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dc.contributor.authorGonzalez Viejo, C.en
dc.contributor.authorTorrico, Damiren
dc.contributor.authorDunshea, F. R.en
dc.contributor.authorFuentes, S.en
dc.date.accessioned2020-09-20T23:04:11Z
dc.date.available2019-11-01en
dc.date.issued2019-11-01en
dc.date.submitted2019-10-10en
dc.identifier.urihttps://hdl.handle.net/10182/12725
dc.description.abstractBeverages is a broad and important category within the food industry, which is comprised of a wide range of sub-categories and types of drinks with different levels of complexity for their manufacturing and quality assessment. Traditional methods to evaluate the quality traits of beverages consist of tedious, time-consuming, and costly techniques, which do not allow researchers to procure results in real-time. Therefore, there is a need to test and implement emerging technologies in order to automate and facilitate those analyses within this industry. This paper aimed to present the most recent publications and trends regarding the use of low-cost, reliable, and accurate, remote or non-contact techniques using robotics, machine learning, computer vision, biometrics and the application of artificial intelligence, as well as to identify the research gaps within the beverage industry. It was found that there is a wide opportunity in the development and use of robotics and biometrics for all types of beverages, but especially for hot and non-alcoholic drinks. Furthermore, there is a lack of knowledge and clarity within the industry, and research about the concepts of artificial intelligence and machine learning, as well as that concerning the correct design and interpretation of modeling related to the lack of inclusion of relevant data, additional to presenting over- or under-fitted models.en
dc.format.extent25en
dc.languageenen
dc.language.isoenen
dc.publisherMDPI AGen
dc.relationThe original publication is available from - MDPI AG - https://doi.org/10.3390/beverages5040062en
dc.relation.urihttps://doi.org/10.3390/beverages5040062en
dc.rights© 2019 by the authorsen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectroboticsen
dc.subjectmachine learningen
dc.subjectcomputer visionen
dc.subjectbiometricsen
dc.subjectartificial intelligenceen
dc.titleEmerging technologies based on artificial intelligence to assess the quality and consumer preference of beveragesen
dc.typeJournal Article
lu.contributor.unitLincoln Universityen
lu.contributor.unitFaculty of Agriculture and Life Sciencesen
lu.contributor.unitDepartment of Wine, Food and Molecular Biosciencesen
dc.identifier.doi10.3390/beverages5040062en
dc.subject.anzsrc080104 Computer Visionen
dc.subject.anzsrc080199 Artificial Intelligence and Image Processing not elsewhere classifieden
dc.subject.anzsrc170203 Knowledge Representation and Machine Learningen
dc.subject.anzsrc080101 Adaptive Agents and Intelligent Roboticsen
dc.subject.anzsrc0706 Horticultural Productionen
dc.subject.anzsrc0908 Food Sciencesen
dc.relation.isPartOfBeveragesen
pubs.issue4en
pubs.notesArticle number: 62en
pubs.organisational-group/LU
pubs.organisational-group/LU/Agriculture and Life Sciences
pubs.organisational-group/LU/Agriculture and Life Sciences/WFMB
pubs.publication-statusPublished onlineen
pubs.volume5en
dc.identifier.eissn2306-5710en
dc.rights.licenceAttributionen
lu.identifier.orcid0000-0003-1482-2438


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