A guide to the role microbes play in the enhanced production and productivity of agriculture to feed our growing population Phytomicrobiome Interactions and Sustainable Agriculture offers an essential guide to the importance of 'Phytomicrobiome' and explores its various components. The authors - noted experts on the topic - explore the key benefits of plant development such as nutrient availability, amelioration of stress and defense to plant disease. Throughout the book, the authors introduce and classify the corresponding Phytomicrobiome components and then present a detailed discussion related to its effect on plant development: controlling factors of this biome, its behaviour under the prevailing climate change condition and beneficial effects. The book covers the newly emerging technical concept of Phytomicrobiome engineering, which is an advanced concept to sustain agricultural productivity in recent climatic scenario. The text is filled with comprehensive, cutting edge data, making it possible to access this ever-growing wealth of information. This important book: Offers a one-stop resource on phytomicrobiome concepts Provides a better understanding of the topic and how it can be employed for understanding plant development Contains a guide to sustaining agriculture using phytomicrobiome engineering Presents information that can lead to enhanced production and productivity to feed our growing population Written for students, researchers and policy makers of plant biology, Phytomicrobiome Interactions and Sustainable Agriculture offers a clear understanding of the importance of microbes in overall plant growth and development.

Advances in Agronomy, Volume 170, the latest release in this leading reference on agronomy, contains a variety of updates and highlights new advances in the field. Each chapter is written by an international board of authors.

The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm.