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

This manuscript presents a new method to monitor and localize the moisture distribution in a rice silo based on tomography images. Because the rice grain is naturally hygroscopic, the stored grains’ quality depends on their level of moisture content. Higher moisture content leads to fibre degradatio...

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Autores principales: Mohd Ramli, Nurul Amira, Fazalul Rahiman, Mohd Hafiz, Kamarudin, Latifah Munirah, Mohamed, Latifah, Zakaria, Ammar, Ahmad, Anita, Rahim, Ruzairi Abdul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197968/
https://www.ncbi.nlm.nih.gov/pubmed/34073162
http://dx.doi.org/10.3390/s21113686
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author Mohd Ramli, Nurul Amira
Fazalul Rahiman, Mohd Hafiz
Kamarudin, Latifah Munirah
Mohamed, Latifah
Zakaria, Ammar
Ahmad, Anita
Rahim, Ruzairi Abdul
author_facet Mohd Ramli, Nurul Amira
Fazalul Rahiman, Mohd Hafiz
Kamarudin, Latifah Munirah
Mohamed, Latifah
Zakaria, Ammar
Ahmad, Anita
Rahim, Ruzairi Abdul
author_sort Mohd Ramli, Nurul Amira
collection PubMed
description This manuscript presents a new method to monitor and localize the moisture distribution in a rice silo based on tomography images. Because the rice grain is naturally hygroscopic, the stored grains’ quality depends on their level of moisture content. Higher moisture content leads to fibre degradation, making the grains too frail and possibly milled. If the moisture is too low, the grains become brittle and are susceptible to higher breakage. At present, the single-point measurement method is unreliable because the moisture build-up inside the silo might be distributed unevenly. In addition, this method mostly applies gravimetric analysis, which is destructive. Thus, we proposed a radio tomographic imaging (RTI) system to address these problems. Four simulated phantom profiles at different percentages of moisture content were reconstructed using Newton’s One-Step Error Reconstruction and Tikhonov Regularization algorithms. This simulation study utilized the relationship between the maximum voxel weighting of the reconstructed RTI image and the percentage of moisture content. The outcomes demonstrated promising results, in which the weighting voxel linearly increased with the percentage of moisture content, with a correlation coefficient higher than 0.95 was obtained. Therefore, the results support the possibility of using the RTI approach for monitoring and localizing the moisture distribution inside the rice silo.
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spelling pubmed-81979682021-06-14 A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images Mohd Ramli, Nurul Amira Fazalul Rahiman, Mohd Hafiz Kamarudin, Latifah Munirah Mohamed, Latifah Zakaria, Ammar Ahmad, Anita Rahim, Ruzairi Abdul Sensors (Basel) Article This manuscript presents a new method to monitor and localize the moisture distribution in a rice silo based on tomography images. Because the rice grain is naturally hygroscopic, the stored grains’ quality depends on their level of moisture content. Higher moisture content leads to fibre degradation, making the grains too frail and possibly milled. If the moisture is too low, the grains become brittle and are susceptible to higher breakage. At present, the single-point measurement method is unreliable because the moisture build-up inside the silo might be distributed unevenly. In addition, this method mostly applies gravimetric analysis, which is destructive. Thus, we proposed a radio tomographic imaging (RTI) system to address these problems. Four simulated phantom profiles at different percentages of moisture content were reconstructed using Newton’s One-Step Error Reconstruction and Tikhonov Regularization algorithms. This simulation study utilized the relationship between the maximum voxel weighting of the reconstructed RTI image and the percentage of moisture content. The outcomes demonstrated promising results, in which the weighting voxel linearly increased with the percentage of moisture content, with a correlation coefficient higher than 0.95 was obtained. Therefore, the results support the possibility of using the RTI approach for monitoring and localizing the moisture distribution inside the rice silo. MDPI 2021-05-26 /pmc/articles/PMC8197968/ /pubmed/34073162 http://dx.doi.org/10.3390/s21113686 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mohd Ramli, Nurul Amira
Fazalul Rahiman, Mohd Hafiz
Kamarudin, Latifah Munirah
Mohamed, Latifah
Zakaria, Ammar
Ahmad, Anita
Rahim, Ruzairi Abdul
A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images
title A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images
title_full A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images
title_fullStr A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images
title_full_unstemmed A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images
title_short A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images
title_sort new method of rice moisture content determination using voxel weighting-based from radio tomography images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197968/
https://www.ncbi.nlm.nih.gov/pubmed/34073162
http://dx.doi.org/10.3390/s21113686
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