Bioproduction Engineering: Automation and Precision Agronomics for Sustainable Agricultural Systems. Second Edition

Tofael Ahamed, PhD
Graduate School of Life and Environmental Sciences, University of Tsukuba, Ibaraki, Japan

Ryozo Noguchi
Faculty of Life and Environmental Sciences, University of Tsukuba, Japan

Tomohiro Takigawa, PhD
Graduate School of Life and Environmental Sciences, University of Tsukuba, Ibaraki, Japan

Lei Tian, PhD
Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, IL, USA

Series: Biotechnology in Agriculture, Industry and Medicine
BISAC: PSY036000




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Crop production varies spatially and temporally within the field boundaries depending on soil and environmental conditions. The major concern of variability for agronomic inputs addresses how best to intervene in the right place, at the right time and in the right quantity to improve the potential yield of crops and feedstock. This book addresses the important question of how large a role bioproduction and renewable energy can play in achieving sustainable agricultural practices in the present system of agricultural production. Agronomy is local, which brings the challenges to the remote optimization of agricultural machinery operations for seeding, fertilizing, crop protecting, and harvesting in the field level to adopt precise agriculture technologies. Cloud computing and big data analytics bring the potential about in machine optimization and agronomy to enable the site-specific management. Understanding bioproduction engineering and development can help improve the efficiency of a sustainable agriculture system.

With the aim of understanding this process, this book focuses on bioproduction and sustainability issues, covering sensors, agricultural decision-making systems and the relationship between bioproduction and sustainable practices of agriculture. The chapters are organized as follows: information oriented technology that can be implemented to address the variability of bioproduction systems, sensors and control systems, precision agricultural technology, decision support systems in agriculture, renewable energy resources and analytical hierarchy processes for agricultural management. The crop growth monitoring parameters like LAI and NDVI points were clarified in the pre-processing stage of images. The decisions and logistics that influence the market prices of agricultural products is emphasized within the revised edition of this book. (Imprint: Nova)



Chapter 1. Bioproduction Engineering

Chapter 2. Sensors for Intelligent Systems in Agriculture

Chapter 3. Control and Navigation for Intelligent Systems in Agriculture

Chapter 4. Sensors for Monitoring Agricultural Productivity

Chapter 5. Spectral Imagery and Remote Sensing in Agriculture

Chapter 6. GIS and Decision Support Systems in Agriculture

Chapter 7. System Design for Renewable Energy Resources in Agriculture

Chapter 8. System Hierarchy for Determining the Potential of Renewable Energy in Agriculture



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