Vascular rinsing and chilling effects on meat quality attributes from cull dairy cows associated with the two lowest-valued marketing classes.

Commercially harvested cull dairy cow carcasses (n = 64) from the two lowest-valued marketing classes (MC: Lean, LE; Light, LI) were conventionally chilled (CN) or vascularly rinsed with a chilled isotonic substrate solution (Rinse & Chill®; RC). Longissimus lumborum (LL) and Triceps brachii (TB) muscles were processed (steaks, ground). Early postmortem (first 24 h), RC resulted in a lower pH at each time measured. RC steaks had longer sarcomeres and lower shear force than CN. RC produced greater redness associated with blooming and display times. RC LE beef resulted in greater oxymyoglobin during display times. RC ground TB had greater moisture fat-free than CN. RC Lean LL had less purge loss compared to CN LE. RC had greater total pigments than CN. RC ground TB had greater oxygen consumption and lower thiobarbituric acid reactive substances compared to CN. RC has the potential to improve tenderness and color as well as limit lipid oxidation with similar benefits across the two marketing classes.

Predicting carcass cut yields in cattle from digital images using artificial intelligence.

Deep Learning (DL) has proven to be a successful tool for many image classification problems but has yet to be applied to carcass images. The aim of this study was to train DL models to predict carcass cut yields and compare predictions to more standard machine learning (ML) methods. Three approaches were undertaken to predict the grouped carcass cut yields of Grilling cuts and Roasting cuts from a large dataset of 54,598 and 69,246 animals respectively. The approaches taken were (1) animal phenotypic data used as features for a range of ML algorithms, (2) carcass images used to train Convolutional Neural Networks, and (3) carcass dimensions measured directly from the carcass images, combined with the associated phenotypic data and used as feature data for ML algorithms. Results showed that DL models can be trained to predict carcass cuts yields but an approach that uses carcass dimensions in ML algorithms performs slightly better in absolute terms.

Line-scan Raman scattering image and multivariate analysis for rapid and noninvasive detection of restructured beef.

The mean spectral (MS) features were extracted from Raman scattering images (RSI) of beef samples over the region of interest covering the spectral range of 789-1710cm-1 and the spatial offset range of 0-5 mm (for two sides of the incident laser). The RSI monitored the main change in the protein, amide bands, lipids, and amino acid residues. The classification model performance based on MS features compared the conventional Raman spectral features and confirmed the usefulness of RSI. Finally, the results showed that RSI technology is a reliable tool for rapid and noninvasive detection of restructured beef.

Rapid and non-destructive spectroscopic method for classifying beef freshness using a deep spectral network fused with myoglobin information.

A simple, novel, rapid, and non-destructive spectroscopic method that employs the deep spectral network for beef-freshness classification was developed. The deep-learning-based model classified beef freshness by learning myoglobin information and reflectance spectra over different freshness states. The reflectance spectra (480-920 nm) were measured from 78 beef samples for 17 days, and the datasets were sorted into three freshness classes based on their pH values. Myoglobin information showed statistically significant differences depending on the freshness; consequently, it was utilized as a crucial parameter for classification. The model exhibited improved performance when the reflectance spectra were combined with the myoglobin information. The accuracy of the proposed model improved to 91.9%, whereas that of the single-spectra model was 83.6%. Further, a high value for the area under the receiver operating characteristic curve (0.958) was recorded. This study provides a basis for future studies on the investigation of myoglobin information associated with meat freshness.

Discrimination of mutton from different sources (regions, feeding patterns and species) by mineral elements in Inner Mongolia, China.

The traceability of mineral element fingerprints to mutton in a small area of China was studied. The element data of 104 sheep and 24 goat samples from Inner Mongolia were measured, and the data were analyzed by multivariate statistical analysis from different origins, species and feeding patterns. The results shows that 11 elements (Mg, Al, K, Ca, Mn, Fe, Cu, Zn, Rb, Sr, Ba) in sheep meat had significant differences between different regions (P < 0.05), and the results of linear discriminant analysis (LDA) showed that the accuracy of the original classification rate was 95.2%, and the cross-validation rate was 85.9%. Goat meat and sheep meat samples from Alxa League were also clearly identified with LDA results showing that the cross-validation accuracy of the two species was 70.2%. Then the feeding patterns of sheep meat were effectively classified. The results showed that the multi-element analysis has certain potential as a method to distinguish mutton in a small area.

