Document Detail

Chemometric analysis of proteolysis during ripening of Ragusano cheese.
MedLine Citation:
PMID:  15377592     Owner:  NLM     Status:  MEDLINE    
Chemometric modeling of peptide and free amino acid data was used to study proteolysis in Protected Denomination of Origin Ragusano cheese. Twelve cheeses ripened 3 to 7 mo were selected from local farmers and were analyzed in 4 layers: rind, external, middle, and internal. Proteolysis was significantly affected by cheese layer and age. Significant increases in nitrogen soluble in pH 4.6 acetate buffer and 12% trichloroacetic acid were found from rind to core and throughout ripening. Patterns of proteolysis by urea-PAGE showed that rind-to-core and age-related gradients of moisture and salt contents influenced coagulant and plasmin activities, as reflected in varying rates of hydrolysis of the caseins. Analysis of significant intercorrelations among chemical parameters revealed that moisture, more than salt content, had the largest single influence on rates of proteolysis. Lower levels of 70% ethanol-insoluble peptides coupled to higher levels of 70% ethanol-soluble peptides were found by reversed phase-HPLC in the innermost cheese layers and as the cheeses aged. Non-significant increases of individual free amino acids were found with cheese age and layer. Total free amino acids ranged from 14.3 mg/g (6.2% of total protein) at 3 mo to 22.0 mg/g (8.4% of total protein) after 7 mo. Glutamic acid had the largest concentration in all samples at each time and, jointly with lysine and leucine, accounted for 48% of total free amino acids. Principal components analysis and hierarchical cluster analysis of the data from reversed phase-HPLC chromatograms and free amino acids analysis showed that the peptide profiles were more useful in differentiating Ragusano cheese by age and farm origin than the amino acid data. Combining free amino acid and peptide data resulted in the best partial least squares regression model (R(2) = 0.976; Q(2) = 0.952) predicting cheese age, even though the peptide data alone led to a similarly precise prediction (R(2) = 0.961; Q(2) = 0.923). The most important predictors of age were soluble and insoluble peptides with medium hydrophobicity. The combined peptide data set also resulted in a 100% correct classification by partial least squares discriminant analysis of cheeses according to age and farm origin. Hydrophobic peptides were again discriminatory for distinguishing among sample classes in both cases.
V Fallico; P L H McSweeney; K J Siebert; J Horne; S Carpino; G Licitra
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of dairy science     Volume:  87     ISSN:  0022-0302     ISO Abbreviation:  J. Dairy Sci.     Publication Date:  2004 Oct 
Date Detail:
Created Date:  2004-09-20     Completed Date:  2005-01-25     Revised Date:  2009-11-19    
Medline Journal Info:
Nlm Unique ID:  2985126R     Medline TA:  J Dairy Sci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  3138-52     Citation Subset:  IM    
CoRFiLaC, Regione Siciliana, 97100 Ragusa, Italy.
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MeSH Terms
Amino Acids / analysis
Caseins / metabolism
Cheese / analysis*
Chromatography, High Pressure Liquid
Electrophoresis, Polyacrylamide Gel
Fibrinolysin / metabolism
Food Handling
Hydrogen-Ion Concentration
Milk Proteins / metabolism*
Peptides / analysis
Time Factors
Reg. No./Substance:
0/Amino Acids; 0/Caseins; 0/Milk Proteins; 0/Peptides; 57-13-6/Urea; EC

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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