[Rapid identification of potato cultivars using NIR-excited fluorescence and Raman spectroscopy].

PubMed

Dai, Fen; Bergholt, Mads Sylvest; Benjamin, Arnold Julian Vinoj; Hong, Tian-Sheng; Zhiwei, Huang

2014-03-01

Potato is one of the most important food in the world. Rapid and noninvasive identification of potato cultivars plays a important role in the better use of varieties. In this study, The identification ability of optical spectroscopy techniques, including near-infrared (NIR) Raman spectroscopy and NIR fluorescence spectroscopy, for invasive detection of potato cultivars was evaluated. A rapid NIR Raman spectroscopy system was applied to measure the composite Raman and NIR fluorescence spectroscopy of 3 different species of potatoes (98 samples in total) under 785 nm laser light excitation. Then pure Raman and NIR fluorescence spectroscopy were abstracted from the composite spectroscopy, respectively. At last, the partial least squares-discriminant analysis (PLS-DA) was utilized to analyze and classify Raman spectra of 3 different types of potatoes. All the samples were divided into two sets at random: the calibration set (74samples) and prediction set (24 samples), the model was validated using a leave-one-out, cross-validation method. The results showed that both the NIR-excited fluorescence spectra and pure Raman spectra could be used to identify three cultivars of potatoes. The fluorescence spectrum could distinguish the Favorita variety well (sensitivity: 1, specificity: 0.86 and accuracy: 0.92), but the result for Diamant (sensitivity: 0.75, specificity: 0.75 and accuracy: 0. 75) and Granola (sensitivity: 0.16, specificity: 0.89 and accuracy: 0.71) cultivars identification were a bit poorer. We demonstrated that Raman spectroscopy uncovered the main biochemical compositions contained in potato species, and provided a better classification sensitivity, specificity and accuracy (sensitivity: 1, specificity: 1 and accuracy: 1 for all 3 potato cultivars identification) among the three types of potatoes as compared to fluorescence spectroscopy.

In-line and real-time process monitoring of a freeze drying process using Raman and NIR spectroscopy as complementary process analytical technology (PAT) tools.

PubMed

De Beer, T R M; Vercruysse, P; Burggraeve, A; Quinten, T; Ouyang, J; Zhang, X; Vervaet, C; Remon, J P; Baeyens, W R G

2009-09-01

The aim of the present study was to examine the complementary properties of Raman and near infrared (NIR) spectroscopy as PAT tools for the fast, noninvasive, nondestructive and in-line process monitoring of a freeze drying process. Therefore, Raman and NIR probes were built in the freeze dryer chamber, allowing simultaneous process monitoring. A 5% (w/v) mannitol solution was used as model for freeze drying. Raman and NIR spectra were continuously collected during freeze drying (one Raman and NIR spectrum/min) and the spectra were analyzed using principal component analysis (PCA) and multivariate curve resolution (MCR). Raman spectroscopy was able to supply information about (i) the mannitol solid state throughout the entire process, (ii) the endpoint of freezing (endpoint of mannitol crystallization), and (iii) several physical and chemical phenomena occurring during the process (onset of ice nucleation, onset of mannitol crystallization). NIR spectroscopy proved to be a more sensitive tool to monitor the critical aspects during drying: (i) endpoint of ice sublimation and (ii) monitoring the release of hydrate water during storage. Furthermore, via NIR spectroscopy some Raman observations were confirmed: start of ice nucleation, end of mannitol crystallization and solid state characteristics of the end product. When Raman and NIR monitoring were performed on the same vial, the Raman signal was saturated during the freezing step caused by reflected NIR light reaching the Raman detector. Therefore, NIR and Raman measurements were done on a different vial. Also the importance of the position of the probes (Raman probe above the vial and NIR probe at the bottom of the sidewall of the vial) in order to obtain all required critical information is outlined. Combining Raman and NIR spectroscopy for the simultaneous monitoring of freeze drying allows monitoring almost all critical freeze drying process aspects. Both techniques do not only complement each other, they also provided mutual confirmation of specific conclusions.

Near infrared diffuse reflection and laser-induced fluorescence spectroscopy for myocardial tissue characterisation

NASA Astrophysics Data System (ADS)

Nilsson, A. M. K.; Heinrich, D.; Olajos, J.; Andersson-Engels, S.

1997-10-01

In order to evaluate the potential of cardiovascular tissue characterisation using near-infrared (NIR) spectroscopy, spectra in a previously unexplored wavelength region 0.8-2.3 μm were recorded from various pig heart tissue samples in vitro: normal myocardium (with and without endo/epicardium), aorta, fatty and fibrous heart tissue. The spectra were analysed with principal component analysis (PCA), revealing several spectroscopically characteristic features enabling tissue classification. Several of the identified spectral features could be attributed to specific tissue constituents by comparing the tissue signals with spectra obtained from water, elastin, collagen and cholesterol as well as with published data. The results obtained with the NIR spectroscopy technique in terms of its potential to classify different tissue types were compared with those from laser-induced fluorescence (LIF) using 337 nm excitation. LIF and NIR spectroscopy can in combination with PCA be used to discriminate between all previously mentioned tissue groups, apart from fatty versus fibrous tissue (LIF) and aorta versus fibrous tissue (NIR), respectively. The NIR analysis was improved by focusing the PCA to the wavelength segment 2.0-2.3 μm, resulting in successful spectral characterisation of all cardiovascular tissue groups.

Visible/near-infrared spectroscopy to predict water holding capacity in broiler breast meat

USDA-ARS?s Scientific Manuscript database

Visible/Near-infrared spectroscopy (Vis/NIRS) was examined as a tool for rapidly determining water holding capacity (WHC) in broiler breast meat. Both partial least squares (PLS) and principal component analysis (PCA) models were developed to relate Vis/NIRS spectra of 85 broiler breast meat sample...

Transmission near-infrared (NIR) and photon time-of-flight (PTOF) spectroscopy in a comparative analysis of pharmaceuticals.

PubMed

Kamran, Faisal; Abildgaard, Otto H A; Sparén, Anders; Svensson, Olof; Johansson, Jonas; Andersson-Engels, Stefan; Andersen, Peter E; Khoptyar, Dmitry

2015-03-01

We present a comprehensive study of the application of photon time-of-flight spectroscopy (PTOFS) in the wavelength range 1050-1350 nm as a spectroscopic technique for the evaluation of the chemical composition and structural properties of pharmaceutical tablets. PTOFS is compared to transmission near-infrared spectroscopy (NIRS). In contrast to transmission NIRS, PTOFS is capable of directly and independently determining the absorption and reduced scattering coefficients of the medium. Chemometric models were built on the evaluated absorption spectra for predicting tablet drug concentration. Results are compared to corresponding predictions built on transmission NIRS measurements. The predictive ability of PTOFS and transmission NIRS is comparable when models are based on uniformly distributed tablet sets. For non-uniform distribution of tablets based on particle sizes, the prediction ability of PTOFS is better than that of transmission NIRS. Analysis of reduced scattering spectra shows that PTOFS is able to characterize tablet microstructure and manufacturing process parameters. In contrast to the chemometric pseudo-variables provided by transmission NIRS, PTOFS provides physically meaningful quantities such as scattering strength and slope of particle size. The ability of PTOFS to quantify the reduced scattering spectra, together with its robustness in predicting drug content, makes it suitable for such evaluations in the pharmaceutical industry.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: A review.

PubMed

Wang, Pei; Yu, Zhiguo

2015-10-01

Near infrared (NIR) spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geographical origin discrimination.

[Application of near infrared spectroscopy technology (NIRS) in forage field].

PubMed

Yan, Xu; Bai, Shi-Qie; Yan, Jia-Jun; Gan, You-Min; Dao, Zhi-Xue

2012-07-01

The majority of nutrients in ruminants and other herbivores come from forages. Forage quality not only affects the growth and production efficiency of livestock, but also determines the final output and quality of livestock products. Forage quality mainly depends on nutrient concentrations and their digestibility, palatability and the level of presence of antiquality factors and mycotoxins in forage. Near infrared reflectance spectroscopy (NIRS) has been widely used in many research areas because it is a inexpensive, rapid, simple and nondestructive technique offering the potential for qualitative and quantitative analysis. The present paper briefly introduces the principle and characteristics of NIRS, detailedly expounds the application of NIRS in forage quality. In addition, other applications of near infrared spectroscopy technique in forage are also discussed, including forage breeding, identification of variety and classification by kind. This paper comprehensively reviews the status quo of application of NIRS in forage filed, in order to contribute to promoting development of NIRS in this field in China.

Authentication of the botanical origin of honey by near-infrared spectroscopy.

PubMed

Ruoff, Kaspar; Luginbühl, Werner; Bogdanov, Stefan; Bosset, Jacques Olivier; Estermann, Barbara; Ziolko, Thomas; Amado, Renato

2006-09-06

Fourier transform near-infrared spectroscopy (FT-NIR) was evaluated for the authentication of eight unifloral and polyfloral honey types (n = 364 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis. The corresponding error rates were calculated according to Bayes' theorem. NIR spectroscopy enabled a reliable discrimination of acacia, chestnut, and fir honeydew honey from the other unifloral and polyfloral honey types studied. The error rates ranged from <0.1 to 6.3% depending on the honey type. NIR proved also to be useful for the classification of blossom and honeydew honeys. The results demonstrate that near-infrared spectrometry is a valuable, rapid, and nondestructive tool for the authentication of the above-mentioned honeys, but not for all varieties studied.

Quality analysis, classification, and authentication of liquid foods by near-infrared spectroscopy: A review of recent research developments.

PubMed

Wang, Lu; Sun, Da-Wen; Pu, Hongbin; Cheng, Jun-Hu

2017-05-03

Nowadays, near-infrared spectroscopy (NIR) has become one of the most efficient and advanced techniques for analysis of food products. Many relevant researches have been conducted in this regard. However, no reviews about the applications of NIR for liquid food analysis are reported. Therefore, this review summarizes the recent research developments of NIR technology in the field of liquid foods, focusing on the detection of quality attributes of various liquid foods, including alcoholic beverages (red wines, rice wines, and beer), nonalcoholic beverages (juice, fruit vinegars, coffee beverages, and cola beverages), dairy products (milk and yogurt), and oils (vegetable, camellia, peanut, and virgin olive oils and frying oil). In addition, the classification and authentication detection of adulteration are also covered. It is hoped that the current paper can serve as a reference source for the future liquid food analysis by NIR techniques.

An evaluation of the use of near infrared (NIR) spectroscopy to identify water and oil-borne preservatives

Treesearch

Chi-Leung So; Stan T. Lebow; Leslie H. Groom; Todd F. Shupe

2003-01-01

In this research we experimented with a new and rapid way of analyzing wood. Near Infrared (NIR)spectroscopy together with multivariate analysis is becoming a widely used technique in the field of forest products especially for property determination and is already firmly established in the pulp and paper industry. This method is ideal for the chemical analysis of wood...

Near-infrared spectroscopy (NIRS) as a tool to monitor exhaust air from poultry operations.

