AI and remote sensing advance Brazilian agricultural monitoring

Artificial intelligence and remote sensing technologies are being implemented in Brazilian agriculture to improve crop monitoring and disease management.

In rice cultivation, AI and camera systems are being utilized to identify signs of rice blast disease, caused by the fungus Magnaporthe oryzae, before it spreads. This technology aims to overcome the limitations of traditional manual inspections, which are often slow, subjective, and reactive, potentially leading to significant financial losses and food shortages.

In cotton farming, a partnership between Picsel and Bureau Veritas has developed a hybrid model that integrates satellite imagery with AI to assess crop stand density. This system has reduced the need for physical field entries by 75%, replacing a four-visit protocol with a single mandatory in-person inspection supplemented by remote data. The technology has been deployed across more than 10,000 plots and 800,000 hectares in Brazilian states including Mato Grosso, Bahia, Tocantins, Piauí, Rondônia, and Goiás.