Recording systems for monitoring plant growth

One question that many producers of agricultural products ask themselves again and again is probably: 'How can I improve the cultivation process to increase my production and product quality?'

To adapt crops to new conditions such as climate change, water scarcity and extreme weather, more and more varieties are being developed and bred that need to be monitored and analysed. In the future, it will be essential for producers to use a plant monitoring system that records a wide variety of sensor data on the water or energy balance of the plants in parallel to information on the growth process.

This involves questions such as: 'What happened?' and 'Why did it happen?' or 'What will happen?' Based on this data, decisions can be made on how to optimise plant growth in greenhouses or plant factories. This will become increasingly important in the future as fruits and vegetables are grown in nutrient solutions and the growing can then also take place in the city, in buildings, on roofs and in halls.

Monitoring from seeding to harvesting

For some time now, there has been a lot of research into which nutrient solutions ar best for which plants and where and how they grow.

The basic data for this is provided by camera-based recording systems for high-resolution video recordings that observe plants in their growing environment and document the growth process.

For example, a stereo image processing system consisting of two cameras with parallel optical axes mounted on a sliding rail to extend the field of view of the beds, can be used as data source. The system continuously records images that are used to determine plant characteristics.

Image processing algorithms can subsequently determine geometric features such as leaf area, plant height, plant volume and equivalent diameters and derive plant growth curves. Changes such as wilting, the appearance of spots, dicolouration, etc. can also be recorded and assigned in ths way.

However, developments in the field of smart farming go far beyond this. Camera-based systems can use a combination of machine vision and deep learning to recognise when fruit or vegetables are ripe and help robots harvest them.

By using a vision system, data is obtained not only about the harvested plants, but also about those remaining in the field.

Image processing systems help producers of agricultural products to harvest all plants always at the optimal time. The harvesting system in this case would harvest only the plants that are ready for a particular job, and at the same time transmit data about the plants remaining in the field, which can then be correlated with the weather forecast to estimate when the rest of the plants will be ready to harvest, to pick all the plants at the perfect time each time.

Your individual solution

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