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Blockchain in Big Data for Agriculture Supply Chain
Studies in Big Data ; 119:257-291, 2023.
Article in English | Scopus | ID: covidwho-2283988
ABSTRACT
Agricultural food supply chain is a complex system starting from the production of food on a farm to the table of the consumer involving multiple stakeholders and a variety of processes. In recent years, the food supply chain has grown rapidly across nations, with customers demanding fresh, exotic foods all year round. The global shutdown due to the COVID pandemic has further complicated the food supply chain which has become prone to various contaminations and adulterations. Adulterated food is highly toxic to human health leading to several health issues, nutritional deficiencies, kidney disorders, and failure of vital organs. The existing systems used in the food supply chain do not provide enough transparency, traceability, food safety, or consumer trust. With today's Big Data integrated supply chains, such technologies are highly ineffective. In order to ensure food safety and consumer satisfaction, this chapter proposes using blockchain as an efficient technology to provide transparency, traceability, and trust in food supply chains. The chapter discusses the significance of smart agriculture and how blockchain might help agricultural supply chains that have Big Data incorporated overcome their difficulties. A thorough description of exclusive applications of blockchain in Big Data integrated food supply chains is provided. The chapter also describes how blockchain is integrated into each stage of the food supply chain management process and explores the challenges in implementing blockchain in Big Data integrated food supply chain systems. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Studies in Big Data Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Studies in Big Data Year: 2023 Document Type: Article