Application Of Mid-infrared Spectroscopy Research Articles

ПОТЕНЦИАЛ ИСПОЛЬЗОВАНИЯ ИНФРАКРАСНОЙ СПЕКТРОМЕТРИИ В СРЕДНЕМ ДИАПАЗОНЕ ДЛЯ ОЦЕНКИ КАЧЕСТВА ПИЩЕВОГО РЫБНОГО СЫРЬЯ

The application of mid infrared spectroscopy with Fourier-transform provide to determine the quality of fish raw materials. This method could be noted lipid oxidation, water content and protein degradation of fish food raw materials. Mid-infrared spectroscopy as a new tool for the evaluation of fish freshness might to distinguish between fresh, chilled and frozen-thawed sevruga sturgeon samples. This allows to proposed this tool for authentication of fish and fish products.

Classification of Lubricating Oil Types Using Mid-Infrared Spectroscopy Combined with Linear Discriminant Analysis–Support Vector Machine Algorithm

To realize the classification of lubricating oil types using mid-infrared (MIR) spectroscopy, linear discriminant analysis (LDA) was used for the dimensionality reduction of spectrum data, and the classification model was established based on the support vector machine (SVM). The spectra of the samples were pre-processed by interval selection, Savitzky–Golay smoothing, multiple scattering correction, and normalization. The Kennard–Stone algorithm (K/S) was used to construct the calibration and validation sets. The percentage of correct classification (%CC) was used to evaluate the model. This study compared the results obtained with several chemometric methods: PLS-DA, LDA, principal component analysis (PCA)-SVM, and LDA-SVM in MIR spectroscopy applications. In both calibration and verification sets, the LDA-SVM model achieved 100% favorable results. The PLS-DA analysis performed poorly. The cyclic resistance ratio (CRR) of the calibration set was classified via the LDA and PCA-SVM analysis as 100%, but the CRR of the verification set was not as good. The LDA-SVM model was superior to the other three models; it exhibited good robustness and strong generalization ability, providing a new method for the classification of lubricating oil types by MIR spectroscopy.

The Potential Use of Near- and Mid-Infrared Spectroscopy in Kidney Diseases.

Traditional renal biomarkers such as serum creatinine and albuminuria/proteinuria are rather insensitive since they change later in the course of the disease. In order to determine the extent and type of kidney injury, as well as to administer the proper therapy and enhance patient management, new techniques for the detection of deterioration of the kidney function are urgently needed. Infrared spectroscopy is a label-free and non-destructive technique having the potential to be a vital tool for quick and inexpensive routine clinical diagnosis of kidney disorders. The aim of this review is to provide an overview of near- and mid-infrared spectroscopy applications in patients with acute kidney injury and chronic kidney disease (e.g., diabetic nephropathy and glomerulonephritis).

Performance of in situ vs laboratory mid-infrared soil spectroscopy using local and regional calibration strategies

