Call for Chapters: Green Chemistry, AI, and Smart Sensing Technologies for Food Adulteration Detection

Editors

Sheng-Lung Peng, National Taipei University of Business, Taiwan
Udit Mamodiya, Poornima University, India
Manju Lata Joshi, Poornima University, India
Shikha Khullar, Poornima University, India

Call for Chapters

Proposals Submission Deadline: June 28, 2026
 Full Chapters Due: September 20, 2026
 Submission Date: September 20, 2026

Introduction

Adulteration of food has become a major issue of international concern and has a serious impact on human health and food safety as well as compliance with regulations. As food supply chains grow increasingly complex and the need for quick, reliable, and sustainable detection methods, traditional methods of analyzing data may be inadequate to meet contemporary requirements. The aim of this proposed edited volume, Food Adulteration detection: Blending green chemistry, AI and Smart Sensing Technologies, is to present a comprehensive and interdisciplinary platform that would incorporate the latest innovations in science and technology to fight food adulteration. The proposed book examines how green chemistry, artificial intelligence (AI), and smart sensing technologies intersect with each other to create effective, environmentally friendly, and intelligent detection systems. It draws attention to novel techniques like biosensors, detection by nanotechnology, spectroscopy, IoT-based sensing devices, and machine learning algorithms to analyze food quality and authenticity in real-time and with high sensitivity. The importance of reducing environmental impact using green analytical methods and improving detection accuracy and scalability using AI-based models is stressed. The proposed edited book will address theoretical basis and practical applications, including algorithmic structures, sensor design, data analysis and case studies of various food products like dairy, oils, spices, cereals, beverages, etc. It covers also regulatory outlooks, standardization issues and new trends in food safety monitoring systems. The proposed book is written with a target group of researchers, academicians, industrial professionals, policymakers and postgraduate students, and thus it serves as a beneficial resource in the process of comprehending and formulating next generation solutions to food adulteration detection. The proposed volume helps fill gaps in the interdisciplinary areas of chemistry, computer science and sensor engineering, contributing to sustainable, intelligent, and scalable food safety systems in accordance with the global health and environmental objectives.

Objective

1. To develop an interdisciplinary framework for food adulteration detection. 2. To explore sustainable and eco-friendly analytical methodologies. 3. To investigate the role of AI and machine learning in intelligent food analysis. 4. To examine emerging smart sensing technologies and innovations. 5. To bridge theory with practical applications and case studies. 6. To address regulatory, standardization, and future research challenges.

Target Audience

The proposed edited book "Green Chemistry, AI, and Smart Sensing Technologies for Food Adulteration Detection" is aimed at a heterogeneous and interdisciplinary target audience. It will be of most benefit to researchers and academicians in disciplines like computer science, food technology, chemistry, environmental science, and electronics engineering, who are engaged in working on food safety, AI applications, and sustainable methods of analysis. Industry professionals and practitioners in food quality assurance, supply chain management, and regulatory compliance will also find the book useful as it provides insights into new technologies in detection and its application in the real-world environment. Postgraduate and doctoral students will find it handy as a source of coursework, research project and thesis building in the new interdisciplinary areas. Moreover, this resource can be used by policy makers, regulatory bodies and standardization agencies to be familiar with technological progress and evidence-based decision making in food safety regulations. Generally, the book serves both academic and practical communities in need of innovative, sustainable, and intelligent solutions to detect food adulteration.

Recommended Topics

1. Fundamentals of Food Adulteration: Types, Sources, and Global Challenges 2. Conventional vs. Advanced Methods for Food Adulteration Detection 3. Principles of Green Chemistry in Food Safety Analysis 4. Sustainable Analytical Techniques for Food Quality Assessment 5. Role of Artificial Intelligence in Food Adulteration Detection 6. Machine Learning Algorithms for Classification of Adulterated Food Products 7. Deep Learning Approaches for Image-Based Food Quality Inspection 8. Smart Sensing Technologies for Real-Time Food Adulteration Detection 9. Biosensors and Nanotechnology for Rapid Food Analysis 10. Spectroscopy-Based Techniques for Detecting Food Adulterants 11. IoT-Enabled Food Monitoring Systems in Supply Chains 12. Integration of AI and Sensor Data for Intelligent Food Safety Systems 13. Big Data Analytics for Food Authenticity and Traceability 14. Detection of Adulteration in Dairy Products: Techniques and Case Studies 15. Adulteration Detection in Edible Oils and Fats Using Smart Technologies 16. AI-Based Detection of Adulteration in Spices and Condiments 17. Food Adulteration in Cereals and Pulses: Challenges and Solutions 18. Detection Techniques for Beverage Adulteration: Tea, Coffee, and Juices 19. Portable and Low-Cost Devices for On-Site Food Adulteration Testing 20. Regulatory Frameworks and Standards for Food Safety and Adulteration Control 21. Ethical, Social, and Environmental Implications of Food Adulteration Detection Technologies 22. Future Trends: Smart, Sustainable, and AI-Driven Food Safety Ecosystems

Submission Procedure

Researchers and practitioners are invited to submit on or before June 28, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by July 12, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by September 20, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Green Chemistry, AI, and Smart Sensing Technologies for Food Adulteration Detection. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

June 28, 2026: Proposal Submission Deadline
July 12, 2026: Notification of Acceptance
September 20, 2026: Full Chapter Submission
November 1, 2026: Review Results Returned
November 29, 2026: Final Acceptance Notification
December 6, 2026: Final Chapter Submission

Inquiries

Sheng-Lung Peng National Taipei University of Business slpeng@ntub.edu.tw Udit Mamodiya Poornima University assoc.dean_research@poornima.edu.in Manju Lata Joshi Poornima University manjulatajoshi1976@gmail.com Shikha Khullar Poornima University shikha.khullar17@gmail.com
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