showed a majority composition of C (57.19 wt%) and O (37.49 wt%). FTIR and XPS analyses showed that the material had C-O, C=O, -OH, O-C=O, and -NH₂ surface groups. RAMAN and TGA were used to evaluate the composition, being cellulose (40.94%), lignin (20.15%), and hemicellulose (3.35%). Finally, the life-cycle assessment at a laboratory scale showed that the proposed biosorbent presents a 17% reduction in several environmental aspects compared to hydrochar, showing promise as an eco-friendly and highly efficient method for the remediation of water contaminated with dye, as well as being a promising alternative for the responsible management of solid waste generated by the tequila industry.

In the present research work, an algorithm of artificial neural network (ANN) has been developed based on the processing of digital images of Persian lemons with the aim of optimizing the quality control of the product. For this purpose, the physical properties (weight, thickness of the peel, diameter, length, and color) of 90 lemons selected from the company Esperanza de San José Ornelas SPR de RL (Jalisco, Mexico) were studied, which were divided into three groups (Category “extra”, Category I, and Category II) according to their characteristics. The parameters of weight (26.50 ± 3.00 g), diameter/length (0.92 ± 0.08) and thickness of the peel (1.50 ± 0.29 mm) did not present significant differences between groups. On the other hand, the color (determined by the RGB and HSV models) presents statistically significant changes between groups. Due to the above, the proposed ANN correctly classifies 96.60% of the data obtained for each of the groups studied. Once the ANN was trained, its application was tested in an automatic classification process. For this purpose, a prototype based on the operation of a stepper motor was simulated using Simulink from Matlab, which is connected to three ideal switches powered by three variable pulse generators that receive the information from an ANN and provide the corresponding signal for the motor to turn to a specific position. Manual classification is a process that requires expert personnel and is prone to human error. The scientific development presented shows an alternative for the automation of the process using low-cost computational tools as a potential alternative.

The maturation of distilled spirits in wooden barrels is a critical process that defines the sensory profile and quality of the final product, primarily through the release of polyphenols and flavonoids. In this study, the early extraction kinetics of these compounds in agave distillates were investigated using laboratory-scale barrels (5 L) with three toasting levels: light (185 °C/60 s), medium (210 °C/90 s), and intense (235 °C/120 s). The barrels were characterized by FTIR and Raman spectroscopy (SEM), as well as Scanning Electron Microscopy to correlate the chemical structure of the wood with the release of phenolic compounds. For this purpose, the Electrochemical Color Index (ECI), representative of polyphenols and flavonoids, was monitored daily for over 60 days. Results showed no statistically significant differences (p > 0.05) among the toasting levels. On the other hand, the observed kinetics exhibited four characteristic phases: (i) a linear increase during the first week due to the extraction of the most exposed compounds, (ii) a partial decrease in the second week associated with the re-adsorption of extracted compounds onto active sites remaining available on the barrel surface, (iii) a pseudo-steady state up to day 60, and finally, (iv) a subsequent linear increase. These findings provide scientific evidence supporting the official standards for the classification of aged distillates, since at least 60 days are required to condition the barrel surface to achieve a balanced extraction of polyphenols and flavonoids. The results highlight ECI as a robust and sensitive tool for monitoring the early maturation of agave distillates. Furthermore, the proposed approach not only offers complementary analytical criteria but also contributes to supporting the regulatory definitions of the reposado category, providing a practical framework for process standardization.

The contamination of water with toxic metals, such as copper, poses significant environmental and public health challenges, necessitating sustainable treatment solutions. This study investigates the phytoremediation potential of Epipremnum aureum for the removal of Cu(II) from aqueous solutions under both static and dynamic conditions. Batch experiments were conducted using initial copper concentrations of 5, 10, 15, and 20 mg L⁻¹, while a prototype vertical flow system (“green wall”) was implemented for continuous flow studies at 10 mg L⁻¹. Copper removal efficiency, plant morphology, and kinetic behavior were monitored over four weeks. ATR-FTIR, SEM-EDX, and X-ray diffraction analyses were performed to elucidate the sorption mechanism. Results demonstrated that E. aureum tolerates copper concentrations up to 10 mg L⁻¹ without significant morphological damage, achieving up to 70% removal in continuous flow, with sorption occurring via a combination of surface adsorption to oxygenated functional groups and intracellular absorption. At higher concentrations (≥15 mg L⁻¹), plants exhibited severe stress and necrosis, limiting their remediation capacity. The findings indicate that E. aureum is effective for moderate copper contamination and provide mechanistic insights into its metal uptake processes, highlighting its suitability for integration into sustainable water treatment systems. This work contributes to the development of eco-friendly, plant-based strategies for toxic metal remediation, supporting advances in chemical and hybrid technologies for safe water management.

To obtain fundamental information on the Tequila 100% agave Cristalino commercial samples were characterized in their different classes. For this purpose, 12 samples were chosen, defined as: G1 (aged; n = 3, or extra-aged; n = 3) and G2 (aged-Cristalino; n = 3 or extra-aged-Cristalino; n = 3). Analytical characterization was performed on these beverages, consisting of isotope ratio mass spectrometry, gas and liquid chromatography, UV-Vis spectroscopy, and color using digital image processing. The results corroborate that the chromatographic characterization (mg/100 mL A.A.)—higher alcohols (299.53 ± 46.56), methanol (212.02 ± 32.28), esters (26.02 ± 4.60), aldehydes (8.93 ± 4.61), and furfural (1.02 ± 0.56)—and isotopic characterization—δ¹³C_VPDB = −13.02 ± 0.35 ‰ and δ¹⁸O_VSMOW = 21.31 ± 1.33 ‰—do not present statistically significant differences (p > 0.05) between groups. From these techniques, it was possible to reinforce that isotopic ratios can provide information about that the ethanol of these alcoholic beverages come from Agave tequilana Weber blue variety and it is not affected in the filtration process. Based on the UV-Vis analysis, I₂₈₀ and I₃₆₅ were obtained, which were related to the presence of polyphenols and flavonoids—expressed as mg quercetin equivalents/L—only found in group 1. Due to the presence of flavonoids in aged beverages, the oxidation process results in the formation of an amber color, which can be measured by an RGB color model; therefore, the analysis shows that there is a statistically significant difference (p < 0.05) between groups. It can be concluded that Tequila 100% agave Cristalino is a Tequila 100% agave aged or extra-aged without color in which its chromatographic and isotopic profile is not affected.

The Santiago River near the Guadalajara Metropolitan Area is one of the most contaminated water bodies in Mexico, where heavy metals pose a major threat to aquatic ecosystems. Chronic metal pollution has promoted the adaptation of native microbial communities, including the production of metal-chelating metabolites such as siderophores, which represent a valuable resource for remediation-oriented biomaterials. In this study, bacterial strains were isolated from water and sediment samples, then screened for siderophore production using the Chrome Azurol S assay (CAS), complemented by a MATLAB-based image processing approach for semi-quantitative ranking prior to taxonomic identification by MALDI-TOF MS. Based on biosafety considerations and cultivation robustness, Bacillus thuringiensis was selected as a benchmark case, being immobilized onto activated carbon to produce a carbon–bacteria biocomposite (CBM). To evaluate the performance of CBM, Cu(II) was used as a model contaminant due to its industrial relevance, persistence, toxicity, and strong complexation behavior. Batch adsorption experiments showed that the CBM exhibited a 23.9% higher maximum Cu(II) sorption capacity than pristine activated carbon. Acute toxicity assays using Vibrio fischeri further indicated reduced toxicity in CBM-treated effluents, supporting the feasibility of this contained biocomposite for heavy metal remediation.