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Rapid Detection of Fraudulent Rice Using Low-Cost Digital Sensing Devices and Machine Learning
Rice fraud is one of the common threats to the rice industry. Conventional methods to detect rice adulteration are costly, time-consuming, and tedious. This study proposes the quantitative prediction of rice adulteration levels measured through the packaging using a handheld near-infrared (NIR) spec...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9697730/ https://www.ncbi.nlm.nih.gov/pubmed/36433249 http://dx.doi.org/10.3390/s22228655 |