Near Infrared Spectroscopy Spectroscopy Research Articles

Microwave drying and NIR spectroscopy for the rapid moisture measurement of yerba mate (Ilex paraguariensis) leaves during storage

ABSTRACTMicrowave technology was assessed and compared with traditional kiln drying to analyze the moisture content of yerba mate leaves/sticks. The moisture content was also measured by near-infrared spectroscopy (NIR). The samples were stored under different conditions of temperature, relative humidity (RH), and time, until 180 days. The microwave method was similar to the official kiln drying method when 900 W/4.3 min was applied. The use of microwave drying showed similar results to the kiln method in the moisture range of 0–10 g/100 g raw material. The partial least square (PLS) models obtained from NIR spectroscopy showed low predictive power, due to the natural heterogeneity of the samples.

Comparison of NIR spectroscopy coupled to chemometrics and derivative thermogravimetry for relative dating of human fossil bones

The possibility of using near-infrared spectroscopy (NIR) coupled to chemometric exploratory data processing in order to obtain a fast, cheap and nondestructive dating of human fossil bones is presented and discussed. The proposed approach has been applied to the differentiation of human fossil bones from two necropolises in the Middle Nile (Saggai and Geili). Principal component analysis of the spectral data after suitable pretreatment (standard normal variate + first derivative) allowed to evidence cluster of bones corresponding to the different antiquity of the samples, thus indicating that the proposed approach can lead to an accurate (although relative) dating of the fossil samples. Analysis of the PCA loading suggested that the spectral region that are most relevant for the observed differentiation is 4000–4500, 5150–5801 and 6898–7411 cm−1. A confirmation of the reliability of what found using NIR spectroscopy was obtained by comparing the results to those outcoming from the DTG analysis onto the same bone samples followed by PCA, according to a thermogravimetric–chemometric approach already successfully applied in previous researches. Lastly, in order to obtain a more holistic characterization of the samples, a further PCA processing was carried out after “fusion” of data from both analytical techniques.

Abstract 41: Implantable Oxygen Biosensor Reveals Post-Occlusion Tissue Reactive Hyperoxia

INTRODUCTION: This study utilized an implantable biosensor to measure tissue oxygenation before, during, and after a transient ischemic insult. The purpose of this study was to use implantable O2 sensors to quantify local O2 content following ischemic challenges and perfusion restoration. METHODS: All animals were treated according to approved IACUC protocols. First, rats were subjected to unilateral femoral artery and vein ligation and received bilateral biosensor implants in the hind limbs. The biosensors were composed of a porphyrin embedded into a porous poly-hydroxyethylmethacrylate (pHEMA) scaffold and were injected through an 18-gauge needle into the subcutis. The biosensor’s phosphorescence lifetime changed inversely with O2 concentration. Near infrared spectroscopy (NIR) was also used to quantify percent O2 saturation of hemoglobin at the tissue level. Laser Doppler flowmetry was used to quantify blood flow. On post-operative days 28 and 84, the rats underwent a series of systemic hypoxic challenges as well as bilateral hind limb tourniquet application. Response magnitudes, response times and normalized changes were calculated for comparison between techniques. Statistical significance was assessed using ANOVA and two-sample paired t-test at p-value < 0.05. RESULTS: Laser Doppler flowmetry confirmed a reactive hyperemia following tourniquet release. In addition, both the phosphorescence lifetime biosensor and NIR methods suggested that the tissue O2 content temporarily but significantly exceeded baseline following tourniquet release (p<0.05). We term this phenomenon reactive hyperoxia. This suggests that the O2 supply transiently exceeds oxygen consumption. Even though tissue O2 consumption was expected to be elevated following ischemia to repay the O2 debt developed during occlusion, the elevated O2 content indicates that the increased consumption is met with an even greater elevated O2 supply. The NIR spectroscopy and phosphorescence lifetime data are consistent. The phosphorescence lifetime biosensor also demonstrates a more prominent response magnitude in general and a faster response over time (71 secs vs. 143 secs in NIR; p = 0.0053), suggesting that the sensing elements may have gained greater proximity to the blood supply via vascular ingrowth through the porous pHEMA scaffold. CONCLUSION: The implantable phosphorescence lifetime biosensor provided real time monitoring of tissue oxygenation, with a rapid and prominent response, excellent biocompatibility and highly localized measurements. Both the phosphorescence lifetime and NIR spectroscopy techniques demonstrated a reactive hyperoxia post ischemia. Direct assessment of tissue oxygenation may provide helpful diagnostic and prognostic information on wound healing, re-vascularization, 3D scaffold design and efficacy of therapeutics promoting tissue oxygenation.

