Online prediction of beef tenderness using a computer vision system equipped with a BeefCam module

Wavelength Selection FOR Rapid Identification of Different Particle Size Fractions of Milk Powder Using Hyperspectral Imaging

Hyperspectral imaging (HSI) in the spectral range of 400-1000 nm was tested to differentiate three different particle size fractions of milk powder. Partial least squares discriminant analysis (PLS-DA) was performed to observe the relationship of spectral data and particle size information for various samples of instant milk powder. The PLS-DA model on full wavelengths successfully classified the three fractions of milk powder with a coefficient of prediction 0.943. Principal component analysis (PCA) identified each of the milk powder fractions as separate clusters across the first two principal components (PC₁ and PC₂) and five characteristic wavelengths were recognised by the loading plot of the first three principal components. Weighted regression coefficient (WRC) analysis of the partial least squares model identified 11 important wavelengths. Simplified PLS-DA models were developed from two sets of reduced wavelengths selected by PCA and WRC and showed better performance with predictive correlation coefficients (R_p²) of 0.962 and 0.979, respectively, while PLS-DA with complete spectrum had R_p² of 0.943. Similarly, classification accuracy of PLS-DA was improved to 92.2% for WRC based predictive model. Calculation time was also reduced to 2.1 and 2.8 s for PCA and WRC based simplified PLS-DA models in comparison to the complete spectrum model that was taking 32.2 s on average to predict the classification of milk powder samples. These results demonstrated that HSI with appropriate data analysis methods could become a potential analyser for non-invasive testing of milk powder in the future.

Comparison of Machine Learning Algorithms for Predictive Modeling of Beef Attributes Using Rapid Evaporative Ionization Mass Spectrometry (REIMS) Data

Ambient mass spectrometry is an analytical approach that enables ionization of molecules under open-air conditions with no sample preparation and very fast sampling times. Rapid evaporative ionization mass spectrometry (REIMS) is a relatively new type of ambient mass spectrometry that has demonstrated applications in both human health and food science. Here, we present an evaluation of REIMS as a tool to generate molecular scale information as an objective measure for the assessment of beef quality attributes. Eight different machine learning algorithms were compared to generate predictive models using REIMS data to classify beef quality attributes based on the United States Department of Agriculture (USDA) quality grade, production background, breed type and muscle tenderness. The results revealed that the optimal machine learning algorithm, as assessed by predictive accuracy, was different depending on the classification problem, suggesting that a “one size fits all” approach to developing predictive models from REIMS data is not appropriate. The highest performing models for each classification achieved prediction accuracies between 81.5–99%, indicating the potential of the approach to complement current methods for classifying quality attributes in beef.

Use of Visible-Near-Infrared (Vis-NIR) Spectroscopy to Detect Aflatoxin B1 on Peanut Kernels

Current methods for detecting aflatoxin contamination of agricultural and food commodities are generally based on wet chemical analyses, which are time-consuming, destructive to test samples, and require skilled personnel to perform, making them impossible for large-scale nondestructive screening and on-site detection. In this study, we utilized visible-near-infrared (Vis-NIR) spectroscopy over the spectral range of 400-2500 nm to detect contamination of commercial, shelled peanut kernels (runner type) with the predominant aflatoxin B₁ (AFB₁). The artificially contaminated samples were prepared by dropping known amounts of aflatoxin standard dissolved in 50:50 (v/v) methanol/water onto peanut kernel surface to achieve different contamination levels. The partial least squares discriminant analysis (PLS-DA) models established using the full spectra over different ranges achieved good prediction results. The best overall accuracy of 88.57% and 92.86% were obtained using the full spectra when taking 20 and 100 parts per billion (ppb), respectively, as the classification threshold. The random frog (RF) algorithm was used to find the optimal characteristic wavelengths for identifying the surface AFB₁-contamination of peanut kernels. Using the optimal spectral variables determined by the RF algorithm, the simplified RF-PLS-DA classification models were established. The better RF-PLS-DA models attained the overall accuracies of 90.00% and 94.29% with the 20 ppb and 100 ppb thresholds, respectively, which were improved compared to using the full spectral variables. Compared to using the full spectral variables, the employed spectral variables of the simplified RF-PLS-DA models were decreased by at least 94.82%. The present study demonstrated that the Vis-NIR spectroscopic technique combined with appropriate chemometric methods could be useful in identifying AFB₁ contamination of peanut kernels.

