Articles producció científicaEnginyeria Química

Vibrational spectroscopy using portable devices combined with traditional machine learning: a powerful tool for insect rearing and food quality assessment

  • Datos identificativos

    Identificador:  imarina:9484658
    Autores:  Mendez-Sanchez, Carmen; Ortiz, Mayreli; Guell, Carme; Ferrando, Montserrat; Cozzolino, Daniel; De Lamo Castellvi, Silvia
    Resumen:
    The global population will reach 10 billion by 2050, requiring a 70% increase in food and feed production. Alternative nutrient sources, such as edible insects, are being studied to meet this demand due to their high nutritional value and minimal environmental impact. Insects are rich in protein, lipids, and micronutrients, and their nutritional composition changes depending on species, feeding material, and processing methods. Insect proteins are bioavailable and contain essential amino acids, while lipids offer a balanced ratio of unsaturated and saturated fatty acids. Chitin, a major component of insect exoskeletons, is also relevant due to its biological activity. Insect production requires optimized rearing, processing, and quality control methods. Vibrational spectroscopy can be used to ensure the quality and nutritional integrity of insect-based products. Infrared and Raman spectroscopy are two key types of vibrational spectroscopy that provide valuable information about the molecular composition of insect-based products. The incorporation of vibrational spectroscopy into insect farming and production systems could streamline quality control processes, ensure food safety, and support sustainable practices. Portable and miniaturized spectroscopic devices offer a cost-effective solution for on-site monitoring, providing farmers and manufacturers with a convenient tool to maintain the authenticity, quality, and nutritional integrity of insect-based foods.
  • Otros:

    Enlace a la fuente original: https://www.tandfonline.com/doi/full/10.1080/17518253.2025.2608409
    Referencia de l'ítem segons les normes APA: Mendez-Sanchez, Carmen; Ortiz, Mayreli; Guell, Carme; Ferrando, Montserrat; Cozzolino, Daniel; De Lamo Castellvi, Silvia (2026). Vibrational spectroscopy using portable devices combined with traditional machine learning: a powerful tool for insect rearing and food quality assessment. Green Chemistry Letters And Reviews, 19(1), 2608409-. DOI: 10.1080/17518253.2025.2608409
    Referencia al articulo segun fuente origial: Green Chemistry Letters And Reviews. 19 (1): 2608409-
    DOI del artículo: 10.1080/17518253.2025.2608409
    Año de publicación de la revista: 2026-12-31
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2026-01-17
    Autor/es de la URV: De Lamo Castellvi, Silvia / Ferrando Cogollos, Maria Montserrat / Güell Saperas, Maria Carmen / Méndez Sánchez, Carmen / Ortíz Rodríguez, Mayreli
    Departamento: Enginyeria Química
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    Autor según el artículo: Mendez-Sanchez, Carmen; Ortiz, Mayreli; Guell, Carme; Ferrando, Montserrat; Cozzolino, Daniel; De Lamo Castellvi, Silvia
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Biotecnología, Chemistry (all), Chemistry (miscellaneous), Chemistry, multidisciplinary, Ciência de alimentos, Ciências biológicas ii, Engenharias ii, Environmental chemistry, General chemistry, Green & sustainable science & technology, Materiais, Química
    Direcció de correo del autor: montse.ferrando@urv.cat, montse.ferrando@urv.cat, carme.guell@urv.cat, carme.guell@urv.cat, silvia.delamo@urv.cat, silvia.delamo@urv.cat, carmen.mendez@estudiants.urv.cat, mayreli.ortiz@urv.cat
  • Palabras clave:

    Adulteration
    Authenticity
    Chemometrics
    Fat-body
    Ftir
    Identification
    Infrared spectroscopy
    Insects
    Metabolism
    Near-infrared spectroscopy
    Nutritional-value
    Portable and handheld devices
    Raman spectroscopy
    Tenebrio-molitor
    Traditional machine learning
    Chemistry (Miscellaneous)
    Chemistry
    Multidisciplinary
    Environmental Chemistry
    Green & Sustainable Science & Technology
    Biotecnología
    Chemistry (all)
    Ciência de alimentos
    Ciências biológicas ii
    Engenharias ii
    General chemistry
    Materiais
    Química
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