Performances of full cross-validation partial least squares regression models developed using Raman spectral data for the prediction of bull beef sensory attributes
dc.contributor.author | Zhao, Ming | |
dc.contributor.author | Nian, Yingqun | |
dc.contributor.author | Allen, Paul | |
dc.contributor.author | Downey, Gerard | |
dc.contributor.author | Kerry, Joseph P. | |
dc.contributor.author | O’Donnell, Colm P. | |
dc.date.accessioned | 2020-08-04T11:40:24Z | |
dc.date.available | 2020-08-04T11:40:24Z | |
dc.date.issued | 2018-04-23 | |
dc.identifier.citation | Zhao M, Nian Y, Allen P, Downey G, Kerry JP, O’Donnell CP. Performances of full cross-validation partial least squares regression models developed using Raman spectral data for the prediction of bull beef sensory attributes. Data in Brief 2018;19:1355-1360; doi https://doi.org/10.1016/j.dib.2018.04.056 | en_US |
dc.identifier.issn | 2352-3409 | |
dc.identifier.uri | http://hdl.handle.net/11019/2229 | |
dc.description | peer-reviewed | en_US |
dc.description.abstract | The data presented in this article are related to the research article entitled “Application of Raman spectroscopy and chemometric techniques to assess sensory characteristics of young dairy bull beef” [1]. Partial least squares regression (PLSR) models were developed on Raman spectral data pre-treated using Savitzky Golay (S.G.) derivation (with 2nd or 5th order polynomial baseline correction) and results of sensory analysis on bull beef samples (n = 72). Models developed using selected Raman shift ranges (i.e. 250–3380 cm−1, 900–1800 cm−1 and 1300–2800 cm−1) were explored. The best model performance for each sensory attributes prediction was obtained using models developed on Raman spectral data of 1300–2800 cm−1. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier BV | en_US |
dc.relation.ispartofseries | Data in Brief; | |
dc.subject | Selected Raman shift ranges | en_US |
dc.subject | Sensory attributes | en_US |
dc.subject | Bull beef | en_US |
dc.subject | Partial least squares regression models | en_US |
dc.title | Performances of full cross-validation partial least squares regression models developed using Raman spectral data for the prediction of bull beef sensory attributes | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.dib.2018.04.056 | |
dc.contributor.sponsor | Teagasc Walsh Fellowship Programme | en_US |
dc.source.volume | 19 | |
dc.source.beginpage | 1355-1360 | |
refterms.dateFOA | 2019-02-05T00:00:00Z |