The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology
Food safety is gaining increasing attention worldwide. Currently, low-density organic foreign objects such as insects are extremely challenging to detect using conventional metal detectors and X-ray inspection systems. This study aimed to develop a visible-near-infrared single-pixel imaging (Vis-NIR...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/14/2/206 |
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| author | Hidemasa Taketoshi Tetsuya Inagaki Satoru Tsuchikawa Te Ma |
| author_facet | Hidemasa Taketoshi Tetsuya Inagaki Satoru Tsuchikawa Te Ma |
| author_sort | Hidemasa Taketoshi |
| collection | DOAJ |
| description | Food safety is gaining increasing attention worldwide. Currently, low-density organic foreign objects such as insects are extremely challenging to detect using conventional metal detectors and X-ray inspection systems. This study aimed to develop a visible-near-infrared single-pixel imaging (Vis-NIR-SPI) method to detect small insects inside food. The advantages of Vis-NIR light include its ability to analyze samples non-destructively and measure multiple components simultaneously and quickly, while SPI is robust against dark noise, high scattering, and high equipment costs. The experimental results demonstrated that (1) the newly designed system effectively reduces scattering effects from the highly scattering sample (intralipid 20%), allowing for the capture of information beyond the capabilities of a charge-coupled-device camera; (2) insects positioned behind ham and bread were readily detectable using the imaging reconstruction algorithm; and (3) even for chocolate samples with very high light absorption, only 1 uncontaminated sample out of 100 was mistakenly classified as contaminated, yielding an overall accuracy of 99%. This high level of accuracy underscores the potential of the Vis-NIR-SPI method to provide reliable detection while maintaining sample integrity. Furthermore, this method is cost-effective, offering a practical and efficient solution to improve quality control processes and consumer trust in the food industry. |
| format | Article |
| id | doaj-art-d7814334fd5b453f839a5b308c32f4ef |
| institution | Kabale University |
| issn | 2304-8158 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj-art-d7814334fd5b453f839a5b308c32f4ef2025-01-24T13:32:52ZengMDPI AGFoods2304-81582025-01-0114220610.3390/foods14020206The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging TechnologyHidemasa Taketoshi0Tetsuya Inagaki1Satoru Tsuchikawa2Te Ma3Graduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanGraduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanGraduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanGraduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, JapanFood safety is gaining increasing attention worldwide. Currently, low-density organic foreign objects such as insects are extremely challenging to detect using conventional metal detectors and X-ray inspection systems. This study aimed to develop a visible-near-infrared single-pixel imaging (Vis-NIR-SPI) method to detect small insects inside food. The advantages of Vis-NIR light include its ability to analyze samples non-destructively and measure multiple components simultaneously and quickly, while SPI is robust against dark noise, high scattering, and high equipment costs. The experimental results demonstrated that (1) the newly designed system effectively reduces scattering effects from the highly scattering sample (intralipid 20%), allowing for the capture of information beyond the capabilities of a charge-coupled-device camera; (2) insects positioned behind ham and bread were readily detectable using the imaging reconstruction algorithm; and (3) even for chocolate samples with very high light absorption, only 1 uncontaminated sample out of 100 was mistakenly classified as contaminated, yielding an overall accuracy of 99%. This high level of accuracy underscores the potential of the Vis-NIR-SPI method to provide reliable detection while maintaining sample integrity. Furthermore, this method is cost-effective, offering a practical and efficient solution to improve quality control processes and consumer trust in the food industry.https://www.mdpi.com/2304-8158/14/2/206foodcontaminationinsectdigital micro-mirror deviceprincipial component analysisimage reconstruction algorithm |
| spellingShingle | Hidemasa Taketoshi Tetsuya Inagaki Satoru Tsuchikawa Te Ma The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology Foods food contamination insect digital micro-mirror device principial component analysis image reconstruction algorithm |
| title | The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology |
| title_full | The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology |
| title_fullStr | The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology |
| title_full_unstemmed | The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology |
| title_short | The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology |
| title_sort | detection of pest contaminants in chocolate using visible near infrared single pixel imaging technology |
| topic | food contamination insect digital micro-mirror device principial component analysis image reconstruction algorithm |
| url | https://www.mdpi.com/2304-8158/14/2/206 |
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