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MullinsThesisV1ofETDedits
Embargoed Access, Embargo ends: 10/08/2027
Thesis
USING LOCAL SPECTRAL LIBRARIES TO CREATE PREDICTION MODELS FOR SOIL PHYSICAL PROPERTY ASSESSMENT IN WASHINGTON STATE
Master of Science (MS), Washington State University
2025
Abstract
Soil compaction is a major and extensive problem within agriculture, and we do not have standardized way to measure compaction or its effects. We can use tools such as penetrometers
for rapid assessment of soil compaction; however, these measurements require data on soil
organic carbon, clay content, and water content. This study was conducted to set the groundwork
for visible and near infrared (VisNIR) as well as mid-infrared (MIR) spectrometers to measure
multiple soil properties with one measurement. To evaluate MIR spectroscopy, I evaluated the
impact of local vs. statewide spectral libraries for predicting organic carbon and clay content
using lab analyzed soils from Washington State University and a larger statewide dataset derived
from the Kellogg Soil Survey Laboratory. Additionally, partial least square models were
compared with commercial Quant II software. To assess VisNIR spectroscopy, models were built
using partial least squares regression and tested with and without external parameter
orthogonalization, which is a method to correct for soil moisture. MIR prediction models are
accurate at organic carbon prediction at all levels although the accuracy decreases from statewide
to local soil samples. Bootstrapped R code models outperformed those developed with external
parameter orthogonalization treatment improved prediction accuracy for wet-intact samples,
vi
although further testing is needed to address variability caused by moisture content. Ensuring
each spectral library has a wide range of soil properties will improve prediction models. VisNIR
prediction models are accurate for both clay content and organic carbon at a local level. The
development of robust, regionally adaptable spectral libraries and standardized scanning
protocols is essential for scaling these approaches to statewide applications.
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Details
- Title
- USING LOCAL SPECTRAL LIBRARIES TO CREATE PREDICTION MODELS FOR SOIL PHYSICAL PROPERTY ASSESSMENT IN WASHINGTON STATE
- Creators
- Michael Dylan Mullins
- Contributors
- Haly L Neely (Advisor)Markus Flury (Committee Member)Gabriel LaHue (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Department of Crop and Soil Sciences
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Number of pages
- 84
- Identifiers
- 99901297395801842
- Language
- English
- Resource Type
- Thesis