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A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images.

Nurul Amira Mohd Ramli1,2, Mohd Hafiz Fazalul Rahiman1,2, Latifah Munirah Kamarudin2,3

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This study introduces radio tomographic imaging (RTI) to monitor rice moisture distribution in silos. The new method accurately localizes moisture levels, improving grain quality management.

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Area of Science:

  • Agricultural Engineering
  • Food Science
  • Sensor Technology

Background:

  • Rice grain quality is critically dependent on moisture content, affecting fiber integrity and breakage.
  • Current single-point and destructive gravimetric methods for moisture analysis are unreliable for uneven moisture distribution in silos.

Purpose of the Study:

  • To develop and validate a non-destructive method for monitoring and localizing moisture distribution in rice silos.
  • To assess the feasibility of using radio tomographic imaging (RTI) for real-time moisture assessment in stored grains.

Main Methods:

  • Implementation of a radio tomographic imaging (RTI) system.
  • Reconstruction of simulated rice silo phantom profiles using Newton's One-Step Error Reconstruction and Tikhonov Regularization algorithms.
  • Correlation analysis between maximum voxel weighting in RTI images and moisture content percentages.

Main Results:

  • A linear relationship was observed between the maximum voxel weighting of reconstructed RTI images and the percentage of moisture content.
  • A high correlation coefficient (R > 0.95) was achieved, indicating strong predictive power.
  • The study demonstrated the potential for accurate moisture localization within the silo.

Conclusions:

  • Radio tomographic imaging (RTI) offers a promising non-destructive approach for monitoring and localizing moisture distribution in rice silos.
  • The established correlation provides a basis for quantitative moisture assessment using RTI.
  • This technology can significantly enhance the management of stored rice quality and prevent spoilage.