Journal
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Volume 32, Issue 3, Pages -Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0218001418550029
Keywords
Seed sorting; computer vision; haploid identification; color feature
Categories
Funding
- Beijing Municipal Science and Technology Project [D151100004215002]
- China Postdoctoral Science Foundation [2015M581019]
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This study designed an automatic sorting system that can separate haploid maize kernels from cross-breeding kernels that are marked with the Navajo label. This system comprises the seed feeding, image acquisition, sorting and system control units. The seed feeding unit distributes the maize kernels over the synchronous belt. The image acquisition unit acquires the images of maize kernels, as well as distinguishes the heterozygous from haploid kernels based on the color feature of the endosperm. The sorting unit contains mechanical arms and solenoid valves that can select the heterozygote kernels using air suction. Lastly, the system control unit is compatible with other units. Four maize varieties, namely, 958-CAU, 1050-37, LC0990-LN75 and LC0995-CAU, were provided by China Agricultural University, National Maize Improvement Center. These varieties were selected for the experiments conducted. The successful unloading rates of the system are 85.56%, 91.39%, 87.22% and 86.39%, respectively. (R+G) x vertical bar G-B vertical bar/B was employed to distinguish the pigmented endosperm area. The accuracy rates of identification for the heterozygous kernels are 92.91%, 95.04%, 88.82% and 92.65% for 958-CAU, 1050-37, LC0990-LN75 and LC0995-CAU, respectively.
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