ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder
In a preliminary study, commercial insect powders were successfully identified using infrared spectroscopy combined with multivariate analysis. Nonetheless, it is necessary to check if this technology is capable of discriminating, predicting, and quantifying insect species once they are used as an ingredient in food products. The objective of this research was to study the potential of using attenuated total reflection Fourier transform mid-infrared spectroscopy (ATR-FTMIR) combined with multivariate analysis to discriminate doughs and 3D-printed baked snacks, enriched with Alphitobius diaperinus and Locusta migratoria powders. Several doughs were made with a variable amount of insect powder (0–13.9%) replacing the same amount of chickpea flour (46–32%). The spectral data were analyzed using soft independent modeling of class analogy (SIMCA) and partial least squares regression (PLSR) algorithms. SIMCA models successfully discriminated the insect species used to prepare the doughs and snacks. Discrimination was mainly associated with lipids, proteins, and chitin. PLSR models predicted the percentage of insect powder added to the dough and the snacks, with determination coefficients of 0.972, 0.979, and 0.994 and a standard error of prediction of 1.24, 1.08, and 1.90%, respectively. ATR-FTMIR combined with multivariate analysis has a high potential as a new tool in insect product authentication.
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Format: | artículo biblioteca |
Language: | English |
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Multidisciplinary Digital Publishing Institute
2021-08-05
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Subjects: | Insect powder, Authentication, 3D food printer, Mid-infrared spectroscopy, Multivariate analysis, |
Online Access: | http://hdl.handle.net/10261/248512 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100000780 |
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dig-iata-es-10261-2485122021-08-24T00:46:55Z ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder García-Gutiérrez, Nerea Mellado-Carretero, Jorge Bengoa, Christophe Salvador, Ana Sanz Taberner, Teresa Wang, Junjing Ferrando, Montse Güell, Carme de Lamo-Castellví, Silvia Ministerio de Economía y Competitividad (España) Ministerio de Ciencia e Innovación (España) European Commission Insect powder Authentication 3D food printer Mid-infrared spectroscopy Multivariate analysis In a preliminary study, commercial insect powders were successfully identified using infrared spectroscopy combined with multivariate analysis. Nonetheless, it is necessary to check if this technology is capable of discriminating, predicting, and quantifying insect species once they are used as an ingredient in food products. The objective of this research was to study the potential of using attenuated total reflection Fourier transform mid-infrared spectroscopy (ATR-FTMIR) combined with multivariate analysis to discriminate doughs and 3D-printed baked snacks, enriched with Alphitobius diaperinus and Locusta migratoria powders. Several doughs were made with a variable amount of insect powder (0–13.9%) replacing the same amount of chickpea flour (46–32%). The spectral data were analyzed using soft independent modeling of class analogy (SIMCA) and partial least squares regression (PLSR) algorithms. SIMCA models successfully discriminated the insect species used to prepare the doughs and snacks. Discrimination was mainly associated with lipids, proteins, and chitin. PLSR models predicted the percentage of insect powder added to the dough and the snacks, with determination coefficients of 0.972, 0.979, and 0.994 and a standard error of prediction of 1.24, 1.08, and 1.90%, respectively. ATR-FTMIR combined with multivariate analysis has a high potential as a new tool in insect product authentication. This research was funded by Ministerio de Economía i Competitividad (CTQ 2014-54520-P), Ministerio de Ciencia e Innovación (PGC2018-097095-B-I00), and Agencia Estatal de Investigación, Fondo Social Europeo (FSE) and Iniciativa de Empleo Juvenil (PEJ2018-004192-A). Peer reviewed 2021-08-23T06:12:17Z 2021-08-23T06:12:17Z 2021-08-05 artículo http://purl.org/coar/resource_type/c_6501 Foods 10(8): 1806 (2021) http://hdl.handle.net/10261/248512 10.3390/foods10081806 2304-8158 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100000780 en #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CTQ 2014-54520-P info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-097095-B-I00 Publisher's version https://doi.org/10.3390/foods10081806 Sí open Multidisciplinary Digital Publishing Institute |
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Insect powder Authentication 3D food printer Mid-infrared spectroscopy Multivariate analysis Insect powder Authentication 3D food printer Mid-infrared spectroscopy Multivariate analysis |
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Insect powder Authentication 3D food printer Mid-infrared spectroscopy Multivariate analysis Insect powder Authentication 3D food printer Mid-infrared spectroscopy Multivariate analysis García-Gutiérrez, Nerea Mellado-Carretero, Jorge Bengoa, Christophe Salvador, Ana Sanz Taberner, Teresa Wang, Junjing Ferrando, Montse Güell, Carme de Lamo-Castellví, Silvia ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder |
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In a preliminary study, commercial insect powders were successfully identified using infrared spectroscopy combined with multivariate analysis. Nonetheless, it is necessary to check if this technology is capable of discriminating, predicting, and quantifying insect species once they are used as an ingredient in food products. The objective of this research was to study the potential of using attenuated total reflection Fourier transform mid-infrared spectroscopy (ATR-FTMIR) combined with multivariate analysis to discriminate doughs and 3D-printed baked snacks, enriched with Alphitobius diaperinus and Locusta migratoria powders. Several doughs were made with a variable amount of insect powder (0–13.9%) replacing the same amount of chickpea flour (46–32%). The spectral data were analyzed using soft independent modeling of class analogy (SIMCA) and partial least squares regression (PLSR) algorithms. SIMCA models successfully discriminated the insect species used to prepare the doughs and snacks. Discrimination was mainly associated with lipids, proteins, and chitin. PLSR models predicted the percentage of insect powder added to the dough and the snacks, with determination coefficients of 0.972, 0.979, and 0.994 and a standard error of prediction of 1.24, 1.08, and 1.90%, respectively. ATR-FTMIR combined with multivariate analysis has a high potential as a new tool in insect product authentication. |
author2 |
Ministerio de Economía y Competitividad (España) |
author_facet |
Ministerio de Economía y Competitividad (España) García-Gutiérrez, Nerea Mellado-Carretero, Jorge Bengoa, Christophe Salvador, Ana Sanz Taberner, Teresa Wang, Junjing Ferrando, Montse Güell, Carme de Lamo-Castellví, Silvia |
format |
artículo |
topic_facet |
Insect powder Authentication 3D food printer Mid-infrared spectroscopy Multivariate analysis |
author |
García-Gutiérrez, Nerea Mellado-Carretero, Jorge Bengoa, Christophe Salvador, Ana Sanz Taberner, Teresa Wang, Junjing Ferrando, Montse Güell, Carme de Lamo-Castellví, Silvia |
author_sort |
García-Gutiérrez, Nerea |
title |
ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder |
title_short |
ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder |
title_full |
ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder |
title_fullStr |
ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder |
title_full_unstemmed |
ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder |
title_sort |
atr-ftir spectroscopy combined with multivariate analysis successfully discriminates raw doughs and baked 3d-printed snacks enriched with edible insect powder |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021-08-05 |
url |
http://hdl.handle.net/10261/248512 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100000780 |
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