Autor segons l'article: Garcia-Gutierrez, Nerea; Mellado-Carretero, Jorge; Bengoa, Christophe; Salvador, Ana; Sanz, Teresa; Wang, Junjing; Ferrando, Montse; Guell, Carme; de Lamo-Castellvi, Silvia
Departament: Enginyeria Química
Autor/s de la URV: Bengoa, Christophe José / De Lamo Castellvi, Silvia / Ferrando Cogollos, Maria Montserrat / García Gutiérrez, Nerea / Güell Saperas, Maria Carmen / Mellado Carretero, Jorge / Wang, Junjing
Codi de projecte: Grant agreement No. 713679
Paraules clau: Simca Proteins Prediction Multivariate analysis Mid-infrared spectroscopy Insect powder Infrared spectroscopy Heat Food Chitin Authentication 3d food printer
Resum: 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.
Àrees temàtiques: Plant science Microbiology Health professions (miscellaneous) Health (social science) Food science & technology Food science
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: nerea.garciagu@estudiants.urv.cat junjing.wang@estudiants.urv.cat jorge.mellado@estudiants.urv.cat jorge.mellado@estudiants.urv.cat christophe.bengoa@urv.cat silvia.delamo@urv.cat silvia.delamo@urv.cat carme.guell@urv.cat carme.guell@urv.cat montse.ferrando@urv.cat montse.ferrando@urv.cat
Identificador de l'autor: 0000-0001-9160-5010 0000-0002-5261-6806 0000-0002-5261-6806 0000-0002-4566-5132 0000-0002-4566-5132 0000-0002-2076-4222 0000-0002-2076-4222
Data d'alta del registre: 2024-10-26
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://www.mdpi.com/2304-8158/10/8/1806
Programa de finançament: Martí i Franquès COFUND Doctoral Programme
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Foods. 10 (8): 1806-
Referència de l'ítem segons les normes APA: Garcia-Gutierrez, Nerea; Mellado-Carretero, Jorge; Bengoa, Christophe; Salvador, Ana; Sanz, Teresa; Wang, Junjing; Ferrando, Montse; Guell, Carme; de (2021). ATR-FTIR Spectroscopy Combined with Multivariate Analysis Successfully Discriminates Raw Doughs and Baked 3D-Printed Snacks Enriched with Edible Insect Powder. Foods, 10(8), 1806-. DOI: 10.3390/foods10081806
Acrònim: MFP
DOI de l'article: 10.3390/foods10081806
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2021
Acció del programa de finançament: Marie Skłodowska-Curie Actions - European Union's Horizon 2020 research and innovation programme
Tipus de publicació: Journal Publications
Repositori URV