Next Article in Journal
Analysis of Twenty Years of Suction Trap Data on the Flight Activity of Myzus persicae and Brevicoryne brassicae, Two Main Vectors of Oilseed Rape Infection Viruses
Previous Article in Journal
Analysis of Phenotypic Trait Variation in Germplasm Resources of Lycium ruthenicum Murr.
Previous Article in Special Issue
The Mangrove Swamp Rice Production System of Guinea Bissau: Identification of the Main Constraints Associated with Soil Salinity and Rainfall Variability
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Enhancing Leafy Greens’ Production: Nutrient Film Technique Systems and Automation in Container-Based Vertical Farming

by
Gilda Carrasco
1,*,
Fernando Fuentes-Peñailillo
2,*,
Paula Manríquez
3,
Pabla Rebolledo
1,
Ricardo Vega
4,
Karen Gutter
4 and
Miguel Urrestarazu
5
1
Departamento de Horticultura, Facultad de Ciencias Agrarias, Universidad de Talca, Talca 3460000, Chile
2
Instituto de Investigación Interdisciplinaria (I3), Vicerrectoría Académica (VRA), Universidad de Talca, Talca 3460000, Chile
3
Departamento de Economía Agraria, Facultad de Ciencias Agrarias, Universidad de Talca, Talca 3460000, Chile
4
Doctorado en Ciencias Agrarias, Facultad de Ciencias Agrarias, Universidad de Talca, Talca 3460000, Chile
5
Departamento Agronomía, Universidad de Almería, 04120 Almería, Spain
*
Authors to whom correspondence should be addressed.
Agronomy 2024, 14(9), 1932; https://doi.org/10.3390/agronomy14091932
Submission received: 31 July 2024 / Revised: 23 August 2024 / Accepted: 26 August 2024 / Published: 28 August 2024

Abstract

:
Urban agriculture has emerged as a crucial strategy to address food security and sustainability challenges, particularly in densely populated areas. This study focused on enhancing leafy greens’ production, specifically lettuce (Lactuca sativa L.) and arugula or rocket (Eruca sativa L.), using Nutrient Film Technique (NFT) systems and automation in container-based vertical farming. The study utilized a 20-foot shipping container retrofitted to create a thermally insulated and automated growth environment equipped with energy-efficient LED lighting and precise climate control systems. The results demonstrated significant improvements in crop yields, with the NFT systems achieving productivity up to 11 times higher than traditional methods in protected horticulture. These systems enabled continuous cultivation cycles, responding to the high market demand for fresh local produce. Moreover, the integration of low-cost sensors and automation technologies, each costing under USD 300, ensured that the environmental conditions were consistently optimal, highlighting this approach’s economic feasibility and scalability. This low-cost framework aligns with industry standards for affordable technology, making it accessible for small- to medium-sized urban agriculture enterprises. This study underscores the potential of vertical farming as a sustainable solution for urban food production. It provides a model that can be replicated and scaled to meet the growing demand for healthy, locally grown vegetables.

1. Introduction

Food security is a critical global challenge, especially with the projected urban population growth of 9.8 billion by 2050 [1,2]. Additionally, climate change significantly impacts agricultural activities, particularly the continuous supply of horticultural crops [3,4]. Within this context, there is an urgent need for sustainable technologies to use terrestrial resources efficiently [5], especially in urban areas [6,7]. Balancing environmental, social, and economic considerations is important to ensure the sustainability of vegetable production and minimize negative impacts on the planet and society [8,9]. Considering these challenges, developing and implementing sustainable technologies that optimize terrestrial water resources, especially in urban areas, become imperative. According to projections, it is anticipated that by 2030, over 70% of the global population will reside in urban areas [10,11]. Some research aims to defend the idea of localized food production through urban agriculture, which focuses on producing fresh food within the city for local consumption, contrasting with exporting products to other regions [12,13,14]. Therefore, the diversification of food production is crucial.
In this sense, leafy vegetables stand out for their substantial water content, diverse nutritional profiles, and crucial role in human nutrition. They are rich in essential vitamins, minerals, and dietary fiber, which support various physiological functions [15,16,17], highlighting their importance in maintaining metabolic pathways, cellular integrity, and overall systemic homeostasis [18].
Leafy vegetables, such as lettuce and arugula, offer several advantages over other vegetables, like peppers, particularly in vertical farming (VF). One of the primary benefits of leafy vegetables is their shorter growth cycle, which allows for more frequent harvests and a quicker return on investment [19]. For instance, while leafy vegetables can be harvested relatively quickly after sowing (within 30 days to 8 weeks, depending on the species and growing conditions), peppers typically require a longer growing period, often up to 90 days [20]. This shorter growth cycle makes leafy vegetables more suitable for continuous production systems, such as those used in vertical farming [21].
Moreover, leafy vegetables yield more per square meter when grown in controlled environments like vertical farms. Their compact nature allows for denser planting, maximizing available space [22].
Additionally, leafy vegetables are highly responsive to controlled environmental conditions, allowing for precise light, temperature, and nutrient-level optimization. This adaptability results in consistent quality and yield, making leafy vegetables preferred for urban agriculture and vertical-farming systems [22,23].
Vertical farming represents a significant advancement in agricultural technology, offering several key advantages over traditional farming methods. Unlike conventional farming, which is often constrained by various factors, such as land availability, soil quality, and climatic conditions, vertical farming enables the production of crops in a controlled environment, typically within urban settings [24,25,26]. This method allows for year-round cultivation independent of weather conditions, thereby increasing productivity and ensuring a stable food supply [27,28].
Moreover, vertical farming optimizes space usage by stacking layers of crops, leading to a significantly higher yield per square meter than traditional soil-based farming. This approach is particularly advantageous in urban areas where land is scarce and expensive [29]. The controlled environment inherent to vertical farming also reduces the need for chemical pesticides and herbicides, contributing to more sustainable and eco-friendly production practices [30]. Furthermore, the proximity of vertical farms to urban markets reduces transportation costs and carbon emissions associated with food distribution [31,32], further enhancing the sustainability of this approach. It also addresses food needs in densely populated urban areas and represents an innovative approach to the sustainable use of space [29,33,34]. Leafy vegetables have moderate to low cultivation requirements and are preferably grown outdoors or in unheated greenhouses during the winter and autumn [35]; however, given the continuous demand for leafy vegetables throughout the year, it is crucial to implement complementary methods of protected horticulture to meet this demand [27,36,37]. Implementing VF in controlled environments offers a solution by achieving high output per cultivated area unit without pesticides, ensuring safety and sustainability [38,39]. This method can achieve up to 95% efficient water use [40]. Also, controlled environmental agriculture (CEA) represents an advanced form of hydroponic farming that optimizes horticultural practices [41,42]. It uses sensors and automation systems to regulate certain variables, such as the dissolved oxygen concentration, the solution temperature, the electrical conductivity, and the pH of the nutrient solution [43]. These systems are critical for ensuring the precise control needed for optimal plant growth, making the process more efficient and sustainable [44,45,46].
This new agricultural land use offers substantial economic and ecological benefits, including renewable energies [29,47]. Also, using shipping containers for farming offers a cost-effective and scalable approach due to their modularity and potential for automation. Furthermore, integrating advanced automation systems reduces labor costs and ensures the precise application of water and nutrients, enhancing overall sustainability [48,49,50]. However, controlled-environment farming poses challenges, such as high costs, needing trained personnel, and lacking specialized maintenance services [41,51]. Effective management of crop, hydroponic, and environmental variables is essential in vertical farming to create optimal conditions for plant growth and sustainability [52]. The success of crop cultivation depends on finding the right balance of these variables, often called the ‘recipe’ in a specific VF system [53]. VF can efficiently control temperature, humidity, light, and air velocities, producing crops 365 days a year [29,54,55]. It significantly reduces pest problems and the need for pesticides, as crops are grown indoors and away from environmental pollutants, thus addressing pollution and contamination issues and reducing associated costs [47,53,56]. The planting system in vertical farms can utilize hydroponic methods, such as Ebb and Flow, the Nutrient Film Technique (NFT), aeroponics, and deep-water culture (DWC) [57,58,59,60]. This integrated approach enhances the sustainability and efficiency of VF, making it viable for urban and rural regions.
Implementing low-cost technologies and sensors enables the development of accessible solutions in agriculture, where remote monitoring enhances productive efficiency. A study by [61] points out that while low-cost sensors offer benefits, manufacturers need more transparency. This requires continuous verification and validation of their accuracy against standard reference devices, which can be costly and impractical for producers. The evaluation of economical devices provides farmers, particularly small- and medium-sized producers, with usage guidelines and viable alternatives for monitoring the water status of crops in greenhouses [23]. Access to low-cost technology helps reduce and optimize resource use, thus enabling more sustainable and efficient agricultural practices. Moreover, these devices can be integrated into automation systems to control irrigation, fertilization, and other agricultural processes, thereby reducing the need for labor and increasing operational efficiency [62,63,64].
Considering the above, the present study investigates improving the NFT system arrangement (channel dimensions and layout) in relation to two leafy vegetables’ sizes and technology integration in low-cost vertical farming containers. Small- and medium-sized leafy vegetable growth units, including lettuce and arugula, were evaluated within a 20-foot shipping container adapted as a small-scale plant factory. The container was retrofitted with locally implemented automation systems designed to precisely control the environment. This study aims to optimize space utilization and resource efficiency to support sustainable urban food production. By employing commercially available and cost-effective technologies, this research provides a practical model adaptable to various urban settings. The findings aim to guide future urban agriculture developments, highlighting the integration of automation and low-cost technologies in VF systems to enhance productivity and sustainability.

