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Integrating Remote Sensing and GIS for Prediction of Winter Wheat (Triticum aestivum) Protein Contents in Linfen (Shanxi), China

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  • Mei-chen Feng
  • Lu-jie Xiao
  • Mei-jun Zhang
  • Wu-de Yang
  • Guang-wei Ding

Abstract

In this study, relationships between normalized difference vegetation index (NDVI) and plant (winter wheat) nitrogen content (PNC) and between PNC and grain protein content (GPC) were investigated using multi-temporal moderate-resolution imaging spectroradiometer (MODIS) data at the different stages of winter wheat in Linfen (Shanxi, P. R. China). The anticipating model for GPC of winter wheat was also established by the approach of NDVI at the different stages of winter wheat. The results showed that the spectrum models of PNC passed F test. The NDVI4.14 regression effect of PNC model of irrigated winter wheat was the best, and that in dry land was NDVI4.30. The PNC of irrigated and dry land winter wheat were significantly (P

Suggested Citation

  • Mei-chen Feng & Lu-jie Xiao & Mei-jun Zhang & Wu-de Yang & Guang-wei Ding, 2014. "Integrating Remote Sensing and GIS for Prediction of Winter Wheat (Triticum aestivum) Protein Contents in Linfen (Shanxi), China," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    • Handle: RePEc:plo:pone00:0080989
    DOI: 10.1371/journal.pone.0080989
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