Technological Trends and Engineering Issues on Vertical Farms: A Review
Abstract
:1. Introduction
2. Vertical Farming: Concept, Classification, and Key Considerations
2.1. Definition and Types
2.2. General Structures and Characteristics
2.3. Key Considerations
2.3.1. Crop-Cultivation System
2.3.2. Crop Selection
2.3.3. Technological Level
2.3.4. Location
3. Technological Trends
3.1. Sensing Technology
3.1.1. Sensors and Actuators
3.1.2. Nutrient-Sensing Systems
3.1.3. Plant Monitoring and Control Systems
3.2. Unmanned Vertical Farming Systems
3.2.1. Automated Vertical Farming Systems
3.2.2. Robotic Vertical Farming Systems
3.2.3. Vertical Farming with Drones
3.3. AI-Based Research Trends
4. Global Industrial and Market Trends
4.1. Global Status
4.2. Industry and Market Trends in Asia
4.3. Industry and Market Trends in the USA
4.4. Industry and Market Trends in Europe
4.5. Innovative Concepts for Upcoming Vertical Farms
Vertical Farm, Location | Company | Key Features | Reference |
---|---|---|---|
Sunqiao Urban Agricultural District, Shanghai, China | Sasaki Architects, Boston, USA |
| [208] |
La Tour Vivante, Rennes, France, | SOA Architectes, Paris, France |
| [209] |
Jian Mu Tower, Shenzhen, China | Carlo Ratti Associati, Turin, Italy |
| [210] |
Urban Skyfarm, Seoul, South Korea | Aprilli Design Studio, Toronto, Canada |
| [213] |
Hive-Inn™ City Farm, New York, USA | OVA Studio Ltd., Sheung Wan, Hong Kong |
| [216] |
5. Issues and Future Prospects
5.1. Opportunities and Challenges Regarding Crops, the Environment, and Economics
5.1.1. Crop-Production Perspective
5.1.2. Environmental Perspective
5.1.3. Economic Perspective
5.2. Opportunities and Challenges for Global Food Security
5.3. Technological Opportunities and Challenges
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Considered Parameters | Hydroponics Techniques | |||||
---|---|---|---|---|---|---|
NFT | DWC | Ebb–Flow | Aeroponics | Drip | Wick | |
Suitability for vertical farming | High | High | High | High | Low | Low |
Nutrient use efficiency | High | Low | Low | High | Low | Low |
Aeration requirement | Low | High | Low | Low | Low | Low |
Salt build-up possibility | Low | High | Low | Low | High | High |
Root-rot possibility | Low | High | Low | Low | High | High |
Water saving | High | Low | Low | High | High | High |
Long growing period | Low | Low | Low | Low | High | Low |
Energy use | Low | Low | Low | High | Low | Low |
Pump-failure sensitivity | High | Low | High | High | Low | Low |
Setup cost | High | Low | Low | High | High | Low |
Maintenance complexity | Low | Low | Low | High | Low | Low |
Item | Type | Specification | Applications | Image |
Sensors | Temperature and humidity | Measuring range: −40–80 °C, 0–100%; Accuracy: ±2%, ±3%; Response time: 5 s; Resolution: 0.1 °C, 0.01%; Power input: 3.3–5.5 V |
| |
CO2 | Measuring range: 0–10,000 ppm; Accuracy: ±5% Response time: 10 s; Resolution: 1 ppm; Power input: 3.3–5.5 V |
| ||
Light intensity | Measuring range: 0–3000 W/m2; Accuracy: ±1% Response time: 10 µs; Sensitivity: 4 μA per 1000 PPFD in water |
| ||
Electrical conductivity (EC) | Meas. Range: 0–20,000 µS/cm; Accuracy: ±4–8% Response time: 5 s; Resolution: 1 ppm; Power input: 5 V |