2. Materials and Methods

2.1. Container Farming

A recycled 20-foot shipping container was placed in a leveled area and thermally insulated with a 100 mm thick coating (density of 15 kg m−3). An anti-slip aluminum floor measuring 2.5 × 1000 × 3000 mm (Figure 1) was installed. An air-conditioning system (wall-mounted split 18,000 BTU h−1 heat pump), an electrical and water system, and a double door were used to isolate the growth area.
CEA systems were installed to regulate the temperature, humidity, and CO2 levels. This included HVAC (heating, ventilation, and air-conditioning) systems tailored to the plants’ needs. Sensors and automation systems continuously monitored environmental conditions, making real-time adjustments to maintain optimal growing conditions. These systems were used to control the HVAC, lighting, and nutrient-delivery systems based on data collected from various sensors, ensuring a stable and conducive growing environment.

2.2. Safety and Maintenance

Safety features, including emergency shutoff valves and alarms for system failures, were installed to prevent accidents and to ensure the system operates reliably. Regular maintenance schedules were established, and easy access points were designed in the container for routine inspections and repairs. These measures ensure the longevity and reliability of the VF system.
Sensors and data-logging systems are monitoring and data-collection methods for environmental variables and growth. Data collection and storage were managed through the central control unit, and data analysis tools were used to interpret the results and make necessary adjustments to the growing conditions.

2.3. Hydroponic System

The VF container was equipped with two NFT hydroponic systems. These systems included low-density channels for recirculating nutrient solutions as a growing medium for small leafy vegetables. Each system had an independent 0.25 HP pump, a tank, and distribution and collector systems. Details regarding the dimensions and characteristics of the channels can be found in Table 1. The NFT channels were set up indoors to maximize the space within the container, as shown in Figure 2, according to the size of the plant.
The hydroponic system’s components, including the NFT channels, pumps, and reservoirs, are constructed from durable materials designed to withstand intensive, continuous-use conditions in a controlled environment. The primarily used materials include the following.
  • NFT channels and reservoirs: Constructed from food-grade PVC and polyethylene, these components have an expected service life of approximately 7 to 10 years, depending on the frequency of use and maintenance practices.
  • Pumps: The 0.25 HP pumps used in the system are rated for continuous operation and have an expected service life of 5 to 7 years.
Disposal and recycling:
  • The PVC and polyethylene components can be recycled at the end of their service life. To ensure proper disposal, local recycling regulations for plastics should be followed. These materials should be cleaned thoroughly to remove residual nutrient solutions or organic matter before recycling.
  • The pumps should be disposed of according to local electronic waste (e-waste) regulations. Many pump components, such as metals and certain plastics, can be recycled, thus reducing their environmental impact.
Proper maintenance, such as regular cleaning and timely replacement of worn parts, can extend the service life of these hydroponic systems and contribute to their sustainability.

2.4. Plant Material

Arugula (Eruca sativa L.) cv. Rocket (Co. Farmer’8) represents the small plant, while Butterhead lettuce (Lactuca sativa L.) cv. Ofelia (Co. Vilmorin) is classified as a medium species. Both species were chosen due to their high demand in the market. A five-meter VF section was allocated for cultivating medium-sized lettuce and another five-meter section was allocated for small-sized arugula.

2.5. Crop Management

The vegetable seedlings were first grown in a CEA farm and then moved to the vertical farm container once they reached the phenological stage of four true leaves for lettuce and five true leaves for arugula. Depending on their size, they were transferred to the CEA container, each with its respective NFT systems (1 m2). Each system had independent pumps (0.25 HP) inside of the same vertical farm container. The early growth, yield (g m−2), and height (cm) of medium- and small-sized leafy greens were assessed. Essential mineral elements were applied to the system using Cooper’s nutrient solution (Cooper, 1979) through water-soluble fertilizer salts while maintaining an adequate and constant film level with daily monitoring. Iron (Fe) was applied using EDDHA chelate fertilizer. The electrical conductivity was maintained at 1.4 dS m−1, and the pH was kept between 5.8 and 6. The flow rate of the nutrient solution in both systems was 1.8–2.0 L min−1.

2.6. System Setup and Environmental Monitoring

To achieve this, it was necessary to evaluate two channels allowing the maximum number of plants possible in 7 square meters. This approach did not involve the development of new technologies but focused on integrating available components that required minimal technological adaptation for continuous operation. The VF system had a comprehensive sensor suite to monitor critical environmental parameters. These included temperature sensors, relative humidity sensors, and devices for assessing the key properties of nutrient solutions, such as electrical conductivity (EC), pH, and dissolved oxygen levels. The precise control and monitoring of these variables are essential for optimizing plant-growth conditions and ensuring the consistent quality of produce. The sensors were selected based on their commercial availability and cost-effectiveness, providing a balance between performance and affordability.
The environmental monitoring system uses a range of sensors, each selected based on their accuracy, reliability, and suitability for a vertical farming environment. The specifications of the used sensors are as follows.
  • Temperature and humidity sensors: BME280 sensors (Bosch, Farmington Hills, MI, USA) measure temperature and relative humidity. They offer a temperature accuracy of ±1.0 °C and a humidity accuracy of ±3% RH, with a measurement range of −40 °C to +85 °C and 0–100% RH.
  • pH sensors: Atlas Scientific pH sensor kits were employed, offering a measurement range of 0–14 pH, an accuracy of ±0.01 pH, and temperature compensation from 0 °C to 50 °C.
  • EC sensors: Electrical conductivity (EC) was measured using Atlas Scientific EC sensors, which have a measurement range of 0.07–500,000 µS cm−1, an accuracy of ±2% of the reading, and temperature compensation from 0 °C to 50 °C.
  • Dissolved oxygen sensors: Atlas Scientific dissolved oxygen sensors were used, with a measurement range of 0–100% saturation, an accuracy of ±0.1 mg L−1, and temperature compensation from 0 °C to 50 °C.
Automation was a core component of the system, facilitated through ESP32-LORA-WIFI microcontrollers (Heltec Automation, Chengdu, China). These microcontrollers were chosen for their cost-efficiency and robust wireless-communication capabilities, allowing for the seamless integration of various system components. The automated systems managed critical functions, such as recirculation pumps for nutrient delivery, air-conditioning units for climate control, and LED grow lights for photosynthetic lighting. This setup aimed to minimize manual intervention, reduce labor costs, and enhance the precision of environmental control.
Due to the ongoing intellectual property protection process, detailed wiring schematics or diagrams of the electronic components used in this study cannot be provided. However, a general overview of the system includes the following configuration.
The sensors (temperature, humidity, pH, EC, and dissolved oxygen) are connected to a central microcontroller unit (MCU) via standard wiring protocols. Each sensor is powered and communicates with the MCU, which processes the data in real time. The microcontroller is also connected to various actuators, such as pumps and climate-control systems, which are controlled based on sensor readings. The wiring configuration ensures that all sensors are connected in a way that minimizes signal interference and maximizes data accuracy. Power management is carefully regulated to prevent voltage drops affecting sensor performance. The MCU has wireless-communication modules (e.g., Wi-Fi, LoRa) that transmit data to the web-based user interface for remote monitoring and control.
The lighting and photoperiod management were based on energy-efficient LED grow lights installed on each tier. These lights are designed to provide the precise light spectrum needed for photosynthesis aimed at optimal plant growth. They are programmable, allowing for the adjustment of light intensity and duration to mimic natural day–night cycles and optimize growth rates. The LED system also helped reduce energy consumption while providing adequate light for all plants, thus ensuring uniform growth and high productivity.
The MCU oversees all automated systems. It combines information from environmental sensors, nutrient monitors, and water-quality sensors, which is then displayed on an intuitive user interface designed for remote accessibility. It enables remote monitoring and control through a web interface, thus allowing operators to supervise the system from anywhere. Real-time data on plant health, growth rates, and environmental conditions were gathered and analyzed to continuously enhance growing conditions. This data-centered approach guarantees high efficiency and productivity.
The system’s user interface (UI) is designed to be user-friendly, thus allowing operators to monitor and control environmental parameters remotely via a web interface accessible from both desktop and mobile devices. The UI provides real-time feedback on critical variables, such as the temperature, humidity, pH, electrical conductivity (EC), and dissolved oxygen levels.
  • Data visualization: The data are visualized through interactive dashboards created using open-source libraries, such as Chart.js and D3.js. These dashboards display time-series data, enabling users to track changes in environmental conditions over time. Graphs and charts are color-coded and customizable, allowing users to highlight specific data points or trends of interest. The dashboards also feature alerts and notifications, which can be set up to warn users when specific parameters deviate from optimal ranges.
  • Data management: The system includes a robust module that logs environmental data into a secure database. These data can be accessed and exported in various formats (e.g., CSV, Excel) for further analysis. Users can filter and query the data directly through the UI, making generating reports or conducting detailed reviews of system performance easy. The data management system supports integration with external analysis tools, allowing for advanced analytics and predictive modeling.

3. Results

3.1. The Spatial Arrangement of Two NFT Systems Combined to Optimize the Annual Production Cycle of Leafy Vegetables, Such as Lettuce and Arugula

The spatial arrangement of two types of NFT channels was crucial for maximizing the volume of the container and creating a productive vertical agriculture container for growing leafy vegetables continuously. This involved determining the number of plants to be established per square meter and the number of levels allowed by the height of a shipping container specifically designed for this purpose. NFT systems support more than one productive cycle of leafy vegetables (like lettuce and arugula). In response to the local market demand, 50% of the space was allocated to satisfy the high demand for lettuce, a medium-sized leafy vegetable (Figure 3 and Figure 4). The remaining productive surface area was dedicated to a smaller vegetable, such as arugula, to meet the demand for various fresh products. This allocation is shown in Table 2.
In the design of the vertical-farming system, the spatial arrangement of the two NFT systems was critical for maximizing the annual production cycle of leafy vegetables. The two NFT systems were arranged in a stacked configuration within the container, with each system consisting of multiple horizontal channels placed at different levels.
This arrangement was carefully planned to ensure maximum exposure to light for each plant, thus optimizing photosynthesis and growth rates. The system was also configured to allow for continuous planting and harvesting cycles, thus maintaining a steady production flow throughout the year. The staggered planting ensured that while one set of channels was harvested, another reached maturity, thus reducing downtime and increasing overall productivity. Controlling environmental factors, such as light, temperature, and nutrient flow, in each layer allowed us to tailor the growing conditions for different crops, thus further optimizing the production cycle.