Evaluation of WBSF, Color, Cooking Loss of Longissimus Lumborum Muscle with Fiber Optic Near-Infrared Spectroscopy (FT-NIR), Depending on Aging Time

Near-infrared spectroscopy is a known technique for assessing the quality of compounds found in food products. However, it is still not widely used for predicting physical properties of meat using the online system. This study aims to assess the possibility of application of a NIR equipped with fiber optic system as an online measurement system to predict Warner⁻Bratzler shear force (WBSF) value, cooking loss (CL), and color of longissimus lumborum muscle, depending on aging time. The prediction model satisfactorily estimated the WBSF on day 1 and day 7 of aging as well as a* color parameter on day one and CL on day 21. This could be explained by the fact that during beef aging, the physicochemical structure of meat becomes more uniform and less differentiation of raw data is observed. There is still a challenge to obtain a verifiable model for the prediction of physical properties, using NIR, by utilizing more varied raw data.

Recent advances in rapid and nondestructive determination of fat content and fatty acids composition of muscle foods

Conventional methods for determining fat content and fatty acids (FAs) composition are generally based on the solvent extraction and gas chromatography techniques, respectively, which are time consuming, laborious, destructive to samples and require use of hazard solvents. These disadvantages make them impossible for large-scale detection or being applied to the production line of meat factories. In this context, the great necessity of developing rapid and nondestructive techniques for fat and FAs analyses has been highlighted. Measurement techniques based on near-infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance and hyperspectral imaging have provided interesting and promising results for fat and FAs prediction in varieties of foods. Thus, the goal of this article is to give an overview of the current research progress in application of the four important techniques for fat and FAs analyses of muscle foods, which consist of pork, beef, lamb, chicken meat, fish and fish oil. The measurement techniques are described in terms of their working principles, features, and application advantages. Research advances for these techniques for specific food are summarized in detail and the factors influencing their modeling results are discussed. Perspectives on the current situation, future trends and challenges associated with the measurement techniques are also discussed.

Review: Canadian beef grading – Opportunities to identify carcass and meat quality traits valued by consumers

Aalhus, J. L., López-Campos, Ó., Prieto, N., Rodas-González, A., Dugan, M. E. R., Uttaro, B. and Juárez, M. 2014. Review: Canadian beef grading – Opportunities to identify carcass and meat quality traits valued by consumers. Can. J. Anim. Sci. 94: 545–556. Beef value is in the eye, mouth or mind of the consumer; however, currently, producers are paid on the basis of carcass grade. In general, affluent consumers are becoming more discerning and are willing to pay for both credence and measureable quality differences. The Canadian grading system for youthful carcasses identifies both lean yield and quality attributes, whereas mature carcasses are broadly categorized. Opportunities exist to improve the prediction of lean meat yield and better identify meat quality characteristics in youthful beef, and to obtain additional value from mature carcasses through muscle profiling. Individual carcass identification along with development of database systems like the Beef InfoXchange System (BIXS) will allow a paradigm shift for the industry as traits of economic value can be easily identified to improve marketing value chains. In the near future, developing technologies (e.g., grade cameras, dual energy X-ray absorptiometry, and spectroscopic methods such as near infrared spectroscopy, Raman spectroscopy and hyperspectral imaging) will be successfully implemented on-line to identify a multitude of carcass and quality traits of growing importance to segments of the consuming population.

