Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages

Many hyperspectral vegetation indices (VIs) have been developed to estimate crop nitrogen (N) status at leaf and canopy levels. However, most of these indices have not been evaluated for estimating plant N concentration (PNC) of winter wheat (Triticum aestivum L.) at different growth stages using a common on-farm dataset. The objective of this study was to evaluate published VIs for estimating PNC of winter wheat in the North China Plain for different growth stages and years using data from both N experiments and farmers' fields, and to identify alternative promising hyperspectral VIs through a thorough evaluation of all possible two band combinations in the range of 350-1075 nm. Three field experiments involving different winter wheat cultivars and 4-6 N rates were conducted with cooperative farmers from 2005 to 2007 in Shandong Province, China. Data from 69 farmers' fields were also collected to evaluate further the published and newly identified hyperspectral VIs. The results indicated that best performing published and newly identified VIs could explain 51% (R-700/R-670) and 57% (R-418/R-405), respectively, of the variation in PNC at later growth stages (Feekes 8-10), but only 22% (modified chlorophyll absorption ratio index, MCARI) and 43% (R-763/R-761), respectively, at the early stages (Feekes 4-7). Red edge and near infrared (NIR) bands were more effective for PNC estimation at Feekes 4-7, but visible bands, especially ultraviolet, violet and blue bands, were more sensitive at Feekes 8-10. Across site-years, cultivars and growth stages, the combination of R-370 and R-400 as either simple ratio or a normalized difference index performed most consistently in both experimental (R (2) = 0.58) and farmers' fields (R (2) = 0.51). We conclude that growth stage has a significant influence on the performance of different vegetation indices and the selection of sensitive wavelengths for PNC estimation, and new approaches need to be developed for monitoring N status at early growth stages.