AI, Sensors and Robotics in Plant Phenotyping and Precision Agriculture, Volume II PDF Download

Author: Yongliang Qiao
Publisher: Frontiers Media SA
ISBN: 2832527450
Category : Science
Languages : en
Pages : 266

View

Book Description

Author: Yongliang Qiao
Publisher: Frontiers Media SA
ISBN: 2832509770
Category : Science
Languages : en
Pages : 367

View

Book Description

Author: Andreas Hund
Publisher: Frontiers Media SA
ISBN: 2832545459
Category : Science
Languages : en
Pages : 161

View

Book Description
This Research Topic is part of the High-Throughput Field Phenotyping to Advance Precision Agriculture and Enhance Genetic Gain series. The discipline of “High Throughput Field Phenotyping” (HTFP) has gained momentum in the last decade. HTFP includes a wide range of disciplines such as plant science, agronomy, remote sensing, and genetics; as well as biochemistry, imaging, computation, agricultural engineering, and robotics. High throughput technologies have substantially increased our ability to monitor and quantify field experiments and breeding nurseries at multiple scales. HTFP technology can not only rapidly and cost-effectively replace tedious and subjective ratings in the field, but can also unlock the potential of new, latent phenotypes representing underlying biological function. These advances have also provided the ability to follow crop growth and development across seasons at high and previously inaccessible spatial and temporal resolutions. By combining these data with measurements of all environmental factors affecting plant growth and yield (“Envirotyping”), genotypic-specific reaction norms and phenotypic plasticity may be elucidated.

Author: Huajian Liu
Publisher: Frontiers Media SA
ISBN: 283254293X
Category : Science
Languages : en
Pages : 423

View

Book Description
Plant phenotyping (PP) describes the physiological and biochemical properties of plants affected by both genotypes and environments. It is an emerging research field that is assisting the breeding and cultivation of new crop varieties to be more productive and resilient to challenging environments. Precision agriculture (PA) uses sensing technologies to observe crops and then manage them optimally to ensure that they grow in healthy conditions, have maximum productivity, and have minimal negative effects on the environment. Traditionally, the observation of plant traits heavily relies on human experts which is labor intensive, time-consuming, and subjective. Automatic crop traits measurement in PP and PA are two different fields, but they share the same sensing and data processing technologies in many respects. Recently, driven by computer and sensor technologies, machine vision (MV) and machine learning (ML) have contributed to accurate, high-throughput, and nondestructive plant phenotyping and precision agriculture. However, these technologies are still in their infant stage and there are many challenges and questions related to them that still need to be addressed. The goal of this Research Topic is to provide a platform to share the latest research results on the application of MV and ML for PP and PA. It aims to highlight cutting-edge technologies, bottle-necks, and future research directions for MV and ML in crop breeding, crop cultivation, disease management, weed control, and pest control.

Author: Narendra Khatri
Publisher: CRC Press
ISBN: 1000955532
Category : Technology & Engineering
Languages : en
Pages : 506

View

Book Description
This new book delves into how modern technologies—i.e., global positioning systems (GPS), unmanned aerial vehicles (drones), image processing methods, artificial intelligence, machine learning, and deep learning—are being used to make agriculture more farmer-friendly and more economically profitable. The volume focuses on the use of smart sensors, actuators, and decision support systems to provide intelligent data about crop health and for monitoring for yield prediction, soil quality, nutrition requirement prediction, etc. The authors discuss robotic-based innovations in agriculture, soft computing methodologies for crop forecasting, machine learning techniques to classify and identify plant diseases, deep convolutional neural networks for recognizing nutrient deficiencies, and more.

