Prediction of the chemical composition of freeze dried ostrich meat with near infrared reflectance spectroscopy

被引:34
|
作者
Viljoen, M
Hoffman, LC
Brand, TS
机构
[1] Elsenburg Agr Res Ctr, Dept Anim Sci, ZA-7607 Elsenburg, South Africa
[2] Univ Stellenbosch, Dept Anim Sci, ZA-7602 Matieland, South Africa
[3] Univ Pretoria, Dept Anat & Physiol, ZA-0110 Onderstepoort, South Africa
关键词
chemical composition; near infrared reflectance spectroscopy; ostrich meat;
D O I
10.1016/j.meatsci.2004.07.008
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Near infrared reflectance spectroscopy (NIRS) was used to predict the chemical composition of freeze-dried ostrich meat samples. Tenderloin (M. ambiens), big drum (M. iliofibularis) and fan fillet (M. gastrocnemius) samples (n = 160) were included in the study. Samples were minced, freeze-dried and analysed according to standard laboratory procedures for ash, dry matter (DM), crude protein (CP) and fat content. Samples were scanned (1100-2500 nm) and partial least-square regression (PLSR) was used to predict the chemical composition. Multiple correlation coefficients (r) and standard errors of calibration (SEC) for the chemical analysis of freeze-dried ostrich meat were: ash (0.72; 0.29%); DM (0.72; 1.01%); CP (0.98; 0.55%); and fat (0.99; 0.29%). The r values for the validation set and the standard error of performance (SEP) for the different constituents were: ash (0.71; 0.23%); DM (0.84; 0.72%); CP (0.97; 0.64%); and fat (0.99; 0.18%). Calibrations were accurate for CP and fat. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:255 / 261
页数:7
相关论文
共 50 条
  • [1] Prediction of amino acids in freeze dried pork by near infrared reflectance spectroscopy
    Huang, Wei
    Tao, Lin-Li
    Zhang, Xi
    Yang, Xiu-Juan
    Cao, Zhi-Yong
    Hao, Xin-Wei
    INDIAN JOURNAL OF ANIMAL SCIENCES, 2018, 88 (09): : 1078 - 1084
  • [2] Prediction of the chemical composition of mutton with near infrared reflectance spectroscopy
    Viljoen, M.
    Hoffman, L. C.
    Brand, T. S.
    SMALL RUMINANT RESEARCH, 2007, 69 (1-3) : 88 - 94
  • [3] Prediction of fatty acid composition of fresh and freeze-dried cheeses by visible-near-infrared reflectance spectroscopy
    Lucas, Anthony
    Andueza, Donato
    Ferlay, Anne
    Martin, Bruno
    INTERNATIONAL DAIRY JOURNAL, 2008, 18 (06) : 595 - 604
  • [4] Research on Prediction Chemical Composition of Beef by Near Infrared Reflectance Spectroscopy
    Sun Xiao-ming
    Lu Ling
    Zhang Jia-cheng
    Zhang Song-shan
    Sun Bao-zhong
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31 (02) : 379 - 383
  • [5] Near-infrared reflectance spectroscopy for the prediction of chemical composition in walnut kernel
    Yi, Jianhua
    Sun, Yifei
    Zhu, Zhenbao
    Liu, Ning
    Lu, Jiali
    INTERNATIONAL JOURNAL OF FOOD PROPERTIES, 2017, 20 (07) : 1633 - 1642
  • [6] Prediction of chemical composition of sugar beet pulp by near infrared reflectance spectroscopy
    Fernandez, B.
    Andres, S.
    Prieto, N.
    Mantecon, A. R.
    Giraldez, F. J.
    JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2008, 16 (02) : 105 - 110
  • [7] Prediction of the chemical composition of white clover by near-infrared reflectance spectroscopy
    Berardo, N
    GRASS AND FORAGE SCIENCE, 1997, 52 (01) : 27 - 32
  • [8] Prediction of chemical composition of Cynodon spp. by near infrared reflectance spectroscopy
    Fonteneli, RS
    Scheffer-Basso, SM
    Dürr, JW
    Appelt, JV
    Bortolini, F
    Haubert, FA
    REVISTA BRASILEIRA DE ZOOTECNIA-BRAZILIAN JOURNAL OF ANIMAL SCIENCE, 2004, 33 (04): : 838 - 842
  • [9] The assessment of the chemical composition of fishmeal by near infrared reflectance spectroscopy
    Cozzolino, D
    Chree, A
    Murray, I
    Scaife, JR
    AQUACULTURE NUTRITION, 2002, 8 (02) : 149 - 155
  • [10] Prediction of lamb meat fatty acid composition using near-infrared reflectance spectroscopy (NIRS)
    Guy, F.
    Prache, S.
    Thomas, A.
    Bauchart, D.
    Andueza, D.
    FOOD CHEMISTRY, 2011, 127 (03) : 1280 - 1286