• Journal of Innovative Optical Health Sciences
  • Vol. 10, Issue 3, 1650053 (2017)
Kaewkarn Phuangsombut1, Nattaporn Suttiwijitpukdee2, and Anupun Terdwongworakul1、*
Author Affiliations
  • 1Department of Agricultural Engineering, Faculty of Engineering at Kamphaengsaen, Kasetsart University, Kamphaengsaen, Nakhon Pathom, 73140 Thailand
  • 2Kasetsart Agricultural and Agro-Industrial, Product Improvement Institute, Kasetsart University, Bangkok, 10900 Thailand
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    DOI: 10.1142/s179354581650053x Cite this Article
    Kaewkarn Phuangsombut, Nattaporn Suttiwijitpukdee, Anupun Terdwongworakul. Nondestructive classification of mung bean seeds by single kernel near-infrared spectroscopy[J]. Journal of Innovative Optical Health Sciences, 2017, 10(3): 1650053 Copy Citation Text show less

    Abstract

    Near-infrared spectroscopy (NIRS) in the range 900–1700 nm was performed to develop a classifying model for dead seeds of mung bean using single kernel measurements. The use of the combination of transmission-absorption spectra and reflection-absorption spectra was determined to yield a better classification performance (87.88%) than the use of only transmissionabsorption spectra (81.31%). The effect of the orientation of the mung bean with respect to the light source on its absorbance was investigated. The results showed that hilum-down orientation exhibited the highest absorbance compared to the hilum-up and hilum-parallel-to-ground orientations. We subsequently examined the spectral information related to the seed orientation by developing a classifying model for seed orientation. The wavelengths associated with classification based on seed orientation were obtained. Finally, we determined that the re-developed classifying model excluding the wavelengths related to the seed orientation afforded better accuracy (89.39%) than that using the entire wavelength range (87.88%).
    Kaewkarn Phuangsombut, Nattaporn Suttiwijitpukdee, Anupun Terdwongworakul. Nondestructive classification of mung bean seeds by single kernel near-infrared spectroscopy[J]. Journal of Innovative Optical Health Sciences, 2017, 10(3): 1650053
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