Optical scattering with hyperspectral imaging to classify longissimus dorsi muscle based on beef tenderness using multivariate modeling

The objective of this study was to develop a non-destructive method for classifying cooked-beef tenderness using hyperspectral imaging of optical scattering on fresh beef muscle tissue. A hyperspectral imaging system (λ = 922–1739 nm) was used to collect hyperspectral scattering images of the longissimus dorsi muscle (n = 472). A modified Lorentzian function was used to fit optical scattering profiles at each wavelength. After removing highly correlated parameters extracted from the Lorentzian function, principal component analysis was performed. Four principal component scores were used in a linear discriminant model to classify beef tenderness. In a validation data set (n = 118 samples), the model was able to successfully classify tough and tender samples with 83.3% and 75.0% accuracies, respectively. Presence of fat flecks did not have a significant effect on beef tenderness classification accuracy. The results demonstrate that hyperspectral imaging of optical scattering is a viable technology for beef tenderness classification.     

Prediction of beef quality attributes using VIS/NIR hyperspectral scattering imaging technique

Hyperspectral imaging images were used to predict fresh beef tenderness (WBSF: Warner-Bratzler Shear Force) and color parameters (L^∗, a^∗, b^∗). Sixty-five fresh strip loin cuts were collected from 33 carcass after 2 days postmortem. After acquiring hyperspectral images, the samples were vacuum packaged and aged for 7 days, and then the color parameters and WBSF of the samples were measured as references. The optical scattering profiles were extracted from the images and fitted to the Lorentzian distribution (LD) function with three parameters. LD parameters, such as the scattering asymptotic vale, the peak height, and full scattering width were determined at each wavelength. Stepwise discrimination was used to identify optimal wavelengths. The LD parameters’ combinations with optimal wavelengths were used to establish multi-linear regression (MLR) models to predict the beef attributes. The models were able to predict beef WBSF with R_cv = 0.91, and color parameters (L^∗, a^∗, b^∗) with R_cv of 0.96, 0.96 and 0.97, respectively.     

Potential prediction of the microbial spoilage of beef using spatially resolved hyperspectral scattering profiles

Spoilage in beef is the result of decomposition and the formation of metabolites caused by the growth and enzymatic activity of microorganisms. There is still no technology for the rapid, accurate and non-destructive detection of bacterially spoiled or contaminated beef. In this study, hyperspectral imaging technique was exploited to measure biochemical changes within the fresh beef. Fresh beef rump steaks were purchased from a commercial plant, and left to spoil in refrigerator at 8 °C. Every 12 h, hyperspectral scattering profiles over the spectral region between 400 and 1100 nm were collected directly from the sample surface in reflection pattern in order to develop an optimal model for prediction of the beef spoilage, in parallel the total viable count (TVC) per gram of beef were obtained by classical microbiological plating methods. The spectral scattering profiles at individual wavelengths were fitted accurately by a two-parameter Lorentzian distribution function. TVC prediction models were developed, using multi-linear regression, on relating individual Lorentzian parameters and their combinations at different wavelengths to log₁₀(TVC) value. The best predictions were obtained with r² = 0.95 and SEP = 0.30 for log₁₀(TVC). The research demonstrated that hyperspectral imaging technique showed potential for real-time and non-destructive detection of bacterial spoilage in beef.     

Simultaneous determination of tenderness and Escherichia coli contamination of pork using hyperspectral scattering technique

A rapid nondestructive method based on hyperspectral scattering technique for simultaneous determination of pork tenderness and Escherichia coli (E. coli) contamination was studied in the research. The hyperspectral scattering images of thirty-one pork samples were collected in 400-1100 nm, and the scattering profiles were then fitted by Lorentzian distribution function to give three parameters a (asymptotic value), b (peak value) and c (full width at b/2). The combined parameters of (b-a), (b-a) × c, (b-a)/c and “a&b&c” were used to develop multi-linear regression (MLR) models for prediction of pork tenderness and E. coli contamination. It was shown that MLR models developed using parameters a, b, (b-a) and (b-a)/c can give high correlation coefficients of 0.831, 0.860, 0.856 and 0.930 respectively for pork tenderness prediction. For E. coli contamination of pork, MLR models based on parameters a and “a&b&c” can give high R_CV of 0.877 and 0.841 respectively.     