Comparison of in situ mid-infrared spectroscopy (MIRS) with laboratory MIRS is required to demonstrate the accuracy of field-scale prediction of soil properties. Application of MIRS to investigate soil management questions must also be tested. Our objectives were therefore to determine i) the accuracy of lab vs in situ calibrations using various numbers of local and/or regional soils for prediction of organic carbon (OC), total nitrogen (TN), clay and pH; ii) effects of soil moisture content and variability on model performance for coarser and finer soils; and iii) if the method of OC determination (dry combustion vs MIRS-estimation) affects evaluation of tillage effects. Surface field MIRS measurements were made at three loess sites in Germany, each featuring three tillage treatments. Material (0–2 cm) was collected for lab MIRS measurements on dried/ground (<0.2 mm) soil and determination of OC, TN, clay and pH. Spectral Principal Component Analysis (PCA) was conducted and partial least squares regression models were created for several calibration strategies: 1) local calibrations trained with n = 40 or 20 soils and tested with n = 110 soils from the same site; 2) regional calibrations trained with n = 150 or 38 soils from two sites and validated with n = 110 soils from the third site; 3) regional calibrations trained with n = 150 or 38 soils from two sites and n = 20 double- or n = 10 quadruple-weighted “spiked” soils selected from the spectral PCA to be representative of the third site, and validation with n = 110 soils also from the third site. Spiking regional calibrations with local soils generally improved accuracy and decreased performance variability, though there were typically diminishing marginal returns to accuracy from increasing the number of local soils. The first two principal components of the lab-MIRS PCA correlated with OC, TN, clay and pH, while the field-MIRS PCA was dominated by soil moisture effects. Lab outperformed field MIRS for all models and properties. Lab MIRS n = 38 regional models were highly accurate for OC (ratio of prediction to interquartile distance (RPIQ) = 4.3) and TN (RPIQ = 6.7), and estimates detected the same significant differences between tillage treatments as analysis conducted with measured values—thus, small regional models can be considered optimal (balancing accuracy and workload). For field MIRS prediction of OC and TN, calibrations with 150 regional or 38 regional plus 10 quadruple-weighted local soils achieved satisfactory accuracy (RPIQ ≥ 1.89). Although predicted changes to OC in response to tillage were more biased for field MIRS, agreement with measured effects was achieved with n = 40 local models or spiked regional models. Thus, the higher efficiency of field measurement is counterbalanced by a more arduous calibration process to achieve satisfactory accuracy. Accuracies for clay (RPIQ = 0.89–2.8) and pH (RPIQ = 0.60–3.2) were lower and more variable than OC and TN for both devices—thus, spiking calibrations and using more soils than OC/TN calibrations are recommended. Soil moisture more negatively affected OC prediction than clay prediction. No simple trend was established for the performances of soil subsets with low, high or variable moisture content, but accuracy was most negatively affected by moisture for the site with the highest sand content.

Variability in Soil Chemical Quality in Traffic-dependent Zones within Field Headlands

ABSTRACT There is increased stress on soil and crop quality caused by machinery traffic during field operations in tillage systems, especially the area where the machinery turns, known as the headlands. While the influence of traffic on soil physical quality is understood, the impact on soil chemical quality and soil fertility is less so. Furthermore, correcting soil fertility and chemical quality in fields under cereal tillage requires strategic sampling due spatial variability, specifically in headlands. Using a simplified sampling strategy, the objective of this study was to examine the variability in soil chemical quality within traffic-dependent zones in the headland. In a case-study in Ireland, 41 fields under tillage were surveyed, and soil sampling zones delineated within headlands based on typical field traffic patterns. Soil phosphorus (P), potassium (K), lime requirement (LR), pH and organic matter (%OM) were measured at two depths. Elevated values of major nutrients (P, K) were recorded around the main headland tramline. Using a generalized linear mixed model, significant differences in P, K, LR and pH were found between headland zones, whereas %OM values did not vary significantly. In addition to laboratory analyses, predictions from mid-infrared spectroscopy (MIR) models resulted in similar patterns in %OM and LR with comparable statistical significance, which highlights the potential of MIR as an alternative to lab analysis of soil in traffic-dependent headland zones. Sampling headland zones to determine soil chemical quality coupled with the application of MIR for rapid soil analysis will improve decision support for soil management in tillage systems.

Soil organic carbon fractions in the Great Plains of the United States: an application of mid-infrared spectroscopy

Spectroscopy is a powerful means of increasing the availability of soil data necessary for understanding carbon cycling in a changing world. Here, we develop a calibration transfer methodology to appropriately apply an existing mid infrared (MIR) spectral library with analyte data on the distribution of soil organic carbon (SOC) into particulate (POC), mineral-associated (MAOC), and pyrogenic (PyC) forms to nearly 8000 soil samples collected in the Great Plains ecoregion of the United States. We then use this SOC fraction database in combination with a machine learning-based predictive soil mapping approach to explore the controls on the distribution of fractions through soil profiles and across the region. The relative abundance of each fraction had unique depth distribution profiles with POC fraction dropping exponentially with depth, the MAOC fraction having a broad distribution with a maxima at 35–50 cm, and the PyC fraction showed a slight subsurface maxima (10–20 cm) and then a steady decline with increasing depth. Within the Great Plains ecoregion, clay content was a strong control on the total amount and relative proportion of each fraction in both the surface and subsoil horizons. Sandy soils and soils in cool semi-arid regions contained significantly more POC relative to the MAOC and PyC fractions. Cultivated soils had significantly less SOC than grassland soils with losses following a predictable pattern: POC > MAOC ≫ PyC. This SOC fraction database and resulting maps can now form the basis for improved representation of SOC dynamics in biogeochemical models.

