Precision technologies provide ways to visualize data as it pertains to different fields from various implements or platforms. All these data are related through different geospatial concepts that help describe these trends of variability. Historical yield analysis reveals spatial trends in yield variability (Maestrini and Basso, 2018) where field productivity is categorized and mapped. These trends from yield monitor data provide an important understanding into the field’s yield response to biotic and abiotic stressors. Digital elevation models provide insight into topographic features throughout each field, showing areas where water frequently moves and pools.

Combined with the topographic wetness index (TWI), which uses slope and contour (elevation change) to quantify wetness, these maps confirm prominent areas that are more prone to potential disease occurrence. In Martinez-Feria and Basso (2020), areas of fields that fluctuated substantially were categorized as unstable and are further identified as hilltops or depressions. These hilltops where drought is more likely to occur can be useful spots for scouting for potential diseases like charcoal rot, as it favors hot and dry conditions. Depressions accumulate more water due to runoff and water routing during precipitation events and are candidates for white mold.

Remote sensing in the optical wavelength visualizes how the plant canopy size differs throughout the field which can indicate potential threats from disease. Thermal imagery captures heat as it’s reflected from plants in response to the ability to transpire water. Plants that reflect more heat are potentially water stressed or affected by disease, while plants that can transpire with sufficient plant available water and absence of diseases have cooler canopies. These images will clearly inform the scouting process during the growing season to visualize parts of the field that are possibly under threats of disease or insect pressure. Output from this proposal will directly impact farmers and agribusiness by providing a novel method to scout more efficiently and effectively in both small and large soybean fields