Evaluating Soil Color with Farmer Input and Apparent Soil Electrical Conductivity for Management Zone Delineation

Abstract

scale too coarse to be effective. Franzen et al. (2002) compared Order 1 and Order 2 soil surveys with maps Variable rate fertilizer application technology (VRT) can provide from grid sampling and topography based zone maps. an opportunity to more efficiently utilize fertilizer inputs; however, accurate prescription maps are essential. Researchers and farmers Order 2 soil surveys were seldom useful in determining have understood the value of dividing whole fields into smaller, homo-zones for site specific management of NO 3 -N. Order 1 geneous regions or management zones for fertility management. Mansoil surveys were more highly related to soil NO 3 -N agement zones can be defined as spatially homogeneous subregions than Order 2 surveys, but their consistency was not as within a field that have similar crop input needs. Delineating managehigh as when topography based zones or maps from ment zones that characterize the spatial variability within a field may grid sampling were used. Landscape position also has provide effective prescription maps for VRT. The objective of this been used to divide fields (Fiez et al., 1994). They found research was to compare and evaluate management zones developed that landscape position alone was not effective in dividfrom soil color (SC) and farmer experience with management zones ing fields into units for variable rate N management. developed from apparent electrical conductivity (EC a ). These two However, Franzen et al. (2001) concluded that topogramethods of developing management zones were compared with soil nutrient levels, texture, and crop yields collected on two fields in 1997. phy-based zone soil sampling may be useful in semiaridThe soil and yield parameters followed the trends indicated by both environments. Long et al. (1998) proposed using the spamanagement zone methods at Field 1 with the highest values found tial variation in grain protein levels to identify N manin the high productivity zones and the lowest the low productivity agement zones in spring wheat (Triticum aestivum L.). zones. Significant differences were found among the managementCurrently, the procedure is applicable for dryland fields zones. However, at Field 2 the high and medium productivity zones that are cropped annually to wheat. Practical implemenwere generally not significantly different using the SC approach, tation of this procedure requires that an appropriate whereas the EC a approach was effective in identifying three distinct sensor be made available to producers that can continumanagement zones. Both methods of developing management zones ously read the protein concentration of grain from comseem to be identifying homogeneous subregions within fields. bine harvester. Ostergaard (1997) developed management zones for VRT N application based on soil type, yield, topography, aerial photos, and producer experi-Predicted SOM was highly correlated with measured Bldg.

Responsive in-season nitrogen management for cereals

“…2. Soil map units (Wibawa et al, 1993), topography (Kravchenko et al, 2000), remote sensing (Schepers et al, 2004), electrical conductivity sensors (Kitchen et al, 2003;Heiniger et al, 2003;Johnson et al, 2003), crop yield (Flowers et al, 2005;Kitchen et al, 2005) and producer experience (Fleming et al, 2004) have all been used with varying success to delineate MZ. While these data sources for MZ delineation can be used to consistently characterize spatial variation in soil physical and chemical properties that partially affect crop yield potential, they are less consistent in characterizing spatial variation in crop N requirements because of the apparent effect of temporal variation on expression of yield potential (Schepers et al, 2004;Lambert et al, 2006).…”

Spatial variability of apparent electrical conductivity and soil properties in a coffee production field

“…The field information used to delimit management zones is generally based on digital elevation models, soil fertility maps obtained by systematic sampling, apparent soil electrical conductivity maps, soil organic matter maps estimated by remote sensing and crop yield maps obtained over more than one season (FLEMING et al, 2004).…”

Definition of management zones in coffee production fields based on apparent soil electrical conductivity

“…One of the techniques used to reduce the number of required soil samples involves defining management zones based on information that can be collected at a low cost (Moral et al, 2010;Xin-Zhong et al, 2009;Zhang et al, 2010). Generally, the field information used to define management zones is based on maps of apparent soil electrical conductivity, digital elevation models, maps created using remote sensing and yield maps obtained from more than one crop (Fleming et al, 2004).…”