Precision agriculture is an agricultural management system that allows for the controlled and precise exploitation of inputs. Combining productivity with reducing environmental impact, it is expanding around the world and promises to grow 61% by 2026, moving more than R$ 40 billion and boosting agtechs.
This new approach is considered innovative for increasing profitability and, at the same time, reducing costs. impacts on the environment. And precision agriculture reveals itself even more promising when combined with artificial intelligence.
Using advanced technologies such as remote sensors, GPS and data analytics, the combination is helping to address the challenges of modern agriculture. Check out what this concept is, what its benefits are and how artificial intelligence can be an ally in this process.
Precision agriculture: concepts and benefits
Precision agriculture is an approach that uses advanced technologies to collect data and make more accurate decisions in agricultural production. One of its biggest elements is the use of GPS, which allows the exact location of machines and equipment and the creation of productivity maps, identifying areas of highest and lowest yield, assisting in management.
Drones, which are more common in the field today, are also widely used in precision agriculture to fly over crops and capture high-resolution images, which help identify problems such as pest infestations or nutritional deficiencies in plants.
With this data, farmers can take targeted actions, applying inputs only where they are truly needed, thus reducing the use of fertilizers and pesticides.
Furthermore, another tool widely used in precision agriculture are sensors to collect real-time information about soil, humidity, temperature and other environmental factors. They provide continuous monitoring of agricultural conditions and help optimize resource use, avoid waste and maximize productivity
In summary, we can say that precision agriculture brings a series of benefits, because it helps to minimize costs and negative environmental impacts, in the same way that it improves production efficiency, increasing crop productivity.
Applications of Artificial Intelligence in agriculture
Precision agriculture represents the future of sustainable production, and can be even more promising when it is combined with artificial intelligence (AI). See below the main applications of this technology in agriculture:
- Intelligent resource management
Using data from sensors, satellite images and predictive models to optimize the allocation of agricultural resources such as water, fertilizers and pesticides, intelligent resource management is driven by Artificial Intelligence.
With continuous analysis carried out in real time, it is possible to identify the specific needs of plantations and adapt the application of resources, minimizing waste and environmental impacts.
- Crop forecast
To assist farmers with harvest planning, logistics and marketing, AI algorithms analyze historical data, current weather conditions and other relevant factors to make accurate predictions about future production.
- Detection of plant diseases
With machine learning algorithms and large-scale data analysis, AI can offer valuable insights to farmers, such as detecting plant diseases.
The algorithms analyze images and identify patterns that indicate the presence of pathogens in plants, leading the farmer to take quick and precise intervention.
The integration of precision agriculture with Artificial Intelligence also brings some additional benefits, such as the identification of complex patterns and insights for crop management, the automation of decisions, allowing faster and more efficient actions, among other resources that improve productivity and sustainability in agriculture.
Conclusion
The combination of precision agriculture with Artificial Intelligence is revolutionizing work in the field and represents an important advance towards more efficient, productive and ecologically sustainable agriculture. With them, farmers increase operational efficiency and optimize their processes and resources, making production more sustainable.
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