Characterization of animal manures using mid-infrared photoacoustic spectroscopy

The feasibility of using Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) for rapid characterization of animal manures was investigated. Animal manure samples were collected from various places in China, and probabilistic neural networks (PNN) and partial least squares (PLS) were initially applied in the qualitative and quantitative analysis of animal manures, respectively. The animal manures exhibited distinctive bands, specifically around 2900–3700 cm−1, 1200–1800 cm−1 and 500–1100 cm−1. There were numerous differences in the spectra of different animal manures, and manures were successful identified by PNN model; organic matter contents in animal manure were well predicted by PLS model, and the calibration coefficient (R2), validation error and RPD (ratio of standard deviation to predicted error) were 0.93, 2.38% and 2.58%, respectively, suggesting the potential application of FTIR-PAS for the fast characterization of animal manures.