Literature DB >> 22405914

Prediction of pork quality with near infrared spectroscopy (NIRS) 2. Feasibility and robustness of NIRS measurements under production plant conditions.

C Kapper1, R E Klont, J M A J Verdonk, P C Williams, H A P Urlings.   

Abstract

Longissimus dorsi samples (685) collected at four processing plants were used to develop prediction equations for meat quality with near infrared spectroscopy. Equations with R(2)>0.70 and residual prediction deviation (RPD)≥2.0 were considered as applicable for screening. One production plant showed R(2) 0.76 and RPD 2.05, other plants showed R(2)<0.70 and RPD<2.0 for drip loss %. RPD values were ≤2.05 for drip loss%, for colour L*≤1.82 and pH ultimate (pHu)≤1.57. Samples were grouped for drip loss%; superior (<2.0%), moderate (2-4%), inferior (>4.0%). 64% from the superior group and 56% from the inferior group were predicted correctly. One equation could be used for screening drip loss %. Best prediction equation for L* did not meet the requirements (R(2) 0.70 and RPD 1.82). pHu equation could not be used. Results suggest that prediction equations can be used for screening drip loss %.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22405914     DOI: 10.1016/j.meatsci.2012.02.006

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  2 in total

1.  Determination of Pork Meat Storage Time Using Near-Infrared Spectroscopy Combined with Fuzzy Clustering Algorithms.

Authors:  Qiulin Li; Xiaohong Wu; Jun Zheng; Bin Wu; Hao Jian; Changzhi Sun; Yibiao Tang
Journal:  Foods       Date:  2022-07-14

2.  Selecting the quality of mule duck fatty liver based on near-infrared spectroscopy.

Authors:  Christel Marie-Etancelin; Zulma G Vitezica; Laurent Bonnal; Xavier Fernandez; Denis Bastianelli
Journal:  Genet Sel Evol       Date:  2014-06-10       Impact factor: 4.297

  2 in total

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