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Non-invasive lactate- and pH-monitoring in porcine meat using Raman spectroscopy and chemometrics

Title data

Nache, Marius ; Scheier, Rico ; Schmidt, Heinar ; Hitzmann, Bernd:
Non-invasive lactate- and pH-monitoring in porcine meat using Raman spectroscopy and chemometrics.
In: Chemometrics and Intelligent Laboratory Systems. Vol. 142 (2015) . - pp. 197-205.
ISSN 1873-3239
DOI: https://doi.org/10.1016/j.chemolab.2015.02.002

Project information

Project title:
Project's official title
Project's id
Grundlagenuntersuchungen zur Raman-Sensorik von Lactat für eine automatisierbare Beurteilung der Fleischqualität in der Prozesskette
Schm2724/1-1

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

The feasibility of using chemometrics and Raman spectroscopy as a fast and non-invasive method to monitor the early postmortem lactate accumulation and pH decline in pork meat has been investigated. For this application, an on-line monitoring methodology has not yet been established. Based on raw Raman spectra of porcine semimembranosus muscles, a range of spectral pre-processing and multivariate calibration techniques were investigated to develop and test on-line prediction models for the meat quality parameters. The influence of the pre-processing methods on the prediction speed, robustness and accuracy performance of the employed linear and non-linear algorithms was compared. Identification of the most effective chemometric evaluation procedure was performed using least square linear regression together with locally weighted regression and metaheuristic data optimization methods such as the genetic algorithm and the ant colony optimization. The herein presented analysis suggests that the locally weighted regression applied to the standard normal variate (SNV) normalized Raman spectra provides the most accurate and robust models with a cross-validated coefficient of determination (r²cv) of 0.97 for pH and lactate, a cross-validated root mean square error (RMSECV) of 4.5 mmol/kg for the lactate prediction and 0.06 pH-units for the pH prediction. These results demonstrate the great potential of combining chemometrics and Raman spectroscopy for on-line meat quality control applications.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Chemometrics; Raman spectroscopy; Data pre-processing; pH-monitoring; Lactate-monitoring; Meat quality
Institutions of the University: Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Life Sciences: Food, Nutrition and Health > Chair Bioanalytical Sciences and Food Analytics
Profile Fields
Profile Fields > Emerging Fields
Profile Fields > Emerging Fields > Food and Health Sciences
Research Institutions
Research Institutions > Research Units
Research Institutions > Research Units > Forschungsstelle für Nahrungsmittelqualität - ForN
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology
Faculties > Faculty of Life Sciences: Food, Nutrition and Health
Result of work at the UBT: Yes
DDC Subjects: 500 Science
500 Science > 570 Life sciences, biology
Date Deposited: 01 Apr 2015 09:11
Last Modified: 07 Sep 2023 13:48
URI: https://eref.uni-bayreuth.de/id/eprint/9692