Roheet Bhatnagar - The Digital Agricultural Revolution: Innovations and Challenges in Agriculture through Technology Disruptions

Scrivener Publishing

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Publishers at Scrivener

Martin Scrivener ()

Phillip Carmical ()

Edited by

Roheet Bhatnagar

Nitin Kumar Tripathi

Nitu Bhatnagar

and

Chandan Kumar Panda

This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA

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Library of Congress Cataloging-in-Publication Data

ISBN 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

10 9 8 7 6 5 4 3 2 1

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.

• 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.
• 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.
• discusses the use of intelligent irrigation systems, which have recently gained importance in terms of efficient cultivation of plants and the correct use of Earths 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.
• 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.
• 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 Colombias PO producers and aims to help fill this research gap.
• 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.
• 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).