Mapping of TBARS distribution in frozen-thawed pork using NIR hyperspectral imaging

被引:62
作者
Wu, Xiang [1 ]
Song, Xinglin [1 ]
Qiu, Zhengjun [1 ]
He, Yong [1 ]
机构
[1] Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Zhejiang, Peoples R China
关键词
Hyperspectral imaging; Frozen-thawed pork; TBARS; Visualization; NEAR-INFRARED SPECTROSCOPY; LIPID OXIDATION; NONDESTRUCTIVE DETERMINATION; CHICKEN MEAT; PREDICTION; QUALITY; BEEF; CLASSIFICATION; VISUALIZATION; FRESH;
D O I
10.1016/j.meatsci.2015.11.008
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
In this study, NIR hyperspectral imaging technology was applied to determine the distribution of TBARS in frozen-thawed pork. A total of 240 fresh pork samples were assigned to 4 treatment groups (0, 1, 3, 5 frozen thawed cycles). For each sample, a hyperspectral image (874-1734 nm) was collected, followed by chemical TBARS analysis. Successive projection algorithm (SPA) was applied to choose effective wavelengths (EWs). The selected 13 EWs of the calibration set and relevant TBARS value were used as inputs of partial least squares regression (PLSR) model, yielding correlation coefficient of prediction of 0.81 and root mean square error of prediction of 033. The developed PLSR model were applied pixel-wise to produce chemical maps of TBARS for 24 selected samples in the prediction set. The results indicated that NIR hyperspectral imaging combined with image processing has the potential to visualize TBARS distribution in frozen-thawed pork. This technique could be useful in real-time quality monitoring in meat industry. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:92 / 96
页数:5
相关论文
共 27 条
  • [1] From multispectral imaging of autofluorescence to chemical and sensory images of lipid oxidation in cod caviar paste
    Airado-Rodriguez, Diego
    Hoy, Martin
    Skaret, Josefine
    Wold, Jens Petter
    [J]. TALANTA, 2014, 122 : 70 - 79
  • [2] Near-infrared hyperspectral imaging for grading and classification of pork
    Barbin, Douglas
    Elmasry, Gamal
    Sun, Da-Wen
    Allen, Paul
    [J]. MEAT SCIENCE, 2012, 90 (01) : 259 - 268
  • [3] Warmed-over flavour in porcine meat - a combined spectroscopic, sensory and chemometric study
    Brondum, J
    Byrne, DV
    Bak, LS
    Bertelsen, G
    Engelsen, SB
    [J]. MEAT SCIENCE, 2000, 54 (01) : 83 - 95
  • [4] Theory and application of near infrared reflectance spectroscopy in determination of food quality
    Cen, Haiyan
    He, Yong
    [J]. TRENDS IN FOOD SCIENCE & TECHNOLOGY, 2007, 18 (02) : 72 - 83
  • [5] Suitability of hyperspectral imaging for rapid evaluation of thiobarbituric acid (TBA) value in grass carp (Ctenopharyngodon idella) fillet
    Cheng, Jun-Hu
    Sun, Da-Wen
    Pu, Hong-Bin
    Wang, Qi-Jun
    Chen, Yu-Nan
    [J]. FOOD CHEMISTRY, 2015, 171 : 258 - 265
  • [6] Cozzolino D, 2009, CIENC INVESTIG AGRAR, V36, P209
  • [7] Spatial and temporal mass spectrometric profiling and imaging of lipid degradation in bovine M. longissimus dorsi lumborum
    Dyer, Jolon M.
    Deb-Choudhury, Santanu
    Cornellison, Charisa D.
    Krsinic, Gail
    Dobbie, Peter
    Rosenvold, Katja
    Clerens, Stefan
    [J]. JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2014, 33 (02) : 203 - 209
  • [8] Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging
    ElMasry, Gamal
    Sun, Da-Wen
    Allen, Paul
    [J]. FOOD RESEARCH INTERNATIONAL, 2011, 44 (09) : 2624 - 2633
  • [9] PIGMENT OXIDATION IN GROUND VEAL - INFLUENCE OF LIPID OXIDATION, IRON AND ZINC
    FAUSTMAN, C
    SPECHT, SM
    MALKUS, LA
    KINSMAN, DM
    [J]. MEAT SCIENCE, 1992, 31 (03) : 351 - 362
  • [10] A variable elimination method to improve the parsimony of MLR models using the successive projections algorithm
    Galvao, Roberto Kawakami Harrop
    Ugulino Araujo, Mario Cesar
    Fragoso, Wallace Duarte
    Silva, Edvan Cirino
    Jose, Gledson Emidio
    Carreiro Soares, Sofacles Figueredo
    Paiva, Henrique Mohallem
    [J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2008, 92 (01) : 83 - 91