Artificial Intelligence: How technology is transforming agribusiness

23 March 2021

Health, retail, education, finance and so on: Artificial Intelligence (AI) is increasingly occupying spaces in our society, causing major changes in the markets where it passes. It is no wonder that today Brazil already has more than 700 start-ups with applications in this area, according to a study by the District innovation platform. Now it's the turn of agribusiness. Technology began directly impacting the field a few years ago but has already caused unimaginable advances in efficiency.

In summary, we can say that AI is a field of computer sciences that seeks to create technological solutions with the ability to perform activities in a "smart" manner. This means devising systems and machines that can assimilate with the human mind, reasoning, learning and making decisions.

Despite the recent highlight, technology has been developing since 1955, when the concept of AI was first used by mathematics professor John McCarthy at an American university. In the last 65 years, the theme has been researched by thousands of people, finally reaching applications that impact our daily lives, such as e-commerce, internet searches and video streams.

 

But how does this technology relate to agriculture? How has it been revolutionising the field?

Diagnostics and predictability

One of the main applications of Artificial Intelligence in agribusiness happens in relation to diagnostics and predictability. With the advancement of mechanisation, many mills and farms already have an early degree of automation of agricultural machinery. In this scenario, it was possible to install a series of sensors that began to record the activities of this equipment second by second, collecting hundreds of information on the operations performed - from the simplest, such as machine speed and fuel level, to the most complex, such as hydraulic pressure and deployment of implements.

The AI technology works by processing this data received in the cloud, designing scenarios, anticipating undesirable situations and making recommendations in real time. Some examples of common actions are the warning of the ideal time to perform maintenance on the equipment and the choice of more efficient routes and movements to perform the operations. The goal is always to avoid waste, promote savings and optimise productivity.

Image analysis for problem detection

Identifying a disease or pest in a plant is relatively easy for an experienced agronomist. However, when it comes to very extensive areas, such as sugarcane plantations or planted forests, there are not enough experts to identify these problems manually in an agile manner.

With the aid of drones, Artificial Intelligence has been changing this scenario. The equipment, with the ability to capture images of very high precision, flies over large crops daily. In turn, AI technology allows the images collected to be crossed with images of healthy or sick plants, analysing the conditions of each plant. Thus, reports are issued that identify possible threats, weeds, fungal diseases and even nutritional deficiencies, showing exactly where the problems are on the plantation.

Evaluation of climate phenomena

The traditional weather forecast that helps us to plan everyday life is insufficient for the reality of agriculture. For the success of production, agricultural managers need to be aware of details related to temperature, solar incidence, rain, wind and other climatic phenomena.

In recent years, the accuracy of these measurements has grown greatly thanks to AI, which can analyse local property data in real time, producing safer and more reliable information. Thus, decision-making regarding the cultivation period, irrigation and the use of fertilisers and herbicides, for example, is much simpler and more accurate.

Autonomous vehicles

Just as nowadays we already have cars capable of driving without a driver, soon this reality will also reach the field. Currently, there are vehicles with autopilot and prototypes of machines with "auto steering" that need AI in order not to make mistakes or generate accidents. However, with the advancement of technology, in addition to the popularisation of this type of machine, we will soon have tractors and harvesters capable of acting with even more innovative resources.

These machines may, for example, dose the optimal amount of pesticide to be applied in an area, identify plants ready for harvest or that need disposal, and even change route when there is some external interference as an obstacle that has not been mapped. All on its own, without any human intervention.

The future of AI in agribusiness

Undoubtedly, the impact of Artificial Intelligence in the field is already great, but the expectations are that the process will accelerate and bring more and more results, transforming all stages of agricultural operations with its innovations. Of course, there are still challenges to be overcome. The main one is the connection in the field which, in Brazil, still has a very low percentage when compared to the situation in the United States and Europe, for example. Furthermore, we must not forget the amount of uncertainty surrounding the rural environment, with natural unforeseen events that are still beyond our control. However, the more practical experience AI machines and systems gain, the greater their database and learning capacity, which will allow a better understanding of the field and its needs. National players who want to stay ahead of the agricultural and forestry market will need to be aware of these innovations, investing in technology suppliers and training their teams. After all, the future will be marked by an increasingly digital field, with AI as one of the major protagonists of innovation.