Measurement of pork freshness by steady spatially-resolved spectroscopy

被引：0
|
作者：
Wen X. [1 ]
Liang Z. [2 ]
Zhang G. [1 ]
Huang L. [1 ]
Wang Z. [1 ]
机构：
[1] College of Information and Electrical Engineering, China Agricultural University
[2] College of Food Science and Nutritional Engineering, China Agricultural University
来源：
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2010年 / 26卷 / 09期
关键词：
Meat freshness; Meats; Nondestructive exzamination; Spectrum analysis; Steady spatially-resolved spectroscopy; Total volatile basic nitrogen (TVB-N);
D O I：
10.3969/j.issn.1002-6819.2010.09.055
中图分类号：
学科分类号：
摘要：
The objective of this work was to investigate the relationship between optical parameter of pork meat and meat freshness, and establish a fast non-invasive method to evaluate freshness. Based on principles of bio-photonics and steady spatially-resolved short wavelength near infrared spectroscopy, a multiple channel visible and near infrared spectrometer for determination of optical parameter was established, which could measure (or obtain) spectrum of effective attenuation coefficient during changes in pork meat freshness. In this work, the relationships between effective attenuation coefficient and traditional indexes, i.e. total volatile basic nitrogen (TVB-N) as an indicator of freshness, total plate count of bacteria and sensory indicators, were also investigated. The results showed that the variations in tissue structure influenced on scattering due to spoilage resulting in cells membrane damage and rupture; and effective attenuation coefficient of sample was significantly correlated to TVB-N value at 940 nm and 960 nm. The conclusion showed that the relationship between near infrared spectrometer and TVB-N value can be found to evaluate meat freshness.
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页码：334 / 339
页数：5
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共 18 条
  • [1] (2003)
  • [2] Vestergaard J.S., Martens M., Turkki P., Application of an electronic nose system for prediction of sensory quality changes of a meat product (pizza topping) during storage, LWT-Food Science and Technology, 40, pp. 1095-1101, (2007)
  • [3] Han J., Huang L., Gu Z., Et al., Evaluation of fish quality and freshness based on the electronic tongue, Transactions of the CSAE, 24, 12, pp. 141-144, (2008)
  • [4] Panigrahi S., Balasubramanian S., Gu H., Et al., Neural-network-integrated electronic nose system for identification of spoiled beef, LWT-Food Science and Technology, 39, 2, pp. 135-145, (2006)
  • [5] Prieto N., Roehe R., Lavin P., Et al., Application of neat infrared reflectance spectroscopy to predict meat and meat products quality: A review, Meat Science, 83, 2, pp. 175-186, (2009)
  • [6] Liu K., Cheng F., Ying Y., Research progress in pork quality determination, Transactions of the CSAE, 24, SUPPL.1, pp. 239-242, (2008)
  • [7] Yu H., Ying Y., Liu Y., Research progress of factors affecting the determination of the inner quality of agricultural products by near infrared reflectance spectroscopy, Transactions of the CSAE, 21, 11, pp. 160-163, (2005)
  • [8] Hou R., Huang L., Wang Z., Et al., The preliminary study for testing freshness of meat by using near-infrared reflectance spectroscopy, Spectroscopy and Spectral Analysis, 26, 12, pp. 2193-2196, (2006)
  • [9] Wang Z., Hou R., Huang L., Et al., Light transport in multi-layered farm products by using Monte Carlo simulation and experimental investigation, Transactions of the CSAE, 23, 5, pp. 1-5, (2007)
  • [10] Xu Z., Investigation of measurement methods for determining the optical properties in agricultural products' tissue, (2006)
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