000078813 001__ 78813
000078813 005__ 20201105083207.0
000078813 0247_ $$2doi$$a10.1016/j.meatsci.2018.04.006
000078813 0248_ $$2sideral$$a105772
000078813 037__ $$aART-2018-105772
000078813 041__ $$aeng
000078813 100__ $$0(orcid)0000-0001-8042-8688$$aRipoll, G.
000078813 245__ $$aUse of visible and near infrared reflectance spectra to predict lipid peroxidation of light lamb meat and discriminate dam's feeding systems
000078813 260__ $$c2018
000078813 5060_ $$aAccess copy available to the general public$$fUnrestricted
000078813 5203_ $$aMeasurement of thiobarbituric acid reactive substances (TBARS) is a well-established method for determine lipid oxidation in meat. This assay, however, is time-consuming and generates undesired chemical waste. Dam''s milk is the principal source of vitamins and provitamins that delay lipid oxidation of light lamb meat; these compounds are stored in the lamb''s muscle tissue. Hence, lamb meat could be used to determine the origin of the dam''s diet. The aim of this study is to evaluate Near-infrared reflectance spectroscopy (NIRS) as a tool for determining the lipid peroxidation of light lamb meat and differentiate the meat of light lambs according the diet of their dams during lactation (grazing alfalfa, lucerne, or fed a total mixed ration). NIRS using select wavelengths was able to detect the lipid oxidation of meat (TBARS method). NIRS can detect analytes at concentrations of parts per million. Moreover, the feed diets were discriminated successfully.
000078813 536__ $$9info:eu-repo/grantAgreement/ES/DGA/RD188-2008$$9info:eu-repo/grantAgreement/ES/MEC-FEDER/INIA-RTA2009-91-C02-01$$9info:eu-repo/grantAgreement/ES/MEC-FEDER/INIA-RTA2012-80-0$$9info:eu-repo/grantAgreement/ES/MEC-FEDER/INIA-RZP2013-1-0
000078813 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000078813 590__ $$a3.483$$b2018
000078813 591__ $$aFOOD SCIENCE & TECHNOLOGY$$b28 / 135 = 0.207$$c2018$$dQ1$$eT1
000078813 592__ $$a1.397$$b2018
000078813 593__ $$aFood Science$$c2018$$dQ1
000078813 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000078813 700__ $$0(orcid)0000-0002-7829-1448$$aLobón, S.
000078813 700__ $$0(orcid)0000-0002-1796-4223$$aJoy, M.
000078813 773__ $$g143 (2018), 24-29$$pMeat sci.$$tMeat Science$$x0309-1740
000078813 8564_ $$s472159$$uhttps://zaguan.unizar.es/record/78813/files/texto_completo.pdf$$yPostprint
000078813 8564_ $$s48309$$uhttps://zaguan.unizar.es/record/78813/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000078813 909CO $$ooai:zaguan.unizar.es:78813$$particulos$$pdriver
000078813 951__ $$a2020-11-05-08:19:07
000078813 980__ $$aARTICLE