978-1-119-82333-9
Cover image: Pixabay.Com
Cover design by Russell Richardson
Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines
Printed in the USA
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Preface
The practice of agriculture began in ancient civilizations and farmers have always contributed to nation-building by growing produce to feed an ever-growing population. Moreover, agriculture is the foundation of an economy, providing livelihoods for millions of farmers. Therefore, there is a need for synergy between application of modern scientific innovation in the area of artificial intelligence (AI) and agriculture, while taking into consideration the major challenge brought on by climate change, viz., rising temperatures, erratic rainfall patterns, emergence of new crop pests, droughts, floods, etc. The intent of this edited volume is to report high-quality research (practical theory, including prototype and conceptualization of ideas, frameworks, real-world applications, policies, standards, psychological concerns, case studies and critical surveys) on recent advances toward the realization of a digital agricultural revolution resulting from the convergence of different disruptive technologies.
This book highlights the latest achievements in the field of modern agriculture, which is highly driven by technology and aimed at sustainable agriculture. In it is a collection of original contributions by researchers/ academicians from across the globe regarding state-of-the-art solutions using newer methods to enhance and improve crops for smart agriculture. These solutions are arrived at by various means, as indicated in the topics covered in the twenty chapters described below.
– Chapter 1 presents an overview of how AI helps to increase socio-economic and environmental sustainability in the Indian agricultural sector. It also highlights the AI practices incorporated by farmers in India with small and medium-sized agricultural lands.
– Chapter 2 describes the high efficacy of using remote sensing images and neural network models to generate accurate crop yield maps and offers proof of the significant superiority of neural network models over conventional methods.
– Chapter 3 discusses the use of intelligent irrigation systems, which have recently gained importance in terms of efficient cultivation of plants and the correct use of Earth’s water. The use of machine learning and control methods in plant growth modeling and irrigation systems is also explained. The chapter ends with a discussion of current problems along with possible future implementation of new approaches to solve them.
– Chapter 4 provides insight into the opportunities presented by the use of robots in agriculture, known as agribots, and focuses on the advancements in different types of agribots in terms of sensing, mobility, path planning, and manipulation. It also talks about the status and progress of robots in Indian agriculture, concentrating on Indian-based robotic startups and case studies involving the use of robots in harvesting crops along with the challenges faced when deploying robots in the field.
– Chapter 5 delves into the Colombian palm oil (PO) industry. The contribution of this study is twofold: First, it provides a more comprehensive review of the PO industry technology literature based on Scopus and Clarivate Analytics, using the reporting checklist of preferred reporting items for systematic reviews and meta-analyses (PRISMA). Second, as far as the authors know, this is one of the first studies to address the technological solutions applied by Colombia’s PO producers and aims to help fill this research gap.
– Chapter 6 presents a case on smart agriculture and discusses intelligent agriculture in a greenhouse-based multi-agent system (MAS), which is made up of several agents located in an environment that interact according to some defined relationships. In this work, each part of the greenhouse environment is represented by one or more agent, with each agent coordinating with other agents to achieve set goals. In addition, it discusses the society of agents in which two types of agents can be found: 1) reactive agents characterized by simple behavior, whose mission it is to perform tasks that do not require intelligent reasoning, and 2) cognitive or intelligent agents, which are tasked with performing more complex missions and require reasoning to make good decisions.
– Chapter 7 is a study on the use of automatic and intelligent methods in the management of irrigation of agricultural land. Among these technologies are artificial intelligence and the Internet of Things (IoT), which are used to optimize the management of irrigation water in agricultural lands. The elements of the agricultural system and its environment are presented by things in direct contact with each other by relying on information and communication technology (ICT).
– Chapter 8 discusses how modern agriculture has become knowledge intensive and how improved access to and availability of information and communication technologies (ICTs), especially cell phones, computers, radio, internet, and social media, has created many more opportunities for multi-format information gathering, processing, storage, retrieval, management and sharing.
– Chapter 9 presents an overview of nanotechnology and nanosensors in forestry and agriculture, including its use in forest health protection, forest management, wood and paper processing, and chemotaxonomy. The nanotechnology sector has best applied this technology in precision farming by developing nanobionic plants by inserting nanosensors into living plants that can be utilized to communicate as infrared devices and for sensing objects in the plant’s environment. Therefore, the nanobionics approach has opened a new vista into plant nanomaterial research. Some nanobionics approaches for agriculture and forestry development are also briefly discussed.
– Chapter 10 is all about mathematical models of the water resources management process of canals in the middle reaches of the Chirchik River, which were developed using simplified differential equations of Saint Venant in partial derivatives to model the necessary conditions for optimizing water distribution. An algorithm for solving the problem of optimal water resources management of distributed irrigation canals was also developed.
– Chapter 11 discusses various principles of reengineering of agricultural resources and throws light on open problems, challenges, and future trends.
– Chapter 12 shows how the supply chain management method is used for planning maintenance strategy, storing products, moving material through the organization and its distribution channel, which leads directly to maximum profits through cost-saving fulfilment of orders. A simple supply chain acts as a bridge between demand and supply. Startups are bringing a new shape to the agri-supply chain by using new-age technologies like AI, machine learning, IoT and blockchain management, that procure directly from farm gates and supply to retailers.
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