Hyperspectral inversion of soil total nitrogen content in an apple orchard based on mathematical transformation and continuous wavelet transform

doi:10.14088/j.cnki.issn0439-8114.2025.11.022

Abstract

Abstract: To rapidly determine the soil total nitrogen (TN) content in an apple orchard and achieve precise fertilization, soil from the apple orchard at the Tianping Lake Base of the Shandong Institute of Pomology was taken as the research object. Its spectral reflectance (R) was measured and subjected to mathematical transformation (reciprocal, logarithm, square root, first-order derivative, etc.), continuous wavelet transform (CWT), and combined mathematical transformation and CWT processing. The Pearson correlation analysis method was used for feature extraction, and a hyperspectral inversion model for soil TN content was constructed based on support vector regression (SVR). The results showed that after processing the original spectral data with CWT, within the scale range of 2¹ to 2¹⁰, the correlation between the wavelet coefficients and soil TN content first increased and then decreased. Medium scales effectively suppressed noise interference and enhanced the correlation between the spectrum and TN, with a significant effect. Both mathematical transformation and CWT effectively mined the detailed features of the spectrum, with the effect of CWT generally being superior to that of mathematical transformation. The combination of mathematical transformation and CWT significantly improved the model inversion accuracy. Among them, the 1/R-CWT-2⁸ model demonstrated the best performance (R²=0.73, RMSE=0.12 g/kg, RPD = 1.85). The fitting curve between the soil TN content predicted by this model and the measured values was closer to the 1:1 line, indicating high model prediction accuracy. In conclusion, hyperspectral technology could be used as a non-destructive testing method for soil TN content in apple orchards. The hyperspectral inversion model constructed by combining mathematical transformation and CWT could more accurately predict soil TN content.

Key words: mathematical transformation, continuous wavelet transform (CWT), apple orchard, soil, total nitrogen content, hyperspectral, inversion

CLC Number:

S153
S661.1

XIONG Chao-qun, XUN Mi, LI Jian, AN Miao, LI Guo-tian. Hyperspectral inversion of soil total nitrogen content in an apple orchard based on mathematical transformation and continuous wavelet transform[J]. HUBEI AGRICULTURAL SCIENCES, 2025, 64(11): 165-170.

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