Author, as appears in the article.: Mabood F; Boqué R; Alkindi AY; Al-Harrasi A; Al Amri IS; Boukra S; Jabeen F; Hussain J; Abbas G; Naureen Z; Haq QMI; Shah HH; Khan A; Khalaf SK; Kadim I
Department: Química Analítica i Química Orgànica
URV's Author/s: Boqué Martí, Ricard
Keywords: Quality Prediction Pork meat Plsr Pls-da Pca Near-infrared reflectance Near infrared reflectance spectroscopy Identification Beef Authentication Assay Adulteration plsr pls-da pca near infrared reflectance spectroscopy
Abstract: © 2020 Elsevier Ltd This study aimed to develop a fast analytical method, combining near infrared reflectance spectroscopy and multivariate analysis, for detection and quantification of pork meat in other meat samples. A total of 5952 mixture samples from 39 types of meat were prepared in triplicate, with the inclusion of pork at 0%, 1%, 5%, 10%, 30%, 50%, 70%, 90% and 100%. Each sample was scanned using an FT-NIR spectrophotometer in the reflection mode. Spectra were collected in the wavenumber range from 10,000 to 4000 cm−1, at a resolution of 2 cm−1 and a total path length of 0.5 mm. Principal Component Analysis (PCA) revealed the similarities and differences among the various types of meat samples and Partial Least-Squares Discriminant Analysis (PLS-DA) showed a good discrimination between pure and pork-spiked meat samples. A Partial Least-Squares Regression (PLSR) model was built to predict the pork meat contents in other meats, which provided the R2 value of 0.9774 and RMSECV value of 1.08%. Additionally, an external validation was carried out using a test set, providing a rather good prediction error, with an RMSEP value of 1.84%.
Thematic Areas: Zootecnia / recursos pesqueiros Saúde coletiva Química Psicología Odontología Nutrição Medicina veterinaria Medicina ii Medicina i Interdisciplinar Food science & technology Food science Farmacia Engenharias ii Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência de alimentos Biotecnología Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 0309-1740
Author's mail: ricard.boque@urv.cat
Author identifier: 0000-0001-7311-4824
Record's date: 2023-02-22
Journal volume: 163
Papper version: info:eu-repo/semantics/acceptedVersion
Link to the original source: https://www.sciencedirect.com/science/article/abs/pii/S0309174019308708?via%3Dihub
Papper original source: Meat Science. 163 (108084): 108084-
APA: Mabood F; Boqué R; Alkindi AY; Al-Harrasi A; Al Amri IS; Boukra S; Jabeen F; Hussain J; Abbas G; Naureen Z; Haq QMI; Shah HH; Khan A; Khalaf SK; Kadim (2020). Fast detection and quantification of pork meat in other meats by reflectance FT-NIR spectroscopy and multivariate analysis. Meat Science, 163(108084), 108084-. DOI: 10.1016/j.meatsci.2020.108084
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Article's DOI: 10.1016/j.meatsci.2020.108084
Entity: Universitat Rovira i Virgili
Journal publication year: 2020
Publication Type: Journal Publications
Repositori URV