Development of an inspection module for quality assurance of tomatoes on the vine

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Development of an inspection module for quality assurance of tomatoes on the vine

Gepubliceerd op
5 augustus 2014

Wageningen UR Greenhouse Horticulture launched, beginning of this year, a public-private partnership project which focuses on the automatic quality inspection of tomatoes on the vine on the packaging line.

The current quality inspection of tomatoes on the vine is done by simple visual inspection of workers and quality controllers. Under the pressure of production, human errors and loss of attention, it is difficult to assure an objective and constant quality. Camera techniques are well able to deliver reproducible and consistent results and can scan all the products.

Assured quality camera technique

The first phase of the project is a feasibility study. The research should bring answers to the question whether, and with what camera technique it is possible to achieve a better sorted product than the sorting currently done by manual inspection done by the employees. Several product properties such as defects of the fruits (spots, blossom end rot, cracks, splits, etc.), defects of the stem and crown (yellow discoloration, mildew, mold and rot) and detection of the fruit maturity (green-red coloration) are examined.

tomatoes_classified.jpg

Image analysis tomatoes

Recently image data was collected using a number of camera different camera techniques including colour, hyper-spectral in the visible range (400nm-1000nm) and infrared range (900nm-1700nm) and chlorophyll fluorescence. An initial analysis of the data has shown that it should be possible to develop classification algorithms for many of the defects. A particularly interesting range of wavelengths for the detection of mold and fungi turned out to be the (near) infra-red region which cannot be observed with the human eye.

Currently, a lab setup is realized in Wageningen to image at a larger batch of tomatoes on the vine using the selected camera setup. Then, computer vision algorithms for real-time analysis will be developed. If sufficiently high classification scores can be reached an inspection module will be realized. This module will be designed such that it can be integrated in the packaging line.