The Open Crop Manager Platform for Crop Production and Scouting

The Open Crop Manager (OCM), is a data platform for securely collecting soybean production and scouting information at the field scale while enabling the end user to permit how researchers may use data.

The OCM can integrate production field locations, management records, yield outcomes, and field condition reports. The OCM emphasizes the principle that: If it comes from your field, or you create it, it's your data – you control them and what they can be used for.

The end user's willingness to share data with the larger research community enables the development and validation of additional farmer production and management support tools.

Currently, the OCM has the following capabilities:

• Record field location and access instructions for collaborators.
• Record management information, such as seed choice, tillage, and residue management, and any treatments applied.
• Record yield outcomes, including yield files of any format.
• Record and visualize geo-referenced stressor occurrences, including images.
• Receive diagnostic aid for disease identification.

During testing in 2022 and 2023, just under 8,000 scouting reports and almost 8,000 images were obtained. In the 2024 season, we will also have new scouting apps (iOS and Android) that complement the OCM platform, enabling seamless data integration when using either the platform or the app.

The OCM's new tools provide critical information for improving soybean sustainability and profitability, such as the visualization of stressor occurrence in field summaries (Figure 1) and a disease diagnostic aid tool. We are further working on tools for precision scouting, expansion of our monitoring effort, and algorithms for improved disease assessment from images. We also have the schematics for integrating similar tools for corn and wheat.

An example interactive map of the stressors distribution and severity using the Open Crop Manager. Stressors locations (circles) are shown in a field and colored by severity, with yellow being the least severe and red being the most severe. The individual stressors can be observed when the mouse hovers over a single point (Image Source: M. DePriest, Penn State).

If you are interested in learning more about the OCM data platform or testing it in your field, please contact Dr. Paul Esker at pde6@psu.edu. Our team offers training and customer support to ensure that end users are comfortable with the platform, its offerings, and how their data are safe and secure. For further information about training on the OCM, please contact Miranda DePriest at mnd20@psu.edu.

Acknowledgments: We thank our funding sources for the development of the Open Crop Management and soybean production and management platform, including the Penn State Institute of Computational and Data Sciences SAFES-RISE program, The Penn State Center for Socially Responsible Artificial Intelligence, the North Central Soybean Research Program, and the Pennsylvania Soybean Board.