Abstract
In this study, a visual grading system of vegetable grafting machine was developed. The study described key technology of visual grading system of vegetable grafting machine. First, the contrasting experiment was conducted between acquired images under blue background light and natural light conditions, with the blue background light chosen as lighting source. The Visual C++ platform with open-source computer vision library (Open CV) was used for the image processing. Subsequently, maximum frequency of total number of 0-valued pixels was predicted and used to extract the measurements of scion and rootstock stem diameters. Finally, the developed integrated visual grading system was experimented with 100 scions and rootstock seedlings. The results showed that success rate of grading reached up to 98%. This shows that selection and grading of scion and rootstock could be fully automated with this developed visual grading system. Hence, this technology would be greatly helpful for improving the grading accuracy and efficiency.
Highlights
Grafting is a technique whereby branches or buds from one plant are inserted into the appropriate parts of another plant that has a strong affinity
The results showed that in order to obtain best contrast ratio, the blue background light source was found superior to other color light sources
The contrast of the blue background light was obtained to be better than the contrast of the natural light condition, so the scheme used in this study incorporates the blue background light
Summary
Grafting is a technique whereby branches or buds from one plant are inserted into the appropriate parts of another plant that has a strong affinity. A branch or bud to be cultivated (i.e. scion) is encouraged to fuse or graft onto a strong vital plant (i.e. rootstock) so that the scion can grow, blossom, and bear fruit using nutrient soil. Some semi-automatic grafting robots have been developed and commercialized for cucumber, tomato, and watermelon in Japan, South Korea, the Netherlands, and China. In these countries, the working efficiency of semi-automatic grafting robots is three times faster than the traditional manual grafting.[2] for most automatic grafting machines, the grafting speed can reach up to 600 seedlings per hour.
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