Near-infrared Diffuse Reflectance Spectroscopy Research Articles

Near-infrared diffuse reflectance spectroscopy for discriminating fruit and vegetable products preserved in glass containers

Near-infrared (NIR) diffuse reflectance spectroscopy was used in combination with multivariate analytical methods to discriminate between different fruit and vegetable products preserved in glass containers, which are commonly used as receptacles for the pasteurization of fruit and vegetable products. To investigate the samples in this way, i.e. inside the sealed glass containers, is important for this specific application in a food processing facility. In order to adapt digitalization technologies to the pasteurization process, it is necessary to investigate usually consumed products with suitable sensors and data analytics. NIR spectroscopy in combination with multivariate data analysis is a mighty tool to unravel various issues in food research and industry. Thus, this combination is in the focus of this investigation. It is shown for the first time that the discrimination between five types of preserved food in glass containers is possible by using NIR diffuse reflectance spectroscopy and multivariate data analysis (including discrimination methods). The performance parameters sensitivity, specificity, and efficiency, are determined for every product group and analyzed in a misclassification table. On average, the results show that 95 % of ca. 2100 observations are correctly classified with partial least squares discriminant analysis (PLS-DA).

Cs2Zn5(PO4)4 and Cs3La(PO4)2: Two Cs‐Containing Phosphates with Three‐Dimensional Frameworks

Two phosphates, Cs2Zn5(PO4)4 and Cs3La(PO4)2 have been successfully synthesized by employing the conventional solid‐state reaction method, and their structures were determined by single‐crystal X‐ray diffraction. Cs2Zn5(PO4)4 owns a three‐dimensional ∞3[Zn4P4O16] framework and Cs3La(PO4)2 features ∞2[La3P6O29] layers spreading in the bc plane. Infrared spectroscopy, UV/Vis‐NIR diffuse reflectance spectroscopy were performed. The thermal properties and electronic structures of two compounds were investigated. In addition, the Ce3+ doped Cs3La(PO4)2 phosphor was synthesized and its photoluminescence was analyzed. The results indicate that the Cs2Zn5(PO4)4:0.01Ce3+ phosphor can be excited by ultraviolet light to obtain blue luminescence.

Random forest as one-class classifier and infrared spectroscopy for food adulteration detection

This paper proposes the use of random forest for adulteration detection purposes, combining the random forest algorithm with the artificial generation of outliers from the authentic samples. This proposal was applied in two food adulteration studies: evening primrose oils using ATR-FTIR spectroscopy and ground nutmeg using NIR diffuse reflectance spectroscopy. The primrose oil was adulterated with soybean, corn and sunflower oils, and the model was validated using these adulterated oils and other different oils, such as rosehip and andiroba, in pure and adulterated forms. The ground nutmeg was adulterated with cumin, commercial monosodium glutamate, soil, roasted coffee husks and wood sawdust. For the primrose oil, the proposed method presented superior performance than PLS-DA and similar performance to SIMCA and for the ground nutmeg, the random forest was superior to PLS-DA and SIMCA. Also, in both applications using the random forest, no sample was excluded from the external validation set.

Authentication of cocoa bean shells by near- and mid-infrared spectroscopy and inductively coupled plasma-optical emission spectroscopy

The aim of this study was to evaluate the efficacy of a multi-analytical approach for origin authentication of cocoa bean shells (CBS). The overall chemical profiles of CBS from different origins were characterized using diffuse reflectance near-infrared spectroscopy (NIRS) and attenuated total reflectance mid-infrared spectroscopy (ATR-FT-IR) for molecular composition identification, as well as inductively coupled plasma-optical emission spectroscopy (ICP-OES) for elemental composition identification. Exploratory chemometric techniques based on Principal Component Analysis (PCA) were applied to each single technique for the identification of systematic patterns related to the geographical origin of samples. A combination of the three techniques proved to be the most promising approach to establish classification models. Partial Least Squares-Discriminant Analysis modelling of fused PCA scores of three independent models was used and compared with single technique models. Improved classification of CBS samples was obtained using the fused model. Satisfactory classification rates were obtained for Central African samples with an accuracy of 0.84.

