國立高雄大學圖資館 |

Language: English

Back

Harnessing big data in food safety

Record Type:	Electronic resources : Monograph/item
Title/Author:	Harnessing big data in food safetyedited by Jeffrey M. Farber, Rozita Dara, Jennifer Ronholm.
other author:	Farber, Jeffrey M.
Published:	Cham :Springer International Publishing :2023.
Description:	vii, 162 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	FoodSafety measures
Online resource:	https://doi.org/10.1007/978-3-031-07179-9
ISBN:	9783031071799$q(electronic bk.)

Harnessing big data in food safety
Harnessing big data in food safety[electronic resource] /edited by Jeffrey M. Farber, Rozita Dara, Jennifer Ronholm. - Cham :Springer International Publishing :2023. - vii, 162 p. :ill. (chiefly color), digital ;24 cm. - Food microbiology and food safety,2629-1029. - Food microbiology and food safety..

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.

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.

ISBN: 9783031071799$q(electronic bk.)

Standard No.: 10.1007/978-3-031-07179-9doiSubjects--Topical Terms:

953250
Food
--Safety measures

LC Class. No.: RA601

Dewey Class. No.: 363.1920285

Harnessing big data in food safety
LDR:03836nmm a2200361 a 4500 001 644593
003 DE-He213
005 20221123005251.0
006 m d
007 cr nn 008maaau
008 231208s2023 sz s 0 eng d
020 $a 9783031071799$q(electronic bk.)
020 $a 9783031071782$q(paper)
024 7 $a 10.1007/978-3-031-07179-9 $2 doi
035 $a 978-3-031-07179-9
040 $a GP $c GP $e rda
041 0 $a eng
050 4 $a RA601
072 7 $a PSG $2 bicssc
072 7 $a TDCT $2 bicssc
072 7 $a TEC012010 $2 bisacsh
072 7 $a PSG $2 thema
072 7 $a TDCT $2 thema
082 0 4 $a 363.1920285 $2 23
090 $a RA601 $b .H289 2023
245 0 0 $a Harnessing big data in food safety $h [electronic resource] / $c edited by Jeffrey M. Farber, Rozita Dara, Jennifer Ronholm.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a vii, 162 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Food microbiology and food safety, $x 2629-1029
505 0 $a 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.
520 $a 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.
650 0 $a Food $x Safety measures $x Technological innovations. $3 953250
650 0 $a Big data. $3 609582
650 1 4 $a Food Microbiology. $3 235295
650 2 4 $a Big Data. $3 760530
650 2 4 $a IT in Business. $3 703717
650 2 4 $a Food Science. $3 274110
700 1 $a Farber, Jeffrey M. $3 953247
700 1 $a Dara, Rozita. $3 953248
700 1 $a Ronholm, Jennifer. $3 953249
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Food microbiology and food safety. $3 682840
856 4 0 $u https://doi.org/10.1007/978-3-031-07179-9
950 $a Chemistry and Materials Science (SpringerNature-11644)