Abstract
An accurate and rapid determination of soil water-soluble nitrogen is conducive to scientific fertilization in precision agriculture. Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive fingerprint with the advantages of simple operation and high detection efficiency. In this paper, partial least squares (PLS), principal components analysis (PCA), and least squares supports vector machine (LS-SVM) were applied to analyze the relationship between soil water-soluble nitrogen concentration and SERS. The results showed that the SERS-enhancing effect based on Opto Trace Raman 202 (OTR 202) was better than that of silver nanosubstrate and gold nanosubstrate. In addition, the prediction accuracy of soil water-soluble nitrogen in PLS was the highest ( R p 2 = 0.91 , RMSE p = 8.76 mg / L , R P D = 3.00 ) when the original spectra were preprocessed with first-derivative. Moreover, 1028, 1370, 1436, and 1636 cm−1 could be determined as characteristic peaks of soil water-soluble nitrogen, the association between soil water-soluble nitrogen concentration and a SERS intensity of 1370 cm−1 was the highest ( R p 2 = 0.94 ) , and the regression equation was y = 93.491x + 1771.5. Beyond that, the prediction accuracy of distinguishing between a low soil water-soluble nitrogen concentration (22.7–63.7 mg/L) and a high soil water-soluble nitrogen concentration (70.5–118.3 mg/L) based on PCA and LS-LVM was 86.67%. In conclusion, soil water-soluble nitrogen could be detected rapidly and quantitatively using SERS, which was beneficial to provide a rapid, accurate, and reliable scheme for scientific and precise fertilization.
Highlights
Soil nitrogen is the key parameter supporting plant growth and development
The results indicated that the nondestructive approach could identify active nitrogen assimilation cells for genomic analysis and provide a theoretical basis for further comprehending the nitrogen metabolism of environmental microorganisms
The principle of the standard normal variation (SNV) algorithm is that the scattering intensity values of each wavelength point satisfies a certain distribution in each spectrum, and the spectral correction was carried out according to this assumption [22]
Summary
Soil nitrogen is the key parameter supporting plant growth and development. There are many forms of nitrogen in soil, with soil water-soluble nitrogen being one of the more important substances that plants can absorb directly [1]. The acid hydrolysis [3], the alkali hydrolysis diffusion [4], and the alkaline hydrolysis distillation [5] methods are the traditional chemical methods for the determination of soil water-soluble nitrogen. These methods are highly sensitive, the disadvantages of tedious measurement, long detection time, and expensive reagent limit their development [6]. Spectral technology has been widely applied to soil nitrogen detection, among which near infrared spectroscopy has certain advantages and application prospects [7,8]. We established the regression equation between SERS characteristic peaks intensity and soil water-soluble nitrogen, which helped to improve the efficiency of soil water-soluble nitrogen detection and provide a scientific guidance for urea fertilization
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