PH controlled synthesis of UV excited host-sensitized luminescence in Dy3+ doped Ga2O3

A series of Dy3+-doped Ga2O3 powders were prepared via a simple hydrothermal reaction method, conducted without the use of any surfactants at varying initial pH. X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Photo-Luminescence (PL), UV–Vis–NIR Diffuse Reflectance Spectroscopy (DRS), Electron Probe Micro-Analysis (EPMA) and WDS/EDS were employed to characterize the synthesized powders. The influence of starting solution pH on the growth process of the GaOOH particles and on the host-sensitized luminescence of the Dy3+:Ga2O3 powders were investigated in detail. It is revealed that the active energy transfer processes can be influenced by variation of the Dy3+ concentration, and that a starting solution pH value of 8 is optimal for maximizing Dy3+ incorporation into the Ga2O3 lattice. This work presents a method to produce Dy3+:Ga2O3 with tunable UV-pumped emission, and provides evidence that white emission can be achieved through careful control of dopant concentration, which makes the material attractive for solid state UV pumped-white emission applications.

Effects of ultrasonic irradiation on the synthesis, crystallization, thermal and dissolution behaviour of chloride-intercalated, co-precipitated CaFe-layered double hydroxide

The output power (30–150 W) and the periodicity (20–100%) of ultrasound emission were varied in a wide range to regulate and improve the crystallization process in the commonly used co-precipitation technique of chloride-intercalated CaFe-layered double hydroxides. The influence of ultrasound irradiation on the as-prepared materials was studied by X-ray diffractometry, dynamic light scattering, UV–Vis–NIR diffuse reflectance spectroscopy, specific surface area measurement, pore size analysis, ion-selective electrode potentiometric investigations and thermogravimetry. Additionally, structural alterations due to heat treatment at various temperatures were followed in detail by Fourier-transform infrared and X-ray absorption spectroscopies as well as scanning electron microscopy. The ultrasonic treatment was capable of controlling the sizes of primarily formed (from 19 nm to 30 nm) as well as the aggregated (secondary) particles (between 450 nm and 700 nm), and thus modifying their textural parameters and enhancing the incorporation of chloride anions into the interlamellar space. For the first time, the optical energy gap of CaFe-LDH was reported here depending on the nature of applied stirring (4.18–4.34 eV). The heat-treatment investigations revealed that the layered structure was stabile until 200 °C, even at the atomic level.

Titanium dioxide as an adsorbent to enhance the detection ability of near-infrared diffuse reflectance spectroscopy

A method for quantitative determination of fish sperm deoxyribonucleic acid (fsDNA) was developed by using titanium dioxide (TiO2) as an adsorbent and near-infrared diffuse reflectance spectroscopy (NIRDRS). The selective enrichment of fsDNA was proved by comparing the adsorption efficiency of bovine serum albumin, tyrosine and tryptophan, and the low adsorption background of TiO2 was illustrated by comparing the spectra of four commonly-used inorganic adsorbents (alkaline aluminium oxide, neutral aluminium oxide, nano-hydroxyapatite and silica). The spectral feature of fsDNA can be clearly observed in the spectrum of the sample. Partial least squares (PLS) model was built for quantitative determination of fsDNA using 28 solutions, and 13 solutions with interferences were used for validation of the model. The results showed that the correlation coefficient (R) between the predicted and the reference concentration is 0.9727 and the recoveries of the validation samples are in the range of 98.2%–100.7%

Classification of Pathogenic Bacteria Using Near-Infrared Diffuse Reflectance Spectroscopy

Near-infrared diffuse reflectance spectroscopy is proposed for the classification of pathogenic bacteria using optical properties. The spectrally resolved data are analyzed using a diffuse reflectance model to extract the local optical properties, including the reduced scattering coefficient and absorption coefficient. The optical properties at different wavelengths form the feature set. A particle swarm optimization-based support vector machine is used to classify seven categories of bacteria. The experimental results demonstrate the feasibility of the method for the rapid and noninvasive classification of pathogenic bacteria using optical properties.

