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Estimation of Wheat Agronomic Parameters using New Spectral Indices

Author

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  • Xiu-liang Jin
  • Wan-ying Diao
  • Chun-hua Xiao
  • Fang-yong Wang
  • Bing Chen
  • Ke-ru Wang
  • Shao-kun Li

Abstract

Crop agronomic parameters (leaf area index (LAI), nitrogen (N) uptake, total chlorophyll (Chl) content ) are very important for the prediction of crop growth. The objective of this experiment was to investigate whether the wheat LAI, N uptake, and total Chl content could be accurately predicted using spectral indices collected at different stages of wheat growth. Firstly, the product of the optimized soil-adjusted vegetation index and wheat biomass dry weight (OSAVI×BDW) were used to estimate LAI, N uptake, and total Chl content; secondly, BDW was replaced by spectral indices to establish new spectral indices (OSAVI×OSAVI, OSAVI×SIPI, OSAVI×CIred edge, OSAVI×CIgreen mode and OSAVI×EVI2); finally, we used the new spectral indices for estimating LAI, N uptake, and total Chl content. The results showed that the new spectral indices could be used to accurately estimate LAI, N uptake, and total Chl content. The highest R2 and the lowest RMSEs were 0.711 and 0.78 (OSAVI×EVI2), 0.785 and 3.98 g/m2 (OSAVI×CIred edge) and 0.846 and 0.65 g/m2 (OSAVI×CIred edge) for LAI, nitrogen uptake and total Chl content, respectively. The new spectral indices performed better than the OSAVI alone, and the problems of a lack of sensitivity at earlier growth stages and saturation at later growth stages, which are typically associated with the OSAVI, were improved. The overall results indicated that this new spectral indices provided the best approximation for the estimation of agronomic indices for all growth stages of wheat.

Suggested Citation

  • Xiu-liang Jin & Wan-ying Diao & Chun-hua Xiao & Fang-yong Wang & Bing Chen & Ke-ru Wang & Shao-kun Li, 2013. "Estimation of Wheat Agronomic Parameters using New Spectral Indices," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-9, August.
  • Handle: RePEc:plo:pone00:0072736
    DOI: 10.1371/journal.pone.0072736
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    Cited by:

    1. Jin, Xiuliang & Li, Zhenhai & Feng, Haikuan & Ren, Zhibin & Li, Shaokun, 2020. "Estimation of maize yield by assimilating biomass and canopy cover derived from hyperspectral data into the AquaCrop model," Agricultural Water Management, Elsevier, vol. 227(C).
    2. Jing Zhang & Wenjiang Huang & Qifa Zhou, 2014. "Reflectance Variation within the In-Chlorophyll Centre Waveband for Robust Retrieval of Leaf Chlorophyll Content," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-13, November.
    3. Mohamed Elgharib Gomah & Guichen Li & Naseer Muhammad Khan & Changlun Sun & Jiahui Xu & Ahmed A. Omar & B. G. Mousa & Marzouk Mohamed Aly Abdelhamid & M. M. Zaki, 2022. "Prediction of Strength Parameters of Thermally Treated Egyptian Granodiorite Using Multivariate Statistics and Machine Learning Techniques," Mathematics, MDPI, vol. 10(23), pages 1-21, November.

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