Autorentext
Dr. Vivek Sharma is currently an Assistant Professor at the University Centre for Research and Development at Chandigarh University, Mohali (PB). He has more than 12 years of research experience exploring molecular attributes of Trichoderma. His research also involves examining the molecular aspects of microbes beneficial to plants such as Streptomyces and Bacillus. He has published several research papers in international journals, serves as an Academic Editor for PLOS ONE, a review editor for Frontiers in Bioengineering and Biotechnology, an associate editor of Chemical and Biological Technologies in Agriculture, and is also a member of the editorial board of Current Proteomics. He is also a recognized reviewer for the Journal of Advanced Research, Applied Microbiology and Biotechnology, Environmental Research, the Journal of Proteomics, BMC Genomics, BMC Plant Biology, AMB Express, Molecular Biotechnology, MDPI Pathogens, Folia Microbiology, Physiological and Molecular Plant Pathology and Archives of Microbiology. Dr. Richa Salwan is currently an Assistant Professor of microbiology at the College of Horticulture and Forestry (Dr. YS Parmar University of Horticulture and Forestry), Neri, Hamirpur, Himachal Pradesh, India. Dr. Salwan's research interests and contributions are on the diversity of psychrotrophic bacteria from the Western Himalayas and their utilization for industrial applications. She has also worked on the exploration of extremophiles for industrially relevant enzymes and plant beneficial microbes for agricultural benefits. She has published two books and numerous research papers in several international journals. Dr. Salwan serves as an Academic Editor for PLOS ONE and is also a recognized reviewer for several journals including MDPI Genes, MDPI Diversity, MDPI Foods, BMC Microbiology, Journal of Plant Growth Regulation, and Microbial Ecology.Rhydum Sharma has a PhD and MTech in Biotechnology. She is a young researcher who has published seven research articles and three book chapters. She is an active reviewer for various international journals. She has been awarded the second best oral presentation award by Frontiers in Nutrition. Her major research interests involve exploring the genetic diversity of underexplored crops for value additions and microbes for sustainable agriculture.

Klappentext
From Conventional to Artificial Intelligence-Based Agriculture explores the evolving landscape of agriculture as it transitions from traditional practices to advanced, AI-driven solutions. With AI and machine learning revolutionizing industries worldwide, their impact on agriculture is becoming increasingly significant. These technologies are not only aiding in climate modeling but also opening new possibilities for precision farming, enabling more accurate crop health diagnostics, efficient resource management, and timely intervention strategies.

By integrating conventional agricultural knowledge with cutting-edge AI tools, farmers and researchers can better assess soil conditions, predict optimal planting windows, monitor nutrient dynamics, and understand market trends with greater precision. This convergence of tradition and technology supports more resilient, productive, and sustainable agricultural systems, paving the way for a smarter and more food-secure future.

Inhalt

1. Scope of conventional knowledge and deep learning approaches for the identification of plant diseases
2. Plant disease diagnosis and forecasting in the era of artificial intelligence, machine learning, and deep learning
3. AI-powered precision horticulture: Integrating machine learning and unmanned vehicles for crop management
4. Exploring conventional methods and deep learning approaches for plant disease identification
5. Machine learning and artificial intelligence for germplasm phenotyping in plant breeding
6. Genome language models for plant genome mining in accelerating breeding strategies
7. Use of artificial intelligence in hydroponic vegetable production
8. Bibliometric analysis of artificial intelligence and machine learning: A technological revolution in agriculture
9. Soil health monitoring using artificial intelligence and the Internet of Things for sustainable agriculture
10. Generative AI and the potential of robotics in agriculture
11. Artificial intelligence in food science and nutrition
12. Artificial intelligence and machine learning in agriculture: Transforming economics and farm viability in the agricultural sector