According to several projections, the planet's demographic density will continue to increase in the coming decades, a fact that makes it necessary to increase food production to meet population demand. However, there are factors that can make it difficult to achieve production goals, such as the high cost of inputs. Therefore, aiming to increase productivity and reduce costs through optimizing the use of resources and the area available for production, it is necessary to implement alternatives to traditional production control methods. In this aspect, precision agriculture stands out. For precision agriculture to be applied to crops, it is first necessary to observe the spatial and temporal variability of the area, through georeferenced data on the attributes that involve the production system. The correlation of these attributes can indicate sub-regions within the production areas that can receive homogeneous treatment; these fractions of the area can also be called Differentiated Management Units (DMUs). Therefore, the objective of this study was to evaluate the viability of DMU delimitations using data on productivity, slope and vegetation indices, referring to the 2020 harvest for corn cultivation. To this end, geoprocessing of the data obtained using the QGIS software was carried out, so that 3 DMUs were generated for the area evaluated in the study. Thus, the DMUs were compared with the 2021 corn harvest. The results show that the DMUs, produced with data from the 2020 corn harvest, delimited regions with different productivity data in the 2021 harvest, indicating that the possibility of obtaining better parameters in production if differentiated management were carried out in the field, and such planning can be carried out based on the assessments that DMUs allow to be carried out.
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