Evaluation of moisture content and higher heating value of bagasse using Fourier transform near infrared spectroscopy
Main Article Content
Abstract
The objective of this project was to evaluate of energy characteristics of bagasse using a Fourier transform near infrared spectroscopy (FT-NIRS) scanned in reflection mode at wavenumbers of 1000-2500 nm. There are 28 new bagasse samples and 28 old bagasse samples. The models were established by partial least square (PLS). Five difference pretreatments were raw spectra, first derivative, second derivative, standard normal variate and baseline offset. The best results for prediction moisture content and higher heating value were first derivative and standard normal variate, respectively. The models of moisture content and higher heating value showed the coefficients of determination (R2) of validation set were 0.972 and 0.883, standard error of cross validation (SECV) were 2.171 and 259.441, bias were -0.017 and -0.184 %db, ratio of prediction to deviation (RPD) were 5.255 and 2.693, respectively. The model of ash showed the coefficients of determination (R2) which was 0.372. The models of moisture and higher heating value had excellent accuracy while ash models were poor.
Article Details
![Creative Commons License](http://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.