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 , Vivekanand Vivekanand , Nidhi Pareek and Ramesh Chandra Dubey

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.

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Publicly Available

Frontmatter
I

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Dedication
V
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Preface
VII
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Contents
IX

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

Publishing information

Pages and Images/Illustrations in book

eBook published on:

November 7, 2025

eBook ISBN:

9783111548777

Hardcover published on:

November 7, 2025

Hardcover ISBN:

9783111548272

Pages and Images/Illustrations in book

Front matter:

10

Main content:

386

Illustrations:

43

Coloured Illustrations:

28

Tables:

34

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._x000D_

Audience(s) for this book

Researchers and students in microbiology.

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Manufacturer information:
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

Frontmatter

Dedication

Preface

Contents

1 Understanding artificial intelligence: an introduction, history, and foundations

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

3 Cellular image classification and identification of genetic variations using artificial intelligence

4 Artificial intelligence in bacterial staining and cell counting

5 Use of artificial intelligence in the prediction of microbial species

6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions

7 AI in food production and processing: applications and challenges

8 Artificial intelligence in microbial food safety

9 AI in plant growth promotion and plant disease management

10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology

11 Artificial intelligence in diagnostics

12 Artificial intelligence in bacterial culture plate images

13 Prediction of antimicrobial activity using artificial intelligence

14 Artificial intelligence and MALDI-TOF MS

15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare

16 Reimagining perfusion bioreactors with artificial intelligence

Index

Bibliographic data