Prof. Herlina Abdul Rahim
Prof. Herlina Abdul Rahim
Universiti Teknologi Malaysia, Malaysia
Title: Assessment on Free Fatty Acid of Crude Palm Oil using Near-Infrared Spectroscopy
Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of predictive models has facilitated the estimation process in recent years. In this research, 176 crude palm oil (CPO) samples were studied. A FOSS NIRSystem was used to take absorbance measurements from the sample. The wavelength range for the spectral measurement is taken at 1600nm to 1900nm. Free fatty acid (FFA) content of each sample was determined by chemical titration method and prediction models were developed relating FFA value to spectral measurement. Prediction model built from Artificial Neural Network (ANN) yielded R of 0.9999 and 0.9640 for the calibration and validation set respectively. From the results, it is shown that the NIR spectroscopy in a spectral region of 1600nm to 1900nm is suitable and adequate for FFA measurement of CPO and that the accuracy of prediction is high (range from 80.39% to 99.99% of accuracy). There is no doubt that ANN predictive model is the best among all prediction model.