PubMed

Druckenmüller, Katharina; Günther, Klaus; Elbers, Gereon

2018-07-15

Intensive poultry operation systems emit a considerable volume of inorganic and organic matter in the surrounding environment. Monitoring cleaning properties of exhaust air cleaning systems and to detect small but significant changes in emission characteristics during a fattening cycle is important for both emission and fattening process control. In the present study, we evaluated the potential of near-infrared spectroscopy (NIRS) combined with chemometric techniques as a monitoring tool of exhaust air from poultry operation systems. To generate a high-quality data set for evaluation, the exhaust air of two poultry houses was sampled by applying state-of-the-art filter sampling protocols. The two stables were identical except for one crucial difference, the presence or absence of an exhaust air cleaning system. In total, twenty-one exhaust air samples were collected at the two sites to monitor spectral differences caused by the cleaning device, and to follow changes in exhaust air characteristics during a fattening period. The total dust load was analyzed by gravimetric determination and included as a response variable in multivariate data analysis. The filter samples were directly measured with NIR spectroscopy. Principal component analysis (PCA), linear discriminant analysis (LDA), and factor analysis (FA) were effective in classifying the NIR exhaust air spectra according to fattening day and origin. The results indicate that the dust load and the composition of exhaust air (inorganic or organic matter) substantially influence the NIR spectral patterns. In conclusion, NIR spectroscopy as a tool is a promising and very rapid way to detect differences between exhaust air samples based on still not clearly defined circumstances triggered during a fattening period and the availability of an exhaust air cleaning system. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Quality assessment of pharmaceutical tablet samples using Fourier transform near infrared spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Kandpal, Lalit Mohan; Tewari, Jagdish; Gopinathan, Nishanth; Stolee, Jessica; Strong, Rick; Boulas, Pierre; Cho, Byoung-Kwan

2017-09-01

Determination of the content uniformity, assessed by the amount of an active pharmaceutical ingredient (API), and hardness of pharmaceutical materials is important for achieving a high-quality formulation and to ensure the intended therapeutic effects of the end-product. In this work, Fourier transform near infrared (FT-NIR) spectroscopy was used to determine the content uniformity and hardness of a pharmaceutical mini-tablet and standard tablet samples. Tablet samples were scanned using an FT-NIR instrument and tablet spectra were collected at wavelengths of 1000-2500 nm. Furthermore, multivariate analysis was applied to extract the relationship between the FT-NIR spectra and the measured parameters. The results of FT-NIR spectroscopy for API and hardness prediction were as precise as the reference high-performance liquid chromatography and mechanical hardness tests. For the prediction of mini-tablet API content, the highest coefficient of determination for the prediction (R2p) was found to be 0.99 with a standard error of prediction (SEP) of 0.72 mg. Moreover, the standard tablet hardness measurement had a R2p value of 0.91 with an SEP of 0.25 kg. These results suggest that FT-NIR spectroscopy is an alternative and accurate nondestructive measurement tool for the detection of the chemical and physical properties of pharmaceutical samples.

Thermally induced conformational changes in polyethylene studied by two-dimensional near-infrared infrared hetero-spectral correlation spectroscopy

NASA Astrophysics Data System (ADS)

Watanabe, Shin; Noda, Isao; Ozaki, Yukihiro

2008-07-01

The amount of nonplanar gauche bonds was monitored as a function of increasing temperature in three different polyethylene (PE) samples by means of mid-infrared (MIR) and near-infrared (NIR) spectroscopy. The hetero-spectral two-dimensional (2D) correlation analysis was carried out between the NIR spectral region of 4365-4235 cm -1 and the well-established MIR spectral region of 1375-1265 cm -1, where bands due to nonplanar conformer are detected. This approach allowed us to identify the NIR band at 4265 cm -1, which behaves in a way similar to MIR bands originating from conformational-defect sequences. By combining the result of our current study and that of our previous report obtained on different types of PE, it is suggested that the NIR band originates from conformational-defect sequences in PE. This finding opens up a unique and useful way to study the state of conformational disorder in PE crystal by NIR spectroscopy, monitoring the intensity of the NIR band at 4265 cm -1. The use of NIR spectroscopy allows researchers to directly probe the degree in the formation of conformational-defect sequences in thick, real-world PE samples that cannot be studied by conventional MIR spectroscopy. The 2D correlation spectroscopy analysis among the MIR CH 2 wagging conformational-defect-mode bands on linear low-density PE (LLDPE) and low-density PE (LDPE) revealed the formation of nonplanar conformer represented by the band at 1368 cm -1 proceeds prior to those by other band at 1308 cm -1. This result agrees well with our previous finding on high-density PE (HDPE). We therefore propose with strong confidence that the bands at 1368 and 1308 cm -1 arise from different conformational-defect sequences, even though both of the bands have been proposed to arise from the same conformer of gtg' ( kink) + gtg sequence.

Comprehensive study of solid pharmaceutical tablets in visible, near infrared (NIR), and longwave infrared (LWIR) spectral regions using a rapid simultaneous ultraviolet/visible/NIR (UVN) + LWIR laser-induced breakdown spectroscopy linear arrays detection system and a fast acousto-optic tunable filter NIR spectrometer.

PubMed

Yang, Clayton S C; Jin, Feng; Swaminathan, Siva R; Patel, Sita; Ramer, Evan D; Trivedi, Sudhir B; Brown, Ei E; Hommerich, Uwe; Samuels, Alan C

2017-10-30

This is the first report of a simultaneous ultraviolet/visible/NIR and longwave infrared laser-induced breakdown spectroscopy (UVN + LWIR LIBS) measurement. In our attempt to study the feasibility of combining the newly developed rapid LWIR LIBS linear array detection system to existing rapid analytical techniques for a wide range of chemical analysis applications, two different solid pharmaceutical tablets, Tylenol arthritis pain and Bufferin, were studied using both a recently designed simultaneous UVN + LWIR LIBS detection system and a fast AOTF NIR (1200 to 2200 nm) spectrometer. Every simultaneous UVN + LWIR LIBS emission spectrum in this work was initiated by one single laser pulse-induced micro-plasma in the ambient air atmosphere. Distinct atomic and molecular LIBS emission signatures of the target compounds measured simultaneously in UVN (200 to 1100 nm) and LWIR (5.6 to 10 µm) spectral regions are readily detected and identified without the need to employ complex data processing. In depth profiling studies of these two pharmaceutical tablets without any sample preparation, one can easily monitor the transition of the dominant LWIR emission signatures from coating ingredients gradually to the pharmaceutical ingredients underneath the coating. The observed LWIR LIBS emission signatures provide complementary molecular information to the UVN LIBS signatures, thus adding robustness to identification procedures. LIBS techniques are more surface specific while NIR spectroscopy has the capability to probe more bulk materials with its greater penetration depth. Both UVN + LWIR LIBS and NIR absorption spectroscopy have shown the capabilities of acquiring useful target analyte spectral signatures in comparable short time scales. The addition of a rapid LWIR spectroscopic probe to these widely used optical analytical methods, such as NIR spectroscopy and UVN LIBS, may greatly enhance the capability and accuracy of the combined system for a comprehensive analysis.

Application of near-infrared image processing in agricultural engineering

NASA Astrophysics Data System (ADS)

Chen, Ming-hong; Zhang, Guo-ping; Xia, Hongxing

2009-07-01

Recently, with development of computer technology, the application field of near-infrared image processing becomes much wider. In this paper the technical characteristic and development of modern NIR imaging and NIR spectroscopy analysis were introduced. It is concluded application and studying of the NIR imaging processing technique in the agricultural engineering in recent years, base on the application principle and developing characteristic of near-infrared image. The NIR imaging would be very useful in the nondestructive external and internal quality inspecting of agricultural products. It is important to detect stored-grain insects by the application of near-infrared spectroscopy. Computer vision detection base on the NIR imaging would be help to manage food logistics. Application of NIR imaging promoted quality management of agricultural products. In the further application research fields of NIR image in the agricultural engineering, Some advices and prospect were put forward.

Determination of main components and anaerobic rumen digestibility of aquatic plants in vitro using near-infrared-reflectance spectroscopy.

PubMed

Yue, Zheng-Bo; Zhang, Meng-Lin; Sheng, Guo-Ping; Liu, Rong-Hua; Long, Ying; Xiang, Bing-Ren; Wang, Jin; Yu, Han-Qing

2010-04-01

A near-infrared-reflectance (NIR) spectroscopy-based method is established to determine the main components of aquatic plants as well as their anaerobic rumen biodegradability. The developed method is more rapid and accurate compared to the conventional chemical analysis and biodegradability tests. Moisture, volatile solid, Klason lignin and ash in entire aquatic plants could be accurately predicted using this method with coefficient of determination (r(2)) values of 0.952, 0.916, 0.939 and 0.950, respectively. In addition, the anaerobic rumen biodegradability of aquatic plants, represented as biogas and methane yields, could also be predicted well. The algorithm of continuous wavelet transform for the NIR spectral data pretreatment is able to greatly enhance the robustness and predictive ability of the NIR spectral analysis. These results indicate that NIR spectroscopy could be used to predict the main components of aquatic plants and their anaerobic biodegradability. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Nondestructive NIR reflectance spectroscopic method for rapid fatty acid analysis of peanut seeds

USDA-ARS?s Scientific Manuscript database

NIR reflectance spectroscopy was used to analyze the fatty acid concentration present in breeder's peanut seeds samples, rapidly and nondestructively. Absorbance spectra were collected in the wavelength range from 400 nm to 2500 nm using a NIR spectrometer. Fatty acids, oleic, linoleic and palmitic ...

Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis.

PubMed

Carp, Stefan A; Farzam, Parisa; Redes, Norin; Hueber, Dennis M; Franceschini, Maria Angela

2017-09-01

Frequency domain near infrared spectroscopy (FD-NIRS) and diffuse correlation spectroscopy (DCS) have emerged as synergistic techniques for the non-invasive assessment of tissue health. Combining FD-NIRS oximetry with DCS measures of blood flow, the tissue oxygen metabolic rate can be quantified, a parameter more closely linked to underlying physiology and pathology than either NIRS or DCS estimates alone. Here we describe the first commercially available integrated instrument, called the "MetaOx", designed to enable simultaneous FD-NIRS and DCS measurements at rates of 10 + Hz, and offering real-time data evaluation. We show simultaneously acquired characterization data demonstrating performance equivalent to individual devices and sample in vivo measurements of pulsation resolved blood flow, forearm occlusion hemodynamic changes and muscle oxygen metabolic rate monitoring during stationary bike exercise.

Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis

PubMed Central

Carp, Stefan A.; Farzam, Parisa; Redes, Norin; Hueber, Dennis M.; Franceschini, Maria Angela

2017-01-01

Frequency domain near infrared spectroscopy (FD-NIRS) and diffuse correlation spectroscopy (DCS) have emerged as synergistic techniques for the non-invasive assessment of tissue health. Combining FD-NIRS oximetry with DCS measures of blood flow, the tissue oxygen metabolic rate can be quantified, a parameter more closely linked to underlying physiology and pathology than either NIRS or DCS estimates alone. Here we describe the first commercially available integrated instrument, called the “MetaOx”, designed to enable simultaneous FD-NIRS and DCS measurements at rates of 10 + Hz, and offering real-time data evaluation. We show simultaneously acquired characterization data demonstrating performance equivalent to individual devices and sample in vivo measurements of pulsation resolved blood flow, forearm occlusion hemodynamic changes and muscle oxygen metabolic rate monitoring during stationary bike exercise. PMID:29026684

High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

PubMed

Laurens, L M L; Wolfrum, E J

2013-12-18

One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

Two-dimensional correlation spectroscopy reveals the underlying compositions for FT-NIR identification of the medicinal bulbs of the genus Fritillaria

NASA Astrophysics Data System (ADS)

Chen, Jianbo; Wang, Yue; Liu, Aoxue; Rong, Lixin; Wang, Jingjuan

2018-03-01

Fritillariae Bulbus, the dried bulbs of several species of the genus Fritillaria, is often used in traditional Chinese medicine for the treatment of cough and pulmonary diseases. However, the similar appearances make it difficult to identify different kinds of Fritillariae Bulbus. In this research, Fourier transform near-infrared (FT-NIR) spectroscopy with a reflection fiber probe is employed for the direct testing and automatic identification of different kinds of Fritillariae Bulbus to ensure the authenticity, efficacy and safety. The bulbs can be measured directly without pulverizing. According to the two-dimensional (2D) correlation analysis and statistical analysis, the height ratio of the two peaks near 4860 cm-1 and 4750 cm-1 in the second derivative spectra is specific to the species of Fritillariae Bulbus. This indicates that the relative amount of protein and carbohydrate may be critical to identify Fritillariae Bulbus. With the help of the SIMCA model, the four kinds of Fritillariae Bulbus can be identified correctly by FT-NIR spectroscopy. The results show the potential of FT-NIR spectroscopy with a reflection fiber probe in the rapid testing and identification of Fritillariae Bulbus.

