LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status

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 (Win t ha(-1)) and N concentration (%N-a), which can be used to calculate N nutrition index (NNI), where NNI is %N-a/N-c (%N-a is actual N concentration and %N-c is the minimum N concentration required for maximum growth). Using optical remote sensing to estimate crop N status is particularly important during the critical early crop developmental stages when reliable data could still guide effective in-season N fertilizer management decisions (e.g., by adding topdressed fertilizer). 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 Wand %N-a are prone to large errors. Terrestrial LiDAR (light detection and ranging) 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 %N-a from green (532 nm) TLS point return intensity. We evaluated the potential of TLS to assess W, %N-a and NNI of winter wheat (Triticum aestivum L). Green TLS measurements were obtained for two seasons during tillering and jointing. Strong (r(2) > = 0.72, RMSE <= 0.68 t ha(-1)) relationships occurred between observed Wand TLS-derived vegetation volume across all growth stages and seasons. A wider range of relationships existed between %N-a and green laser return intensity (r(2) = 0.10-0.75, RMSE = 0.31-0.63%). When fused to calculate a TLS based NNI, a moderately strong relationship occurred (r(2) = 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. (C) 2014 Elsevier B.V. All rights reserved.