Artificial Intelligence in Microbiology: Environmental, Food, Plant and Clinical Microbiology

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Artificial Intelligence in Microbiology

Environmental, Food, Plant and Clinical Microbiology

Edited by: Pankaj Kumar and Vivekanand Vivekanand

Language: English

Published/Copyright: 2026

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About this book

Due to their high predictive and informative potential, machine learning and deep learning have emerged as essential tools to advance microbiome research. This book provides insights and research findings related to AI in microbiology and demonstrates how AI can be applied to solve complex problems, accelerate research, and improve our understanding of microorganisms. It covers AI and machine learning techniques in plant growth and plant protection, in clinical, food and environmental microbiology. AI in microbiology is an interdisciplinary field, and this book will help bridge the gap between computer science, data analytics, and microbiology.

Bridges the gap between computer science, data analytics, and microbiology.
Addresses the challenges of applying AI in microbiology.

Author / Editor information

Pankaj Kumar, HNBGU, Vivekanand, MNIT, Nidhi Pareek, CURAJ, Ramesh Chandra Dubey, GKV, India.

Topics

Frontmatter Publicly Available Download PDF	I
Dedication Requires Authentication Unlicensed Licensed	V
Preface Requires Authentication Unlicensed Licensed	VII
Contents Publicly Available Download PDF	IX
1 Understanding artificial intelligence: an introduction, history, and foundations P Sonawane Requires Authentication Unlicensed Licensed	1
2 Basics of machine learning (ML) and deep learning (DL), secondary data source and training, application and AI tools, challenges, and future perspectives of AI Aditi Praful Thapliyal, Ayushika Mishra and Kumud Pant Requires Authentication Unlicensed Licensed	25
3 Cellular image classification and identification of genetic variations using artificial intelligence Jaya, Rajni Kumari, V. Vivekanand and Nidhi Pareek Requires Authentication Unlicensed Licensed	47
4 Artificial intelligence in bacterial staining and cell counting G Shree Kumari, V Mohanasrinivasan, Lokesh Ravi and D Poornima Requires Authentication Unlicensed Licensed	65
5 Use of artificial intelligence in the prediction of microbial species Manohar Rahiya, Rajni Kumari, V. Vivekanand and Nidhi Pareek Requires Authentication Unlicensed Licensed	79
6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions Vivek Pandya and Kinjal Upadhyay Requires Authentication Unlicensed Licensed	97
7 AI in food production and processing: applications and challenges Vidhi Jain, Nafees Ahmed, Krishnaveer Singh Jhala, Pradeep Kumar and Namita Ashish Singh Requires Authentication Unlicensed Licensed	125
8 Artificial intelligence in microbial food safety Dominic Panaligan, Riann Martin Sarza and Isaac Cornelius Bensley Sy Requires Authentication Unlicensed Licensed	153
9 AI in plant growth promotion and plant disease management Nileema S. Gore, Rutuja Suryavanshi, Sushma Thakur and Priyanka Patil Requires Authentication Unlicensed Licensed	183
10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology Nitish Kumar Singh, Jaikee Kumar Singh, Vivek Chandra Verma, Syed Mohammad Nasar Ata and Raghvendra Dubey Requires Authentication Unlicensed Licensed	207
11 Artificial intelligence in diagnostics A. H. D. Pushpa Latha, S. Padmavathi, B. Varalakshmi and D. Aruna Padma Requires Authentication Unlicensed Licensed	229
12 Artificial intelligence in bacterial culture plate images Pratishtha Jain, M Jeevan Kumar, Lokesh Ravi and Debasish Kar Requires Authentication Unlicensed Licensed	263
13 Prediction of antimicrobial activity using artificial intelligence Nitish Kumar Singh, Jaikee Kumar Singh, Vivek Chandra Verma, Syed Mohammad Nasar Ata and Aprajita Singh Requires Authentication Unlicensed Licensed	281
14 Artificial intelligence and MALDI-TOF MS Vaidya Mayuri, Jategaonkar Vinaya, Harale Geetanjali and Patil Shweta Requires Authentication Unlicensed Licensed	313
15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare Hem Chandra Pant, Himani Sivaraman, Naveen Gaurav, Harsh Vardhan Pant, Hridoyjit Phukon, Pankaj Kumar and R. C. Dubey Requires Authentication Unlicensed Licensed	337
16 Reimagining perfusion bioreactors with artificial intelligence Hardik S. Shah, Kinchit K. Shah and Priti H. Patel Requires Authentication Unlicensed Licensed	357
Index Requires Authentication Unlicensed Licensed	381

Publishing information

Pages and Images/Illustrations in book

eBook published on:

October 20, 2025

eBook ISBN:

9783111548777

Hardcover published on:

October 20, 2025

Hardcover ISBN:

9783111548272

Pages and Images/Illustrations in book

Front matter:

10

Main content:

375

Illustrations:

10

Coloured Illustrations:

30

Tables:

20

https://doi.org/10.1515/9783111548777

eBook ISBN: 9783111548777

Hardcover ISBN: 9783111548272

Keywords for this book

Artificial Intelligence; Machine Learning; Deep Learning; Plant Disease Management; Clinical Microbiology; Whole Genome Sequencing.

Audience(s) for this book

Researchers and students in microbiology.

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Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com

Artificial Intelligence in Microbiology

Overview

About this book

Author / Editor information

Topics

Table of contents

Bibliographic data