Insight Focus
AI is reshaping Brazilian crop production and processing. Smart systems enable grain farmers to forecast harvests, combat pests and optimise nitrogen application. In cotton processing, automated vision technology identifies impurities, increasing productivity by 30% and commanding premium prices.
Brazilian agriculture is becoming an epicentre of transformation driven by artificial intelligence (AI). In grain farming, the technology has been used to predict productivity and optimise the use of inputs. In cotton processing, AI has provided benefits, especially in terms of reducing losses.
There is no shortage of examples of the application of technology to achieve new competitive advantages in Brazilian agribusiness. This article will explore the main examples below.
AI Transforms Soybean Pest Control
One of the most significant advances is in pest control. Smart traps that use sensors and cameras to identify pests are being adopted across more than 50,000 hectares (ha) of soybean fields in Mato Grosso and Bahia. These devices send data to systems that identify the type and quantity of insects captured, as well as recognise infestation patterns over time.
Soybean crop affected by the Spodoptera sp. Pest
Based on these analyses, the system indicates the ideal time to apply pesticides and even warns when application can be avoided. As a result, it has been possible to reduce the use of insecticides against the Spodoptera sp. pest, which causes damage to soybean crops, by more than 20%.
Source: Conab
AI has also helped farmers predict crop yields and the best time for harvesting. In soybean cultivation in the south, AI models called LSTM neural networks are being used. LSTM learns from data from previous harvests and then uses satellite and weather information to make predictions.
These models can estimate crop yield with a small margin of error, between 0.2 and 0.42 tonnes/ha. It is possible to know 30 to 45 days in advance what the harvest will be like. This precision allows producers to plan better, anticipating decisions about selling and transporting the harvest. This brings more security and a competitive advantage.
Soybean harvest
Smart Sensors Cut Nitrogen Waste in Corn Production
In cornfields in the main producing regions, the combination of optical sensors and AI has made the application of nitrogen, an essential fertiliser, more precise. This is important, especially considering that international fertiliser prices remain elevated.
Source: World Bank
The sensors, installed on agricultural equipment such as harvesters, capture information from the plants in real time, recording parameters such as leaf colour—an indicator of the amount of nitrogen the plant is absorbing.
This data is processed by AI algorithms that define the ideal fertilizer dose for each area of the crop. As a result, an improvement of over 30% in the efficiency of nitrogen use has been observed, ensuring greater utilisation of the input and better crop yield.
Source: Conab
AI Detects Cotton Contaminants With 95% Accuracy
In cotton processing, computer vision models based on YOLOv5—a type of AI capable of distinguishing objects in images and videos in real time—are already achieving up to 95% accuracy in identifying contaminants, such as leaves and other impurities.
Bales of cotton in Mato Grosso
During this process, the fibres pass through cameras installed on the processing lines, which capture images at high speed. These images are sent to a computer, where the model analyses each frame and automatically identifies impurities.
Based on this detection, automated systems can separate clean material from contaminated material, ensuring greater purity and uniformity of the product. Not surprisingly, industries that have adopted this type of intelligent sorting have recorded increases of up to 30% in productivity and a reduction in losses.
Source: Comex
In a market that rewards quality, including in the context of exports, the ability to automatically classify batches by variables such as fibre thickness and strength allows for higher prices. The system objectively proves the quality of the product, allowing superior batches to be directed to buyers willing to pay more.
With the use of these tools, Brazilian agribusiness will be able to take new leaps in productivity. It is worth remembering that AI is already part of the daily routine of the most profitable farms—and should reach more rural producers.
