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portada Modern Techniques for Agricultural Disease Management and Crop Yield Prediction (Advances in Environmental Engineering and Green Technologies)
Type
Physical Book
Language
English
Pages
300
Format
Hardcover
Dimensions
27.9 x 21.6 x 1.9 cm
Weight
1.02 kg.
ISBN13
9781522596325

Modern Techniques for Agricultural Disease Management and Crop Yield Prediction (Advances in Environmental Engineering and Green Technologies)

Sandeep Kautish (Illustrated by) · N. Pradeep (Illustrated by) · C. R. Nirmala (Illustrated by) · Engineering Science Reference · Hardcover

Modern Techniques for Agricultural Disease Management and Crop Yield Prediction (Advances in Environmental Engineering and Green Technologies) - Pradeep, N. ; Kautish, Sandeep ; Nirmala, C. R.

Physical Book

£ 238.47

  • Condition: New
Origin: U.S.A. (Import costs included in the price)
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Synopsis "Modern Techniques for Agricultural Disease Management and Crop Yield Prediction (Advances in Environmental Engineering and Green Technologies)"

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.

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