DOI QR코드

DOI QR Code

Development of Measuring Technique for Somatic Cell Count in Raw Milk by Spectroscopy

분광분석법을 이용한 우유의 체세포수 측정기술 개발

  • Choi, C.H. (Dept. of Bio-Mechatronic Engineering SungKyunKwan University) ;
  • Kim, Y.J. (Dept. of Bio-Mechatronic Engineering SungKyunKwan University) ;
  • Kim, K.S. (Korea Food Research Institute) ;
  • Choi, T.H. (Dept. of Bio-Mechatronic Engineering SungKyunKwan University)
  • Published : 2008.06.25

Abstract

The objective of this study was to develop models to predict SCC (somatic cell count) in unhomogenized milk by visible and near-infrared (NIR) spectroscopic technique. Total of 100 milk samples were collected from dairy farms and preserved to minimize propagation of bacteria cells during transportation. Reductive reagents such as methyl red, methylene blue, bromcresol purple, phenol red and resazurin were added to milk samples, and then colors of milk were changed based on SCC of milk. For optimal reductive reagents, reaction time was controlled at 3 level of reaction time. A spectrophotometer was used to measure reflectance spectra from milk samples. The partial least square (PLS) models were developed to predict SCC of unhomogenized milk. The PLS results showed that milk samples with reductive reagents had a good correlation between predicted and measured SCC at 5 minutes of reaction time in the visible range. The PLS models with resazurin reagent had the best performance in $400{\sim}600\;nm$. The prediction results of milk samples with resazurin had 0.86 of correlation coefficient and 14,184 cell/mL of SEP.

Keywords

References

  1. Berglund, I., G. Pettersson and S. Sjaunja. 2002. Automatic milking: effects on somatic cell count and teat end-quality. Livestock Production Science 78:115-124 https://doi.org/10.1016/S0301-6226(02)00090-8
  2. Chen, J. Y., C. Iyo and S. Kawano. 1999. Development of calibration with sample cell compensation for determining the fat content of unhomogenized raw milk by a simple near infrared transmittance method. Journal of Near Infrared Spectroscopy 7:265-273 https://doi.org/10.1255/jnirs.257
  3. Laporte M. and P. Paquin. 1999. Near-infrared analysis of fat, protein, and casein in cow's milk. Journal of Agriculture Food Chemistry 47:2600-2605 https://doi.org/10.1021/jf980929r
  4. Pravdova, V., B. Walczak, D. L. Massart, S. Kawano, K. Toyoda and R. Tsenkova. 2001. Calibration of somatic cell count in milk based on near-infrared spectroscopy. Analytica Chimica Acta 450:131-141 https://doi.org/10.1016/S0003-2670(01)01373-3
  5. Tsenkova, R., S. Atanassova, K. Toyoda, Y. Ozaki, K. Itoh and T. Fearn. 1999. Near-infrared spectroscopy for dairy management: measurement of unhomogenized milk composition. Journal of Dairy Science 82:2344-2351 https://doi.org/10.3168/jds.S0022-0302(99)75484-6
  6. Tsenkova, R., S. Atanassova, Y. Ozaki, K. Toyoda and K. Itoh. 2001. Near-infrared spectroscopy for biomonitoring influence of somatic cell count on cow's milk composition analysis. International Dairy 11:779-783 https://doi.org/10.1016/S0958-6946(01)00110-8
  7. 국립수의과학검역원. 2004. 우유가 산정체계 기준 변화에 따른 체세포수 관리대책.서울
  8. 한국낙농공학연구센터. 1993. 낙농식품가공학
  9. 한국낙농육우협회. 2002. 우유의 수급안정 대책 방안
  10. 한국식품연구원. 2006. 근적외선을 이용한 우유 체세포수 검사법 개선연구

Cited by

  1. Development of Measuring Technique for Milk Composition by Using Visible-Near Infrared Spectroscopy vol.19, pp.1, 2012, https://doi.org/10.11002/kjfp.2012.19.1.095
  2. Development of real-time chemical properties analysis technique in paddy soil for precision farming vol.41, pp.1, 2014, https://doi.org/10.7744/cnujas.2014.41.1.059
  3. Development of a Milk Filtering System for Decreasing Somatic Cell Count vol.20, pp.1, 2014, https://doi.org/10.11109/JAES.2014.20.1.15
  4. The analysis of oat chemical properties using visible-near infrared spectroscopy vol.43, pp.5, 2016, https://doi.org/10.7744/kjoas.20160074
  5. Development of a Portable Quality Evaluation System for Bee-honeys by Using Near Infrared Spectroscopy vol.18, pp.2, 2011, https://doi.org/10.11002/kjfp.2011.18.2.156