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Agriculture of the future

The agricultural sector is facing a number of new issues that have come to life in the past decades. 

Our climate is changing, soils are eroding, the available production area is shrinking. We have to produce increasingly more ‘beautiful’ produce to meet consumer’s expectations without using crop protection compounds, and we have to adapt to a changing food pattern. How do we deal with this? 

Rise of precision agriculture.

The solution is innovation. Farmers have had to change their management strategy or be competed out of the market. A modern-day farmer is an entrepreneur, who has to keep learning and keep improving his business. This approach leads to the development of Precision Agriculture (PA). 

This is a production management strategy that is often discussed in complex terms, but in essence, is very simple: PA is the use of knowledge and technology to better distribute available resources. Its core principle is to apply the right input at the right place at the right time. 

This means two things. We use high-tech sensors to measure a lot of parameters in our fields, stables, processing lines, harvesters, on drones, satellites, any place you can imagine. This data is then combined with the knowledge of the farmer. This second step is important and is sometimes easily overlooked. Farmers know their fields. It is essential that researchers work closely with farmers to interpret the data and adapt the crop management plan accordingly. 

Good examples

Precision agriculture is based on two practical concepts: increasing yield and reducing costs. Yield-increasing strategies include the use of soil sensors to map variability in the field and then apply fertilizers to the areas where it is most useful. 

This means you will get more ‘bang for your buck’, or better yields for the same amount of fertilizer. Another option is to change your seeding distance based on soil fertility, with the same result in mind. An example from livestock management is the use of sensors that monitor animal behaviour to identify anomalies such as sickness.

Classic examples of cost reduction include the use of drones to detect and map disease in the field. This information can then be used for spraying only certain areas, reducing the amount of crop protection compounds needed. 

The same goes for the aforementioned example of fertilizing more on certain areas of the field. Farmers could also just reduce their fertilization on areas where it has little use, reducing their cost while still obtaining similar yields. This shows that most PA strategies combine yield increase with cost reduction, which is, of course, the dream scenario. 

Think of using thermal cameras on drones to map water status in the field. Farmers can then tackle areas that are too wet, by increasing drainage, and increase irrigation in areas that are too dry, hopefully leading to a reduction of water use and an increase in yield. 

Adoption rate of precision agriculture

The examples above make PA sound like a miracle solution. However, the percentage of farmers actually adopting PA strategies is quite low. This is due to several major hurdles. 

First, many of these sensors are both expensive and complex. Secondly, farmers often do not believe the benefits of these sensors have been shown sufficiently in real farms. This makes them rightfully hesitant to invest in this technology. 

It is therefore essential that researchers work in close collaboration with innovative farmers. These farmers should ideally have larger-scale operations, which allows them the freedom to use part of their fields or livestock to test PA practices, in cooperation with academics. Through constant feedback and improvement, it is possible to build strong case studies that can be used to convince the rest of the sector. 


Photo credit: Pixabay