Articles producció científicaEnginyeria Química

Rapid Determination of Insect Lipids and Their Fatty Acid Profile in Dough Using Handheld and Portable Infrared Spectrometers

  • Dades identificatives

    Identificador:  imarina:9443132
    Autors:  Mendez-Sanchez, C; Ranasinghe, MK; Güell, C; Ferrando, M; Rodriguez-Saona, L; Castellvi, SD
    Resum:
    The objective of the study was to evaluate infrared (IR) spectroscopy in combination with pattern recognition analysis as a rapid technique to quantify the percentage of insect lipid added into the chickpea-based dough as well as the dough's fatty acid profile. Several chickpea-based doughs were prepared with a variable amount of Tenebrio molitor, Alphitobius diaperinus, and Acheta domesticus lipid fraction (0, 2.9%, 5.8%, 8.7%, and 11.6%) replacing the same amount of olive and sunflower oil. The raw dough was analyzed using portable Fourier transform mid-infrared (FT-MIR) and handheld FT near (FT-NIR) spectrometers. The fatty acid profile was determined by using fatty acid methyl esters (FAME) methods. Partial least squares regression (PLSR) with cross-validation (leave-one-out) was used to build up a model to predict the percentage of insect lipid added showing a low standard error of cross-validation (SECV = 0.85), and great predictive ability (RPD, 5.21-5.53) with the external validation set. The saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids as well as the content of palmitic, oleic, and linoleic were correctly predicted with values of SECV = 0.88. Nonetheless, the FT-MIR device tested showed higher performance to predict SFA, MUFA, PUFA, and fatty acids reaching values of 0.97 in coefficient of correlation (RP) and 2.81% in standard error in prediction (SEP).
  • Altres:

    Autor segons l'article: Mendez-Sanchez, C; Ranasinghe, MK; Güell, C; Ferrando, M; Rodriguez-Saona, L; Castellvi, SD
    Departament: Enginyeria Química
    Autor/s de la URV: De Lamo Castellvi, Silvia / Ferrando Cogollos, Maria Montserrat / Güell Saperas, Maria Carmen
    Paraules clau: Replacement; Prediction; Olive; Oi; Near-infrared; Mid-infrared; Inulin; Insect lipids; Ftir spectroscopy; Chemometrics; Chemometric
    Resum: The objective of the study was to evaluate infrared (IR) spectroscopy in combination with pattern recognition analysis as a rapid technique to quantify the percentage of insect lipid added into the chickpea-based dough as well as the dough's fatty acid profile. Several chickpea-based doughs were prepared with a variable amount of Tenebrio molitor, Alphitobius diaperinus, and Acheta domesticus lipid fraction (0, 2.9%, 5.8%, 8.7%, and 11.6%) replacing the same amount of olive and sunflower oil. The raw dough was analyzed using portable Fourier transform mid-infrared (FT-MIR) and handheld FT near (FT-NIR) spectrometers. The fatty acid profile was determined by using fatty acid methyl esters (FAME) methods. Partial least squares regression (PLSR) with cross-validation (leave-one-out) was used to build up a model to predict the percentage of insect lipid added showing a low standard error of cross-validation (SECV = 0.85), and great predictive ability (RPD, 5.21-5.53) with the external validation set. The saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids as well as the content of palmitic, oleic, and linoleic were correctly predicted with values of SECV = 0.88. Nonetheless, the FT-MIR device tested showed higher performance to predict SFA, MUFA, PUFA, and fatty acids reaching values of 0.97 in coefficient of correlation (RP) and 2.81% in standard error in prediction (SEP).
    Grup de recerca: NanoFoods
    Àrees temàtiques: Zootecnia / recursos pesqueiros; Saúde coletiva; Safety, risk, reliability and quality; Química; Process chemistry and technology; Nutrição; Medicina veterinaria; Medicina ii; Medicina i; Materiais; Interdisciplinar; Industrial and manufacturing engineering; Food science & technology; Food science; Farmacia; Ensino; Engenharias ii; Ciências biológicas ii; Ciências biológicas i; Ciências agrárias i; Ciência de alimentos; Biotecnología; Biodiversidade
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: silvia.delamo@urv.cat; carme.guell@urv.cat; montse.ferrando@urv.cat
    Data d'alta del registre: 2026-02-13
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://link.springer.com/article/10.1007/s11947-025-03772-2#article-info
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Food And Bioprocess Technology. 18 (6): 5303-5317
    Referència de l'ítem segons les normes APA: Mendez-Sanchez, C; Ranasinghe, MK; Güell, C; Ferrando, M; Rodriguez-Saona, L; Castellvi, SD (2025). Rapid Determination of Insect Lipids and Their Fatty Acid Profile in Dough Using Handheld and Portable Infrared Spectrometers. Food And Bioprocess Technology, 18(6), 5303-5317. DOI: 10.1007/s11947-025-03772-2
    DOI de l'article: 10.1007/s11947-025-03772-2
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2025-06-01
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Food Science,Food Science & Technology,Industrial and Manufacturing Engineering,Process Chemistry and Technology,Safety, Risk, Reliability and Quality
    Replacement
    Prediction
    Olive
    Oi
    Near-infrared
    Mid-infrared
    Inulin
    Insect lipids
    Ftir spectroscopy
    Chemometrics
    Chemometric
    Zootecnia / recursos pesqueiros
    Saúde coletiva
    Safety, risk, reliability and quality
    Química
    Process chemistry and technology
    Nutrição
    Medicina veterinaria
    Medicina ii
    Medicina i
    Materiais
    Interdisciplinar
    Industrial and manufacturing engineering
    Food science & technology
    Food science
    Farmacia
    Ensino
    Engenharias ii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Ciência de alimentos
    Biotecnología
    Biodiversidade
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