Walmart Foundation tackles food safety in China

Jul 11 2018

 The University of Arkansas has received a $2.3m grant from the Walmart Foundation to fund projects involving the poultry industry in China.

 

Work will include collecting foodborne pathogens and antibiotic samples in poultry products, providing a risk assessment model for universities, organizations and companies worldwide to improve food safety and supply chains and creation of a “farm to table” risk assessment strategy.

 

The university is working with the Walmart Food Safety Collaboration Center in Beijing.

 

Preventing foodborne illness in China

 

The purpose of the center is to fund research focused on analyzing the causes and prevention of foodborne illness in the Chinese supply chain.

 

Joseph E. Steinmetz, chancellor, said it was an excellent opportunity for the university to share its scientific expertise with the world.

 

“We are honored to be partners in this vitally important project and for the opportunity to reduce the instances of foodborne illness among the Chinese people.”

 

China is the second largest producer of poultry meat and eggs and 70% of foodborne bacterial infections in humans are caused by Salmonella.

 

The university will work with three regional poultry companies to improve in-field rapid detection technology and risk assessment models, three universities, one research institute and one food test and inspection lab and three poultry companies.

 

Walmart recently partnered with IBM and Tsinghua University to improve the way food is tracked, transported and sold to consumers across China.

 

 

 

The parties said they will use blockchain technology to generate transparency and efficiency in supply chain record-keeping.

 

MIT reveals collaboration

 

Meanwhile, the Massachusetts Institute of Technology (MIT) will also collaborate with the Walmart Foundation in China.

 

The MIT Sloan School of Management and the MIT Center for Biomedical Innovation will develop predictive risk models to proactively manage risks related to contamination in supply chains.

 

The group, partially funded by the MIT Abdul Latif Jameel World Water and Food Security Lab, will collaborate with Tsinghua University and other academic and industry partners.

 

“China is a major global producer and consumer of food in the world, but it is affected by serious food adulteration incidents that have had major adverse outcomes in China and in the world,” said MIT Sloan’s Retsef Levi, the J. Spencer Standish (1945) professor of management.

 

“Our work could have a longstanding positive impact on food products that are critical to China and to the worldwide global food system.”

 

The project’s focus is on safety risks in core primary supply chains in the country, particularly economically motivated adulteration. Upstream parts of these chains are known to be highly distributed with little visibility, said MIT.

 

The team will create systems to predict, monitor and mitigate risks including supply chain predictive analytics tools with real-time monitoring of socioeconomic and environmental risk drivers and robust and rapid testing capabilities for use in the field.

 

“Food supply chains are often under economic pressure because of a range of factors, including weather effects, epidemics like the avian flu, competitive pressure, and pricing dynamics,” said Levi.

 

“These pressures could create situations in which firms and individuals could benefit financially from adulterating food ingredients and products, risking the health of consumers.

 

“The overall message is that food supply chain structures and dynamics matter and can be used to predict adulteration problems.”

 

Stacy Springs, a co-principal investigator and program director/research scientist at MIT CBI, said: “Our team uses an iterative process of applying technical and manufacturing expertise to inform the supply chain analysis, developing testing capabilities that both help secure the food system and inform where there are vulnerabilities that can be addressed with predictive analytical tools.”

 

 

 

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