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Producers are continually being exposed to new technologies and the
Computer Age. Site specific management in agriculture has been gaining
acceptance and use in some areas of the country and continues to grow
across the Cotton Belt. Global Positioning Systems (GPS) and Geographic
Information System (GIS) make it possible to geo-reference fields which
become the framework for multi-layered data that can be used to describe
relationships or events occurring in the field or a specific management
zone. This study on 15-acre field at the Delta Research and Extension
Center was initiated in 1998 in an effort to evaluate the spatial variability
of corn and cotton yields as wells the spatial variability of topsoil and
subsoil soil characteristics measured in the same areas. Corn grown in 1998
had yields which ranged from a low 132 bu/A to a high of 186 bu/A and a
field average of 156 bu/A. In 1998, the same area had corn yields which
ranged from 151 bu/A to a high of 222 bu/A and a field average of 182
bu/A. The area was rotated to cotton in 1999 with total lint yields ranging
from a low of 949 lb/A to a high of 1508 lb/A and a average across the field
of 1248 lb/A. Regression analysis was used was used to examine the the
soil characteristics with respect to corn yields. When considering a single
factor in 1998, the highest correlation occurred between yield and subsoil
P (r 2 = 0.2460) followed by topsoil P (r 2 = 0.2394). When two factors were
considered in the model, the highest correlation occurred with subsoil P +
subsoil K (r 2 = 0.2725). Adding the second factor did not greatly increase
the correlation. With the second corn crop in 2000, subsoil P was again the
factor with the highest correlation to yield (r 2 = 0.0751). The correlation
was poorer in 2000 than had been observed in 1998 indicating that other
factors were exhibiting a stronger influence than before. The soil pH
became more of a factor in 2000 with the second highest single factor
correlation (r 2 = 0.0657). These two factors together increased the
correlation to r 2 = 0.1344. When evaluating factors that influenced cotton
lint yields, soil characteristics such as topsoil exchangeable acidity (r 2 = |
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©National Cotton Council, Memphis TN |
Document last modified XXXXXX, XXX XX 2001
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