The Identification of Single Soybean Seed Variety by Laser Light Backscattering Imaging
Abstract:The identification of soybean cultivars was important for germ plasma resources utilization and breeding. Traditional method for crude identification soybean variety was conducted by human eyes according to the seed morphological characteristics or the seedling characteristics. The molecular level methods including isoenzyme zymogram analysis, Restriction Fragment Length Polymorphism (RFLP), and ISSR Markers were accuracy, however it was expensive, destructive, time consuming, and laborious. In this study, the laser light backscattering imaging technology was used to measure the single soybean seed. Laser light was directly illuminated on the surface of soybean seed, and a CCD camera was applied to capture the laser facula. Then the characteristic of laser facula that related to soybean seed quality was analyzed by image processing technology. Two varieties of soybean were measured, which contained 60 KENJIANDOU43 seeds and 60 ZHONGHUANG13 seeds. The frequency of pixels excluding laser intensities was used to describe the characteristic of back scattering image. Principle component analysis (PCA) and Soft independent modeling of class analogy (SIMCA) was used to construct the qualitative models. It showed that the gray values between 90 and 200 of scattering image represented the diffuse reflection of seed. The pixel frequency with 11 pixel intensity intervals could be used to discriminate the soybean seeds. The two cultivars of KENJIANDOU43 seeds and ZHONGHUANG13 soybean distributed in different areas in the PCA interspaces, thus two cultivars of seed could be separated using a suitable threshold value, and the classification accuracy achieved 84.2%. For the construction of SIMCA model, the discrimination accuracy was 87.5%. The present study indicated that laser light scattering imaging was a promising method for the identification of the cultivars of single soybean seeds.
Document Type: Research Article
Publication date: January 1, 2012
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