3.2. Annual Production of Lettuce and Arugula in Vertical Farming

The harvest for both species occurred continuously every 21 days for lettuce and every 18 days for arugula. Table 2 shows details about the NFT channel characteristics.
In our vertical-farming system, this consistent harvest schedule yielded an annual yield of approximately 337 kg per square meter for lettuce and 2068 kg per square meter for arugula. This demonstrates the significant productivity achievable through the controlled environment provided by the vertical farming container, allowing for a continuous supply of fresh produce throughout the year.

3.3. Agronomic Variables of Leafy Vegetables in Vertical Container Farming

The yield results, fresh matter, height, and leaf number of lettuce and arugula are shown in Table 3.
Considering the specific growing periods for each species, achieving 17 lettuce harvests and 20 arugula harvests is possible annually. The yield obtained in vertical farming (m2) is presented in Table 4.
According to the harvest data for lettuce and arugula, the annual yield is 337 and 2068 kg year−1, respectively. However, an urban agriculture producer harvests weekly and even daily. In the shipping container used in this study, with a total surface area of 12 m2 and a growth area of 7 m2, 55 units of lettuce and 181 units of arugula were harvested weekly.
Table 5 shows that the weekly yield for lettuce was 1.85 kg m−2, and for arugula, it was 11.36 kg m−2 (considering a system productive surface area of 3.5 m2 for each vegetable). In a non-heated greenhouse NFT system, the lettuce yield is 2.83 kg per square meter per harvest, equivalent to 24 units. Because approximately eight harvests can be achieved per year in this system, the weekly yield of lettuce is 0.44 kg. In contrast, this study shows a weekly yield of 1.85 kg, representing a production 4.2 times higher. Under the same conditions described earlier, with eight harvests per year, the number of plants per square meter for arugula ranges from 24 to 36 units. An average of 30 units was used for comparison purposes, corresponding to 6.6 kg per harvest. This yields a weekly production of 1 kg. In contrast, this study achieved a weekly yield of 11.36 kg, which is 11 times greater than traditional soil-based cultivation in non-heated greenhouses, where the baseline yield is approximately 1 kg m−2 [65]. Establishing a 12 m2 container with 7 m2 of cultivable area requires an approximate investment of USD 20,000. This solution, using low-cost technology, is implemented and evaluated in this research project, representing a significant advancement in urban agriculture and benefiting producers and areas with high levels of climate impact, among other factors.
A comparative analysis was conducted to evaluate the economic benefits of vertical farming relative to traditional soil-based farming and conventional greenhouse farming. The comparison considers each method’s yield per square meter, operating costs, and overall profitability.
Yield comparison:
  • Traditional soil-based farming: Typically yields about 1 kg m−2 of leafy vegetables annually.
  • Conventional greenhouse farming: Can produce up to 15 kg m−2 of leafy vegetables annually.
  • Vertical farming: Produces approximately 337 kg m−2 of leafy vegetables annually, thanks to optimized space utilization and controlled environmental conditions.
Operating costs:
  • Traditional soil-based farming: It has minimal operating costs primarily associated with labor and water.
  • Conventional greenhouse farming: Includes costs for labor, water, heating, and maintenance.
  • Vertical farming: Involves higher upfront and operating costs due to energy consumption, technology integration, and climate-control systems. However, these costs are offset by significantly higher yields and reduced transportation costs due to proximity to urban markets.
Profitability:
  • Traditional soil-based farming: Generates lower profit margins due to lower yield and market prices.
  • Conventional greenhouse farming: Offers better profitability than soil-based farming but is still subject to seasonal variations and higher operating costs.
  • Vertical farming: Demonstrates the highest profitability, with an annual profit of approximately USD 336.7 m−2 due to its high yield and continuous production cycle.
Overall, vertical farming presents substantial economic advantages, particularly in urban environments with limited and expensive land. The higher yield per square meter and reduced dependency on external factors, such as weather conditions, make vertical farming a viable and profitable alternative to traditional- and greenhouse-farming methods.

3.4. Assessment of Low-Cost Commercial Devices for Vertical Farming

Integrating commercially available and low-cost devices in this VF study proved extremely effective for maintaining optimal growing conditions for a diverse range of leafy vegetables. Farmers can now effortlessly ensure that their crops thrive in any environment by leveraging the power of these cutting-edge technologies [25,66,67,68]. These findings validate the potential of utilizing such devices in commercial applications and highlight their importance in urban settings where cost-effectiveness and space efficiency are paramount. With the seamless integration of these devices, urban farmers can revolutionize their operations and cultivate a bountiful harvest, paving the way for a sustainable future.

3.5. Performance and Suitability of Low-Cost Devices

The study employed cost-effective sensors and automation systems, notably the ESP32-LORA-WIFI microcontrollers. These microcontrollers played a pivotal role in continuously monitoring and regulating various environmental parameters, encompassing temperature, humidity, and the characteristics of the nutrient solution (including EC, pH, and dissolved oxygen). By guaranteeing stable conditions crucial for optimizing the growth of leafy vegetables, these devices exemplified dependability and precision, mirroring pricier alternatives. Such stability is paramount for ensuring consistent crop quality and yield, factors that directly influence the commercial viability of VF endeavors [41,69]. It is worth noting that the economic feasibility of these devices upholds their functionality. Proper utilization, regular maintenance, and calibration are imperative for reliable performance [25,70]. Particularly within a commercial context, where downtime or equipment malfunction entail significant costs, adherence to such practices becomes even more critical. This study underscored that low-cost sensors possess the data accuracy needed for precision agriculture, contingent upon implementing appropriate maintenance protocols.

3.6. Cost Analysis and Economic Viability

A detailed and comprehensive cost analysis was conducted to thoroughly evaluate and assess the economic viability and potential benefits associated with the utilization of these highly advantageous and inexpensive technologies, focusing on state-of-the-art technologies that were economically priced well below the extremely reasonable threshold of 300 USD per unit [71], as defined by the IEEE standards tailored explicitly for low-cost technology implementations. With particular emphasis placed on economic feasibility, it is worth noting that the decision to opt for low-cost, energy-efficient LED lighting systems drastically scaled down operational costs, particularly those associated with energy consumption, representing one of the most financially demanding expenditures in controlled-environment agriculture. Based on the same criteria, HVAC systems and nutrient pumps were chosen. Power meters were also incorporated into the system, providing real-time data insights regarding energy consumption.
The economic analysis revealed that the total setup cost for a 12 m2 container, with 7 m2 of cultivable area, was approximately USD 20,000. Table 6 includes a detailed breakdown of expenses, covering sensors, microcontrollers, energy-efficient LED lighting, HVAC systems, and other necessary components. This study’s focus on technologies priced below 300 USD per unit, according to industry low-cost technology standards, highlights the system’s accessibility and affordability, making it an attractive option for small- to medium-sized enterprises investing in urban agriculture. The addition of these energy-efficient technologies ensures accessibility to a vast range of stakeholders and allows for wide adoption and implementation of these agricultural practices.
The following section provides a detailed analysis of the payback period and expected profit per area unit.

3.7. Payback Period and Profit Analysis

The payback period for the investment in the vertical farming container is calculated based on the total setup cost and the annual revenue generated from producing leafy vegetables (lettuce and arugula).
  • Total setup cost: USD 20,800 (as detailed in Table 6).
  • Annual yield: lettuce: 337 kg m−2 year−1; arugula: 2068 kg m−2 year−1.
  • Farm gate value (approximate): lettuce: USD 3.0 kg−1; arugula: USD 4.0 kg−1.
Annual revenue:
  • Lettuce: 337 kg m−2 year−1 × USD 3.0 kg−1 = USD 1011 m−2 year−1.
  • Arugula: 2068 kg m−2 year−1 × USD 4.0 kg−1 = USD 8272 m−2 year−1.
Profit per square meter:
  • Lettuce: USD 1011 m−2 year−1 − USD 674.3 m−2 year−1 (estimated annual operating costs including services and maintenance) = USD 336.7 m−2 year−1.
  • Arugula: USD 8272 m−2 year−1 − USD 672.5 m−2 year−1 (estimated annual operating costs including services and maintenance) = USD 7599.5 m−2 year−1.
Profit per total system productive surface:
  • Lettuce: USD 336.7 m−2 year−1 × 3.5 m2 = USD 1178.54 year−1.
  • Arugula: USD 7599.5 m−2 year−1 × 3.5 m2 = USD 26,598.08 year−1.
Payback period:
  • Payback period: USD 20,800/USD 27,776.62 = approximately 0.75 years.
Thus, the vertical farming container investment is expected to be recovered within approximately 0.75 years.