| ||
pH | Measuring range: 0–14; Accuracy: ±0.2%; Response time: 1 s Resolution: 1 ppm; Power input: 5 V |
| ||
Ion-selective electrode (ISE) | Measuring range: 1–14,000 ppm; Accuracy: ±10% Response time: 1 s; Resolution: 1 ppm; Power input: 5 V |
| ||
Dissolved oxygen (DO) | Measuring range: 0–20 ppm; Accuracy: ±2%; Response time: 40 s; Resolution: 0.006 ppm; Power input: 5 V |
| ||
Water level | Measuring range: 0.1–3 m; Accuracy: ±0.2%; Resolution: 0.5 mm Dead band: 0.1 m; Power input: 12–28 V |
| ||
Actuators | Heater | Power input: 110, 220 V; Power: 2.8 kW |
| |
Cooler | Power input: 110, 220 V; Lowest temp: 0 °C; Coverage: 450 m2 |
| ||
Humidifier | Power input: 110, 220 V; Coverage: 2000 m2; Power: 2.2 kW |
| ||
Dehumidifier | Power input: 110, 220 V; Humidity removal: 2.5 L/h Air flow rate: 30 m3/h; Coverage: 50–100 m2 |
| ||
LEDs | Power input: 110, 220 V; Light intensity: 17,400 flux; Output: 300 W |
| ||
Fan | Power input: 110, 220 V; Air flow rate: 4400 m3/h Output: 1.1 kW, 437 rpm |
| ||
CO2 regulator | Power input: 110, 220 V; Flow rate: 0.5–15 SCFH Control type: Digital, solenoid |
| ||
Nutrient pump | Power input: 110, 220 V; Maximum flow: 100 L/min Maximum head: 24 m; Power: 0.75 HP/0.55 kW |
|
Vertical Farm | Location | Key Technical Features | Reference |
---|---|---|---|
GreenCUBE | Singapore |
| [121] |
iFarm | Helsinki, Finland |
| [122] |
Seasony | Copenhagen, Denmark |
| [123] |
Organifarms | Konstanz, Germany |
| [124] |
Eagle Technologies | Michigan, USA |
| [118] |
Intelligent Growth Solutions | Edinburgh, Scotland |
| [125] |
Badia Farms | Dubai, United Arab Emirates |
| [126] |
Spread (Techno Farm Keihanna) | Kyoto, Japan |
| [127] |
A-Plus (Farm and Factory TAMURA) | Fukushima, Japan |
| [128] |
Itoh Denki | Kasai, Japan |
| [129] |
Model/Algorithm | Observed Features | Accuracy (%) | Plant Type (Application) | Reference |
---|---|---|---|---|
CNN, ResNet50 | Plant leaf | 86.0 | Lettuce (disease detection and identification) | [146] |
3D plant modeling, deep segmentation | Plant height, leaf area, leaf weight | - | Basil (phenotyping) | [102] |
Mask-RCNN with pseudo crop mixing | Leaf area | 76.9 | Lettuce (growth monitoring) | [148] |
ANN algorithm, big data | Plant growth | 98.32 | Lettuce (growth prediction) | [149] |
ANN, backpropagation | Plant height | 72.8 | Lettuce (growth prediction) | [150] |
Dual segmented regression | Plant leaf | 97.0 | Lettuce (leaf stress) | [151] |
MFC-CNN | Plant leaf | 87.95 | Lettuce (leaf stress) | [152] |
CNN, ResNet26 | Plant leaf | 91.78 | Mix plants (plant stress) | [153] |
WGAN, deep CNN architectures | Plant leaf | 87.0 | Lettuce (leaf stress) | [154] |
DeepLabV3+ | Plant leaf | 83.26 | Lettuce (leaf abnormalities) | [155] |
Deep-learning models | Plant leaf | 94.15 | Moss (water stress) | [156] |
RF, SVM, MLP | Plant leaf | 95.3, 72.9, 84.4 | Rosette (phenotyping) | [157] |
InceptionResNetv2, Xception, DarkNet 53 | Plant leaf | 82.0, 75.0, 98.0 | Lettuce (phytomorphological attributes) | [158] |
LSSVM | Plant leaf | 99.0 | Wheat (water stress) | [159] |
Neural network, SVM classifier | Plant growth | 80.0 | Strawberry (disease detection) | [160] |
