Project Summary

Review of Literature to Understand the Knowledge Gaps in Dark-Cutting Beef Research

Principle Investigator(s):
Anna Scott, Keayla Harr, Morgan Pfeiffer, Gretchen Mafi, Ranjith Ramanathan
Institution(s):
Department of Animal and Food Science, Oklahoma State University, Stillwater, OK
Completion Date:
September 2024
While the full article for this executive summary is currently under peer review, these initial findings are being made available on BeefResearch.org to enable the industry to act on the research, inform the scientific community of ongoing work, and help prevent duplication of research efforts. Once peer review is complete, a link to the published article will be added to this summary. 
Key Findings

  • Dark-cutting beef is a widely recognized problem for the global beef industry and is estimated to cost the U.S. beef industry over $180 million.
  • Studies have focused on the post-harvest aspect of identifying methodology to improve color and analyzing the altered postmortem biochemistry.
  • There is a lack of research incorporating live animal data and understanding of animal management effects on dark-cutting beef.
  • Genomic studies, large feedlot and packer data sets, and improvements in the reporting of basic color and carcass characteristics related to dark-cutting beef are all areas in need of further research.

background

The beef industry incurs considerable economic losses when the color of beef deviates from the consumer-accepted bright cherry-red color. One major deviation from consumer-accepted color is dark-cutting beef. In the U.S., the 2021 National Beef Quality Audit reported the frequency of dark cutters to be 1.7% in the fed cattle population; however, many plants within the industry can experience rates as high as 7-10% per week in certain months. Additionally, global rates of dark-cutting remain high in countries such as Australia, Mexico, and Brazil. It is estimated that dark-cutting beef costs the U.S. beef industry over $180 million annually in economic losses due to discounted carcasses. Little is still known about the root cause of dark-cutting beef, even though it is a widely recognized problem for the global beef industry and has been a popular area of study for product quality research. Over 10 different reviews have addressed dark-cutting beef and have investigated both live animal and post-harvest factors that impact dark-cutting beef. 

Although reviews and research have helped to understand dark-cutting beef after harvest, limited progress has been made in predicting dark-cutters. The methods for classifying dark-cutting beef vary widely between researchers and grading systems in different countries. In some countries, such as the U.S., visual color is assessed; other countries rely solely on the measured pH. There is a critical need to identify knowledge gaps and provide guidelines to include details in future peer-reviewed manuscripts over dark-cutting beef. Therefore, the objective of this study was to conduct a scoping review and meta-analysis of the literature related to dark-cutting beef to evaluate both ante- and post-mortem factors that predispose to the occurrence of dark-cutting beef. 

methodology

A systematic evaluation of all literature and published reports was conducted using multiple scientific search engines. All article citations were downloaded, and information deemed critical for analysis was screened by researchers to be put into a spreadsheet to organize all data systematically. Studies used in the evaluation were included in the analysis if they were related to beef cattle, utilized dark-cutting beef in the analysis, and included all relevant methodologies related to the study. Additionally, a meta-analysis was conducted to analyze several meat quality measurements as well as the frequency at which factors have been reported on dark-cutting beef. Summary statistics for pH, objective color, and carcass data were generated. The frequency of reported factors related to dark-cutting was based on the methodology used and reported in articles. A list of methodologies used was made from every paper included in the analysis, transformed into a single list, and classified according to a list of factors set by the research team to more accurately assess the type of parameters reported. Finally, the available literature was summarized into a review to detail the parameters that have been reported and provide future insight and direction for further scientific study.

findings

While much progress has been made in identifying some of the predisposing risk factors of dark-cutting beef, there is still much progress to be made in the management and identification of cattle that may be susceptible. Numerous studies have focused on the post-harvest aspect of identifying methodology to improve color and analyzing the altered postmortem biochemistry. Yet, there is a gap in the research incorporating live animal data and understanding animal management with post-harvest meat quality traits. The meta-analysis reported cattle production and management factors in 27.5% of articles, while pH and objective color were reported in 72.5% and 47.1%, respectively. Moreover, needs within the research include incorporating genomic studies, large feedlot and packer data sets, and improvements in reporting basic color and carcass characteristics related to dark-cutting beef. To solve this global problem, continued research will need to investigate factors from conception to harvest that may play a role in the occurrence of dark-cutting beef.

industry Implications

Dark-cutting beef continues to remain one of the largest challenges for the global beef industry, especially in the face of product quality and economic sustainability. The aim of this review was to provide the scientific body, funding agencies, and commodity groups a glimpse into areas that require further study to reduce dark-cutting beef occurrences. Specifically, future studies need to use large data sets that encompass data from conception to harvest and lifecycle assessments detailing production factors and technology used. 

ARMS#120525-20