109-9 Web-Based Statistical Tools and Data Visualization for the IPNI North American Soil Test Summary.

Poster Number 155-1207

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry & Statistical Computing Poster

Monday, November 7, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Quentin Rund1, Ryan Williams1, Elle Williams1 and T. Scott Murrell2, (1)PAQ Interactive, Monticello, IL
(2)International Plant Nutrition Institute Americas Group, West Lafayette, IN
Abstract:
The International Plant Nutrition Institute (IPNI) recently completed the 2015 North American Soil Test Summary. This summary offers a snapshot view of soil test levels in 2015, but also provides a comparison to the previous three summaries which were completed in 2001, 2005, and 2010.

Private and public soil test laboratories throughout North America submitted complete frequency distributions of soil test results for phosphorus, potassium, sulfur, magnesium, zinc, chloride and pH. These distributions are presented in the Summary in chart format, along with charts of median test values and changes in test values over time, for states and provinces.

A major advancement of the 2015 summary was the creation of the Soil Test Summary website and incorporation of Web-based statistical analyses using the R Statistical package. The Soil Test Summary website allows users to create their own queries using intuitive menus and an interactive map where users can select the states or regions they wish to view data for. The user’s query is then run on the web server and a statistical report is created using SQL database technology coupled with the R statistics program and the Google Charts chart creation engine.

The incorporation of R into the Soil Test Summary website means analyses can be performed in real-time using robust statistical analysis routines. These include analysis of fertility level distributions, median soil test values and trends over time for a state, region or a user-defined custom region.

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry & Statistical Computing Poster

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