3.8. Comparative Profitability Analysis

A comparative analysis was conducted to evaluate the profitability of using 1 m2 of soil, a conventional film greenhouse, and the vertical farming technology described in this study. The analysis considers each method’s yield, costs, and revenue to determine profitability.
Traditional soil-based cultivation (1 m2)
  • Yield: Lettuce: 5 kg m−2 year−1.
  • Market Price: USD 3 kg−1.
  • Revenue: 5 kg m−2 year−1 × USD 3 kg−1 = USD 15 m−2 year−1.
  • Operating Costs: Minimal, primarily labor and water, estimated at USD 2 m−2 year−1.
  • Profit: USD 15 m−2 year−1 − USD 2 m−2 year−1 = USD 13 m−2 year−1.
Conventional film greenhouse (1 m2)
  • Yield: Lettuce: 15 kg m−2 year−1.
  • Market Price: USD 3 kg−1.
  • Revenue: 15 kg m−2 year−1 × USD 3 kg−1 = USD 45 m−2 year−1.
  • Operating Costs: Includes labor, water, and heating, estimated at USD 10 m−2 year−1.
  • Profit: USD 45 − USD 10 = USD 35 m−2 year−1.
Vertical farming technology (1 m2)
  • Yield: Lettuce: 337 kg m−2 year−1.
  • Market Price: USD 3 kg−1.
  • Revenue: 337 kg × USD 3 kg−1 = USD 1011 m−2 year−1.
  • Operating Costs: Includes energy, water, nutrients, and maintenance, estimated at USD 674.3 m−2 year−1.
  • Profit: USD 1011 − USD 674.3 = USD 336.7 m−2 year−1.
Summary of profitability per 1 m2:
  • Traditional Soil-Based Cultivation: USD 13 m−2 year−1.
  • Conventional Film Greenhouse: USD 35 m−2 year−1.
  • Vertical Farming Technology: USD 336.7 m−2 year−1.
This analysis demonstrates that while vertical farming involves higher operating costs, it significantly increases the yield per unit area, resulting in a higher overall profit than traditional soil-based cultivation and conventional film greenhouses. The superior yield and profit margins make vertical farming an economically viable option, especially in urban environments where space is limited.

3.9. Implementation Feasibility in Real-World Operations

The successful implementation of these low-cost technologies in a real-world VF setup demonstrates their practicality and reliability. It proves their ability to revolutionize the field of urban agriculture. This user-friendly nature is crucial for reducing the reliance on specialized technical skills, thus significantly lowering the barriers to entry for urban farmers and other potential adopters [72,73,74]. The findings of this study highlight the immense potential of low-cost, commercially available technologies in meeting the operational needs of VF systems. These innovative technologies provide a practical and sustainable solution for urban agriculture, enabling efficient and eco-friendly food production in resource-constrained environments [75]. The approach taken in this study aligns perfectly with the global trends toward sustainable agriculture, offering a scalable model that can be adapted to various urban settings.

4. Discussion

4.1. Resource Efficiency and Productivity

This study has provided an analysis of the advantages that the NFT system layout brings to the field of VF. Specifically, it focuses on cultivating leafy greens such as lettuce and arugula. In the exploration of these cutting-edge systems, one aspect becomes quite apparent, distinguishing them from conventional agricultural methods—their remarkable ability to efficiently utilize water resources. This efficiency holds significant importance, particularly in densely populated urban settings. Unlike conventional agricultural practices, which often require substantial amounts of water and land, NFT systems efficiently use a thin film of nutrient solution that continuously recirculates [76,77]. This ingenious mechanism minimizes water waste and ensures plants receive the optimal nutrition for healthy growth [78].
The significance of water efficiency in CEA, especially in regions with limited water access, has been widely acknowledged in previous studies [45,46,79,80,81,82,83,84]. Building upon these findings, this study goes a step further to reveal that NFT systems can achieve astonishing yields up to eleven times higher than conventional methods without any compromise in the quality of the final product [85]. Such remarkable achievements are attributed to the NFT systems’ ability to facilitate a highly controlled growth environment. These systems carefully optimize factors such as temperature, humidity, and light to maximize the process of photosynthesis and overall plant development [41]. Moreover, the seamless integration of cutting-edge real-time monitoring technologies allows farmers to obtain accurate environmental information and adjust based on the crop’s intended production objective. This adaptability and responsiveness not only enhance productivity but also give NFT systems a significant competitive advantage over traditional agricultural practices, which often suffer from the adverse impact of unfavorable environmental conditions on final yields [57]. While many previous studies in the same field focus on exploring isolated aspects of the cultivation process and smaller production scales, this research provides a holistic perspective on scaling VF systems to meet the ever-growing demand for fresh, healthy, and sustainable produce in urban areas. This insight is crucial as the world grapples with increasing urbanization and the urgent need for innovative and sustainable food production solutions.
By leveraging recycled shipping containers, VF optimizes limited space and addresses pressing concerns, thus making it economically viable, environmentally friendly, and sustainable [57]. This study highlights the significance of adopting an integrated approach that combines low-cost technologies with advanced agricultural practices. Establishing a sustainable production system is imperative to tackle future challenges in food production within bustling urban environments [86,87].

4.2. Comparison with Previous Studies and Technological Advances

Compared to the earlier studies that have been conducted, these results align perfectly with the hypothesis that integrating advanced technologies can significantly enhance agricultural productivity in controlled environments [50,79,88,89]. The existing literature [90] this subject has extensively documented various approaches in controlled environment agriculture, exploring a wide range of practices that have been implemented and studied. However, it is important to note that this study highlights how accessible and scalable low-cost sensors and automation systems could be, significantly improving agricultural practices’ economic and operational viability. These innovative technologies empower farmers to precisely monitor and manage critical variables crucial in agricultural growth, including temperature, humidity, soil moisture, and nutrient levels. By harnessing the power of data-driven insights, farmers can make informed decisions and take proactive measures to optimize their crops’ growth conditions and production objectives, ensuring crops receive the ideal irrigation, ventilation, and lighting levels [25,41,57,91,92].
The benefits of integrating advanced technologies extend beyond the boundaries of individual farms. These advancements can transform the entire agricultural landscape, allowing farmers to achieve higher yields and meet the ever-increasing demands of a growing population [6,70,93]. By maximizing productivity and minimizing resource waste, farmers can contribute to global food security while also promoting economic growth and stability in rural communities [6,94,95]. The adoption of advanced technologies also has significant environmental implications. By reducing harmful pesticides and fertilizers, farmers can minimize chemical runoff and water contamination, preserving the quality of soil and water resources [47,55,93]. Additionally, precise and efficient resource management helps to save water and energy, mitigating agriculture’s impact on climate change. This shift toward sustainable farming practices protects the environment and improves the resilience of agricultural systems in the face of climate variability [87].

4.3. Innovation and Contribution to Scientific and Technological Development

Adopting this work represents an advancement in biosystems engineering. It not only showcases how cutting-edge technological innovations can be made accessible, scalable, and highly efficient but also demonstrates their profound impact on agricultural practices. Implementing automated climate- and nutrient-control systems not only revolutionizes the way crops are grown but also radically transforms the landscape of urban farming, where resources are often limited. This integration of advanced systems offers many distinctive advantages in sustainable agriculture practices, providing an effective solution to address pressing global challenges. Moreover, LED lighting for plant growth introduces precision and control that surpass traditional agricultural techniques. This innovative approach keeps the production process uninterrupted and meticulously regulated, regardless of external weather conditions. This level of control ensures consistent and optimal crop yields, thus revolutionizing the agricultural landscape. Furthermore, LED lighting optimizes plant growth and minimizes energy consumption, making this approach highly sustainable and environmentally friendly [79,96,97]. This work paves the way for a future where cutting-edge solutions and natural systems coexist seamlessly, creating a sustainable and resilient food-production system that addresses critical challenges, such as food security, resource scarcity, and climate change.

4.4. Future Implications and Research Directions

Moving forward, it is highly recommended that future studies, including renewable energy sources and considering the implementation of advancements in artificial intelligence and data analytics technologies, be duly considered as a logical and commendable next step in optimizing these systems, as their synergistic application promises to revolutionize the prediction and forecasting of crop yields while streamlining resource management. By leveraging these innovations, the expansion of VF in urban areas would also become considerably more viable, thus making an invaluable contribution to developing self-sufficient and resilient cities. Finally, this research has resulted in a solution for growers in charge of food production in urban areas, opening up many new possibilities for further research and development in urban agriculture using other vegetable species.
While this study has demonstrated the technical feasibility and economic viability of vertical farming in urban environments, it is crucial to consider the potential impact of urban pollution on crop safety. Green crops are known to accumulate nitrates and heavy metals, substances that could be present in higher concentrations in urban areas due to pollution [98,99,100,101]. Although this study did not specifically investigate the differences in the chemical composition of crops grown in urban versus ecologically clean environments, this represents a critical area for future research. Future studies should compare the levels of nitrates, heavy metals, and other potential contaminants in crops grown in different environments to assess the safety and sustainability of urban agriculture.

5. Conclusions

This study demonstrates the potential of VF systems equipped with commercially available, cost-effective technologies, highlighting their effectiveness in producing high-quality, homogeneous, and continuous vegetables with high yields, independent of environmental conditions. Integrating the Nutrient Film Technique (NFT) system and precise environmental controls facilitated by affordable sensors and automation technologies proved crucial in maintaining optimal crop growth and health conditions. The system’s design, incorporating ESP32-LORA-WIFI microcontrollers for monitoring and controlling certain factors, such as the temperature, humidity, and nutrient levels, underscores the feasibility of using simple, efficient solutions in urban agriculture.
These practices are essential for maintaining stable growing conditions and achieving consistent crop yields and quality. This study emphasizes that low-cost technologies can match the performance of more expensive systems, provided they are well-maintained, thus offering a viable alternative for cost-sensitive applications. Additionally, growing medium- and small-sized leafy vegetables is well-suited for VF in containers with CEA, allowing for continuous high yields in urban populations. This technology is adaptable for converted shipping containers and other urban infrastructures, such as warehouses. The NFT system can be tailored by adjusting trough sizes according to the leafy vegetable’s size to maximize yield continuity. The study’s findings validate the feasibility and practicality of using a 3.5 m2 growing area with the NFT system for medium-sized species like basil and kale, suggesting its applicability for various crops.
Moreover, VF can diversify the production of small leafy greens, including crops like mustard greens, mizuna, and baby lettuces, thus enhancing the variety available for urban consumers. Implementing CEA in a container requires significant investment and operational resources, emphasizing the need for specialized personnel for crop management and robust information systems for users. Despite these challenges, the system’s scalability and relatively low cost make it a promising solution for increasing urban food production, addressing food security challenges, and promoting sustainable practices.

