Near infrared spectra of cows' milk for milk quality evaluation: disease diagnosis and pathogen identification

被引:33
作者
Tsenkova, Roumiana [1 ]
Atanassova, Stefka
Morita, Hiroyuki
Ikuta, Kentaro
Toyoda, Kiyohiko
Iordanova, Illina K.
Hakogi, Etsuji
机构
[1] Kobe Univ, Dept Environm Informat & Bioprod Engn, Kobe, Hyogo 657, Japan
[2] Thracia Univ, Dept Math & Phys, Stara Zagora, Bulgaria
[3] Univ Cambridge, Dept Anat, Cambridge CB2 3DY, England
关键词
NIR; in vivo diagnosis; mastitis; bacteria; cell count; electrical conductivity;
D O I
10.1255/jnirs.661
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Food quality and safety, as well as bacteria identification, have become very important issues. Establishing fast and non-destructive methods for control is of a great importance. The performance and safety of processed milk and milk products are influenced by the quality of the raw milk used and animal health. Cell count in udder quarter milk has been established as the main criteria by which milk abnormality is evaluated and, in addition to electrical conductivity and pathogen identification, it is also a principle means for the diagnosis of the inflammatory udder disease known as mastitis. Near infrared (NIR) spectroscopy has proved to be a fast non-destructive method for the analysis of food and agricultural products, including non-homogenised milk. In this study, we have analysed NIR spectra of udder quarter milk samples collected continuously from individual cows, at various farms, at different times of the year. We report that NIR spectra of cows' udder quarter milk, when subjected to multivariate data analysis, provides information about milk abnormality and health disorders in cows. We have developed spectroscopic models for the simultaneous measurement of somatic cell count and electrical conductivity, as well as for identification of the main mastitis-causing bacterial pathogens in cow's udder quarter milk. These findings present NIR spectroscopy as a powerful technology for in vivo health monitoring, disease diagnosis at molecular level and bacteria identification.
引用
收藏
页码:363 / 370
页数:8
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