Brian Keating

What is he best known for?

The fields of study he is best known for:

• Agriculture
• Ecology
• Agronomy

Brian Keating mainly focuses on Agriculture, Agronomy, Soil water, Agricultural productivity and Water use. His work in the fields of Food security overlaps with other areas such as Decision support system. In most of his Agronomy studies, his work intersects topics such as Water balance.

The study incorporates disciplines such as Supply chain, Systems design, Resource management and Cropping in addition to Water balance. His Soil water research incorporates themes from Tillage and Drainage. The Water use study combines topics in areas such as Soil science and Yield.

His most cited work include:

• An overview of APSIM, a model designed for farming systems simulation (1830 citations)
• APSIM - Evolution towards a new generation of agricultural systems simulation (689 citations)
• APSIM's water and nitrogen modules and simulation of the dynamics of water and nitrogen in fallow systems (444 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Agriculture, Agronomy, Agricultural productivity, Food security and Agricultural economics. His work on Sustainable agriculture as part of general Agriculture study is frequently linked to Decision support system, therefore connecting diverse disciplines of science. Brian Keating combines subjects such as Water balance, Soil water and Drainage with his study of Agronomy.

His Agricultural productivity research includes themes of Cropping, Simulation, Sustainability and Environmental resource management. His Food security course of study focuses on Food processing and Food safety. The concepts of his Agricultural economics study are interwoven with issues in Productivity and Sugar.

He most often published in these fields:

• Agriculture (27.52%)
• Agronomy (26.61%)
• Agricultural productivity (15.60%)

What were the highlights of his more recent work (between 2014-2020)?

• Food security (14.68%)
• Agriculture (27.52%)
• Agricultural productivity (15.60%)

In recent papers he was focusing on the following fields of study:

Brian Keating mostly deals with Food security, Agriculture, Agricultural productivity, Environmental planning and Sustainability. His work carried out in the field of Food security brings together such families of science as Economic growth, Productivity, Knowledge management and Process management. His studies deal with areas such as Innovation system, Industrial organization and Systems research as well as Agriculture.

His research in Agricultural productivity intersects with topics in Cropping, Land use, land-use change and forestry and Agricultural economics. His Cropping research includes elements of Agricultural engineering, Cropping system and Soil processes. His biological study spans a wide range of topics, including Environmental resource management, Agronomy and Land use.

Between 2014 and 2020, his most popular works were:

• Brief History of Agricultural Systems Modeling (196 citations)
• Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science (134 citations)
• Towards a new generation of agricultural system data, models and knowledge products: Design and improvement (53 citations)

In his most recent research, the most cited papers focused on:

• Agriculture
• Ecology
• Irrigation

His primary areas of investigation include Food security, Agriculture, Systems science, Data modeling and Knowledge-based systems. His research integrates issues of Scale, Environmental planning, Climate change mitigation, Climate change and Agricultural policy in his study of Food security. In his works, he performs multidisciplinary study on Agriculture and Technological change.

Systems science is integrated with Systems simulation, Complex system, Decision support system, Data science and Information system in his study. Brian Keating regularly ties together related areas like Environmental resource management in his Data science studies. His Data modeling research is multidisciplinary, incorporating perspectives in New product development, Use case, Knowledge management and Process management.