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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

Full text
Author(s):
Cruz-Tirado, J. P. [1] ; da Silva Medeiros, Maria Lucimar [1] ; Barbin, Douglas Fernandes [1]
Total Authors: 3
Affiliation:
[1] Univ Estadual Campinas, Dept Food Engn, Rua Monteiro Lobato 80, Cidade Univ, BR-13083862 Campinas, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: Journal of Food Engineering; v. 306, OCT 2021.
Web of Science Citations: 7
Abstract

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)

FAPESP's process: 19/06846-5 - Multivariate statistical analyses applied to NIR spectroscopy and digital image analyses for food products
Grantee:Maria Lucimar da Silva Medeiros
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 15/24351-2 - Applications of image analyses and NIR spectroscopy for quality assessment and authentication of food products
Grantee:Douglas Fernandes Barbin
Support Opportunities: Research Grants - Young Investigators Grants
FAPESP's process: 18/02500-4 - Food analyses using NIR spectral imaging
Grantee:Luis Jam Pier Cruz Tirado
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 19/04833-3 - A new approach based on hyperspectral imaging for farming system authentication of seeds
Grantee:Luis Jam Pier Cruz Tirado
Support Opportunities: Scholarships abroad - Research Internship - Master's degree