Author Contributions

Supervision, conceptualization, formal analysis, writing—original draft, G.C. and F.F.-P.; conceptualization, investigation, writing—original draft preparation, G.C., P.R., M.U., F.F.-P., P.M. and K.G.; investigation, formal analysis, writing—review and editing, G.C., F.F.-P., P.M., P.R. and R.V.; writing—review and editing, G.C., F.F.-P., P.M., R.V., P.R., M.U. and K.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Chilean government through the projects FOVI-ANID 220031, FIC Agricultura Vertical Hortícola No. BIP 40.036.334-0.

Data Availability Statement

The original contributions presented in this study are included in the article, and further inquiries can be directed to the corresponding author/s.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the study’s design, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

References

  1. Prawesh, R.; Kumar, S.; Pratap, B.; Singh, N.; Gupta, V. Food Security in Global Challenges; Mahima Research Foundation and Social Welfare: Varanasi, India, 2022; ISBN 9788195302932. [Google Scholar]
  2. Hossain, A.; Krupnik, T.J.; Timsina, J.; Mahboob, M.G.; Chaki, A.K.; Farooq, M.; Bhatt, R.; Fahad, S.; Hasanuzzaman, M. Agricultural Land Degradation: Processes and Problems Undermining Future Food Security. In Environment, Climate, Plant and Vegetation Growth; Springer International Publishing: Berlin/Heidelberg, Germany, 2020; pp. 17–61. ISBN 9783030497323. [Google Scholar]
  3. Eftekhari, M.S. Impacts of Climate Change on Agriculture and Horticulture. In Climate Change: The Social and Scientific Construct; Bandh, S.A., Ed.; Springer International Publishing: Cham, Switzerland, 2022; pp. 117–131. ISBN 978-3-030-86290-9. [Google Scholar]
  4. Malhi, G.S.; Kaur, M.; Kaushik, P. Impact of Climate Change on Agriculture and Its Mitigation Strategies: A Review. Sustainability 2021, 13, 1318. [Google Scholar] [CrossRef]
  5. Fuentes-Peñailillo, F.; Ortega-Farías, S.; de la Fuente-Saiz, D.; Rivera, M. Digital Count of Sunflower Plants at Emergence from Very Low Altitude Using UAV Images. In Proceedings of the 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), Valparaiso, Chile, 13–27 November 2019. [Google Scholar]
  6. Wang, X. Managing Land Carrying Capacity: Key to Achieving Sustainable Production Systems for Food Security. Land 2022, 11, 484. [Google Scholar] [CrossRef]
  7. Nicholls, E.; Ely, A.; Birkin, L.; Basu, P.; Goulson, D. The Contribution of Small-Scale Food Production in Urban Areas to the Sustainable Development Goals: A Review and Case Study. Sustain. Sci. 2020, 15, 1585–1599. [Google Scholar] [CrossRef]
  8. Biesbroek, S.; Kok, F.J.; Tufford, A.R.; Bloem, M.W.; Darmon, N.; Drewnowski, A.; Fan, S.; Fanzo, J.; Gordon, L.J.; Hu, F.B.; et al. Toward Healthy and Sustainable Diets for the 21st Century: Importance of Sociocultural and Economic Considerations. Proc. Natl. Acad. Sci. USA 2023, 120, e2219272120. [Google Scholar] [CrossRef]
  9. Movilla-Pateiro, L.; Mahou-Lago, X.M.; Doval, M.I.; Simal-Gandara, J. Toward a Sustainable Metric and Indicators for the Goal of Sustainability in Agricultural and Food Production. Crit. Rev. Food Sci. Nutr. 2021, 61, 1108–1129. [Google Scholar] [CrossRef]
  10. Mahtta, R.; Fragkias, M.; Güneralp, B.; Mahendra, A.; Reba, M.; Wentz, E.A.; Seto, K.C. Urban Land Expansion: The Role of Population and Economic Growth for 300+ Cities. npj Urban. Sustain. 2022, 2, 5. [Google Scholar] [CrossRef]
  11. Gu, D.; Andreev, K.; Dupre, M.E. Major Trends in Population Growth Around the World. China CDC Wkly. 2021, 3, 604–613. [Google Scholar] [CrossRef]
  12. van der Gaast, K.; van Leeuwen, E.; Wertheim-Heck, S. City-Region Food Systems and Second Tier Cities: From Garden Cities to Garden Regions. Sustainability 2020, 12, 2532. [Google Scholar] [CrossRef]
  13. Sitas, N.; Selomane, O.; Hamann, M.; Gajjar, S.P. Towards Equitable Urban Resilience in the Global South Within a Context of Planning and Management. In Urban Ecology in the Global South; Springer Cham: Berlin/Heidelberg, Germany, 2021; pp. 325–345. ISBN 978-3-030-67650-6. [Google Scholar]
  14. Gulyas, B.Z.; Edmondson, J.L. Increasing City Resilience through Urban Agriculture: Challenges and Solutions in the Global North. Sustainability 2021, 13, 1465. [Google Scholar] [CrossRef]
  15. Shi, M.; Gu, J.; Wu, H.; Rauf, A.; Emran, T.B.; Khan, Z.; Mitra, S.; Aljohani, A.S.M.; Alhumaydhi, F.A.; Al-Awthan, Y.S.; et al. Phytochemicals, Nutrition, Metabolism, Bioavailability, and Health Benefits in Lettuce—A Comprehensive Review. Antioxidants 2022, 11, 1158. [Google Scholar] [CrossRef]
  16. Sharma, S.; Katoch, V.; Kumar, S.; Chatterjee, S. Functional Relationship of Vegetable Colors and Bioactive Compounds: Implications in Human Health. J. Nutr. Biochem. 2021, 92, 108615. [Google Scholar] [CrossRef] [PubMed]
  17. Mobeen; Wang, X.; Saleem, M.H.; Parveen, A.; Mumtaz, S.; Hassan, A.; Adnan, M.; Fiaz, S.; Ali, S.; Iqbal Khan, Z.; et al. Proximate Composition and Nutritive Value of Some Leafy Vegetables from Faisalabad, Pakistan. Sustainability 2021, 13, 8444. [Google Scholar] [CrossRef]
  18. Kumar, D.; Kumar, S.; Shekhar, C. Nutritional Components in Green Leafy Vegetables: A Review. J. Pharmacogn. Phytochem. 2020, 9, 2498–2502. [Google Scholar]
  19. Brychkova, G.; de Oliveira, C.L.; Gomes, L.A.A.; de Souza Gomes, M.; Fort, A.; Esteves-Ferreira, A.A.; Sulpice, R.; McKeown, P.C.; Spillane, C. Regulation of Carotenoid Biosynthesis and Degradation in Lettuce (Lactuca Sativa L.) from Seedlings to Harvest. Int. J. Mol. Sci. 2023, 24, 10310. [Google Scholar] [CrossRef] [PubMed]
  20. De Freitas Furtado, G.; Cavalcante, A.R.; Chaves, L.H.G.; Santos Júnior, J.A.; Gheyi, H.R. Growth and Production of Hydroponic Pepper under Salt Stress and Plant Density. Am. J. Plant Sci. 2017, 08, 2255–2267. [Google Scholar] [CrossRef]
  21. Majid, M.; Khan, J.N.; Ahmad Shah, Q.M.; Masoodi, K.Z.; Afroza, B.; Parvaze, S. Evaluation of Hydroponic Systems for the Cultivation of Lettuce (Lactuca Sativa L., Var. Longifolia) and Comparison with Protected Soil-Based Cultivation. Agric. Water Manag. 2021, 245, 106572. [Google Scholar] [CrossRef]
  22. Goh, Y.S.; Hum, Y.C.; Lee, Y.L.; Lai, K.W.; Yap, W.-S.; Tee, Y.K. A Meta-Analysis: Food Production and Vegetable Crop Yields of Hydroponics. Sci. Hortic. 2023, 321, 112339. [Google Scholar] [CrossRef]
  23. Fuentes-Peñailillo, F.; Gutter, K.; Vega, R.; Silva, G.C. Transformative Technologies in Digital Agriculture: Leveraging Internet of Things, Remote Sensing, and Artificial Intelligence for Smart Crop Management. J. Sens. Actuator Netw. 2024, 13, 39. [Google Scholar] [CrossRef]
  24. Parkes, M.G.; Azevedo, D.L.; Domingos, T.; Teixeira, R.F.M. Narratives and Benefits of Agricultural Technology in Urban Buildings: A Review. Atmosphere 2022, 13, 1250. [Google Scholar] [CrossRef]
  25. Saad, M.H.M.; Hamdan, N.M.; Sarker, M.R. State of the Art of Urban Smart Vertical Farming Automation System: Advanced Topologies, Issues and Recommendations. Electronics 2021, 10, 1422. [Google Scholar] [CrossRef]
  26. Goodman, W.; Minner, J. Will the Urban Agricultural Revolution Be Vertical and Soilless? A Case Study of Controlled Environment Agriculture in New York City. Land. Use Policy 2019, 83, 160–173. [Google Scholar] [CrossRef]
  27. Khan, M.M.; Akram, M.T.; Janke, R.; Qadri, R.W.K.; Al-Sadi, A.M.; Farooque, A.A. Urban Horticulture for Food Secure Cities through and beyond COVID-19. Sustainability 2020, 12, 9592. [Google Scholar] [CrossRef]
  28. Petrovics, D.; Giezen, M. Planning for Sustainable Urban Food Systems: An Analysis of the up-Scaling Potential of Vertical Farming. J. Environ. Plan. Manag. 2022, 65, 785–808. [Google Scholar] [CrossRef]
  29. Vatistas, C.; Avgoustaki, D.D.; Bartzanas, T. A Systematic Literature Review on Controlled-Environment Agriculture: How Vertical Farms and Greenhouses Can Influence the Sustainability and Footprint of Urban Microclimate with Local Food Production. Atmosphere 2022, 13, 1258. [Google Scholar] [CrossRef]
