Author, as appears in the article.: Garcia-Gutierrez, Nerea; Mellado-Carretero, Jorge; Bengoa, Christophe; Salvador, Ana; Sanz, Teresa; Wang, Junjing; Ferrando, Montse; Guell, Carme; de Lamo-Castellvi, Silvia
Department: Enginyeria Química
URV's Author/s: Bengoa, Christophe José / De Lamo Castellvi, Silvia / Ferrando Cogollos, Maria Montserrat / García Gutiérrez, Nerea / Güell Saperas, Maria Carmen / Mellado Carretero, Jorge / Wang, Junjing
Project code: Grant agreement No. 713679
Keywords: Simca Proteins Prediction Multivariate analysis Mid-infrared spectroscopy Insect powder Infrared spectroscopy Heat Food Chitin Authentication 3d food printer
Abstract: 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.
Thematic Areas: Plant science Microbiology Health professions (miscellaneous) Health (social science) Food science & technology Food science
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: 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
Author identifier: 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
Record's date: 2024-10-26
Papper version: info:eu-repo/semantics/publishedVersion
Funding program: Martí i Franquès COFUND Doctoral Programme
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Foods. 10 (8): 1806-
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
Acronym: MFP
Entity: Universitat Rovira i Virgili
Journal publication year: 2021
Funding program action: Marie Skłodowska-Curie Actions - European Union's Horizon 2020 research and innovation programme
Publication Type: Journal Publications
Repositori URV