Patrick J. English, Mississippi State University, Delta Research and Extension Center, Stoneville, MS, Sherri L. DeFauw, Department of Agricultural Economics and Rural Sociology, The Pennsylvania State University, University Park, PA, Aaron K. Hoshide, School of Economics, 206 Winslow Hall, University of Maine, Orono, ME and Andrew Plant, Agriculture Education, UMaine Cooperative Extension, Houlton, ME
Sustainability of Maine’s potato production systems has been of major concern for at least the past 50 years. A key historical challenge is the identification of profitable rotation crops. Geospatial frameworks help resolve patterns and trends in production environments at multiple scales; these assessments may, in turn, enable improvements in adaptive management strategies which enhance potato yield, increase whole-farm profitability, and foster sustainable land use. The objectives of this investigation were to: (1) assess farm size classes, field clustering and typologies using USDA, Common Land Unit (CLU - highly aggregated and recoded), Cropland Data Layer (CDL) and National Agriculture Imagery Program (NAIP) products; (2) extract crop sequences in potato systems based on CDL (2008-2011) and NAIP classified imagery (2009, 2011); and (3) evaluate potential economic impacts of select alternate crops identified in potato production fields (from 2008-2010) using various farm-size models. Geospatial integration of CDLs and CLUs from Maine revealed a 4-year potato systems footprint estimated at 56,000 ha, ranging from 24,000-25,000 ha per annum. Five farmscape groupings were resolved based on geometric frequency distribution of acreages. Categories were extra-small (40 ha), small (65 ha), medium (120 ha), large (324 ha), and extra-large (>580 ha). The standard distance function (ArcGIS v10) was used to calculate field dispersion for each group. Mean field dispersions for farmscape groups 1 through 5 were 1.4, 1.7, 3.7, 7.8, and 18.0 km, respectively. Representative enterprise and whole-farm economic budgets were engineered for each of the five farm-size classes to determine economies of scale; detailed outcomes (ranked by crop profitability) are summarized and discussed. Development of an interactive, user-friendly, web-based version of these farm budget models would encourage more farmers and researchers to evaluate the relative profitability of alternative cropping strategies to improve the financial viability of farming in Aroostook County and elsewhere in Maine.