Dataset of the application of handheld NIR and machine learning for chicken fillet authenticity study
| Autor: | Geert H. van Kollenburg, Jeroen J. Jansen, Yannick Weesepoel, André van den Doel, Hadi Parastar, Lutgarde M. C. Buydens |
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| Rok vydání: | 2020 |
| Předmět: |
Materials science
Growth conditions lcsh:Computer applications to medicine. Medical informatics Analytical Chemistry Chicken breast Chemometrics 03 medical and health sciences 0302 clinical medicine Agricultural and Biological Science BU Authenticity & Bioassays Ensemble learning Fillet (mechanics) lcsh:Science (General) neoplasms FOIL method Chicken breast fillet 030304 developmental biology Remote sensing 0303 health sciences Handheld near-infrared Multidisciplinary technology industry and agriculture equipment and supplies Meat authenticity BU Authenticiteit & Bioassays surgical procedures operative lcsh:R858-859.7 Nir spectra 030217 neurology & neurosurgery lcsh:Q1-390 |
| Zdroj: | Data in Brief, 29 Data in Brief, Vol 29, Iss, Pp-(2020) Data in Brief 29 (2020) Data in Brief |
| ISSN: | 2352-3409 |
| DOI: | 10.1016/j.dib.2020.105357 |
| Popis: | Diffuse reflectance near-infrared (NIR) data (908–1676 nm) of chicken breast fillets was recorded in a non-destructive way using a portable miniaturised NIR spectrometer. The NIR data was used to discriminate between fresh and thawed breast fillets and to determine the birds’ growth conditions. NIR data was recorded of 153 commercial supermarket chicken fillet samples by applying the NIR device equipped with the standard issue collar on the samples in three different ways: (i) directly on the meat (ii) through the top foil of the package (i.e. with an air pocket between the foil and the breast fillet), and (iii) through the top foil with the packaging turned bottom up (i.e. no air pocket between the foil and the breast fillet). In order to generate thawed samples, the fresh samples were frozen and subsequently thawed. The freshness of the fillets was checked using β-hydroxyacyl-CoA-dehydrogenase of 13% of the sample set. Five NIR spectra were collected per measurement mode from each sample resulting in 4590 raw NIR spectra. Multivariate statistics was applied and the interpretation of these calculations can be found in Parastar et al. [1]. The NIR data has a reuse potential for follow-up studies of chicken breast fillet authentication using a similar brand NIR device or to serve as calibration transfer data. Keywords: Handheld near-infrared, Chicken breast fillet, Meat authenticity, Growth conditions, Chemometrics, Ensemble learning |
| Databáze: | OpenAIRE |
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