Using innovation to predict the productivity of cultivations

Fertilisation, plant protection and pruning are key aspects of tree cultivation, and they can now be carried out using precision agriculture systems. These systems can provide data for predicting the productivity of a crop, while also helping the farmer to manage and schedule practices like those mentioned above. Systems also used in Greece and installed on tractors and tractor attachments can record and predict productivity at every point in a field, creating management zones for field tasks. These systems include cameras and advanced optical recognition models that monitor the robustness and productivity of cultivations.

Using artificial intelligence, the aforementioned systems carry out high-speed analyses of images collected in the field and identify the amount of fruit on each tree, leaf area, and the symptoms of pests, malnutrition and phytotoxicities. Systems like this are generally supplied as off-the-shelf solutions that are installed on tractors and tractor attachments.

These technologies are also associated with sensors that collect data during the spraying process. This process enables selective spraying, directing and adjusting the volume of spray with precision. With this system, producers can see in real time how much fertiliser is being applied to their field at a given moment. This ensures that every spot on the field receives the necessary amount of fertiliser, helping farmers to increase production and optimise the quality of their product, while also reducing costs and protecting the environment from excessive fertilisation.

Use of such technologies and systems is quite widespread in other countries, and mainly in the USA, where parcels are very large and farmers are more familiar with such systems, having known for years their benefits for crops and the environment, but also for reducing production costs. Targeted use of chemicals in the field can also improve the quality of the crops produced, as plants receive the precise amount of agricultural inputs needed, eliminating waste and reducing environmental impact.