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- 实验方案
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Comparison of Calibration Approaches in Laser-Induced Breakdown Spectroscopy for Proximal Soil Sensing in Precision Agriculture
摘要： The lack of soil data, which are relevant, reliable, a?ordable, immediately available, and su?ciently detailed, is still a signi?cant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within ?elds, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, di?erent calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural ?elds in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The ?rst method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both ?elds. The second univariate model derived the calibration from the reference analytics of all samples from one ?eld. The prediction is validated by LIBS data of the second ?eld. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the ?rst ?eld are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the ?rst ?eld and independently on the second ?eld data. The second univariate method yielded better calibration and prediction results compared to the ?rst method, since matrix e?ects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.
关键词： laser-induced breakdown spectroscopy,soil nutrients,elemental composition,proximal soil sensing,LIBS
更新于2025-09-12 10:27:22
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[IEEE 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) - Amsterdam, Netherlands (2019.9.24-2019.9.26)] 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) - Closed-Loop Moving Windows Wavelength Selection Method With Application To Near-Infrared Spectroscopic Analysis
摘要： Wavelength selection plays a very important role in near-infrared (NIR) spectroscopy, which has always been an important research direction. Based on the reverse-deletion waveband idea, the closed-loop moving window-partial least squares (closed-loop MW-PLS) method was proposed, which can eliminate interference wavelengths and enable flexible multi-band wavelength selection. NIR analysis of soil organic matter was taken as an example to evaluate the performance of closed-loop MW-PLS. And the MW-PLS was also used for comparison. The proposed algorithm traversed all the sub-bands of the original range to perform forward and backward optimization. The forward optimization was just the original MW-PLS. Therefore, the closed-loop MW-PLS completely covered the MW-PLS. The results of soil organic matter indicated that the close-loop MW-PLS was strictly superior to original MW-PLS, and the method extension was meaningful and had no increase in operational complexity. We believe that the closed-loop MW-PLS method will have a wider application.
关键词： soil,organic matter,closed-loop moving window-partial least squares,wavelength model optimization,Near-infrared spectroscopic analysis
更新于2025-09-12 10:27:22
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Optical Fiber Strain Measurements and Numerical Modeling of Load Tests on Grouted Anchors
摘要： This paper reports on the behavior of a grouted anchor instrumented with a fiber optic strain sensor in the grout body along the entire anchor length. During load tests up to the estimated pull-out capacity, the strain measurements indicate that a delamination occurs in the tendon bond length between the steel tendons and the grout body. The upper delaminated part of the grout body is under compression, whereas the lower bonded part of the grout body is under tension. This delamination gradually progresses as the anchor load increases. Furthermore, a significant part of the load is transferred from the anchor to the soil in the tendon free length. The anchor behavior is further modeled with a one-dimensional finite-element model that includes the steel tendons and the grout body, where an interface damage model is used to account for possible delamination of the interface. The numerical model confirms that the observed compressive and tensile strains in the grout can be related to a delamination of the steel strands in the tendon bond length. The experiment and numerical modeling demonstrate how optical fiber measurements in the grout body can be used, in operational conditions, to assess the anchor behavior, the mobilization of the soil resistance, and the estimation of the remaining anchor capacity.