Diagnosis of colorectal cancer by near-infrared optical fiber spectroscopy and random forest

NASA Astrophysics Data System (ADS)

Chen, Hui; Lin, Zan; Wu, Hegang; Wang, Li; Wu, Tong; Tan, Chao

2015-01-01

Near-infrared (NIR) spectroscopy has such advantages as being noninvasive, fast, relatively inexpensive, and no risk of ionizing radiation. Differences in the NIR signals can reflect many physiological changes, which are in turn associated with such factors as vascularization, cellularity, oxygen consumption, or remodeling. NIR spectral differences between colorectal cancer and healthy tissues were investigated. A Fourier transform NIR spectroscopy instrument equipped with a fiber-optic probe was used to mimic in situ clinical measurements. A total of 186 spectra were collected and then underwent the preprocessing of standard normalize variate (SNV) for removing unwanted background variances. All the specimen and spots used for spectral collection were confirmed staining and examination by an experienced pathologist so as to ensure the representative of the pathology. Principal component analysis (PCA) was used to uncover the possible clustering. Several methods including random forest (RF), partial least squares-discriminant analysis (PLSDA), K-nearest neighbor and classification and regression tree (CART) were used to extract spectral features and to construct the diagnostic models. By comparison, it reveals that, even if no obvious difference of misclassified ratio (MCR) was observed between these models, RF is preferable since it is quicker, more convenient and insensitive to over-fitting. The results indicate that NIR spectroscopy coupled with RF model can serve as a potential tool for discriminating the colorectal cancer tissues from normal ones.

A novel combined approach of diffuse reflectance UV-Vis-NIR spectroscopy and multivariate analysis for non-destructive examination of blue ballpoint pen inks in forensic application

NASA Astrophysics Data System (ADS)

Kumar, Raj; Sharma, Vishal

2017-03-01

The present research is focused on the analysis of writing inks using destructive UV-Vis spectroscopy (dissolution of ink by the solvent) and non-destructive diffuse reflectance UV-Vis-NIR spectroscopy along with Chemometrics. Fifty seven samples of blue ballpoint pen inks were analyzed under optimum conditions to determine the differences in spectral features of inks among same and different manufacturers. Normalization was performed on the spectroscopic data before chemometric analysis. Principal Component Analysis (PCA) and K-mean cluster analysis were used on the data to ascertain whether the blue ballpoint pen inks could be differentiated by their UV-Vis/UV-Vis NIR spectra. The discriminating power is calculated by qualitative analysis by the visual comparison of the spectra (absorbance peaks), produced by the destructive and non-destructive methods. In the latter two methods, the pairwise comparison is made by incorporating the clustering method. It is found that chemometric method provides better discriminating power (98.72% and 99.46%, in destructive and non-destructive, respectively) in comparison to the qualitative analysis (69.67%).

Near and mid infrared spectroscopy and multivariate data analysis in studies of oxidation of edible oils.

PubMed

Wójcicki, Krzysztof; Khmelinskii, Igor; Sikorski, Marek; Sikorska, Ewa

2015-11-15

Infrared spectroscopic techniques and chemometric methods were used to study oxidation of olive, sunflower and rapeseed oils. Accelerated oxidative degradation of oils at 60°C was monitored using peroxide values and FT-MIR ATR and FT-NIR transmittance spectroscopy. Principal component analysis (PCA) facilitated visualization and interpretation of spectral changes occurring during oxidation. Multivariate curve resolution (MCR) method found three spectral components in the NIR and MIR spectral matrix, corresponding to the oxidation products, and saturated and unsaturated structures. Good quantitative relation was found between peroxide value and contribution of oxidation products evaluated using MCR--based on NIR (R(2) = 0.890), MIR (R(2) = 0.707) and combined NIR and MIR (R(2) = 0.747) data. Calibration models for prediction peroxide value established using partial least squares (PLS) regression were characterized for MIR (R(2) = 0.701, RPD = 1.7), NIR (R(2) = 0.970, RPD = 5.3), and combined NIR and MIR data (R(2) = 0.954, RPD = 3.1). Copyright © 2015 Elsevier Ltd. All rights reserved.

Sleep apnea termination decreases cerebral blood volume: a near-infrared spectroscopy case study

NASA Astrophysics Data System (ADS)

Virtanen, Jaakko; Noponen, Tommi; Salmi, Tapani; Toppila, Jussi; Meriläinen, Pekka

2009-07-01

Medical near-infrared spectroscopy (NIRS) can be used to estimate cerebral haemodynamic changes non-invasively. Sleep apnea is a common sleep disorder where repetitive pauses in breathing decrease the quality of sleep and exposes the individual to various health problems. We have measured oxygenated and deoxygenated haemoglobin concentration changes during apneic events in sleep from the forehead of one subject using NIRS and used principal component analysis to extract extracerebral and cortical haemodynamic changes from NIRS signals. Comparison of NIRS signals with EEG, bioimpedance, and pulse oximetry data suggests that termination of apnea leads to decreases in cerebral blood volume and flow that may be related to neurological arousal via neurovascular coupling.

[Application of near-infrared spectroscopy to agriculture and food analysis].

PubMed

Wang, Duo-jia; Zhou, Xiang-yang; Jin, Tong-ming; Hu, Xiang-na; Zhong, Jiao-e; Wu, Qi-tang

2004-04-01

Near-Infrared Spectroscopy (NIRS) is the most rapidly developing and the most noticeable spectrographic technique in the 90's (the last century). Its principle and characteristics were explained in this paper, and the development of NIRS instrumentation, the methodology of spectrum pre-processing, as well as the chemical metrology were also introduced. The anthors mainly summarized the applications to agriculture and food, especially in-line analysis methods, which have been used in production procedure by fiber optics. The authors analyzed the NIRS application status in China, and made the first proposal to establish information sharing mode between central database and end-user by using network technology and concentrating valuable resources.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review.

PubMed

Kamran, Muhammad A; Mannan, Malik M Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review

PubMed Central

Kamran, Muhammad A.; Mannan, Malik M. Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized. PMID:27375458

Design of an FT-NIR spectrometer for online quality analysis of traditional Chinese medicine manufacturing process

NASA Astrophysics Data System (ADS)

Zhu, Ren; Wu, Lan; Wang, Shiming; Ye, Linhua; Ding, Zhihua

2008-03-01

As a fast, non-destructive analysis method, Fourier transform (FT) near-infrared (NIR) spectroscopy is very suitable and effective for online quality analysis of traditional Chinese medicine (TCM) manufacturing process. In this thesis, the theoretics of FT-NIRS was analyzed and an FT-NIR spectrometer with 4 cm -1 resolution in the 12500-5000 cm -1 frequency range was designed. The spectrometer was based on a Michelson interferometer with Bromine tungsten lamp as the NIR light source and InGaAs detector to collect the interference signal. Each element was designed and chosen to provide maximum sensitivity in the NIR spectral region. A fiber-optic flow cell system was used to realize online analysis of traditional Chinese medicine. The performance of the spectrometer was evaluated and the feasibility of using FT-NIR spectrometer to get absorption spectra of traditional Chinese medicine was demonstrated.

Near-infrared imaging spectroscopy for counterfeit drug detection

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2011-06-01

Pharmaceutical counterfeiting is a significant issue in the healthcare community as well as for the pharmaceutical industry worldwide. The use of counterfeit medicines can result in treatment failure or even death. A rapid screening technique such as near infrared (NIR) spectroscopy could aid in the search for and identification of counterfeit drugs. This work presents a comparison of two laboratory NIR imaging systems and the chemometric analysis of the acquired spectroscopic image data. The first imaging system utilizes a NIR liquid crystal tuneable filter and is designed for the investigation of stationary objects. The second imaging system utilizes a NIR imaging spectrograph and is designed for the fast analysis of moving objects on a conveyor belt. Several drugs in form of tablets and capsules were analyzed. Spectral unmixing techniques were applied to the mixed reflectance spectra to identify constituent parts of the investigated drugs. The results show that NIR spectroscopic imaging can be used for contact-less detection and identification of a variety of counterfeit drugs.

[Near infrared reflectance spectroscopy (NIRS): a novel approach to reconstructing historical changes of primary productivity in Antarctic lake].

PubMed

Chen, Qian-Qian; Liu, Xiao-Dong; Liu, Wen-Qi; Jiang, Shan

2011-10-01

Compared with traditional chemical analysis methods, reflectance spectroscopy has the advantages of speed, minimal or no sample preparation, non-destruction, and low cost. In order to explore the potential application of spectroscopy technology in the paleolimnological study on Antarctic lakes, we took a lake sediment core in Mochou Lake at Zhongshan Station of Antarctic, and analyzed the near infrared reflectance spectroscopy (NIRS) data in the sedimentary samples. The results showed that the factor loadings of principal component analysis (PCA) displayed very similar depth-profile change pattern with the S2 index, a reliable proxy for the change in historical lake primary productivity. The correlation analysis showed that the values of PCA factor loading and S2 were correlated significantly, suggesting that it is feasible to infer paleoproductivity changes recorded in Antarctic lakes using NIRS technology. Compared to the traditional method of the trough area between 650 and 700 nm, the authors found that the PCA statistical approach was more accurate for reconstructing the change in historical lake primary productivity. The results reported here demonstrate that reflectance spectroscopy can provide a rapid method for the reconstruction of lake palaeoenviro nmental change in the remote Antarctic regions.

Development and Testing of an LED-Based Near-Infrared Sensor for Human Kidney Tumor Diagnostics

PubMed Central

Zabarylo, Urszula; Kirsanov, Dmitry; Belikova, Valeria; Ageev, Vladimir; Usenov, Iskander; Galyanin, Vladislav; Minet, Olaf; Sakharova, Tatiana; Danielyan, Georgy; Feliksberger, Elena; Artyushenko, Viacheslav

2017-01-01

Optical spectroscopy is increasingly used for cancer diagnostics. Tumor detection feasibility in human kidney samples using mid- and near-infrared (NIR) spectroscopy, fluorescence spectroscopy, and Raman spectroscopy has been reported (Artyushenko et al., Spectral fiber sensors for cancer diagnostics in vitro. In Proceedings of the European Conference on Biomedical Optics, Munich, Germany, 21–25 June 2015). In the present work, a simplification of the NIR spectroscopic analysis for cancer diagnostics was studied. The conventional high-resolution NIR spectroscopic method of kidney tumor diagnostics was replaced by a compact optical sensing device constructively represented by a set of four light-emitting diodes (LEDs) at selected wavelengths and one detecting photodiode. Two sensor prototypes were tested using 14 in vitro clinical samples of 7 different patients. Statistical data evaluation using principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) confirmed the general applicability of the LED-based sensing approach to kidney tumor detection. An additional validation of the results was performed by means of sample permutation. PMID:28825612

Exploring the use of optical flow for the study of functional NIRS signals

NASA Astrophysics Data System (ADS)

Fernandez Rojas, Raul; Huang, Xu; Ou, Keng-Liang; Hernandez-Juarez, Jesus

2017-03-01

Near infrared spectroscopy (NIRS) is an optical imaging technique that allows real-time measurements of Oxy and Deoxy-hemoglobin concentrations in human body tissue. In functional NIRS (fNIRS), this technique is used to study cortical activation in response to changes in neural activity. However, analysis of activation regions using NIRS is a challenging task in the field of medical image analysis and despite existing solutions, no homogeneous analysis method has yet been determined. For that reason, the aim of our present study is to report the use of an optical flow method for the analysis of cortical activation using near-infrared spectroscopy signals. We used real fNIRS data recorded from a noxious stimulation experiment as base of our implementation. To compute the optical flow algorithm, we first arrange NIRS signals (Oxy-hemoglobin) following our 24 channels (12 channels per hemisphere) head-probe configuration to create image-like samples. We then used two consecutive fNIRS samples per hemisphere as input frames for the optical flow algorithm, making one computation per hemisphere. The output from these two computations is the velocity field representing cortical activation from each hemisphere. The experimental results showed that the radial structure of flow vectors exhibited the origin of cortical activity, the development of stimulation as expansion or contraction of such flow vectors, and the flow of activation patterns may suggest prediction in cortical activity. The present study demonstrates that optical flow provides a power tool for the analysis of NIRS signals. Finally, we suggested a novel idea to identify pain status in nonverbal patients by using optical flow motion vectors; however, this idea will be study further in our future research.

