Maize Agriculture,

Edition 1 Remote Sensing, Artificial Intelligence, and Advance Phenotyping

Editors: Edited by Sheikh Mansoor, PhD, Nusret Zencirci, Chao Bian, Faheem Shahzad Baloch, PhD, Gönül Cömertpay and Yong Suk Chung, PhD

Publication Date: 04 Jan 2027

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As the global population approaches 9 billion, the pressure on agriculture to produce sufficient food will escalate, leading to significant challenges in sustainable food production. Maize Agriculture addresses the urgent need to develop improved maize cultivars grown under advanced technological conditions to combat these future food shortages and nutritional deficiencies. Furthermore, climate change, with its impacts on temperature, precipitation, carbon dioxide levels, and the frequency and severity of extreme weather events, is likely to significantly affect soil water availability, carbon storage, and crop yields. This book digs into these pressing issues, offering an in-depth exploration review of the latest technologies in maize research. This comprehensive resource covers a wide range of topics essential for modern maize agriculture. Beginning with an overview of global maize production, the book progresses through chapters on advanced phenotyping platforms for sustainable maize production. Following that, it explores the integration of genomics and phenomics for maize breeding and the application of AI and machine learning models for genomic trait prediction. Further chapters discuss the use of GIS and global databases for agricultural planning, remote sensing for biotic and abiotic stress monitoring, and advanced AI-based approaches for disease management. Each chapter is carefully structured to provide in-depth insights and practical applications, ensuring a thorough understanding of the subject matter. Maize Agriculture is an invaluable resource for upper-level undergraduate students and researcher across various life science and agriculture disciplines, including agriculture, horticulture, botany, biochemistry, and biotechnology. Additionally, maize breeders, agronomists, and agricultural professionals engaged in maize research will find the actionable strategies in this book invaluable. By integrating digital tools with traditional farming practices, this book ensures that readers are prepared for the future of maize agriculture.

Key Features

Provides a comprehensive overview of modern maize agriculture for food security
Functions as an essential resource on advanced technologies in maize research
Equips upper-level undergraduate students across various life sciences and agriculture disciplines with practical knowledge
Addresses the gap in accessible, up-to-date resources on the integration of digital technologies in maize agriculture
Explores the integration of genomics and phenomics for transforming maize breeding

About the author

Edited by Sheikh Mansoor, PhD, Postdoctoral Researcher, Phenomics Laboratory, Department of Plant Resources and Environment, Jeju National University, South Korea; Nusret Zencirci, Çukurova University's Faculty of Agriculture, Department of Field Crops; Chao Bian, Principal Investigator, Frontier Science Center of Molecular Breeding and the Department of Plant Genetics and Breeding at China Agricultural University, China; Faheem Shahzad Baloch, PhD, Professor, Plant Genetics and Breeding, Mersin University, Turkey; Gönül Cömertpay, Associate Professor of Maize Breeding and Genetics at the Eastern Mediterranean Agricultural Research Institute in Adana, Turkey and Yong Suk Chung, PhD, Associate Professor, Department of Plant Resources and Environment, Jeju National University, South Korea

1. Global maize production and cultivation for food safety: challenges and opportunities
2. Transformation in maize cultivation: An overview of research and development
3. Smart farming technologies: Advanced phenotyping platforms for sustainable maize production
4. Conventional to advanced high throughput phenotyping in maize breeding
5. Maize genetic resources and machine learning in big data integration
6. Integration of genomics and phenomics for transforming maize breeding
7. In-silico machine learning models for maize genomic trait prediction
8. GIS, global databases and agricultural planning in maize research
9. Biotic and abiotic stress monitoring in maize using remote sensing
10. Integrating AI and remote sensing technologies for sustainable irrigation and fertilization in maize
11. Enhancing maize resilience to climate change with remote sensing and AI
12. Remote sensing-based framework for monitoring maize crop yield and quality
13. Revolutionizing maize improvement programs with digital tools

Maize Agriculture,

Editors: Edited by Sheikh Mansoor, PhD, Nusret Zencirci, Chao Bian, Faheem Shahzad Baloch, PhD, Gönül Cömertpay and Yong Suk Chung, PhD

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About the author

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