Sustainable agriculture faces major issues with resource efficiency, nutrient distribution, and plant health. Traditional soil-based and soilless farming systems encounter issues including excessive water use, insufficient nutrient uptake, nitrogen deficiency, and restricted plant development. According to the previous literature, aeroponic systems accelerate plant growth rates, improve root oxygenation, and significantly enhance water use efficiency, particularly when paired with both low- and high-pressure misting systems. However, despite these advantages, they also present certain challenges. A major drawback is the inefficiency of nitrogen fixation, resulting in insufficient nutrient availability and heightened plant stress from uncontrolled misting, which ultimately reduces yield. Many studies have investigated plasma uses in both soil-based and soilless plant cultures; nevertheless, however, its function in aeroponics remains unexplored. Therefore, the present work aims to thoroughly investigate and review the integration of plasma-activated water (PAW) and plasma-activated mist (PAM) in aeroponics systems to solve important problems. A review of the current literature discloses that PAW and PAM expand nitrogen fixation, promote nutrient efficiency, and modulate microbial populations, resulting in elevated crop yields and enhanced plant health, akin to soil-based and other soilless systems. Reactive oxygen and nitrogen species (RONS) produced by plasma treatments improve nutrient bioavailability, root development, and microbial equilibrium, alleviating critical challenges in aeroponics, especially within fine-mist settings. This review further examines artificial intelligence (AI) and the Internet of Things (IoT) in aeroponics. Models driven by AI enable the accurate regulation of fertilizer concentrations, misting cycles, temperature, and humidity, as well as real-time monitoring and predictive analytics. IoT-enabled smart farming systems employ sensors for continuous nutrient monitoring and gas detection (e.g., NO₂, O₃, NH₃), providing automated modifications to enhance aeroponic efficiency. Based on a brief review of the current literature, this study concludes that the future integration of plasma technology with AI and IoT may address the limitations of aeroponics. The integration of plasma technology with intelligent misting and data-driven control systems can enhance aeroponic systems for sustainable and efficient agricultural production. This research supports the existing body of research that advocates for plasma-based innovations and intelligent agricultural solutions in precision farming.

This study reports the development of an impedimetric sensor for the selective detection of sodium lactate using platinum interdigital electrodes functionalized with a lactate-specific ssDNA aptamer. Designed to overcome the limitations of enzyme-based biosensors, the sensor offers improved stability, reusability, and specificity. The device capacitance increased monotonously as a function of lactate concentration from 100 nM–800 nM with 4.6 pF/nM sensitivity measured at 15 kHz. Atomic force microscope imaging showed lower surface roughness of lactate on aptamer (∼45 nm) compared with glucose (560 nM) and dopamine (890 nM), indicating a higher affinity of the aptamer to bind with sodium lactate that results in a smoother surface.

Atmospheric-pressure plasma optical emission spectroscopy (OES) is a promising technique for rapid, and label-free characterization of particulate materials because of its ability to generate material-dependent optical emission signatures under ambient conditions. In this work, an enhanced plasma-induced ionization fluorescence spectroscopy (PIFS) platform based on an open atmospheric-pressure discharge configuration is presented for the characterization of representative organic and inorganic particulate materials. The PIFS system uses two porous nickel electrodes separated by a dielectric (glass) spacer to generate a stable DC plasma discharge while simultaneously providing a large effective discharge nanotextured surface for plasma-particle interactions. Unlike our previously reported PIFS platforms, the porous-electrode architecture enhances plasma stability and promotes localized electrostatic particle accumulation, thereby improving plasma-particle interactions and measurement reproducibility. Optical emission generated during particle excitation was collected using a fiber-optic probe coupled to an Ocean Insight QE Pro spectrometer with approximately 1 nm spectral resolution. Representative organic materials, consisting of bee pollen, cellulose, and lactate, together with inorganic materials such as rust particles (iron oxide), sodium chloride, and blowing dust, were investigated at particle loadings of 1, 3, and 6 mg. The measured spectra revealed distinct emission fingerprints over the visible and near-infrared spectral regions. Bee pollen and iron oxide showed the largest spectral modifications, whereas cellulose, sodium chloride, and blowing dust produced comparatively smaller perturbations of the plasma emission profile. Quantitative comparison of characteristic emission wavelengths at 590, 660, 775, and 950 nm further indicated that each material possesses a unique normalized intensity distribution suitable for spectral discrimination. Analysis of the influence of particle loading showed increasing emission intensity for bee pollen, relatively stable responses for cellulose, lactate, and sodium chloride, and a decreasing response for blowing dust, due to particle deposition, optical attenuation and insulation of electrode surfaces. The proposed experimental platform provides a simple, reproducible, and cost-effective approach for plasma-based particulate characterization and demonstrates considerable potential for environmental monitoring, aerosol identification, and industrial process diagnostics.