Effect of Calibration Set Selection on Quantitatively Determining Test Weight of Maize by Near-Infrared Spectroscopy - Archive ouverte HAL Access content directly
Conference Papers Year : 2019

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

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Lianping Jia
  • Function : Author
  • PersonId : 1050491
Peng Jiao
  • Function : Author
  • PersonId : 1050492
Zhen Zeng
  • Function : Author
  • PersonId : 1050493
Xunpeng Jiang
  • Function : Author
  • PersonId : 1050494

Abstract

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.
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Dates and versions

hal-02179969 , version 1 (12-07-2019)

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Attribution - CC BY 4.0

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Lianping Jia, Peng Jiao, Junning Zhang, Zhen Zeng, Xunpeng Jiang. Effect of Calibration Set Selection on Quantitatively Determining Test Weight of Maize by Near-Infrared Spectroscopy. 10th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2016, Dongying, China. pp.481-488, ⟨10.1007/978-3-030-06155-5_49⟩. ⟨hal-02179969⟩
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