Practical Applications of Machine Learning and Artificial Intelligence in the Food Industry

Jaiswal, Amit K. (EDT)/ Kaushik, Abhishek (EDT)/ Jaiswal, Swarna (EDT)

Academic Press Inc（2025/11発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 384 p.
• 言語 ENG
• 商品コード 9780443289262

Full Description

Practical Applications of Machine Learning and Artificial Intelligence in the Food Industry provides a comprehensive overview of the applications of machine learning and artificial intelligence in the food industry. The book covers a wide range of topics including food safety, quality control, sustainability, personalized nutrition, and supply chain optimization. It also discusses various machine-learning techniques and provides examples of successful implementations in the industry.

The book is divided into six sections, the introductory section sets the stage by detailing key machine learning and artificial intelligence concepts, and their relevancy to the food industry. The second section addresses data collection and predictive analysis, featuring chapters on predictive maintenance, yield optimization, and consumer behaviour analytics. The third section focuses on food safety and quality control, detailing how machine learning can be deployed for tasks such as food fraud detection, predictive microbiology, and quality control enhancements. Section four further explores how these technologies can help in food texture, flavour, and shelf-life predictions. The fifth section presents an in-depth exploration of supply chain optimization and traceability, discussing the role of AI and machine learning in areas like real-time food safety monitoring, product authenticity assurance, and big data for food traceability. The final section highlights the application of these technologies in creating personalized nutrition strategies and promoting sustainable agricultural practices. Each section includes real-world examples of successful implementations, reinforcing the practicality of these applications.

Practical Applications of Machine Learning and Artificial Intelligence in the Food Industry serves as an ultimate practical guide for implementing machine learning and artificial intelligence in the food industry and provides readers with valuable insights into emerging technologies in the field.

Contents

Section 1: Introduction
1. Introduction to Artificial Intelligence and Machine Learning in Food Industry

Section 2: Data Collection and Predictive Analysis
2. Data Collection and Management for ML in Food Industry
3. Predictive Maintenance for Food Processing Equipment
4. Yield Optimization in Food Production with Machine Learning
5. Predictive Analytics for Consumer Behaviour

Section 3: Food Safety and Quality Control
6. Improving Quality Control with Machine Learning
7. Machine Learning for Food Safety
8. Machine Learning for Food Fraud Detection
9. Predictive Microbiology using Machine Learning

Section 4: Food Texture, Flavour and Shelf-life Prediction
10. Texture Analysis with Machine Learning
11. Flavour Prediction using Machine Learning
12. Shelf-Life Prediction with Machine Learning

Section 5: Supply Chain Optimization and Traceability
13. Optimizing the Food Supply Chain with Machine Learning
14. IoT for Real-Time Food Safety Monitoring
15. Ensuring Product Authenticity using Machine Learning and AI
16. Big Data and AI for Food Traceability

Section 6: Personalized Nutrition and Sustainability
17. Personalized Nutrition with Machine Learning
18. Sustainable Agriculture through Machine Learning
19. Machine Learning for Allergen Detection in Food
20. Machine Learning for Food Preservation
21. Recipe Generation with Machine Learning