The Effects of Drying Temperature on Nitrogen Concentration Detection in Calcium Soil Studied by NIR Spectroscopy

Nie, Ping; Dong, Tao; He, Yong; Xiao, Shupei; Qu, Fangfang; Lin, Lie

doi:10.3390/app8020269

Cited by 10 publications

(8 citation statements)

References 38 publications

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“…The noise caused by the equipment and the interference of the fluorescence background in the Raman signal could affect the detection results. Therefore, five pretreatment methods were applied to preprocessing the original Raman spectra in this paper [ 39 ]. For this paper, four spectral preprocessing methods were applied to dealing with the original spectra.…”

Section: Methodsmentioning

confidence: 99%

Density Functional Theory Analysis of Deltamethrin and Its Determination in Strawberry by Surface Enhanced Raman Spectroscopy

Dong

Lin

et al. 2018

Molecules

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Deltamethrin is widely used in pest prevention and control such as red spiders, aphids, and grubs in strawberry. It is important to accurately monitor whether the deltamethrin residue in strawberry exceeds the standard. In this paper, density functional theory (DFT) was used to theoretically analyze the molecular structure of deltamethrin, gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were used to enhance the surface enhanced Raman spectroscopy (SERS) detection signal. As a result, the theoretical Raman peaks of deltamethrin calculated by DFT were basically similar to the measured results, and the enhancing effects based on AuNPs was better than that of AgNPs. Moreover, 554, 736, 776, 964, 1000, 1166, 1206, 1593, 1613, and 1735 cm−1 could be determined as deltamethrin characteristic peaks, among which only three Raman peaks (736, 1000, and 1166 cm−1) could be used as the deltamethrin characteristic peaks in strawberry when the detection limit reached 0.1 mg/L. In addition, the 500–1800 cm−1 SERS of deltamethrin were analyzed by the partial least squares (PLS) and backward interval partial least squares (BIPLS). The prediction accuracy of deltamethrin in strawberry (Rp2 = 0.93, RMSEp = 4.66 mg/L, RPD = 3.59) was the highest when the original spectra were pretreated by multiplicative scatter correction (MSC) and then modeled by BIPLS. In conclusion, the deltamethrin in strawberry could be qualitatively analyzed and quantitatively determined by SERS based on AuNPs enhancement, which provides a new detection scheme for deltamethrin residue determination in strawberry.

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Section: Methodsmentioning

confidence: 99%

Density Functional Theory Analysis of Deltamethrin and Its Determination in Strawberry by Surface Enhanced Raman Spectroscopy

Dong

Lin

et al. 2018

Molecules

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“…In this paper, R 2 c and R 2 p represent the coefficient of the determination of the calibration set and the prediction set respectively, while RMSE c and RMSE p represent the root mean square error of the calibration set and the prediction set respectively. In addition, the RPD was suggested to be at least three for agriculture applications; while 2 < RPD <3 indicated a model with a good predictive ability; 1.4 < RPD < 2 was an intermediate model needing some improvement; and RPD < 1.4 indicated that the model had a poor predictive ability [28].…”

Section: Model Evaluation Indexmentioning

confidence: 99%

Rapid and Quantitative Determination of Soil Water-Soluble Nitrogen Based on Surface-Enhanced Raman Spectroscopy Analysis

Dong

Xiao

et al. 2018

Applied Sciences

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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 2 p = 0.91, RMSE p = 8.76 mg/L, RPD = 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 2 p = 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.

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“…They concluded that the smaller the soil particle diameter, the higher the estimation accuracy of the total nitrogen (TN) content, where the model established by the support vector machine (SVM) is superior to partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR). Nie et al [15] studied the influence of drying temperatures on soil nitrogen determination by near-infrared spectroscopy. Low or extremely high drying temperatures will adversely affect soil nitrogen detection, and a drying temperature of 40°C and competitive adaptive reweighted squares-backward interval partial least squares-partial least squares (CARS-BIPLS-PLS) method is the best method to improve the soil nitrogen detection accuracy.…”

Section: Introductionmentioning

confidence: 99%

Method for detecting soil total nitrogen contents based on pyrolysis and artificial olfaction

Zhu

et al. 2022

International Journal of Agricultural and Biological Engineering

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Soil nitrogen is an essential nutrient element for crop growth and development, and an important indicator of soil fertility characteristics. This study proposed a method based on pyrolysis and artificial olfaction to quickly and accurately determine the soil total nitrogen (STN) content. A muffle furnace was used to pyrolyze the soil samples, and ten different types of oxide semiconductor gas sensors were used to construct a sensor array to detect the soil samples' pyrolysis gas. The response curves of the sensors were tested at pyrolysis temperatures of 200°C, 300°C, 400°C, and 500°C and at pyrolysis times of 1 min, 3 min, 5 min, and 10 min to obtain the optimal pyrolysis state of the soil samples. The optimal pyrolysis temperature was 400°C, and the pyrolysis time was 3 min. The response area, maximum value, average differential coefficient, variance value, maximum gradient value, average value, and 8th-second transient value of the sensor response curve were extracted to construct an artificial olfactory feature space of 121×10×7 (121 soil samples, ten sensor numbers, seven extracted eigenvalues). Back-propagation neural network algorithm (BPNN), partial least squares regression algorithm (PLSR), and partial least squares regression combined with back-propagation neural network algorithm (PLSR-BPNN) were used to establish a prediction model of artificial olfactory feature space and STN content. Moreover, coefficient of determination (R 2 ), root mean square error (RMSE), and the ratio of performance to deviation (RPD) were used as the performance indicators of the prediction results. The test results showed that the R 2 of the PLSR, BPNN, and PLSR-BPNN models were 0.89033, 0.81185, and 0.92186, and the RMSE values were 0.24297, 0.37370, and 0.21781, and the RPD were 2.9964, 1.9482, and 3.3426, respectively. The model established by the PLSR-BPNN algorithm has the highest R 2 and RPD and the smallest RMSE, can achieve the accurate prediction of STN content, and therefore the model is rated as "excellent". The detection method in this study achieves a low-cost, rapid, and accurate determination of STN content, and provides a new reference for the measurement of STN.

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The Effects of Drying Temperature on Nitrogen Concentration Detection in Calcium Soil Studied by NIR Spectroscopy

Cited by 10 publications

References 38 publications

Density Functional Theory Analysis of Deltamethrin and Its Determination in Strawberry by Surface Enhanced Raman Spectroscopy

Density Functional Theory Analysis of Deltamethrin and Its Determination in Strawberry by Surface Enhanced Raman Spectroscopy

Rapid and Quantitative Determination of Soil Water-Soluble Nitrogen Based on Surface-Enhanced Raman Spectroscopy Analysis

Method for detecting soil total nitrogen contents based on pyrolysis and artificial olfaction

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