Relation among meat pH, color and tenderness- A review

Meat quality is fundamentally influenced by postmortem biochemical changes, with pH decline playing a central role in determining both visual appeal and eating satisfaction. This review explores the interrelationships among meat pH, color, and tenderness, focusing on how variations in muscle acidification impact these key quality traits. A rapid pH decline at high carcass temperatures can result in pale, soft, exudative (PSE) meat, while an insufficient drop may lead to dark, firm, dry (DFD) meat—both of which are undesirable. Meat color is primarily governed by the chemical state of myoglobin, which is sensitive to pH-induced changes in muscle structure and oxygenation. Tenderness is likewise influenced by pH, as it affects the activity of endogenous proteolytic enzymes like calpains and the structural integrity of muscle fibers. Optimal tenderness and color are generally achieved when the ultimate pH ranges between 5.5 and 5.8. Extremely low or high pH values impair enzyme function and protein integrity, leading to poor textural and visual quality. This paper also highlights recent advancements in molecular biology and omics technologies that offer new insights into predicting and controlling meat quality through pH regulation. Understanding these complex relationships can help the meat industry refine processing techniques and improve consumer satisfaction.

Authors

Publication Details

Journal
Meat Research | ISSN (Online Version) 2790-1971
Published
2025-06-30
DOI
https://doi.org/10.55002/mr.5.3.117
Citations
1
Primary Topic
Meat and Animal Product Quality
Type
article
Field-Weighted Citation Impact
1.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Relation among meat pH, color and tenderness- A review

Nilanjan Das, Afroza Akhter, MA Hashem, PR Sristi et al.
1 citations
Meat Research | ISSN (Online Version) 2790-1971
Meat and Animal Product Quality
1.19
article

Relation among meat pH, color and tenderness- A review

Nilanjan Das, Afroza Akhter, MA Hashem, PR Sristi, NM Kaniya
article en
1 citations

Abstract

Meat quality is fundamentally influenced by postmortem biochemical changes, with pH decline playing a central role in determining both visual appeal and eating satisfaction. This review explores the interrelationships among meat pH, color, and tenderness, focusing on how variations in muscle acidification impact these key quality traits. A rapid pH decline at high carcass temperatures can result in pale, soft, exudative (PSE) meat, while an insufficient drop may lead to dark, firm, dry (DFD) meat—both of which are undesirable. Meat color is primarily governed by the chemical state of myoglobin, which is sensitive to pH-induced changes in muscle structure and oxygenation. Tenderness is likewise influenced by pH, as it affects the activity of endogenous proteolytic enzymes like calpains and the structural integrity of muscle fibers. Optimal tenderness and color are generally achieved when the ultimate pH ranges between 5.5 and 5.8. Extremely low or high pH values impair enzyme function and protein integrity, leading to poor textural and visual quality. This paper also highlights recent advancements in molecular biology and omics technologies that offer new insights into predicting and controlling meat quality through pH regulation. Understanding these complex relationships can help the meat industry refine processing techniques and improve consumer satisfaction.

Meat Research | ISSN (Online Version) 2790-1971Vol. 5(03)
Openalex Percentile: Top 20%
Meat and Animal Product Quality
1.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.