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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Publications at this Location » Publication #276229

Title: Simulating potential production capacity of potatoes in Maine at multiple scales using a geospatial crop model

item Resop, Jonathan
item Fleisher, David
item Timlin, Dennis
item Reddy, Vangimalla

Submitted to: ASABE Annual International Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 12/8/2011
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Heavily populated areas, such as the northeast region of the U.S., depend on the production of distantly produced food, particularly for urban populations. Food systems are vulnerable to uncertainties such as energy costs, environmental conditions, urban growth, and climate change. Research into the potential production capacity of regional food systems would go a long way to better serve local populations. The objective of this study was to evaluate potato production throughout Maine as influenced by different scenarios: 1) land use availability for production (e.g. current potato land, grass and scrub, cropland, pasture); 2) planting date variability (e.g. early planting, late planting); and, 3) water use (e.g. rain-fed, irrigation). Estimates of production were made by combining an explanatory crop model (SPUDSIM) with spatial input data layers using a geographic information system (ArcGIS) and a Python-based scripting interface. The combined interface provides a mechanistic representation of crop production by relating variations in inputs (i.e. weather, soil, management, and land use) to the outputs generated by the model (i.e. yield, water use, and nitrogen demand). The combined geospatial crop model interface has the ability to estimate potential crop production over multiple scales: automating crop simulation over field-scale modeling units and aggregating the results to the county level. The results will provide valuable information for regional policy planners in terms of the productivity of local food systems to be used for improving crop yield and sustainability.