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...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Capítulo de libro |
| Language: | Inglés |
| Published: |
Elsevier
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11939/6573 https://www.elsevier.com/books/hyperspectral-imaging/amigo/978-0-444-63977-6 |
| _version_ | 1855492110548992000 |
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| author | Blasco, José Munera, Sandra Cubero, Sergio Aleixos, Nuria |
| author2 | Amigo, José M. |
| author_browse | Aleixos, Nuria Amigo, José M. Blasco, José Cubero, Sergio Munera, Sandra |
| author_facet | Amigo, José M. Blasco, José Munera, Sandra Cubero, Sergio Aleixos, Nuria |
| author_sort | Blasco, José |
| collection | ReDivia |
| description | 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. |
| format | Capítulo de libro |
| id | ReDivia6573 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | ReDivia65732025-04-25T14:50:37Z Food and feed production Blasco, José Munera, Sandra Cubero, Sergio Aleixos, Nuria Amigo, José M. N01 Agricultural engineering Food quality Image analysis 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. 2020-08-10T10:30:43Z 2020-08-10T10:30:43Z 2020 bookPart Blasco, J., Munera, S., Cubero, S. & Aleixos, N. (2019) Food and feed production. In: Amigo, J. M. (ed.) Hyperspectral Imaging. Elsevier, (Amsterdam, Holland) 978-0-4446-3977-6 http://hdl.handle.net/20.500.11939/6573 https://www.elsevier.com/books/hyperspectral-imaging/amigo/978-0-444-63977-6 en Hyperspectral Imaging Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ closedAccess Elsevier electronico |
| spellingShingle | N01 Agricultural engineering Food quality Image analysis Blasco, José Munera, Sandra Cubero, Sergio Aleixos, Nuria Food and feed production |
| title | Food and feed production |
| title_full | Food and feed production |
| title_fullStr | Food and feed production |
| title_full_unstemmed | Food and feed production |
| title_short | Food and feed production |
| title_sort | food and feed production |
| topic | N01 Agricultural engineering Food quality Image analysis |
| url | http://hdl.handle.net/20.500.11939/6573 https://www.elsevier.com/books/hyperspectral-imaging/amigo/978-0-444-63977-6 |
| work_keys_str_mv | AT blascojose foodandfeedproduction AT munerasandra foodandfeedproduction AT cuberosergio foodandfeedproduction AT aleixosnuria foodandfeedproduction |