Viola–Jones algorithm, Haar | Fruit | - | Tomato (disease detection) | [161] |
Self-organizing map (SOM), hierarchical, K-means | Plant leaf | 91.3, 98.6, 99.1 | Lettuce (growth prediction) | [162] |
Logistic regression | Plant growth | 97.1 | Lettuce (yield) | [163] |
KNN algorithm | Plant growth | 93.0 | Leafy vegetables (growth) | [164] |
Reinforcement learning | Plant leaf | 82.0 | Chili, beans, potatoes, onions (phenotyping) | [165] |
MobileNetV2 | Plant leaf | 98.4 | Lettuce (growth prediction) | [166] |
U-Net | Leaf area, fresh weight | 97.0 | Arabidopsis (phenotyping) | [167] |
Genetics algorithms, back propagation | Leaf area | 99.3 | Tomato (LAI) | [168] |
DeepFlow, principal-component analysis | Plant area, weight | 74.3 | Lettuce (growth prediction) | [169] |
Deepabv3+ | Plant height, coverage | 98.2 | Lettuce (plant spacing) | [170] |
Vertical Farm, Location | Types of Crops | Production Capacity | Cultivation System | Technical Features | Website |
---|---|---|---|---|---|
Shinnippo Ltd. 808 Factory, Shizuoka, Japan | Mainly lettuce (frilly, green leaf, silky, and romaine) |
|
|
| https://www.808factory.jp/ (accessed on 7 March 2023) |
Spread Co., Ltd., Kyoto, Japan | Leafy greens (lettuce), strawberries |
| DFT |
| https://spread.co.jp/en/ (accessed on 7 March 2023) |
Mirai Co. Ltd., Chiba, Japan | Greenleaf, kale, oakleaf, spinach, basil |
| DFT |
| https://miraigroup.jp/ (accessed on 7 March 2023) |
N.Thing, Seoul, South Korea | Salad vegetables |
| Modular hydroponics |
| https://nthing.net/ (accessed on 10 February 2023) |
NextOn, Seoul, South Korea | Special leafy vegetables (caipira, ezatrix, Isabelle), herbs, strawberries, biomaterial |
| Smart hydroponics |
| http://nexton.ag/farm/index.php (accessed on 7 March 2023) |
Farm8, Gyeonggi-do, South Korea | Salad vegetables, special vegetables (herbs, asparagus, minivegetables, etc.) |
| Hydroponics |
| http://en.farm8.co.kr/ (accessed on 10 February 2023) |
SANANBIO, Fujian, China | Leafy greens, fruits, microgreens, herbs, medicinal plants, edible flowers, etc. |
| NFT-DWC hybrid irrigation |
| https://www.sananbiofarm.com/ (accessed on 7 March 2023) |
Vertical Farm, Location | Types of Crops | Production Capacity | Cultivation System | Technical Features | Website |
---|---|---|---|---|---|
80 Acres Urban Agriculture limited liability company (LLC), Ohio, USA | Lettuce, rocket (arugula), kale, basil, microgreens | 90,718.4 kg/year | NFT |
| https://www.80acresfarms.com/ (accessed on 12 April 2023) |
AeroFarms, New Jersey, USA | Baby bok choy, spinach, and micro arugula, broccoli, and kale | 907,184 kg/year | Aeroponics |
| https://www.aerofarms.com/ (accessed on 7 March 2023) |
American Hydroponics, California, USA | Leafy greens, herbs, tomatoes, peppers, cucumbers | NFT, Bato bucket, and gutter |
| https://amhydro.com/ (accessed on 7 March 2023) | |
Bright Farms, New York, USA | Lettuce, butterhead lettuce, baby spinach, basil, chickpeas | Hydroponics |
| https://www.brightfarms.com/ (accessed on 31 May 2023) | |
Gotham Greens, New York, USA | Lettuces, herbs | 136,000 kg/year | NFT |
| https://www.gothamgreens.com/ (accessed on 7 March 2023) |
Plenty Unlimited, California, USA | Lettuce | Hydroponics |
