FOR IMMEDIATE RELEASE

Newly Launched: Purdue Agricultural Data Engine (PADE) Tool to Help Farmers Realize Value in Data

Figure 1. Image of the PADE interface

Despite agriculture becoming more data-driven and data-enabled with advancements in Internet of Things devices, cloud computing, and intelligent machines, a weak link remains: the end user, i.e. farmer. A majority of farmers lack training in data management software for realizing the value of information locked in the data. Commercially available data management solutions have seen limited success because farmers often have reservations about how the data may be used after it has been shared with those beyond their trusted circle.

To address the challenges associated with agricultural data management, a Purdue University associate professor of agricultural and biological engineering, Dharmendra Saraswat, has launched an innovative web-based tool named the Purdue Agricultural Data Engine (PADE).

PADE uses a lean user interface for uploading data and then allows for understanding trends, patterns, or spatial variability in it through various algorithms provided within the tool. Users are able to interactively create charts, explore effects of various methods to fit data into an appropriate mathematical model, draw areas of interest in a farm field to obtain information contained in the drawn area, and import soil data from the NRCS soil data mart to visualize soil spatial variability and draw any association with variable yields. They can also create management zones using yield data and access weather data for the entire United States. To help untrained users, PADE offers smart prompts for uploading appropriate data. It enables learning-on-the-go by directing users to external websites for further education.

PADE is available to public users (“un-signed users”) as well as Purdue employees (“signed users”). The tool can be accessed at https://precision.ag.purdue.edu/ Dr. Saraswat invites you to explore PADE and offer him feedback for fixes and improvements.