Apricot Mass Modeling Based on Geometrical Attributes

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In this study, eighteen linear regression models for modeling apricot mass based on some geometrical attributes of apricot such as major diameter (a), intermediate diameter (b), minor diameter (c), geometrical mean diameter (GMD), first projected area (PA1), second projected area (PA2), third projected area (PA3), criteria area (CAE), estimated volume based on an ellipsoid assumed shape (VE11) and measured volume (VM) were suggested.  Models were divided into three main classifications, i.e. first classification (outer dimensions), second classification (projected areas) and third classification (volumes). The statistical results of the study indicated that in order to predict apricot mass based on outer dimensions, the mass model based on GMD as M = - 26.79 + 1.45 GMD with R2= 0.93 can be recommended. Moreover, to predict apricot mass based on projected areas, the mass model based on CAE as M = - 5.08 + 3.05 CAE with R2 = 0.93 can be suggested. Besides, to predict apricot mass based on volumes, the mass model based on VEll as M = 2.24 + 1.01 VE11 with R = 0.92 can be 2 utilized. These models can also be used to design and develop sizing machines equipped with an image processing system.

Autores: 
Majid Rashidi
Autores: 
Hossein Beheshty Asl
Autores: 
Siavash Behboodi
Editora: 
Agricultural Engineering Research Journal
Año: 
2018