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Prediction of wheat grain protein yield by canopy hyperspectal remote sensing.

FENG Wei1,2;ZHU Yan2;TIAN Yong-chao2;CAO Wei-xing2;GUOTian-cai1;WANG Cheng-yang1   

  1. 1National Engineering Research Center for Wheat, Henan Agricultural Uni
    versity, Zhengzhou 450002, China;2HiTech Key Laboratory of Information
    Agriculture of Jiangsu Province, Nanjing Agricultural University, Nanjing 210095
    , China
  • Received:2007-09-14 Revised:1900-01-01 Online:2008-06-10 Published:2008-06-10

Abstract: Three years (2003-2006) field experiment was conducted with different wheat varieties and nitrogen (N) supply, and timecourse measurements were made on the canopy hyperspectral reflectance, plant dry mass and its N content. Based on the technique route of characteristic spectral parameters-leaf N nutrition-grain protein yield, and with leaf N nutrition as a link, the prediction models of wheat grain protein yield based on the canopy hyperspectal parameters at anthesis were constructed. The results showed that the wheat grain protein yield at maturity increased with increasing N supply. Plant N nutritional status, such as leaf N content (LNC) and leaf N accumulation (LNA) at anthesis and leaf N transportation (LNT) after anthesis, could well indicate the grain protein yield at maturity. The regression analysis between existing vegetation indices and leaf N index indicated that some key spectral parameters could accurately estimate the changes in leaf N status across a broad ranges of growth stages, N supply and growing seasons, with unified spectral parameters for each wheat cultivar, such as REPle and mND705 for leaf N content, and SDr/SDb and FD742 for leaf N accumulation. The testing of the prediction models with independent dataset indicated that the spectral indices of REPle, SDr/SDb and FD742 could give accurate grain protein yield estimation, and the R2 of REPle, SDr/SDb and FD742 was 0.854, 0.803 and 0.795, with the RE of 16.4%, 18.2% and 14.9%, respectively. Overall, the wheat grain protein yield at maturity could be predicted by the key characteristic spectral indices at anthesis.

Key words: Grazing Leymus chinensis grassland, Fenced Leymus chinensis grassland, Soil respiration