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

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Abstract

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% (R700/R670) and 57% (R418/R405), respectively, of the variation in PNC at later growth stages (Feekes 8–10), but only 22% (modified chlorophyll absorption ratio index, MCARI) and 43% (R763/R761), 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 R370 and R400 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.

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Acknowledgements

This research was financially supported by the National Basic Research Program (973-2009CB118606), Key Project of National Science & Technology Support Plan (2008BADA4B02), Sino-German Cooperative Nitrogen Management Project (2007DFA30850), International Bureau of the German Federal Ministry of Research and Technology (BMBF, Project No. CHN 08/051), Special Fund for Agriculture Profession (200803030), The Innovative Group Grant of NSFC (No. 30821003) and the GIS & RS Group of the University of Cologne, Germany.

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Authors and Affiliations

  1. International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China

    Fei Li, Yuxin Miao, Martin L. Gnyp, Xinping Chen & Georg Bareth

  2. College of Ecology and Environmental Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010019, China

    Fei Li

  3. Institute of Geography, University of Cologne, 50923, Cologne, Germany

    Simon D. Hennig, Martin L. Gnyp & Georg Bareth

  4. Institute of Agricultural Resource and Environment, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, 050051, China

    Liangliang Jia

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This is an “enhanced” version of the paper published as “Comparing hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat” in E.J. van Henten, D. Goense and C. Lokhorst (Ed.) Precision Agriculture’09. Proceedings of the 7th European Conference on Precision Agriculture (7ECPA), 5–9 July 2009, Wagningen, The Netherlands. Wageningen Academic Publishers, Wageningen, The Netherlands.

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Li, F., Miao, Y., Hennig, S.D. et al. Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages. Precision Agric 11, 335–357 (2010). https://doi.org/10.1007/s11119-010-9165-6

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