Food and feed production
Conventional analytical techniques employ destructive methods, which are normally expensive, contaminating, time-consuming and only a few samples per batch can be monitored at a time. Hyperspectral imaging, instead, can be applied to the inspection of a large range of food, including fish, meat, fru...
| Autores principales: | , , , |
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| Otros Autores: | |
| Formato: | bookPart |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2020
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/6573 https://www.elsevier.com/books/hyperspectral-imaging/amigo/978-0-444-63977-6 |
| Sumario: | Conventional analytical techniques employ destructive methods, which are normally expensive, contaminating, time-consuming and only a few samples per batch can be monitored at a time. Hyperspectral imaging, instead, can be applied to the inspection of a large range of food, including fish, meat, fruit, and vegetables. Depending on the type of food and the properties to be analyzed, different wavelength dispersion devices, cameras, or illumination sources have to be used to capture images in the most appropriate spectral ranges. Later, specific statistical prediction or classification models have to be built to analyze the huge amount of data captured by such devices. This chapter explores the use of hyperspectral imaging for practical applications in food quality and safety inspection. Different technologies for acquiring the images as well as the most commonly used methods to extract useful information from the images are described by analyzing the most recent applications. |
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