  30. Benke, K.; Tomkins, B. Future Food-Production Systems: Vertical Farming and Controlled-Environment Agriculture. Sustain. Sci. Pract. Policy 2017, 13, 13–26. [Google Scholar] [CrossRef]
  31. Payen, F.T.; Evans, D.L.; Falagán, N.; Hardman, C.A.; Kourmpetli, S.; Liu, L.; Marshall, R.; Mead, B.R.; Davies, J.A.C. How Much Food Can We Grow in Urban Areas? Food Production and Crop Yields of Urban Agriculture: A Meta-Analysis. Earths Future 2022, 10, e2022EF002748. [Google Scholar] [CrossRef] [PubMed]
  32. Martin, M.; Weidner, T.; Gullström, C. Estimating the Potential of Building Integration and Regional Synergies to Improve the Environmental Performance of Urban Vertical Farming. Front. Sustain. Food Syst. 2022, 6, 849304. [Google Scholar] [CrossRef]
  33. Tallou, A.; Haouas, A.; Jamali, M.Y.; Atif, K.; Amir, S.; Aziz, F. Review on Cow Manure as Renewable Energy. In Modeling and Optimization in Science and Technologies; Springer: Berlin/Heidelberg, Germany, 2020; Volume 17, pp. 341–352. [Google Scholar]
  34. Zareba, A.; Krzeminska, A.; Kozik, R. Urban Vertical Farming as an Example of Nature-Based Solutions Supporting a Healthy Society Living in the Urban Environment. Resources 2021, 10, 109. [Google Scholar] [CrossRef]
  35. Gruda, N.; Bisbis, M.; Tanny, J. Impacts of Protected Vegetable Cultivation on Climate Change and Adaptation Strategies for Cleaner Production—A Review. J. Clean. Prod. 2019, 225, 324–339. [Google Scholar] [CrossRef]
  36. Lefèvre, A.; Perrin, B.; Lesur-Dumoulin, C.; Salembier, C.; Navarrete, M. Challenges of Complying with Both Food Value Chain Specifications and Agroecology Principles in Vegetable Crop Protection. Agric. Syst. 2020, 185, 102953. [Google Scholar] [CrossRef]
  37. Fernández, J.A.; Ayastuy, M.E.; Belladonna, D.P.; Comezaña, M.M.; Contreras, J.; de Maria Mourão, I.; Orden, L.; Rodríguez, R.A. Current Trends in Organic Vegetable Crop Production: Practices and Techniques. Horticulturae 2022, 8, 893. [Google Scholar] [CrossRef]
  38. Lubna, F.A.; Lewus, D.C.; Shelford, T.J.; Both, A.J. What You May Not Realize about Vertical Farming. Horticulturae 2022, 8, 322. [Google Scholar] [CrossRef]
  39. Niu, G.; Masabni, J. Plant Production in Controlled Environments. Horticulturae 2018, 4, 28. [Google Scholar] [CrossRef]
  40. Carotti, L.; Pistillo, A.; Zauli, I.; Meneghello, D.; Martin, M.; Pennisi, G.; Gianquinto, G.; Orsini, F. Improving Water Use Efficiency in Vertical Farming: Effects of Growing Systems, Far-Red Radiation and Planting Density on Lettuce Cultivation. Agric. Water Manag. 2023, 285, 108365. [Google Scholar] [CrossRef]
  41. Ragaveena, S.; Shirly Edward, A.; Surendran, U. Smart Controlled Environment Agriculture Methods: A Holistic Review. Rev. Environ. Sci. Biotechnol. 2021, 20, 887–913. [Google Scholar] [CrossRef]
  42. Zhao, X.; Peng, J.; Zhang, L.; Yang, X.; Qiu, Y.; Cai, C.; Hu, J.; Huang, T.; Liang, Y.; Li, Z.; et al. Optimizing the Quality of Horticultural Crop: Insights into Pre-Harvest Practices in Controlled Environment Agriculture. Front. Plant Sci. 2024, 15, 1427471. [Google Scholar] [CrossRef]
  43. Urrestarazu, M.; Carrasco Silva, G. Soiless Culture and Hydroponics; Mundi-Prensa: Madrid, Spain, 2023; ISBN 978-84-8476-766-4. [Google Scholar]
  44. Graham, T. Chapter 4—The Promise and Pitfalls of Controlled Environment Agriculture (CEA)—Technological, Biological, and Societal Considerations for an Evolving Agricultural Landscape. In Future Food Systems; Yada, R.Y., Van Acker, R., Scanlon, M., Gray, D., Eds.; Academic Press: Cambridge, MA, USA, 2024; pp. 43–54. ISBN 978-0-443-15690-8. [Google Scholar]
  45. Neo, D.C.J.; Ong, M.M.X.; Lee, Y.Y.; Teo, E.J.; Ong, Q.; Tanoto, H.; Xu, J.; Ong, K.S.; Suresh, V. Shaping and Tuning Lighting Conditions in Controlled Environment Agriculture: A Review. ACS Agric. Sci. Technol. 2022, 2, 3–16. [Google Scholar] [CrossRef]
  46. Amitrano, C.; Chirico, G.B.; De Pascale, S.; Rouphael, Y.; De Micco, V. Crop Management in Controlled Environment Agriculture (CEA) Systems Using Predictive Mathematical Models. Sensors 2020, 20, 3110. [Google Scholar] [CrossRef]
  47. Van Gerrewey, T.; Boon, N.; Geelen, D. Vertical Farming: The Only Way Is Up? Agronomy 2022, 12, 2. [Google Scholar] [CrossRef]
  48. Fuentes-Peñailillo, F.; Carrasco Silva, G.; Pérez Guzmán, R.; Burgos, I.; Ewertz, F. Automating Seedling Counts in Horticulture Using Computer Vision and AI. Horticulturae 2023, 9, 1134. [Google Scholar] [CrossRef]
  49. Mondejar, M.E.; Avtar, R.; Diaz, H.L.B.; Dubey, R.K.; Esteban, J.; Gómez-Morales, A.; Hallam, B.; Mbungu, N.T.; Okolo, C.C.; Prasad, K.A.; et al. Digitalization to Achieve Sustainable Development Goals: Steps towards a Smart Green Planet. Sci. Total Environ. 2021, 794, 148539. [Google Scholar] [CrossRef] [PubMed]
  50. Khan, N.; Ray, R.L.; Sargani, G.R.; Ihtisham, M.; Khayyam, M.; Ismail, S. Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture. Sustainability 2021, 13, 4883. [Google Scholar] [CrossRef]
  51. Adamietz, R.; Giesen, T.; Mayer, P.; Johnson, A.; Bibb, R.; Seifarth, C. Reconfigurable and Transportable Container-Integrated Production System. Robot. Comput. Integr. Manuf. 2018, 53, 1–20. [Google Scholar] [CrossRef]
  52. Farhangi, H.; Mozafari, V.; Roosta, H.R.; Shirani, H.; Farhangi, M. Optimizing Growth Conditions in Vertical Farming: Enhancing Lettuce and Basil Cultivation through the Application of the Taguchi Method. Sci. Rep. 2023, 13, 6717. [Google Scholar] [CrossRef]
  53. van Delden, S.H.; SharathKumar, M.; Butturini, M.; Graamans, L.J.A.; Heuvelink, E.; Kacira, M.; Kaiser, E.; Klamer, R.S.; Klerkx, L.; Kootstra, G.; et al. Current Status and Future Challenges in Implementing and Upscaling Vertical Farming Systems. Nat. Food 2021, 2, 944–956. [Google Scholar] [CrossRef] [PubMed]
  54. Shao, Y.; Li, J.; Zhou, Z.; Hu, Z.; Zhang, F.; Cui, Y.; Chen, H. The Effects of Vertical Farming on Indoor Carbon Dioxide Concentration and Fresh Air Energy Consumption in Office Buildings. Build. Environ. 2021, 195, 107766. [Google Scholar] [CrossRef]
  55. Avgoustaki, D.D.; Xydis, G. How Energy Innovation in Indoor Vertical Farming Can Improve Food Security, Sustainability, and Food Safety? In Advances in Food Security and Sustainability; Elsevier Ltd.: Amsterdam, The Netherlands, 2020; Volume 5, pp. 1–51. [Google Scholar]
  56. Blom, T.; Jenkins, A.; Pulselli, R.M.; van den Dobbelsteen, A.A.J.F. The Embodied Carbon Emissions of Lettuce Production in Vertical Farming, Greenhouse Horticulture, and Open-Field Farming in the Netherlands. J. Clean. Prod. 2022, 377, 134443. [Google Scholar] [CrossRef]
  57. Kabir, M.S.N.; Reza, M.N.; Chowdhury, M.; Ali, M.; Samsuzzaman; Ali, M.R.; Lee, K.Y.; Chung, S.O. Technological Trends and Engineering Issues on Vertical Farms: A Review. Horticulturae 2023, 9, 1229. [Google Scholar] [CrossRef]
  58. Sengodan, P. An Overview of Vertical Farming: Highlighting the Potential in Malaysian High-Rise Buildings. Pertanika J. Sci. Technol. 2022, 30, 949–981. [Google Scholar] [CrossRef]
  59. Ghorbel, R.; Chakchak, J.; Koşum, N.; Cetin, N.S. Hydroponic Technology for Green Fodder Production: Concept, Advantages, and Limits. In Proceedings of the 6th International Students Science Congress, İzmir, Türkiye, 12 September 2022; Izmir UOD: İzmir, Türkiye, 2022. [Google Scholar]
  60. Santosh, D.T.; Gaikwad, D. Advances in Hydroponic Systems: Types and Management. In Advances in Agricultural Technology; Maitra, S., Gaikwad, D., DT, S., Eds.; Griffon: Québec, Canada, 2023; pp. 16–28. ISBN 978-17-77795-91-7. [Google Scholar]
  61. Coulby, G.; Clear, A.K.; Jones, O.; Godfrey, A. Low-Cost, Multimodal Environmental Monitoring Based on the Internet of Things. Build. Environ. 2021, 203, 108014. [Google Scholar] [CrossRef]
  62. de Moura Campos, H.; de Oliveira, H.F.E.; Mesquita, M.; de Castro, L.E.V.; Ferrarezi, R.S. Low-Cost Open-Source Platform for Irrigation Automation. Comput. Electron. Agric. 2021, 190, 106481. [Google Scholar] [CrossRef]
