Predicting the heating value of solid manure with visible and near-infrared spectroscopy

Abstract

Visible and near-infrared spectral data were used to predict the higher heating value (HHV) and dry, ash-free HHV (HHVdaf) of solid manure samples collected from cattle fed diets containing wet distillers grains plus solubles (WDGS) in 0%, 15%, 30%, 45%, and 60% dry matter concentrations. The HHV was determined by isoperibol bomb calorimetry and the HHVdaf was calculated from an equation based on the HHV and proximate analysis. Spectral models were developed in “The Unscrambler” software. The spectral models based on all treatments with random samples withheld for validation predicted the HHV with excellent reliability within 1.7%; RMSD=60.19calg−1 (108Btulb−1), RPD=2.29 (excellent), and bias=−15.29calg−1 (28Btulb−1), using five PLS factors and identifying 129 important wavebands. Accounting for estimated N and S content reduced the predictive accuracy of the spectral models by 0.1% with an RPD=2.28 (excellent). Spectral models based on all treatments with random samples withheld for validation predicted the HHVdaf with acceptable reliability within 2.0% with an RMSD=96.17calg−1 (173Btulb−1), RPD=1.17 (acceptable), and bias=−19.83calg−1 (−37Btulb−1), using five PLS (partial least squares) factors and identifying 29 important wavebands. Spectral models reliably predicted the HHV of feedlot manure with accuracy well under the 5% error margin tolerated in practical applications such as feedlot manure gasification.