Vertical farming has emerged as a promising solution to cope with increasing food demand, urbanization pressure, and limited resources and to ensure sustainable year-round urban agriculture. The aim of this review was to investigate the evolving technological landscape and engineering considerations, with a focus on innovative developments and future prospects. This paper presents technological trends in vertical farming, covering advances in sensing technologies, monitoring and control systems, and unmanned systems. It also highlights the growing role of artificial intelligence (AI) in contributing to data-driven decision-making and the optimization of vertical farms. A global perspective on vertical farming is presented, including the current status and advanced technological trends across regions like Asia, the USA, and Europe. Innovative concepts and upcoming enterprises that could shape the future of vertical agriculture are explored. Additionally, the challenges and future prospects of vertical farming are also addressed, focusing on crop production limitations, environmental sustainability, economic feasibility, and contributions to global food security. This review provides guidance on the state of vertical farming, technological advancements, global trends, challenges, and prospects, offering insights into the roles of researchers, practitioners, and policymakers in advancing sustainable vertical agriculture and food security.

The growth of plants and their glucosinolate content largely depend on the cultivation environment; however, there are limited reports on the optimization of ambient environmental factors for kale grown in plant factories. This study was conducted to investigate the effects of temperature, relative humidity, and the carbon dioxide (CO₂) concentration on kale growth and glucosinolate content in different growth stages of cultivation in a plant factory. Kale was grown under different temperatures (14, 17, 20, 23, and 26 °C), relative humidities (45, 55, 65, 75, and 85%), and CO₂ concentrations (400, 700, 1000, 1300, and 1600 ppm) in a plant factory. Two and four weeks after transplantation, leaf samples were collected to evaluate the physical growth and glucosinolate contents. The statistical significance of the treatment effects was determined by two-way analysis of variance, and Duncan’s multiple range test was used to compare the means. A correlation matrix was constructed to show possible linear trends among the dependent variables. The observed optimal temperature, relative humidity, and CO₂ range for growth (20–23 °C, 85%, and 700–1000 ppm) and total glucosinolate content (14–17 °C, 55–75%, and 1300–1600 ppm) were different. Furthermore, the glucosinolate content in kale decreased with the increase of temperature and relative humidity levels, and increased with the increase of CO₂ concentration. Most of the physical growth variables showed strong positive correlations with each other but negative correlations with glucosinolate components. The findings of this study could be used by growers to maintain optimum environmental conditions for the better growth and production of glucosinolate-rich kale leaves in protected cultivation facilities.

Pepper is one of the most vital agricultural products with high economic value, and pepper production needs to satisfy the growing worldwide population by introducing automatic seedling transplantation techniques. Optimal design and dimensioning of picking device components for an automatic pepper transplanter are crucial for efficient and effective seedling transplantation. Therefore, kinematic analysis, virtual model simulation, and validation testing of a prototype were conducted to propose a best-suited dimension for a clamp-type picking device. The proposed picking device mainly consisted of a manipulator with five grippers and a picking stand. To analyze the influence of design variables through kinematic analysis, 250- to 500-mm length combinations were considered to meet the trajectory requirements and suit the picking workspace. Virtual model simulation and high-speed photography tests were conducted to obtain the kinematic characteristics of the picking device. According to the kinematic analysis, a 350-mm picking stand and a 380-mm manipulator were selected within the range of the considered combinations. The maximum velocity and acceleration of the grippers were recorded as 1.1, 2.2 m/s and 1.3, 23.7 m/s², along the x- and y-axes, respectively, for 30 to 90 rpm operating conditions. A suitable picking device dimension was identified and validated based on the suitability of the picking device working trajectory, velocity, and acceleration of the grippers, and no significant difference (p ≤ 0.05) occurred between the simulation and validation tests. This study indicated that the picking device under development would increase the pepper seedling picking accuracy and motion safety by reducing the operational time, gripper velocity, acceleration, and mechanical damage.

