Rapid on-line Glycogen measurement and prediction of ultimate pH in slaughter beef
| aut.thirdpc.contains | No | |
| dc.contributor.advisor | Young, Owen | |
| dc.contributor.advisor | Wiklund, Eva | |
| dc.contributor.author | Lomiwes, Dominic | |
| dc.date.accessioned | 2010-07-13T04:11:05Z | |
| dc.date.available | 2010-07-13T04:11:05Z | |
| dc.date.copyright | 2008 | |
| dc.date.issued | 2008 | |
| dc.date.updated | 2010-07-13T04:10:41Z | |
| dc.description.abstract | The rapid determination of glycogen on indicator muscle immediately after slaughter is advantageous as it permits the prediction of a muscle’s ultimate pH (pHu) and allows the identification of high pHu meat carcasses by extrapolation. This thesis examines the development of two rapid glycogen determination methods. The first aim of this thesis was to find a new glucometer to replace the Bayer ESPRIT™ (Bayer) glucometer currently used in the Rapid pH (RpH) method. Roche’s Accuchek® Advantage II (Accuchek) and Abbott’s Medisense Optium™ (Medisense) glucometers were compared. Accuchek measurements exhibited a positive linear relationship in glucose standards made with water, RpH buffer and glucose spiked meat/buffer slurries ranging from 0 to 500 mg dL-1 (r2 = 0.999, 0.998 and 0.995 respectively). Medisense also exhibited a strong positive relationship for glucose standards made with water and RpH buffer; however, a non-linear trend in spiked meat slurries was observed. The second aim of this thesis was to explore the calibration of the KES K201 (KES Analysis Inc., NY, USA) near-infrared (NIR) diode array spectrometer to measure glycogen and pH at approximately 45 minutes after slaughter (pH45), and to predict pHu in pre-rigor M. longissimus dorsi (LD) from beef. This first required finding a reference method to calibrate against the NIR instrument. The RpH, Iodine and Bergmeyer methods were compared. Analysis of glycogen in replicate samples of three beef LD muscles at timepoints post-mortem (1, 4, 9 and 20 hours) was conducted. No significant difference in glycogen concentration was found between an enzymatic and an iodine based colorimetric method at each timepoint; however, the Iodine method was more consistent than the Bergmeyer method at all timepoints. Glucose measurements from the RpH method were consistent; however the pattern of glycogen decline at increasing timepoints post-mortem did not correspond with existing published studies. NIR spectra (538 to 1677 nm) of LD muscles from steers (n = 47), cows (n = 28) and bulls (n = 20) routinely slaughtered in a commercial abattoir were collected on-line approximately 45 minutes after slaughter. Poor results were obtained for Partial Least Squares (PLS) models generated from the mean reflectance spectra of each animal to measure glycogen and pH45, and predict pHu (r2 = 0.23, 0.37 and 0.20 respectively). A high mean square error of prediction (MSEP) for glycogen was also obtained (7.75). Validation of qualitative models generated with Generalised Partial Least Squares regression (GPLS) found that the optimum model was able to correctly categorise only 42% of high pHu samples with the remaining portion being wrongly classified as normal pHu meat. When the effect of gender was removed, only 21% of high pHu carcasses were correctly categorised. Exploratory analysis of the absorbance spectra of the LD muscles showed that a group composed predominantly of steers had a significantly lower pH45 than other existing groups. Further work is recommended for NIR to be successfully utilised on-line to measure glycogen or predict pHu in pre-rigor carcasses. | |
| dc.identifier.uri | https://hdl.handle.net/10292/970 | |
| dc.language.iso | en_NZ | |
| dc.publisher | Auckland University of Technology | |
| dc.rights.accessrights | OpenAccess | |
| dc.subject | Glycogen | |
| dc.subject | pH | |
| dc.subject | Beef | |
| dc.subject | NIR | |
| dc.title | Rapid on-line Glycogen measurement and prediction of ultimate pH in slaughter beef | |
| dc.type | Thesis | |
| thesis.degree.grantor | Auckland University of Technology | |
| thesis.degree.level | Masters Theses | |
| thesis.degree.name | Master of Applied Science |