{"title":"The contribution of digital and sensing technologies and big data towards sustainable food supply and value chains","authors":"Daniel Cozzolino","doi":"10.1039/D4FB00317A","DOIUrl":null,"url":null,"abstract":"<p >Modern digital and sensing technologies enable agile and modern food supply and value chains. These technologies contributed to the development of analytical tools to assess food composition, food safety and security (<em>e.g.</em> authenticity, contamination, fraud, and provenance). The utilization of digital and sensing technologies determines that a large amount of data is generated during the analysis of food ingredients and products. In this context, big data is defined as the rapid collection of complex data in large quantities during the analysis of foods using sensors (<em>e.g.</em> electronic noses and infrared spectroscopy). Therefore, to implement an application, the data must be analysed and interpreted using different data analytics, statistics and machine learning tools. This paper presents the definition of big data, as well as examples of the utilization of digital and sensing technologies combined with data analytics to develop applications targeting food safety and security in the food supply and value chains.</p>","PeriodicalId":101198,"journal":{"name":"Sustainable Food Technology","volume":" 1","pages":" 181-187"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2025/fb/d4fb00317a?page=search","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Food Technology","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/fb/d4fb00317a","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Modern digital and sensing technologies enable agile and modern food supply and value chains. These technologies contributed to the development of analytical tools to assess food composition, food safety and security (e.g. authenticity, contamination, fraud, and provenance). The utilization of digital and sensing technologies determines that a large amount of data is generated during the analysis of food ingredients and products. In this context, big data is defined as the rapid collection of complex data in large quantities during the analysis of foods using sensors (e.g. electronic noses and infrared spectroscopy). Therefore, to implement an application, the data must be analysed and interpreted using different data analytics, statistics and machine learning tools. This paper presents the definition of big data, as well as examples of the utilization of digital and sensing technologies combined with data analytics to develop applications targeting food safety and security in the food supply and value chains.