Trace elements and machine learning for Brazilian beef traceability.

Brazilian livestock with a herd of more than 215 million animals is distributed over a vast area of 160 million hectares, leading the country to the first position in the world beef exports and second in beef production and consumption. Animals risen in the biomes Amazônia, Caatinga, Cerrado, Pampa and Pantanal were selected for this study. Beef samples were analyzed for their elemental content by neutron activation analysis and classified according to their origin by three machine learning algorithms (Multilayer Perceptron, Random Forest and Classification and Regression Tree). Significant differences (p < 0.0001) were observed between the beef elemental content from the different biomes for all multivariate contrasts using NPMANOVA. The highest classification performance was obtained for the biomes Amazônia and Caatinga using Multilayer Perceptron. Results showed the feasibility of combining trace element content and machine learning approaches for the Brazilian beef traceability.

Cattle production practices and the incidence of dark cutting beef.

The effects of cattle sex, production system, growth promotant use, slaughter season, carcass phenotype, and pre-slaughter cattle management on the incidence of beef carcasses grading Canada B4 (dark cutting) were investigated using two data sets (A, n = 2009, and B, n = 86,408) containing data from cattle that produced Canada Prime, AAA, AA, A, and B4 carcasses. The probability of producing a Canada B4 carcass was greater (P < .0001) for heifers than steers in both data sets, with the likelihood of dark cutting decreasing with increased carcass weight in heifers in data set B. The incidence of dark cutting was increased (P < .0001) in Winter-born calf-fed (WC) and Fall-born calf-fed (FC) heifers. Production system and phenotype appear to interact to influence the incidence of dark cutting.

Automatic ham classification method based on support vector machine model increases accuracy and benefits compared to manual classification.

The thickness of the subcutaneous fat (SFT) is a very important parameter in the ham, since determines the process the ham will be submitted. This study compares two methods to predict the SFT in slaughter line: an automatic system using an SVM model (Support Vector Machine) and a manual measurement of the fat carried out by an experienced operator, in terms of accuracy and economic benefit. These two methods were compared to the golden standard obtained by measuring SFT with a ruler in a sample of 400 hams equally distributed within each SFT class. The results show that the SFT prediction made by the SVM model achieves an accuracy of 75.3%, which represents an improvement of 5.5% compared to the manual measurement. Regarding economic benefits, SVM model can increase them between 12 and 17%. It can be concluded that the classification using SVM is more accurate than the one performed manually with an increase of the economic benefit for sorting.

Number of consumers and days of display necessary for the assessment of meat colour acceptability.

Visual assessment is regarded as the gold standard to evaluate meat colour shelf-life, but it is costly and time consuming. To address this issue, this paper aims to evaluate the number of consumers and days of display that are necessaries in order to assess the colour shelf-life of meat, presented with different methods, all using images. Photographs of thirty-six lamb steaks were taken just after cutting (day 0) and on each of the following days until the 14th day of display under standardized conditions. Images were presented in three different manners: 1) with days of display and animals in random order (Random); 2) days of display in sequential and animals in random order (Sequential); and, 3) days of display and animals in sequential order (Animal); they were presented to 211 consumers who evaluated visual acceptability on a 9-point scale. At day zero, visual acceptability scores were the highest in Animal, followed by Sequential, and then by the Random (P < .05) method. Scores decreased over time for all methods tested (P < .05). The Random method presented the highest standard deviation; however, an increase in standard deviation among consumers along days of display was observed for all methods tested (P < .05). Shelf-life determined by regression varied according to the method of presentation (7.83, 7.00 and 7.54 days for Random, Sequential and Animal, respectively). A minimum number of 4 day points before and 4 day points after neutral scores had been reached (scores = 5.0) were necessary in order to obtain a robust model. The minimum number of required consumers (α = 0.05; d = 0.1 and ß = 0.2 or 0.1) varied according to methodology: it was 81 to 109 consumers for Random, 69 to 92 for Sequential, and 55 to 74 for Animal. Our study indicates that an optimal number of days and evaluators can be calculated depending on the manner of sample presentation. These findings should be taken into account in further studies that aim to balance data reliability with the cost involved in meat colour analyses.

