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פותח על ידי קלירמאש פתרונות בע"מ -
Yeast detection in apple juice using Raman spectroscopy and chemometric methods
Year:
2007
Source of publication :
Transactions of the ASABE
Authors :
מזרח, עמוס
;
.
שמילוביץ', זאב
;
.
Volume :
50
Co-Authors:
Mizrach, A., Institute of Agricultural Engineering, Bet Dagan, Israel, Institute of Agricultural Engineering, P.O. Box 6, Bet Dagan, 50250, Israel
Schmilovitch, Z., Institute of Agricultural Engineering, Bet Dagan, Israel
Korotic, R., Institute of Agricultural Engineering, Bet Dagan, Israel
Irudayaraj, J., Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, United States
Shapira, R., Faculty of Agriculture, Hebrew University of Jerusalem, Israel
Facilitators :
From page:
2143
To page:
2149
(
Total pages:
7
)
Abstract:
Yeast (Saccharomyces cerevisiae spp.) causes unwanted fermentation in apple juice production. Current methods for detecting yeast in the fermentation process are labor intensive and time consuming; therefore, a rapid, reliable method will help ensure consumers a safe and high-quality product. Raman spectroscopy, an advanced optical technique based on light scattering, was investigated as a rapid on-site detection method for yeasts contained in an apple juice droplet. In this study, a dispersive spectrophotometer with a 785 nm diode laser was employed. Chemometric methods such as single linear regression (SLR), partial least squares regression (PLS), principle components regression (PCR), and classification analysis were used to evaluate low-concentration solutions of yeasts in apple juice drops smeared on glass plates. Apple juice samples containing yeast in various concentrations, along with pure samples, were analyzed to predict yeast detection thresholds. Yeast was detected in 85% to 100% of the contaminated samples. The best detection (100%) was achieved at the predicted concentration of 10 CFU mL -1. The results suggest that Raman spectroscopy could be used in apple juice industries as a quality-control tool for rapid, accurate, on-line detection of yeast where a zero tolerance to yeast at 10 CFU mL -1 of pasteurized final product is required. © 2007 American Society of Agricultural and Biological Engineers.
Note:
Related Files :
Apple juice
food quality
food safety
fungi
Linear regression
Yeast
עוד תגיות
תוכן קשור
More details
DOI :
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
26753
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:25
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Scientific Publication
Yeast detection in apple juice using Raman spectroscopy and chemometric methods
50
Mizrach, A., Institute of Agricultural Engineering, Bet Dagan, Israel, Institute of Agricultural Engineering, P.O. Box 6, Bet Dagan, 50250, Israel
Schmilovitch, Z., Institute of Agricultural Engineering, Bet Dagan, Israel
Korotic, R., Institute of Agricultural Engineering, Bet Dagan, Israel
Irudayaraj, J., Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, United States
Shapira, R., Faculty of Agriculture, Hebrew University of Jerusalem, Israel
Yeast detection in apple juice using Raman spectroscopy and chemometric methods
Yeast (Saccharomyces cerevisiae spp.) causes unwanted fermentation in apple juice production. Current methods for detecting yeast in the fermentation process are labor intensive and time consuming; therefore, a rapid, reliable method will help ensure consumers a safe and high-quality product. Raman spectroscopy, an advanced optical technique based on light scattering, was investigated as a rapid on-site detection method for yeasts contained in an apple juice droplet. In this study, a dispersive spectrophotometer with a 785 nm diode laser was employed. Chemometric methods such as single linear regression (SLR), partial least squares regression (PLS), principle components regression (PCR), and classification analysis were used to evaluate low-concentration solutions of yeasts in apple juice drops smeared on glass plates. Apple juice samples containing yeast in various concentrations, along with pure samples, were analyzed to predict yeast detection thresholds. Yeast was detected in 85% to 100% of the contaminated samples. The best detection (100%) was achieved at the predicted concentration of 10 CFU mL -1. The results suggest that Raman spectroscopy could be used in apple juice industries as a quality-control tool for rapid, accurate, on-line detection of yeast where a zero tolerance to yeast at 10 CFU mL -1 of pasteurized final product is required. © 2007 American Society of Agricultural and Biological Engineers.
Scientific Publication
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