Mid-infrared spectroscopy for entomological purposes: A review

• MIRS is widely used for studying the chemical composition in food matrices. • However, it has found few applications in entomology to date. • Major applications include profiling cuticular hydrocarbons and in metabolomics. • Others are ID of cryptic species, detecting Wolbachia , sexing, and measuring age. • Characterisation of surface chemistry may assist in form-function studies. Mid-infrared spectroscopy (MIRS) is a well-established technique in the field of chemical analysis. Although it has been applied to problems in the entomological field for over 65 years, MIRS typically remains underutilised in this discipline. Potential applications of MIRS include profiling of cuticular hydrocarbons, taxonomic discrimination between cryptic species, sex discrimination, age prediction, detection of endosymbionts such as Wolbachia , and characterisation of the surface chemistry of insect body parts and products. The number of potential applications is expected to continue rising rapidly as MIR technology advances and it is adopted by more members of the entomological community.

Application of mid-infrared spectroscopy and PLS-Kernel calibration for quick detection of pork in higher value meat mixes

Analytical methods for meat-species identification and detection of adulteration are always needed for quality control and the safety of consumers. A novel application of PLS-Kernel with MIR for quick detection of pork in beef mixes down to 1.4 wt% is outlined. PLS-Kernel algorithm showed an excellent performance for handling many variables spectral data, which makes it suitable for food analysis by IR. Raw spectral data indicated a nonlinear relationship between pork level and IR band intensities of proteins and fats in the mixes. The ratios $${{\text{A}}_{\text{1654}\ \text{c}{{\text{m}}^{-1}}}}\ \left( \text{amid-I} \right)/{{\text{A}}_{\text{1745}\ \text{c}{{\text{m}}^{-1}}}}$$ (C=O band of ester), $${{\text{A}}_{\text{154}0\ \text{c}{{\text{m}}^{-1}}}}\ \left( \text{amid-II} \right)/{{\text{A}}_{\text{1745}\ \text{c}{{\text{m}}^{-1}}}}$$ , and $$\left( {{\text{A}}_{\text{1395}\ \text{c}{{\text{m}}^{-1}}}}\,+\,{{\text{A}}_{\text{145}0\ \text{c}{{\text{m}}^{-1}}}} \right)/{{\text{A}}_{\text{1175}\ \text{c}{{\text{m}}^{-1}}}}$$ were correlated with pork level to establish a useful analytical signal for detection purposes. Chemometric analysis was carried out on 900–1900 cm−1 as an informative spectral range for protein. PLS-Kernel model is recommended over PCR and PLS for handling many variables in IR data due to the lower computation cycles and less-memory storage. The proposed method would replace advanced techniques for quick pork detection in minced meat mixes.

Application of mid-infrared spectroscopy in analyzing different segmented production of Angelica by AB-8 macroporous resin

As complicated mixture systems, chemical components of Angelica are very difficult to identify and discriminate, so as not to control its quality effectively. In recent years, Mid-infrared spectroscopy has been innovatively employed to identify and assess the quality of Traditional Chinese medicine (TCM) products. In this paper, the macroscopic IR fingerprint method including Fourier transform infrared spectroscopy (FT-IR), the second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2D-IR), are applied to study and identify Angelica raw material, the decoction and different segmented production of AB-8 macroporous resin. FT-IR spectrum indicates that Angelica raw material is rich in sucrose and the correlation coefficient is 0.8465. The decoction of Angelica contains varieties of polysaccharides components and the content is gradually decreased with increasing concentration of ethanol. In addition, the decoction of Angelica contains a certain amount of protein components and 50% ethanol eluate has more protein than other eluates. Their second derivative spectra amplify the differences and reveal the potentially characteristic IR absorption bands, then we conclude that the decoction of Angelica contains a certain amount of ferulic acid and ligustilide. And 30% ethanol eluate, 50% ethanol eluate and 70% ethanol eluate are similar to ligustilide. Further, 2D-IR spectra enhance the spectral resolution and obtain much new information for discriminating the similar complicated samples. It is demonstrated that the above three-step infrared spectroscopy could be applicable for effective, visual and accurate analysis and identification of very complicated and similar mixture systems of traditional Chinese medicines.

