Precision agriculture: how it can meet future challenges?

A proposal for a standardised definition of precision agriculture was endorsed by the ISPA (International Society of Precision Agriculture) in 2019. Precision agriculture can be defined as a farm management strategy. In practice, it combines data from different sources to guide farmers' decisions. The main goal is to improve practices in order to make agriculture more sustainable, economically, environmentally, and socially.

The challenges of connected agriculture

Precision agriculture is emerging as a vital solution to meeting global challenges. It has to feed an ever-increasing world population. Increasing yields is one response to this food-requirement issue, but it must respect resources and the environment. The use of new technologies makes it possible to reduce the ecological footprint, by optimising practices, particularly concerning inputs. However, adapting doses to conditions and requirements can be a challenge as the necessary investment in new technologies can seem costly. Other hurdles relate to the connectivity of certain white zones, as well as the question of ownership and use of agricultural data which remains a major challenge to be addressed if the benefits of this approach are to be maximised. On the other hand, it is a modern vision which attracts the new generation as it makes working conditions easier and learning faster. As such, it can boost generation renewal in the world of farming.

How does precision agriculture help farmers improve their practices?

Precision agriculture can assist farmers with farm management, production, commercialisation, and knowledge sharing. There are many different applications which make it possible access large amounts of diverse data, process it, and analyse it in order to respond to specific issues. Precision farming assists the agricultural sector with innovative equipment for agricultural production: drones, sensors, robots, connected objects, etc. Through dedicated software or web platforms it can also be an effective decision-making tool. Sharing knowledge through web services, prior to production, is popular with the agricultural community who use various marketplaces, social networks and dedicated exchange platforms. Another important use, for farms with direct outlets (e-commerce), is communicating and connecting with consumers.  

Data used to improve farm performance

Agricultural data are generated by connected objects. These objects, which collect data on plants, animals, and practices, are increasingly common on farms. They are equipped with wireless communication modules that send the data to diverse applications. Connected objects can be:

• Sensors, fitted to agricultural machinery to detect plants, their properties, yields, and humidity levels to trigger irrigation, etc., 
• Connected terminals to control machines and monitor operations etc., 
• Weather stations to collect data on temperatures, rainfall, wind, etc., 
• Drones to collect mapping data (biomass, plant density, rates of chlorophyl, etc.)., 
• Sensors on cattle collars, or in milking robots, to collect data on animal wellbeing, heat, rumination, milk analyses, etc., 
• Silo sensors, to monitor temperatures, load levels, etc.,

The data make up the 5 Vs: volume, velocity, variety, veracity, value. 
Being in control of these 5 pillars is a prerequisite to entering the age of precision farming. An impressive number of technologies are involved, from data collection to use.

How to get started with new technologies?

Application rate modulation is now a well-established practice and is often one of the first measures implemented on arable farms. The yield potential of crops is different depending on species, and soil and climate conditions. Therefore, application rate modulation can be a good solution for optimising input quantities and gross margins, as well as avoiding losses that cause pollution. It means the rate of inputs, fertilisers, plant-protection products, and seeds, for example, can be adapted to requirements and the type of crop. This is possible by creating a modulation map using field data (soil resistivity, storage capacity, pedology, humidity, etc.) and/or past operations (yields, etc.). The map informs on input quantities required per surface unit (pixel or homogeneous zone). 

In practice, application rate modulation is carried out with a tractor and connected agricultural machine, such as a spreader, sprayer, or seed drill. It can be manual, by observing the modulation map in the cab and opening the valves at the right moment, or automatic, if the tractor has a geolocation and guidance system. The automatic system is more precise. Guidance is also a method used in precision agriculture and is not necessary for application rate modulation. To use these systems, the agricultural machines must be compatible and equipped with the necessary devices.

Six steps are essential when implementing precision agriculture on your farm. For application rate modulation, they are:

• Getting the necessary information and training from colleagues, dealers, training centres, etc.
• Preparing the basics, i.e., mapping your fields, essential to using the new technologies.  
• Choosing your data (yield map, biomass map, soil analyses, etc.) and analysing them to create an application map during the crop-growing cycle.
• Working with the method: using either the manual or automatic application-rate modulation technique.  
• Measuring the indicators at the end of the season.
• Improving your practices in accordance with your objectives.

Taking precision agriculture further