International Congress on Mechanization and Energy in Agriculture, Antalya, Turkey, pp.745
Fruits are often graded on the basis of size and projected area, but it may be more economical to develop a machine which grade by mass. Therefore, the relationship between mass and other geometrical properties of fruits are needed. In this study, Washington Navel variety of orange were used to determine some physical characteristics, and to accomplish the best suitable mass modeling of orange fruits. Orange mass was predicted by appliying different geometrical characteristics with linear and non linear models as three different classifications: (1) Single or multi variable regression of orange based on dimensional properties, (2) Single or multi variable regression of orange projected areas and (3) Estimating orange mass based on its volume. The results showed that the best model in order to estimate the mass of orange fruit based on minor diameter and three projected areas were the most appropriate mmodels in the first and second classifications, respecticely. But, because usage of three projected areas in fruit packing line for sizing the fruits is not practical and expensive best appropriate and applicable model was chosen as minor projected areas in single linear regression model. In third classification, the highest determination coefficient was obtained for mass modeling based on the actual volume wit a R2 of 1.00 whereas corresponding values were 0.86, 0.85, 0.84 and 0.75 for assumed orange shapes (sphere, ellipsoid, prolate spheroid and oblate spheroid), respectively.