Can data science drive advances in food safety? Panellists in the “Data Revolution: Is Food Safety Sitting on the Sidelines?” session tackled big questions about big data in a wide-ranging IFT SHIFT20 conference conversation.
The Creme-RIFM Model is the most comprehensive of its kind. We built the model on real-life data from more than 41,000 people on how consumers use fragranced products (how often and where on the body) on a daily basis.
One of the less obvious effects of the COVID-19 pandemic has been its impact on the traditional food supply chain. From initial lockdowns that brought about shortages to later normalisation of the pandemic measures that drove a significant shift from in-person shopping to digital, online channels.
SAFFI (SAfe Food For Infants in the EU and China) targets food for EU’s 15 million and China’s 45 million children under the age of three. Project aims at developing an integrated approach to enhance the identification, assessment, detection and mitigation of safety risks raised by microbial and chemical hazards all along EU and China infant food chains.
Properly harnessing available data requires innovative and validated solutions that circumvent hype and buzzwords and instead focus on using advanced data access, analytics and predictive modelling harmoniously. Such solutions can then be used to underpin important safety and risk assessment decisions made by the industry and governments.
COVID-19 has accelerated digital transformation of the food production chain across the globe.
As the COVID-19 pandemic continues to put a strain on our lives, people are forced to change everyday habits to remain healthy. One positive outcome is that healthy living is now top priority, and people are actively looking to find ways to boost their immune system through exercise and diet.
Before your inbox gets filled with heart emojis and other love related imagery ahead of Valentine’s Day, now is the perfect time to consider what you’re doing to keep your real heart healthy.
Creme Global Head of Data Modelling and Statistics, John O’Brien, offered his insights for the discussion paper ‘AI & Predictive Analytics for Food Risk Prevention’, published as part of the EU-funded digital transformation initiative called Big Data Grapes.