Gross calorific and ash content assessment of recycled sawdust from mushroom cultivation using near infrared spectroscopy

¹ Department of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand
² Department of Agricultural Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand
³ Applied Engineering for Important Crops of the North East Research Group, Department of Agricultural Engineering, Faculty of Engineering, Khon Kaen University 40002, Thailand
⁴ Post Harvest Innovation Research and Development Laboratory, Department of Agricultural Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

^* Corresponding author : ravipat.la@kmitl.ac.th

Abstract

The aim of this study was to use the near infrared spectroscopy for predicting the gross calorific value (GCV) and ash content (AC) of recycled sawdust from mushroom cultivation. The wavenumber was in range of 12500-4000 cm-1 with the diffuse reflection mode was used. The NIR models was established using partial least square regression (PLSR) and was validated via using full cross validation. GCV model provided the coefficient of determination (R²), root mean square error of cross validation (RMSECV), ratio of prediction to deviation (RPD), and bias of 0.90, 445 J/g, 3.19 and 4 J/g, respectively. The AC model gave the R2, RMSECV, RPD and bias of 0.83, 1.7000 %wt, 2.44 and 0.0059 %wt, respectively. For prediction of unknow samples, GCV model provided the standard error of prediction (SEP) and bias of 670 J/g and -654 J/g, respectively. The AC model gave the SEP and bias of 1.84 %wt and 0.912 %wt, respectively. The result represented that the GCV and AC model probably used as the rapid method and non-destructive method.