Generation of broadband 17-μJ mid-infrared femtosecond pulses at 3.75 μm by silicon carbide crystal.

In this contribution, we report the generation of 17-μJ mid-infrared (MIR) pulses with duration of 70 fs and bandwidth of 550 nm centered at 3.75 μm at 1-kHz repetition rate, by a two-stage femtosecond optical parametric amplifier utilizing 4H-silicon carbide crystal as the nonlinear medium. The crystal is selected as it processes orders of magnitude higher damage threshold than traditional MIR nonlinear crystals, and it supports extreme broad parametric bandwidth. With its distinguished features such as MIR central wavelength, ultra-broad bandwidth, self-stable carrier-envelope phase, and potential for energy scaling, this kind of MIR source holds promise for new approaches to extreme short isolated attosecond pulse generation as well as MIR spectroscopy applications.

Application of Mid-Infrared Spectroscopy to the Development and Transfer of a Manufacturing Process for an Active Pharmaceutical Ingredient

The use of in situ mid-infrared spectroscopy to support the development of a pharmaceutical manufacturing process is disclosed. Data on this two-stage telescoped reaction from several reaction scales (<50 mL to 1600 liters) and at multiple manufacturing locations is shown. In addition to providing data on both reactions in the telescope, the mid-IR data has been used to monitor an intermediate distillation operation and therefore it has been possible to profile the whole process. Data is also shown on aliquot addition during the first chemical transformation, which is used to check the instrumentation.

Application of Mid-Infrared Spectroscopy in the Quality Control of Traditional Chinese Medicines

Chinese herbal medicines are often referred to as Chinese materia medica (CMM). Composite formulae containing mixtures of CMM are prescribed for treatment and prevention of diseases in the practice of traditional Chinese medicine (TCM). Some of the well-known CMM formulae (Fufang in Chinese) are manufactured and marketed as proprietary Chinese medicines (PCM). Quality assessment and assurance of these products are difficult; they are a challenging task. Mid-infrared spectroscopy, a classic molecular structure analysis method, has been innovatively applied in the quality control of TCM, and has gained significant impact and advancement in analytical fields. Infrared fingerprinting features appear particularly suitable for the identification of multicomponent matrices in samples whose chemical integrity has not been altered or destroyed because no extraction procedure is needed. This review summarizes and gives an overall view on the application of mid-infrared and two-dimensional correlation infrared (2D-IR) spectroscopy as well as chemometric techniques in the identification of CMM, investigation of TCM processing procedures, and analysis of herb extracts and preparations.

Integration of mid-infrared spectroscopy and geostatistics in the assessment of soil spatial variability at landscape level