A preliminary study of preservative retention and penetration in ACQ-treated timbers using near infrared spectroscopy

Treesearch

Chi-Leung So; Thomas L. Eberhardt; Stan T. Lebow; Leslie H. Groom

2006-01-01

Near infrared (NIR) spectroscopy has been previously used in our laboratory to predict copper, chromium, and arsenic levels in samples of chromated copper arsenate (CCA)-treated wood. In the present study, we utilized our custom-made NIR scanning system, NIRVANA (near infrared visual and automated numerical analysis), to scan cross sections of ACQ (alkaline copper quat...

Infrared Spectroscopy as a Versatile Analytical Tool for the Quantitative Determination of Antioxidants in Agricultural Products, Foods and Plants

PubMed Central

Cozzolino, Daniel

2015-01-01

Spectroscopic methods provide with very useful qualitative and quantitative information about the biochemistry and chemistry of antioxidants. Near infrared (NIR) and mid infrared (MIR) spectroscopy are considered as powerful, fast, accurate and non-destructive analytical tools that can be considered as a replacement of traditional chemical analysis. In recent years, several reports can be found in the literature demonstrating the usefulness of these methods in the analysis of antioxidants in different organic matrices. This article reviews recent applications of infrared (NIR and MIR) spectroscopy in the analysis of antioxidant compounds in a wide range of samples such as agricultural products, foods and plants. PMID:26783838

Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity

NASA Astrophysics Data System (ADS)

Zhang, Lei; Sun, Jinyan; Sun, Bailei; Luo, Qingming; Gong, Hui

2014-05-01

Near-infrared spectroscopy (NIRS) is a developing and promising functional brain imaging technology. Developing data analysis methods to effectively extract meaningful information from collected data is the major bottleneck in popularizing this technology. In this study, we measured hemodynamic activity of the prefrontal cortex (PFC) during a color-word matching Stroop task using NIRS. Hemispheric lateralization was examined by employing traditional activation and novel NIRS-based connectivity analyses simultaneously. Wavelet transform coherence was used to assess intrahemispheric functional connectivity. Spearman correlation analysis was used to examine the relationship between behavioral performance and activation/functional connectivity, respectively. In agreement with activation analysis, functional connectivity analysis revealed leftward lateralization for the Stroop effect and correlation with behavioral performance. However, functional connectivity was more sensitive than activation for identifying hemispheric lateralization. Granger causality was used to evaluate the effective connectivity between hemispheres. The results showed increased information flow from the left to the right hemispheres for the incongruent versus the neutral task, indicating a leading role of the left PFC. This study demonstrates that the NIRS-based connectivity can reveal the functional architecture of the brain more comprehensively than traditional activation, helping to better utilize the advantages of NIRS.

[Research progress and application prospect of near infrared spectroscopy in soil nutrition analysis].

PubMed

Ding, Hai-quan; Lu, Qi-peng

2012-01-01

"Digital agriculture" or "precision agriculture" is an important direction of modern agriculture technique. It is the combination of the modern information technique and traditional agriculture and becomes a hotspot field in international agriculture research in recent years. As a nondestructive, real-time, effective and exact analysis technique, near infrared spectroscopy, by which precision agriculture could be carried out, has vast prospect in agrology and gradually gained the recognition. The present paper intends to review the basic theory of near infrared spectroscopy and its applications in the field of agrology, pointing out that the direction of NIR in agrology should based on portable NIR spectrograph in order to acquire qualitative or quantitative information from real-time measuring in field. In addition, NIRS could be combined with space remote sensing to macroscopically control the way crop is growing and the nutrition crops need, to change the current state of our country's agriculture radically.

Rapid characterization of transgenic and non-transgenic soybean oils by chemometric methods using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Luna, Aderval S.; da Silva, Arnaldo P.; Pinho, Jéssica S. A.; Ferré, Joan; Boqué, Ricard

Near infrared (NIR) spectroscopy and multivariate classification were applied to discriminate soybean oil samples into non-transgenic and transgenic. Principal Component Analysis (PCA) was applied to extract relevant features from the spectral data and to remove the anomalous samples. The best results were obtained when with Support Vectors Machine-Discriminant Analysis (SVM-DA) and Partial Least Squares-Discriminant Analysis (PLS-DA) after mean centering plus multiplicative scatter correction. For SVM-DA the percentage of successful classification was 100% for the training group and 100% and 90% in validation group for non transgenic and transgenic soybean oil samples respectively. For PLS-DA the percentage of successful classification was 95% and 100% in training group for non transgenic and transgenic soybean oil samples respectively and 100% and 80% in validation group for non transgenic and transgenic respectively. The results demonstrate that NIR spectroscopy can provide a rapid, nondestructive and reliable method to distinguish non-transgenic and transgenic soybean oils.

[Proximate analysis of straw by near infrared spectroscopy (NIRS)].

PubMed

Huang, Cai-jin; Han, Lu-jia; Liu, Xian; Yang, Zeng-ling

2009-04-01

Proximate analysis is one of the routine analysis procedures in utilization of straw for biomass energy use. The present paper studied the applicability of rapid proximate analysis of straw by near infrared spectroscopy (NIRS) technology, in which the authors constructed the first NIRS models to predict volatile matter and fixed carbon contents of straw. NIRS models were developed using Foss 6500 spectrometer with spectra in the range of 1,108-2,492 nm to predict the contents of moisture, ash, volatile matter and fixed carbon in the directly cut straw samples; to predict ash, volatile matter and fixed carbon in the dried milled straw samples. For the models based on directly cut straw samples, the determination coefficient of independent validation (R2v) and standard error of prediction (SEP) were 0.92% and 0.76% for moisture, 0.94% and 0.84% for ash, 0.88% and 0.82% for volatile matter, and 0.75% and 0.65% for fixed carbon, respectively. For the models based on dried milled straw samples, the determination coefficient of independent validation (R2v) and standard error of prediction (SEP) were 0.98% and 0.54% for ash, 0.95% and 0.57% for volatile matter, and 0.78% and 0.61% for fixed carbon, respectively. It was concluded that NIRS models can predict accurately as an alternative analysis method, therefore rapid and simultaneous analysis of multicomponents can be achieved by NIRS technology, decreasing the cost of proximate analysis for straw.

A novel combined approach of diffuse reflectance UV-Vis-NIR spectroscopy and multivariate analysis for non-destructive examination of blue ballpoint pen inks in forensic application.

PubMed

Kumar, Raj; Sharma, Vishal

2017-03-15

The present research is focused on the analysis of writing inks using destructive UV-Vis spectroscopy (dissolution of ink by the solvent) and non-destructive diffuse reflectance UV-Vis-NIR spectroscopy along with Chemometrics. Fifty seven samples of blue ballpoint pen inks were analyzed under optimum conditions to determine the differences in spectral features of inks among same and different manufacturers. Normalization was performed on the spectroscopic data before chemometric analysis. Principal Component Analysis (PCA) and K-mean cluster analysis were used on the data to ascertain whether the blue ballpoint pen inks could be differentiated by their UV-Vis/UV-Vis NIR spectra. The discriminating power is calculated by qualitative analysis by the visual comparison of the spectra (absorbance peaks), produced by the destructive and non-destructive methods. In the latter two methods, the pairwise comparison is made by incorporating the clustering method. It is found that chemometric method provides better discriminating power (98.72% and 99.46%, in destructive and non-destructive, respectively) in comparison to the qualitative analysis (69.67%). Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation of Sensory Analysis Cupping Test Arabica Coffee Using NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Safrizal; Sutrisno; Lilik, P. E. N.; Ahmad, U.; Samsudin

2018-05-01

Flavors have become the most important coffee quality parameters now day, many coffee consuming countries require certain taste scores for the coffee to be ordered, the currently used cupping method of appraisal is the method designed by The Specialty Coffee Association Of America (SCAA), from several previous studies was found that Near-Infrared Spectroscopy (NIRS) can be used to detect chemical composition of certain materials including those associated with flavor so it is possible also to be applied to coffee powder. The aim of this research is to get correlation between NIRS spectrum with cupping scoring by tester, then look at the possibility of testing coffee taste sensors using NIRS spectrum. The coffee samples were taken from various places, altitudes and postharvest handling methods, then the samples were prepared following the SCAA protocol, for sensory analysis was done in two ways, with the expert tester and with the NIRS test. The calibration between both found that Without pretreatment using PLS get RMSE cross validation 6.14, using Multiplicative Scatter Correction spectra obtained RMSE cross validation 5.43, the best RMSE cross-validation was 1.73 achieved by de-trending correction, NIRS can be used to predict the score of cupping.

7 CFR 801.7 - Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers.

Code of Federal Regulations, 2013 CFR

2013-01-01

..._of_federal_regulations/ibr_locations.html. (b) Tolerances—(1) NIRS wheat protein analyzers. The... Method 992.23. (3) NIRS corn oil, protein, and starch analyzers. The maintenance tolerances for the NIRS... methods and tolerances for near-infrared spectroscopy (NIRS) analyzers. (a) Reference methods. (1) The...

7 CFR 801.7 - Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers.

Code of Federal Regulations, 2011 CFR

2011-01-01

..._of_federal_regulations/ibr_locations.html. (b) Tolerances—(1) NIRS wheat protein analyzers. The... Method 992.23. (3) NIRS corn oil, protein, and starch analyzers. The maintenance tolerances for the NIRS... methods and tolerances for near-infrared spectroscopy (NIRS) analyzers. (a) Reference methods. (1) The...

7 CFR 801.7 - Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers.

Code of Federal Regulations, 2014 CFR

2014-01-01

..._of_federal_regulations/ibr_locations.html. (b) Tolerances—(1) NIRS wheat protein analyzers. The... Method 992.23. (3) NIRS corn oil, protein, and starch analyzers. The maintenance tolerances for the NIRS... methods and tolerances for near-infrared spectroscopy (NIRS) analyzers. (a) Reference methods. (1) The...

7 CFR 801.7 - Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers.

Code of Federal Regulations, 2012 CFR

2012-01-01

..._of_federal_regulations/ibr_locations.html. (b) Tolerances—(1) NIRS wheat protein analyzers. The... Method 992.23. (3) NIRS corn oil, protein, and starch analyzers. The maintenance tolerances for the NIRS... methods and tolerances for near-infrared spectroscopy (NIRS) analyzers. (a) Reference methods. (1) The...

NIR monitoring of in-service wood structures

Treesearch

Michela Zanetti; Timothy G. Rials; Douglas Rammer

2005-01-01

Near infrared spectroscopy (NIRS) was used to study a set of Southern Yellow Pine boards exposed to natural weathering for different periods of exposure time. This non-destructive spectroscopic technique is a very powerful tool to predict the weathering of wood when used in combination with multivariate analysis (Principal Component Analysis, PCA, and Projection to...

Application of the near-infrared spectroscopy in the pharmaceutical technology.

PubMed

Jamrógiewicz, Marzena

2012-07-01

Near-infrared (NIR) spectroscopy is currently the fastest-growing and the most versatile analytical method not only in the pharmaceutical sciences but also in the industry. This review focuses on recent NIR applications in the pharmaceutical technology. This article covers monitoring, by NIR, of many manufacturing processes, such as granulation, mixing or drying, in order to determine the end-point of these processes. In this paper, apart from basic theoretical information concerning the NIR spectra, there are included determinations of the quality and quantity of pharmaceutical compounds. Some examples of measurements and control of physicochemical parameters of the final medicinal products, such as hardness, porosity, thickness size, compression strength, disintegration time and potential counterfeit are included. Biotechnology and plant drug analysis using NIR is also described. Moreover, some disadvantages of this method are stressed and future perspectives are anticipated. Copyright © 2012 Elsevier B.V. All rights reserved.

Reflectance-mode interferometric near-infrared spectroscopy quantifies brain absorption, scattering, and blood flow index in vivo.

