Post-slaughter changes in ATP metabolites, reducing and phosphorylated sugars in chicken meat.

The formation of ATP breakdown products in chicken M. pectoralis major post-slaughter is reported. The concentrations of metabolites were followed in chicken breast throughout the carcass processing post-slaughter and during chilled storage. The concentration of glucose remains similar throughout the period whilst that of glucose-6-phosphate decreases linearly. Glucose and glucose-6-phosphate concentrations were inversely related to the pHu of the breast meat throughout chilled storage. Rapid post-mortem glycolysis and high pHu values suggest the occurrence of stress at and pre-slaughter. Whilst ATP, ADP and AMP were rapidly broken down, the concentration of IMP rose rapidly and remained high. Concentrations of inosine, ribose and hypoxanthine increased gradually post-slaughter but an initial increase in ribose phosphate was not sustained. Most of the potential ribose present in chicken meat, believed to be important for flavor formation, remains bound in the form of inosine and IMP. There is evidence that additional breakdown pathways for ribose and ribose-5-phosphate may deplete the concentrations of these precursors.

Comparison of consumer perception and acceptability for steaks cooked to different endpoints: validation of photographic approach.

Photographs have been used to enhance consumer reporting of preference of meat doneness, however, the use of photographs has not been validated for this purpose. This study used standard cooking methods to produce steaks of five different degrees of doneness (rare medium, medium well, well done and very well done) to study the consumer's perception of doneness, from both the external and internal surface of the cooked steak and also from corresponding photographs of each sample. Consumers evaluated each surface of the cooked steaks in relation to doneness for acceptability, 'just about right' and perception of doneness. Data were analysed using a split plot ANOVA and least significant test. Perception scores (for both external and internal surfaces) between different presentation methods (steak samples and corresponding photos), were not significantly different (p>0.05). The result indicates that photographs can be used as a valid approach for assessing preference for meat doneness.

Red meat consumption: an overview of the risks and benefits.

Red meat is long established as an important dietary source of protein and essential nutrients including iron, zinc and vitamin B12, yet recent reports that its consumption may increase the risk of cardiovascular disease (CVD) and colon cancer have led to a negative perception of the role of red meat in health. The aim of this paper is to review existing literature for both the risks and benefits of red meat consumption, focusing on case-control and prospective studies. Despite many studies reporting an association between red meat and the risk of CVD and colon cancer, several methodological limitations and inconsistencies were identified which may impact on the validity of their findings. Overall, there is no strong evidence to support the recent conclusion from the World Cancer Research Fund (WCRF) report that red meat has a convincing role to play in colon cancer. A substantial amount of evidence supports the role of lean red meat as a positive moderator of lipid profiles with recent studies identifying it as a dietary source of the anti-inflammatory long chain (LC) n-3 PUFAs and conjugated linoleic acid (CLA). In conclusion, moderate consumption of lean red meat as part of a balanced diet is unlikely to increase risk for CVD or colon cancer, but may positively influence nutrient intakes and fatty acid profiles, thereby impacting positively on long-term health.

Preliminary investigations on the effects of ageing and cooking on the Raman spectra of porcine longissimus dorsi.

The influence of ageing and cooking on the Raman spectrum of porcine longissimus dorsi was investigated. The rich information contained in the Raman spectrum was highlighted, with numerous changes attributed to changes in the environment and conformations of the myofibrillar proteins. Predictions equations for shear force and cooking loss were developed from the Raman spectra of both raw and cooked pork. Good correlations and standard errors of prediction were obtained for both WB shear force and cooking loss, with the raw and the cooked samples showing almost identical results R(2)=0.77, root mean standard error of prediction (RMSEP)% of mean=12% for shear force; R(2)=0.71, RMSEP% of mean=10% for cooking loss. The Raman spectra were also able to predict the extent of cooking that occurred within the pork (R(2)(val)=0.94, RMSEP% of range=5.5%). Raman spectroscopy has considerable potential as a method for non-destructive and rapid determination of pork quality parameters such as tenderness. Raman spectroscopy may provide a means of determining changes during cooking and the extent to which foods have been cooked.

Classification of adipose tissue species using Raman spectroscopy.