Bovine M. longissimus thoracis meat quality differences due to Canada quality grade.

Differences in meat quality characteristics between the four Canada beef quality grades (Canada Prime, AAA, AA, and A) at days 4 and 18 post mortem were investigated using 48 (n = 12/grade) bovine M. longissimus thoracis (LT, rib eye). There was no difference in intramuscular fat content between Canada A and AA LT, and Canada AA LT had a higher mean Warner-Bratzler shear force (WBSF) than LT from all other grades (P = 0.0009) at day 18 post mortem. Canada Prime muscles were lighter and yellower than muscle from all other grades, and their increased lightness persisted with ageing. Mean cooking loss was lowest in Canada Prime LT and correlated with intramuscular fat content (r = -0.41 and - 0.29, days 4 and 18, respectively). Results confirmed differences in cooked product toughness can exist between the grades, with the potential for reduced tenderization in Canada AA LT.

Credence cues of pork are more important than consumers' culinary skills to boost their purchasing intention.

The role of consumers' culinary skills on purchasing cues of pork, with emphasis on niche demands (outdoor husbandry and/or certified organic), was assessed in cross-country regions of Spain (Catalonia and Aragon) and Portugal (North). A sample of 974 respondents answered an on-line survey with questions regarding consumer purchasing habits, product involvement and intrinsic and credence attributes. They also chose between two contrasting boneless pork loins and express willingness to pay (WTP) for different product scenarios with different pig farm facilities and for organic pork standards. Two optimal segments were identified based on food-related habits: 'uninvolved' and 'innovative cook lovers', both similarly balanced across socio-demographics, score for credence attributes or consumer involvement dimensions. Overall mean WTP premium across countries was 11.8% for marbled pork, 20.0% for outdoor pork and 24.3% for organic logo stamp. Credence cues of pork claiming health issues (absence of antibiotics and hormone residues) rather than consumers' culinary skills defined the WTP for niche pork in these regions.

Classification of beef carcasses from Portugal using animal characteristics and pH/temperature decline descriptors.

Previous research showed that meat of optimal tenderness is produced when rigor mortis temperature falls between 12 - 35 °C. This study aimed to classify beef carcasses quality according to the ideal window rule using pH/temperature decay descriptors and animal characteristics. Seventy-four Mirandesa breed and 52 Crossbreds, with an average age of 10.1 ±â€¯2.32 months, were slaughtered at one abattoir located in the Northeast of Portugal. Carcass temperature and pH, logged during 24 h post-mortem, were modelled by exponential decay equations that estimated temperature (kT) and pH (kpH) decay rates. Additionally, other pH/temperature descriptors were estimated from the fitted models. From linear models adjusted to each descriptor, it was found that hot carcass weight, age, breed, gender, age class, fat cover, conformation and transport and lairage time had influence (P < 0.05) on pH and temperature decay rates. Thus, combining the variables kT and kpH, and selected animal/carcass characteristics as linear predictors, a system to classify quality of carcasses was developed.

Special-Fed Veal: Separable components, proximate composition, and nutrient analysis of selected raw and cooked, wholesale and retail cuts.

Nutrition research continues to be important for consumers to make informed food purchasing decisions and is used in nutrition policy decisions. The objective of this study was to analyze the nutrient concentration of raw and cooked cuts from special-fed veal calves to update nutrient data in the USDA National Nutrient Database for Standard Reference (SR) Release 27. Packages of wholesale (whole loin roasts, center-cut hindshanks and ground veal) and retail veal cuts (osso buco foreshanks, loin chops, leg cutlets and shoulder blade chops) were randomly collected in original vacuum packaging from six U.S. suppliers. Packages were shipped to the Colorado State University Meat Laboratory for cut dissection, cooking, and nutrient analysis. Composites of lean, external fat and seam fat were formed for analysis of proximate, fatty acid, vitamin and mineral composition. Results from this study identified additional fatty acids, established choline concentration, and provided updated veal nutrient composition information for inclusion in USDA SR 27.

