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Modernizing pork's grading system

Tuesday, October 29, 2019

Industry stakeholders aim to improve pork classification tools, which should increase the sector's market competitiveness.

by Kate Ayers

While pork remains the third-most popular meat (behind chicken and beef) for Canadians, global "pork consumption is stagnating in established markets at a time when world meat consumption is increasing.

We are failing to get our share of the increased market," says Grant Walling, director at JSR Genetics in the United Kingdom and senior genetic scientist and chair of the Topigs Norsvin Meat Group.

Topigs Norsvin established a global meat group to develop solutions to the challenges that slaughterhouses, processors, packers and retailers face in the pork sector, the company's website says.

Many stakeholders point to the sector's outdated grading system, which largely focuses on carcass yield and lean meat yield, as the cause of this lag. The system lacks quality criteria.

"Currently, no official pork quality classification system is available in Canada. Commercial packers use different approaches to meet clients' demands in terms of quality classification," says Dr. Manuel Juárez, a livestock phenomics scientist with Agriculture and Agri-Food Canada (AAFC) in Lacombe, Alta.

These approaches are "mostly based on subjective sorting of primals for high-end domestic and international markets," he says. Primals are the whole cuts, including loins, ribs or hams, into which processors divide the carcasses of food animals, the Merriam-Webster dictionary says.

Pork packers commonly use "subjective standards and train staff on foreign quality control practices. An optimal classification system should be able to guarantee a minimum level of quality, with a high degree of accuracy."

Bill Wymenga, a pork producer from Chatham-Kent, Ont. and former Canadian Pork Council director, believes quality measurement tools would benefit both producers and consumers.

These tools "would put measurables in place so that producers could have better feedback, which would help the industry by providing more information to genetics suppliers," he says. Such changes would help the swine sector provide higher-value products to consumers, Wymenga adds.

And industry stakeholders are hard at work on these projects.

Better Pork spoke with a producer, scientists and industry leaders to gain insights into what tools and methods of classification could come down the pipeline and how these developments could enhance Canada's pork sector.

Grading system limitations

Canada's pork carcass classification system is based on data from the 1992 National Pork Carcass Cutout project.

AAFC conducted this project to determine the average meat yield for carcasses and cuts, Canada Pork International's "Meat Yield" webpage says. In 1995, officials updated the equation that processing plants use to calculate the percentage of lean yield.

The pork classification system has seven hog grade classes, including ridgling, sow, stag and boar. These classes are subdivided into 12 grades of hog carcasses, says "Grading Regulations for Meat," an article published by the B.C. Cook Articulation Committee. Sows, for example, may fit into one of seven grades, depending on their back-fat levels and muscling.

Pork Grading System
    AAFC Lacombe Research and Development Centre photo

At federally inspected plants, workers use electronic probes to grade hogs and determine producer payments. Staff insert the probe between the third and fourth ribs on the left side of the carcass, the article says.

A sensor light at the end of the probe measures muscle and fat depths. Packers then use an equation to generate an estimate of the percentage of lean meat and assign a yield classification.

However, over the span of 25 years, the sector has improved pig genetics and evolved its processing practices, leading to significant changes in carcass composition. So, the sector could benefit from updates to develop accurate classification systems based on meat quality traits.

Some stakeholders argue, for example, that an "individual assessment point does not give an accurate depiction of the entire carcass," says Walling.

New classification tools should "assess the carcass from a much broader range of measures."

Color Code classification
    AAFC Lacombe Research and Development Centre photo

Currently, packing plant staff use colour cards to differentiate pork based on the amount of white colouring or marbling, says Jeng-Hung Liu, a research assistant at North Dakota State University.

Liu is working on computer vision system (CVS) technology that packers might be able to add to their operation lines within the next few years to identify meat quality.

Using colour cards as a method of "classification is very subjective, and the repeatability is low. You can have different results due to changes in personnel," Liu adds.

"Fatigue and work environment can also affect grading" and increase the cases of human error.

Juárez agrees.

"Most of the current classification systems for pork-quality attributes lack accuracy and repeatability, are highly subjective, slow and time consuming, require manpower and often require extensive training."

Meaty comparisons

In the beef sector, personnel trained by the Canadian Beef Grading Agency (CBGA) assign cattle carcasses one of 13 grades.

The labels range from Prime to E.

When grading a beef carcass, trained staff consider the animal's maturity, sex, conformation (muscling), fat (colour, texture and cover) and meat (colour, texture and marbling), the Beef Cattle Research Council's "Carcass Grading" webpage says. Evaluators further assess grade A meats to determine the intramuscular fat content (marbling). Graders then label cuts with such grades as Canada A, AA, AAA or Prime to indicate quality.

To date, the pork sector does not have a scoring system for quality that retailers use at the consumer level. One possible reason: the sector selects animals for production efficiency and focuses less on improving meat quality, Liu says.

Unlike in the beef sector, only limited measures of meat quality traits exist in the pork sector. These measures are often necessary to comply with specific export market requirements. Though staff classify pork products for different global markets, cuts are not differentiated by official nomenclature in retail stores. So, consumers may not get consistent products with every pork purchase.

This situation may explain the reason why pork is failing to grow with increased meat consumption, Walling says.

Consumers want pork that is flavourful, tender and succulent, he says.

Ontario Pork Label

"Multiple studies have shown that pork colour and firmness, followed by flavour, juiciness and marbling are the most important attributes affecting a pork buyer's purchasing decision," Juárez adds.

"If we include quality attributes for all primals, additional traits – such as primal composition and fat softness – must be considered when packing plant personnel try to meet the needs of all potential buyers.

"Developing new classification tools would help to increase domestic and international client confidence and willingness to pay, differentiate pork qualities from our main competitors and provide an enhanced national platform for further brand development," he says.

