Hyperspectral imaing approach for contaminant detection in food: A review

In recent years, growing health concerns have highlighted the urgent need for innovative detection methods in the field of food safety. Hyperspectral imaging (HSI) has emerged as a highly promising and widely recognized technology, offering non-destructive detection capabilities that are crucial for...

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Autores principales: Aquino, Dominga C., San Lorenzo, André L.
Formato: Artículo revista
Lenguaje:Español
Publicado: Instituto Agrotécnico "Pedro M. Fuentes Godo" - Facultad de Ciencias Agrarias (UNNE) 2025
Materias:
Detection of microorganisms
Toxins
Non-destructive technique
Food safety
Detección de microorganismos
Toxinas
Técnica no destructiva
Inocuidad alimentaria
Acceso en línea:https://revistas.unne.edu.ar/index.php/agr/article/view/8920
Aporte de:
Revistas UNNE - Universidad Nacional del Noroeste (UNNE) de Universidad Nacional del Nordeste
id I48-R154-article-8920
record_format ojs
spelling I48-R154-article-89202025-12-03T11:31:49Z Hyperspectral imaing approach for contaminant detection in food: A review Aplicación de imágenes hiperespectrales en la detección de contaminantes en alimentos: una revisión Aquino, Dominga C. San Lorenzo, André L. Detection of microorganisms Toxins Non-destructive technique Food safety Detección de microorganismos Toxinas Técnica no destructiva Inocuidad alimentaria In recent years, growing health concerns have highlighted the urgent need for innovative detection methods in the field of food safety. Hyperspectral imaging (HSI) has emerged as a highly promising and widely recognized technology, offering non-destructive detection capabilities that are crucial for identifying food contamination. This paper explores the key characteristics of HSI, its significance in scientific research, and its technological advancements, particularly in its integration with machine learning techniques to enhance the accuracy and efficiency of contamination detection. It becomes evident that HSI not only has the potential to revolutionize food safety practices but also plays a critical role in improving decision-making processes through precise data analysis. The increasing accessibility and global application of HSI technology, combined with advanced data processing methods, position it as a vital tool in addressing the growing challenges related to food contamination. This offers significant benefits for both industry and public health. En los últimos años, las crecientes preocupaciones de salud han resaltado la necesidad urgente de métodos innovadores para garantizar la seguridad alimentaria. La tecnología de imágenes hiperespectrales (HSI, por sus siglas en inglés) ha surgido como una herramienta altamente prometedora y ampliamente reconocida, ofreciendo capacidades de detección no destructivas esenciales para identificar contaminantes en alimentos. Este artículo analiza las principales características de la HSI, su relevancia en la investigación científica y sus avances tecnológicos, en particular su integración con técnicas de aprendizaje automático para mejorar la precisión y eficiencia en la detección de contaminación. Queda claro que la HSI no solo tiene el potencial de revolucionar las prácticas de seguridad alimentaria, sino que también desempeña un papel crítico en la mejora de los procesos de toma de decisiones mediante un análisis de datos preciso. La creciente accesibilidad y aplicación global de esta tecnología, junto con métodos avanzados de procesamiento de datos, posicionan a la HSI como una herramienta clave para abordar los desafíos relacionados con la contaminación de alimentos, ofreciendo beneficios significativos tanto para la industria como para la salud pública. Instituto Agrotécnico "Pedro M. Fuentes Godo" - Facultad de Ciencias Agrarias (UNNE) 2025-12-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unne.edu.ar/index.php/agr/article/view/8920 10.30972/agr.368920 Agrotecnia; Núm. 36 (2025); 1-11 2545-8906 0328-4077 spa https://revistas.unne.edu.ar/index.php/agr/article/view/8920/8551 http://creativecommons.org/licenses/by-nc-sa/4.0
institution Universidad Nacional del Nordeste
institution_str I-48
repository_str R-154
container_title_str Revistas UNNE - Universidad Nacional del Noroeste (UNNE)
language Español
format Artículo revista
topic Detection of microorganisms
Toxins
Non-destructive technique
Food safety
Detección de microorganismos
Toxinas
Técnica no destructiva
Inocuidad alimentaria
spellingShingle Detection of microorganisms
Toxins
Non-destructive technique
Food safety
Detección de microorganismos
Toxinas
Técnica no destructiva
Inocuidad alimentaria
Aquino, Dominga C.
San Lorenzo, André L.
Hyperspectral imaing approach for contaminant detection in food: A review
topic_facet Detection of microorganisms
Toxins
Non-destructive technique
Food safety
Detección de microorganismos
Toxinas
Técnica no destructiva
Inocuidad alimentaria
author Aquino, Dominga C.
San Lorenzo, André L.
author_facet Aquino, Dominga C.
San Lorenzo, André L.
author_sort Aquino, Dominga C.
title Hyperspectral imaing approach for contaminant detection in food: A review
title_short Hyperspectral imaing approach for contaminant detection in food: A review
title_full Hyperspectral imaing approach for contaminant detection in food: A review
title_fullStr Hyperspectral imaing approach for contaminant detection in food: A review
title_full_unstemmed Hyperspectral imaing approach for contaminant detection in food: A review
title_sort hyperspectral imaing approach for contaminant detection in food: a review
description In recent years, growing health concerns have highlighted the urgent need for innovative detection methods in the field of food safety. Hyperspectral imaging (HSI) has emerged as a highly promising and widely recognized technology, offering non-destructive detection capabilities that are crucial for identifying food contamination. This paper explores the key characteristics of HSI, its significance in scientific research, and its technological advancements, particularly in its integration with machine learning techniques to enhance the accuracy and efficiency of contamination detection. It becomes evident that HSI not only has the potential to revolutionize food safety practices but also plays a critical role in improving decision-making processes through precise data analysis. The increasing accessibility and global application of HSI technology, combined with advanced data processing methods, position it as a vital tool in addressing the growing challenges related to food contamination. This offers significant benefits for both industry and public health.
publisher Instituto Agrotécnico "Pedro M. Fuentes Godo" - Facultad de Ciencias Agrarias (UNNE)
publishDate 2025
url https://revistas.unne.edu.ar/index.php/agr/article/view/8920
work_keys_str_mv AT aquinodomingac hyperspectralimaingapproachforcontaminantdetectioninfoodareview
AT sanlorenzoandrel hyperspectralimaingapproachforcontaminantdetectioninfoodareview
AT aquinodomingac aplicaciondeimageneshiperespectralesenladetecciondecontaminantesenalimentosunarevision
AT sanlorenzoandrel aplicaciondeimageneshiperespectralesenladetecciondecontaminantesenalimentosunarevision
first_indexed 2025-12-17T05:00:28Z
last_indexed 2025-12-17T05:00:28Z
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