Non-destructive prediction of soluble solids and dry matter content using NIR spectroscopy and its relationship with sensory quality in sweet cherries

Near infrared spectroscopy (NIR) models developed in the spectral region between 729 and 975nm for a handheld instrument have been demonstrated to be accurate, robust and versatile for the rapid and non-destructive evaluation of soluble solids (SSC) and dry matter (DMC) content in sweet cherries at two different temperatures, 0 and 23°C. Coefficient of determination (R2) values for model calibrations ranged from 0.922 to 0.946 for SSC and from 0.910 to 0.933 for DMC, with standard errors of calibration from 0.612 to 0.792 and from 0.687 to 0.911% for SSC and DMC, respectively, depending on the variety and the temperature of the fruit. External validation of the models demonstrated they could be confidently used for ‘Chelan’ and ‘Bing’ sweet cherries; R2 values for SSC ranged from 0.726 to 0.891 and for DMC from 0.670 to 0.725 between the predicted and the observed values in the external validation set, respectively. Consumer preference evaluation for ‘Bing’ and ‘Chelan’ sweet cherries with differing SSC (16.38–28.45) and DMC (17.67–31.62%) revealed higher acceptance by consumers for cherries with high DMC as well as for cherries with high SSC. DMC was equal to or superior to SSC for predicting flavor intensity and balance of sweet to sour taste as assessed by consumers. Considering the revealed importance in sensory evaluation of DMC, as well as SSC, in the eating quality of sweet cherry, the use of handheld NIR devices, which are rapid, lightweight and user-friendly should be considered for routine, non-destructive analysis of sweet cherry quality.

Analysis of bee pollen constituents from different Brazilian regions: Quantification by NIR spectroscopy and PLS regression

In the present work partial least square regression (PLS) models were built for quantification of the major components of 154 Brazilian bee pollen samples. Bee pollen has nutritive and therapeutic properties that make it attractive for human health. However, studies on the nutrient and bioactive compound composition of this product are needed, as well as the verification of the presence of contaminants that are harmful to health. The conventional analysis methods are costly and time-consuming, while near infrared spectroscopy (NIR) associated to PLS regression allows a fast and non-costly quantification of the bee pollen components without samples pre-treatment.The calibration models exhibited the determination coefficients, R2 > 0.94. The mean percent calibration error varied from 1.49 to 5.58%. For external validation, R2 ranged from 0.89 to 0.98 among the six. The results indicated that some models are good for quantification, while others are qualified for screening calibration.

Classification and quantification of palm oil adulteration via portable NIR spectroscopy

Short wave near infrared spectroscopy (NIR) method was used to detect the presence of lard adulteration in palm oil. MicroNIR was set up in two different scan modes to study the effect of path length to the performance of spectral measurement. Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. Additionally, by employing partial least square (PLS) regression, the coefficient of determination (R2) of transflectance and transmission were 0.9987 and 0.9994 with root mean square error of calibration (RMSEC) of 0.5931 and 0.6703 respectively. In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. The result of R2 and RMSEC after variable selection for transflectance and transmission were improved significantly. Based on the result of classification and quantification analysis, the transmission mode has yield better prediction model compared to the transflectance mode to distinguish the pure and adulterated palm oil.

Study of Nafion Membrane below Freezing Temperature By Using Near Infrared-Spectroscopy and Electrochemical Impedance Spectroscopy

