No, the title of this column does not contain a typo. Under the right circumstances, most of which are unpredictable, Salmonella can give you a real body slam.
Margins in the food industry have always been thin. This is because retailers and other customers are continuously pushing food manufacturers and suppliers to lower costs.
For years, experts and analysts have predicted a future in which artificial intelligence (AI) and machine learning would revolutionize the industry. By all indications, the future is here.
As COVID-19 cases continue to rise in the United States, the meat industry increasingly faces the potential of pandemic-related economic and legal threats.
The U.S. Department of Agriculture’s Food Safety and Inspection Service (FSIS) recently announced plans to plans to significantly expand its routine verification testing for Shiga toxin-producing Escherichia coli (STECs), which includes the six non-O157 strains O26, O45, O103, O111, O121 and O145.
As most of you know, as a food industry lawyer, I have represented the food industry for over 20 years. During the course of that time, I have closely tracked evolving USDA policy, the strengthening of FSIS inspection and surveillance programs, the continuing parade of food product recalls, and the nearly monthly emergence of new foodborne illness outbreaks.
There remains a great deal of uncertainty in the world right now. That uncertainty extends to all aspects of our lives, including our businesses. Setting aside the personal toll taken by the spread of the novel coronavirus and resultant COVID-19 pandemic, businesses are struggling because of disruptions caused by mandatory closures, travel bans, quarantines and worker shortages.
With the Coronavirus in the news, now seems to be a good time to talk about disease defense and prevention. Coronaviruses are a family of zoonotic viruses (meaning transmitted between animals and humans) that can cause respiratory illness in humans.
The future is an unpredictable place. As such, we generally prefer to leave predictions to others. We would be reluctant to break our no-prediction rule even in the most stable times, when little in the way of change is expected.