Discrimination study between carcass yield and meat quality by gender in Korean native cattle (Hanwoo)

Modeling of Ethiopian Beef Meat Marbling Score Using Image Processing for Rapid Meat Grading

Meat characterized by a high marbling value is typically anticipated to display enhanced sensory attributes. This study aimed to predict the marbling scores of rib-eye, steaks sourced from the Longissimus dorsi muscle of different cattle types, namely Boran, Senga, and Sheko, by employing digital image processing and machine-learning algorithms. Marbling was analyzed using digital image processing coupled with an extreme gradient boosting (GBoost) machine learning algorithm. Meat texture was assessed using a universal texture analyzer. Sensory characteristics of beef were evaluated through quantitative descriptive analysis with a trained panel of twenty. Using selected image features from digital image processing, the marbling score was predicted with R2 (prediction) = 0.83. Boran cattle had the highest fat content in sirloin and chuck cuts (12.68% and 12.40%, respectively), followed by Senga (11.59% and 11.56%) and Sheko (11.40% and 11.17%). Tenderness scores for sirloin and chuck cuts differed among the three breeds: Boran (7.06 ± 2.75 and 3.81 ± 2.24, respectively), Senga (5.54 ± 1.90 and 5.25 ± 2.47), and Sheko (5.43 ± 2.76 and 6.33 ± 2.28 Nmm). Sheko and Senga had similar sensory attributes. Marbling scores were higher in Boran (4.28 ± 1.43 and 3.68 ± 1.21) and Senga (2.88 ± 0.69 and 2.83 ± 0.98) compared to Sheko (2.73 ± 1.28 and 2.90 ± 1.52). The study achieved a remarkable milestone in developing a digital tool for predicting marbling scores of Ethiopian beef breeds. Furthermore, the relationship between quality attributes and beef marbling score has been verified. After further validation, the output of this research can be utilized in the meat industry and quality control authorities.

Investigation of high correlation with carcass traits of SNPs of the PLCB1, C/EBPα, and TDRKH genes and the combinations of SNPs using the MDR method in the Hanwoo

BACKGROUND

Recently, many researchers focus on the best way to produce high-quality meat, as the trend in food consumption today is to focus on quality. In general, consumers' preferences in beef differ depending on taste and meatiness. Therefore, researchers are interested in how the marbling score affects the flavors of meat or the various factors that make up the meatiness to captivate the consumers' tastes.

OBJECTIVE

This study identifies single nucleotide polymorphisms (SNPs) or gene combinations that affect the carcass traits of Korean cattle (Hanwoo) by using the multifactor dimensionality reduction (MDR) method.

METHODS

We collected the candidate SNPs to identify SNPs related to marbling scores from whole-exome sequencing and bovine SNP genotyping data. Using 96 Hanwoo samples, we performed PCR amplification to investigate the polymorphism status. In addition, we investigated genetic relationships between carcass traits and SNPs using 612 Hanwoo samples. Furthermore, each candidate SNP genotype and the combinations of SNP genotypes were verified to improve the accuracy of genetic relationships using MDR method.

RESULTS

Twenty-four candidate SNPs associated with carcass trait and marbling scores were identified from SNP genotyping and whole-exome sequencing. Among them, three SNP markers (c.459 T > C of the PLCB1 gene, c.271 A > C of the C/EBPα gene, and g.17257 A > G of the TDRKH gene) were showed statistically significant differences between intramuscular fat and genotypes. Especially, two candidate SNPs, including c.459 T > C located in the PLCB1 gene and c.271 A > C located in the C/EBPα gene, could be highly associated with the intramuscular fat of Hanwoo quality grade. In addition, the combination of SNP genotypes is showed higher significant differences with carcass weight, backfat thickness, and longissimus dorsi muscle area.

CONCLUSION

Three SNP genotypes and the combination of SNP genotypes in the PLCB1, C/EBPα, and TDRKH genes may be useful genetic markers for improving beef quality.