Mass modeling of kinnow mandarin based on some physical attributes

Abstract

The correlation between the physical properties of fruits such as their dimensions, projected areas, volume, and mass may assist in predicting fruit quality along with the development of post-harvest machinery. Thus, the present study aims to predict the mass of kinnow mandarin (Citrus reticulata L.) fruit as a function of its axial dimensions, projected areas, and volume using linear and nonlinear mathematical models (quadratic, power, and s-curve). Further, the mass models were presented under three different classifications: dimension based, projected area based, and volume based. The effect of size grading was also evaluated and compared with the data of ungraded fruits. Results showed that mass modeling based on dimensions and volume of ungraded fruits was more appropriate compared to individual grades. The quadratic model based on geometric mean diameter (R2 = 0.956) and ellipsoid volume (R2 = 0.955) are recommended for predicting the mass of ungraded fruits with maximal accuracy.