Prediction of the intramuscular connective tissue components of fresh and freeze-dried samples by near infrared spectroscopy

被引:6
作者
Andueza, D. [1 ]
Picard, F. [1 ]
Hocquette, J. F. [1 ]
Listrat, A. [1 ]
机构
[1] Univ Clermont Auvergne, UMR Herbivores, VetAgro Sup, INRAE, F-63122 St Genes Champanelle, France
关键词
Hydroxyproline; Collagen; Proteoglycans; Cross-links; NIR; Beef; REFLECTANCE SPECTROSCOPY; CHEMICAL-COMPOSITION; MEAT; COLLAGEN; QUALITY; HYDROXYPROLINE; PRODUCTS; WATER; NIRS; RAW;
D O I
10.1016/j.meatsci.2021.108537
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
This study compared the performance of near-infrared spectroscopy (NIRS) models on fresh and freeze-dried beef muscle samples to predict intramuscular connective tissue (IMCT) components and to determine whether the accuracy of the models differed among different muscles from beef cattle. The hypothesis was that the water content of muscle samples would negatively influence the accuracy of the models, which would differ among muscles. Fresh and freeze-dried samples (n = 171) of four muscles were used to develop NIRS models to predict the contents IMCT. For the total collagen content, the standard error of cross validation (SECV) for model using freeze-dried samples (0.75 mg OH-prol/g DM) was lower than that for model using fresh samples (0.84 mg OHprol/g DM). For cross-links and proteoglycans, the SECV for models using fresh sample spectra was lower than that for models using freeze-dried sample spectra. The accuracy of the prediction of the models also differed among predicted muscle types.
引用
收藏
页数:8
相关论文
共 42 条
[1]   Load-unloading response of intact and artificially degraded articular cartilage correlated with near infrared (NIR) absorption spectra [J].
Afara, I. O. ;
Singh, S. ;
Oloyede, A. .
JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS, 2013, 20 :249-258
[2]   Visible and Near-Infrared Multispectral Features in Conjunction with Artificial Neural Network and Partial Least Squares for Predicting Biochemical and Micro-Structural Features of Beef Muscles [J].
Ait-Kaddour, Abderrahmane ;
Andueza, Donato ;
Dubost, Annabelle ;
Roger, Jean-Michel ;
Hocquette, Jean-Francois ;
Listrat, Anne .
FOODS, 2020, 9 (09)
[3]   Chemical and discriminant analysis of bovine meat by near infrared reflectance spectroscopy (NIRS) [J].
Alomar, D ;
Gallo, C ;
Castañeda, M ;
Fuchslocher, R .
MEAT SCIENCE, 2003, 63 (04) :441-450
[4]   Prediction of beef meat fatty acid composition by visible-near-infrared spectroscopy was improved by preliminary freeze-drying [J].
Andueza, D. ;
Listrat, A. ;
Durand, D. ;
Normand, J. ;
Mourot, B. P. ;
Gruffat, D. .
MEAT SCIENCE, 2019, 158
[5]   NIRS prediction of the feed value of temperate forages: efficacy of four calibration strategies [J].
Andueza, D. ;
Picard, F. ;
Jestin, M. ;
Andrieu, J. ;
Baumont, R. .
ANIMAL, 2011, 5 (07) :1002-1013
[6]   Fecal Near-Infrared Reflectance Spectroscopy Prediction of the Feed Value of Temperate Forages for Ruminants and Some Parameters of the Chemical Composition of Feces: Efficiency of Four Calibration Strategies [J].
Andueza, Donato ;
Picard, Fabienne ;
Dozias, Dominique ;
Aufrere, Jocelyne .
APPLIED SPECTROSCOPY, 2017, 71 (09) :2164-2176
[7]  
[Anonymous], 1995, Statistical methods
[8]   STANDARD NORMAL VARIATE TRANSFORMATION AND DE-TRENDING OF NEAR-INFRARED DIFFUSE REFLECTANCE SPECTRA [J].
BARNES, RJ ;
DHANOA, MS ;
LISTER, SJ .
APPLIED SPECTROSCOPY, 1989, 43 (05) :772-777
[9]   Measurement of water-holding capacity in raw and freeze-dried broiler breast meat with visible and near-infrared spectroscopy [J].
Bowker, B. ;
Hawkins, S. ;
Zhuang, H. .
POULTRY SCIENCE, 2014, 93 (07) :1834-1841
[10]   Analysis of water in food by near infrared spectroscopy [J].
Büning-Pfaue, H .
FOOD CHEMISTRY, 2003, 82 (01) :107-115