Machine vision based alternative testing approach for physical purity, viability and vigour testing of soybean seeds (Glycine max)

The conventional methods for seed quality testing have several limitations as they involve visual assessment and are destructive. In this context, a study was performed to assess the suitability of non-contact, non-destructive type imaging techniques such as visible imaging and X-ray imaging for con...

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Bibliographic Details
Published in:Journal of food science and technology 2018-10, Vol.55 (10), p.3949-3959
Main Authors: Mahajan, Shveta, Mittal, Sudesh Kumar, Das, Amitava
Format: Article
Language:English
Subjects:
Chemistry
Chemistry and Materials Science
Chemistry/Food Science
Destructive testing
Food Science
Germination
Image analysis
Image processing
Imaging techniques
Machine vision
Nondestructive testing
Nutrition
Original
Original Article
Purity
Quality assessment
Quality control
Seeds
Soybeans
Viability
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Summary:The conventional methods for seed quality testing have several limitations as they involve visual assessment and are destructive. In this context, a study was performed to assess the suitability of non-contact, non-destructive type imaging techniques such as visible imaging and X-ray imaging for conducting physical purity, viability and vigour tests of soybean seeds. The seeds that appeared healthy in external surface examination using visible tests as well as in internal assessment using X-ray tests were classified as sound seeds while the other seeds were marked as not-sound seeds. The obtained results were then correlated with the results of the standard germination tests. The high correlation results between the imaging tests and the standard conventional germination tests indicate the effectiveness and usability of the proposed image analysis based technique as an attractive alternative to the existing quality assessment methods for soybean seeds.
ISSN:0022-1155
0975-8402
DOI:10.1007/s13197-018-3320-x