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ARS Home » Plains Area » Brookings, South Dakota » Integrated Cropping Systems Research » Research » Publications at this Location » Publication #136126
Title: REMOTE SENSING FOR ESTIMATING CORN BIOMASS, YIELD, AND N CONTENT

Author
item Osborne, Shannon
item Schepers, James
item Francis, Dennis
item Schlemmer, Michael

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/14/2002
Publication Date: 3/30/2003
Citation: OSBORNE, S.L., SCHEPERS, J.S., FRANCIS, D.D., SCHLEMMER, M.R. REMOTE SENSING FOR ESTIMATING CORN BIOMASS, YIELD, AND N CONTENT. INTERNATIONAL CONFERENCE ON PRECISION AGRICULTURE ABSTRACTS & PROCEEDINGS. 2003.

Interpretive Summary: Increased irrigation application and concern over environmental contamination has brought about an awareness of efficiently utilizing our limited resources and the need to decrease the negative impact of fertilizer leaching and runoff. Remote sensing has the potential to help producers determine the onset of water stress to trigger irrigation. This could lead to increase use efficiency and minimizing negative environmental impact. The objective of this two-year experiment was to determine specific wavelengths and/or wavelength ratios that are indicative of water stress, N deficiency, in-season biomass, and grain yield in corn (Zea mays L.). A field experiment was established that evaluated different N rates (0, 40, 80, 120, and 240 lb N ac-1) and water treatments (dry land, irrigation based on 0.5 evapotranspiration (ET) and full ET). Canopy spectral radiance measurements (350-2500 nm) were taken at various growth stages and correlated to total plant N and biomass measurements. Total N and biomass estimation in the presence of a water stress was best predicted using reflectance in the near-infrared (NIR) portion of the spectrum and the water absorption bands. Reflectance in the green and NIR regions was best for predicting total N and biomass without a water stress.

Technical Abstract: Available nitrogen (N) and water are the most limiting factors to corn growth in the central Great Plains, and proper management of these resources is important both economically and environmentally. Because in-season plant N and water status methods are time-consuming and require numerous observations to characterize a field, managers could benefit from remote sensing techniques to assist in irrigation and N management decisions. A 2-yr experiment was initiated to determine specific wavelengths and/or combinations of wavelength indicative of water stress and N deficiencies, and to evaluate these wavelengths for estimating in-season biomass and corn (Zea mays L.) grain yield. The experiment was a split-plot design with three replications. Main plot treatments were water level and sub-plot treatments were N rate. The treatment structure had three water treatments [dryland, 0.5 evapotranspiration (ET), and full ET] and five N rates (0, 45, 90, 134, and 269 kg N ha-1). Canopy spectral radiance measurements (350-2500 nm) were taken at various growth stages (V6-V7, V13-V16, and V14-R1). Specific wavelengths for estimating crop biomass, N concentration, grain yield, and chlorophyll meter readings changed with growth stage and sampling date. Changes in total N and biomass in the presence of a water stress were estimated using near-infrared (NIR) reflectance and the water absorption bands. Total corn N and biomass under conditions without water stress can be adequately estimated by measuring reflectance in the green and NIR regions.