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Reasoning Geo-Spatial Neutral Similarity from Seismic Data Using Mixture and State Clustering Models Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Using Conditional Probability and a Nonlinear Kriging Technique to Predict Potato Early Die Caused by Verticllium Dahliae

Authors : Luke Steere, Noah Rosenzweig, William Kirk

Published in: Geographical Information Systems Theory, Applications and Management

Publisher: Springer International Publishing

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Abstract

Verticillium dahliae is a plant pathogenic fungus that can be devastating to commercial potato production. Potato growers in the state of Michigan have experienced yield declines and decreased marketability as a direct result of the persistence of V. dahliae in soil. A team of researchers at Michigan State University conducted a soil evaluation using geostatistics and geographic information systems (GIS). The use of a nonlinear Kriging method allowed the team to predict where infection may occur. Nonlinear Kriging is a useful tool for creating conditional probability maps based on a threshold, which can be built into the equation. Verticillium dahliae has an inoculum threshold needed to cause infection in a potato plant. Using this threshold, maps can be created based on a probability of any point in space being greater than the threshold. The methods used in this paper show how geostatistics can be a valuable tool for commercial growers.

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Metadata
Title
Using Conditional Probability and a Nonlinear Kriging Technique to Predict Potato Early Die Caused by Verticllium Dahliae
Authors
Luke Steere
Noah Rosenzweig
William Kirk
Copyright Year
2016
Book
Geographical Information Systems Theory, Applications and Management

Print ISBN: 978-3-319-29588-6

Electronic ISBN: 978-3-319-29589-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-29589-3_9

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