• Spectroscopy and Spectral Analysis
  • Vol. 42, Issue 3, 984 (2022)
ZHAO Rui1、1;, SONG Hai-yan1、1; *;, ZHAO Yao2、2;, SU Qin1、1;, LI Wei1、1;, SUN Yi-shu1、1;, and CHEN Ying-min1、1;
Author Affiliations
  • 11. College of Agricultural Engineering, Shanxi Agricultural University, Taigu 030800, China
  • 22. College of Horticulture, Shanxi Agricultural University, Taigu 030800, China
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    DOI: 10.3964/j.issn.1000-0593(2022)03-0984-06 Cite this Article
    Rui ZHAO, Hai-yan SONG, Yao ZHAO, Qin SU, Wei LI, Yi-shu SUN, Ying-min CHEN. Research on Anti-Moisture Interference Soil Organic Matter Model Based on Characteristic Wavelength Integration Algorithm[J]. Spectroscopy and Spectral Analysis, 2022, 42(3): 984 Copy Citation Text show less

    Abstract

    As an important component in soil, soil organic matter (SOM) is a critical nutrition index in the process of crop growth. Rapid and accurate detection of SOM content is of great significance for the fertilization management. In recent years, NIR has been widely used in the rapid detection of SOM. However, soil moisture is one of the important factors that affect the prediction results of SOM. In this study, 140 soil samples were collected in Shanxi Province, and the spectral information with different water content (0%, 5%, 10%, 15%, 17%) was collected by ASD spectrometer (350~2 500 nm). In order to improve the accuracy of the SOM prediction model, a characteristic wavelength integration algorithm (taking the integral absorbance value at characteristic wavelength as the independent variable) was proposed. The results show that: (1) the statistical parameters of the SOM prediction model established by this algorithm are better than the traditional characteristic wavelength modeling method; (2) the moisture correction model established by this algorithm can eliminate the influence of moisture, and the corrected spectra of wet soil samples are closer to the corresponding dry soil samples; (3) the prediction accuracy of wet soil samples is improved. The RP increased by about 0.09 and RMSEP decreased by about 1.72. The results show that the method can effectively reduce the influence of soil moisture on the spectral characteristics of SOM, improve the prediction accuracy of SOM with different water content, and provide theoretical support for the subsequent instrument development.

    Introduction

    Near-infrared spectroscopy (NIRS) has been widely used in analysing and detecting material components in the agricultural field due to its advantages of high efficiency, rapid measurement, and non-destructivity. The soil organic matter (SOM) content is an important indicator to measure soil fertility. The measurement of SOM by NIRS has become an important direction in soil science research.

    Copy Citation Text
    Rui ZHAO, Hai-yan SONG, Yao ZHAO, Qin SU, Wei LI, Yi-shu SUN, Ying-min CHEN. Research on Anti-Moisture Interference Soil Organic Matter Model Based on Characteristic Wavelength Integration Algorithm[J]. Spectroscopy and Spectral Analysis, 2022, 42(3): 984
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