Well-designed solutions for your

agribusiness.

Transforming Data

into Successful Harvests.

The use of technologies and advanced analyses to identify issues, anomalies, or opportunities in complex systems. In agriculture, this refers to the ability to collect and analyze data in real time or near real time, often with the support of machine learning algorithms and artificial intelligence. This enables the identification of patterns, trends, or issues that may not be easily detected through traditional methods.

Through the use of sensors and technologies, it is possible to accurately understand the existing variability in the area and, when necessary, provide correct and representative guidance for field sampling. Once quality data is collected, it is plotted in map format for possible localized management. This enables greater efficiency and profitability in management.

01. Conductivity Mapping: Mapping of soil electrical conductivity at depths of 0.5 and 1 meter to identify variabilities, define management zones, and establish permanent soil sampling points. 02. Nematode Mapping: Diagnose possible abnormalities through images, enabling the identification and quantification of damage-causing species through the collection of soil and root samples to determine the types of nematodes present in that location and their infestation level. LESION NEMATODE (pratylenchus brachyurus), CYST NEMATODE (heterodera glycines), ROOT-KNOT NEMATODE (meloidogyne spp). 03. Weed Mapping: Digital weed mapping is a process that involves the use of technology, such as drones, remote sensors, GPS, and geographic information systems (GIS), to identify, map, and monitor the presence and distribution of weeds in agricultural areas. This enables weed control and management to be carried out more efficiently and precisely. 04. Compaction Mapping: Through the use of precision agriculture tools, soil penetration resistance sampling is performed when the soil is at Field Capacity, and variabilities and compaction levels in soil layers up to 60 cm are identified. In this way, thematic maps with compaction layer indices are generated.

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