THERMAL-ANALYSIS OF PEAT

Thermal analysis has been performed on samples of plants, pest, chemical fractions of pest, and coal. Simultaneous thermogravimetry (TG) and differential scanning calorimetry (DSC) technique has proved to be useful in classifying and separating the samples. Due to probable redundant information in the TG and DSC signals the sampling frequency has been investigated. Quantitative predictions of 15 chemical and physical constituents in peat are performed using partial least squares regression (PLSR). Prediction properties are compared with near infrared reflectance spectroscopy (NIR) which shows that TG/DSC and NIR are comparable in predictability of investigated constituents. The use of simultaneous TG and DSC signals in predictions, compared using TG or DSC separately, shows that the combination leads to increases in the predictability, as shown by the use of standard error of prediction (SEP) values.