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Head of Institute: Prof. Ido Braslavsky

Administrative manager: Rakefet Kalev

Office Address:
Institute of Biochemistry, Food Science and Nutrition,
Robert H. Smith Faculty of Agriculture, Food and Environment,
The Hebrew University of Jerusalem, 
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Crowdsourcing: A new conceptual view for food safety and quality

Citation:

Soon, J. M. ; Saguy, I. . Crowdsourcing: A New Conceptual View For Food Safety And Quality. Trends in Food Science and Technology 2017, 66, 63-72.

Abstract:

Background Crowdsourcing is a new tool offered mainly over the internet for obtaining ideas, content, funding by seeking contributions from a large group of people and especially from the online community rather than from traditional employees or suppliers. Crowdsourcing is widespread in numerous food applications (e.g., technology, entrepreneurial projects, start-ups funding, innovative product developments). Scope and approach Although the use of crowdsourcing has increased rapidly, there is still much untapped potential in harnessing its vast innovative potential in food quality and safety solutions. This paper aims to review recent utilization of crowdsourcing practices in the food domain. Additionally, to furnish a conceptual view on possible application where crowdsourcing can be harnessed in enhancing food quality, safety and reducing risks. Key findings and conclusions It argues that crowdsourcing initiative is potentially a very useful tool as a part of the big data by utilizing the crowd's data in shelf-life monitoring, inventory control, foodborne illness surveillance, identification of contaminated products and to improve food businesses’ hygiene, enhance food safety, communication and allergen management and minimizing risk. The limitations include the number of reports and data generated may overwhelm the food industry or authority due to lack of internal resources i.e. time and technical expert to process the information. There is also risk of lack of crowd participation and loss of control. Hence, a mechanism to facilitate, evaluate and process the data should be in place. © 2017 Elsevier Ltd

Publisher's Version

Last updated on 12/31/2019