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Site‐Specific Analysis of a Droughted Corn Crop: I. Growth and Grain Yield
Author(s) -
Sadler E. John,
Bauer Philip J.,
Busscher Warren J.
Publication year - 2000
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2000.923395x
Subject(s) - yield (engineering) , spatial variability , precision agriculture , agronomy , environmental science , crop , soil survey , phenology , biomass (ecology) , crop yield , grain yield , scale (ratio) , soil water , agriculture , soil science , mathematics , geography , biology , statistics , ecology , cartography , materials science , metallurgy
Soil in the southeastern USA Coastal Plain exhibits marked variation, especially near shallow depressions called Carolina Bays. This variation causes correspondingly severe variation in yield, particularly for corn ( Zea mays L.) during drought. Though important to precision farming, these features often are overlooked in 1:20000 scale county soil surveys. They are visible in 1:1200 scale soil surveys, but the ability to explain yield variation using soil map units at this scale must be unequivocally demonstrated before committing resources to such a detailed survey. Our objectives were (i) to compare paired samples of four soil map units to determine if grain yield variation were sufficiently explained to be of practical value, and (ii) to extend this evaluation to include data with greater spatial coverage. Corn grain yields were measured at 209 sites in an 8‐ha field, including two Carolina Bays near Florence, SC. Site‐specific effects of soil variation on crop phenology, biomass, and yield components were measured at 11 sites during a drought. Variations in yield components were large and sometimes compensatory (e.g., kernel number and mass), with distinctly different routes to sometimes similar final grain yields. Multiple sites within map units were frequently different at α = 0.05. Analysis of variance for grain yield on soil map unit was statistically significant ( P < 0.001) but of limited explanatory value ( r 2 = 0.16). We conclude that to create soil management zones for precision farming, one must augment even detailed soil map units with additional spatial data, such as yield maps.