Enhancing Agricultural Research and Precision Management for Subsistence Farming by Integrating System Models with Experiments

Authors: Timlin, Dennis; Anapalli, Saseendran

Submitted to: Advances in Agricultural Systems Modeling
Publication Type: Book / Chapter
Publication Acceptance Date: 9/22/2021
Publication Date: 4/20/2022
Citation: Timlin, D.J., Anapalli, S.S. 2022. Enhancing Agricultural Research and Precision Management for Subsistence Farming by Integrating System Models with Experiments. Advances in Agricultural Systems Modeling. 9:1-5. https://doi.org/10.1002/9780891183891.ch1.
DOI: https://doi.org/10.1002/9780891183891.ch1

Interpretive Summary: Agriculture in many countries where subsistence farming is the dominant form of farming is facing increasing pressure from growing populations and climate change. New management practices and varieties will be needed to meet these demands and help agriculture adapt to changes in the environment. One approach to address these challenges is to use crop simulation models. Such models are important tools that can be used to assess crop response to management and climate change. This book presents examples that show how crop simulation models can be used in subsistence agriculture to enhance field research for improved crop management practices that increase the resilience and sustainability of these systems. The effects of climate change and increased intensification of land use on subsistence and low input agriculture are expected to be severe due to lack of research on alternative management practices and limited resources for farmers. However, the simulation studies in this book show that increased diversification through crop rotations and use of alternative crops can decrease the variability caused by climate change and result in decreased impact of heat and water stress. This book will be useful research scientists, policy makers and others interested in developing approaches to help low input agriculture adapt to climate change.

Technical Abstract: Agriculture in many countries where subsistence farming is the dominant form of farming is facing increasing pressure from growing populations and climate change. New management practices and varieties will be needed to meet these demands and help agriculture adapt to changes in the environment. One approach to address these challenges is to use crop simulation models. Such models are important tools that can be used to assess crop response to management and climate change. Crop models encapsulate the main processes involved in plant growth and development in the form of computer algorithms that are developed from laboratory, growth chamber and field research results. These models can be used to vary management variables, plant cultivar properties, and environmental variables such as weather and soil to investigate crop response to the environment and management. This book presents a number of examples that show how crop simulation models can be used in subsistence agriculture to enhance field research to improve crop management to increase the resilience and sustainability of these systems. The effects of climate change and increased intensification of land use on subsistence and low input agriculture are expected to be severe due to lack of research on alternative management practices and limited resources for farmers. However, most of the simulation studies in this book show that increased diversification through crop rotations and use of alternative crops can decrease the variability caused by climate change and result in decreased impact of heat and water stress.