Artificial growth conditions
Here, artificial growth conditions cover greenhouses and artificial growth media (including aeroponics, hydroponics and other growth media that are not just open-field soil). In greenhouses and when using or making artificial growth media, the environment is much more controllable than in the open field. This, in turn, creates a broad range of modelling and automation possibilities which all require data input.
- Greenhouses
Smart greenhouses are advanced agricultural systems that integrate technology to optimise the growing environment for plants. These greenhouses use sensors, automation and data analytics to monitor and control various environmental factors such as temperature, humidity, light and carbon dioxide levels. By continuously collecting data, smart greenhouses can adjust these parameters in real-time to create optimal conditions for plant growth. Devices or systems for heating, ventilating, regulating temperature, illuminating or watering/irrigation in greenhouses and controlling these systems allows for remote monitoring and management, enabling farmers to make informed decisions and respond quickly to any changes or issues.
Sensing and Imaging
Advanced sensors and imaging systems in greenhouses continuously monitor environmental parameters, such as temperature, humidity, carbon dioxide levels and light intensity to maintain optimal growing conditions. Infrared cameras mounted at canopy height, for instance, can detect uneven heat distribution, prompting automatic shade adjustments to prevent crop stress. Spectral sensors can measure leaf reflectance to gauge plant health, signalling nutrient imbalances before visual symptoms appear.
Data processing and AI
In greenhouse operations, data platforms aggregate sensor readings, historical climate records, and growth models into round-the-clock AI-driven decision tools. These algorithms predict disease outbreaks by recognizing subtle shifts in microclimate or foliar spectral signatures, advising on preventative sprays only where needed and reducing the use of pesticides while minimizing crop losses. They can also optimize lighting recipes by varying red, blue, and far-red LED ratios and intensities to accelerate flowering, germination or vegetative growth at key stages. As a result, growers can move from reactive troubleshooting to proactive crop management, while lowering their use of chemicals and energy costs.
Automation and robotics
Robotic systems in greenhouses take over repetitive tasks such as transplanting, pruning and harvesting. Autonomous carts transport trays along rail grids, while robotic arms fitted with soft-grip end-effectors selectively harvest ripe fruits or clip spent foliage. Conveyor belts and gantry robots handle potting and media replacement, synchronizing with crop schedules to minimize manual labour. This integrated automation ensures consistent plant handling, improves worker safety and allows round-the-clock operation in a fully controlled environment.
Vertical farming
Vertical farming is a method of growing crops in vertically stacked, controlled‐environment structures such as towers or shelving systems, using hydroponics, aeroponics or soil-based media. By optimizing light, temperature, humidity and nutrient delivery, it maximizes yield per square meter all year round, while drastically reducing water use and land requirements compared to traditional agriculture. Although not categorised as digital agriculture as such, the environment is usually extremely well monitored and controlled by various digital technologies. Plant specific levels of humidity, fertilisation, light and temperature lead to maximum yield with minimum input.
Solar energy and energy efficiency
Greenhouses use a significant amount of energy. Various measures can be taken to reduce their energy consumption, ranging from the use of renewable energy sources such as solar energy to better energy-management. While this may not be classified as digital agriculture, it generally includes some digital component to enhance efficiency and leads to more sustainable cultivation.
- Growth media
Cultivation in the absence of soil. Plants can grow in air or liquid, e.g. nutrient solutions (hydroponics/aeroponics/soilless) or in growth substrates. Growth substrates in agriculture refers to the various materials used to support plant growth, providing a stable environment for roots and supplying essential nutrients, water and air. Examples of substrates are coconut coir, rockwool, perlite, vermiculite, lava rock, saw dust and expanded clay pebbles. Unlike natural soil, growth media can be tailored to specific plant needs and growing conditions, making them ideal for controlled environments such as greenhouses and hydroponic systems.
Sensing and imaging
In hydroponic and aeroponic systems, sensor arrays measure nutrient solution EC (electrical conductivity), pH, dissolved oxygen and temperature to ensure roots receive the correct balance of water and minerals. Imaging systems, such as root-zone cameras or transparent troughs, monitor root development, detecting signs of oxygen deprivation or pathogen invasion. A submerged camera, for example, can reveal root browning early, prompting an immediate increase in aeration or nutrient adjustment.
Nutrient control in growth media
Precise nutrient control in growth media ensures that plants receive the exact balance of minerals they need for optimal photosynthesis, root development and overall health. Maintaining correct pH and electrical conductivity prevents nutrient lockout and deficiency symptoms, which can severely stunt growth or reduce yields. By closely monitoring and adjusting nutrient concentrations, growers maximize resource efficiency, reduce waste and achieve more consistent crop quality.
Automation and AI
Data platforms collect real-time readings from nutrient tanks, environmental sensors and plant growth metrics, integrating them with crop models to drive AI recommendations. Machine learning can create dynamic feeding schedules, adjusting nutrient concentrations based on plant developmental stage, water uptake rates and prior growth responses. In aeroponic towers, AI may modulate mist cycles and droplet size to optimize oxygenation and nutrient absorption for leafy greens. This predictive management reduces waste, avoids nutrient lock-out and improves uniformity across stacked cultivation racks.