Abstract
The goal of this study is to develop an approach to determine the internal qualities in oil palm (Elaeis guineensis Jacq. var. tenera). Bunches and fruits belonging to 4 classes of ripeness (overripe, ripe, underripe and unripe) were used for this study. For these bunches, three of internal qualities as ripeness, oil content and free fatty acid content were examined. Since the estimation of internal qualities based on the overall data for a bunch was difficult, we focused on the average reflectance and the average relative reflectance values of fruits that were not concealed by fronds in bunch. By our approach, it was necessary to estimate the ripeness of the bunch before the oil content and free fatty acid content were determined. To classify ripeness of a bunch, the average relative reflectance values of bunches in different classes of ripeness were used and classified based on Euclidean distance. In addition, ratio of chlorophyll to carotenoids (Rp) was also used for estimating ripeness of a bunch. Then oil content (OC) and free fatty acid (FFA) content were predicted by calibration models corresponding to the class of ripeness. Correct estimation results in all classes of ripeness were obtained by both methods. The coefficients of determination (R2) were 99.7% and 99.5% with a standard error of prediction (SEP) of 0.421 and 0.190 in the validation of oil content and free fatty acid models, respectively. For oil palm fruits, methods to estimate the ripeness of the fruits were developed. Ripeness estimation using the average relative reflectance values in lower part of the fruit was compared with ripeness estimation using the ratio of a not-pale greenish yellow area, a not-yellow area and a not-reddish orange area to the entire area of fruit. The correct estimation in all classes of ripeness was obtained by using the average relative reflectance at lower part of fruit while a correct ripeness estimation rate of 97.92% was gained by using ratio of area in fruit. Since the ripeness estimation using the ratio of the area of the fruits can be done automatically, it may provide more practically applicable for the assessment of fruit ripeness in the factory.
