1- Department of Agricultural Machinery Engineering, College of Agriculture, University of Tehran, Islamic
Republic of Iran.
Abstract: (7493 Views)
There are instances in which it is desirable to determine relationships among fruit
physical attributes. For example, fruits are often graded on the basis of size and projected
area, but it may be more suitable and/or economical to develop a machine which grades
by mass. Therefore, a relationship between mass and dimensions or projected areas and/
or volume of fruits is needed. Various grading systems, size fruits on the basis of specific
parameters. Sizing parameter depends on fruit and machine characteristics.Models for
predicting mass of orange from its dimensions and projected areas were identified. Models
were divided into three classifications: 1- Single and multiple variable regression of
orange dimensions (1st classification). 2- Single and multiple variable regression of projected
areas (2nd classification). 3- Estimation of orange shape; ellipsoid or spheroid based
on volume (3rd classification). Ten Iranian varieties of oranges were selected for the study.
3rd classification models had the highest performance followed by 2nd and 1st classifications
respectively, with R2close to unity. The 2nd classification models need electronic systems
with cameras for projection whereas, 1st classification models are used in the simple
mechanical systems, except multiple variable ones, of and 3rd classification models need
more complex mechanical systems. Among the systems that sorted oranges based on one
dimension (Model 2), system that applies intermediate diameter suited better with nonlinear
relationship as: M = 0.07b2 – 2.95 b + 39.15 with R2= 0.97.
Subject:
Agricultural Machinery Received: 2010/05/15 | Accepted: 2010/05/15 | Published: 2010/05/15