关键词： soil resistance,fiber optic strain sensor,grouted anchor,delamination,finite-element model
更新于2025-09-12 10:27:22
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Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
摘要： Release of carbon from high-latitude soils to the atmosphere may have significant effects on Earth’s climate. In this contribution, we evaluate visible–near-infrared spectroscopy (vis-NIRS) as a time- and cost-efficient tool for assessing soil organic carbon (SOC) concentrations in South Greenland. Soil samples were collected at two sites and analyzed with vis-NIRS. We used partial least square regression (PLS-R) modeling to predict SOC from vis-NIRS spectra referenced against in situ dry combustion measurements. The ability of our approach was validated in three setups: (1) calibration and validation data sets from the same location, (2) calibration and validation data sets from different locations, and (3) the same setup as in (2) with the calibration model enlarged with few samples from the opposite target area. Vis-NIRS predictions were successful in setup 1 (R2 = 0.95, root mean square error of prediction [RMSEP] = 1.80 percent and R2 = 0.82, RMSEP = 0.64 percent). Predictions in setup 2 had higher errors (R2 = 0.90, RMSEP = 7.13 percent and R2 = 0.78, RMSEP = 2.82 percent). In setup 3, the results were again improved (R2 = 0.95, RMSEP = 2.03 percent and R2 = 0.77, RMSEP = 2.14 percent). We conclude that vis-NIRS can obtain good results predicting SOC concentrations across two subarctic ecosystems, when the calibration models are augmented with few samples from the target site. Future efforts should be made toward determination of SOC stocks to constrain soil–atmosphere carbon exchange.
关键词： visible–near-infrared spectroscopy,subarctic,Soil organic carbon,Greenland
更新于2025-09-12 10:27:22
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Applications of Laser-Induced Breakdown Spectroscopy for Soil Analysis, Part I: Review of Fundamentals and Chemical and Physical Properties
摘要： Laser-induced breakdown spectroscopy (LIBS) has become a prominent analytical technique in recent years for real-time characterization of soil properties. However, only a few studies of soil chemical and physical properties have been reported using LIBS until recently. The aims of this article are to: (1) provide the basic principles of LIBS for soil analysis and (2) present the use of LIBS for soil pH, soil texture, and humification degree of soil organic matter (SOM). The second article will cover soil classification and soil elemental analysis, including plant nutrients, carbon (C), and toxic elements. LIBS is a multi-element analytical technique based on atomic spectroscopy that employs a high-energy laser pulse focused onto a sample surface to create a transient plasma. It is a spectroscopic analytical technique that requires very little or no sample preparation, examines each sample in seconds, and offers a flexible platform for the examination of a broad array of elements in the sample. LIBS also can be used to infer soil chemical and physical properties if a relationship exists between the chemical composition and the soil properties. With proper calibration, LIBS has a great potential for real-time in-field soil analysis and precision farming that could lead to improved soil management and agricultural production, and reduced agricultural environmental impacts.
关键词： humification degree of soil organic matter,soil texture,precision agriculture,soil sensing,soil analysis,soil pH
更新于2025-09-11 14:15:04
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Applications of Laser-Induced Breakdown Spectroscopy for Soil Characterization, Part II: Review of Elemental Analysis and Soil Classification
摘要： In-field soil health assessments, including plant nutrients and toxic elements, are needed and could improve the sustainability of agriculture production. Among the available analytical techniques for these analyses, laser-induced breakdown spectroscopy (LIBS) has become one of the most promising techniques for real-time soil analysis at low cost and without the need of reagents. The first part of this two-part review (Part I, Villas-Boas et al., 2019) in this issue focused on the fundamentals of LIBS for soil analysis and its use for soil chemical and physical characterization. Our objectives in this review article (Part II) are to review (i) the main applications of LIBS in the determination of soil carbon (C), nutrients and toxic elements, spatial elemental mapping, and (ii) its use in soil classification. Traditional and more recent techniques will be compared to LIBS, considering their advantages and disadvantages. LIBS is a promising, versatile technique for detecting many elements in soil samples, requires little or no sample preparation, takes only a few seconds per sample, and has a low cost per sample compared to other techniques. However, overcoming matrix effects is a challenge for LIBS applications in soil analysis, since most studies are conducted with limited changes in the matrix. In spite of the limitation of matrix effects, a typical LIBS system has a limit of detection of 0.3, 0.6, 4, 7, 10, 18, 46, and 89 mg kg-1 for Mo, Cu, Mg, Mn, Fe, Zn, K, and Ca, respectively. LIBS holds potential for real-time in-field spatial elemental analysis of soils and practical applications in precision farming with proper calibration. This could lead to immediate diagnoses of contaminated soil and inefficient nutrient supplies and facilitate well-informed soil management, increasing agricultural production while minimizing environmental impacts.
