摘要

This study determined iodine value (IV) and free fatty acids (FFA) content of four different animal fat wastes and their blends using Fourier transform near-infrared spectroscopy (FT-NIR). Chemometric analysis by partial least squares (PIS) regression was used to correlate spectral data with IV and FFA reference values of the samples. The effects of four spectra pre-processing (first derivative (FD), second derivative (SD), multiplicative scatter correction (MSC) and vector normalization (VN)) methods were investigated to predict the reproducibility and robustness of the PLS-NIR model developed. A set of 70% of animal fat wastes and their blends were used for developing PLS calibration models for measuring IV and FFA content using the remaining 30% samples as an independent test set validation. The coefficient of determination (R-2), the root mean square error estimation (RMSEE), and the residual prediction deviation (RPD) were used as indicators for the predictability of the PLS models. PLS-NIR models developed using first derivative and second derivative spectral preprocessing methods were the best for both IV and FFA content analysis (For IV, FD; R-2 = 0.9870, RMSEE = 1.40 gI(2)/100 g, RPD = 8.76, SD; R-2 = 0.9892, RMSEE = 1.28 gI(2)/100 g, RPD = 9.64 while For FFA, FD; R-2 = 0.9991, RMSEE = 0.195%, RPD = 34.00, SD; R-2 = 0.9993, RMSEE = 0.182%, RPD = 36.8). Overall, the results of this study demonstrate the suitability of FT-NIR spectroscopy for the quality control analysis of feedstocks for biodiesel production.

  • 出版日期2014-5
  • 单位McGill