Big Data Applications in Food Safety and Quality

Pollard S., Namazi H. & Khaksar R.

Abstract

Big data and data analytics has evolved to become an indispensable facet across all industries, enabling new advances in management strategies, product development, and data insight that has never before been possible. Traditionally, scientists have approached scientific questions by formulating a hypothetical model and carefully designing experiments to accept or reject the proposed model. The more modern statistical method, fueled by the big data revolution, is to refrain from relying on hypothetical models and allow the data itself to identify pertinent variables and patterns that shape the observed outcome. This evolution of big data can be applied to food safety and food quality in ways that will reshape the way consumers and producers think about and make decisions regarding food purchases and production practices. With the rise of consumer demand for food transparency, consumers are more concerned than ever with where their food comes from and expect companies to provide clear, accurate and useful food-related information for the products they purchase. Big data can enable greater transparency throughout the farm to fork continuum by driving more informed safety and quality decisions, such as shelf-life prediction, improved sanitation and supply chain decisions, and predictive risk assessment among many other applications.

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