Determination of Point of Sale and Consumption for Hanwoo Beef Based on Quality Grade and Aging Time

Effect of glucose and lysine supplementation on myogenic and adipogenic gene expression in muscle satellite cells isolated from Hanwoo with different genotypes of PLAG1: Implications for cell-based food production

Research on Hanwoo cattle has focused on the pleomorphic adenoma gene (PLAG) family, vital for traits like growth and carcass quality. Single nucleotide polymorphisms (SNPs) within this gene family profoundly impact economic traits. At the cellular level, energy and protein sources, notably glucose and lysine, crucially regulate muscle satellite cell (MSC) growth and differentiation. This study delved into how varied glucose and lysine levels affect gene expression patterns in Hanwoo MSC. MSC from 9 Hanwoo, aged 29-36 months, categorized into 3 PLAG1 genotypes (GG, GC, CC), were treated with six combinations of glucose (5.5 and 25 mM) and lysine (2, 4, and 8 mM). Analysis of myogenic and adipogenic genes linked to meat quality and quantity ensued. The GG genotype displayed superior dressed percentage, yield grade, and marbling score, hinting at genotype-associated carcass characteristic disparities. In cell culture, gene expression generally rose with lysine addition to high glucose in the GG group. Contrarily, significant differences across all treatments in the GC genotype suggested distinct responses. Significant effects of genotype, glucose, and lysine on cell proliferation-related gene expression were noted. Highest mRNA expression for MyoD, MyoG, and FASN occurred in the CC genotype, while Myf5 and Pax7 expression peaked in the GG genotype. Glucose significantly influenced Pax7 and FASN expression, while lysine positively impacted MyoD and MyoG genes. Notable interactions, especially in Genotype × Lysine, influenced MyoD, Myf5, and Pax7 expression, highlighting complex relationships in cell proliferation. Regarding cell differentiation, Pax7 expression was highest in PLAG1 GG type. High glucose prompted wider myotubes, while lower lysine concentrations slightly favored cell differentiation. Correspondingly, MyoG expression decreased with higher lysine levels. This study furnishes insights into lysine and glucose supplementation effects on bovine MSC proliferation and differentiation, considering PLAG1 genotype influence. It offers valuable data for beef production system establishment and optimizing cell-based food production.

Distinguishing aroma profile of highly-marbled beef according to quality grade using electronic nose sensors data and chemometrics approach

Fat deposition in animal muscles differs according to the genetics and muscle anatomical locations. Moreover, different fat to lean muscle ratios (quality grade, QG) might contribute to aroma development in highly marbled beef. Scientific evidence is required to determine whether the abundance of aroma volatiles is positively correlated with the amount of fat in highly marbled beef. Therefore, this study aims to investigate the effect of QG on beef aroma profile using electronic nose data and a chemometric approach. An electronic nose with metal oxide semiconductors was used, and discrimination was performed using multivariate analysis, including principal component analysis and hierarchical clustering. The M. longissimus lumborum (striploin) of QG 1++, 1+, 1, and 2 of Hanwoo steers (n=6), finished under identical feeding systems on similar farms, were used. In contrast to the proportion of monounsaturated fatty acids (MUFAs), the abundance of volatile compounds and the proportion of polyunsaturated fatty acids (PUFAs) decreased as the QG increased. The aroma profile of striploin from carcasses of different QGs was well-discriminated. QG1++ was close to QG1+, while QG1 and QG2 were within a cluster. In conclusion, aroma development in beef is strongly influenced by fat deposition, particularly the fat-to-lean muscle ratio with regard to the proportion of PUFA. As MUFA slows down the oxidation and release of volatile compounds, leaner beef containing a higher proportion of PUFA produces more volatile compounds than beef with a higher amount of intramuscular fat.

Total volatile basic nitrogen and trimethylamine in muscle foods: Potential formation pathways and effects on human health

The use of total volatile basic nitrogen (TVB-N) as a quality parameter for fish is rapidly growing to include other types of meat. Investigations of meat quality have recently focused on TVB-N as an index of freshness, but little is known on the biochemical pathways involved in its generation. Furthermore, TVB-N and methylated amines have been reported to exert deterimental health effects, but the relationship between these compounds and human health has not been critically reviewed. Here, literature on the formative pathways of TVB-N has been reviewed in depth. The association of methylated amines and human health has been critically evaluated. Interventions to mitigate the effects of TVB-N on human health are discussed. TVB-N levels in meat can be influenced by the diet of an animal, which calls for careful consideration when using TVB-N thresholds for regulatory purposes. Bacterial contamination and temperature abuse contribute to significant levels of post-mortem TVB-N increases. Therefore, controlling spoilage factors through a good level of hygiene during processing and preservation techniques may contribute to a substantial reduction of TVB-N. Trimethylamine (TMA) constitutes a significant part of TVB-N. TMA and trimethylamine oxide (TMA-N-O) have been related to the pathogenesis of noncommunicable diseases, including atherosclerosis, cancers, and diabetes. Proposed methods for mitigation of TMA and TMA-N-O accumulation are discussed, which include a reduction in their daily dietary intake, control of internal production pathways by targeting gut microbiota, and inhibition of flavin monooxygenase 3 enzymes. The levels of TMA and TMA-N-O have significant health effects, and this should, therefore, be considered when evaluating meat quality and acceptability. Agreed international values for TVB-N and TMA in meat products are required. The role of feed, gut microbiota, and translocation of methylated amines to muscles in farmed animals requires further investigation.

The association between total volatile basic nitrogen (TVB-N) concentration and other biomarkers of quality and spoilage for vacuum packaged beef

Beef longissimus lumborum muscles (24) were each portioned into 6 steaks, and these were held at ~0.5 °C for up to 14 weeks. Total volatile basic nitrogen (TVB-N) data was compared against other measures of quality and freshness: total viable microbial count (TVC), ultimate pH, drip loss, purge, moisture content, cook loss, shear force, particle size, vitamin E, intramuscular fat content (IMF) and colour parameters. There was an association between TVB-N and colour parameters; and between TVB-N and several parameters for microbial load, tenderness and moisture. IMF and vitamin E were not correlated to TVB-N. TVB-N of 5.1 mg/100 g (95% confidence intervals: 4.6-5.5 mg/100 g) was estimated as equivalent to a TVC of log 7 cfu/g. When beef samples were categorised as either spoilt or fresh using this TVC recommendation, TVB-N was correct in 77.9% of its assignments. Additional investigation is necessary to confirm this result against a larger sample population with a broader range of TVB-N values.

Utilization of Electrical Impedance Spectroscopy and Image Classification for Non-Invasive Early Assessment of Meat Freshness

This study presents a system for assessing the freshness of meat with electrical impedance spectroscopy (EIS) in the frequency range of 125 Hz to 128 kHz combined with an image classifier for non-destructive and low-cost applications. The freshness standard is established by measuring the aerobic plate count (APC), 2-thiobarbituric acid reactive substances (TBARS), and composition analysis (crude fat, crude protein, and moisture) values of the microbiological detection to represent the correlation between EIS and meat freshness. The EIS and images of meat are combined to predict the freshness with the Adaboost classification and gradient boosting regression algorithms. As a result, when the elapsed time of beef storage for 48 h is classified into three classes, the time prediction accuracy is up to 85% compared to prediction accuracy of 56.7% when only images are used without EIS information. Significantly, the relative standard deviation (RSD) of APC and TBARS value predictions with EIS and images datum achieves 0.890 and 0.678, respectively.