On-site Method for Beef Detection Based on Strand Exchange Amplification.

Meat screening plays a significant role in human health and religion. But the identification methods for beef were little reported. In this work, a simple colorimetric method based on denaturation bubble-mediated strand exchange amplification (SEA) was developed for the rapid and sensitive identification of beef. The whole strategy was performed on a portable metal bath and the distinguishable color between positive and negative controls was observed directly by the naked eyes. The feasibility using crude extraction samples by a heating treatment in PBS for 2 min was evaluated in duck spiked by beef. The result demonstrated that the developed method could identify as low as 1% (w/w) beef/duck within 50 min. Meanwhile, the results showed the method had a good repeatability and specificity. Therefore, this assay allows for the rapid, sensitive, specific detection of beef, and can be recommended as an effective, promising strategy for on-site meat identification.

Palatability of beef chuck, loin, and round muscles from three USDA quality grades.

The objective of this study was to determine the palatability of various beef cuts from 3 USDA quality grades. Five different beef subprimals from USDA Prime, Choice, and Select (n = 10/quality grade) carcasses were utilized for the study, including: strip loins, inside rounds, bottom rounds, shoulder clods, and chuck rolls. Subprimals were fabricated into 9 retail cuts, which contained the following beef muscles: longissimus lumborum (LL); longissimus thoracis, complexus, and spinalis dorsi (LCS); infraspinatus (IF); serratus ventralis (SV); triceps brachii (TB); teres major (TM); adductor (AD); semimembranosus (SM); and biceps femoris (BF). The pH and percentage of fat, moisture, protein, and collagen was determined for each muscle on a raw basis. Additionally, cooked steak measurements included Warner-Bratzler shear force (WBSF) and slice shear force (SSF). Consumer and trained sensory panelists evaluated palatability traits of each cut and quality grade combination. A quality grade × muscle interaction was determined for trained panelists assessment of overall tenderness (P = 0.03), SSF (P = 0.02), proximate composition (P < 0.01), and pH (P < 0.01). In all objective and subjective measurements of tenderness, the LCS was the most tender (P < 0.05), while cuts from the round (BF, AD, and SM) were among the toughest and least juicy (P < 0.05). Conversely, consumers and trained sensory panelists identified the LCS, IF, and SV to be juicier (P < 0.05) than all others. The TB, TM, and LL were perceived by consumers most often as being everyday quality. The LCS was found by consumers to be the most acceptable (P < 0.05) across all attributes, with the SM being the least (P < 0.05) acceptable muscle. For each muscle, fat percentage was the greatest (P < 0.05) in Prime cuts. Slice shear force determined Prime IF, LL, and SV to be more tender (P < 0.05) than Choice and Select. No SSF differences (P > 0.05) were found among quality grades for the AD, BF, and SM. The WBSF values decreased (P < 0.05) across all muscles, as quality grade increased (Prime < Choice < Select). The results of this study indicate that muscles from the chuck may be utilized to provide consumers with a positive eating experience. Meanwhile, muscles from the round are likely to provide consumers with a lower quality eating experience.

Impact of elevated aging temperatures on retail display, tenderness, and consumer acceptability of beef.

Palatability, color, and aroma of steaks derived from subprimals aged for 14 d at conventional temperatures (0.0 to 1.1 °C) versus those aged for 7 d at conventional temperatures followed by 7 d at elevated temperatures (3.3 to 4.4 °C) were evaluated before and after 5-d retail display. Subprimals from the elevated temperature aging treatment had stronger (P < 0.05) sweet and sour aromas, and the top sirloin had stronger (P < 0.05) bloody/serumy scores. After the 5-day retail display, aroma (sour, bloody/serumy) and discoloration of T-bone/Porterhouse steaks were most impacted compared to other steaks. Elevated temperature during the last 7 d of aging did not significantly improve consumer panelists' palatability scores, and no differences (P = 0.66) were seen in WBS force between aging treatments. Using higher storage temperatures to age beef does not warrant the risk associated with impacting color and odor characteristics that could negatively influence consumer acceptance of retail beef.