Wymenga agrees.

"If the marketplace wants a higher-quality product," packers must have a way to incentivize producers to meet the demands, he says. "We need a system to make that process work."

New classification tools

Researchers and industry stakeholders are stepping up to the challenge to develop an improved classification system.

In June 2018, the pork sector welcomed a federal investment to address priorities. The Government of Canada will invest up to $12.7 million in Swine Innovation Porc (SIP) through the Canadian Agricultural Partnership, an AAFC release says. SIP will also contribute up to $5.8 million to this Swine Research and Development Cluster.

As part of this work, researchers are studying the best methods and tools for the classification of pork based on quality attributes, the release says.

One such tool is CVS, Liu says. These systems have three main components:

  • Industrial cameras are more tolerant of cold, hot or humid conditions than digital cameras. Users can clean industrial cameras and employ coding to do more than just take pictures. For example, these cameras can connect to Wi-Fi, store data or crop images.
  • Dome light ensures even and proper lighting, which is crucial with a CVS, to detect colour differences between muscle and lean tissue, for example.
  • computer automatically analyzes and grades pork. CVSs are best at detecting marbling in pork loins. However, loins often have white connective tissue running down the middle of the cut. So, readings may not be accurate if workers have not trimmed off all the connective tissue, Liu says.

Researchers are also exploring the use of hyperspectral imaging to grade pork. This technology "grabs visible wavelengths of light and turns them into a picture," Liu says.

"Hyperspectral imaging grabs both visible and invisible wavelengths of light. The advantage of a hyperspectral imaging system versus a CVS is that it covers a larger scale of wavelengths."

While hyperspectral imaging can assess meat below a loin's surface and provide detailed information about meat characteristics, the computer needs a lot of time to scan and compile those readings, Liu says.

And the technology's "application in the industry is a challenge because its analyses are much deeper than CVS. So, you must have someone who can analyze and interpret the data."

Other potential tools for grading include commercial ultrasound and MRI (magnetic resonance imaging) technologies, says "Objective Methods for Pork Quality Evaluation," an article published by the Canadian Centre for Swine Improvement.

In addition to automating colour recognition technologies, packers should examine and classify separate primals instead of using a single point measure to classify whole carcasses, some stakeholders say.

This approach could be an effective way to grade pork and ensure product quality, as customers "use each of those primals very differently," Walling says.

And the sector may soon have new technology in its reach.

Teams at "Agriculture and Agri-Food Canada, the Canadian Centre for Swine Improvement, the Centre de développement du porc du Québec and McGill University, for example, are collaborating with industry partners to come up with systems that could be implemented by commercial packers within the next two to five years," Juárez says.

"These systems include both instruments currently available in the market as well as prototypes and new approaches with the potential to be fully developed in the short term.

"Other institutions in Canada, such as the University of Guelph, are working on projects related to tools linked to quality attributes in pork. Some commercial packers are also partnering with private companies to develop proprietary solutions to address specific quality issues."

Path to implementation

Overall, new tools or technologies that could improve the pork industry's classification system must focus on ease of "implementation and what the factories want," says Liu.

Pork Cutting Room
    AAFC Lacombe Research and Development Centre photo

Companies "want tools to be accurate, automated and easy to use. Tools also have to be robust enough so that workers don't need to worry about them."

Juárez agrees.

"To be implemented in commercial plants, these classification systems and tools need to integrate within the workflow and be able to operate at line speed," he says.

"Automated systems, or those systems where the influence of the operator is minimized, would have greater chances of being adopted by commercial plants."

The complexity of the global pork market and diversity in processors' and consumers' demands present challenges to the people who introduce a new system.

Pork Cutting Room
    AAFC Lacombe Research and Development Centre photo

"The pork market is not homogeneous – different sectors and different countries are looking for different things," says Arnold Drung, president of Conestoga Meat Packers in Breslau, Ont. This vertically integrated pork-processing plant works with family farms across Ontario, the company's website says.

"This (market) situation makes a single classification system difficult," Drung says.

"New tools will only benefit the industry if they provide a means to better meet the needs of the Canadian pork industry's customers. There is no one-size-fits-all method of classification," he adds.

Improving Canada's pork label

Advanced Canadian pork classification systems could allow producers to see better carcass attributes of animals they raise and guarantee that customers and consumers have access to consistent pork products.

Pork Cutting Room
    AAFC Lacombe Research and Development Centre photo

New "technologies could help processors get a better value for their end products as they could adjust customer and consumer product specifications," says Jorge Correa, vice-president of market access and technical affairs at the Canadian Meat Council.

"With this more sophisticated information, producers could improve carcasses according to customer demands," he says.

Juárez agrees.

"By combining different approaches and technologies with expertise in meat physiology and biochemistry," packers can adapt new tools "to provide information that can be used to classify pork based on specific quality traits," he says.

Introducing a quality element to pork classification and marketing could improve Canada's position in the global marketplace.

"Pork quality consistency is critical for national and international buyers. With Canadian suppliers ranked at the top of buyers' satisfaction survey lists, a new quality-guaranteed system would put Canadian pork in a more advantageous position to compete in international markets," says Juárez.

"Moreover, with increasing market segmentation, a classification system based on quality would create efficiencies and new opportunities for Canadian companies. The development of rapid, objective and reliable methods for classifying pork quality will allow players at different points of the value chain to make decisions and enhance efficiency by selecting practices conducive to greater product consistency and increase the percentage of high-quality cuts."

The development and implementation of new tools for pork quality assessment and classification in processing plants could help producers achieve new premiums.

And consistent quality could prompt global consumers to go hog wild for Canadian pork. BP

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