International Journal of Applied Earth Observations and Geoinformation (Oct 2021)

Retrieving potassium levels in wheat blades using normalised spectra

  • Tiancheng Yang,
  • Jingshan Lu,
  • Feng Liao,
  • Hao Qi,
  • Xia Yao,
  • Tao Cheng,
  • Yan Zhu,
  • Weixing Cao,
  • Yongchao Tian

Journal volume & issue
Vol. 102
p. 102412

Abstract

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This work explored potassium nutrient retrieval in wheat blades using reflectance spectra. Spectral data were collected from wheat blades at different growth stages, in different cultivars, and following different fertilisation treatments from 2016 to 2019 using a leaf clip and halogen bulb with an ASD spectrometer. Reflectance data from 350 to 2500 nm were collected, and data of 400 to 2400 nm were used in the retrieval. Using a leaf clip to measure the reflectance of a narrow blade can cause bias, which can be corrected using a normalisation method, i.e. the reflectance of each band was divided by the average reflectance of all bands. Three such methods were employed: vegetation index (VI), partial least squares (PLS), and random forest (RF). The approach yielded leaf potassium content (LKC, %) and leaf potassium per area (LKA, g/m2). The results showed that newly developed VIs outperformed previously published indices. The model using a modified ratio spectral index, mRSI(2275, 1875), yielded LKC with a coefficient of determination (R2) of 0.61 and a root mean square error (RMSE) of 0.57%. Normalisation methods can eliminate multiplicative error in blade spectra, thereby correcting the underestimated reflectance of narrow blades, and improving the accuracy of potassium retrieval models. Among the three methods, PLS achieved the highest accuracy. The retrieval of LKC and LKA based on normalised spectra and the PLS method yielded R2 values of 0.74 and 0.65, respectively, and their corresponding RMSE values were 0.46% and 0.21 g/m2. LKC retrieval models had higher R2 values than LKA models. This comprehensive analysis of different methods revealed the importance of reflectance at 1883 nm and 2305 nm. In conclusion, it is feasible to retrieve wheat leaf potassium levels using spectral data.

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