Metabolomic comparison of meat quality and metabolites of geese breast muscle at different ages

Wang, Y.; Li, Wanqing; Zhang, Chi; Li, Fushi; Yang, Haiming; Wang, Zhiyue

doi:10.1016/j.fochx.2023.100775

Cited by 8 publications

(4 citation statements)

References 41 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Glycine is the main structural unit of connective tissue and can bind with collagen protein to enhance the tenderness of meat [32]. Threonine is an important component of myofibrillar protein and collagen protein, which contributes to the increase in tenderness and flavor [33]. The amino acid content in group X was significantly lower, which may be the reason for the poor tenderness of buffalo meat.…”

Section: Discussionmentioning

confidence: 99%

Integrated Analysis of Transcriptome and Metabolome Profiles in the Longissimus Dorsi Muscle of Buffalo and Cattle

Wu,

Qiu,

Jiao

et al. 2023

CIMB

View full text Add to dashboard Cite

Buffalo meat is gaining popularity for its nutritional properties, such as its low fat and cholesterol content. However, it is often unsatisfactory to consumers due to its dark color and low tenderness. There is currently limited research on the regulatory mechanisms of buffalo meat quality. Xinglong buffalo are raised in the tropical Hainan region and are undergoing genetic improvement from draught to meat production. For the first time, we evaluated the meat quality traits of Xinglong buffalo using the longissimus dorsi muscle and compared them to Hainan cattle. Furthermore, we utilized a multi-omics approach combining transcriptomics and metabolomics to explore the underlying molecular mechanism regulating meat quality traits. We found that the Xinglong buffalo had significantly higher meat color redness but lower amino acid content and higher shear force compared to Hainan cattle. Differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) were identified, with them being significantly enriched in nicotinic acid and nicotinamide metabolic and glycine, serine, and threonine metabolic pathways. The correlation analysis revealed that those genes and metabolites (such as: GAMT, GCSH, PNP, L-aspartic acid, NADP+, and glutathione) are significantly associated with meat color, tenderness, and amino acid content, indicating their potential as candidate genes and biological indicators associated with meat quality. This study contributes to the breed genetic improvement and enhancement of buffalo meat quality.

show abstract

Section: Discussionmentioning

confidence: 99%

Integrated Analysis of Transcriptome and Metabolome Profiles in the Longissimus Dorsi Muscle of Buffalo and Cattle

Wu,

Qiu,

Jiao

et al. 2023

CIMB

View full text Add to dashboard Cite

show abstract

“…These cryotubes were stored in liquid nitrogen and then sent for analysis to Qingdao Sci-tech Quality Inspection Co., Ltd. The analysis included the determination of the content of 17 hydrolyzed amino acids, 16 fatty acids, 8 mineral elements, and cholesterol in the breast muscle samples of each experimental group ( Wang et al, 2023 ).…”

Section: Methodsmentioning

confidence: 99%

Comparison of growth performance, meat quality, and blood biochemical indexes of Yangzhou goose under different feeding patterns

Zhang,

Qi,

Fan

et al. 2024

Poultry Science

View full text Add to dashboard Cite

“…A critical aspect of goose meat quality is the protein denaturation process, which is a complex phenomenon involving dynamic processes at the molecular level that largely determine the final structure and characteristics of meat products [8,9]. This is a key process in shaping the unique characteristics of goose meat, affecting its cohesion, juiciness, and durability [10,11]. Understanding the correlation between thermal process parameters and protein denaturation in goose meat can provide valuable insights into optimizing these parameters to achieve the desired balance between meat durability and preserving its taste, consistency, and nutritional value [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Innovative Implementation of Computational Fluid Dynamics in Proteins Denaturation Process Prediction in Goose Breast Meat and Heat Treatment Processes Optimization

Szpicer,

Bińkowska,

Stelmasiak

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

This study aimed to calculate the optimal thermal processing parameters for goose meat using CFD simulation. CFD provides a precise determination of heat treatment conditions by predicting protein denaturation and mass loss, leading to higher quality and improved sensory experience and, thus, acceptance of products. Accurate calculation of these conditions reduces energy losses and enhances process efficiency in the food industry. This study focused on the prediction of protein denaturation and cooking loss in goose breast meat during roasting. Specific CFD techniques, including conjugate heat transfer and phase change models, were utilized to ensure accuracy in protein denaturation prediction. These models accounted for variations in meat composition, such as fat and water content across different samples, which improved the accuracy of the predictions. Optimal conditions were determined using a mathematical model. These conditions were 164.65 °C, 63.58% humidity, and a fan rotation of 16.59 rpm for 2000 s. The myosin, collagen, and actin denaturation levels, as well as cooking loss, closely matched predicted values. The findings show that CFD is a valuable method for evaluating protein denaturation and cooking loss in goose breast meat, potentially improving product quality and consistency in gastronomy and the meat industry. This innovative optimization method enhances food production efficiency and elevates sensory characteristics, physicochemical properties, and nutritional value, contributing to consumer satisfaction and market competitiveness. The model proposed in this paper can be adapted to predict denaturation in other types of meat or food products with necessary modifications, offering broad applicability. Potential limitations of using CFD in protein denaturation prediction in complex food matrices include the need for detailed compositional data and computational resources, which can be addressed in future research.

show abstract

Metabolomic comparison of meat quality and metabolites of geese breast muscle at different ages

Cited by 8 publications

References 41 publications

Integrated Analysis of Transcriptome and Metabolome Profiles in the Longissimus Dorsi Muscle of Buffalo and Cattle

Integrated Analysis of Transcriptome and Metabolome Profiles in the Longissimus Dorsi Muscle of Buffalo and Cattle

Comparison of growth performance, meat quality, and blood biochemical indexes of Yangzhou goose under different feeding patterns

Innovative Implementation of Computational Fluid Dynamics in Proteins Denaturation Process Prediction in Goose Breast Meat and Heat Treatment Processes Optimization

Contact Info

Product

Resources

About