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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Main Authors: Mohd. Ramli, Nurul Amira, Rahiman, Mohd. Hafiz Fazalul, Kamarudin, Latifah Munirah, Mohamed, Latifah, Zakaria, Ammar, Ahmad, Anita, Abdul Rahim, Ruzairi
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Published: MDPI AG 2021
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Online Access:http://eprints.utm.my/id/eprint/95333/
http://dx.doi.org/10.3390/s21113686
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spelling my.utm.953332022-04-29T22:26:32Z http://eprints.utm.my/id/eprint/95333/ A new method of rice moisture content determination using voxel weighting-based from radio tomography images Mohd. Ramli, Nurul Amira Rahiman, Mohd. Hafiz Fazalul Kamarudin, Latifah Munirah Mohamed, Latifah Zakaria, Ammar Ahmad, Anita Abdul Rahim, Ruzairi TK Electrical engineering. Electronics Nuclear engineering 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 AG 2021 Article PeerReviewed Mohd. Ramli, Nurul Amira and Rahiman, Mohd. Hafiz Fazalul and Kamarudin, Latifah Munirah and Mohamed, Latifah and Zakaria, Ammar and Ahmad, Anita and Abdul Rahim, Ruzairi (2021) A new method of rice moisture content determination using voxel weighting-based from radio tomography images. Sensors, 21 (11). p. 3686. ISSN 1424-8220 http://dx.doi.org/10.3390/s21113686
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd. Ramli, Nurul Amira
Rahiman, Mohd. Hafiz Fazalul
Kamarudin, Latifah Munirah
Mohamed, Latifah
Zakaria, Ammar
Ahmad, Anita
Abdul Rahim, Ruzairi
A new method of rice moisture content determination using voxel weighting-based from radio tomography images
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.
format Article
author Mohd. Ramli, Nurul Amira
Rahiman, Mohd. Hafiz Fazalul
Kamarudin, Latifah Munirah
Mohamed, Latifah
Zakaria, Ammar
Ahmad, Anita
Abdul Rahim, Ruzairi
author_facet Mohd. Ramli, Nurul Amira
Rahiman, Mohd. Hafiz Fazalul
Kamarudin, Latifah Munirah
Mohamed, Latifah
Zakaria, Ammar
Ahmad, Anita
Abdul Rahim, Ruzairi
author_sort Mohd. Ramli, Nurul Amira
title 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_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_sort new method of rice moisture content determination using voxel weighting-based from radio tomography images
publisher MDPI AG
publishDate 2021
url http://eprints.utm.my/id/eprint/95333/
http://dx.doi.org/10.3390/s21113686
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