A NEW TECHNIQUE FOR GRAPE INSPECTION AND SORTING CLASSIFICATION
2006
Elbatawi I.E | M.T. Ebaid
Sorting and classification of fruits are the main problem specially for Superiorand King Ruby varieties which represent more than 50% of grape production inEgypt. A usual procedure to carry out this task is based on human visual inspectionconsidering general fruit attributes like color, size, shape, firmness and sugar contentof grape cluster. Color contains important information about fruit status and in somecases it is decisive for fruit quality differences. This paper provides a new techniqueto investigate the applicability of color classification, sugar content and firmness ofgrape. Standard RGB color chart, artificial neural network and a potential of nearinfrared(NIR) reflectance as a means for nondestructive measurements of grapefirmness and sugar content were used. NIR spectral data were collected from the twovarieties of grape in the spectral region between 800 nm and 1700 nm. Statisticalmodels were developed using the partial least square method to predict the firmnessand sugar content of grape. The models gave relatively good predictions of thefirmness of both Superior and King Ruby, with corresponding r values of 0.80 and0.65. The NIR models gave excellent prediction for grape sugar content with valuesof 0.71 % and 0.65 % Brix for Superior and King Ruby, respectively.
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