On-line monitoring of egg freshness using a portable NIR spectrometer in tandem with machine learning

Autor(es)

Cruz-Tirado, J. P. ^[1] ; da Silva Medeiros, Maria Lucimar ^[1] ; Barbin, Douglas Fernandes ^[1]

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas, Dept Food Engn, Rua Monteiro Lobato 80, Cidade Univ, BR-13083862 Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Journal of Food Engineering; v. 306, OCT 2021.
• Citações Web of Science: 7

Resumo

Despite having an affordable price, several reports of egg mislabeling are published annually, which involves selling stale eggs as fresh. NIR spectroscopy has been successfully used for the prediction of eggs' freshness. In recent years, a new generation of low-cost, portable NIR sensors has been investigated for on-line and in situ food analysis. The main goal of this work was to investigate the performance of one of the smallest and cheapest NIR spectrometer for on-line estimation of egg freshness. Spectral data obtained was processed using different combinations of pre-treatment, and machine learning methods have been assayed to predict the Haugh unit (HU) value (PLS-R and SVM-R) and to classify fresh and stale eggs (PLS-DA and SVM-C). PLS-R and SVM-R regression showed similar performance, but SVM-R model in the spectral region of 1300-1690 nm showed the best results with a relative error of 7.32% and RPD of 2.56. PLS-DA presented better results than SVM-C for the classification of fresh and stale eggs, with an accuracy of 87.0%, with higher sensitivity for identification of stale eggs. The results show that a small portable NIR spectrometer is a cost-effective and reliable device to predict the freshness of hen's eggs with prediction accuracy comparable to benchtop devices. This could help food control agencies implement portable NIR sensors at different egg supply chain stages. (AU)

• Processo FAPESP: 19/06846-5 - Análise multivariada combinada à espectroscopia por infravermelho próximo e imagens digitais aplicada a alimentos
• Beneficiário: Maria Lucimar da Silva Medeiros
• Modalidade de apoio: Bolsas no Brasil - Mestrado
• Processo FAPESP: 15/24351-2 - Análise de imagens e espectroscopia de infravermelho próximo (NIR) na avaliação de qualidade e autenticação de alimentos
• Beneficiário: Douglas Fernandes Barbin
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores
• Processo FAPESP: 18/02500-4 - Análise de alimentos: uma abordagem utilizando imagens NIR
• Beneficiário: Luis Jam Pier Cruz Tirado
• Modalidade de apoio: Bolsas no Brasil - Mestrado
• Processo FAPESP: 19/04833-3 - Uma nova abordagem baseada em imagens hiperespectrais para autenticação do sistema de cultivo de sementes
• Beneficiário: Luis Jam Pier Cruz Tirado
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Mestrado