关键词： soil contamination,soil fertility,rhizosphere,toxic elements,spatial elemental mapping,SOM,precision agriculture,Plant nutrients,soil carbon
更新于2025-09-11 14:15:04
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Subwavelength polarization optics via individual and coupled helical traveling-wave nanoantennas
摘要： Soil spectral allocation or classification is usually conducted on air-dried soils. However, the field soils are not all air-dried, and the change of soil moisture will affect soil reflectance. We introduce a soil allocation model that considers the effect of soil moisture for the purpose of eliminating the effect of soil moisture. The topsoil spectral curves of four typical soils from the Songnen Plain in Northeast China were re-sampled to 10-nm intervals and converted to first-derivative spectral curves and continuum removal curves. The spectral feature parameters were extracted from continuum removal curves in the visible-near infrared (VNIR) range (350–2500 nm), and the range of 430–2400 nm was used to build soil allocation models for reducing the effect of noise. Samples with different soil moisture were mixed into air-dried soils and we calculated the coefficient of variation (CV) of different inputs to assess the effect of soil moisture and to find allocation indices that were not affected by soil moisture. We used allocation indices of Zhang et al. (2018) because of the high accuracy of their DT (Decision Tree) model to allocate mixed-soil samples. We also used allocation indices that were not affected by soil moisture to allocate mixed-soil samples with decision tree (DT), multinomial logistic regression (MLR) and multi-layer perception neural network (MLPNN), and compared the results of the two methods. The results show the following: 1) As SFPs were built with shorter bands, SFP was less sensitive to soil moisture than PCR and PCFD and thus SFP is more suitable to build soil allocation models that consider the effect of soil moisture as input than PCR and PCFD. 2) Differences in soil moisture had little effect on absorption valley shoulders, symmetry and absorption positions, moderate effect on absorption area and depth, and a major effect on the slope of different bands. 3) The effect of soil moisture on continuum removal curves of different soil classes was variable. There was little effect on Arenosols, a moderate effect on Chernozems and Cambisols, and a large effect on Phaeozems. 4) The accuracy of the DT model using allocation indices that were not affected by soil moisture was 91.892% with a Kappa coefficient of 0.888. Our results suggest that it is feasible to build soil spectral allocation models that are not affected by soil moisture, and this improves the universality of soil spectral allocation, especially to field soils, which can be of considerable help in soil classification.
关键词： Decision tree,Visible-near infrared,Soil moisture,Spectral feature parameter,Soil spectral allocation
更新于2025-09-11 14:15:04
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A Self-Adaptive Model for the Prediction of Soil Organic Matter Using Mid-Infrared Photoacoustic Spectroscopy
摘要： Fast quantification of soil organic matter (SOM) is important in crop production and soil fertility evaluation. Fourier-transform infrared (FTIR) spectroscopy has been widely utilized for rapid, cost-effective, and non-destructive SOM determination. However, the lack of accuracy has limited the application of FTIR spectroscopy to quantitative SOM prediction because the models are built from a typical database, resulting in large errors in new independent samples. In this study, using 933 paddy soil samples collected in Lishui, China, a “self-adaptive” model was designed for predicting SOM content, in conjunction with Fourier-transform mid-infrared photoacoustic spectroscopy (FTIR-PAS). The resulting FTIR-PAS spectra afforded abundant soil information, reflected in O–H, N–H, and C–H vibrations (4000–2800 cm?1), C=O and C–H vibrations (2500–1200 cm?1), and the fingerprint region (1200–500 cm?1). The self-adaptive model was established by: (i) identification of soil samples, selected by Euclidean distance, with soil spectra to similar the target (unknown) soil sample and ranking of the Euclidean distance values in ascending order; (ii) selection of the optimal parameters to build a partial least squares (PLS) model based on an optimal calibration sample subset; and (iii) prediction and validation of the unknown soil sample. The predictive capabilities of the self-adaptive model and conventional PLS model were compared; the self-adaptive and conventional PLS models had R2 values of 0.9293 and 0.5796, root mean square errors of prediction of 1.65 and 3.26 g kg?1, and ratios of percentage deviation (RPD) of 3.18 and 1.62, respectively. Therefore, the self-adaptive model showed greater potential for application, having significantly enhanced applicability while improving the accuracy of prediction.
