Modern Techniques for Agricultural Disease Management and Crop Yield Prediction

Modern Techniques for Agricultural Disease Management and Crop Yield Prediction

N. Pradeep (Bapuji Institute of Engineering and Technology, India), Sandeep Kautish (Guru Kashi University, India), C.R. Nirmala (Bapuji Institute of Engineering and Technology, India), Vishal Goyal (Punjabi University, Patiala, India) and Sonia Abdellatif (Seoul National University, South Korea)
Projected Release Date: August, 2019|Copyright: © 2020 |Pages: 300
ISBN13: 9781522596325|ISBN10: 1522596321|EISBN13: 9781522596349|DOI: 10.4018/978-1-5225-9632-5

Description

Since agriculture is one of the key parameters in assessing the gross domestic product (GDP) of any country, it has become crucial to transition from traditional agricultural practices to smart agriculture. New agricultural technologies provide numerous opportunities to maximize crop yield by recognizing and analyzing diseases and other natural variables that may affect it. Therefore, it is necessary to understand how computer-assisted technologies can best be utilized and adopted in the conversion to smart agriculture.

Modern Techniques for Agricultural Disease Management and Crop Yield Prediction is an essential publication that widens the spectrum of computational methods that can aid in agriculture disease management, weed detection, and crop yield prediction. Featuring coverage on a wide range of topics such as soil and crop sensors, swarm robotics, and weed detection, this book is ideally designed for environmentalists, farmers, botanists, agricultural engineers, computer engineers, scientists, researchers, practitioners, and students seeking current research on technology and techniques for agricultural diseases and predictive trends.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Agricultural Disease Management
  • Agriculture Market Trends
  • Climate-Smart Agriculture
  • Crop Sensors
  • Machine Learning
  • Pattern Recognition
  • Precision Agriculture
  • Predictive Analytics
  • Smart Agriculture
  • Swarm Robotics
  • Weed Detection

Table of Contents and List of Contributors

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