Knowledge of soil spatial variability is important in natural resource management, interpolation and soil sampling design, but requires a considerable amount of geo-referenced data. In this study, mid-infrared spectroscopy in combination with spatial analyses tools is being proposed to facilitate landscape evaluation and monitoring. Mid-infrared spectroscopy (MIRS) and geostatistics were integrated for evaluating soil spatial structures of three land settlement schemes in Zimbabwe (i.e. communal area, old resettlement and new resettlement; on loamy-sand, sandy-loam and clay soils, respectively). A nested non-aligned design with hierarchical grids of 750, 150 and 30 m resulted in 432 sampling points across all three villages (730–1360 ha). At each point, a composite topsoil sample was taken and analyzed by MIRS. Conventional laboratory analyses on 25–38% of the samples were used for the prediction of concentration values on the remaining samples through the application of MIRS–partial least squares regression models. These models were successful ( R 2 ≥ 0.89) for sand, clay, pH, total C and N, exchangeable Ca, Mg and effective CEC; but not for silt, available P and exchangeable K and Al ( R 2 ≤ 0.82). Minimum sample sizes required to accurately estimate the mean of each soil property in each village were calculated. With regard to locations, fewer samples were needed in the new resettlement area than in the other two areas (e.g. 66 versus 133–473 samples for estimating soil C at 10% error, respectively); regarding parameters, less samples were needed for estimating pH and sand (i.e. 3–52 versus 27–504 samples for the remaining properties, at same error margin). Spatial analyses of soil properties in each village were assessed by constructing standardized isotropic semivariograms, which were usually well described by spherical models. Spatial autocorrelation of most variables was displayed over ranges of 250–695 m. Nugget-to-sill ratios showed that, in general, spatial dependence of soil properties was: new resettlement > old resettlement > communal area; which was potentially attributed to both intrinsic (e.g. texture) and extrinsic (e.g. management) factors. As a new approach, geostatistical analysis was performed using MIRS data directly, after principal component analyses, where the first three components explained 70% of the overall variability. Semivariograms based on these components showed that spatial dependence per village was similar to overall dependence identified from individual soil properties in each area. In fact, the first component (explaining 49% of variation) related well with all soil properties of reference samples (absolute correlation values of 0.55–0.96). This showed that MIRS data could be directly linked to geostatistics for a broad and quick evaluation of soil spatial variability. It is concluded that integrating MIRS with geostatistical analyses is a cost-effective promising approach, i.e. for soil fertility and carbon sequestration assessments, mapping and monitoring at landscape level.

Application of mid-infrared spectroscopy with multivariate analysis and soft independent modeling of class analogies (SIMCA) for the detection of adulterants in minced beef

Chemometric MID-FTIR methods were developed to detect and quantify the adulteration of mince meat with horse meat, fat beef trimmings, and textured soy protein. Also, a SIMCA (Soft Independent Modeling Class Analogy) method was developed to discriminate between adulterated and unadulterated samples. Pure mince meat and adulterants (horse meat, fat beef trimmings and textured soy protein) were characterized based upon their protein, fat, water and ash content. In order to build the calibration models for each adulterant, mixtures of mince meat and adulterant were prepared in the range 2-90% (w/w). Chemometric analyses were obtained for each adulterant using multivariate analysis. A Partial Least Square (PLS) algorithm was tested to model each system (mince meat+adulterant) and the chemical composition of the mixture. The results showed that the infrared spectra of the samples were sensitive to their chemical composition. Good correlations between absorbance in the MID-FTIR and the percentage of adulteration were obtained in the region 1800-900 cm(-1). Values of R(2) greater than 0.99, standard errors of calibration (SEC) in the range to 0.0001-1.278 and standard errors of prediction (SEP estimated) between 0.001 and 1.391 for the adulterant and chemical parameters were obtained. The SIMCA model showed 100% classification of adulterated meat samples from unadulterated ones. Chemometric MID-FTIR models represent an attractive option for meat quality screening without sample pretreatments which can identify the adulterant and quantify the percentage of adulteration and the chemical composition of the sample.

Potential and Challenges for Mid-Infrared Sensors in Breath Diagnostics

Exhaled breath contains more than 1000 constituents at trace level concentrations, with a wide variety of these compounds potentially serving as biomarkers for specific diseases, physiologic status, or therapeutic progress. Some of the compounds in exhaled breath (EB) are well studied, and their relationship with disease pathologies is well established. However, molecularly specific analysis of such biomarkers in EB at clinically relevant levels remains an analytical and practical challenge due to the low levels of such biomarkers frequently below the ppb (v/v) range in EB. In this contribution, mid-infrared (MIR) spectroscopic sensing techniques are reviewed for potential application in breath diagnostics. While the spectral regime from 3-20 ?m has already been utilized for fundamental studies on breath analysis, significant further improvements are in demand for substantiating MIR spectroscopy and sensing techniques as a suitable candidate for clinically deployable breath analyzers. Several advantageous features including inherent molecular selectivity, real-time monitoring capability, comparable ease of operation, potentially low costs, and a compact device footprint promise reliable optical diagnostics in the MIR. Hence, while the application of MIR spectroscopy and sensing systems to breath analysis yet appear in their infancy, recent progress on advanced MIR light sources, waveguides, and device concepts forecasts next-generation optical sensing platforms suitable for addressing the challenges of in situ breath diagnostics.