The exposure of tomato fruits to unfavorable environments during the postharvest could result in severe losses along the supply chain. In this research, four tomato cultivars were stored in a controlled chamber under three levels of postharvest conditions to investigate the effects of delayed cooling on selected physicochemical quality parameters of the tomatoes. The tomato cultivars were subjected to three postharvest treatments: Immediate storage (IS) at harvest day; delayed storage (DS), leaving tomatoes without cover for one day; and under cover (DSC), separately in a greenhouse, and then stored in a controlled chamber at a temperature of 10 ± 1 °C and relative humidity of 90% ± 3%. Fresh weight, firmness, total soluble solids (TSS), and hue angle (h°) were examined over 15 days, every 5 days. Among the tomato cultivars, Cherry (7160), treated under DS showed the highest weight loss (13.01%) and firmness loss (42.14%) after 15 days of storage. Dabol (large) tomatoes treated with DS showed higher changes in TSS (°Bx) values (4.79 to 5.76). Low changes in hue angle values were found in IS-treated Cherry (7160) tomatoes at the end of the storage period. Overall quality changes were slower for all tomato cultivars treated with IS than with other treatments throughout the storage period. This study indicated the importance of reducing cooling delays to maintain the quality during the postharvest and prolong storage of harvested tomatoes.

The spectral reflectance technique for the quantification of the functional components was applied in different studies for different crops, but related research on kale leaves is limited. This study was conducted to estimate the glucosinolate and anthocyanin components of kale leaves cultivated in a plant factory based on diffuse reflectance spectroscopy through regression methods. Kale was grown in a plant factory under different treatments. After specific periods of transplantation, leaf samples were collected, and reflectance spectra were measured immediately from nine different points on each leaf. The same leaf samples were freeze-dried and stored for analysis of the functional components. Regression procedures, such as principal component regression (PCR), partial least squares regression (PLSR), and stepwise multiple linear regression (SMLR), were applied to relate the functional components with the spectral data. In the laboratory analysis, progoitrin and glucobrassicin, as well as cyanidin and malvidin, were found to be dominating components in glucosinolates and anthocyanins, respectively. From the overall analysis, the SMLR model showed better performance, and the identified wavelengths for estimating the glucosinolates and anthocyanins were in the early near-infrared (NIR) region. Specifically, reflectance at 742, 761, 787, 796, 805, 833, 855, 932, 947, and 1000 nm showed a strong correlation.

The monitoring and control of environmental conditions are crucial as they influence crop quality and yield in Chinese solar greenhouses (CSGs). The objectives of this study were to assess the spatial, temporal, and vertical variability of major environmental parameters in CSGs during winter and to provide greenhouse climate/microclimate characteristics in order to facilitate the monitoring and control of greenhouse environmental conditions. A wireless sensor network (WSN) was deployed in two CSGs: one with crops and one without. Sensors were placed at different locations inside and outside the greenhouses, and the air temperature, humidity, CO₂ concentration, light intensity, solar radiation, and wind conditions were measured and analyzed. Significant variability in the spatial, temporal, and vertical distribution of environmental factors was observed in both greenhouses. The average minimum and maximum temperatures and humidity inside the CSG with crops were 9.96 °C (4:00 h) and 24.5 °C (12:00 h), and 32.6% (12:00 h) and 92.1% (5:00 h), respectively. The temperature difference was 2.2 °C between layers in the CSG without crops and 1.4 °C between layers in the CSG with crops. The CO₂ concentration in the different layers inside the CSG with crops was highest at night. The average maximum light intensity inside the CSG with crops was 32,660.19 lx, 36,618.12 lx, and 40,660.48 lx (12:00 h to 13:00 h) in the bottom, middle, and top layers, respectively. Sensor positioning in the greenhouse was evaluated by considering the sensors’ data variability. The findings of this study could aid in the development of a better monitoring and control system for CSG’s microclimate during winter. More research is needed on greenhouse microclimate control systems based on this variability analysis, which could improve crop quality and yield in greenhouses.