Introduction The conductive polymer is one of the important materials for polymer electrolyte fuel cell (PEFC). Nowadays many researchers have been developed the membrane in order to improve the durability and power performance of PEFC. Kunimatsu et al. analyzed Nafion membrane by FT-IR spectroscopy and reported that the electric conductivity depended strongly on the state of water molecule hydrated around a hydrophilic group[1]. In the membrane, the sulfonic acid groups are aggregated and form a nano-tube structure called “proton conducting channel”[2]. Water molecules confined in the nano-tube are considered to take various hydrogen-bond states (free water, bound water and unfreezing water)[3]. However, the relationship between water state and proton conductivity has not comprehensively investigated. The in-situ measurement by near infrared spectroscopy (NIR) is superior to detecting the absorbance of the water molecules, since the other signals are not appeared in near infrared region. In this study, we apply NIR for analyzing the hydrated state of water molecules in Nafion below freezing temperature and simultaneously measure the in-plane resistance by the electrochemical impedance spectroscopy (EIS). The mechanism of proton conductivity is discussed by comparing NIR spectroscopy with Arrhenius plots. Experimental Nafion membrane (NRE-212) was set between two copper plates (3.5×1.0 cm2) for the in-situ transmission measurement of NIR. To penetrate the infrared incident light, the hole of 5 mm was made a hole at the center of the holder. The membrane was hydrated by exposing to humidified N2gas for 1 hour at 20 ̊C before measurement. The NIR measurement was conducted by the use of NIR detector (Ocean Photonics Co., NIR256-2.1) and halogen light source which was connected with optical fibers. The range of wavenumber was from 7700 to 5000 cm−1 and the resolution was 4.0 cm−1. A cryostat using liquid nitrogen as a coolant was used to adjust the experimental temperature between −140 ̊C and 20 ̊C. The impedance spectroscopy was carried out by frequency-response analyzer (Toyo Co., Solartron). The frequency was between 10 MHz and 50 mHz and the amplitude of ±100 mV. A two-terminal AC impedance method was employed and Au wires (φ=0.5 mm) were placed in contact with membrane as a sensor. The distance between two wires was 9 mm. Results and discussion Figure 1 (a) shows the NIR spectra during cooling and heating hydrous Nafion membrane. Two peaks attributed to vibration of water molecules were observed. The one arround 7000 cm−1 was assigned to combination tone of symmetric stretch and asymmetric stretch. The other arround 5200 cm−1was done to deformation vibration and asymmetric stretch. Both peaks were shifted to higher wavenumber with decreasing in temperature. This suggests that the individual O-H bonding force was weakened. The hydrated number per one water molecule was increased by lessening the thermal molecular motion at low temperature. This probably change increases the number of “bound water” and “unfreezing water”. Figure 1 (b) shows the Arrhenius plots of the electrical conductivity obtained from EIS measurement. The conductivity was significantly decreased with decreasing in temperature. As indicated by the broken line in Figure 1 (b), the slope could be divided into three regions, i.e. first, second and third are from 20 ̊C to −40 ̊C, from −40 ̊C to −100 ̊C and from −100 ̊C to −140 ̊C, respectively. Activation energy at the first, second and third are 27 kJ mol−1, 52 kJ mol−1 and 23 kJ mol−1, respectively. By comparing NIR result, it was suggested that conduction mechanism of proton depended on the hydrated state such as “bound water” and “unfreezing water”. Reference [1] J. D. Kim, Y. Park, K. Kobayashi, M. Nagai, M. Kunimatsu, Solid State Ionics, 140 (2001) 313-325. [2] W. Y. Hsu and T. D. Gierke, Journal of Membrane Science, 13 (1983) 307-326. [3] N. Hara, H. Ohashi, T. Ito, and T. Yamaguchi, Journal of Physical Chemistry, 113 (2009) 4656-4663. Figure 1

Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics

The present study investigated the application of near infrared spectroscopy as a green, quick, and efficient alternative to analytical methods currently used to evaluate the quality (moisture, total sugars, acidity, soluble solids, pH and ascorbic acid) of frozen guava and passion fruit pulps. Fifty samples were analyzed by near infrared spectroscopy (NIR) and reference methods. Partial least square regression (PLSR) was used to develop calibration models to relate the NIR spectra and the reference values. Reference methods indicated adulteration by water addition in 58% of guava pulp samples and 44% of yellow passion fruit pulp samples. The PLS models produced lower values of root mean squares error of calibration (RMSEC), root mean squares error of prediction (RMSEP), and coefficient of determination above 0.7. Moisture and total sugars presented the best calibration models (RMSEP of 0.240 and 0.269, respectively, for guava pulp; RMSEP of 0.401 and 0.413, respectively, for passion fruit pulp) which enables the application of these models to determine adulteration in guava and yellow passion fruit pulp by water or sugar addition. The models constructed for calibration of quality parameters of frozen fruit pulps in this study indicate that NIR spectroscopy coupled with the multivariate calibration technique could be applied to determine the quality of guava and yellow passion fruit pulp.

