Urban vertical farming is an innovative solution to address the increasing demand for food in densely populated cities. With advanced technology and precise monitoring, closed urban vertical farms can optimize growing conditions for plants, resulting in higher yields and improved crop quality. However, to fully optimize closed urban vertical farming systems, research is needed to enhance crop yields and reduce the growing season. The present study is focused on the research of the mutual influence of microclimate parameters, such as temperature, humidity, and carbon dioxide concentration, as well as the spectral composition of light, humidity, and amount of peat in the substrate. The research was conducted within the cultivation of the “Innovator” potato variety at the experimental automated vertical farm of the “Fundamentals of Biotechnology” of the Russian Academy of Sciences. Based on the correlation and Fourier analysis of the dependences of soil moisture and carbon dioxide concentration on time, it is shown that after watering potatoes, there is a 56 h delayed decrease in the concentration of carbon dioxide in the cultivation room, which can be explained by a delayed increase in the intensity of the photosynthesis process. Moreover, a comparison of CO₂ dependence on time with the lighting dynamics at the scale of one day indicates the presence of the intrinsic daily biological rhythm of the CO₂ absorption rate that does not depend on the external lighting conditions. In addition, by analyzing the dependencies of microclimate parameters and the spectral composition of the lighting over time, it was found that switching on lighting influences the microclimate parameters, which can be explained by the heating of LEDs used for lighting. Moreover, the multiple regression analysis of microclimate parameters and soil moisture showed that an increase in peat content in the substrate leads to a transition from the decisive influence of air humidity on soil moisture to the dominant influence of air temperature. The obtained results reveal the complex mutual influence of the parameters determining the growing conditions within automated closed vertical farms. Consideration of this influence is necessary when optimizing the conditions of vegetation and the development of intelligent plant-growing systems.

The cultivation of aromatic plants that are valuable for nutritional and medical aims under artificial conditions with narrow-band LED lighting is becoming widespread. A comparison of the effects of conventional basil field and greenhouse conditions and a city farm (CF) with LED lighting on essential oil and its components was studied in Ocimum × citriodorum Vis. “Kapriz” (OcK), O. basilicum L. “Queen Sheba” (ObQS) and O. minimum L. “Vasilisk” (OmV). Essential oil (EO) was extracted by hydrodistillation from dry leaves of the basil varieties. EO composition was studied by gas chromatography, while the number of glandular trichomes was studied by scanning electron microscopy. We found that in leaves of CF plants, ObQS and OmV increased EO yield (22.9 and 22.7 g/kg DW, respectively) compared to field conditions (10.9 and 13.7 g/kg DW, respectively). The number of glands with four-celled heads also increased. In OcK plants, the amount of EO was almost unchanged, but the number of capitate glandular trichomes was strongly increased. Biochemical analysis showed that in CF plants compared to field ones, eugenol accumulated 40% more in ObQS and three times more in OmV. In addition, 10.9% estragol was detected in the leaves of OcK plants, which was absent in field plants. Thus, LED lighting conditions increased the biosynthesis of phenylpropanoid volatile components in Ocimum.

The implementation of advanced precision farming systems, which are becoming relevant due to rapid technological development, requires the invention of new approaches to the diagnostics and control of the growing process of cultivated crops. This is especially relevant for potato, as it is one of the most demanded crops in the world. In the present work, an analytic model of the dependence of potato tubers mass on carbon dioxide concentration under cultivation in a closed vegetation system is presented. The model is based on the quantitative description of starch molecule synthesis from carbon dioxide under photosynthesis. In the frame of this work, a comprehensive description of the proposed model is presented, and the verification of this model was conducted on the basis of experimental data from a closed urban vertical farm with automated climate control. The described model can serve as a basis for the non-contact non-invasive real-time measurement of potato tuber mass under growth in closed vegetation systems, such as vertical farms and greenhouses, as well as orbital and space crop production systems.