Effect of Calibration Set Selection on Quantitatively Determining Test Weight of Maize by Near-Infrared Spectroscopy

  • Lianping Jia
  • Peng Jiao
  • Junning Zhang
  • Zhen Zeng
  • Xunpeng Jiang
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)


To study the effect of calibration set on quantitatively determining test weight of maize by near-infrared spectroscopy, 584 maize samples were collected and scanned for near-infrared spectral data. Test weight was measured following the standard GB 1353-2009, resulting the sample test weight of 693–732 g•L−1. Two calibration models were respectively built using partial least squares regression, based on two different calibration sets. Test weight of two calibration sets distribute differently, with normal and homogeneous distributions. Both quantitative models were selected by root mean square error of cross validation (RMSECV), and evaluated by validation set. Results show the RMSECV of the model based on normal distribution calibration set is 4.28 g•L−1, the RMSECV of the model based on homogeneous distribution calibration set is 2.99 g•L−1, the predication of two models have significant difference for the samples with high or low test weight.


Test weight Near-infrared Calibration set selection 



This work was supported financially by the National key research and development program (Project No. 2016YFD0700204) and S&T Nova Program of Beijing (Project No. Z1511000003150116).


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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Lianping Jia
    • 1
  • Peng Jiao
    • 1
  • Junning Zhang
    • 2
  • Zhen Zeng
    • 3
  • Xunpeng Jiang
    • 1
  1. 1.COFCO Feed Co., LtdBeijingChina
  2. 2.Chinese Academy of Agricultural Mechanization SciencesBeijingChina
  3. 3.Patent Examination of Cooperation Beijing Center of the Patent OfficeSIPOBeijingChina

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