Early detection of emerging street drugs by near infrared spectroscopy and chemometrics

Near-infrared spectroscopy (NIRs) is spreading as the tool of choice for fast and non-destructive analysis and detection of different compounds in complex matrices. This paper investigated the feasibility of using near infrared (NIR) spectroscopy coupled to chemometrics calibration to detect new psychoactive substances in street samples. The capabilities of this approach in forensic chemistry were assessed in the determination of new molecules appeared in the illicit market and often claimed to contain “non-illegal” compounds, although exhibiting important psychoactive effects. The study focused on synthetic molecules belonging to the classes of synthetic cannabinoids and phenethylamines. The approach was validated comparing results with officials methods and has been successfully applied for “in site” determination of illicit drugs in confiscated real samples, in cooperation with the Scientific Investigation Department (Carabinieri-RIS) of Rome. The achieved results allow to consider NIR spectroscopy analysis followed by chemometrics as a fast, cost-effective and useful tool for the preliminary determination of new psychoactive substances in forensic science.

Partial least square with discriminant analysis and near infrared spectroscopy for evaluation of geographic and genotypic origin of arabica coffee

The agronomic practices and environmental conditions for coffee cultivation, such as climate, soil type and altitude, promote influence in the final chemical composition of the grain. Furthermore, the genotype directly influences the essential features of the beverage, increasing its aggregate price. Proof of geographic and genotypic origin of the coffee genotype must be done using reliable methods. Thus, near infrared spectroscopy (NIR) was used to analyze different coffee genotypes that were cultivated in Brazil. Due to complexity and quantity of information within the spectra, partial least square discriminant analysis (PLS-DA) were applied to analyze the NIR data. The multiplicative scatter correction (MSC) and the Savitzky–Golay second-derivative were tested as preprocessing techniques to find which one provides an appropriate identification model. The best model achieved correctly identified 94.4% of validation samples for both geographic and genotypic origin. The results demonstrate that NIR spectroscopy provides significant analytical data to be used in tandem with PLS-DA to distinguish green coffee samples geographically and genotypically.

Prediction of Colour Change of Thermally Modified Wood by near Infrared Spectroscopy

Colour changes of untreated and thermally modified (120°C, 180°C and 220°C) southern pine wood are predicted by near infrared spectroscopy (NIR). Colour change information originating from thermal chemical decomposition was assessed by NIR spectroscopy while wood surface colour change values in the CIE1976 L*a*b* system were determined with a colour measurement instrument. Calibration models were built using partial least squares and corresponding cross-validation. A close relationship between colour change values and NIR spectra of thermally modified wood allowed for easy clustering. The proposed colour prediction model for thermally modified wood produced very high R2 values (above 0.90) and was well suited to NIR spectra acquired from wood tangential surfaces, suggesting that the method can provide effective, online quality control.

Robust PLS models for soluble solids content and firmness determination in low chilling peach using near-infrared spectroscopy (NIR)

The objectives of this study was to develop partial least square (PLS) models using NIR spectroscopy for the determination of SSC and firmness in intact low chilling ‘Aurora-1’ peach fruit, and verify the influence of maturity stage and harvest season on the models to be developed (robustness). FT-NIR spectra were obtained as log 1/R with fruit harvested in 2013 at 3 maturity stages and in 2014. The spectra were collected on the background and blush colour skin areas of the each fruit. Model performance was evaluated based on the values of root mean square error for prediction (RMSEP) and coefficient of determination (RP2) obtained from validation fruit set (Kennard-Stone), and prediction fruit set (2014). PCA could not group the fruit based on blush and background skin colour, maturity stages, and harvest season. The model constructed using the external validation method obtained a RMSEVE of 1.08 % with 11 latent variables (LVS) and a RVE2 of 0.59. The prediction set, independent data, resulting in a less accurate model (RMSEP 1.04 %, Rp2 0.45 and 11 LVS). The same trend happened for determining firmness with the external validation resulting in better model with RMSEVE 9.51N and RVE2 of 0.40 and the prediction set with RMSEP of 13.2N, RP2 0.40 with 7 LVS. The NIR spectroscopy showed to be a potential analytical method to determine SSC and firmness of intact low chilling ‘Aurora 1’ cultivar. However, it is necessary to optimize the models in other to reduce the prediction errors.

