Modern Techniques for Agricultural Disease Management and Crop Yield Prediction

Modern Techniques for Agricultural Disease Management and Crop Yield Prediction
PDF, ePUB
  • eBook:
    Modern Techniques for Agricultural Disease Management and Crop Yield Prediction
  • Author:
    N. Pradeep, Sandeep Kautish, C.R. Nirmala
  • Edition:
    -
  • Categories:
  • Data:
    July 15, 2019
  • ISBN:
    1522596321
  • ISBN-13:
    9781522596325
  • Language:
    English
  • Pages:
    316 pages
  • Format:
    PDF, ePUB

Book 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.

Content

Chapter 1. Issues and Challenges in Smart Farming for Sustainable Agriculture
Chapter 2. Image Processing Techniques Aiding Smart Agriculture
Chapter 3. Expert System Design for Diagnosis of Diseases for Paddy Crop
Chapter 4. Deep Learning and Computer Vision in Smart Agriculture
Chapter 5. Computer Vision for Green Plant Segmentation and Leaf Count
Chapter 6. Automatic Data Acquisition and Spot Disease Identification System in Plants Pathology Domain: Agricultural Intelligence System in Plant Pathology Domain
Chapter 7. Applications of Data Mining Techniques in Smart Farming for Sustainable Agriculture
Chapter 8. Agro Guardian: A Smart Agriculture Framework for Precision Farming
Chapter 9. A Study on Technology-LED Solutions for Fruit Grading to Address Post-Harvest Handling Issues of Horticultural Crops
Chapter 10. Optimized Data Mining Techniques for Outlier Detection, Removal, and Management Zone Delineation for Yield Prediction

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