Near-Infrared Hyperspectral Absorption/Scattering Imaging Method Using Multiple Ground Plates for Evaluating Polymer Composites.

This paper proposes a nondestructive method of evaluating polymer composites using near-infrared (NIR) diffuse reflection spectroscopy with multiple ground plates. Wavelength-dependent absorption and reduced scattering coefficients were acquired to evaluate the chemical structure and the concentration of the substances from absorption and to determine the size and the dispersity of filler in the polymer domain from scattering. NIR spectra of the sample were measured on multiple ground plates, namely, "ground-plate-dependent" diffuse reflection spectra. The effects of the external reflection on the ground-plate-dependent diffuse reflection spectra were subsequently removed. The internal reflection coefficient was calculated based on the difference between the diffuse reflectances of the neat resin and ground plates without prior information on the incident angle of light and the refractive index of sample. The external reflection coefficient was evaluated by the gap of diffuse reflectances between the sample and a white ground plate. After the corrections of reflections, the spectra were fitted by a physical model of light propagation based on the two-flux theory to acquire the absorption and the reduced scattering coefficients. The calculated absorption coefficients indicated a good linear relationship with particle concentration. The calculated reduced scattering coefficients agreed with the theoretical values by Mie scattering theory. It was demonstrated that the proposed method achieved the simultaneous evaluation of particulate-filler concentrations and sizes in polymer composites.

Effect of Residual Na+ on the Combustion of Methane over Co3O4 Bulk Catalysts Prepared by Precipitation

The effect of the presence of residual sodium (0.4 %wt) over a Co3O4 bulk catalyst for methane combustion was studied. Two samples, with and without residual sodium, were synthesized by precipitation and thoroughly characterised by X-ray diffraction (XRD), N2 physisorption, Wavelength Dispersive X-ray Fluorescence (WDXRF), temperature-programmed reduction with hydrogen followed by temperature-programmed reduction with oxygen (H2-TPR/O2-TPO), temperature-programmed reaction with methane (CH4-TPRe), ultraviolet–visible–near-infrared diffuse reflectance spectroscopy (UV-vis-NIR DRS), Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). It was found that during calcination, a fraction of the sodium atoms initially deposited on the surface diffused and migrated into the spinel lattice, inducing a distortion that improved its textural and structural properties. However, surface sodium had an overall negative impact on the catalytic activity. It led to a reduction of surface Co3+ ions in favour of Co2+, thus ultimately decreasing the Co3+/Co2+ molar ratio (from 1.96 to 1.20) and decreasing the amount and mobility of active lattice oxygen species. As a result, the catalyst with residual sodium (T90 = 545 °C) was notably less active than its clean counterpart (T90 = 500 °C). All of this outlined the significance of a proper washing when synthesizing Co3O4 catalyst using a sodium salt as the precipitating agent.

Molecular-Level Understanding of Selectively Photocatalytic Degradation of Ammonia via Copper Ferrite/N-Doped Graphene Catalyst under Visible Near-Infrared Irradiation

Developing photocatalysts with molecular recognition function is very interesting and desired for specific applications in the environmental field. Copper ferrite/N-doped graphene (CuFe2O4/NG) hybrid catalyst was synthesized and characterized by surface photovoltage spectroscopy, X-ray powder diffraction, transmission electron microscopy, Raman spectroscopy, UV–Vis near-infrared diffuse reflectance spectroscopy and X-ray photoelectron spectroscopy. The CuFe2O4/NG catalyst can recognize ammonia from rhodamine B (RhB) in ammonia-RhB mixed solution and selectively degrade ammonia under visible near-infrared irradiation. The degradation ratio for ammonia reached 92.6% at 6 h while the degradation ratio for RhB was only 39.3% in a mixed solution containing 100.0 mg/L NH3-N and 50 mg/L RhB. Raman spectra and X-ray photoelectron spectra indicated ammonia adsorbed on CuFe2O4 while RhB was adsorbed on NG. The products of oxidized ammonia were detected by gas chromatography, and results showed that N2 was formed during photocatalytic oxidization. Mechanism studies showed that photo-generated electrons flow to N-doped graphene following the Z-scheme configuration to reduce O2 dissolved in solution, while photo-generated holes oxidize directly ammonia to nitrogen gas.

