Rapid fertilizer nutrient analysis enabled by handheld LIBS (hLIBS) and an intelligent Euclidean distance prediction...

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Agricultural Science

Background:

• Conventional fertilizer nutrient analysis is slow and labor-intensive, hindering rapid on-site assessments.
• Accurate and timely nutrient content determination is crucial for optimizing fertilizer application and promoting sustainable agriculture.

Purpose of the Study:

• To develop and validate a rapid, on-site method for quantifying nitrogen (N), phosphorus (P), and potassium (K) in compound fertilizers.
• To assess the performance of laser-induced breakdown spectroscopy (LIBS) coupled with partial least squares regression (PLSR) for this application.

Main Methods:

• Utilized laser-induced breakdown spectroscopy (LIBS) to generate emission spectra of compound fertilizers within the 190-950 nm range.
• Constructed a feature matrix from spectral data using a Euclidean distance algorithm.
• Developed a partial least squares regression (PLSR) model for quantitative analysis of N, P, and K content.

Main Results:

• The LIBS-PLSR model demonstrated high accuracy for N, P, and K detection, with coefficients of determination (R²) ranging from 0.9541 to 0.9828.
• Root mean square errors (RMSE) were low (0.44-1.02 g kg⁻¹), and residual predictive deviation (RPD) values indicated good predictive ability (4.64-7.46).
• Prediction errors for all nutrients were below 6%, confirming the method's precision.

Conclusions:

• The developed LIBS method provides a rapid, efficient, and accurate solution for on-site analysis of N, P, and K in compound fertilizers.
• This technique has significant potential for use by fertilizer producers, regulators, and agricultural agencies to enhance nutrient management.
• The method supports sustainable agricultural practices by enabling real-time nutrient detection and improving fertilizer use efficiency.