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              <text>Food quality traceability prototype for restaurants using blockchain and food quality data index</text>
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        <element elementId="49">
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              <text>Blockchain; Food quality index; Food traceability</text>
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              <text>As competition between organizations are evolving into competition between supply chains, to survive and indeed grow, it is necessary to deliver added value to customers. Traceability has emerged as one of the key measures of operational efficiencies within supply chains and ultimately, customer service. Over the years, organizations have deployed number of methods in delivering food traceability. This paper examines major methods of food traceability currently in existence and proposes a restaurant prototype for implementing more reliable food traceability using Blockchain and product identifiers. The prototype captures data from various stakeholders across the food supply chain, segregates it and finally, applies the Food Quality Index (FQI) algorithm to generate an FQI value. The FQI value helps in identifying whether the food is good for consumption on specified parameters. FQI value is generated based on extant standard storage and handling regulations specified by food safety authorities, and checks whether value so derived, is within the permissible range. The prototype helps in grading food quality for human consumption besides strengthening food (product) traceability. This prototype can be customized to address future requirements of traceability triggered through new information emanating from any stakeholder or the node in the supply chain.  2019 Elsevier Ltd</text>
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          <name>Creator</name>
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              <text>George R.V.; Harsh H.O.; Ray P.; Babu A.K.</text>
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              <text>Journal of Cleaner Production, Vol-240</text>
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              <text>Elsevier Ltd</text>
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              <text>2019-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1016/j.jclepro.2019.118021" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.jclepro.2019.118021&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071357214&amp;amp;doi=10.1016%2Fj.jclepro.2019.118021&amp;amp;partnerID=40&amp;amp;md5=efb88a874063ddf72674893d17a457bb" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071357214&amp;amp;doi=10.1016%2fj.jclepro.2019.118021&amp;amp;partnerID=40&amp;amp;md5=efb88a874063ddf72674893d17a457bb&lt;/a&gt;</text>
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          <name>Rights</name>
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              <text>Restricted Access</text>
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              <text>ISSN: 9596526; CODEN: JCROE</text>
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          <name>Format</name>
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              <text>Online</text>
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              <text>English</text>
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              <text>George R.V., Department of Lean Operations &amp;amp; Systems, Institute of Management, Christ (Deemed to be University), Bangalore, 560029, Karnataka, India; Harsh H.O., Department of Lean Operations &amp;amp; Systems, Institute of Management, Christ (Deemed to be University), Bangalore, 560029, Karnataka, India; Ray P., Garden City University &amp;amp; Assistant Professor at Christ (Deemed to be University), Bangalore, 560029, Karnataka, India; Babu A.K., Department of Lean Operations &amp;amp; Systems, Institute of Management, Christ (Deemed to be University), Bangalore, 560029, Karnataka, India</text>
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