PubMed

Borycki, Dawid; Kholiqov, Oybek; Srinivasan, Vivek J

2017-02-01

Interferometric near-infrared spectroscopy (iNIRS) is a new technique that measures time-of-flight- (TOF-) resolved autocorrelations in turbid media, enabling simultaneous estimation of optical and dynamical properties. Here, we demonstrate reflectance-mode iNIRS for noninvasive monitoring of a mouse brain in vivo. A method for more precise quantification with less static interference from superficial layers, based on separating static and dynamic components of the optical field autocorrelation, is presented. Absolute values of absorption, reduced scattering, and blood flow index (BFI) are measured, and changes in BFI and absorption are monitored during a hypercapnic challenge. Absorption changes from TOF-resolved iNIRS agree with absorption changes from continuous wave NIRS analysis, based on TOF-integrated light intensity changes, an effective path length, and the modified Beer-Lambert Law. Thus, iNIRS is a promising approach for quantitative and noninvasive monitoring of perfusion and optical properties in vivo.

Variety identification of brown sugar using short-wave near infrared spectroscopy and multivariate calibration

NASA Astrophysics Data System (ADS)

Yang, Haiqing; Wu, Di; He, Yong

2007-11-01

Near-infrared spectroscopy (NIRS) with the characteristics of high speed, non-destructiveness, high precision and reliable detection data, etc. is a pollution-free, rapid, quantitative and qualitative analysis method. A new approach for variety discrimination of brown sugars using short-wave NIR spectroscopy (800-1050nm) was developed in this work. The relationship between the absorbance spectra and brown sugar varieties was established. The spectral data were compressed by the principal component analysis (PCA). The resulting features can be visualized in principal component (PC) space, which can lead to discovery of structures correlative with the different class of spectral samples. It appears to provide a reasonable variety clustering of brown sugars. The 2-D PCs plot obtained using the first two PCs can be used for the pattern recognition. Least-squares support vector machines (LS-SVM) was applied to solve the multivariate calibration problems in a relatively fast way. The work has shown that short-wave NIR spectroscopy technique is available for the brand identification of brown sugar, and LS-SVM has the better identification ability than PLS when the calibration set is small.

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

PubMed

Risoluti, R; Materazzi, S; Gregori, A; Ripani, L

2016-06-01

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. Copyright © 2016 Elsevier B.V. All rights reserved.

Univariate and multivariate analysis of tannin-impregnated wood species using vibrational spectroscopy.

PubMed

Schnabel, Thomas; Musso, Maurizio; Tondi, Gianluca

2014-01-01

Vibrational spectroscopy is one of the most powerful tools in polymer science. Three main techniques--Fourier transform infrared spectroscopy (FT-IR), FT-Raman spectroscopy, and FT near-infrared (NIR) spectroscopy--can also be applied to wood science. Here, these three techniques were used to investigate the chemical modification occurring in wood after impregnation with tannin-hexamine preservatives. These spectroscopic techniques have the capacity to detect the externally added tannin. FT-IR has very strong sensitivity to the aromatic peak at around 1610 cm(-1) in the tannin-treated samples, whereas FT-Raman reflects the peak at around 1600 cm(-1) for the externally added tannin. This high efficacy in distinguishing chemical features was demonstrated in univariate analysis and confirmed via cluster analysis. Conversely, the results of the NIR measurements show noticeable sensitivity for small differences. For this technique, multivariate analysis is required and with this chemometric tool, it is also possible to predict the concentration of tannin on the surface.

A fiber optic probe coupled low-cost CMOS-camera-based system for simultaneous measurement of oxy-, deoxyhemoglobin, and blood flow

NASA Astrophysics Data System (ADS)

Seong, Myeongsu; Phillips, Zephaniah; Mai, Phuong M.; Yeo, Chaebeom; Song, Cheol; Lee, Kijoon; Kim, Jae G.

2015-07-01

Appropriate oxygen supply and blood flow are important in coordination of body functions and maintaining a life. To measure both oxygen supply and blood flow simultaneously, we developed a system that combined near-infrared spectroscopy (NIRS) and diffuse speckle contrast analysis (DSCA). Our system is more cost effective and compact than such combined systems as diffuse correlation spectroscopy(DCS)-NIRS or DCS flow oximeter, and also offers the same quantitative information. In this article, we present the configuration of DSCA-NIRS and preliminary data from an arm cuff occlusion and a repeated gripping exercise. With further investigation, we believe that DSCA-NIRS can be a useful tool for the field of neuroscience, muscle physiology and metabolic diseases such as diabetes.

Near-Infrared Spatially Resolved Spectroscopy for Tablet Quality Determination.

PubMed

Igne, Benoît; Talwar, Sameer; Feng, Hanzhou; Drennen, James K; Anderson, Carl A

2015-12-01

Near-infrared (NIR) spectroscopy has become a well-established tool for the characterization of solid oral dosage forms manufacturing processes and finished products. In this work, the utility of a traditional single-point NIR measurement was compared with that of a spatially resolved spectroscopic (SRS) measurement for the determination of tablet assay. Experimental designs were used to create samples that allowed for calibration models to be developed and tested on both instruments. Samples possessing a poor distribution of ingredients (highly heterogeneous) were prepared by under-blending constituents prior to compaction to compare the analytical capabilities of the two NIR methods. The results indicate that SRS can provide spatial information that is usually obtainable only through imaging experiments for the determination of local heterogeneity and detection of abnormal tablets that would not be detected with single-point spectroscopy, thus complementing traditional NIR measurement systems for in-line, and in real-time tablet analysis. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibodies in blood sera of domestic cats

NASA Astrophysics Data System (ADS)

Duarte, Janaina; Pacheco, Marcos T. T.; Silveira, Landulfo, Jr.; Machado, Rosangela Z.; Martins, Rodrigo A. L.; Zangaro, Renato A.; Villaverde, Antonio G. J. B.

2001-05-01

Near-infrared (NIR) Raman spectroscopy has been studied for the last years for many biomedical applications. It is a powerful tool for biological materials analysis. Toxoplasmosis is an important zoonosis in public health, cats being the principal responsible for the transmission of the disease in Brazil. The objective of this work is to investigate a new method of diagnosis of this disease. NIR Raman spectroscopy was used to detect anti Toxoplasma gondii antibodies in blood sera from domestic cats, without sample preparation. In all, six blood serum samples were used for this study. A previous serological test was done by the Indirect Immunoenzymatic Assay (ELISA) to permit a comparative study between both techniques and it showed that three serum samples were positive and the other three were negative to toxoplasmosis. Raman spectra were taken for all the samples and analyzed by using the principal components analysis (PCA). A diagnosis parameter was defined from the analysis of the second and third principal components of the Raman spectra. It was found that this parameter can detect the infection level of the animal. The results have indicated that NIR Raman spectroscopy, associated to the PCA can be a promising technique for serological analysis, such as toxoplasmosis, allowing a fast and sensitive method of diagnosis.

Quantitative analysis of binary polymorphs mixtures of fusidic acid by diffuse reflectance FTIR spectroscopy, diffuse reflectance FT-NIR spectroscopy, Raman spectroscopy and multivariate calibration.

PubMed

Guo, Canyong; Luo, Xuefang; Zhou, Xiaohua; Shi, Beijia; Wang, Juanjuan; Zhao, Jinqi; Zhang, Xiaoxia

2017-06-05

Vibrational spectroscopic techniques such as infrared, near-infrared and Raman spectroscopy have become popular in detecting and quantifying polymorphism of pharmaceutics since they are fast and non-destructive. This study assessed the ability of three vibrational spectroscopy combined with multivariate analysis to quantify a low-content undesired polymorph within a binary polymorphic mixture. Partial least squares (PLS) regression and support vector machine (SVM) regression were employed to build quantitative models. Fusidic acid, a steroidal antibiotic, was used as the model compound. It was found that PLS regression performed slightly better than SVM regression in all the three spectroscopic techniques. Root mean square errors of prediction (RMSEP) were ranging from 0.48% to 1.17% for diffuse reflectance FTIR spectroscopy and 1.60-1.93% for diffuse reflectance FT-NIR spectroscopy and 1.62-2.31% for Raman spectroscopy. The results indicate that diffuse reflectance FTIR spectroscopy offers significant advantages in providing accurate measurement of polymorphic content in the fusidic acid binary mixtures, while Raman spectroscopy is the least accurate technique for quantitative analysis of polymorphs. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of reflectance spectroscopies (FTIR-ATR & FT-NIR) coupled with multivariate methods for robust in vivo detection of begomovirus infection in papaya leaves

NASA Astrophysics Data System (ADS)

Haq, Quazi M. I.; Mabood, Fazal; Naureen, Zakira; Al-Harrasi, Ahmed; Gilani, Sayed A.; Hussain, Javid; Jabeen, Farah; Khan, Ajmal; Al-Sabari, Ruqaya S. M.; Al-khanbashi, Fatema H. S.; Al-Fahdi, Amira A. M.; Al-Zaabi, Ahoud K. A.; Al-Shuraiqi, Fatma A. M.; Al-Bahaisi, Iman M.

2018-06-01

Nucleic acid & serology based methods have revolutionized plant disease detection, however, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic infection, in addition, they need at least 1-2 days for sample harvesting, processing, and analysis. In this study, two reflectance spectroscopies i.e. Near Infrared reflectance spectroscopy (NIR) and Fourier-Transform-Infrared spectroscopy with Attenuated Total Reflection (FT-IR, ATR) coupled with multivariate exploratory methods like Principle Component Analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been deployed to detect begomovirus infection in papaya leaves. The application of those techniques demonstrates that they are very useful for robust in vivo detection of plant begomovirus infection. These methods are simple, sensitive, reproducible, precise, and do not require any lengthy samples preparation procedures.

Investigation of the composition of anabolic tablets using near infrared spectroscopy and Raman chemical imaging.

PubMed

Rebiere, Hervé; Ghyselinck, Céline; Lempereur, Laurent; Brenier, Charlotte

2016-01-01

The use of performance enhancing drugs is a widespread phenomenon in professional and leisure sports. A spectroscopic study was carried out on anabolic tablets labelled as 5 mg methandienone tablets provided by police departments. The analytical approach was based on a two-step methodology: a fast analysis of tablets using near infrared (NIR) spectroscopy to assess sample homogeneity based on their global composition, followed by Raman chemical imaging of one sample per NIR profile to obtain information on sample formulation. NIR spectroscopy assisted by a principal components analysis (PCA) enabled fast discrimination of different profiles based on the excipient formulation. Raman hyperspectral imaging and multivariate curve resolution - alternating least square (MCR-ALS) provided chemical images of the distribution of the active substance and excipients within tablets and facilitated identification of the active compounds. The combination of NIR spectroscopy and Raman chemical imaging highlighted dose-to-dose variations and succeeded in the discrimination of four different formulations out of eight similar samples of anabolic tablets. Some samples contained either methandienone or methyltestosterone whereas one sample did not contain an active substance. Other ingredients were sucrose, lactose, starch or talc. Both techniques were fast and non-destructive and therefore can be carried out as exploratory methods prior to destructive screening methods. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain

PubMed Central

Huppert, Theodore J.; Diamond, Solomon G.; Franceschini, Maria A.; Boas, David A.

2009-01-01

Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging tool for studying evoked hemodynamic changes within the brain. By this technique, changes in the optical absorption of light are recorded over time and are used to estimate the functionally evoked changes in cerebral oxyhemoglobin and deoxyhemoglobin concentrations that result from local cerebral vascular and oxygen metabolic effects during brain activity. Over the past three decades this technology has continued to grow, and today NIRS studies have found many niche applications in the fields of psychology, physiology, and cerebral pathology. The growing popularity of this technique is in part associated with a lower cost and increased portability of NIRS equipment when compared with other imaging modalities, such as functional magnetic resonance imaging and positron emission tomography. With this increasing number of applications, new techniques for the processing, analysis, and interpretation of NIRS data are continually being developed. We review some of the time-series and functional analysis techniques that are currently used in NIRS studies, we describe the practical implementation of various signal processing techniques for removing physiological, instrumental, and motion-artifact noise from optical data, and we discuss the unique aspects of NIRS analysis in comparison with other brain imaging modalities. These methods are described within the context of the MATLAB-based graphical user interface program, HomER, which we have developed and distributed to facilitate the processing of optical functional brain data. PMID:19340120

Determination of polarimetric parameters of honey by near-infrared transflectance spectroscopy.

