Lighting conditions are an important controller of plant growth and development, and they affect secondary metabolite synthesis. In this research, we explored the effect of additional UV irradiation of various ranges in addition to the main one at PPFD 160 µmol m⁻² s⁻¹ on the accumulation of some secondary metabolites of stevia (Stevia rebaudiana Bertoni). The fresh weight of leaves was slightly higher under additional UV-A and UV-B irradiation compared with the control variant, and the leaf surface area was significantly larger, respectively, by 23.3 and 20.7% than in the control variant, while the rate of photosynthesis did not decrease. Plants under additional UV-B and UV-C irradiation were under the greatest light stress, as evidenced by a decrease in antioxidant capacity by an average of 30% compared to the control and UV-A. The total flavonoid content was significantly higher (by 74%) under UV-B irradiation. The highest concentration of steviol glycoside was observed during budding and flowering under UV-B and UV-C irradiation (by 13.2 and 11.3%, respectively). Analysis of hyperspectral images, chlorophyll fluorescence, and vegetation indices showed light stress increasing under UV-C irradiation, which caused an increase in the relative chlorophyll content, scorches, leaf morphology changes, a CO₂ absorption rate decrease, and plant growth inhibition. UV-B irradiation can be used as an optimal type of irradiation based on a set of indicators.

This research is aimed at the assessing the impact of the ultraviolet radiation in the A, B, and C ranges (as additives to the main light) on general plan condition, the stress experienced by them, the pigment concentration in the leaves and leaf reflective characteristics. Under studying, there were the photo-protective reactions of the purple variety basil plants. The plants were grown in plastic pots in a phyto-chamber equipped with an automatic microclimate system. The phyto-chamber was divided into four compartments where, in addition to the main lighting, there were installed the additional LEDs emitting their radiation in the ranges UV-A, UV-B, and UV-C. Plant reactions were evaluated by the contents of the main pigments as detected by the spectrometric method. Then correlations were revealed between those values and the vegetative indices obtained based on the hyperspectral images. A strong correlation (R² ˃ 0.83) was observed between the values of the vegetative indices ARI and mARI and the anthocyanins concentration in basil leaves. A weak correlation (R² = 0.0479) was found between the ARI and mARI values and the carotenoids index CRI700, which is attributed to the shielding effect of the anthocyanins. Deviations in the results are influenced by leaf surface unevenness, its thickness and density. Additional research is needed including developing reflection indices taking into account the shielding effect of the purple pigments.

The present study has been carried out to determine the effects of four different illuminators with red, far-red, blue, and white light-emitting diodes (LEDs) on the growth, morphology, pigment composition, and chlorophyll fluorescence of spinach (Spinacia oleracea L.) of the ‘Zhirnolistny’ cultivar. We investigated these variants in two photon flux densities, 400–800 nm (PFD) 120 µmol m⁻² s⁻¹ and 180 µmol m⁻² s⁻¹. The studies were carried out in a climate chamber. Plant measurements were carried out on the 30th and 45th days of cultivation. The results showed that during the period of active growth, on the 30th day, spinach plants accumulated 2.6 and 2.4 times more fresh weight in the variant with a higher PFD (180 µmol m⁻² s⁻¹). At the end of the growing season, only a decrease in PFD had an effect on the fresh and dry weight of plants. The highest concentration of chlorophyll on both the 30th and 45th days of vegetation was found when spinach plants were grown under red-blue (RB) LEDs in a spectrum proportion of R70:B30. It was found that the variants had a higher proportion of green radiation in the spectrum of illuminators with PFD 180 µmol m⁻² s⁻¹, and the nitrate content in spinach was slightly lower than in other variants.

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.

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.