Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification
Joint Authors
Barbon, Sylvio
Costa Barbon, Ana Paula Ayub da
Mantovani, Rafael Gomes
Barbin, Douglas Fernandes
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-07
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Identification of chicken quality parameters is often inconsistent, time-consuming, and laborious.
Near-infrared (NIR) spectroscopy has been used as a powerful tool for food quality assessment.
However, the near-infrared (NIR) spectra comprise a large number of redundant information.
Determining wavelengths relevance and selecting subsets for classification and prediction models are mandatory for the development of multispectral systems.
A combination of both attribute and wavelength selection for NIR spectral information of chicken meat samples was investigated.
Decision Trees and Decision Table predictors exploit these optimal wavelengths for classification tasks according to different quality grades of poultry meat.
The proposed methodology was conducted with a support vector machine algorithm (SVM) to compare the precision of the proposed model.
Experiments were performed on NIR spectral information (1050 wavelengths), colour (CIEL∗a∗b∗, chroma, and hue), water holding capacity (WHC), and pH of each sample analyzed.
Results show that the best method was the REPTree based on 12 wavelengths, allowing for classification of poultry samples according to quality grades with 77.2% precision.
The selected wavelengths could lead to potential simple multispectral acquisition devices.
American Psychological Association (APA)
Barbon, Sylvio& Costa Barbon, Ana Paula Ayub da& Mantovani, Rafael Gomes& Barbin, Douglas Fernandes. 2018. Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification. Journal of Spectroscopy،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1202682
Modern Language Association (MLA)
Barbon, Sylvio…[et al.]. Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification. Journal of Spectroscopy No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1202682
American Medical Association (AMA)
Barbon, Sylvio& Costa Barbon, Ana Paula Ayub da& Mantovani, Rafael Gomes& Barbin, Douglas Fernandes. Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification. Journal of Spectroscopy. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1202682
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202682