Rapid determination of the texture properties of cooked cereals using near-infrared reflectance spectroscopy

Rapid determination of the texture properties of various cooked cereals, including the hardness, springiness, stickiness, chewiness, gumminess and cohesiveness, was performed by near-infrared (NIR) diffuse reflectance spectroscopy. Calibration models were established by partial least squares (PLS) or principal component regression (PCR) after derivative and smoothing pretreatments. The coefficients of determination (R2c) were over 0.94 in PCR models and over 0.91 in PLS models. High performance can also be achieved at selected wavebands 1000–2500, 1122–2294, 1243–1428, 1728–2452, 1125–1760 and 1107–2466 nm, for hardness, springiness, stickiness, chewiness, gumminess and cohesiveness, respectively. Good prediction results were obtained for the texture parameters, which demonstrated that NIR reflectance spectroscopy with common models of PLS or PCR can be used as a rapid tool to determine the texture properties of cooked cereals.

CHEMOMETRIC ANALYSIS OF DIFFUSE REFLECTANCE SPECTRAL DATA USING SINGULAR VALUE DECOMPOSITION FOR BLOOD GLUCOSE DETECTION

Diabetes mellitus is a metabolic disorder that affects the production or usage of insulin by the body. Diabetes prevails in the body as a long-term condition which causes several other disorders if left unnoticed. Proper control of Diabetes needs continuous monitoring. The current measurement technique is invasive in nature and requires the withdrawal of blood from the body. Periodic quantification of blood glucose leads to pain and discomfort for the subject. This paper presents a non-invasive glucose measuring system using near-infrared diffuse reflectance spectroscopy (DRS). This work attempts to determine the blood glucose value from the diffuse reflected spectra in the NIR region. The study is executed with the spectral signatures of 33 diabetic subjects collected non-invasively using diffuse reflectance spectrometer from a diabetic centre. Blood glucose level of the same subjects are also recorded using the clinical method. The spectral information is subjected to standard normal variate (SNV) preprocessing method to remove baseline drift and then dimension reduction using singular value decomposition (SVD) is applied to the preprocessed data. The extracted singular values when compared with the clinically measured blood glucose is found to have a proportional relationship. The proposed study using singular value decomposition paves us the way for estimating the blood glucose value non-invasively with the obtained set of clinical blood glucose and the corresponding singular value table as a standard reference set.

Effect of homogenisation on detection of milk protein content based on NIR diffuse reflectance spectroscopy

SummaryInvestigating the effect of homogenisation on the prediction performance of protein content by using near‐infrared (NIR) spectroscopy is helpful to improve protein determination precision. For this purpose, the influence of homogenisation on milk fat globules and NIR spectra was analysed firstly. Then, NIR spectra of eighty‐seven cow milk samples before and after homogenisation were obtained. Multiplicative scatter correction was used to do spectral pretreatment. Uninformative variable elimination based on partial least squares (UVE‐PLS) and successive projection algorithm was used to extract characteristic variables. Partial least squares regression (PLSR) and least squares support vector machine models were established. The results showed that homogenisation made milk fat globules be distributed evenly, decreased the size of fat globules and improved NIR spectral repeatability and prediction precision on protein content. The best model was PLSR‐UVE‐PLS, having good and excellent protein prediction ability for un‐homogenised milk (RMSEP = 0.06 g/100 g, RPD = 2.69) and homogenised milk (RMSEP = 0.04 g/100 g, RPD = 3.59), respectively.

