Sensing Technologies for Field and In-House Crop Production Technology Review and Case Studies

This book focuses on state-of-the-art sensing and automation technologies for field crops and in-house product production and provides a lot of innovative knowledge on image processing, AI algorithms and applications in agriculture, and robotics. This book provides undergraduate or graduate students with take-away knowledge for unmanned agricultural production, including but not limited to corn disease detection, wheat head detection and counting, and soil nutrient condition monitoring. The first three chapters focus on reviewing plant phenotyping sensing technology and robotics and soil nutrient monitoring, followed by in-house crop sensing robotics. Then two case studies on corn and the other two case studies on wheat are presented.

A Review of Three-Dimensional Multispectral Imaging in Plant Phenotyping.- Recent Advances in Soil Nutrient Monitoring: A Review.- Plant phenotyping robot platform.- Autonomous crop image acquisition system based on ROS system.- SeedingsNet: Field wheat seedling density detection based on deep learning.- Wheat lodging detection using smart vision-based method.- Design, construction, and experiment-based key parameter de-2 termination of auto maize seed placement system.- Development and test of an auto seedling detection System.