Technological Progress on Variable Rate Fertilization

Overview

This book features interdisciplinary of agricultural engineering and precision agriculture, focusing on real-time variable-rate fertilization (VRF) based on crop phenotypic biological information. It systematically presents cutting-edge research on intelligent sensing, inversion modeling, actuator optimization, and practical system validation.

Scientific Methods

Key scientific methods include hybrid neural network models (such as LFA-PSO-MLP), discrete element modeling (DEM), and deep learning-based flow detection (YOLOv5s-seg). These approaches are illustrated with clear diagrams, data tables, and experimental results, linking theoretical insights with practical engineering applications.

Innovative Designs and Validation

The book introduces innovative designs like centrifugal VRF spreaders and phenotypic sensing systems, validated through field trials to improve fertilization accuracy, reduce input waste, and enhance sustainability.

Technology Framework

It offers a comprehensive technology framework integrating "crop-sensor-decision-actuator" into a closed-loop control system.

Target Audience

For researchers and practitioners in smart farming, crop sensing, and equipment development, this book serves as a valuable reference bridging theory and field applications. Target readers include graduate and undergraduate students in agricultural engineering, precision agriculture researchers, intelligent equipment developers, and agricultural extension professionals.