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Developing Nitrogen Fertilizer Recommendations for Corn Using an Active Sensor
Author(s) -
Dellinger Adam E.,
Schmidt John P.,
Beegle Doug B.
Publication year - 2008
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/agronj2007.0386
Subject(s) - normalized difference vegetation index , agronomy , sowing , fertilizer , manure , environmental science , nitrogen , mathematics , crop , leaf area index , chemistry , biology , organic chemistry
Producers often overapply N fertilizer to corn ( Zea mays L.) because of the uncertainty in predicting the economic optimum nitrogen rate (EONR). Remote sensing represents a potential opportunity to reduce this uncertainty with an in‐season assessment of crop N status. This study examines the relationship between EONR and reflectance from a ground‐based sensor, and considers its potential for developing sidedress N recommendations for corn. Four fields with unique cropping histories were planted to corn during each of 2 yr. Three preplant whole plot treatments (control, 56 kg N ha −1 as NH 4 NO 3 , and manure) were used to create a range of N availability. Split plot treatments included seven sidedress rates (0, 22, 45, 90, 135, 180, and 280 kg N ha −1 ) and one preplant rate (280 kg N ha −1 ) as NH 4 NO 3 . The EONR for the sidedress N rates was determined for each whole plot treatment at each site. A ground‐based active sensor was used at the sixth‐ to seventh‐leaf growth stage (V6–V7) to collect reflectance data at 590 and 880 nm, which were then used to calculate the Green Normalized Difference Vegetation Index (GNDVI). The EONRs for sidedress N application for the 24 preplant treatment–site combinations ranged from 0 to 202 kg N ha −1 . The EONR was strongly related to relative GNDVI ( r 2 = 0.84) for the control and manure preplant treatments; but unrelated when NH 4 NO 3 was applied at planting ( r 2 = 0.20). Developing sidedress N recommendations for corn using an active sensor could be an effective N management tool in Pennsylvania.