• Laser & Optoelectronics Progress
  • Vol. 53, Issue 12, 123001 (2016)
Wang Chaopeng1、2、3、4、*, Huang Wenqian2、3、4, Fan Shuxiang2、3、4, Zhang Baohua2、3、4, Liu Chen1、2、3、4, Wang Xiaobin2、3、4、5, and Chen Liping1、2、3、4
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
  • 5[in Chinese]
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    DOI: 10.3788/lop53.123001 Cite this Article Set citation alerts
    Wang Chaopeng, Huang Wenqian, Fan Shuxiang, Zhang Baohua, Liu Chen, Wang Xiaobin, Chen Liping. Moisture Content Detection of Maize Kernels Based on Hyperspectral Imaging Technology and CARS[J]. Laser & Optoelectronics Progress, 2016, 53(12): 123001 Copy Citation Text show less
    References

    [1] Fang Yingjie. Detection method of high moisture corn[J]. Modern Food, 2015, 23: 65-67.

    [2] Gai Yanxin, Wang Yanzhi, Ji Zhiqiang, et al. The effect of moisture content and drying rate of maize seed[J]. China Seed Industry, 2010, 5: 33-34.

    [3] Jia Wan, Mao Peisheng. Review on thenear infrared spectroscopy in seed quality testing research[J]. Seed, 2013, 32(11): 46-51.

    [4] Cao Pengfei, Li Hongning, Luo Yanlin, et al. Selection of feature bands for phaseolus vulgaris leaves based on multispectral imaging[J]. Laser & Optoelectronics Progress, 2014, 51(1): 011101.

    [5] Zhang B, Huang W, Li J, et al. Principles, developments and applications of computer vision for external quality inspection of fruits and vegetables: A review[J]. Food Research International, 2014, 62: 326-343.

    [6] Wu D, Shi H, Wang S, et al. Rapid prediction of moisture content of dehydrated prawns using online hyperspectral imaging system[J]. Analytica Chimica Acta, 2012, 726(9): 57-66.

    [7] Deng Xiaoqin, Zhu Qibing, Huang Min. Variety discrimination for single rice seed by integrating spectral, texture and morphological features based on hyperspectral image[J]. Laser & Optoelectronics Progress, 2015, 52(2): 021001.

    [8] He Yong, Peng Jiyu, Liu Fei, et al. Critical review of fast detection of crop nutrient and physiological information with spectral and imaging technology[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(3): 174-189.

    [9] Wu Longguo, He Jianguo, Liu Guishan, et al. Non-destructived determination of moisture in jujubes based on near-infrared hyperspectral imaging technique[J]. Journal of Optoelectronics·Laser, 2014, 25(1): 135-140.

    [10] Fan Shuxiang, Huang Wenqian, Guo Zhiming, et al. Assessment of influence of origin variability on robustness of near infrared models for soluble solid content of apples[J]. Chinese Journal of Analytical Chemistry, 2015, 43(2): 239-244.

    [11] Liu Yande, Shi Yu, Cai Lijun, et al. On-line NIR detection model optimization of soluble solids content in navel orange based on CARS[J]. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(9): 138-144.

    [12] Han Donghai, Chang Dong, Song Shuhui, et al. Information collection of mini watermelon quality using near-infrared non-destructive detection[J]. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(7): 174-178.

    [13] Sun Tong, Wu Yiqing, Li Xiaozhen, et al. Discrimination of camellia oil adulteration by NIR spectra and subwindow permutation analysis[J]. Acta Optica Sinica, 2015, 35(6): 0630005.

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    [1] Libo Rao, Tao Pang, Ranshi Ji, Xiaoyan Chen, Jie Zhang. Firmness Detection for Apples Based on Hyperspectral Imaging Technology Combined with Stack Autoencoder-Extreme Learning Machine Method[J]. Laser & Optoelectronics Progress, 2019, 56(11): 113001

    [2] Libo Rao, Tao Pang, Ranshi Ji, Xiaoyan Chen, Jie Zhang. Firmness Detection for Apples Based on Hyperspectral Imaging Technology Combined with Stack Autoencoder-Extreme Learning Machine Method[J]. Laser & Optoelectronics Progress, 2019, 56(11): 113001

    Wang Chaopeng, Huang Wenqian, Fan Shuxiang, Zhang Baohua, Liu Chen, Wang Xiaobin, Chen Liping. Moisture Content Detection of Maize Kernels Based on Hyperspectral Imaging Technology and CARS[J]. Laser & Optoelectronics Progress, 2016, 53(12): 123001
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