The paper considers the operation of an LED lighting system with a parallel power supply from photovoltaic modules and a power grid. Such systems are supposed to be widely applicable in premises with limited natural lighting, particularly agrosystems where artificial light of a certain spectrum is specifically required to ensure efficient plant growth. The paper presents the scheme of the developed LED lighting system, as well as an assembled prototype containing a single 36-watt lamp. The data of the experimental study are provided on the developed LED lighting system using the developed monitoring system. The experimental study demonstrates an efficient power take-off and the reliability of the proposed scheme to competently select the characteristics and circuit solutions for the converter of voltage from the PV module. The proposed LED system allows simplification of the PV system by eliminating circuits with an inverter and storage devices, hence significantly reducing the cost of the photovoltaic systems. Likewise, such a simplicity has a positive effect on PV system reliability, which benefits the cost as well.

When growing plants in artificial conditions, it is important to control the lighting parameters, both natural and artificial. This study explored the feasibility of creating a low-cost portable spectroradiometer for assessing the light environment in crop production. The multi-channel spectrometer sensors AS7341 and AS7263 and the ESP32 module were selected for this task. An analysis of the problem was conducted, and ways to solve it were identified. Machine learning methods (linear regression and decision trees) were used to determine the light source type, recover the spectrum from sensor readings at individual wavelengths, and estimate the photon flux density. The obtained results were evaluated using the MAE, MRPE, and R² metrics, resulting in MRPE up to 10% for photon flux higher than 50 µmol m⁻² s⁻¹, MAE up to 10 µmol m⁻² s⁻¹ for less intensities, R² of at least 0.96 for almost all cases. It is shown that the developed algorithm achieves acceptable accuracy on various light sources, including those not used during the training process. The research results will be useful in the development of low-cost spectroradiometers for measuring illumination in crop production.

Modern agriculture, with the use of artificial lighting, requires high-intensity LED luminaires with compact dimensions. In this regard, new approaches to the design of LED luminaires using both new materials and technical solutions have been considered. The theoretical evaluation of the influence of different materials on the efficiency of removal of thermal energy from LEDs was shown. A new material PMS-5 is proposed and evaluated as an immersion liquid, which can be used as an effective heat sink in the lower part of the luminaire up to the level of LEDs located in the top light LED luminaires. The proposed polymethylsiloxane PMS-5 liquid has more than twice the thermal conductivity (0.167 W/(m·K)) of HFE7200 and NS15 liquids used in immersion-cooled LED luminaires. Based on the theoretical evaluation, the requirements for parameters, such as metal profile area, immersion liquid volume, wall thickness area, and external area of the cylinder, are highlighted and shown. The noted parameters have a key role in the design of an efficient top light LED luminaire. It has been shown that the design of the metal profile significantly affects the efficiency of the removal of thermal energy from LEDs and it is necessary to use specialized profiles optimized for the diameter of the LED luminaire cylinder. A number of LED luminaire designs were proposed, depending on the thermal properties of the construction materials, technical and economic performance, as well as actual operating and installation conditions. The analysis of the presented theoretical evaluations allowed overlay of the design basis of LED luminaires within the presented concept and top light.

Stevia (Stevia rebaudiana Bertoni) is an important source of natural sweeteners. Since its commercial value depends on steviol glycosides, quality assessment primarily involves quantifying these compounds in leaves and shoots. While chromatography is the standard analytical method, it is labor-intensive and time-consuming; it involves multiple processing steps that may cumulatively introduce errors and remains relatively expensive. Although chromatography remains the most accurate method, this exploratory study evaluates the potential of using spectroscopy as an auxiliary method for the approximate assessment of steviol glycoside content. Leaf reflectance spectroscopy could be a simpler and more cost-effective approach. However, relationships between leaf reflectance and steviol glycoside content are indirect and mediated by physiological processes. To account for these indirect dependencies, cumulative UVB exposure was included as an additional feature because it influences both leaf optical properties and plant metabolic processes. A low-cost spectrometer was utilized as the measuring instrument. The study was conducted over a period of three months on 77 S. rebaudiana clones, divided into four groups based on their level of UVB irradiance (control without irradiation, 400, 600, and 800 μW m⁻²). Based on the collected data, linear and polynomial regression, Random Forest, XGBoost, PLSR, and ElasticNetCV models were trained. Cumulative UVB exposure was found to be the most important feature. Of the spectral features, the most informative for assessing the content of steviol glycosides were spectral indicators in the far-red and near-infrared (NIR) ranges. Our results indicate a detectable relationship, with Random Forest being the best-performing model and achieving a moderate predictive performance (R² = 0.66). Despite their limited predictive performance, the models demonstrate that leaf reflectance spectra combined with cumulative UVB exposure contain information related to steviol glycoside content. These findings support further investigation of remote sensing approaches for crop quality assessment.