Determination of soil physicochemical attributes in farming sites through visible, near-infrared diffuse reflectance spectroscopy and PLSR modeling

IntroductionAn accurate and reliable detection of soil physicochemical attributes (SPAs) is a difficult and complicated issue in soil science. The SPA may be varied spatially and temporally with the complexity of nature. In the past, SPA detection has been obtained through routine soil chemical and physical laboratory analysis. However, these laboratory methods do not fulfill the rapid requirements. Accordingly, diffuse reflectance spectroscopy (DRS) can be used to nondestructively detect and characterize soil attributes with superior solution. In the present article, we report a study done through spectral curves in the visible (350–700 nm) and near-infrared (700–2500 nm) (VNIR) region of 74 soil specimens which were agglomerated by farming sectors of Phulambri Tehsil of the Aurangabad region of Maharashtra, India. The quantitative analysis of VNIR spectrum was done.ResultsThe spectra of agglomerated farming soils were acquired by the Analytical Spectral Device (ASD) Field spec 4 spectroradiometer. The soil spectra of the VNIR region were preprocessed to get pure spectra which were the input for regression modeling. The partial least squares regression (PLSR) model was computed to construct the calibration models, which were individually validated for the prediction of SPA from the soil spectrum. The computed model was based on a correlation study between reflected spectra and detected SPA. The detected SPAs were soil organic carbon (SOC), nitrogen (N), soil organic matter (SOM), pH values, electrical conductivity (EC), phosphorus (P), potassium (K), iron (Fe), sand, silt, and clay. The accuracy of the PLSR model-validated determinant (R2) values were SOC 0.89, N 0.68, SOM 0.93, pH values 0.82, EC 0.89, P 0.98, K 0.82, Fe 0.94, sand 0.98, silt 0.90, and clay 0.69 with root mean square error of prediction (RMSEP) 3.51, 4.34, 2.66, 2.12, 4.11, 1.41, 4.22, 1.56, 1.89, 1.97, and 9.91, respectively. According to the experimental results, the VNIR-DRS was better for detection of SPA and produced more accurate predictions for SPA.ConclusionsIn conclusion, the methods examined here offered rapid and novel detection of SPA from reflectance spectroscopy. The outcome of the present research will be apt for precision farming and decision-making.

Rapid Determination of Saponins in the Honey-Fried Processing of Rhizoma Cimicifugae by Near Infrared Diffuse Reflectance Spectroscopy.

Objective: A model of Near Infrared Diffuse Reflectance Spectroscopy (NIR-DRS) was established for the first time to determine the content of Shengmaxinside I in the honey-fried processing of Rhizoma Cimicifugae. Methods: Shengmaxinside I content was determined by high-performance liquid chromatography (HPLC), and the data of the honey-fried processing of Rhizoma Cimicifugae samples from different batches of different origins by NIR-DRS were collected by TQ Analyst 8.0. Partial Least Squares (PLS) analysis was used to establish a near-infrared quantitative model. Results: The determination coefficient R2 was 0.9878. The Cross-Validation Root Mean Square Error (RMSECV) was 0.0193%, validating the model with a validation set. The Root Mean Square Error of Prediction (RMSEP) was 0.1064%. The ratio of the standard deviation for the validation samples to the standard error of prediction (RPD) was 5.5130. Conclusion: This method is convenient and efficient, and the experimentally established model has good prediction ability, and can be used for the rapid determination of Shengmaxinside I content in the honey-fried processing of Rhizoma Cimicifugae.

Magnetic infrared responsive photocatalyst: fabrication, characterization, and photocatalytic performance of β-NaYF4:Yb3+,Tm3+/TiO2/Fe3O4@SiO2 composite

