Big Data technologies have the potential to revolutionize the agriculture sector, in particular food safety and quality practices. This book is designed to provide a foundational understanding of various applications of Big Data in Food Safety. Big Data requires the use of sophisticated approaches for cleaning, processing and extracting useful information to improve decision-making. The contributed volume reviews some of these approaches and algorithms in the context of real-world food safety studies. Food safety and quality related data are being generated in large volumes and from a variety of sources such as farms, processors, retailers, government organizations, and other industries. The editors have included examples of how big data can be used in the fields of bacteriology, virology and mycology to improve food safety. Additional chapters detail how the big data sources are aggregated and used in food safety and quality areas such as food spoilage and quality deterioration along the supply chain, food supply chain traceability, as well as policy and regulations. The volume also contains solutions to address standardization, data interoperability, and other data governance and data related technical challenges. Furthermore, this volume discusses how the application of machine-learning has successfully improved the speed and/or accuracy of many processes in the food supply chain, and also discusses some of the inherent challenges. Included in this volume as well is a practical example of the digital transformation that happened in Dubai, with a particular emphasis on how data is enabling better decision-making in food safety. To complete this volume, researchers discuss how although big data is and will continue to be a major disruptor in the area of food safety, it also raises some important questions with regards to issues such as security/privacy, data control and data governance, all of which must be carefully considered by governments and law makers.
Farber / Dara / Ronholm
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Zielgruppe
Professional/practitioner
Weitere Infos & Material
Machine Learning Application in Food Safety, Production, and Quality.- Foodborne Bacterial Pathogen Big Data – Genomic Analysis.- Foodborne Viral Pathogen Big Data - Genomic Analysis.- The Use of Big Data in the Field of Food Mycology and Mycotoxins.- Big data and its role in mitigating food spoilage and quality deterioration along the supply chain.- "Algorithms to Localize Food Contamination Events in Blockchain-based Trusted Food Supply Chains".- The need for Data Standardization in the Food Supply Chain.- Big Data Digital Transformation in Food Safety - A Dubai Experience.- The Role of Policy and Regulations in The Adoption of Big Data Technologies in Food Safety and Quality.- index.
Dr. Farber is currently the Director of an international consulting firm, which does food safety consulting with various organizations and countries. In addition, he is a senior advisor for Index Biosystems, a Canadian biotechnology company working in the area of food traceability and authenticity. Dr. Farber is also currently an Adjunct Professor and member of the graduate faculty in the Department of Food Science at the University of Guelph, in Guelph, Ontario.
Dr. Rozita Dara is the Principal Investigator of Data Management and Privacy Governance research program at the University of Guelph. Her research interest includes data analytics and data governance with a focus on digital agriculture. She current research projects include food safety, verification, and traceability including data standardization and interoperability and digital agri-food platforms.
Dr. Ronholm is an Assistant Professor in agricultural microbiology in theFaculty of Agricultural and Environmental Sciences at McGill University. She is a William Dawson Scholar. Her research focuses on defining the composition of healthy microbiomes in livestock species and devising strategies to optimize the livestock microbiome to resist bacterial infections.