PubMed

García-Alvarez, M; Ceresuela, S; Huidobro, J F; Hermida, M; Rodríguez-Otero, J L

2002-01-30

NIR transflectance spectroscopy was used to determine polarimetric parameters (direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides) and sucrose in honey. In total, 156 honey samples were collected during 1992 (45 samples), 1995 (56 samples), and 1996 (55 samples). Samples were analyzed by NIR spectroscopy and polarimetric methods. Calibration (118 samples) and validation (38 samples) sets were made up; honeys from the three years were included in both sets. Calibrations were performed by modified partial least-squares regression and scatter correction by standard normal variation and detrend methods. For direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides, good statistics (bias, SEV, and R(2)) were obtained for the validation set, and no statistically (p = 0.05) significant differences were found between instrumental and polarimetric methods for these parameters. Statistical data for sucrose were not as good as those of the other parameters. Therefore, NIR spectroscopy is not an effective method for quantitative analysis of sucrose in these honey samples. However, NIR spectroscopy may be an acceptable method for semiquantitative evaluation of sucrose for honeys, such as those in our study, containing up to 3% of sucrose. Further work is necessary to validate the uncertainty at higher levels.

Diagnostic potential of Raman spectroscopy in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Wong Kee Song, Louis-Michel; Molckovsky, Andrea; Wang, Kenneth K.; Burgart, Lawrence J.; Dolenko, Brion; Somorjai, Rajmund L.; Wilson, Brian C.

2005-04-01

Patients with Barrett's esophagus (BE) undergo periodic endoscopic surveillance with random biopsies in an effort to detect dysplastic or early cancerous lesions. Surveillance may be enhanced by near-infrared Raman spectroscopy (NIRS), which has the potential to identify endoscopically-occult dysplastic lesions within the Barrett's segment and allow for targeted biopsies. The aim of this study was to assess the diagnostic performance of NIRS for identifying dysplastic lesions in BE in vivo. Raman spectra (Pexc=70 mW; t=5 s) were collected from Barrett's mucosa at endoscopy using a custom-built NIRS system (λexc=785 nm) equipped with a filtered fiber-optic probe. Each probed site was biopsied for matching histological diagnosis as assessed by an expert pathologist. Diagnostic algorithms were developed using genetic algorithm-based feature selection and linear discriminant analysis, and classification was performed on all spectra with a bootstrap-based cross-validation scheme. The analysis comprised 192 samples (112 non-dysplastic, 54 low-grade dysplasia and 26 high-grade dysplasia/early adenocarcinoma) from 65 patients. Compared with histology, NIRS differentiated dysplastic from non-dysplastic Barrett's samples with 86% sensitivity, 88% specificity and 87% accuracy. NIRS identified 'high-risk' lesions (high-grade dysplasia/early adenocarcinoma) with 88% sensitivity, 89% specificity and 89% accuracy. In the present study, NIRS classified Barrett's epithelia with high and clinically-useful diagnostic accuracy.

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine

PubMed Central

Hsiung, Chang; Pederson, Christopher G.; Zou, Peng; Smith, Valton; von Gunten, Marc; O’Brien, Nada A.

2016-01-01

Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we demonstrated the use of portable miniature near-infrared (MicroNIR) spectrometers for NIR-based pharmaceutical RMID and solved two challenges in this area, model transferability and large-scale classification, with the aid of support vector machine (SVM) modeling. We used a set of 19 pharmaceutical compounds including various active pharmaceutical ingredients (APIs) and excipients and six MicroNIR spectrometers to test model transferability. For the test of large-scale classification, we used another set of 253 pharmaceutical compounds comprised of both chemically and physically different APIs and excipients. We compared SVM with conventional chemometric modeling techniques, including soft independent modeling of class analogy, partial least squares discriminant analysis, linear discriminant analysis, and quadratic discriminant analysis. Support vector machine modeling using a linear kernel, especially when combined with a hierarchical scheme, exhibited excellent performance in both model transferability and large-scale classification. Hence, ultra-compact, portable and robust MicroNIR spectrometers coupled with SVM modeling can make on-site and in situ pharmaceutical RMID for large-volume applications highly achievable. PMID:27029624

[Applications of near infrared reflectance spectroscopy in detecting chitin, ergosterol and mycotoxins].

PubMed

Yi, Yong-Yan; Li, De-Rong; Zhang, Yun-Wei; Yang, Fu-Yu

2009-07-01

The invasion extent and harmfulness of fungi can be determined by chitin, ergosterol and mycotoxins. It is important to monitor chitin, ergosterol and mycotoxins changes to prevent contamination of forage and feed products, and effectively control the sustainable development of the mildew. Predication of these chemical materials was often completed by laboratory analysis, which was time-consuming and cumbersome and could not reflect the results in time in the past. Near infrared reflectance spectroscopy (NIRS) is a rapid, convenient, highly efficient, nondestructive and low-cost analytical technique, which has been widely used in various fields such as food field and feed field for quantitative and qualitative analysis. It has a great potentiality of application in quality analysis. In this paper, the principle and the characteristic of NIRS and its applications in food, forage, feed and other agriculture products quality analysis were introduced. Its applications in fungal biomass (chitin, ergosterol) and mycotoxins were mainly reviewed. NIRS was used to quantify chitin, ergosterol and mycotoxins. Calibration equations and validation equations for these materials were developed. It is also expected that NIRS will play a more and more important role in the field of fungi with the establishment of calibration equation and improvement of model database.

Evaluation of PLS, LS-SVM, and LWR for quantitative spectroscopic analysis of soils

USDA-ARS?s Scientific Manuscript database

Soil testing requires the analysis of large numbers of samples in laboratory that are often time consuming and expensive. Mid-infrared spectroscopy (mid-IR) and near-infrared spectroscopy (NIRS) are fast, non-destructive, and inexpensive analytical methods that have been used for soil analysis, in l...

Determination of Protein Content by NIR Spectroscopy in Protein Powder Mix Products.

PubMed

Ingle, Prashant D; Christian, Roney; Purohit, Piyush; Zarraga, Veronica; Handley, Erica; Freel, Keith; Abdo, Saleem

2016-01-01

Protein is a principal component in commonly used dietary supplements and health food products. The analysis of these products, within the consumer package form, is of critical importance for the purpose of ensuring quality and supporting label claims. A rapid test method was developed using near-infrared (NIR) spectroscopy as a compliment to current protein determination by the Dumas combustion method. The NIR method was found to be a rapid, low-cost, and green (no use of chemicals and reagents) complimentary technique. The protein powder samples analyzed in this study were in the range of 22-90% protein. The samples were prepared as mixtures of soy protein, whey protein, and silicon dioxide ingredients, which are common in commercially sold protein powder drink-mix products in the market. A NIR regression model was developed with 17 samples within the constituent range and was validated with 20 independent samples of known protein levels (85-88%). The results show that the NIR method is capable of predicting the protein content with a bias of ±2% and a maximum bias of 3% between NIR and the external Dumas method.

7 CFR 801.7 - Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Reference methods and tolerances for near-infrared spectroscopy (NIRS) analyzers. 801.7 Section 801.7 Agriculture Regulations of the Department of Agriculture... methods and tolerances for near-infrared spectroscopy (NIRS) analyzers. (a) Reference methods. (1) The...

Comparison of motion correction techniques applied to functional near-infrared spectroscopy data from children

NASA Astrophysics Data System (ADS)

Hu, Xiao-Su; Arredondo, Maria M.; Gomba, Megan; Confer, Nicole; DaSilva, Alexandre F.; Johnson, Timothy D.; Shalinsky, Mark; Kovelman, Ioulia

2015-12-01

Motion artifacts are the most significant sources of noise in the context of pediatric brain imaging designs and data analyses, especially in applications of functional near-infrared spectroscopy (fNIRS), in which it can completely affect the quality of the data acquired. Different methods have been developed to correct motion artifacts in fNIRS data, but the relative effectiveness of these methods for data from child and infant subjects (which is often found to be significantly noisier than adult data) remains largely unexplored. The issue is further complicated by the heterogeneity of fNIRS data artifacts. We compared the efficacy of the six most prevalent motion artifact correction techniques with fNIRS data acquired from children participating in a language acquisition task, including wavelet, spline interpolation, principal component analysis, moving average (MA), correlation-based signal improvement, and combination of wavelet and MA. The evaluation of five predefined metrics suggests that the MA and wavelet methods yield the best outcomes. These findings elucidate the varied nature of fNIRS data artifacts and the efficacy of artifact correction methods with pediatric populations, as well as help inform both the theory and practice of optical brain imaging analysis.

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory.

PubMed

Keshmiri, Soheil; Sumioka, Hidenubo; Yamazaki, Ryuji; Ishiguro, Hiroshi

2018-01-01

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli.

Reflectance-mode interferometric near-infrared spectroscopy quantifies brain absorption, scattering, and blood flow index in vivo

PubMed Central

Borycki, Dawid; Kholiqov, Oybek; Srinivasan, Vivek J.

2017-01-01

Interferometric near-infrared spectroscopy (iNIRS) is a new technique that measures time-of-flight- (TOF-) resolved autocorrelations in turbid media, enabling simultaneous estimation of optical and dynamical properties. Here, we demonstrate reflectance-mode iNIRS for noninvasive monitoring of a mouse brain in vivo. A method for more precise quantification with less static interference from superficial layers, based on separating static and dynamic components of the optical field autocorrelation, is presented. Absolute values of absorption, reduced scattering, and blood flow index (BFI) are measured, and changes in BFI and absorption are monitored during a hypercapnic challenge. Absorption changes from TOF-resolved iNIRS agree with absorption changes from continuous wave NIRS analysis, based on TOF-integrated light intensity changes, an effective path length, and the modified Beer–Lambert Law. Thus, iNIRS is a promising approach for quantitative and non-invasive monitoring of perfusion and optical properties in vivo. PMID:28146535

Detection of Lipitor counterfeits: a comparison of NIR and Raman spectroscopy in combination with chemometrics.

PubMed

de Peinder, P; Vredenbregt, M J; Visser, T; de Kaste, D

2008-08-05

Research has been carried on the feasibility of near infrared (NIR) and Raman spectroscopy as rapid screening methods to discriminate between genuine and counterfeits of the cholesterol-lowering medicine Lipitor. Classification, based on partial least squares discriminant analysis (PLS-DA) models, appears to be successful for both spectroscopic techniques, irrespective of whether atorvastatine or lovastatine has been used as the active pharmaceutical ingredient (API). The discriminative power of the NIR model, in particular, largely relies on the spectral differences of the tablet matrix. This is due to the relative large sample volume that is probed with NIR and the strong spectroscopic activity of the excipients. PLS-DA models based on NIR or Raman spectra can also be applied to distinguish between atorvastatine and lovastatine as the API used in the counterfeits tested in this study. A disadvantage of Raman microscopy for this type of analysis is that it is primarily a surface technique. As a consequence spectra of the coating and the tablet core might differ. Besides, spectra may change with the position of the laser in case the sample is inhomogeneous. However, the robustness of the PLS-DA models turned out to be sufficiently large to allow a reliable discrimination. Principal component analysis (PCA) of the spectra revealed that the conditions, at which tablets have been stored, affect the NIR data. This effect is attributed to the adsorption of water from the atmosphere after unpacking from the blister. It implies that storage conditions should be taken into account when the NIR technique is used for discriminating purposes. However, in this study both models based on NIR spectra and Raman data enabled reliable discrimination between genuine and counterfeited Lipitor tablets, regardless of their storage conditions.

Resting-state functional brain connectivity: lessons from functional near-infrared spectroscopy.

