Evidence on the discrimination of quinoa grains with a combination of FT-MIR and FT-NIR spectroscopy
Quinoa is considered as a valuable re-emergent crop due to its nutritional composition. In this study, five quinoa grains from different geographical origin (Real, CHEN 252, Regalona, BO25 and UDc9) were discriminated using a combination of FT-MIR and FT-NIR spectra as input for principal component...
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| Veröffentlicht in: | Journal of food science and technology 2019-10, Vol.56 (10), p.4457-4464 |
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| creator | Rodríguez, Silvio D. López-Fernández, M. P. Maldonado, S. Buera, M. P. |
| description | Quinoa is considered as a valuable re-emergent crop due to its nutritional composition. In this study, five quinoa grains from different geographical origin (Real, CHEN 252, Regalona, BO25 and UDc9) were discriminated using a combination of FT-MIR and FT-NIR spectra as input for principal component analysis (PCA), cluster analysis (CA) and soft independent modelling class analogy (SIMCA). The results obtained from PCA and CA show a great power of discrimination, with an average silhouette width value of 0.96. Moreover, SIMCA showed an error rate and accuracy values of 0 and 1 respectively with only 4% misclassified samples. A relationship between each principal component and the most important variables for the discrimination were mainly due to vibrations of several oleofins groups (C–H, C–H
2
, C–H
3
), alkene group (–CH=CH–), hydroxyl group (O–H) and Amides I and II vibrational modes. |
| doi_str_mv | 10.1007/s13197-019-03948-7 |
| format | Article |
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2
, C–H
3
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2
, C–H
3
), alkene group (–CH=CH–), hydroxyl group (O–H) and Amides I and II vibrational modes.</description><subject>Amides</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Chemistry/Food Science</subject><subject>Cluster analysis</subject><subject>Discrimination</subject><subject>Food Science</subject><subject>Grain</subject><subject>Hydroxyl groups</subject><subject>Nutrition</subject><subject>Original</subject><subject>Original Article</subject><subject>Principal components analysis</subject><subject>Quinoa</subject><subject>Spectroscopy</subject><subject>Spectrum analysis</subject><subject>Vibrations</subject><issn>0022-1155</issn><issn>0975-8402</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9UV1vFCEUJUZjm9o_4BOJL76MXi4MDC8mpmltk6qJqc-EAWaXZhe2MFPTfy_bbfx6kBdO4JyTe-4h5DWDdwxAva-MM606YLoDrsXQqWfkGLTqu0EAPm8YEDvG-v6InNZ6C-1wVAPCS3LEmRykVOqY-PP76ENygeZE53WgPlZX4jYmO8f2lCd6t8SULV0VG1OlP-K8ppa6vB3_4FzcdJ-vvlGb_B5-abDugptLri7vHl6RF5Pd1HD6dJ-Q7xfnN2eX3fXXT1dnH687J3o2d26cZBgZYksxWa9R4BCUAMe1VqPXWoxCuB69xKCU5IDgwyA5RwQH08RPyIeD724Zt8G7kOZiN2bX8tjyYLKN5u-fFNdmle-NHICh1M3g7ZNByXdLqLPZtnWEzcamkJdqkLfplO4VNuqbf6i3eSmpxTOIEnuhOewN8cBybRW1hOnXMAzMvkdz6NG0Hs1jj0Y1ET-IaiOnVSi_rf-j-gkJTJ4G</recordid><startdate>20191001</startdate><enddate>20191001</enddate><creator>Rodríguez, Silvio D.</creator><creator>López-Fernández, M. 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P. ; Maldonado, S. ; Buera, M. P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c451t-cbf6eb122975fad92428e740c3997bd994b44c52d62e7763020de8633220c0ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Amides</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Chemistry/Food Science</topic><topic>Cluster analysis</topic><topic>Discrimination</topic><topic>Food Science</topic><topic>Grain</topic><topic>Hydroxyl groups</topic><topic>Nutrition</topic><topic>Original</topic><topic>Original Article</topic><topic>Principal components analysis</topic><topic>Quinoa</topic><topic>Spectroscopy</topic><topic>Spectrum analysis</topic><topic>Vibrations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rodríguez, Silvio D.</creatorcontrib><creatorcontrib>López-Fernández, M. 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The results obtained from PCA and CA show a great power of discrimination, with an average silhouette width value of 0.96. Moreover, SIMCA showed an error rate and accuracy values of 0 and 1 respectively with only 4% misclassified samples. A relationship between each principal component and the most important variables for the discrimination were mainly due to vibrations of several oleofins groups (C–H, C–H
2
, C–H
3
), alkene group (–CH=CH–), hydroxyl group (O–H) and Amides I and II vibrational modes.</abstract><cop>New Delhi</cop><pub>Springer India</pub><pmid>31686677</pmid><doi>10.1007/s13197-019-03948-7</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-5559-8124</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Amides Chemistry Chemistry and Materials Science Chemistry/Food Science Cluster analysis Discrimination Food Science Grain Hydroxyl groups Nutrition Original Original Article Principal components analysis Quinoa Spectroscopy Spectrum analysis Vibrations |
| title | Evidence on the discrimination of quinoa grains with a combination of FT-MIR and FT-NIR spectroscopy |
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