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ARS Home » Pacific West Area » Pullman, Washington » Northwest Sustainable Agroecosystems Research » Research » Publications at this Location » Publication #308613
Title: LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status

Author
item EITEL, JAN - University Of Idaho
item MAGNEY, TROY - University Of Idaho
item VIERLING, LEE - University Of Idaho
item BROWN, TABITHA - Washington State University
item Huggins, David

Submitted to: Field Crops Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/20/2014
Publication Date: 3/1/2014
Citation: Eitel, J.U., Magney, T.S., Vierling, L.S., Brown, T.T., Huggins, D.R. 2014. LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status. Field Crops Research. 159:21–32.

Interpretive Summary: Crops that utilize nitrogen (N) more efficiently will result in less nitrous oxide (a greenhouse gas) production, less loss of nitrate to surface and ground water, and more profits to farmers as they need less nitrogen to produce the same crop. Optical remote sensing of crop N status is developing into a powerful diagnostic tool that can improve N management decisions. Using optical remote sensing to estimate crop N status is important during early crop developmental stages when reliable data could guide effective in-season N fertilizer management decisions. However, because the spectral signal measured by traditional optical remote sensing devices during early crop development is often dominated by soil spectral reflectance, early season estimates of N status are prone to large errors. Terrestrial laser scanning (TLS) may alleviate errors as fine scale TLS point data can be used to directly quantify and derive N crop N status from green (532 nm) TLS point return intensity. We evaluated the potential of TLS to assess crop N status of winter wheat. Green TLS measurements were obtained for two seasons during wheat tillering and jointing. A strong relationship occurred between observed and TLS-derived crop N status. Our results demonstrate that green TLS can provide useful information for improving N management during early season wheat growth. This information will stimulate interest among growers, agribusiness and scientists to further develop precision farming strategies for nitrogen management in the dryland farming areas of eastern Washington, northwestern Oregon and northern Idaho.

Technical Abstract: Optical remote sensing of crop nitrogen (N) status is developing into a powerful diagnostic tool that can improve N management decisions. Crop N status is a function of dry mass per unit area (W) and N concentration (%Na), which can be used to calculate N nutrition index (NNI),where NNI is %Na/%Nc (%Na is actual N concentration and %Nc the minimum N concentration required for maximum growth). Using optical remote sensing to estimate crop N status is particularly important during early crop developmental stages when reliable data could still guide effective in-season N fertilizer management decisions. However, because the spectral signal measured by traditional optical remote sensing devices during early crop development is often dominated by soil spectral reflectance, early season estimates of W and %Na are prone to large errors. Terrestrial laser scanning (TLS) may alleviate errors as fine scale TLS point data can be used to directly quantify physical W proxies (e.g. crop height or volume) and derive %Na from green (532 nm) TLS point return intensity. We evaluated the potential of TLS to assess W, %Na and NNI of winter wheat (Triticum aestivum L.). Green TLS measurements were obtained for two seasons during tillering and jointing. Strong (r2> = 0.72, RMSE <= 0.68 t ha-1) relationships occurred between observed W and TLS-derived vegetation volume across all growth stages and seasons. A wider range of relationships existed between %Na and green laser return intensity (r2 range = 0.10-0.75, RMSE range = 0. 31-0.63%). When fused to calculate a TLS based NNI, a moderately strong relationship occurred (r2 range = 0.45-0.54, RMSE = 0.11 NNI). Our results demonstrate that green TLS can provide useful information for improving N management during early season wheat growth.