A systematized review on the applications of hyperspectral imaging for quality control of potatoes

Peraza Alemán, Carlos Miguel; López Maestresalas, Ainara; Jarén Ceballos, Carmen; Rubio Padilla, Niuton; Arazuri Garín, Silvia

A systematized review on the applications of hyperspectral imaging for quality control of potatoes

dc.contributor.author	Peraza Alemán, Carlos Miguel
dc.contributor.author	López Maestresalas, Ainara
dc.contributor.author	Jarén Ceballos, Carmen
dc.contributor.author	Rubio Padilla, Niuton
dc.contributor.author	Arazuri Garín, Silvia
dc.contributor.department	Ingeniería	es_ES
dc.contributor.department	Ingeniaritza	eu
dc.contributor.department	Institute on Innovation and Sustainable Development in Food Chain - ISFOOD	en
dc.contributor.funder	Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa	es
dc.date.accessioned	2024-02-23T17:34:55Z
dc.date.available	2024-02-23T17:34:55Z
dc.date.issued	2024
dc.date.updated	2024-02-23T16:52:59Z
dc.description.abstract	The application of hyperspectral imaging (HSI) has gained signifcant importance in the past decade, particulary in the context of food analysis, including potatoes. However, the current literature lacks a comprehensive systematic review of the application of this technique in potato cultivation. Therefore, the aim of this work was to conduct a systematized review by analysing the most relevant compounds, diseases and stress factors in potatoes using hyperspectral imaging. For this purpose, scientifc studies were retrieved through a systematic keyword search in Web of Science and Scopus databases. Studies were only included in the review if they provided at least one set of quantitative data. As a result, a total of 52 unique studies were included in the review. Eligible studies were assigned an in-house developed quality scale identifying them as high, medium or low risk. In most cases the studies were rated as low risk. Finally, a comprehensive overview of the HSI applications in potatoes was performed. It has been observed that most of the selected studies obtained better results using linear methods. In addition, a meta-analysis of studies based on regression and classifcation was attempted but was not possible as not enough studies were found for a specifc variable.	en
dc.description.sponsorship	The funding of this work has been covered by the Ministry of Science and Innovation (Spain) project: PID2019-109790RR-C22 and the predoctoral grant (PRE2020-094533) associated to it. The Open Access funding was provided by Universidad Pública de Navarra.	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Peraza-Alemán, C. M., López-Maestresalas, A., Jarén, C., Rubio-Padilla, N., Arazuri, S. (2024) A systematized review on the applications of hyperspectral imaging for quality control of potatoes. Potato Research, 1-23. https://doi.org/10.1007/s11540-024-09702-7.	en
dc.identifier.doi	10.1007/s11540-024-09702-7
dc.identifier.issn	0014-3065
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/47557
dc.language.iso	eng	en
dc.publisher	Springer	en
dc.relation.ispartof	Potato Research 2024, 1-23	en
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-109790RR-C22/ES/
dc.relation.publisherversion	https://doi.org/10.1007/s11540-024-09702-7
dc.rights	Creative Commons BY-NC-ND 4.0 Attribution-NonCommercial-NoDerivs 4.0 International	en
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Food quality control	en
dc.subject	Hyperspectral imaging	en
dc.subject	Machine learning	en
dc.subject	Nondestructive techniques	en
dc.subject	Potatoes	en
dc.subject	Solanum tuberosum L.	en
dc.subject	Systematized review	en
dc.title	A systematized review on the applications of hyperspectral imaging for quality control of potatoes	en
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/publishedVersion
dspace.entity.type	Publication
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