Elemental composition and moisture prediction in manure by portable X-ray fluorescence spectroscopy using random...

Area of Science:

• Agricultural Science
• Environmental Science
• Analytical Chemistry

Background:

• Accurate manure elemental composition is vital for farm nutrient budgets and environmental risk assessment.
• Portable X-ray fluorescence (PXRF) offers a rapid, cost-effective, and hazardous waste-free method for elemental analysis.
• Sample moisture significantly impacts X-ray-based elemental determinations in manure.

Purpose of the Study:

• To quantify the effect of moisture content on elemental analysis of livestock manure using PXRF.
• To develop predictive models for manure moisture content.
• To establish methods for correcting elemental concentration data for moisture effects.

Main Methods:

• Manure samples (n=40) were adjusted to five moisture ranges (<10% to 60-70%).
• Samples were analyzed using PXRF (180s scan, vacuum, no filter).
• Random forest regression was employed for calibration (n=200) and validation (all data, cross-validation, external validation).

Main Results:

• Moisture negatively affected elemental determination, but the back end of the spectrum (14-15 keV) showed strong moisture prediction (r² = .98).
• Random forest regression significantly improved accuracy (r² > .90 for P, K, Mg; r² > .98 for Fe) compared to traditional methods.
• Accurate elemental measurements were achieved in both dried and moist manure samples.

Conclusions:

• PXRF can accurately determine elemental concentrations in livestock manure across a wide range of moisture levels.
• The developed methods overcome moisture-related challenges, expanding PXRF applications in agriculture and environmental monitoring.
• This facilitates in situ elemental analysis for improved farm management and environmental protection.