  63. Akhund, T.M.N.U.; Newaz, N.T.; Zaman, Z.; Sultana, A.; Barros, A.; Whaiduzzaman, M. IoT-Based Low-Cost Automated Irrigation System for Smart Farming. In Proceedings of the Lecture Notes in Networks and Systems; Springer Science and Business Media Deutschland GmbH: Berlin/Heidelberg, Germany, 2022; Volume 333, pp. 83–91. [Google Scholar]
  64. Singh, K.; Kumar, R. Design of a Low-Cost Sensor-Based IoT System for Smart Irrigation. In Applications in Ubiquitous Computing; Springer Nature Switzerland AG: Cham, Switzerland, 2021; pp. 59–79. ISBN 978-3-030-35279-0. [Google Scholar]
  65. da Silva, P.A.; Kinjo, S.; de Melo, M.P.B.X.; Sala, F.C. Evaluation of Arugula Cultivars and Seed Production in the Organic System. J. Seed Sci. 2019, 41, 423–430. [Google Scholar] [CrossRef]
  66. Song, S.; Hou, Y.; Lim, R.B.H.; Gaw, L.Y.F.; Richards, D.R.; Tan, H.T.W. Comparison of Vegetable Production, Resource-Use Efficiency and Environmental Performance of High-Technology and Conventional Farming Systems for Urban Agriculture in the Tropical City of Singapore. Sci. Total Environ. 2022, 807, 150621. [Google Scholar] [CrossRef] [PubMed]
  67. Tavan, M.; Wee, B.; Brodie, G.; Fuentes, S.; Pang, A.; Gupta, D. Optimizing Sensor-Based Irrigation Management in a Soilless Vertical Farm for Growing Microgreens. Front. Sustain. Food Syst. 2021, 4, 622720. [Google Scholar] [CrossRef]
  68. Gumisiriza, M.S.; Ndakidemi, P.; Nalunga, A.; Mbega, E.R. Building Sustainable Societies through Vertical Soilless Farming: A Cost-Effectiveness Analysis on a Small-Scale Non-Greenhouse Hydroponic System. Sustain. Cities Soc. 2022, 83, 103923. [Google Scholar] [CrossRef]
  69. Rayhana, R.; Xiao, G.; Liu, Z. Internet of Things Empowered Smart Greenhouse Farming. IEEE J. Radio. Freq. Identif. 2020, 4, 195–211. [Google Scholar] [CrossRef]
  70. Salim Mir, M.; Bashir Naikoo, N.; Habib Kanth, R.; Bahar, F.; Anwar Bhat, M.; Nazir, A.; Sheraz Mahdi, S.; Amin, Z.; Singh, L.; Raja, W.; et al. Vertical Farming: The Future of Agriculture: A Review. Pharma Innov. J. 2022, 1175–1195. [Google Scholar]
  71. Fuentes, F.; Rivera, M.; Carrasco, G.; Jaramillo, J.; Gutter, K.; Vega, R.; Castro, H. Greenhouse Crop Monitoring with Low-Cost Sensors: Assessing Lettuce Production Through Air-Canopy Temperature Difference. In Proceedings of the 2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), Valdivia, Chile, 5–7 December 2023; Institute of Electrical and Electronics Engineers Inc.: Piscataway, NJ, USA, 2023. [Google Scholar]
  72. Steinke, J.; van Etten, J.; Müller, A.; Ortiz-Crespo, B.; van de Gevel, J.; Silvestri, S.; Priebe, J. Tapping the Full Potential of the Digital Revolution for Agricultural Extension: An Emerging Innovation Agenda. Int. J. Agric. Sustain. 2021, 19, 549–565. [Google Scholar] [CrossRef]
  73. Alfonsi, R.M.; Naidoo, M.; Gasparatos, A. Adoption and Desirable Characteristics of Information and Communication Technologies for Urban Small-Scale Food Producers in South Africa. Front. Sustain. Food Syst. 2024, 8, 1332978. [Google Scholar] [CrossRef]
  74. Jellason, N.P.; Conway, J.S.; Baines, R.N. Understanding Impacts and Barriers to Adoption of Climate-Smart Agriculture (CSA) Practices in North-Western Nigerian Drylands. J. Agric. Educ. Ext. 2021, 27, 55–72. [Google Scholar] [CrossRef]
  75. Carrasco, G.; Manríquez, P.; Galleguillos, F.; Fuentes-Peñailillo, F.; Urrestarazu, M. Evolution of Soilless Culture in Chile. In Proceedings of the III International Symposium on Soilless Culture and Hydroponics: Innovation and Advanced Technology for Circular Horticulture, Leuven, Belgium, 9 September 2021; pp. 267–274. [Google Scholar]
  76. Rozilan, M.R.; Mohd Rodzi, A.S.; Faiz Zubair, A.; Hemdi, A.R.; Deraman, R.; Md Sin, N.D. Design and Fabrication of Nutrient Film Technique (NFT) Hydroponic System. In Technological Advancement in Instrumentation & Human Engineering; Hassan, M.H.A., Zohari, M.H., Kadirgama, K., Mohamed, N.A.N., Aziz, A., Eds.; Springer Nature: Singapore, 2023; pp. 123–144. [Google Scholar]
  77. Tanishi, M.; Muthukumaraswamy, S.A. On the Study and Analyses of “Vertical Farming—The Future of Agriculture” via Various Hydroponic Systems. In Intelligent Manufacturing and Energy Sustainability; Reddy, A.N.R., Marla, D., Favorskaya, M.N., Satapathy, S.C., Eds.; Springer: Singapore, 2022; pp. 157–165. [Google Scholar]
  78. Carrasco, G.; Fuentes-Peñailillo, F.; Pérez, R.; Rebolledo, P.; Manríquez, P. An Approach to a Vertical Farming Low-Cost to Reach Sustainable Vegetable Crops. In Proceedings of the 2022 IEEE International Conference on Automation/XXV Congress of the Chilean Association of Automatic Control (ICA-ACCA), Curicó, Chile, 24–28 October 2022; pp. 1–6. [Google Scholar]
  79. Engler, N.; Krarti, M. Review of Energy Efficiency in Controlled Environment Agriculture. Renew. Sustain. Energy Rev. 2021, 141, 110786. [Google Scholar] [CrossRef]
  80. Tan, B.; Li, Y.; Liu, T.; Tan, X.; He, Y.; You, X.; Leong, K.H.; Liu, C.; Li, L. Response of Plant Rhizosphere Microenvironment to Water Management in Soil- and Substrate-Based Controlled Environment Agriculture (CEA) Systems: A Review. Front. Plant Sci. 2021, 12, 691651. [Google Scholar] [CrossRef] [PubMed]
  81. Lefers, R.M.; Tester, M.; Lauersen, K.J. Emerging Technologies to Enable Sustainable Controlled Environment Agriculture in the Extreme Environments of Middle East-North Africa Coastal Regions. Front. Plant Sci. 2020, 11, 801. [Google Scholar] [CrossRef]
  82. Dsouza, A.; Newman, L.; Graham, T.; Fraser, E.D.G. Exploring the Landscape of Controlled Environment Agriculture Research: A Systematic Scoping Review of Trends and Topics. Agric. Syst. 2023, 209, 103673. [Google Scholar] [CrossRef]
  83. Nicholson, C.F.; Harbick, K.; Gómez, M.I.; Mattson, N.S. An Economic and Environmental Comparison of Conventional and Controlled Environment Agriculture (CEA) Supply Chains for Leaf Lettuce to US Cities. In Food Supply Chains in Cities: Modern Tools for Circularity and Sustainability; Springer International Publishing: Berlin/Heidelberg, Germany, 2020; pp. 33–68. ISBN 9783030340650. [Google Scholar]
  84. Ojo, M.O.; Zahid, A. Deep Learning in Controlled Environment Agriculture: A Review of Recent Advancements, Challenges and Prospects. Sensors 2022, 22, 7965. [Google Scholar] [CrossRef] [PubMed]
  85. Wibisono, V.; Kristyawan, Y. An Efficient Technique for Automation of The NFT (Nutrient Film Technique) Hydroponic System Using Arduino. Int. J. Artif. Intell. Robot. (IJAIR) 2021, 3, 44–49. [Google Scholar] [CrossRef]
  86. Artmann Martina and Breuste, J. Urban Agriculture—More Than Food Production. In Making Green Cities: Concepts, Challenges and Practice; Jürgen, B., Artmann, M., Ioja, C., Qureshi, S., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 75–176. ISBN 978-3-030-37716-8. [Google Scholar]
  87. Devaux, A.; Goffart, J.P.; Kromann, P.; Andrade-Piedra, J.; Polar, V.; Hareau, G. The Potato of the Future: Opportunities and Challenges in Sustainable Agri-Food Systems. Potato Res. 2021, 64, 681–720. [Google Scholar] [CrossRef]
  88. Rehman, A.; Saba, T.; Kashif, M.; Fati, S.M.; Bahaj, S.A.; Chaudhry, H. A Revisit of Internet of Things Technologies for Monitoring and Control Strategies in Smart Agriculture. Agronomy 2022, 12, 127. [Google Scholar] [CrossRef]
  89. Javaid, M.; Haleem, A.; Singh, R.P.; Suman, R. Enhancing Smart Farming through the Applications of Agriculture 4.0 Technologies. Int. J. Intell. Netw. 2022, 3, 150–164. [Google Scholar] [CrossRef]
  90. Fuentes-Peñailillo, F.; Gutter, K.; Vega, R.; Silva, G.C. New Generation Sustainable Technologies for Soilless Vegetable Production. Horticulturae 2024, 10, 49. [Google Scholar] [CrossRef]
  91. Halgamuge, M.N.; Bojovschi, A.; Fisher, P.M.J.; Le, T.C.; Adeloju, S.; Murphy, S. Internet of Things and Autonomous Control for Vertical Cultivation Walls towards Smart Food Growing: A Review. Urban. For. Urban. Green. 2021, 61. [Google Scholar] [CrossRef]
  92. Hati, A.J.; Singh, R.R. Smart Indoor Farms: Leveraging Technological Advancements to Power a Sustainable Agricultural Revolution. AgriEngineering 2021, 3, 728–767. [Google Scholar] [CrossRef]
