Effects of Sample Processing on Ash Content Determination in Solid Cattle Manure with Visible/Near-Infrared Spectroscopy

Abstract

Visible and near-infrared (VisNIR, 350-2500 nm) diffuse reflectance spectroscopy (DRS) may be a useful tool for determining crude ash content of solid cattle manure. However, the effect of sample preprocessing protocols on the predictive ability of the VisNIR-DRS models is unknown. In this study we explored the effects of drying and milling on the prediction of crude ash in feedyard manure using VisNIR-DRS. Samples (n = 120) of beef manure from open lots were evaluated for ash content by dry oxidation and then subjected to four preprocessing treatment protocols: oven-dried and milled, air-dried and milled, oven-dried and not milled, and air-dried and not milled. Each treatment protocol was used to calibrate partial least squares regression models for prediction of ash content by VisNIR-DRS. Two thirds of the samples were randomly selected to build calibration models, and the remaining third was used for validation. The root mean squared deviation (RMSD) and the ratio of the standard deviation over the RMSD (RPD) for each treatment were assessed to determine the best pretreatment protocol for ash determination of manure. The first derivative of the reflectance from air-dried, unmilled samples consistently generated the best predictive models with an RMSD of 5% crude ash (d.b.), an RPD of 2, and a bias of 0% crude ash (d.b.).