Relationships of slice shear force and Warner-Bratzler shear force of beef strip loin steaks as related to the tenderness gradient of the strip loin

This study was conducted to investigate the effects of steak location within a strip loin and USDA quality grade on muscle fiber angle, slice shear force (SSF), and Warner-Bratzler shear force (WBSF) and to determine the relationship between SSF and WBSF. Steak location influenced both SSF and WBSF values, as steaks from the anterior portion were typically tenderer than steaks from the posterior end. Although there is some discrepancy between the two shear force methods, both agree that at least the first 5 anterior-most steaks are comparable. Muscle fiber angle was affected by steak position within the strip loin, as the fiber angle shifted between steaks 7 and 8. Quality grade had a significant effect on beef tenderness for both SSF and WBSF. Finally, there was a strong relationship between lateral SSF and average WBSF (r = 0.64), which are currently the most commonly used measurements for instrumental tenderness.     

Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging

This study was carried out for post-mortem non-destructive prediction of water holding capacity (WHC) in fresh beef using near infrared (NIR) hyperspectral imaging. Hyperspectral images were acquired for different beef samples originated from different breeds and different muscles and their spectral signatures were extracted. Both principal component analysis (PCA) and partial least squares regression (PLSR) models were developed to obtain an overview of the systematic spectral variations and to correlate spectral data of beef samples to its real WHC estimated by drip loss method. Partial least squares modeling resulted in a coefficient of determination (R_CV²) of 0.89 and standard error estimated by cross validation (SECV) of 0.26%. The PLSR loadings showed that there are some important absorption peaks throughout the whole spectral range that had the greatest influence on the predictive models. Six wavelengths (940, 997, 1144, 1214, 1342, and 1443 nm) were then chosen as important wavelengths to build a new PLS prediction model. The new model led to a coefficient of determination (R_CV²) of 0.87 and standard error estimated by cross validation (SECV) of 0.28%. Image processing algorithm was then developed to transfer the predicting model to each pixel in the image for visualizing drip loss in all portions of the sample. The results showed that hyperspectral imaging has the potential to predict drip loss non-destructively in a reasonable accuracy and the results could be visualised for identification and classification of beef muscles in a simple way. In addition to realize the difference in WHC within one sample, it was possible to accentuate the difference in samples having different drip loss values.     

Using shear force,sarcomere length,particle size,collagen content,and protein solubility metrics to predict consumer acceptance of aged beef tenderness

In this study, the relationship between sensory evaluation and several objective metrics of beef tenderness was tested. Objective metrics included shear force, sarcomere length, collagen content, myofibrillar, and sarcoplasmic protein solubility and particle size analysis. These results were compared to consumer panel scores of tenderness for the same aged beef striploin (longissimus lumborum muscle) samples. There was found to be a significant relationship between sarcomere length, shear force, and particle size with tenderness scores. Collagen content and protein solubilities were not associated to tenderness scores (p > 0.05). Sarcomere length contributions for explaining tenderness variation were overlapped by the contributions of shear force (collinearity). Independent models demonstrated that the lower 95% confidence interval of the fitted regression line exceeded 50% acceptance of tenderness when shear force values <42.6 N and when particle size values <198 μm. We can recommend these as thresholds for consumer acceptance of beef tenderness, although considerations of sample type, analytical methodology, and consumer demographics should be made prior to their adoption. This provision was based on the variation in tenderness scores evident between individual panelists and experimental striploins.     

Variation in the response to manipulation of post-mortem glycolysis in beef muscles by low-voltage electrical stimulation and conditioning temperature

The aim of this study was to investigate how manipulation of glycolytic rate by post-mortem processing conditions influences quality of aged beef of two bovine muscles of different physiological character, longissimus dorsi (LD) and adductor (AD). Post-mortem glycolysis was manipulated by low-voltage electrical stimulation (LV-ES) of half carcasses and by chilling rate of the muscles. Multivariate statistical analysis was used to visualise the data, while ANOVA was used to identify significant effects and interactions. As expected there was a significant effect of LV-ES on the pH decline in the first hours post-mortem in both muscles. Moreover, significant effects of LV-ES on WB shear force measured 2 and 8 days after slaughter were observed for LD at both chilling temperatures, while for AD no effect on WB shear force was observed. Furthermore, the results revealed a large individual variation in the response of LV-ES on both pH decline and WB shear force, and this variation did not always correlate for the two responses. Some animals showed no response of LV-ES on pH decline, but still had an improved WB shear force, and vice versa. The results from this study indicate that there probably are other mechanisms than accelerated pH decline and prevention of cold-shortening, by which LV-ES can affect meat tenderness.