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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #128215

Title: DETECTING SPATIALLY VARIABLE CORN NITROGEN NEEDS USING GREEN REFLECTANCE FROM 35 MM PHOTOGRAPHS

Author
item WILLIAM, JARED - U OF MO
item Kitchen, Newell
item SCHARF, PETER - U OF MO

Submitted to: North Central Extension Industry Soil Fertility Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 11/15/2001
Publication Date: N/A
Citation: N/A

Interpretive Summary: Midwestern farmers are aware that current cropping practices have contributed to an increase in nitrogen(N)in the Mississippi River. Also, N fertilizer costs have spiked in recent years in response to elevated oil and gas prices. These facts have motivated farmers to improve N management practices. We conducted this research to learn if using inexpensive 35 mm photographs taken from an airplane could detect corn N need during the early part of the growing season by measuring the relative greenness of corn plants at different growth stages. The study was conducted on two MO fields representing Mississippi alluvial and deep loess soil types. We found that the optimal N rate varied within both fields, between 40 and 180 lb/ac for the deep loess soil field and between 40 and 210 lb/ac for the Mississippi alluvial soil field. Farmers in these areas commonly blanket apply N between 200 and 225 lb/ac. Assuming these fields are representative of other corn fields, our results indicate that N fertilize is over applied on many field areas. We related plant greenness obtained from 35 mm aerial photographs to the economic optimal N rate. Relative greenness and optimal N rates were well correlated for both sites but not for all growth stages. Relative plant greenness showed potential to be used for variable rate N fertilizer mapping, but significant obstacles will need to be overcome before implementing this approach. For example, farmers will have to be convinced to wait until the corn is at a mid- vegetative growth stage or later to apply side-dressed N fertilizer. These results will be useful to producers and crop consultants in improving their site-specific N management plans to increase profitability and reduce N discharge to streams and rivers.

Technical Abstract: Rising fertilizer costs and heightened environmental concern along coastal waters are reasons corn producers are looking to decrease nitrogen (N) fertilizer rates. Many N management guidelines recommend an application of N to non-leguminous crops at rates that are expected to supply almost all crop N needs. Further, recommendations are often based on best field conditions resulting in the poorer producing areas of fields being greatly over fertilized. This study investigated the use of relative green reflectance from 35 mm aerial photographs to detect spatially variable corn [Zea mays L.] N needs and its potential for developing variable rate fertilizer maps. Photographs were taken at three different growth stages (V7, V11, R3) at altitudes from 900 to 1,700 m for two Missouri fields, representing Mississippi alluvial and deep loess soil types. At growth stage V5, N was applied in strips across the field ranging from 0 to 280 kg/ha in 56 kg/ha increments. Relative green reflectance was developed using a ratio of the green reflectance values of the 0 and 280 kg/ha N fertilizer treatments. Economic optimal N rates were assessed using a quadratic plateau response model with yield as a function of N fertilizer rates. Relative green reflectance and optimal N rates were significantly correlated for both sites but not for all growth stages. Areas that had high apparent soil electrical conductivity (soil EC) showed a strong relationship between relative reflectance and optimal N rates with r**2 values as high as 0.76. These results will be used to further explore the potential for aerial images to detect corn N status, explain soil type and crop color interactions, and develop in-season variable N fertilizer maps for producers.