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An effective moisture interference correction method for maize powder NIR spectra analysis.

Xiaohong Li1, Zhuopin Xu2, Liwen Tang3

  • 1Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; University of Science and Technology of China, Hefei 230026, China.

Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
|February 21, 2024
PubMed
Summary
This summary is machine-generated.

Accurate maize starch detection using near-infrared spectroscopy (NIRS) is vital. External parameter orthogonalization (EPO) combined with wavelength selection improves NIRS accuracy by overcoming moisture interference.

Keywords:
External parameters orthogonalizationMaize starchMoisture correctionNear infrared spectroscopySynergy interval partial least squares

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Area of Science:

  • Agricultural Science
  • Analytical Chemistry
  • Spectroscopy

Background:

  • Accurate maize starch content detection is crucial for the maize processing industry.
  • Near-infrared spectroscopy (NIRS) is a rapid and ideal technology for this analysis.
  • Moisture interference significantly hinders the accuracy of NIRS quantitative analysis in maize.

Purpose of the Study:

  • To develop improved NIRS methods for accurate maize starch detection.
  • To address the challenge of moisture interference in NIRS analysis of maize.
  • To evaluate the performance of external parameter orthogonalization (EPO) combined with wavelength selection algorithms.

Main Methods:

  • Investigated two groups of maize starch samples with varying moisture content.
  • Applied external parameter orthogonalization (EPO) combined with synergy interval partial least squares (siPLS) algorithm.
  • Compared predictive performance against PLS, EPO-PLS, and siPLS models.

Main Results:

  • The EPO-siPLS model demonstrated superior prediction accuracy.
  • Achieved a 9.7% improvement in RMSEP/RMSEPck compared to siPLS.
  • Showed significant improvements over EPO-PLS (25.3%) and PLS (45.8%) models.

Conclusions:

  • External parameter orthogonalization (EPO) combined with synergy interval partial least squares (siPLS) offers a more accurate and robust method for maize starch detection.
  • This approach effectively mitigates moisture interference in NIRS analysis.
  • Provides valuable insights for the application of NIRS in agricultural product analysis.