Articles

Harvest bin placement based on machine vision data in mango orchards

Article number
1395_41
Pages
311 – 316
Language
English
Abstract
New technologies providing information on spatial distribution of fruit load in tree crops offer potential for improved orchard management operations.
One harvest management task is the distribution of empty fruit bins through the orchard prior to harvest.
This concept is explored for a mango orchard, with use of fruit load data derived from RGB-D cameras mounted to a ground vehicle-based platform for measurement of fruit size and fruit number some weeks before harvest, and a fruit growth model applied to forecast fruit mass distribution at harvest.
The system has inputs of cultivar parameters, fruit load distribution from machine vision mapping, average fruit size and bin size, and output of an in-field bin placement online map.
A cumulative yield along each row is calculated from fruit count and mass distribution estimates, with bin placement tied to a user-defined bin capacity (nominally 400 kg).

Publication
Authors
H.K. Dhonju, K.B. Walsh, T.P. Bhattarai
Keywords
field bin, fruit count, fruit size, machine vision, spatial location
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