Fig 1.
Linear mixed effects model for relationship between gross profit margin ($ ha-1) and plant density (plants ha-1) under six candidate recommendation domain models (RDM).
The peak of each curve identifies the optimum plant density of each RDM level.
Fig 2.
Calculation of additional processor profit ($ ha-1) for a field in a given level of a recommendation domain model (RDM).
Red line represents the optimum plant density (plants ha-1) for maximum gross profit margin ($ ha-1) under a level of a RDM (solid black curve). Blue line represents current plant density for an individual field (dotted black curve). The difference in gross profit margin observed at the optimum plant density under RDM level and current plant density of a field give additional processor profit from the field.
Table 1.
Brief description of the thirty fields in which optimum plant density for processing sweet corn was quantified in field trials in Illinois (IL), Minnesota (MN), and Wisconsin (WI) from 2013 to 2017.
Table 2.
Summary statistics of the environmental and crop management variables of thirty fields in which optimum plant density for processing sweet corn was quantified in field trials in Illinois, Minnesota, and Wisconsin from 2013 to 2017.
Universal Transverse Mercator (UTM) uses a 2-dimensional Cartesian coordinate system to give locations on the surface of the Earth. GDDpt and GDDth represent growing degree days observed during planting-tassel and tassel-harvest, respectively.
Table 3.
Pearson’s partial correlation coefficients between environmental and crop management variables of thirty fields in which optimum plant density for processing sweet corn was quantified in field trials in Illinois, Minnesota, and Wisconsin from 2013 to 2017.
Coefficients in bold are significant at α = 0.05. GDDpt and GDDth represent growing degree days observed during planting-tassel and tassel-harvest, respectively.
Table 4.
Exploratory factor analysis results, based on varimax rotation, using the correlation matrix of environmental and crop management variables from thirty fields in which optimum plant density for processing sweet corn was quantified in field trials in Illinois, Minnesota, and Wisconsin from 2013 to 2017.
Factor loadings from variables that were greater than 0.400 in magnitude are in bold.
Table 5.
Mean additional processor profit ($ha-1) and grower returns ($ ha-1), standard error, and sample size for each level of the six candidate recommendation domain models (RDM).
RDM mean additional processor profit and grower returns were determined using the weighted average of RDM levels. For a description of how additional processor profit were calculated, see Fig 2.