These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Prediction of coagulating and noncoagulating milk samples using mid-infrared spectroscopy.
    Author: De Marchi M, Toffanin V, Cassandro M, Penasa M.
    Journal: J Dairy Sci; 2013 Jul; 96(7):4707-15. PubMed ID: 23628254.
    Abstract:
    Recently, a general deterioration of milk coagulation properties (MCP) has been observed in Italy; thus, the prediction of noncoagulating (NC) milk, defined as milk not forming a curd within 30min from rennet addition, is of immediate interest in the Italian cheese industry. The present study investigated the ability of mid-infrared (MIR) spectroscopy to predict NC milk using individual and bulk samples from Holstein cows. Samples were selected according to MIR analysis to cover the range of coagulation time between 5 and 60min. Milks were then analyzed for MCP through the reference instrument (Formagraph) over an extended testing period of 60min to identify coagulating and NC samples. Measured traits were rennet coagulation time, curd-firming time, and curd firmness 30 and 60min after rennet addition. Results showed no specific spectral information distinguishing NC from coagulating samples. The most accurate prediction model was developed for rennet coagulation time followed by curd-firming time and curd firmness 30min after rennet addition, whereas curd firmness 60min after enzyme addition could not be accurately predicted. Based on these findings, MIR spectroscopy might be proposed in payment systems to reward or penalize milk according to MCP. Moreover, the ability of MIR spectroscopy to predict the MCP of samples that form a curd beyond 30min from enzyme addition may be of interest for genetic improvement of coagulation traits in dairy breeds, because until now most studies have excluded NC information from genetic analysis, leading to possible biases in the estimation of genetic parameters and in the prediction of sire's merit for MCP.
    [Abstract] [Full Text] [Related] [New Search]