Spectroscopy and Spectral Analysis, Volume. 42, Issue 11, 3373(2022)

Study on Optimization of Apple Sugar Degree and Illumination Position Based on Near-Infrared Technology

Yan-de LIU*, Hui-zhen CUI, Bin LI, Guan-tian WANG, Zhen XU, and Mao-peng LI
Author Affiliations
  • School of Mechanical, Electrical and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
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    Figures & Tables(10)
    Schematic diagram of the spectrum detection system
    Schematic diagram of light rays go through the apple along two paths designed for near infrared diffuse transmission experiment
    Schematic diagram of intensity distributions of light go through the apple at different illumination positions based on near infrared diffuse transmission
    Linear fitting between real and predicted sugar contents of msc-pls
    Schematic diagram of linear fitting between true value and predicted value of sugar content for external verification
    • Table 1. Statistical results of physical and chemical indices of apple

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      Table 1. Statistical results of physical and chemical indices of apple

      照射
      位置
      数据集样品数
      /个
      果径范围
      /mm
      糖度范围
      /(°Brix)
      上部训练集
      预测集
      188
      62
      73±2
      73±2
      8.2~16.8
      8.8~16.2
      斜上部训练集
      预测集
      188
      62
      73±2
      73±2
      9.1~16.6
      10.5~16.6
    • Table 2. Ranges and average values of SSC in calibration set and prediction set

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      Table 2. Ranges and average values of SSC in calibration set and prediction set

      位置ParameterData SetSamplesMeanRange
      上部SSC/(°Brix)Calibration
      Prediction
      188
      62
      12.969 4
      13.180 7
      8.2~16.8
      8.8~16.2
      斜上部SSC/(°Brix)Calibration
      Prediction
      188
      62
      13.259 7
      13.373 9
      9.1~16.6
      10.5~16.6
    • Table 3. Modeling results of PLS with different pretreatment methods based on diffuse transmission data of apple samples using illuminations of upper and inclined upper

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      Table 3. Modeling results of PLS with different pretreatment methods based on diffuse transmission data of apple samples using illuminations of upper and inclined upper

      检测
      方式
      预处理方法CalibrationPrediction
      RMSECRcRMSEPRp
      上部Raw0.288 20.960 60.343 60.934 9
      SG-PLS0.408 10.921 00.400 00.911 9
      SG- Derivauive0.245 40.971 40.432 70.896 8
      SNV0.264 90.966 70.303 70.949 2
      MSC0.264 40.966 90.301 50.949 9
      斜上部Raw0.340 70.931 10.513 30.863 6
      SG-PLS0.474 90.866 10.579 30.826 1
      SG- Derivative0.295 80.948 10.633 10.792 4
      SNV0.317 70.940 10.451 70.894 3
      MSC0.322 90.938 10.454 60.893 0
    • Table 4. Modeling results of PCR with different pretreatment methods based on diffuse transmission data of apple samples using illuminations of upper and inclined upper

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      Table 4. Modeling results of PCR with different pretreatment methods based on diffuse transmission data of apple samples using illuminations of upper and inclined upper

      检测
      方式
      预处理方法CalibrationPrediction
      RMSECRcRMSEPRp
      上部Raw0.576 30.842 40.601 40.800 7
      SG0.577 00.842 10.599 60.801 9
      SG-Derivative0.859 30.949 60.982 60.468 1
      SNV0.538 20.862 50.579 50.815 0
      MSC0.540 00.861 80.585 20.811 4
      斜上部Raw0.709 20.701 40.797 40.670 7
      SG0.708 50.702 00.794 80.672 8
      SG- Derivative0.903 60.515 30.968 90.513 7
      SNV0.687 80.719 10.781 50.683 6
      MSC0.695 10.713 20.770 70.692 4
    • Table 5. Different model evaluation indexes of upper irradiation position

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      Table 5. Different model evaluation indexes of upper irradiation position

      建模
      方式
      预处理方法CalibrationPrediction
      RMSECRcRMSEPRp
      PLSRaw0.288 20.960 60.343 60.934 9
      SG-PLS0.408 10.921 00.400 00.911 9
      SG- Derivative0.245 40.971 40.432 70.896 8
      SNV0.264 90.966 70.303 70.949 2
      MSC0.264 40.966 90.301 50.949 9
      PCRRaw0.576 30.842 40.601 40.800 7
      SG-PLS0.577 00.842 10.599 60.801 9
      SG- Derivative0.859 30.949 60.982 60.468 1
      SNV0.538 20.862 50.579 50.815 0
      MSC0.540 00.861 80.585 20.811 4
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    Yan-de LIU, Hui-zhen CUI, Bin LI, Guan-tian WANG, Zhen XU, Mao-peng LI. Study on Optimization of Apple Sugar Degree and Illumination Position Based on Near-Infrared Technology[J]. Spectroscopy and Spectral Analysis, 2022, 42(11): 3373

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    Paper Information

    Category: Research Articles

    Received: Aug. 20, 2021

    Accepted: --

    Published Online: Nov. 23, 2022

    The Author Email: LIU Yan-de (jxliuyd@163.com)

    DOI:10.3964/j.issn.1000-0593(2022)11-3373-07

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