Precision agriculture - Smart Farming

Dossier

Precision agriculture - Smart Farming

Precision agriculture or Smart Farming means that plants (or animals) get precisely the treatment they need, determined with great accuracy thanks to the latest technology. A range of forms of technology are used to this end, including GPS, sensor technology, ICT and robotics. Technology can assist in strategic decision-making at farm level as well as with operational actions at plant level. This allows production to be optimised and means we can work on more sustainable crops. The big difference with classical agriculture is that rather than determining the necessary action for each individual field, precision agriculture allows actions to be determined per square metre or even per plant.

Observation - Diagnostics - Decisions - Implementation

precisielandbouw: land bemesten

A range of technologies are deployed for plant-specific crop actions in Smart Farming such as GPS, sensor technology, ICT and robotics. Crop actions at plant level form the basis for the further optimisation of the production and improved sustainability of the crops.

In order to achieve this, sensors are required to record observational data from the crops and/or the soil (Observation). On the basis of the sensor values, specific software with decision rules and models is used to ascertain the condition of the crop or soil and any deficiencies or needs (Diagnostics) and determine whether location-specific treatment is necessary and if so, which (Decisions). Lastly, the treatment also needs to be performed by means of the correct operation of machines (Implementation). After evaluation, the chain starts again from the beginning. The Smart Farming system is also being developed within livestock farming, particularly dairy farming (Smart Dairy Farming).

Improvements required in Smart Farming

In order to make Smart Farming a widely-accepted notion, various additional improvements and new developments are still needed. The ease of use, the accuracy, the robustness and the business advantages still need to be improved. For that reason, the study focuses on four strategic topics within Smart Farming:

  1. Improvement of the practical applicability of sensor images
  2. The continued development of computation models and decision rules that translate sensor images and data into better cultivation measures for the end users: growers and agricultural contractors.
  3. The improvement of the ICT infrastructure, data interchangeability and standardisation.
  4. Demonstrating the advantages of precision agriculture that the growers and agricultural contractors could enjoy.

The project National Smart Farming pilot project aims on showing farmers the advantages in smart farming. The above mentioned themes will be tested in different cases on farms during four years.

The initial successes achieved through Smart Farming

The first success stories have already been achieved through Smart Farming. Fixed tracks and straight-line systems have been introduced in arable farming and vegetable cultivation businesses, primarily in order to make cultivation measures such as ploughing easier. Section control is possible when using sprayers, thus reducing duplication in spraying activities. Yield maps can be created using measuring equipment on harvesting machines, making it possible to estimate and show the location-specific variations in yield. Crop reflectance measurements obtained through remote and near sensing can also be used to produce maps showing yield predictions. In turn, these measurements can be used as input for location-specific fertilisation and crop protection.

Ongoing research into Smart Farming

The experts at Wageningen University & Research are participating in a variety of research programmes in the field of Smart Farming. The objective of these public-private partnerships is to accelerate the implementation of innovative technologies and to clearly set out their advantages for growers, chair parties and society in general. The partners within the research programme are end users, suppliers, chain parties and knowledge institutes.

Ongoing research programmes