Near-infrared spectroscopy and variable selection techniques to discriminate Pseudomonas aeruginosa strains in clinical samples

Pseudomonas aeruginosa is a leading cause of nosocomial infections, ranking second among the negative Gram pathogens reported to the National Nosocomial Infection Surveillance System. P. aeruginosa may develop resistant during prolonged therapy with all antimicrobial agents. Therefore, isolates that are initially susceptible may become resistant within 3–4days after initiation of therapy. Testing of repeat isolates may be warranted. There is a need for sensitive and specific tests. We set out to determine whether near-infrared spectroscopy (NIR) combined with variable selection techniques employing successive projection algorithm – linear discriminant analysis (SPA-LDA) or genetic algorithm – (GA-LDA) could discriminate P. aeruginosa strains according to resistant vs. sensitive. The variables selected were then used for discriminating the strains. The influence of various spectral pre-treatments (Savitzky–Golay smoothing, multiplicative scatter correction (MSC), and Savitzky–Golay derivatives) was calculated. In addition, accuracy test results including sensitivity and specificity were determined. Sensitivity in the resistant category was 95% using a SPA-LDA model with 70 wavelengths. Sensitivity and specificity in both categories was 93% using a GA-LDA model with 32 wavelengths. We show that NIR spectroscopy of P. aeruginosa combined with variable selection techniques is a powerful tool for resistant vs. sensitive strains based on the unique spectral “fingerprints” of their biochemical microbial identification, emerging as an alternative for rapid and cost-effective identification of strains.

Near Infrared Investigation of Polypropylene-Clay Nanocomposites for Further Quality Control Purposes-Opportunities and Limitations.

Polymer nanocomposites are usually characterized using various methods, such as small angle X-ray diffraction (XRD) or transmission electron microscopy, to gain insights into the morphology of the material. The disadvantages of these common characterization methods are that they are expensive and time consuming in terms of sample preparation and testing. In this work, near infrared spectroscopy (NIR) spectroscopy is used to characterize nanocomposites produced using a unique twin-screw mini-mixer, which is able to replicate, at ~25 g scale, the same mixing quality as in larger scale twin screw extruders. We correlated the results of X-ray diffraction, transmission electron microscopy, G′ and G″ from rotational rheology, Young’s modulus, and tensile strength with those of NIR spectroscopy. Our work has demonstrated that NIR-technology is suitable for quantitative characterization of such properties. Furthermore, the results are very promising regarding the fact that the NIR probe can be installed in a nanocomposite-processing twin screw extruder to measure inline and in real time, and could be used to help optimize the compounding process for increased quality, consistency, and enhanced product properties.

Analyzing the network formation and curing kinetics of epoxy resins by in situ near-infrared measurements with variable heating rates

Near-infrared spectroscopy (NIR) turned out to be well suited for analyzing the degree of cure for epoxy systems. In contrast to dynamic scanning calorimetry (DSC), where the released heat of reaction determines the degree of epoxy conversion indirectly, NIR spectroscopy is able to determine the conversion directly by analyzing structural changes. Therefore, a new heatable NIR cell was equipped with an integrated thermocouple, which enables the real sample temperature to be controlled and monitored in situ during epoxy curing. Dynamic scans at different heating rates were used for kinetic modelling, to define kinetic parameters and to predict real curing processes. The kinetic models and their parameters were validated with an isothermal and a more complex multi-step curing scenario. Two available commercial epoxy systems based on DGEBA were used with an anhydride and with an amine hardener. NIR results were compared with DSC data. The simulated conversion predicted with a model fitted on the basis of NIR and DSC dynamic scans showed good agreement with the conversion measured in the isothermal curing validation test. Due to the proven reliability of NIR in measuring the reaction progress of curing, it can be considered a versatile measurement system for in situ monitoring of component production in the automotive, aerospace and wind energy sectors.

Detection of adulteration in acetonitrile using near infrared spectroscopy coupled with pattern recognition techniques

In this paper, near infrared spectroscopy (NIR) in cooperation with the pattern recognition techniques were used to determine the type of neat acetonitrile and the adulteration in acetonitrile. NIR spectra were collected between 400nm and 2498nm. The experimental data were first subjected to analysis of principal component analysis (PCA) to reveal significant differences and potential patterns between samples. Then support vector machine (SVM) were applied to develop classification models and the best parameter combination was selected by grid search. Under the best parameter combination, the classification accuracy rates of three types of neat acetonitrile reached 87.5%, and 100% for the adulteration with different concentration levels. The results showed that NIR spectroscopy combined with SVM could be utilized for determining the potential adulterants including water, ethanol, isopropyl alcohol, acrylonitrile, methanol, and by-products associated with the production of acetonitrile.

