Abstract
This thesis deals with process analytical technology and how it can be implemented in the meat industry through on-line grading of chemical meat quality. The focus will be on two applications, namely the rapid quality control of fat quality and the development of a method for on-line detection of boar taint.
The chemical makeup of fat has a large effect on meat cut quality. Fat quality has traditionally been determined by methylation of a tissue sample followed by chromatography on a GC-MS system, elucidating the composition of the individual fatty acids. As this procedure typically takes far more time than is available on a slaughter line, it is obviously not very applicable for on-line use when thousands of carcasses need to be classified in full production speed. This thesis presents the research into several spectroscopic methods (IR, NIR, Raman), each promising candidates for rapid analysis. An on-line NIR instrument is presented, capable of performing in high production speed (1200 measurements per hour). The system is calibrated against a GC-MS standard, yielding an error comparable to the accuracy of the reference.
Boar taint detection has become a hot topic, as an EU ban on surgical castration will be in effect starting 2018. With the ban, the risk of meat products with the malodorous taint reaching the consumer is highly increased, and thus, detection of boar taint is a necessity. No current on-line detection system is available; the only alternative is chemical extraction of the compounds and subsequent quantification by GC-MS or LC-MS analysis. On-line detection with sub-ppm sensitivity is a major challenge and thus spectroscopic candidates with the required capabilities in speed and sensitivity are researched. Thus, a Surface Enhanced Raman Scatter method is presented capable of nano-molar quantification in few seconds, in addition to an accelerated extraction-free GC-MS method that through automation can deliver results much faster than other similar methods.
The implementation of these high tech methods will provide the meat industry with a leading edge not only with product quality, but also with environmental issues such as energy and water use and animal welfare. Future research into the technologies will ultimately allow broad on-line screening of biomarkers, leading to on-line metabolomics
The chemical makeup of fat has a large effect on meat cut quality. Fat quality has traditionally been determined by methylation of a tissue sample followed by chromatography on a GC-MS system, elucidating the composition of the individual fatty acids. As this procedure typically takes far more time than is available on a slaughter line, it is obviously not very applicable for on-line use when thousands of carcasses need to be classified in full production speed. This thesis presents the research into several spectroscopic methods (IR, NIR, Raman), each promising candidates for rapid analysis. An on-line NIR instrument is presented, capable of performing in high production speed (1200 measurements per hour). The system is calibrated against a GC-MS standard, yielding an error comparable to the accuracy of the reference.
Boar taint detection has become a hot topic, as an EU ban on surgical castration will be in effect starting 2018. With the ban, the risk of meat products with the malodorous taint reaching the consumer is highly increased, and thus, detection of boar taint is a necessity. No current on-line detection system is available; the only alternative is chemical extraction of the compounds and subsequent quantification by GC-MS or LC-MS analysis. On-line detection with sub-ppm sensitivity is a major challenge and thus spectroscopic candidates with the required capabilities in speed and sensitivity are researched. Thus, a Surface Enhanced Raman Scatter method is presented capable of nano-molar quantification in few seconds, in addition to an accelerated extraction-free GC-MS method that through automation can deliver results much faster than other similar methods.
The implementation of these high tech methods will provide the meat industry with a leading edge not only with product quality, but also with environmental issues such as energy and water use and animal welfare. Future research into the technologies will ultimately allow broad on-line screening of biomarkers, leading to on-line metabolomics
| Original language | English |
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| Publisher | Department of Food Science, Faculty of Science, University of Copenhagen |
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| Number of pages | 253 |
| Publication status | Published - 2015 |