Low divergence single-mode surface emitting quantum cascade ring lasers

We describe the fabrication and operation of surface emitting second-order distributed feedback quantum cascade ring lasers. The devices exhibit single-mode emission at a wavelength of 3.95μm with a side mode suppression ratio of 25dB. A linear tuning coefficient of 0.13cm−1∕K is observed. A single longitudinal mode in the ring shaped resonator results in a highly symmetric far-field pattern and a low beam divergence, represented by a full width at half maximum of ∼3°. Based on these characteristics the presented compact coherent light source may find its way into today’s midinfrared spectroscopy applications.

Preliminary study on application of mid infrared spectroscopy for the evaluation of the virgin olive oil “freshness”

The freshness of virgin olive oils (VOO) from typical cultivars of Garda regions was evaluated by attenuated total reflectance (ATR) and Fourier transform infrared (FTIR) spectroscopy, in combination with multivariate analysis. The olive oil freshness decreased during storage mainly because of oxidation processes. In this research, 91 virgin olive oils were packaged in glass bottles and stored either in the light or in the dark at room temperature for different periods. The oils were analysed, before and after storage, using both chemical methods and spectroscopic technique.Classification strategies investigated were partial least square discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and soft independent modelling of class analogy (SIMCA).The results show that ATR-MIR spectroscopy is an interesting technique compared with traditional chemical index in classifying olive oil samples stored in different conditions. In fact, the FTIR PCA results allowed a better discrimination among fresh and oxidized oils, than samples separation obtained by PCA applied to chemical data. Moreover, the results obtained by the different classification techniques (PLS-DA, LDA, SIMCA) evidenced the ability of FTIR spectra to evaluate the olive oil freshness. FTIR spectroscopy results are in agreement with classical methods. The spectroscopic technique could be applied for the prediction of VOOs freshness giving information related to chemical modifications. The great advantages of this technique, compared to chemical analysis, are related to rapidity, non-destructive characteristics and low cost per sample. In conclusion, ATR-MIR represents a reliable, cheap and fast classification tool able to assess the freshness of virgin olive oils.

Application of mid infrared spectroscopy and iPLS for the quantification of contaminants in lubricating oil

The feasibility of using a narrow spectral range in the mid infrared region for a rapid and conclusive determination of contaminants (gasoline, ethylene glycol and water) in lubricating oil was investigated. A graphically-oriented local multivariate calibration modeling procedure called interval partial least-squares (iPLS) was applied to select a spectral range that provides the lowest prediction error, in comparison to the full-spectrum model. The region from 650 to 784 cm −1, attributed to aromatics, was selected for gasoline determination. The region from 918 to 1052 cm −1, for C−O stretching from glycol, was selected for ethylene glycol determination. Finally, the region from 3598 to 3732 cm −1, absorption from hydrogen bonded OH groups, was chosen for water determination. In the determinations, a root mean square error of prediction (RMSEP) of 0.34% for gasoline, 0.037% for ethylene glycol and 0.023% for water, were obtained after interval selection.

Fourier Transform Infrared Spectroscopic Studies of Diabetic Rat Heart Crude Membranes

Application of mid infrared spectroscopy in diabetic tissues will be presented which highlight the promise of this technique in medical research. Examples presented mainly will focus on diabetic rat heart crude membranes. Diabetes mellitus (DM) was induced in rats by streptozotocin (STZ) injection that is one of the most popular experimental models for the study of type I diabetes. The shift in the peak positions, bandwidths and the intensity of the bands in FTIR spectra were analyzed to have valuable structural and functional information, which may have diagnostic value. In the diabetic membranes significant increase was observed in lipid order and lipids concentration. While the concentration of saturated lipids increases, the concentration of unsaturated lipids decreases. In addition, broadening of the amide I bands and the appearance of the new band around 1640 cm−1together with the decrease in the amide I to amide II ratio indicate the structural changes occurring in proteins of diabetic membranes. A dramatic increase in oligosaccarite band (1042 cm−1) and a decrease in olefinic stretching band (3012 cm−1), were also observed.