Low-cost visible-near infrared sensor for on-line monitoring of fat and fatty acids content during the manufacturing process of the milk - PubMed

Low-cost visible-near infrared sensor for on-line monitoring of fat and fatty acids content during the manufacturing process of the milk

Alberto Villar et al. Food Chem. 2012.

Abstract

This paper describes the calibration, validation and testing process of a low-cost on-line visible-near infrared (400-1100 nm) sensor for the monitoring of fat and fatty acids content in milk during the manufacturing process of milk. The optical, mechanical and electronic designs of the sensor have been developed in Tekniker IK4 research centre just as its manufacturing process. The measurement range of the sensor is 400-1100 nm thus it covers the visible range (400-780 nm) and the short-wave near infrared (780-1100 nm). Chemometric techniques were applied with the purpose of obtaining a predictive model for each parameter correlating the spectra obtained by the sensor with the parameters analysed in the laboratory. The models were developed by Partial Least Squares Regression (PLS) obtaining one model for each parameter. The raw milk samples used in this work were provided by CAPSA (Asturias, Spain).

Similar articles

• [Determination of fat, protein and DM in raw milk by portable short-wave near infrared spectrometer].

  Li XY, Wang JH, Huang YW, Han DH. Li XY, et al. Guang Pu Xue Yu Guang Pu Fen Xi. 2011 Mar;31(3):665-8. Guang Pu Xue Yu Guang Pu Fen Xi. 2011. PMID: 21595214 Chinese.

• At-line near-infrared spectroscopy for prediction of the solid fat content of milk fat from New Zealand butter.

  Meagher LP, Holroyd SE, Illingworth D, van de Ven F, Lane S. Meagher LP, et al. J Agric Food Chem. 2007 Apr 18;55(8):2791-6. doi: 10.1021/jf063215m. Epub 2007 Mar 23. J Agric Food Chem. 2007. PMID: 17378579

• Invited review: technical solutions for analysis of milk constituents and abnormal milk.

  Brandt M, Haeussermann A, Hartung E. Brandt M, et al. J Dairy Sci. 2010 Feb;93(2):427-36. doi: 10.3168/jds.2009-2565. J Dairy Sci. 2010. PMID: 20105515 Review.

• Major advances in nutrition: impact on milk composition.

  Jenkins TC, McGuire MA. Jenkins TC, et al. J Dairy Sci. 2006 Apr;89(4):1302-10. doi: 10.3168/jds.S0022-0302(06)72198-1. J Dairy Sci. 2006. PMID: 16537962 Review.

Cited by

• Application of FTIR Method for the Assessment of Immobilization of Active Substances in the Matrix of Biomedical Materials.

  Kowalczuk D, Pitucha M. Kowalczuk D, et al. Materials (Basel). 2019 Sep 13;12(18):2972. doi: 10.3390/ma12182972. Materials (Basel). 2019. PMID: 31540255 Free PMC article.

• Low Cost Photonic Sensor for in-Line Oil Quality Monitoring: Methodological Development Process towards Uncertainty Mitigation.

  Lopez P, Mabe J, Miró G, Etxeberria L. Lopez P, et al. Sensors (Basel). 2018 Jun 22;18(7):2015. doi: 10.3390/s18072015. Sensors (Basel). 2018. PMID: 29932444 Free PMC article.

• Real-Time Monitoring of Yogurt Fermentation Process by Aquaphotomics Near-Infrared Spectroscopy.

  Muncan J, Tei K, Tsenkova R. Muncan J, et al. Sensors (Basel). 2020 Dec 29;21(1):177. doi: 10.3390/s21010177. Sensors (Basel). 2020. PMID: 33383861 Free PMC article.

Publication types

MeSH terms

Substances