Author: Utku Kose
Publisher: CRC Press
ISBN: 1000604373
Category : Computers
Languages : en
Pages : 291

View

Book Description
This book was created with the intention of informing an international audience about the latest technological aspects for developing smart agricultural applications. As artificial intelligence (AI) takes the main role in this, the majority of the chapters are associated with the role of AI and data analytics components for better agricultural applications. The first two chapters provide alternative, wide reviews of the use of AI, robotics, and the Internet of Things as effective solutions to agricultural problems. The third chapter looks at the use of blockchain technology in smart agricultural scenarios. In the fourth chapter, a future view is provided of an Internet of Things-oriented sustainable agriculture. Next, the fifth chapter provides a governmental evaluation of advanced farming technologies, and the sixth chapter discusses the role of big data in smart agricultural applications. The role of the blockchain is evaluated in terms of an industrial view under the seventh chapter, and the eighth chapter provides a discussion of data mining and data extraction, which is essential for better further analysis by smart tools. The ninth chapter evaluates the use of machine learning in food processing and preservation, which is a critical issue for dealing with issues concerns regarding insufficient foud sources. The tenth chapter also discusses sustainability, and the eleventh chapter focuses on the problem of plant disease prediction, which is among the critical agricultural issues. Similarly, the twelfth chapter considers the use of deep learning for classifying plant diseases. Finally, the book ends with a look at cyber threats to farming automation in the thirteenth chapter and a case study of India for a better, smart, and sustainable agriculture in the fourteenth chapter. This book presents the most critical research topics of today’s smart agricultural applications and provides a valuable view for both technological knowledge and ability that will be helpful to academicians, scientists, students who are the future of science, and industrial practitioners who collaborate with academia.

Author: Jianfeng Zhou
Publisher: Springer Nature
ISBN: 3030737349
Category : Science
Languages : en
Pages : 249

View

Book Description
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.

Author: Dr Leisa Armstrong
Publisher: Burleigh Dodds Science: Instant Insights
ISBN: 9781801466257
Category :
Languages : en
Pages : 0

View

Book Description
This collection considers the variety of applications of Artificial Intelligence in agriculture, highlighting its use in vineyards to improve precision irrigation, as well as its use in harvest-assist platforms in citrus orchards.

Author: Minzan Li
Publisher: Springer Nature
ISBN: 3030704327
Category : Technology & Engineering
Languages : en
Pages : 331

View

Book Description
Soil and crop sensing is a fundamental component and the first important step in precision agriculture. Unless the level of soil and crop variability is known, appropriate management decisions cannot be made and implemented. In the last few decades, various ground-based sensors have been developed to measure spatial variability in soil properties and nutrients, crop growth and yield, and pest conditions. Remote sensing as an important data collection tool has been increasingly used to map soil and crop growth variability as spatial, spectral and temporal resolutions of image data have improved significantly in recent years. While identifying spatial variability of soil and crop growth within fields is an important first step towards precision management, using that variability to formulate variable rate application plans of farming inputs such as fertilizers and pesticides is another essential step in precision agriculture.The purpose of this book is to present the historical, current and future developments of soil and crop sensing technologies with fundamentals and practical examples. The first chapter gives an overview of soil and crop sensing technologies for precision crop production. The next six chapters provide details on theories, methods, practical applications, as well as challenges and future research needs for all aspects of soil and crop sensing. The last two chapters show how soil and crop sensing technologies can be used for plant phenotyping and precision fertilization. The chapters are written by some of the world’s leading experts who have contributed significantly to the developments of precision agriculture technologies, especially in the area of soil and crop sensing. They use their knowledge, experiences, and successful stories to present informative and up-to-date information on relevant topics. Therefore, this book is an invaluable addition to the literature and can be used as a reference by scientists, engineers, practitioners, and college students for the dissemination and advancement of precision agriculture technologies for practical applications.

Author: Xanthoula Eirini Pantazi
Publisher: Academic Press
ISBN: 0128143924
Category : Business & Economics
Languages : en
Pages : 330

View

Book Description
Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms. Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (IoTs) in agriculture Addresses AI use in weed management, disease detection, yield prediction and crop production Utilizes case studies to provide real-world insights and direction