Agriculture and Food Science Book series aims to bring together leading academic scientists, researchers and research scholars to publish their experiences and research results on all aspects of Agriculture and Food Science. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Agriculture and Food Science. High quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of Agriculture and Food Science are cordially invited for publication. Authors are solicited to contribute to the book series by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to 1. Textile Engineering 2. Agronomy 3. Soil Science 4. Microbiology 5. Phsiology 6. Ecology 7. Epidemology 8. Genetics & Plant Breeding 9. Plant Pathology 10. Entomology 11. Agricultural Biotechnology 12. Environmental Sciences 13. Agricultural Engineering 14. Food Science 15. Waste Management 16. Animal Husbandry and Dairying 17. Agricultural Statistics 18. Food Storage and Preservation 19. Food Technology and Processing 20. Agricultural Sustainability 21. Irrigation 22. Root Morphology Sensing 23. Yield-Monitoring 24. Industrial Crops and Products Engineering 25. Artificial Intelligence in Agriculture 26. Poultry Science 27. Forestry 28. Horticulture 29. Fisheries Science 30. Agriculture Equipments & Smart Technologies 31. Veternary Sciences 32. Contract & Integrated Farming 33. Sericulture

This book provides an overview of the innovations in crop phenotyping using emerging technologies, i.e., high-throughput crop phenotyping technology, including its concept, importance, breakthrough and applications in different crops and environments. Emerging technologies in sensing, machine vision and high-performance computing are changing the world beyond our imagination. They are also becoming the most powerful driver of the innovation in agriculture technology, including crop breeding, genetics and management. It includes the state of the art of technologies in high-throughput phenotyping, including advanced sensors, automation systems, ground-based or aerial robotic systems. It also discusses the emerging technologies of big data processing and analytics, such as advanced machine learning and deep learning technologies based on high-performance computing infrastructure. The applications cover different organ levels (root, shoot and seed) of different crops (grains, soybean, maize, potato) at different growth environments (open field and controlled environments). With the contribution of more than 20 world-leading researchers in high-throughput crop phenotyping, the authors hope this book provides readers the needed information to understand the concept, gain the insides and create the innovation of high-throughput phenotyping technology.

Plant Breeding and Cultivar Development features an optimal balance between classical and modern tools and techniques related to plant breeding. Written for a global audience and based on the extensive international experience of the authors, the book features pertinent examples from major and minor world crops. Advanced data analytics (machine learning), phenomics and artificial intelligence are explored in the book's 28 chapters that cover classical and modern plant breeding. By presenting these advancements in specific detail, private and public sector breeding programs will learn about new, effective and efficient implementation. The insights are clear enough that non-plant breeding majoring students will find it useful to learn about the subject, while advanced level students and researchers and practitioners will find practical examples that help them implement their work. - Bridges the gap between conventional breeding practices and state-of-the-art technologies - Provides real-world case studies of a wide range of plant breeding techniques and practices - Combines insights from genetics, genomics, breeding science, statistics, computer science and engineering for crop improvement and cultivar development

Identification of desirable genotypes with traits of interest is discernible for making genetic improvement of crop plants. In this direction, screening of a large number of germplasm for desirable traits and transfer of identified traits into agronomic backgrounds through recombination breeding is the common breeding approach. Although visual screening is easier for qualitative traits, its use is not much effective for quantitative traits and also for those, which are difficult to score visually. Therefore, it is imperative to phenotype the germplasm accessions and breeding materials precisely using high throughput phenomics tools for challenging and complex traits under natural, controlled and harsh environmental conditions. Realizing the importance of phenotyping data towards identification and utilization of a germplasm as donors, global scientific community has exerted increased focus on advancing phenomics in crop plants leading to development of a number of techniques and methodologies for screening of agronomic, physiological, and biochemical traits. These technologies have now become much advanced and entered the era of digital science. This book provides exhaustive information on various aspects related to phenotyping of crop plants and offers a most comprehensive reference on the developments made in traditional and high throughput phenotyping of agricultural crops.

Access to food with enough calories and nutrients is a fundamental right of every human. The global population has exceeded 7.8 billion and is expected to pass 10 billion by 2055. Such rapid population increase presents a great challenge for food supply. More grain production is needed to provide basic calories for humans. Thus, it is crucial to produce 60-110% more food to fill the gap between food production and the demand of future generations. Meanwhile food nutritional values are of increasing interest to accommodate industrialized modern lives. The instability of food production caused by global climate change presents another great challenge. The global warming rate has become more rapid in recent decades, with more frequent extreme climate change including higher temperatures, drought, and floods. Our world faces various unprecedented scenarios such as rising temperatures, which causes melting glaciers and the resulting various biotic and abiotic stresses, ultimately leading to food scarcity. In these circumstances it is of utmost importance to examine the genetic basis and extensive utilization of germplasm to develop “climate resilient cultivars” through the application of plant breeding and biotechnological tools. Future crops must adapt to these new and unpredictable environments. Crop varieties resistant to biotic and abiotic stresses are also needed as plant disease, insects, drought, high- and low-temperature stresses are expected to be impacted by climate change. Thus, we need a food production system that can simultaneously satisfy societal demands and long-term development. Since the Green Revolution in the 1960s, farming has been heavily dependent on high input of nitrogen and pesticides. This leads to environmental pollution which is not sustainable in the long run. Therefore, a new breeding scheme is urgently needed to enable sustainable agriculture; including new strategies to develop varieties and crops that have high yield potential, high yield stability, and superior grain quality and nutrition while also using less consumption of water, fertilizer, and chemicals in light of environmental protection. While we face these challenges, we also have great opportunities, especially with flourishing developments in omics technologies. High-quality reference genomes are becoming available for a larger number of species, with some species having more than one reference genome. The genome-wide re-sequencing of diverse varieties enables the identification of core- and pan-genomes. An integration of omics data will enable a rapid and high-throughput identification of many genes simultaneously for a relevant trait. This will change our current research paradigm fundamentally from single gene analysis to pathway or network analysis. This will also expand our understanding of crop domestication and improvement. In addition, with the knowledge gained from omics data, in combination with new technologies like targeted gene editing, we can breed new varieties and crops for sustainable agriculture.

PlantOmics: The Omics of Plant Science provides a comprehensive account of the latest trends and developments of omics technologies or approaches and their applications in plant science. Thirty chapters written by 90 experts from 15 countries are included in this state-of-the-art book. Each chapter describes one topic/omics such as: omics in model plants, spectroscopy for plants, next generation sequencing, functional genomics, cyto-metagenomics, epigenomics, miRNAomics, proteomics, metabolomics, glycomics, lipidomics, secretomics, phenomics, cytomics, physiomics, signalomics, thiolomics, organelle omics, micro morphomics, microbiomics, cryobionomics, nanotechnology, pharmacogenomics, and computational systems biology for plants. It provides up to date information, technologies, and their applications that can be adopted and applied easily for deeper understanding plant biology and therefore will be helpful in developing the strategy for generating cost-effective superior plants for various purposes. In the last chapter, the editors have proposed several new areas in plant omics that may be explored in order to develop an integrated meta-omics strategy to ensure the world and earth’s health and related issues. This book will be a valuable resource to students and researchers in the field of cutting-edge plant omics.

Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size