Evaluation of palatability and muscle composition of novel value-added beef cuts.

The aim of this study was to evaluate the muscle profile of novel added-value beef cuts including the caudal tip of the M. infraspinatus (Bonanza Cut; TIP) and M. subscapularis (SUB) and two traditional sirloin steak cuts, M. gluteus medius (top sirloin; GLM) and M. rectus femoris (sirloin tip; REC). Samples were subjected to Warner-Braztler Shear Force (WBSF), sensory, cooking loss, and proximate analysis. The muscle TIP had superior values of subjective tenderness, juiciness, and slight off-flavor intensity when compared to all other muscles. The TIP and SUB were similar in WBSF. Cooking loss and moisture values of raw samples were lowest for TIP. Results suggest that TIP can provide enhanced eating experience for consumers and improved marketability for the meat industry.

Evaluation of the thermal property of bovine intramuscular adipose tissue using differential scanning calorimetry.

The thermal property of bovine intramuscular adipose tissue (IAT) was evaluated using differential scanning calorimetry (DSC) and compared with the melting point temperature (MP) of the fat extract of IAT, which was measured using the slip point method. The beef samples were classified according to the beef marbling score (BMS). Beef with a high BMS contained less protein than that with middle or low BMS. Beef with a high BMS contained significantly more fat than that with a low BMS (P < 0.05). The endothermic point temperature (EP) of IAT, measured by DSC, was significantly higher than the MP of IAT fat (P < 0.05). The EP showed no significant difference among the three marbling grade groups. Although the MP was correlated with the monounsaturated fatty acids (MUFA) content of IAT (R2  = 0.505), there was no correlation between the EP and the MUFA (R2  = 0.040). However, the EP of IAT treated with collagenase was relatively highly correlated with the MP (R2  = 0.655). Thus, these results suggested that DSC analysis would give us the practical thermal information regarding the melt-in the-mouth of beef such as the gelatinization of collagen, along with the melting of fat in IAT.

Classification of organic beef freshness using VNIR hyperspectral imaging.

Consumer trust in the food industry is heavily reliant upon accurate labelling of meat products. As such, methods, which can verify whether meat is correctly labelled are of great value to producers, retailers, and consumers. This paper illustrates two approaches to classify between, fresh and frozen thawed, and in a novel manner matured and matured frozen-thawed, as well as fresh and matured beef using the 500-1010nm waveband, captured using hyperspectral imaging, and CIELAB measurements. The results show successful classification based upon CIELAB between 1) fresh and frozen-thawed (CCR=0.93), and 2) fresh and matured (CCR=0.92). With successful classification between matured and matured frozen-thawed beef using the entire spectral range (CCR=1.00). The performance of reduced spectral models is also investigated. Overall it was found that CIELAB co-ordinates can be used for successful classification for all comparisons except between matured and matured frozen-thawed. Biochemical and physical changes of the meat are thoroughly discussed for each condition.

Genetic Factors Affecting Pork Quality: Halothane and Rendement Napole Genes.

The most common pork quality problems are pale, soft, and exudative (PSE) and acid pork (AP). PSE is associated with the expression of recessive halothane (Hal) allele Haln. Recessive Hal pigs (Halnn) have defective Ca2+ release channels (CRC) or Ryanodine Receptors (RYR1) within the sarcoplasmic reticulum that allow uncontrolled release of Ca2+ in response to stress. Abnormal lactic acid metabolism caused by stress prior to slaughter leads to the sudden drop in postmortem muscle pH producing the PSE pork. Conversely, AP is caused by the dominant RN- allele of the Rendement Napole gene. RN- pigs have high glycolytic potential that causes the lower ultimate pHu due to excessive lactic acid production postmortem. Poor water holding capacity of muscle cells in PSE and AP causes excessive drip loss leading to low cooking and processing yields. The conventional methods to evaluate Hal and RN genotypes are less effective compared to the more accurate gene marker tests. Selection against the Haln and RN- alleles by genomic selection can potentially reduce the frequencies of the defective genes with high accuracy in less time. As more quantitative trait loci (QTL) are identified, pig breeders are able to select traits more effectively to increase efficiency of pig production and enhance pork quality.