To enhance photocatalytic activity spectra area of the TiO2 based photocatalyst, and to separate and recycle photocatalyst easily, magnetic photocatalyst was prepared with β-NaYF4:Yb3+,Tm3+, TiO2, Fe3O4 as carriers, and tetraethyl orthosilicate as precursor. The magnetic infrared responsive photocatalysts were thoroughly characterized by field emission scanning electron microscopy, X-ray diffraction, a fluorescence spectrometer and UV–Vis–NIR diffuse reflectance spectroscopy. They showed that the composite of β-NaYF4:Yb3+,Tm3+/TiO2/Fe3O4@SiO2 (UCTFS) emits visible luminescence upon 980 nm excitation, and energy transfer from β-NaYF4:Yb3+,Tm3+ to TiO2 was verified. The photocatalytic activities of the UCTFS were studied by orthogonal experiments for photodegradating methylene blue (MB). The degradation rate of MB can reach 86.69% under the optimal conditions. After the four recycles, the degradation rate remained 52.72%. It also showed that 50.27% of the degradation efficiency of phenol can be obtained under the same experimental parameters. These results suggest that magnetic UCTFS composite is stable and a magnetic NIR-driven photocatalyst for degradation of organic pollutants. Moreover, the NIR driven photocatalytic mechanism of this reported composite was proposed. The strategy suggested here may be indicated for the effective fabrication of magnetic NIR-driven photocatalyst for application in the water purification by full spectra of solar energy.

English

Sustainable reuse of pre-treated drill cuttings (a hazardous waste) as part substitute for fine aggregate in concrete for construction purposes is becoming increasingly attractive; however, issues remain. With recent studies focusing on the use of near-infrared spectroscopic technique for non-invasive determination of chloride concentration in concrete structures, this review examines the applicability of this new technique in the rapid determination of other equally important physicochemical characteristics of concrete produced with this hazardous waste. The nature, source, composition, ecological effects of, and management options for drill cuttings are reviewed. Furthermore, the principles of near-infrared diffuse reflectance spectroscopy are highlighted and lessons from its practical applications in soil science and petrochemical, environmental, and civil engineering are discussed. A framework for a rapid near-infrared analysis of concrete produced with pre-treated drill cuttings for enhanced sustainability as a construction material is also proposed. Key words: Characterization, concrete, drill cuttings, diffuse reflectance spectroscopy.

Determination of acid end group in Polybutylene Terepthalate using Fourier Transform near-infrared (FT-NIR) spectroscopy and chemometrics

A robust quantitative method for the determination of acid end group (AEG) in Polybutylene Terepthalate (PBT) pellets using near-infrared (NIR) diffuse reflectance spectroscopy and chemometrics is presented in this paper. A set of 66 calibration samples were used to develop a multivariate calibration model based on partial least-squares (PLS) regression. The AEG in the calibration samples varied from normalized concentration of 20–90 meq/kg. To minimize non-chemical spectral variations, the acquired NIR spectra were preprocessed using standard normal variate (SNV). Spectral range selection was explored in order to identify optimal spectral regions that were required to generate a robust PLS regression model for AEG. The performance of the optimized PLS model was evaluated on a set of 219 independent validation samples. The optimized calibration models exhibited RMSEP of 2.87 meq/kg.

Accuracy and application of milk fatty acid estimation with diffuse reflectance near-infrared spectroscopy.

Near infrared spectroscopy (NIRS) has the potential to estimate contents of fatty acids (FA) in milk frequently at-farm or during daily milking routine. In this study, a total of 738 raw milk spectra collected from 33 Holstein cows over a period of 30 weeks were recorded. Reference data on FA composition in milk and in milk fat were analysed in laboratory. Calibration models were calculated for single FA and groups of FA in milk and in milk fat. Validation resulted in sufficient Ratio of Prediction to Deviation (RPD) values for some single FA and in higher RPD values for groups of FA when concentrations of FA in milk were predicted. Since the concentrations of most FA in milk are highly correlated with milk fat content, the prediction of FA contents in milk fat is more meaningful when independent predictions are intended. The accuracy of predicting single FA concentrations in milk fat is rather poor for most FA but still comparable to alternative analysing methods such as MIR analysis. The estimation of different groups of FA in milk fat resulted in an improved accuracy based on higher RPD values, which was sufficient to mirror the development in the different lactation phases. The course of cow individual long chain fatty acid (LCFA) concentration in the early lactation stage can be an indicator for body fat mobilisation. The accurate estimation of the extent and duration of body fat mobilisation in cow individuals was rather difficult with NIR predicted LCFA concentrations and would require a higher measuring frequency than applied in this study.