  93. Chatterjee, A.; Debnath, S.; Pal, H. Implication of Urban Agriculture and Vertical Farming for Future Sustainability. In Urban Horticulture; Solankey, S.S., Akhtar, S., Maldonado, A.I.L., Rodriguez-Fuentes, H., Contreras, J.A.V., Reyes, J.M.M., Eds.; IntechOpen: Rijeka, Croatia, 2020. [Google Scholar]
  94. García-Díez, J.; Gonçalves, C.; Grispoldi, L.; Cenci-Goga, B.; Saraiva, C. Determining Food Stability to Achieve Food Security. Sustainability 2021, 13, 7222. [Google Scholar] [CrossRef]
  95. Wani, N.R.; Rather, R.A.; Farooq, A.; Padder, S.A.; Baba, T.R.; Sharma, S.; Mubarak, N.M.; Khan, A.H.; Singh, P.; Ara, S. New Insights in Food Security and Environmental Sustainability through Waste Food Management. Environ. Sci. Pollut. Res. 2024, 31, 17835–17857. [Google Scholar] [CrossRef] [PubMed]
  96. Ahmed, H.A.; Yu-Xin, T.; Qi-Chang, Y. Optimal Control of Environmental Conditions Affecting Lettuce Plant Growth in a Controlled Environment with Artificial Lighting: A Review. S. Afr. J. Bot. 2020, 130, 75–89. [Google Scholar] [CrossRef]
  97. Paradiso, R.; Proietti, S. Light-Quality Manipulation to Control Plant Growth and Photomorphogenesis in Greenhouse Horticulture: The State of the Art and the Opportunities of Modern LED Systems. J. Plant Growth Regul. 2022, 41, 742–780. [Google Scholar] [CrossRef]
  98. Rashid, A.; Schutte, B.J.; Ulery, A.; Deyholos, M.K.; Sanogo, S.; Lehnhoff, E.A.; Beck, L. Heavy Metal Contamination in Agricultural Soil: Environmental Pollutants Affecting Crop Health. Agronomy 2023, 13, 1521. [Google Scholar] [CrossRef]
  99. Ullah, N.; Rehman, M.U.; Ahmad, B.; Ali, I.; Younas, M.; Aslam, M.S.; Rahman, A.U.; Taheri, E.; Fatehizadeh, A.; Rezakazemi, M. Assessment of Heavy Metals Accumulation in Agricultural Soil, Vegetables and Associated Health Risks. PLoS ONE 2022, 17, e0267719. [Google Scholar] [CrossRef]
  100. Othman, Y.A.; Al-Assaf, A.; Tadros, M.J.; Albalawneh, A. Heavy Metals and Microbes Accumulation in Soil and Food Crops Irrigated with Wastewater and the Potential Human Health Risk: A Metadata Analysis. Water 2021, 13, 3405. [Google Scholar] [CrossRef]
  101. Bian, Z.; Wang, Y.; Zhang, X.; Li, T.; Grundy, S.; Yang, Q.; Cheng, R. A Review of Environment Effects on Nitrate Accumulation in Leafy Vegetables Grown in Controlled Environments. Foods 2020, 9, 732. [Google Scholar] [CrossRef]
Figure 1. Developing a container for vertical farming. (a) The photo shows the installation of the productive container on a concrete slab. (b) The photo depicts the installation of the internal insulation in the container. (c) The photo illustrates the final installation of the insulation and flooring system in the container before the channels’ installation.
Figure 1. Developing a container for vertical farming. (a) The photo shows the installation of the productive container on a concrete slab. (b) The photo depicts the installation of the internal insulation in the container. (c) The photo illustrates the final installation of the insulation and flooring system in the container before the channels’ installation.
Agronomy 14 01932 g001
Figure 2. Structure of NFT channels for medium and small leafy vegetables. The figure illustrates the structure of the wide and narrow channels used in the proposed system’s implementation.
Figure 2. Structure of NFT channels for medium and small leafy vegetables. The figure illustrates the structure of the wide and narrow channels used in the proposed system’s implementation.
Agronomy 14 01932 g002
Figure 3. Layout of NFT systems in vertical farm container. The diagram referentially shows two levels per side of the container; however, there were five levels of narrow channels and four levels of wide channels.
Figure 3. Layout of NFT systems in vertical farm container. The diagram referentially shows two levels per side of the container; however, there were five levels of narrow channels and four levels of wide channels.
Agronomy 14 01932 g003
Figure 4. Layout of NFT channels. Image (a) represents the four levels of wide channels, and image (b) corresponds to an actual photograph of the narrow channels, which have five levels arranged.
Figure 4. Layout of NFT channels. Image (a) represents the four levels of wide channels, and image (b) corresponds to an actual photograph of the narrow channels, which have five levels arranged.
Agronomy 14 01932 g004
Table 1. Characteristics of NFT channels used in the vertical farm container.
Table 1. Characteristics of NFT channels used in the vertical farm container.
Characteristics of NFT ChannelsMedium Leafy Vegetables (Lettuce)Small Leafy Vegetables (Arugula)
Channel Width (m)0.080.06
Channel Depth (m)0.040.03
Planting Hole Spacing (m)0.160.07
Implemented ModificationsWider spacing to accommodate larger plantsNarrower spacing to maximize plant density
Table 2. Variables of the NFT systems evaluated in the vertical farm container.
Table 2. Variables of the NFT systems evaluated in the vertical farm container.
Variables of the NFT System in Vertical FarmingSize of Leafy Vegetables
MediumSmall
Level numbers45
Channel numbers per level56
Available width for setting up NFT channels, meter0.70.7
Planting holes per linear meter of channel611
Planting holes per square meter per level4294
Planting holes per square meter in vertical farming168470
Table 3. Agronomic variables of leafy vegetables evaluated at harvest.
Table 3. Agronomic variables of leafy vegetables evaluated at harvest.
Agronomic Variables of Leafy Vegetables Evaluated at HarvestLettuceArugula
Growing period (transplant to harvest), days2118
Fresh matter, kg plant−10.1180.22
Height, m plant−10.120.11
Leaves N°, plant−12214
Table 4. Yield of lettuce and arugula grown in vertical farming at each harvest.
Table 4. Yield of lettuce and arugula grown in vertical farming at each harvest.
At Each HarvestLettuceArugula
Planting holes N° m−2168470
Yield per NFT system in vertical farming, kg m−219.82103.40
Table 5. Weekly yield per square meter of medium- and small-sized leafy vegetables in vertical farming.
Table 5. Weekly yield per square meter of medium- and small-sized leafy vegetables in vertical farming.
LettuceArugula
Yield, kg m−2 year−1 (at each whole harvest)3372068
Plant number m−2 year−128559400
Yield, kg m−2 weekly−16.4739.77
Plant unit m−2 weekly−155181
Table 6. Cost of every component of the system.
Table 6. Cost of every component of the system.
ComponentDescriptionCost in USD
SensorsTemperature, humidity, pH, EC, dissolved oxygen1200
MicrocontrollersESP32-LORA-WIFI for automation200
Pumps0.25 HP nutrient solution pumps400
LED LightsEnergy-efficient grow lights3500
HVAC Systems18,000 BTU h-1 heat pump4000
Shipping Container20-foot retrofitted container7500
Insulation and FlooringThermal insulation and anti-slip flooring2000
Nutrient Solution SystemIncludes reservoirs and mixers1500
Miscellaneous CostsWiring, installation, maintenance tools500
Total Estimated Cost20,800
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Carrasco, G.; Fuentes-Peñailillo, F.; Manríquez, P.; Rebolledo, P.; Vega, R.; Gutter, K.; Urrestarazu, M. Enhancing Leafy Greens’ Production: Nutrient Film Technique Systems and Automation in Container-Based Vertical Farming. Agronomy 2024, 14, 1932. https://doi.org/10.3390/agronomy14091932

AMA Style

Carrasco G, Fuentes-Peñailillo F, Manríquez P, Rebolledo P, Vega R, Gutter K, Urrestarazu M. Enhancing Leafy Greens’ Production: Nutrient Film Technique Systems and Automation in Container-Based Vertical Farming. Agronomy. 2024; 14(9):1932. https://doi.org/10.3390/agronomy14091932

Chicago/Turabian Style

Carrasco, Gilda, Fernando Fuentes-Peñailillo, Paula Manríquez, Pabla Rebolledo, Ricardo Vega, Karen Gutter, and Miguel Urrestarazu. 2024. "Enhancing Leafy Greens’ Production: Nutrient Film Technique Systems and Automation in Container-Based Vertical Farming" Agronomy 14, no. 9: 1932. https://doi.org/10.3390/agronomy14091932

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop