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 (dairy manure, pig manure and chicken manure) was investigated. Animal manure samples were collected from various places in China; organic matter content was determined with conventional chemical analysis, and the FTIR-PAS spectra of animal manures were recorded; probabilistic neural network (PNN) and partial least square (PLS) were applied in the qualitative and quantitative purpose, respectively. The various animal manures exhibited distinctive bands, specifically around 2900-3700 cm^-1, 1200-1800 cm^-1 and 500-1100 cm^-1. Different animal manures show similar spectral appearance, but still there are numerous differences, and PNN model can make successful manure identification; PLS model based qualification of organic matter content in animal manure indicates an excellent predicting results; the second derivative calculation are the best spectral data pre-treatment, and the calibration coefficient (R²), validation error and RPD (ratio of standard deviation to predicted error) are 0.95, 2.45% and 2.52, respectively, which shows that FTIR-PAS can be applied in a wide range of animal manures.