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Table 5 Quantitative relationship between trilateral parameters and NO3–N content in petioles

From: Estimation of nitrate nitrogen content in cotton petioles under drip irrigation based on wavelet neural network approach using spectral indices

Trilateral parameters Functional model Regression equation R2 RMSE (g/L)
Dr Linear y = − 1E + 06x + 21,084 0.64 1.40
Exponential y = 59,355e−160.9x 0.61 1.45
Quadratic y = − 2E + 08x2 + 6E + 06x − 23990 0.67 2.93
SDr Linear y = − 12,321x + 13,673 0.52 2.28
Exponential y = 18,355e−1.876x 0.47 2.59
Quadratic y = − 58,926x2 + 48,072x − 895.38 0.60 2.53
Dy Linear y = − 1E + 08x + 1114.1 0.72 1.08
Exponential y = 2691.4e−17931x 0.67 1.82
Quadratic y = − 4E + 12x2 − 5E + 08x − 9212.4 0.84 2.73
SDy Linear y = − 193,244x − 1139.4 0.73 2.91
Exponential y = 1924.3e−29.42x 0.67 2.54
Quadratic y = − 8E + 06x2 − 905,730x − 16273 0.79 2.51
Db Linear y = 4E + 06x − 836.47 0.80 1.04
Exponential y = 2036.5e619.48x 0.72 1.50
Quadratic y = − 3E + 09x2 + 2E + 07x − 14359 0.89 1.64
SDb Linear y = 498,071x − 9405.9 0.81 1.45
Exponential y = 492.37e78.986x 0.80 1.53
Quadratic y = 9E + 06x2 − 84,605x − 199.84 0.82 1.98
  1. E stands for scientific counting; e is the base of natural logarithm