Determination of Bio-Based Fertilizer Composition Using Combined NIR and MIR Spectroscopy: A Model Averaging Approach

Abstract

Application of bio-based fertilizers is considered a practical solution to enhance soil fertility and maintain soil quality. However, the composition of bio-based fertilizers needs to be quantified before their application to the soil. Non-destructive techniques such as near-infrared (NIR) and mid-infrared (MIR) are generally used to quantify the composition of bio-based fertilizers in a speedy and cost-effective manner. However, the prediction performances of these techniques need to be quantified before deployment. With this motive, this study investigates the potential of these techniques to characterize a diverse set of bio-based fertilizers for 25 different properties including nutrients, minerals, heavy metals, pH, and EC. A partial least square model with wavelength selection is employed to estimate each property of interest. Then a model averaging, approach is tested to examine if combining model outcomes of NIR with MIR could improve the prediction performances of these sensors. In total, 17 of the 25 elements could be predicted to have a good performance status using individual spectral methods. Combining model outcomes of NIR with MIR resulted in an improvement, increasing the number of properties that could be predicted from 17 to 21. Most notably the improvement in prediction performance was observed for Cd, Cr, Zn, Al, Ca, Fe, S, Cu, Ec, and Na. It was concluded that the combined use of NIR and MIR spectral methods can be used to monitor the composition of a diverse set of bio-based fertilizers.

Keywords: Near-infrared (NIR) and Mid-infrared (MIR) spectroscopy; bio-based fertilizers; model averaging; partial least square regression; wavelength selection.

Figure 1

Chemical distribution of plants’ essential nutrients (N, P, K and plant-available form of nitrogen), and total elements derived through chemical analysis from bio-solid (red-color circles), composts (orange-color circles), manure (green-color circles) and plants residues (blue-color circles). y-axis shows the concentration of each element with all units in mg kg⁻¹ except N which is in mg g⁻¹ and the number of each element is shown on the x-axis. (a–x) Different properties of the 85 bio-based fertilizer samples.

Figure 2

Mean square error as a function of the number of latent variables (without variable selection for nitrogen content).

Figure 3

NIR pretreated spectrum.

Figure 4

PLS regression coefficients absolute values against each wavelength for nitrogen contents.

Figure 5

Selected bands of wavelengths for nitrogen contents.

Figure 6

Model averaging for NIR and MIR prediction.