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Effects of duration of zilpaterol hydrochloride and days on the finishing diet on carcass cutability, composition, tenderness, and skeletal muscle gene expression in feedlot steers

Preselected carcasses (n = 112) from feedlot steers fed zilpaterol hydrochloride (ZH; 8.33 mg/kg, DM basis) in a serial slaughter experiment were evaluated to determine the effects of ZH upon carcass cutability, composition, and tenderness. A 4 x 4 factorial arrangement of treatments in a completely random design was used with days on ZH (0, 20, 30, and 40 d before slaughter with a 3-d withdrawal) and days on the finishing diet (DOF; 136, 157, 177, and 198 d). No relevant ZH duration x slaughter group interactions were detected (P > 0.05) for carcass cutability, composition, or tenderness data. Exposure to ZH increased the lean yield of 22 of the 33 subprimals evaluated with every subprimal within the round showing increased cutability (P < or = 0.04). Carcass fat was decreased, whereas carcass protein and moisture were increased due to ZH (P < 0.01). Lengthening the ZH feeding period did not result in additive gains in subprimal yield or chemical composition (P > 0.05). Warner-Bratzler shear force analysis of the LM indicated that ZH caused a toughening effect (P < 0.01) regardless of the length of the aging period (7, 14, or 21 d). Extending the ZH dose duration caused a linear increase in Warner-Bratzler shear force at 7 (P = 0.06) and 21 d (P < 0.01) of aging. Within 10 min postmortem, samples (n = 48) were collected from the semimembranosus muscle for RNA isolation from 4 randomly selected steers from each treatment within the 157, 177, and 198 d slaughter groups. Feeding ZH did not alter beta1- or beta2-adrenergic receptor (AR), calpastatin (CAL), IGF-I, or myosin heavy chain (MHC) isoform I mRNA abundance (P > 0.10). There was a ZH duration x DOF interaction (P < 0.01) for the expression of MHC-IIa and -IIx. Expression of MHC-IIa was decreased in every ZH treatment within the 177 and 198 DOF groups (P < 0.02). Expression of MHC-IIx was increased in the 20-d ZH group in the 157 DOF group (P = 0.03), and the 40-d ZH group in the 177 (P = 0.10) and 198 (P = 0.03) DOF groups. There was a tendency for a linear decrease in CAL mRNA abundance as ZH duration increased (P = 0.07), and there was a linear increase in beta2-AR (P = 0.03) and CAL (P < 0.01) mRNA abundance as DOF increased. Collectively, the data indicate that ZH may influence net protein turnover by decreasing MHC-IIa mRNA transcription and possibly increasing MHC-IIx. Furthermore, a ZH feeding duration of 20 d appeared to be adequate for capturing lean yield benefits while limiting tenderness losses.

International perspective: characterisation of United States Department of Agriculture and Meat Standards Australia systems for assessing beef quality

The intent, in this manuscript, is to characterise the United States Department of Agriculture (USDA) and Meat Standards Australia (MSA) systems for assessing beef quality and to describe the research evidence that supports the principles involved in grade application. USDA beef quality grading standards rely on carcass-trait-only assessments of approximate age of the animal at harvest and amount of intramuscular fat (as marbling) inside the muscles. USDA beef quality grading started 82 years ago. Then, as now, because no traceability system was in place, each animal’s history (exact age, feeding regimen, management practices, etc.) was incomplete; those who assigned quality grades used indicators of age (physiological maturity) and plane of nutrition (amount of marbling), and they do so still. Since 1926, research studies have identified a multitude of palatability-determining live-animal factors (e.g. genetics, use of hormonal growth promotants, high-energy diet finishing) and carcass-treatment factors (e.g. electrical stimulation, tenderstretch carcass suspension, postmortem aging) that cannot be incorporated into a carcass-trait-only quality assessment system. The USA beef industry has depended on development of more than 100 beef brands – some using palatability assurance critical control point plans, total quality management (TQM) philosophies, USDA certification and process verification programs, or combinations of live-animal factors, carcass-treatment factors and carcass-trait constraints – to further differentiate fresh beef products. The MSA grading system is a TQM grading approach that incorporates animal-specific traits (e.g. genetics, sex, age), control of certain pre-harvest and post-harvest processes in the beef chain, cut-specific quality differences and consumer preferences, into a beef pricing system. A unique aspect of the MSA grading system is that the grades are assigned to cuts or muscles, not carcasses; cuts or muscles from the same carcass are assigned individual (and in many cases, different) grades that reflect differences in expected eating quality performance among the various cuts of beef further adjusted to reflect the influence of cut or muscle aging and alternative cooking methods. The MSA grading system is still being modified and refined (using results of an extensive, ongoing consumer testing program), but it represents the best existing example of a TQM grading approach for improving beef quality and palatability. Research studies have shown that the accuracy of palatability-level prediction by use of the two systems – USDA quality grades for US customers and consumers and MSA grades for Australian customers and consumers – is sufficient to justify their continued use for beef quality assessment.