Quantification of Extra-virgin Olive Oil Adulteration with Soybean Oil: a Comparative Study of NIR, MIR, and Raman Spectroscopy Associated with Chemometric Approaches

In this work, blends of olive and soybean oils were analyzed by near-infrared spectroscopy (NIR), mid-infrared (MIR), and Raman techniques to evaluate adulterations in olive oils. A representative group of different commercial brands of soybean oil and extra-virgin olive oil were analyzed by gas chromatography with flame ionization detector in order to explore the chemical similarity and composition of the fatty acid (FA) profile. Two stock solutions were prepared, one produced from a mixture of soybean oils and the other from the mixture of olive oils. From these stock solutions, 60 samples were prepared, simulating adulteration levels of extra-virgin olive oil with soybean oil between 0 and 100 %. It was possible to fit a model able to predict fraud within the interval investigated by partial least squares regression approach, with precision and accuracy values for root mean squared error of prediction of 1.76 (NIR), 4.89 (MIR), and 1.57 (Raman) and coefficient of determination R 2 greater than 0.98 for the three techniques. The methodologies demonstrated to be very useful for the quantification of extra-virgin olive oil adulteration with soybean oil, presenting short analysis time, low cost, and absence of sample preparation procedures as main advantages.

Agro-environmental characterization of semi-arid Mediterranean soils using NIR reflection and mid-IR-attenuated total reflection spectroscopies

The use of infrared spectroscopy to perform an agro-environmental soil characterization in areas with high degradation risks, like the Mediterranean semi-arid environments, has been evaluated using diffuse reflection near infrared spectroscopy (NIR) and attenuated total reflection middle infrared spectroscopy (ATR-FTIR). Soils from calcareous substratum, beneath three management types (organic, conventional and natural vegetation) have been studied. Factors like the parent material, the depth of sampling and the slope position have been considered. Although the parent material seems to be the factor most influencing the infrared spectral pattern, especially in the mid-IR region, soils under different management practices can also be differentiated on the basis of their spectral characteristics. It is interesting to note that the differences between the soils under conventional practices and after more than twenty years of organic management are much more evident for soils developed on marls than for those developed on colluvial limestones. This can be attributed to less degradation of the latter type of soils even under conventional management due to their more evolved nature and resilience. Considering the results, a combination of NIR and mid-IR spectroscopy could improve soil classification performance, being especially useful for the fast identification of those soils suffering severe degradation.

The application of near infrared spectroscopy to study lipid characteristics and deterioration of frozen lean fish muscles

Near infrared spectroscopy (NIR) was applied to estimate lipid composition and degradation of two lean fish species, saithe (Pollachius virens) and hoki (Macruronus novaezelandiae). Calibration models were developed, using partial least squares (PLS) regression, for total lipid content and composition, free fatty acids (FFA), thiobarbituric acid reactive substances (TBARS) and fluorescent interaction compounds (OFR). Coefficients of determination for calibration (R2cv) and root-mean-square error of cross validation (RMSECV) ranged from 0.82 to 0.99 and 0.66 to 3.69 for hoki and from 0.64 to 0.99 and 0.06 to 2.65 for saithe, respectively. The validations of the calibrations indicated that lipid composition and FFA of hoki and saithe can be estimated by NIR with good accuracy. Furthermore, NIR differentiate fish muscles with low, medium and high concentration of OFR and TBARS. Overall, the results demonstrate the potential for use of NIR spectroscopy as an objective and non-destructive method to inspect the lipid characteristics and quality of frozen lean fish.

Quality assessment of fruit juices by NIR spectroscopy

In the article there is described the detection of substances used for adulteration of fruit juices. They were investigated in juice products distributed within the network of retail markets. This detection was performed using the method of near-infrared spectroscopy (NIR). There were analysed samples of orange juices, apple juices, and grapefruit juices. At the beginning, there were assessed quality parameters (soluble dry matter, total acids, formol number, malic acid, citric acid, ascorbic acid, lactic acid, specific density, and ethanol content) and their compatibility with the limit values specified by the Association of the Industries of Juices and Nectars. The research covered 45 kinds of fruit juices and there was found 10 cases when at least one parameter was out of the approved limits. After that there was used the discrimination analysis and it enabled to separate pure juices from those containing at least 1 % of admixtures. This method also helped to distinguish between the group of fresh squeezed juices and the juices made of fruit concentrates. Using the diagnostics “Principal Component Scores 3D Display”, there were arranged various numbers of similar groups of juice samples with similar compound profiles.