| https://www.plenty.ag/ (accessed on 26 August 2023) | |
Bowery Farming, New York, USA | Leafy greens, lettuce, herbs, tomatoes | Aeroponics |
| https://bowery.co/ (accessed on 26 August 2023) | |
Altius Farms, Washington, USA | Variety of leafy greens, herbs | Aeroponics |
| https://altiusfarms.com/ (accessed on 7 March 2023) | |
Green Spirit Farms, Colorado, USA | Variety of leafy greens, herbs | 38,100 kg/year | Aeroponics |
| https://www.greenspiritliving.com/https://altiusfarms.com/ (accessed on 7 March 2023) |
Vertical Farm, Location | Types of Crops | Production Capacity | Cultivation System | Technical Features | Website |
---|---|---|---|---|---|
PlantLab, Hertogenbosch, Netherlands | Lettuce, basil, mint, coriander, fresh-cut herbs, tomatoes | - | Aeroponics |
| https://plantlab.com/ (accessed on 15 April 2023) |
Jones Food Company, North Lincolnshire, England | Lettuce, cress, komatsuna, hazel, basil, coriander, parsley, mint, dill, rocket, strawberries | 136,078 kg/year | Aeroponics |
| https://www.jonesfoodcompany.co.uk/ (accessed on 7 March 2023) |
Agricool, Paris, France | Strawberries, basil, arugula | - | Aeroponics |
| https://www.agritecture.com/agricool (accessed on 7 March 2023) |
Infarm, Berlin, Germany | Lettuce, tomatoes, cucumbers, herbs, microgreens, mushrooms, leafy greens | - | Aeroponics |
| https://www.infarm.com/ (accessed on 2 June 2023) |
B-Four Agro, Warmenhuizen, Netherlands | Leafy greens, lettuce, kale, spinach | - | Aeroponics |
| https://b4agro.nl/ (accessed on 15 April 2023) |
Byspire, Oslo, Norway | Lettuce, kale, spinach | 50,000 plants/year | Aeroponics |
| https://www.byspire.no/ (accessed on 7 March 2023) |
CityFarm, Stockholm, Sweden | Lettuce, arugula, basil | - | Closed-loop aeroponics |
| www.cityfarmer.org (accessed on 7 March 2023) |
Deliscious, Beesel, Netherlands | Lettuce | - | Aeroponics |
| https://www.deliscious.eu/ (accessed on 7 March 2023) |
Farmers Cut, Hamburg, Germany | Leafy greens, microgreens, herbs, cress | 400 kg/day | Aeroponics |
| https://farmerscut.com/ (accessed on 2 June 2023) |
Future Crops, Poeldijk, Netherlands | Herbs, lettuce, baby lettuce, basil, cilantro, parsley | 77,100 kg/year | Aeroponics |
| http://www.future-crops.com/ (accessed on 7 March 2023) |
BrightBox, Venlo, Netherlands | Lettuce, arugula, basil | - | Aeroponics |
| https://brightbox-venlo.nl/en/ (accessed on 7 March 2023) |
Urbanika Farms, Kraków, Poland | Lettuce, arugula, basil | - | Hydroponics |
| https://www.urbanikafarms.com/ (accessed on 7 March 2023) |
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Share and Cite
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. https://doi.org/10.3390/horticulturae9111229
Kabir MSN, Reza MN, Chowdhury M, Ali M, Samsuzzaman, Ali MR, Lee KY, Chung S-O. Technological Trends and Engineering Issues on Vertical Farms: A Review. Horticulturae. 2023; 9(11):1229. https://doi.org/10.3390/horticulturae9111229
Chicago/Turabian StyleKabir, Md Shaha Nur, Md Nasim Reza, Milon Chowdhury, Mohammod Ali, Samsuzzaman, Md Razob Ali, Ka Young Lee, and Sun-Ok Chung. 2023. "Technological Trends and Engineering Issues on Vertical Farms: A Review" Horticulturae 9, no. 11: 1229. https://doi.org/10.3390/horticulturae9111229