Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment
In recent years, new and emerging digital technologies applied to food science have been gaining attention and increased interest from researchers and the food/beverage industries. In particular, those digital technologies that can be used throughout the food value chain are accurate, easy to implem...
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| Materyal Türü: | Online |
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| Dil: | İngilizce |
| Baskı/Yayın Bilgisi: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Konular: | |
| Online Erişim: | ONIX_20220506_9783036540801_130 |
| Etiketler: |
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| _version_ | 1869515192028626944 |
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| collection | Directory of Open Access Books |
| description | In recent years, new and emerging digital technologies applied to food science have been gaining attention and increased interest from researchers and the food/beverage industries. In particular, those digital technologies that can be used throughout the food value chain are accurate, easy to implement, affordable, and user-friendly. Hence, this Special Issue (SI) is dedicated to novel technology based on sensor technology and machine/deep learning modeling strategies to implement artificial intelligence (AI) into food and beverage production and for consumer assessment. This SI published quality papers from researchers in Australia, New Zealand, the United States, Spain, and Mexico, including food and beverage products, such as grapes and wine, chocolate, honey, whiskey, avocado pulp, and a variety of other food products. |
| format | Online |
| id | doab-20.500.12854ir-81064 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-810642024-03-28T03:31:18Z Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment Fuentes, Sigfredo sensory physicochemical measurements artificial neural networks near infra-red spectroscopy wine quality machine learning modeling weather consumer acceptance prediction data fusion emotion recognition facial expression recognition galvanic skin response machine learning neural networks sensory analysis avocado cultivars preference mapping sensory evaluation sensory descriptive analysis consumer science unifloral honeys botanical origin physicochemical parameters classification natural language processing deep learning sensory science flavor lexicon long short-term memory n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes In recent years, new and emerging digital technologies applied to food science have been gaining attention and increased interest from researchers and the food/beverage industries. In particular, those digital technologies that can be used throughout the food value chain are accurate, easy to implement, affordable, and user-friendly. Hence, this Special Issue (SI) is dedicated to novel technology based on sensor technology and machine/deep learning modeling strategies to implement artificial intelligence (AI) into food and beverage production and for consumer assessment. This SI published quality papers from researchers in Australia, New Zealand, the United States, Spain, and Mexico, including food and beverage products, such as grapes and wine, chocolate, honey, whiskey, avocado pulp, and a variety of other food products. 2022-05-06T11:25:32Z 2022-05-06T11:25:32Z 2022 book ONIX_20220506_9783036540801_130 9783036540801 9783036540795 https://directory.doabooks.org/handle/20.500.12854/81064 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/5406 https://mdpi.com/books/pdfview/book/5406 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-4079-5 10.3390/books978-3-0365-4079-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036540801 9783036540795 114 Basel open access |
| spellingShingle | sensory physicochemical measurements artificial neural networks near infra-red spectroscopy wine quality machine learning modeling weather consumer acceptance prediction data fusion emotion recognition facial expression recognition galvanic skin response machine learning neural networks sensory analysis avocado cultivars preference mapping sensory evaluation sensory descriptive analysis consumer science unifloral honeys botanical origin physicochemical parameters classification natural language processing deep learning sensory science flavor lexicon long short-term memory n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment |
| title | Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment |
| title_full | Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment |
| title_fullStr | Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment |
| title_full_unstemmed | Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment |
| title_short | Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment |
| title_sort | implementation of artificial intelligence in food science food quality and consumer preference assessment |
| topic | sensory physicochemical measurements artificial neural networks near infra-red spectroscopy wine quality machine learning modeling weather consumer acceptance prediction data fusion emotion recognition facial expression recognition galvanic skin response machine learning neural networks sensory analysis avocado cultivars preference mapping sensory evaluation sensory descriptive analysis consumer science unifloral honeys botanical origin physicochemical parameters classification natural language processing deep learning sensory science flavor lexicon long short-term memory n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes |
| topic_facet | sensory physicochemical measurements artificial neural networks near infra-red spectroscopy wine quality machine learning modeling weather consumer acceptance prediction data fusion emotion recognition facial expression recognition galvanic skin response machine learning neural networks sensory analysis avocado cultivars preference mapping sensory evaluation sensory descriptive analysis consumer science unifloral honeys botanical origin physicochemical parameters classification natural language processing deep learning sensory science flavor lexicon long short-term memory n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes |
| url | ONIX_20220506_9783036540801_130 |