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Discrimination of Kernel Quality Characteristics for Sunflower Seeds Based on Multispectral Imaging Approach

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Abstract

Multispectral imaging in the visible and near-infrared (405–970 nm) regions was tested for nondestructive discrimination of insect-infested, moldy, heterochromatic, and rancidity in sunflower seeds. An excellent classification (accuracy >97 %) for intact sunflower seeds could be achieved using Fisher’s linear discriminant function based on 10 feature wavelengths that were selected from the original 19 wavelengths by Wilks’ lambda stepwise method. Intact sunflower seeds with different degree of rancidity could be precisely clustered by multispectral imaging technology combined with principal component analysis-cluster analysis (PCA-CA). Our results demonstrate the capability of multispectral imaging technology as a tool for rapid and nondestructive analysis of seed quality attributes, which enables many applications in the agriculture and food industry.

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Acknowledgments

The authors would like to thank the Anhui Truelove Foods Co., Ltd., China, which provided sunflower seed samples. We also thank for the helps of Mr Gaojun Sun, Miss Shanshan Shui, and Miss Qiupin Wu in rancidity test. This study is supported by the specialized Research Fund for the National Key Technologies R&D Programme (2012BAD07B01), the Doctoral Program of Higher Education (20120111110024), the Anhui Province Key Technologies Research & Development Program (2013AKKG0798), the Key Project of Anhui Provincial Educational Department (JZ2014AJZR0113), the Fundamental Research Funds for the Central Universities (2012HGCX0003), and the Funds for Huangshan Professorship of Hefei University of Technology (407-037019).

Conflict of Interest

Fei Ma declares that he has no conflict of interest. Ju Wang declares that she has no conflict of interest. Changhong Liu declares that she has no conflict of interest. Xuzhong Lu declares that he has no conflict of interest. Wei Chen declares that he has no conflict of interest. Conggui Chen declares that he has no conflict of interest. Jianbo Yang declares that he has no conflict of interest. Lei Zheng declares that he has no conflict of interest.

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This article does not contain any studies with human or animal subjects.

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Authors and Affiliations

  1. School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei, 230009, Anhui province, People’s Republic of China

    Fei Ma, Ju Wang, Changhong Liu, Wei Chen, Conggui Chen & Lei Zheng

  2. Rice Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China

    Xuzhong Lu & Jianbo Yang

  3. School of Medical Engineering, Hefei University of Technology, Hefei, 230009, China

    Lei Zheng

Authors
  1. Fei Ma
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  2. Ju Wang
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  3. Changhong Liu
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  4. Xuzhong Lu
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  5. Wei Chen
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  6. Conggui Chen
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  7. Jianbo Yang
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Correspondence to Conggui Chen, Jianbo Yang or Lei Zheng.

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Ma, F., Wang, J., Liu, C. et al. Discrimination of Kernel Quality Characteristics for Sunflower Seeds Based on Multispectral Imaging Approach. Food Anal. Methods 8, 1629–1636 (2015). https://doi.org/10.1007/s12161-014-0038-x

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  • DOI: https://doi.org/10.1007/s12161-014-0038-x

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