초분광 반사광 영상을 이용한 무(Raphanus sativus L) 종자의 발아와 불발아 비파괴 판별
Nondestructive Classification of Viable and Non-viable Radish (Raphanus sativus L) Seeds using Hyperspectral Reflectance Imaging
- Resource Type
- Article
- Authors
- 안치국 / Chi Kook Ahn; 모창연 / Chang Yeun Mo; 강점순 / Jum Soon Kang; 조병관 / Byoung Kwan Cho
- Source
- 바이오시스템공학(구 한국농업기계학회지) / Journal of biocystems Engineering. Dec 25, 2012 37(6):411
- Subject
- Radish seed
Seed viability
Nondestructive sorting
Hyperspectral image
Image processing
- Language
- Korean
- ISSN
- 1738-1266
Purpose: Nondestructive evaluation of seed viability is a highly demanded technique in the seed industry. In this study, hyperspectral imaging system was used for discrimination of viable and non-viable radish seeds. Method: The spectral data with the range from 400 to 1000 nm measured by hyperspectral reflectance imaging system were used. A calibration and a test models were developed by partial least square discrimination analysis (PLS-DA) for classification of viable and non-viable radish seeds. Either each data set of visible (400∼750 nm) and NIR (750∼1000 nm) spectra and the spectra of the combined spectral ranges were used for developing models. Results: The discrimination accuracy of calibration was 84% for visible range and 76.3% for NIR range. The discrimination accuracy of test was 84.2% for visible range and 75.8% for NIR range. The discrimination accuracies of calibration and test with full range were 92.2% and 92.5%, respectively. The resultant images based on the optimal PLS-DA model showed high performance for the discrimination of the nonviable seeds from the viable seeds with the accuracy of 95%. Conclusions: The results showed that hyperspectral reflectance imaging has good potential for discriminating nonviable radish seeds from massive amounts of viable seeds.