Electronic nose (e-nose) and electronic tongue (e-tongue) are among the most modern olfactory and gustatory bionic systems that have been able to compensate for the limitations of the human olfactory and gustatory system. These bionic systems have been very successful in evaluating and measuring the quality of food. The enose is capable of evaluating the quality of food through the detection of volatile organic compounds (VOCs) and the e-tongue applies electrochemical methods to assess food quality. Unfortunately, nowadays food fraud is frequently practiced especially in spices that are offered in powdered form in the market. The purpose of this piece of research is thus to evaluate e-nose and e-tongue systems and use machine learning techniques to measure the authenticity and quality of ginger powder. In this study, chickpea powder was used as an adulterant to combine with ginger powder. Ginger powder and fraud samples were prepared in 7 classes (pure chickpea powder, pure ginger powder, 10%, 20%, 30%, 40% and 50% fraud in ginger powder using chickpea powder). Finally, the features extracted from the samples were evaluated and classified using basic CNN, improved CNN, PCA, MLP, Fuzzy, SVM, KNN, GBT and EDT algorithms. The results showed that the e-nose and e-tongue systems in combination with the improved CNN were able to classify the ginger powder and the fraud samples with accuracies of 95.24% and 100%, respectively. In the e-nose system, TGS2620, TGS822 and TGS2610 sensors, and in the e-tongue system, gold and platinum sensors had the strongest performance in detecting and distinguishing ginger powder and fraud samples.
The development of stable nanofluids (NFs) for enhanced oil recovery (EOR) relies on optimizing interactions between reservoir rocks and fluids. In this manuscript, a new hydrophilic nanocomposite (NC) of zinc oxide, titanium dioxide, cetyltrimethylammonium bromide (CTAB), and polydopamine was synthesized. The novelty of this work lies in the unique multicomponent design that leverages the synergistic action of polydopamine properties and CTAB surfactant functionality, creating a stable agent with dual functionality for superior EOR performance. The NCs structural and morphological properties were characterized using field emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD). Interfacial behaviour was quantified via contact angle (CA), and interfacial tension (IFT), and core flooding measurements. The results showed that a 70 ppm NC concentration achieved optimal performance, identified through a systematic experimental design. At this concentration, the NF exhibited a strongly negative zeta potential of approximately -50 mV, confirming excellent colloidal stability. It reduced the oil-water IFT from 22 to 1.98 mN/m and altered the contact angle on aged carbonate plates from 155 degrees (oil-wet) to 19 degrees (strongly water-wet). Core flooding tests showed a significant 35% increase in oil recovery over the low-salinity water flood baseline, recovering an additional 26% of the original oil in place (OOIP). Stability testing was also performed through zeta potential analysis. The NCs stability and dual functionality wettability alteration and IFT reduction are attributed to polydopamine properties and cetyltrimethylammonium bromides surfactant action at the oil/water interface. These results underscore the NCs potential as a scalable solution for nano-EOR, with broader applications in subsurface energy.
Synthesis of guanidine-functionalized and nickel-functionalized magnetic biochar nanoparticles (MBC-Guanidine-Ni) was done through a multi-step protocol, including pyrolysis, precipitation of Fe3O4, silane grafting, guanidine modification and coordination of nickel to magnetic biochar nanoparticles using olive kernel waste. The catalyst that was obtained had a nickel content of 4.14 wt.% (EDX) and saturation magnetization of 42.01 emu/g, making it possible to separate the catalyst within less than 20 s. Successful functionalization, high dispersion of nickel species and good thermal stability up to 300(degrees)C were determined by structural characterization (XRD, FT-IR, TEM, BET, XPS and TGA). A(3) model coupling (benzaldehyde, morpholine, phenylacetylene) reaction optimization studies indicated that in solvent-free conditions at 90(degrees)C with 15 mg catalyst, propargylamines were produced in a yield of up to 98% within 30-55 min. The catalyst was reused seven times, successively, with insignificant loss of activity (98-94%). Hot filtration and ICP-OES analysis showed very low nickel leaching (<0.5%). The combined activities of guanidine and nickel were necessary to achieve better catalytic activity, as demonstrated by control experiments verifying the dual-activation mechanism of synergy. The decrease in the E-factor relative to the former systems, the solvent-free protocol, and the biomass-based base is a factor in favor of better sustainability metrics and supports the system's environmental friendliness and cost savings.
Optimizing plant growth and stimulating the production of specialized metabolites, including essential oils, are key objectives for advancing agricultural productivity and meeting the growing demands of the pharmaceutical industry. Bioelicitors, particularly endophytic bacteria, offer a sustainable strategy to promote the accumulation of these bioactive compounds. This study aimed to isolate and characterize endophytic bacterial strains with the potential to enhance plant growth and increase the synthesis of targeted phytochemicals in Zataria multiflora Boiss. A completely randomized design (CRD) with three replications was used in two phases: a laboratory experiment to assess seedling responses and a greenhouse trial to evaluate morphophysiological and biochemical traits, essential oil content, and composition. Eight endophytic bacterial isolates were screened, and Agrobacterium sp. ER40 and Paenibacillus peoriae ER11 were the most effective in enhancing seedling growth parameters. Molecular identification using the NCBI database confirmed their identities. Greenhouse experiments significantly improved growth, physiology, and biochemical traits following inoculation. Agrobacterium sp. ER40 increased chlorophyll a (16.46
Accurate prediction of wheat grain yield (WGY) is vital for crop management and food security in arid regions. This study evaluates WGY prediction in the Dehloran Plain, western Iran, by integrating multi-source data: multi-temporal Sentinel-2 imagery, proximal Vis–NIR soil spectroscopy, and topographic attributes. A Random Forest (RF) model was developed with 135 field samples, comparing two scenarios: S1, using soil spectroscopy and remote sensing indices, and S2, which also included topographic variables. Results show that S2 significantly outperforms S1 (R² = 0.78, CCC = 0.79, nRMSE = 6.25
