Abstract
The study used near-infrared reflectance spectroscopy and hybrid calibration methods to predict oil and free fatty acid content of oil palm fruitlets non-destructively. The reflectance and chemical content of oil palm fruitlets were measured and the calibration between near infrared spectra and chemical content was performed using hybrid calibration methods. The developed hybrid calibration model was validated to predict oil and free fatty acid of other oil palm fruitlets. The best models to predict oil and free fatty acid of oil palm fruitlets respectively were the hybrid model of Partial Least Square-Artificial Neural Network with 25 factor components (R2 = 0.96; SEP= 2.21%, RPD = 4.79) and 19 factor components (R2 = 0.96; SEP= 0.25%, RPD = 4.24) using Savitzky-Golay first derivative spectra pre-treatment.
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