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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| Published in | Sensors (Basel, Switzerland) Vol. 21; no. 11; p. 3686 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
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| Abstract | 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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| AbstractList | 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. |
| Author | Fazalul Rahiman, Mohd Hafiz Mohamed, Latifah Rahim, Ruzairi Abdul Zakaria, Ammar Kamarudin, Latifah Munirah Mohd Ramli, Nurul Amira Ahmad, Anita |
| AuthorAffiliation | 3 Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia 2 Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia; latifahmunirah@unimap.edu.my 1 Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia; amira90.ramli@gmail.com (N.A.M.R.); latifah@unimap.edu.my (L.M.); ammarzakaria@unimap.edu.my (A.Z.) 4 School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor 81310, Malaysia; anita@utm.my (A.A.); ruzairi@utm.my (R.A.R.) |
| AuthorAffiliation_xml | – name: 3 Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia – name: 4 School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor 81310, Malaysia; anita@utm.my (A.A.); ruzairi@utm.my (R.A.R.) – name: 1 Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia; amira90.ramli@gmail.com (N.A.M.R.); latifah@unimap.edu.my (L.M.); ammarzakaria@unimap.edu.my (A.Z.) – name: 2 Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Pauh Putra Campus, Perlis 02600, Malaysia; latifahmunirah@unimap.edu.my |
| Author_xml | – sequence: 1 givenname: Nurul Amira orcidid: 0000-0002-8965-6297 surname: Mohd Ramli fullname: Mohd Ramli, Nurul Amira – sequence: 2 givenname: Mohd Hafiz orcidid: 0000-0002-0933-5566 surname: Fazalul Rahiman fullname: Fazalul Rahiman, Mohd Hafiz – sequence: 3 givenname: Latifah Munirah orcidid: 0000-0002-2547-3934 surname: Kamarudin fullname: Kamarudin, Latifah Munirah – sequence: 4 givenname: Latifah orcidid: 0000-0003-0271-1722 surname: Mohamed fullname: Mohamed, Latifah – sequence: 5 givenname: Ammar orcidid: 0000-0002-7108-215X surname: Zakaria fullname: Zakaria, Ammar – sequence: 6 givenname: Anita surname: Ahmad fullname: Ahmad, Anita – sequence: 7 givenname: Ruzairi Abdul surname: Rahim fullname: Rahim, Ruzairi Abdul |
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| CitedBy_id | crossref_primary_10_1016_j_biosystemseng_2024_03_005 crossref_primary_10_1016_j_flowmeasinst_2022_102234 crossref_primary_10_1088_1755_1315_1338_1_012049 crossref_primary_10_4081_jae_2022_1472 |
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| Snippet | 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... |
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| SubjectTerms | Agricultural production Algorithms Correlation coefficients Dielectric properties Embrittlement Grain Grain storage Gravimetric analysis image reconstruction Measurement methods Moisture content moisture measurement radio tomography Regularization Rice rice moisture content rice silo Sensors Simulation Tomography Weighting Wireless networks |
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| Title | A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images |
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