PubMed

Niu, Haijing; He, Yong

2014-04-01

Resting-state functional near-infrared spectroscopy (R-fNIRS) is an active area of interest and is currently attracting considerable attention as a new imaging tool for the study of resting-state brain function. Using variations in hemodynamic concentration signals, R-fNIRS measures the brain's low-frequency spontaneous neural activity, combining the advantages of portability, low-cost, high temporal sampling rate and less physical burden to participants. The temporal synchronization of spontaneous neuronal activity in anatomically separated regions is referred to as resting-state functional connectivity (RSFC). In the past several years, an increasing body of R-fNIRS RSFC studies has led to many important findings about functional integration among local or whole-brain regions by measuring inter-regional temporal synchronization. Here, we summarize recent advances made in the R-fNIRS RSFC methodologies, from the detection of RSFC (e.g., seed-based correlation analysis, independent component analysis, whole-brain correlation analysis, and graph-theoretical topological analysis), to the assessment of RSFC performance (e.g., reliability, repeatability, and validity), to the application of RSFC in studying normal development and brain disorders. The literature reviewed here suggests that RSFC analyses based on R-fNIRS data are valid and reliable for the study of brain function in healthy and diseased populations, thus providing a promising imaging tool for cognitive science and clinics.

Novel near-infrared sampling apparatus for single kernel analysis of oil content in maize.

PubMed

Janni, James; Weinstock, B André; Hagen, Lisa; Wright, Steve

2008-04-01

A method of rapid, nondestructive chemical and physical analysis of individual maize (Zea mays L.) kernels is needed for the development of high value food, feed, and fuel traits. Near-infrared (NIR) spectroscopy offers a robust nondestructive method of trait determination. However, traditional NIR bulk sampling techniques cannot be applied successfully to individual kernels. Obtaining optimized single kernel NIR spectra for applied chemometric predictive analysis requires a novel sampling technique that can account for the heterogeneous forms, morphologies, and opacities exhibited in individual maize kernels. In this study such a novel technique is described and compared to less effective means of single kernel NIR analysis. Results of the application of a partial least squares (PLS) derived model for predictive determination of percent oil content per individual kernel are shown.

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

PubMed Central

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Oh, Kyoungmin; Yoo, Hyeonchae; Ham, Hyeonheui; Kim, Moon S.

2017-01-01

The purpose of this study is to use near-infrared reflectance (NIR) spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA) was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method. PMID:28974012

[A review on studies and applications of near infrared spectroscopy technique(NIRS) in detecting quality of hay].

PubMed

Ding, Wu-Rong; Gan, You-Min; Guo, Xu-Sheng; Yang, Fu-Yu

2009-02-01

The quality of hay can directly affect the price of hay and also livestock productivity. Many kinds of methods have been developed for detecting the quality of hay and the method of near infrared spectroscopy (NIRS) has been widely used with consideration of its fast, effective and nondestructive characteristics during detecting process. In the present paper, the feasibility and effectiveness of application of NIRS to detecting hay quality were expounded. Meanwhile, the advance in the study of using NIRS to detect chemical compositions, extent of incursion by epiphyte, amount of toxicant excreted by endogenetic epiphyte and some minim components that can not be detected by using chemical methods were also introduced detailedly. Based on the review of the progresses in using NIRS to detect the quality of hay, it can be concluded that using NIRS to detect hay quality can avoid the disadvantages of time wasting, complication and high cost when using traditional chemical method. And for better utilization of NIRS in practice, some more studies still need to be implemented to further perfect and improve the utilization of NIRS for detecting forage quality, and more accurate modes and systematic analysis software need to be established in times to come.

[Real-time detection of quality of Chinese materia medica: strategy of NIR model evaluation].

PubMed

Wu, Zhi-sheng; Shi, Xin-yuan; Xu, Bing; Dai, Xing-xing; Qiao, Yan-jiang

2015-07-01

The definition of critical quality attributes of Chinese materia medica ( CMM) was put forward based on the top-level design concept. Nowadays, coupled with the development of rapid analytical science, rapid assessment of critical quality attributes of CMM was firstly carried out, which was the secondary discipline branch of CMM. Taking near infrared (NIR) spectroscopy as an example, which is a rapid analytical technology in pharmaceutical process over the past decade, systematic review is the chemometric parameters in NIR model evaluation. According to the characteristics of complexity of CMM and trace components analysis, a multi-source information fusion strategy of NIR model was developed for assessment of critical quality attributes of CMM. The strategy has provided guideline for NIR reliable analysis in critical quality attributes of CMM.

Pattern recognition of visible and near-infrared spectroscopy from bayberry juice by use of partial least squares and a backpropagation neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cen Haiyan; Bao Yidan; He Yong

2006-10-10

Visible and near-infrared reflectance (visible-NIR) spectroscopy is applied to discriminate different varieties of bayberry juices. The discrimination of visible-NIR spectra from samples is a matter of pattern recognition. By partial least squares (PLS), the spectrum is reduced to certain factors, which are then taken as the input of the backpropagation neural network (BPNN). Through training and prediction, three different varieties of bayberry juice are classified based on the output of the BPNN. In addition, a mathematical model is built and the algorithm is optimized. With proper parameters in the training set,100% accuracy is obtained by the BPNN. Thus it ismore » concluded that the PLS analysis combined with the BPNN is an alternative for pattern recognition based on visible and NIR spectroscopy.« less

Detection of resting state functional connectivity using partial correlation analysis: A study using multi-distance and whole-head probe near-infrared spectroscopy.

PubMed

Sakakibara, Eisuke; Homae, Fumitaka; Kawasaki, Shingo; Nishimura, Yukika; Takizawa, Ryu; Koike, Shinsuke; Kinoshita, Akihide; Sakurada, Hanako; Yamagishi, Mika; Nishimura, Fumichika; Yoshikawa, Akane; Inai, Aya; Nishioka, Masaki; Eriguchi, Yosuke; Matsuoka, Jun; Satomura, Yoshihiro; Okada, Naohiro; Kakiuchi, Chihiro; Araki, Tsuyoshi; Kan, Chiemi; Umeda, Maki; Shimazu, Akihito; Uga, Minako; Dan, Ippeita; Hashimoto, Hideki; Kawakami, Norito; Kasai, Kiyoto

2016-11-15

Multichannel near-infrared spectroscopy (NIRS) is a functional neuroimaging modality that enables easy-to-use and noninvasive measurement of changes in blood oxygenation levels. We developed a clinically-applicable method for estimating resting state functional connectivity (RSFC) with NIRS using a partial correlation analysis to reduce the influence of extraneural components. Using a multi-distance probe arrangement NIRS, we measured resting state brain activity for 8min in 17 healthy participants. Independent component analysis was used to extract shallow and deep signals from the original NIRS data. Pearson's correlation calculated from original signals was significantly higher than that calculated from deep signals, while partial correlation calculated from original signals was comparable to that calculated from deep (cerebral-tissue) signals alone. To further test the validity of our method, we also measured 8min of resting state brain activity using a whole-head NIRS arrangement consisting of 17 cortical regions in 80 healthy participants. Significant RSFC between neighboring, interhemispheric homologous, and some distant ipsilateral brain region pairs was revealed. Additionally, females exhibited higher RSFC between interhemispheric occipital region-pairs, in addition to higher connectivity between some ipsilateral pairs in the left hemisphere, when compared to males. The combined results of the two component experiments indicate that partial correlation analysis is effective in reducing the influence of extracerebral signals, and that NIRS is able to detect well-described resting state networks and sex-related differences in RSFC. Copyright © 2016 Elsevier Inc. All rights reserved.

Feasibility of Functional Near-Infrared Spectroscopy (fNIRS) to Investigate the Mirror Neuron System: An Experimental Study in a Real-Life Situation

PubMed Central

Sun, Pei-Pei; Tan, Fu-Lun; Zhang, Zong; Jiang, Yi-Han; Zhao, Yang; Zhu, Chao-Zhe

2018-01-01

The mirror neuron system (MNS), mainly including the premotor cortex (PMC), inferior frontal gyrus (IFG), superior parietal lobule (SPL), and rostral inferior parietal lobule (IPL), has attracted extensive attention as a possible neural mechanism of social interaction. Owing to high ecological validity, functional near-infrared spectroscopy (fNIRS) has become an ideal approach for exploring the MNS. Unfortunately, for the feasibility of fNIRS to detect the MNS, none of the four dominant regions were found in previous studies, implying a very limited capacity of fNIRS to investigate the MNS. Here, we adopted an experimental paradigm in a real-life situation to evaluate whether the MNS activity, including four dominant regions, can be detected by using fNIRS. Specifically, 30 right-handed subjects were asked to complete a table-setting task that included action execution and action observation. A double density probe configuration covered the four regions of the MNS in the left hemisphere. We used a traditional channel-based group analysis and also a ROI-based group analysis to find which regions are activated during both action execution and action observation. The results showed that the IFG, adjacent PMC, SPL, and IPL were involved in both conditions, indicating the feasibility of fNIRS to detect the MNS. Our findings provide a foundation for future research to explore the functional role of the MNS in social interaction and various disorders using fNIRS. PMID:29556185

Cartilage analysis by reflection spectroscopy

NASA Astrophysics Data System (ADS)

Laun, T.; Muenzer, M.; Wenzel, U.; Princz, S.; Hessling, M.

2015-07-01

A cartilage bioreactor with analytical functions for cartilage quality monitoring is being developed. For determining cartilage composition, reflection spectroscopy in the visible (VIS) and near infrared (NIR) spectral region is evaluated. Main goal is the determination of the most abundant cartilage compounds water, collagen I and collagen II. Therefore VIS and NIR reflection spectra of different cartilage samples of cow, pig and lamb are recorded. Due to missing analytical instrumentation for identifying the cartilage composition of these samples, typical literature concentration values are used for the development of chemometric models. In spite of these limitations the chemometric models provide good cross correlation results for the prediction of collagen I and II and water concentration based on the visible and the NIR reflection spectra.

Prediction of essential oil content of oregano by hand-held and Fourier transform NIR spectroscopy.

PubMed

Camps, Cédric; Gérard, Marianne; Quennoz, Mélanie; Brabant, Cécile; Oberson, Carine; Simonnet, Xavier

2014-05-01

In the framework of a breeding programme, the analysis of hundreds of oregano samples to determine their essential oil content (EOC) is time-consuming and expensive in terms of labour. Therefore developing a new method that is rapid, accurate and less expensive to use would be an asset to breeders. The aim of the present study was to develop a method based on near-inrared (NIR) spectroscopy to determine the EOC of oregano dried powder. Two spectroscopic approaches were compared, the first using a hand-held NIR device and the second a Fourier transform (FT) NIR spectrometer. Hand-held NIR (1000-1800 nm) measurements and partial least squares regression allowed the determination of EOC with R² and SEP values of 0.58 and 0.81 mL per 100 g dry matter (DM) respectively. Measurements with FT-NIR (1000-2500 nm) allowed the determination of EOC with R² and SEP values of 0.91 and 0.68 mL per 100 g DM respectively. RPD, RER and RPIQ values for the model implemented with FT-NIR data were satisfactory for screening application, while those obtained with hand-held NIR data were below the level required to consider the model as enough accurate for screening application. The FT-NIR approach allowed the development of an accurate model for EOC prediction. Although the hand-held NIR approach is promising, it needs additional development before it can be used in practice. © 2013 Society of Chemical Industry.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy.

PubMed

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. The results showed that 86.0% ([Formula: see text]) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Characterization and correction of the false-discovery rates in resting state connectivity using functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Santosa, Hendrik; Aarabi, Ardalan; Perlman, Susan B.; Huppert, Theodore J.

2017-05-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of red to near-infrared light to measure changes in cerebral blood oxygenation. Spontaneous (resting state) functional connectivity (sFC) has become a critical tool for cognitive neuroscience for understanding task-independent neural networks, revealing pertinent details differentiating healthy from disordered brain function, and discovering fluctuations in the synchronization of interacting individuals during hyperscanning paradigms. Two of the main challenges to sFC-NIRS analysis are (i) the slow temporal structure of both systemic physiology and the response of blood vessels, which introduces false spurious correlations, and (ii) motion-related artifacts that result from movement of the fNIRS sensors on the participants' head and can introduce non-normal and heavy-tailed noise structures. In this work, we systematically examine the false-discovery rates of several time- and frequency-domain metrics of functional connectivity for characterizing sFC-NIRS. Specifically, we detail the modifications to the statistical models of these methods needed to avoid high levels of false-discovery related to these two sources of noise in fNIRS. We compare these analysis procedures using both simulated and experimental resting-state fNIRS data. Our proposed robust correlation method has better performance in terms of being more reliable to the noise outliers due to the motion artifacts.

