Effect of agro-climatic conditions on near infrared spectra of extra virgin olive oils
Authentication of extra virgin olive oil requires fast and cost-effective analytical procedures, such as near infrared spectroscopy. Multivariate analysis and chemometrics have been successfully applied in several papers to gather qualitative and quantitative information of extra virgin olive oils f...
| Autores: | , , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2018 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/178509 |
| Acesso em linha: | https://hdl.handle.net/2117/178509 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Extra virgin olive oil infrared spectroscopy agro-climatic data linear correlations redundancy analysis Classificació AMS::82 Statistical mechanics, structure of matter Classificació AMS::62 Statistics::62H Multivariate analysis Classificació AMS::62 Statistics::62P Applications Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica |
| Resumo: | Authentication of extra virgin olive oil requires fast and cost-effective analytical procedures, such as near infrared spectroscopy. Multivariate analysis and chemometrics have been successfully applied in several papers to gather qualitative and quantitative information of extra virgin olive oils from near infrared spectra. Moreover, there are many examples in the literature analysing the effect of agro-climatic conditions on food content, in general, and in olive oil components, in particular. But the majority of these studies considered a factor, a non-numerical variable, containing this meteorological information. The present work uses all the agro-climatic data with the aim of highlighting the linear relationships between them and the near infrared spectra. The study begins with a graphical motivation, continues with a bivariate analysis and, finally, applies redundancy analysis to extend and confirm the previous conclusions. |
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