Shifted excitation Raman difference spectroscopy as enabling technique for the analysis of animal feedstuff

Sowoidnich, Kay; Oster, Michael; Wimmers, Klaus; Maiwald, Martin

doi:10.1002/jrs.6140

Cited by 8 publications

(5 citation statements)

References 66 publications

(71 reference statements)

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“…A similar issue with highly fluorescent/luminescent specimens has already been reported in another study conducted by our group. 33 To remove such outliers from the spectral data set, for each sample an empirically determined threshold of four times the mean intensity of the spectra recorded at the 100 different locations was calculated. On the one hand, this threshold allowed to reliably identify outliers but on the other hand it enabled to retain the natural variability of Raman signal intensities recorded on heterogenous soil.…”

Section: Methodsmentioning

confidence: 99%

Determination of Soil Constituents Using Shifted Excitation Raman Difference Spectroscopy

2022

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Soil analysis to estimate soil fertility parameters is of great importance for precision agriculture but nowadays it still relies mainly on complex and time-consuming laboratory methods. Optical measurement techniques can provide a suitable alternative. Raman spectroscopy is of particular interest due to its ability to provide a molecular fingerprint of individual soil components. To overcome the major issue of strong fluorescence interference inherent to soil, we applied shifted excitation Raman difference spectroscopy (SERDS) using an in-house-developed dual-wavelength diode laser emitting at 785.2 and 784.6 nm. To account for the intrinsic heterogeneity of soil components at the millimeter scale, a raster scan with 100 individual measurement positions has been applied. Characteristic Raman signals of inorganic (quartz, feldspar, anatase, and calcite) and organic (amorphous carbon) constituents within the soil could be recovered from intense background interference. For the first time, the molecule-specific information derived by SERDS combined with partial least squares regression was demonstrated for the prediction of the soil organic matter content (coefficient of determination R2 = 0.82 and root mean square error of cross validation RMSECV = 0.41%) as important soil fertility parameter within a set of 33 soil specimens collected from an agricultural field in northeast Germany.

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Section: Methodsmentioning

confidence: 99%

Determination of Soil Constituents Using Shifted Excitation Raman Difference Spectroscopy

2022

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“…The observed band is rather due to residual contributions from intense and spectrally narrow luminescence bands that have already been observed and discussed in our previous studies on different phosphate species. [ 5,57 ] This type of luminescence feature is likely caused by impurities due to rare earth elements and has been reported for apatites before. [ 58 ]…”

Section: Resultsmentioning

confidence: 60%

Shifted excitation Raman difference spectroscopy for soil component identification and soil carbonate determination in the presence of strong fluorescence interference

Sowoidnich

Maiwald

Ostermann

et al. 2023

J Raman Spectroscopy

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Detailed knowledge about soil composition is an important prerequisite for many applications, for example precision agriculture. Current standard laboratory methods are complex and time‐consuming but could be complemented by non‐invasive optical techniques. Its capability to provide a molecular fingerprint of individual soil components makes Raman spectroscopy a very promising candidate. A major challenge is strong fluorescence interference inherent to soil, but this issue can be overcome effectively using shifted excitation Raman difference spectroscopy (SERDS). A customized dual‐wavelength diode laser emitting at 785.2 and 784.6 nm was used to investigate 117 soil samples collected from an agricultural field along a distance of 624 m and down to depths of 1 m. To address soil spatial heterogeneity, a raster scan approach comprising 100 measurement spots per sample was applied. Based on the Raman spectroscopic fingerprint extracted from intense fluorescence interference by SERDS, 13 mineral soil constituents were identified, and even closely related molecular species could be discriminated, for example polymorphs of titanium dioxide and calcium carbonate. For the first time, the capability of SERDS is demonstrated to predict the calcium carbonate content as an important soil parameter using partial least squares regression (R2 = 0.94, root mean square error of cross‐validation RMSECV = 2.1%). Our findings demonstrate that SERDS can extract a wealth of spectroscopic information from disturbing backgrounds enabling qualitative and quantitative soil analysis. This highlights the large potential of SERDS for precision agriculture but also in further application areas, for example geology, cultural heritage and planetary exploration.

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“…SERDS can obtain molecular vibration, rotation, and other information from spectrum analysis, effectively analyze molecular structure and functional groups, and can combine with various chemometrics methods to model and process data. As an advanced NDT method [21,22], SERDS not only has the advantages of traditional Raman spectroscopy such as simple operation and no special sample pretreatment, but also can eliminate strong fluorescence interference, filter interference peaks, and improve signal-to-noise ratio by mathematical means. It can be well applied to NTD of paper cup in customs, border inspection, on-site, and other scenes.…”

Section: Introductionmentioning

confidence: 99%

A rapid and non‐destructive identification for paper cup evidence based on shifted‐excitation Raman difference spectroscopy and SOM clustering

Tian,

Jiang,

Zhang

2023

Journal of Forensic Sciences

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In order to achieve rapid, non‐destructive, efficient, and accurate classification of paper cup samples, we propose a classification model that integrates shifted‐excitation Raman difference spectroscopy (SERDS) with self‐organizing map (SOM) and Bayesian optimization–support vector machine (BO‐SVM). We collected differential Raman data from 52 paper cup samples using SERDS, with an excitation wavelength range of 784–785 nm, a laser power of 440 mW, an integration time of 10 s, and a spectral range spanning from 280 to 2700 cm−1. Subsequently, principal component analysis (PCA) was applied to reduce the dimensionality of the data. The SOM clustering outcomes were utilized as the foundation for constructing the discriminant analysis (FDA) and BO‐SVM classification models. The primary constituent of the paper cup samples was identified as cellulose, while additional fillers such as talc, calcium carbonate, and kaolin were also present. The SOM clustering categorized the samples into seven distinct groups. The FDA model achieved a classification accuracy of 92.3%, and the BO‐SVM model reached a classification accuracy of 96.2%. The SOM clustering effectively discerned samples with different fillers, as evidenced by distinct peak numbers and shapes in the differential Raman spectra, thereby underscoring the practical significance of SOM clustering. In comparison with FDA, BO‐SVM exhibited enhanced classification accuracy and exceptional performance in handling outliers and linearly inseparable data, indicating its superior generalization capabilities.

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Shifted excitation Raman difference spectroscopy as enabling technique for the analysis of animal feedstuff

Cited by 8 publications

References 66 publications

Determination of Soil Constituents Using Shifted Excitation Raman Difference Spectroscopy

Determination of Soil Constituents Using Shifted Excitation Raman Difference Spectroscopy

Shifted excitation Raman difference spectroscopy for soil component identification and soil carbonate determination in the presence of strong fluorescence interference

A rapid and non‐destructive identification for paper cup evidence based on shifted‐excitation Raman difference spectroscopy and SOM clustering

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