Near-infrared data for the prediction of beef marbling

DOI

A total of 832 animals from 2 slaughterhouses in France and Italy were involved. Marbling was assessed according to the 3G (Global Grading Guaranteed) protocol from 100 to 1190 in increments of 10 indicating the amount, the size, the fineness, and the distribution of visible fat inclusions in muscles. Spectra were recorded using the SCiO™ molecular sensor (Consumer Physics Inc., Tel Aviv, Israel), a handheld web-based wireless spectrometer that operates in reflectance mode in the NIR region between 740 and 1070 nm of wavelength at intervals of 1 nm which is the default mode of the spectrometer. The instrument was calibrated every day before starting the spectra collection, then five scans per sample were taken in 5 different positions on the surface of Longissimus thoracis muscle by applying an adapter to the scanning head in order to maintain a fixed distance from the sample of 1 cm over the surface and avoid any external light source. Each final spectrum to be used for the development of prediction models of marbling was then calculated as the average of the 5 scans.

Identifier
DOI https://doi.org/10.57745/FRDOJC
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.57745/FRDOJC
Provenance
Creator Hocquette, Jean-François; Kombolo Ngah Moise; Goi Arianna; Santinello Matteo; Rampado Nicola; Liu Jingjing; Faure Pascal; Thoumy Laure; Neveu Alix; De Marchi Massimo
Publisher Recherche Data Gouv
Contributor Hocquette, Jean-François; INRAE; University of Padova; Entrepôt-Catalogue Recherche Data Gouv
Publication Year 2023
Rights etalab 2.0; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/etalab-2.0.html
OpenAccess true
Contact Hocquette, Jean-François (INRAE)
Representation
Resource Type Dataset
Format text/tab-separated-values
Size 3286725
Version 1.1
Discipline Agriculture, Forestry, Horticulture; Agricultural Sciences; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences