2026-09-22T19:05:38Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/129648 2025-10-20 col_2142_5131 com_2142_5130

https://hdl.handle.net/2142/129648 Nowicki, Michael Joseph Quantifying soil particulate organic matter using image analysis Rapid and cost-effective quantification of soil organic carbon (SOC) fractions that are responsive to management will improve soil health assessment and associated decision support tools. The particulate organic matter (POM) fraction of SOC is of interest due to its sensitivity to management and significant contributions to soil structure and biological integrity. Conventional laboratory methods for assessing POM include size and density fractionation, processes that are laborious and time-consuming. This study evaluated the potential for a rapid image-based POM quantification method. This novel approach only requires lightly prepared samples to be saturated then placed in a table-top imaging box, where a series of images are taken. Preliminary tests were performed on a series of assembled soil samples with POM contents ranging from approximately 6.5-50 g/kg soil. A series of images enabled differentiation of POM from surrounding microaggregates using image analysis. Illumination was provided by Light Emitting Diodes (LED) spanning limited sections of visible to near-infrared (Vis-NIR) spectrum. Estimates of POM area were regressed against known concentrations. Initial regressions were performed on separate POM types and size fractions. Grass residue (POMG) model fits of R2 = 0.83, 0.91 and 0.90 for estimates POM< 0.75 mm, 0.5 to 1 mm, and 1.0 - 2.0 mm. Broadleaf POM (POMB) estimates R2 = 0.90, 0.89 and 0.69 for size fractions 0.1 - 0.5 mm, 0.5 - 1.0 mm and 1.0 - 2.0 mm. This study found the predictive power decreased with the inclusion of multiple POM size fractions, with model fits of R2 = 0.53 for grass, and R2 = 0.38 for broadleaf. A regression combining broadleaf and grass lowered predictive strength further with R2 = 0.31. Despite a decline in fit for combined size sample estimates, there remained a promising capacity to reproduce estimates for size medium (average particles) for both POMG and POMB fractions. Particulate Organic Matter Image Analysis Soil Analysis Wander, Michelle M Grift, Tony Ugarte, Carmen 2024-08 2024-07-16 application/pdf en text Thesis Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-08-01 The student, Michael Nowicki, accepted the attached license on 2024-07-15 at 16:57. The student, Michael Nowicki, submitted this Thesis for approval on 2024-07-15 at 17:12. This Thesis was approved for publication on 2024-07-16 at 10:40. DSpace SAF Submission Ingestion Package generated from Vireo submission #21124 on 2025-10-19 at 19:52:01 Copyright 2024 Michael Nowicki M.S. Thesis Natural Res & Env Sciences University of Illinois Urbana-Champaign Natural Res & Env Sci