In this study multivariate analysis of Raman spectra has been used to classify adipose tissue from four different species (chicken, beef, lamb and pork). The adipose samples were dissected from the carcass and their spectra recorded without further preparation. 102 samples were used to create and compare a range of statistical models, which were then tested on 153 independent samples. Of the classical multivariate methods employed, Partial Least Squares Discriminant Analysis (PLSDA) performed best with 99.6% correct classification of species in the test set compared with 96.7% for Principal Component Linear Discrimination Analysis (PCLDA). Kohenen and Feed-forward artificial neural networks compared well with the PLSDA, giving 98.4 and 99.2% correct classification, respectively.

Prediction of adipose tissue composition using Raman spectroscopy: average properties and individual fatty acids.

Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (> or = 2 double bonds per chain) was also well predicted with R2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

A critical evaluation of Raman spectroscopy for the analysis of lipids: fatty acid methyl esters.

The work presented here is aimed at determining the potential and limitations of Raman spectroscopy for fat analysis by carrying out a systematic investigation of C4-C24 FAME. These provide a simple, well-characterized set of compounds in which the effect of making incremental changes can be studied over a wide range of chain lengths and degrees of unsaturation. The effect of temperature on the spectra was investigated over much larger ranges than would normally be encountered in real analytical measurements. It was found that for liquid FAME the best internal standard band was the carbonyl stretching vibration v(C=O), whose position is affected by changes in sample chain length and physical state; in the samples studied here, it was found to lie between 1729 and 1748 cm(-1). Further, molar unsaturation could be correlated with the ratio of the nu(C=O) to either nu(C=C) or delta(H-C=) with R2 > 0.995. Chain length was correlated with the delta(CH2)tw/v(C=O) ratio, (where "tw" indicates twisting) but separate plots for odd- and even-numbered carbon chains were necessary to obtain R2 > 0.99 for liquid samples. Combining the odd- and even-numbered carbon chain data in a single plot reduced the correlation to R2 = 0.94-0.96, depending on the band ratios used. For molal unsaturation the band ratio that correlated linearly with unsaturation (R2 > 0.99) was nu(C=C)/delta(CH2)sc (where "sc" indicates scissoring). Other band ratios show much more complex behavior with changes in chemical and physical structure. This complex behavior results from the fact that the bands do not arise from simple vibrations of small, discrete regions of the molecules but are due to complex motions of large sections of the FAME so that making incremental changes in structure does not necessarily lead to simple incremental changes in spectra.

Preliminary investigation of the application of Raman spectroscopy to the prediction of the sensory quality of beef silverside.

The potential of Raman spectroscopy for the determination of meat quality attributes has been investigated using data from a set of 52 cooked beef samples, which were rated by trained taste panels. The Raman spectra, shear force and cooking loss were measured and PLS used to correlate the attributes with the Raman data. Good correlations and standard errors of prediction were found when the Raman data were used to predict the panels' rating of acceptability of texture (R(2)=0.71, Residual Mean Standard Error of Prediction (RMSEP)% of the mean (µ)=15%), degree of tenderness (R(2)=0.65, RMSEP% of µ=18%), degree of juiciness (R(2)=0.62, RMSEP% of µ=16%), and overall acceptability (R(2)=0.67, RMSEP% of µ=11%). In contrast, the mechanically determined shear force was poorly correlated with tenderness (R(2)=0.15). Tentative interpretation of the plots of the regression coefficients suggests that the α-helix to ß-sheet ratio of the proteins and the hydrophobicity of the myofibrillar environment are important factors contributing to the shear force, tenderness, texture and overall acceptability of the beef. In summary, this work demonstrates that Raman spectroscopy can be used to predict consumer-perceived beef quality. In part, this overall success is due to the fact that the Raman method predicts texture and tenderness, which are the predominant factors in determining overall acceptability in the Western world. Nonetheless, it is clear that Raman spectroscopy has considerable potential as a method for non-destructive and rapid determination of beef quality parameters.

Multivariate prediction of clarified butter composition using Raman spectroscopy.

Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed good prediction for the five major (abundance >5%) FA with R2 = 0.74-0.92 and a root mean SE of prediction (RMSEP) that was 5-7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was <10% for all but one of the 10 FA present at levels >1.25%. The Raman method has the best prediction ability for unsaturated FA (R2 = 0.85-0.92), and in particular trans unsaturated FA (best-predicted FA was 18:1 t delta9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R2 = 0.80) and solid fat content at low temperature (R2 = 0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R2 = 0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.