The integration of semi-transparent photovoltaics into the roof of greenhouses is an emerging technique used in recent years, due to the simultaneous energy and food production from the same piece of land. Although shading in many cases is a solution to maintain the desired microclimate, in the case of photovoltaic installations, the permanent shading of the crop is a challenge, due to the importance of light to the growth, morphogenesis, and other critical physiological processes. In this study, the effect of shade from semi-transparent photovoltaics on a strawberry crop (Fragaria x ananassa Duch.) was examined, in terms of growth and quality (phenolic and flavonoid concentration of fruits). According to the results, in non-shaded plants, there was a trend of larger plants, but without a significant change in leaf number, while the total number of flowers was slightly higher at the end of the cultivation period. Moreover, it was found that the percentage change between the number of ripe fruits was smaller than that of the corresponding change in fruit weight, implying the increased size of the fruits in non-shaded plants. Finally, regarding the antioxidant capacity, it was clearly demonstrated that shading increased the total phenolic content, as well as the free-radical-scavenging activity of the harvested fruits. Although the shading from the semi-transparent photovoltaics did not assist the production of large fruits, it did not affect their number and increased some of their quality characteristics. In addition, the advantageous impact of the semi-transparent photovoltaics in the energy part must not be neglected.

Radiation is a crucial factor in the field of agrivoltaics in greenhouses. Depending on the type of photovoltaics integrated into greenhouses, the effect on radiation varies through the phenomenon of shading. Shading in greenhouses can be either beneficial or detrimental, making its analysis imperative. In this study, the improvements and modifications made in an algorithm capable of calculating the shading from photovoltaic units installed in greenhouses are presented. A key modification to the algorithm is the calculation of shading from semi-transparent photovoltaic modules, in contrast to its original form, in which photovoltaic modules were considered opaque. The algorithm was validated using radiation data from pyranometers within a greenhouse. The coefficients used were Pearson's r correlation coefficient and the Coefficient of Variation. The correlation coefficients for times without shading effect approached the values for the case without photovoltaics installed on the roof. Simultaneously, based on the coefficients of variation, the uniformity of radiation within the shade was validated, thereby confirming its existence. Finally, the effect of semi-transparent photovoltaic units on Global Horizontal Irradiance and Photosynthetically Active Radiation was studied, with the reduction for the former approaching 52% and about 60% for the latter. These changes in radiation can be either beneficial or not, depending on the type of crop and the needs of the greenhouse, such as cooling.

In recent years, the global demand for medicinal plants has been rising steadily. This study focuses on cultivating Aloe vera within a large-scale, pilot smart greenhouse installed at the University of Patras, Greece. The integration of advanced Internet of Things (IoT) technologies, sensors, and the KYTION cablebot robotic device plays a crucial role in monitoring the cultivation process and deriving valuable insights. The greenhouse structure presented in this study not only recognizes these challenges but actively addresses them through state-of-the-art IoT technology-based measurements. Preliminary quantitative results indicate that cultivating A. vera in greenhouses significantly enhances blooming and production compared to open-field cultivation. This promising approach addresses the growing demand for A. vera specifically and medicinal plants in general. Additionally, it maximizes the use of available arable land, labor, water, and energy, ensuring stable production under unstable and variable climatic conditions. The study aims to control and automate the microclimate, optimizing conditions for A. vera growth within a controlled digital environment. By offering insights into the intersection of smart agricultural practices, technology-driven measurement and automation, and ad-hoc crop-specific cultivation strategies, this research provides a promising pathway for sustainably enhancing A. vera cultivation in controlled environments.

Several years have passed since the linear economy model proved unsustainable, leading to the transition toward the circular economy (CE) model. Significant amounts of agricultural residues and waste from livestock farming units remain unutilized in fields. The anaerobic digestion (AD) method addresses this issue by generating energy in the form of thermal (TE) and electrical energy (EE). This article examines greenhouse heating using thermal energy from a biogas plant. For this purpose, a thermal load model is developed and applied in two regions, northern (Florina) and central Greece (Trikala), to assess the greenhouse’s energy requirements in areas with differing characteristics, especially during the winter months. Additionally, the economic benefits of a biogas plant from selling electricity to the grid are analyzed. Thermal energy constitutes 59.7% of the system’s total energy output. On average, the generated electrical energy amounts to 518 MW h per month, while thermal energy reaches 770 MW h per month. The biogas plant’s daily electricity consumption ranges from 1564 kW h to 2173 kW h, depending on its needs. Ambient temperatures vary between 0 °C and 37 °C, significantly influencing the greenhouse heating system’s efficiency. The biogas plant also demonstrates financial profitability, earning 504,549 € annually from the sale of surplus electricity. Furthermore, the article explores greenhouse crops in the broader Thessaly region, where tomato cultivation seems to be dominant. Greenhouse heating requirements depend on crop type, location, weather conditions, sunlight exposure, and heat loss based on covering materials. Meanwhile, the thermal energy output that can heat a given greenhouse area is directly proportional to the biogas plant’s capacity.