关键词： Fourier-transform mid-infrared photoacoustic spectroscopy,partial least squares,paddy soils,self-adaptive model,soil organic matter
更新于2025-09-11 14:15:04
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Elucidating molecular level impact of peat fire on soil organic matter by laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry
摘要： In this work, laser desorption ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (LDI–FTICRMS) was used to investigate the molecular composition of a peat fire and laboratory heated soil organic matter (SOM). SOM isolated from soils obtained from unburned and burned sites at Central Kalimantan, Indonesia, were analyzed with LDI–FTICRMS. About 7500 peaks were found and assigned with molecular formulas for each mass spectrum. SOM isolated from fire-affected soil sites are relatively more abundant in low oxygenated classes (e.g., O1–O5) and thermally stable compounds, including condensed hydrocarbon and nitrogen heterocyclic compounds. Abundances of highly condensed hydrocarbon compounds with carbon number > 30 were increased for the fire-affected SOM. In vivo heating experiments were conducted for SOM extracted from unburned sites, and the prepared SOMs were analyzed with LDI–FTICRMS. Overall, the same trend of change at the molecular level was observed from both the laboratory heated and the peat fire-affected SOM samples. In addition, it was observed that heat caused the degradation of SOM, generating lignin and tannin-type molecules. It was hypothesized that they were formed by thermal degradation of high molecular weight SOM. All the information presented in this study was obtained by consuming ~ 5 μg of sample. Therefore, this study shows that LDI–FTICRMS is a sensitive analytical technique that is effective in obtaining molecular level information of SOM.
关键词： Soil organic matter,Molecular transformation,LDI–FTICRMS,Peat fire
更新于2025-09-11 14:15:04
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Investigating the impact of anthropogenic land use on a hemiboreal lake ecosystem using carbon/nitrogen ratios and coupled-optical emission spectroscopy
摘要： Anthropogenic impacts on lake ecosystems have increased substantially towards the present. However, the strength and timing in most cases are not evaluated in detail, missing valuable information on the response and recovery of an aquatic system. In this study, we use the sediment total organic carbon/total nitrogen ratio (C/N) and inductively coupled-optical emission spectroscopy (ICP-OES) elements and the available information about the biological processes to explore anthropogenic land use impact on the lake ecosystem. As a case study we selected a hemiboreal lake Trikātas (Latvia, NE Europe). The Pearson correlation was used to statistically test the correlations of all variables. Our results show that the C/N ratio lowered immediately with the onset of crop cultivation at 500 BCE. Extensive forest clearance and an abrupt increase in land use are re?ected through the associated chemical elements from ICP-OES and the increasing presence of herbivore dung spores since 1200 CE. These changes concur with the excess of ?sh remains suggesting a decrease in ?sh populations. Interestingly, anthropogenic land use driven erosion and accompanied calcium carbonate (CaCO3) matter in?ux favoured the abundance of Chara spp. in Lake Trikātas since 500 CE, which currently forms the protected speci?c habitat-type (H3140) of the European Union. At present, speci?c submerged macrophyte Chara habitat-type diminished almost entirely due to increased nutrient input, phytoplankton blooming, hypertrophic conditions and reduced light availability. The continued land use practices led to a switch in organic matter source in the lake from macrophytes to solely algal origin. The current study underlines the need of additional methods used to detect the sensitivity of lake ecosystem to external disturbances such as minor anthropogenic land use that might not necessarily be apparent in more traditional analyses such as palynology.
关键词： Environmental change,Soil erosion,Non-pollen palynomorphs,EU H3140,Paleolimnology,Chara
更新于2025-09-11 14:15:04