Genetic parameters for image analysis traits on M. longissimus thoracis and M. trapezius of carcass cross section in Japanese Black steers

In Japan, the degree of marbling in ribeye (M. longissimus thoracis) is evaluated in the beef meat grading process. However, other muscles (e.g., M. trapezius) are also important in determining the meat quality and carcass market prices. The purpose of this study was to estimate genetic parameters for M. longissimus thoracis (M-LONG) and M. trapezius (M-TRAP) of carcass cross section of Japanese Black steers by computer image analysis. The number of records of Japanese Black steers and the number of pedigree records were 2,925 and 10,889, respectively. Digital images of the carcass cross section were taken between the sixth and seventh ribs by photographing equipment. Muscle area (MA), fat area ratio (FAR), overall coarseness of marbling particles (OCM), and coarseness of maximum marbling particle (MMC) in M-LONG and M-TRAP were calculated by image analysis. Genetic parameters for these traits were estimated using the AIREMLF90 program with an animal model. Fixed effects that were included in the model were dates of arrival at the carcass market and slaughter age (mo), and random effects of fattening farms, additive genetic effects and residuals were included in the model. For M-LONG, heritability estimates (+/-SE) were 0.46 +/- 0.06, 0.59 +/- 0.06, 0.47 +/- 0.06, and 0.20 +/- 0.05 for MA, FAR, OCM, and MMC, respectively. Heritability estimates (+/-SE) in M-TRAP were 0.47 +/- 0.06, 0.57 +/- 0.07, 0.49 +/- 0.07, and 0.13 +/- 0.04 for the same traits. Genetic correlations between subcutaneous fat thickness and FAR for M-LONG and M-TRAP were negative (-0.21 and -0.19, respectively). Those correlations between M-LONG and M-TRAP were moderate to high for MA, FAR, OCM, and MMC (0.38, 0.52, 0.39, and 0.60, respectively). These results indicate that other muscles including M-LONG should be evaluated for more efficient genetic improvement.

Relationships of consumer sensory ratings, marbling score, and shear force value to consumer acceptance of beef strip loin steaks

Logistic regression was used to quantify and characterize the effects of changes in marbling score, Warner-Bratzler shear force (WBSF), and consumer panel sensory ratings for tenderness, juiciness, or flavor on the probability of overall consumer acceptance of strip loin steaks from beef carcasses (n = 550). Consumers (n = 489) evaluated steaks for tenderness, juiciness, and flavor using nine-point hedonic scales (1 = like extremely and 9 = dislike extremely) and for overall steak acceptance (satisfied or not satisfied). Predicted acceptance of steaks by consumers was high (> 85%) when the mean consumer sensory rating for tenderness,juiciness, or flavor for a steak was 3 or lower on the hedonic scale. Conversely, predicted consumer acceptance of steaks was low (< or = 10%) when the mean consumer rating for tenderness, juiciness, or flavor for a steak was 5 or higher on the hedonic scale. As mean consumer sensory ratings for tenderness, juiciness, or flavor decreased from 3 to 5, the probability of acceptance of steaks by consumers diminished rapidly in a linear fashion. These results suggest that small changes in consumer sensory ratings for these sensory traits have dramatic effects on the probability of acceptance of steaks by consumers. Marbling score displayed a weak (adjusted R2 = 0.053), yet significant (P < 0.01), relationship to acceptance of steaks by consumers, and the shape of the predicted probability curve for steak acceptance was approximately linear over the entire range of marbling scores (Traces67 to Slightly Abundant97), suggesting that the likelihood of consumer acceptance of steaks increases approximately 10% for each full marbling score increase between Slight to Slightly Abundant. The predicted probability curve for consumer acceptance of steaks was sigmoidal for the WBSF model, with a steep decline in predicted probability of acceptance as WBSF values increased from 3.0 to 5.5 kg. Changes in WBSF within the high (> 5.5 kg) or low (< 3.0 kg) portions of the range of WBSF values had little effect on the probability of consumer acceptance of steaks.