A NEW TECHNIQUE FOR GRAPE INSPECTION AND SORTING CLASSIFICATION | ||||
| Arab Universities Journal of Agricultural Sciences | ||||
| Article 2, Volume 14, Issue 2, September 2006, Page 555-573 PDF (780.82 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ajs.2006.15293 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Elbatawi I.E* ; M.T. Ebaid | ||||
| Agricultural Engineering Research Institute, Nadi Elsaid St., Dokki, Giza, Egypt | ||||
| Abstract | ||||
| Sorting and classification of fruits are the main problem specially for Superior and King Ruby varieties which represent more than 50% of grape production in Egypt. A usual procedure to carry out this task is based on human visual inspection considering general fruit attributes like color, size, shape, firmness and sugar content of grape cluster. Color contains important information about fruit status and in some cases it is decisive for fruit quality differences. This paper provides a new technique to investigate the applicability of color classification, sugar content and firmness of grape. Standard RGB color chart, artificial neural network and a potential of nearinfrared (NIR) reflectance as a means for nondestructive measurements of grape firmness and sugar content were used. NIR spectral data were collected from the two varieties of grape in the spectral region between 800 nm and 1700 nm. Statistical models were developed using the partial least square method to predict the firmness and sugar content of grape. The models gave relatively good predictions of the firmness of both Superior and King Ruby, with corresponding r values of 0.80 and 0.65. The NIR models gave excellent prediction for grape sugar content with values of 0.71 % and 0.65 % Brix for Superior and King Ruby, respectively. | ||||
| Keywords | ||||
| Machine vision; Grape inspection; Sorting; Sugar content | ||||
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