Influence of data preprocessing on the quantitative determination of nutrient content in poultry manure by near infrared spectroscopy

With increasing concern over potential polltion from farm wastes, there is a need for rapid and robust methods that can analyze livestock manure nutrient content. The near infrared spectroscopy (NIRS) method was used to determine nutrient content in diverse poultry manure samples (n=91). Various standard preprocessing methods (derivatives, multiplicative scatter correction, Savitsky-Golay smoothing, and standard normal variate) were applied to reduce data systemic noise. In addition, a new preprocessing method known as direct orthogonal signal correction (DOSC) was tested. Calibration models for ammonium nitrogen, total potassium, total nitrogen, and total phosphorus were developed with the partial least squares (PLS) method. The results showed that all the preprocessed data improved prediction results compared with the non-preprocessing method. Compared with the other preprocessing methods, the DOSC method gave the best results. The DOSC method achieved moderately successful prediction for ammonium nitrogen, total nitrogen, and total phosphorus. However, all preprocessing methods did not provide reliable prediction for total potassium. This indicates the DOSC method, especially combined with other preprocessing methods, needs further study to allow a more complete predictive analysis of manure nutrient content.