Facial Vibrotactile Stimulation Activates the Parasympathetic Nervous System: Study of Salivary Secretion, Heart Rate, Pupillary Reflex, and Functional Near-Infrared Spectroscopy Activity

PubMed Central

Hiraba, Hisao; Inoue, Motoharu; Gora, Kanako; Sato, Takako; Nishimura, Satoshi; Yamaoka, Masaru; Kumakura, Ayano; Ono, Shinya; Wakasa, Hirotugu; Nakayama, Enri; Abe, Kimiko; Ueda, Koichiro

2014-01-01

We previously found that the greatest salivation response in healthy human subjects is produced by facial vibrotactile stimulation of 89 Hz frequency with 1.9 μm amplitude (89 Hz-S), as reported by Hiraba et al. (2012, 20011, and 2008). We assessed relationships between the blood flow to brain via functional near-infrared spectroscopy (fNIRS) in the frontal cortex and autonomic parameters. We used the heart rate (HRV: heart rate variability analysis in RR intervals), pupil reflex, and salivation as parameters, but the interrelation between each parameter and fNIRS measures remains unknown. We were to investigate the relationship in response to established paradigms using simultaneously each parameter-fNIRS recording in healthy human subjects. Analysis of fNIRS was examined by a comparison of various values between before and after various stimuli (89 Hz-S, 114 Hz-S, listen to classic music, and “Ahh” vocalization). We confirmed that vibrotactile stimulation (89 Hz) of the parotid glands led to the greatest salivation, greatest increase in heart rate variability, and the most constricted pupils. Furthermore, there were almost no detectable differences between fNIRS during 89 Hz-S and fNIRS during listening to classical music of fans. Thus, vibrotactile stimulation of 89 Hz seems to evoke parasympathetic activity. PMID:24511550

Monitoring ibuprofen-nicotinamide cocrystal formation during solvent free continuous cocrystallization (SFCC) using near infrared spectroscopy as a PAT tool.

PubMed

Kelly, A L; Gough, T; Dhumal, R S; Halsey, S A; Paradkar, A

2012-04-15

The purpose of this work was to explore NIR spectroscopy as a PAT tool to monitor the formation of ibuprofen and nicotinamide cocrystals during extrusion based solvent free continuous cocrystallization (SFCC). Drug and co-former were gravimetrically fed into a heated co-rotating twin screw extruder to form cocrystals. Real-time process monitoring was performed using a high temperature NIR probe in the extruder die to assess cocrystal content and subsequently compared to off-line powder X-ray diffraction measurements. The effect of processing variables, such as temperature and mixing intensity, on the extent of cocrystal formation was investigated. NIR spectroscopy was sensitive to cocrystal formation with the appearance of new peaks and peak shifts, particularly in the 4800-5200 cm(-1) wave-number region. PXRD confirmed an increased conversion of the mixture into cocrystal with increase in barrel temperature and screw mixing intensity. A decrease in screw rotation speed also provided improved cocrystal yield due to the material experiencing longer residence times within the process. A partial least squares analysis in this region of NIR spectrum correlated well with PXRD data, providing a best fit with cocrystal conversion when a limited range of process conditions were considered, for example a single set temperature. The study suggests that NIR spectroscopy could be used to monitor cocrystal purity on an industrial scale using this continuous, solvent-free process. Copyright © 2011 Elsevier B.V. All rights reserved.

Correlation between near infrared spectroscopy and electrical techniques in measuring skin moisture content

NASA Astrophysics Data System (ADS)

Mohamad, M.; Sabbri, A. R. M.; Mat Jafri, M. Z.; Omar, A. F.

2014-11-01

Near infrared (NIR) spectroscopy technique serves as an important tool for the measurement of moisture content of skin owing to the advantages it has over the other techniques. The purpose of the study is to develop a correlation between NIR spectrometer with electrical conventional techniques for skin moisture measurement. A non-invasive measurement of moisture content of skin was performed on different part of human face and hand under control environment (temperature 21 ± 1 °C, relative humidity 45 ± 5 %). Ten healthy volunteers age between 21-25 (male and female) participated in this study. The moisture content of skin was measured using DermaLab® USB Moisture Module, Scalar Moisture Checker and NIR spectroscopy (NIRQuest). Higher correlation was observed between NIRQuest and Dermalab moisture probe with a coefficient of determination (R2) above 70 % for all the subjects. However, the value of R2 between NIRQuest and Moisture Checker was observed to be lower with the R2 values ranges from 51.6 to 94.4 %. The correlation of NIR spectroscopy technique successfully developed for measuring moisture content of the skin. The analysis of this correlation can help to establish novel instruments based on an optical system in clinical used especially in the dermatology field.

[Identification of varieties of textile fibers by using Vis/NIR infrared spectroscopy technique].

PubMed

Wu, Gui-Fang; He, Yong

2010-02-01

The aim of the present paper was to provide new insight into Vis/NIR spectroscopic analysis of textile fibers. In order to achieve rapid identification of the varieties of fibers, the authors selected 5 kinds of fibers of cotton, flax, wool, silk and tencel to do a study with Vis/NIR spectroscopy. Firstly, the spectra of each kind of fiber were scanned by spectrometer, and principal component analysis (PCA) method was used to analyze the characteristics of the pattern of Vis/NIR spectra. Principal component scores scatter plot (PC1 x PC2 x PC3) of fiber indicated the classification effect of five varieties of fibers. The former 6 principal components (PCs) were selected according to the quantity and size of PCs. The PCA classification model was optimized by using the least-squares support vector machines (LS-SVM) method. The authors used the 6 PCs extracted by PCA as the inputs of LS-SVM, and PCA-LS-SVM model was built to achieve varieties validation as well as mathematical model building and optimization analysis. Two hundred samples (40 samples for each variety of fibers) of five varieties of fibers were used for calibration of PCA-LS-SVM model, and the other 50 samples (10 samples for each variety of fibers) were used for validation. The result of validation showed that Vis/NIR spectroscopy technique based on PCA-LS-SVM had a powerful classification capability. It provides a new method for identifying varieties of fibers rapidly and real time, so it has important significance for protecting the rights of consumers, ensuring the quality of textiles, and implementing rationalization production and transaction of textile materials and its production.

Identification of Serine Conformers by Matrix-Isolation IR Spectroscopy Aided by Near-Infrared Laser Induced Conformational Change, 2D Correlation Analysis, and Quantum Mechanical Anharmonic Computations

PubMed Central

Najbauer, Eszter E.; Bazsó, Gábor; Apóstolo, Rui; Fausto, Rui; Biczysko, Malgorzata; Barone, Vincenzo; Tarczay, György

2018-01-01

The conformers of α-serine were investigated by matrix-isolation IR spectroscopy combined with NIR laser irradiation. This method, aided by 2D correlation analysis, enabled unambiguously grouping the spectral lines to individual conformers. On the basis of comparison of at least nine experimentally observed vibrational transitions of each conformer with empirically scaled (SQM) and anharmonic (GVPT2) computed IR spectra, 6 conformers were identified. In addition, the presence of at least one more conformer in Ar matrix was proved, and a short-lived conformer with a half-live of (3.7±0.5)·103 s in N2 matrix was generated by NIR irradiation. The analysis of the NIR laser induced conversions revealed that the excitation of the stretching overtone of both the side-chain and the carboxylic OH groups can effectively promote conformational changes, but remarkably different paths were observed for the two kinds of excitations. PMID:26201050

The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments.

PubMed

Ferrari, Marco; Muthalib, Makii; Quaresima, Valentina

2011-11-28

This article provides a snapshot of muscle near-infrared spectroscopy (NIRS) at the end of 2010 summarizing the recent literature, offering the present status and perspectives of the NIRS instrumentation and methods, describing the main NIRS studies on skeletal muscle physiology, posing open questions and outlining future directions. So far, different NIRS techniques (e.g. continuous-wave (CW) and spatially, time- and frequency-resolved spectroscopy) have been used for measuring muscle oxygenation during exercise. In the last four years, approximately 160 muscle NIRS articles have been published on different physiological aspects (primarily muscle oxygenation and haemodynamics) of several upper- and lower-limb muscle groups investigated by using mainly two-channel CW and spatially resolved spectroscopy commercial instruments. Unfortunately, in only 15 of these studies were the advantages of using multi-channel instruments exploited. There are still several open questions in the application of NIRS in muscle studies: (i) whether NIRS can be used in subjects with a large fat layer; (ii) the contribution of myoglobin desaturation to the NIRS signal during exercise; (iii) the effect of scattering changes during exercise; and (iv) the effect of changes in skin perfusion, particularly during prolonged exercise. Recommendations for instrumentation advancements and future muscle NIRS studies are provided.

Effective Identification of Low-Gliadin Wheat Lines by Near Infrared Spectroscopy (NIRS): Implications for the Development and Analysis of Foodstuffs Suitable for Celiac Patients.

PubMed

García-Molina, María Dolores; García-Olmo, Juan; Barro, Francisco

2016-01-01

The aim of this work was to assess the ability of Near Infrared Spectroscopy (NIRS) to distinguish wheat lines with low gliadin content, obtained by RNA interference (RNAi), from non-transgenic wheat lines. The discriminant analysis was performed using both whole grain and flour. The transgenic sample set included 409 samples for whole grain sorting and 414 samples for flour experiments, while the non-transgenic set consisted of 126 and 156 samples for whole grain and flour, respectively. Samples were scanned using a Foss-NIR Systems 6500 System II instrument. Discrimination models were developed using the entire spectral range (400-2500 nm) and ranges of 400-780 nm, 800-1098 nm and 1100-2500 nm, followed by analysis of means of partial least square (PLS). Two external validations were made, using samples from the years 2013 and 2014 and a minimum of 99% of the flour samples and 96% of the whole grain samples were classified correctly. The results demonstrate the ability of NIRS to successfully discriminate between wheat samples with low-gliadin content and wild types. These findings are important for the development and analysis of foodstuff for celiac disease (CD) patients to achieve better dietary composition and a reduction in disease incidence.

A review on the applications of portable near-infrared spectrometers in the agro-food industry.

PubMed

dos Santos, Cláudia A Teixeira; Lopo, Miguel; Páscoa, Ricardo N M J; Lopes, João A

2013-11-01

Industry has created the need for a cost-effective and nondestructive quality-control analysis system. This requirement has increased interest in near-infrared (NIR) spectroscopy, leading to the development and marketing of handheld devices that enable new applications that can be implemented in situ. Portable NIR spectrometers are powerful instruments offering several advantages for nondestructive, online, or in situ analysis: small size, low cost, robustness, simplicity of analysis, sample user interface, portability, and ergonomic design. Several studies of on-site NIR applications are presented: characterization of internal and external parameters of fruits and vegetables; conservation state and fat content of meat and fish; distinguishing among and quality evaluation of beverages and dairy products; protein content of cereals; evaluation of grape ripeness in vineyards; and soil analysis. Chemometrics is an essential part of NIR spectroscopy manipulation because wavelength-dependent scattering effects, instrumental noise, ambient effects, and other sources of variability may complicate the spectra. As a consequence, it is difficult to assign specific absorption bands to specific functional groups. To achieve useful and meaningful results, multivariate statistical techniques (essentially involving regression techniques coupled with spectral preprocessing) are therefore required to extract the information hidden in the spectra. This work reviews the evolution of the use of portable near-infrared spectrometers in the agro-food industry.

Visible and near-infrared spectroscopic analysis of raw milk for cow health monitoring: reflectance or transmittance?

PubMed

Aernouts, B; Polshin, E; Lammertyn, J; Saeys, W

2011-11-01

The composition of produced milk has great value for the dairy farmer. It determines the economic value of the milk and provides valuable information about the metabolism of the corresponding cow. Therefore, online measurement of milk components during milking 2 or more times per day would provide knowledge about the current health and nutritional status of each cow individually. This information provides a solid basis for optimizing cow management. The potential of visible and near-infrared (Vis/NIR) spectroscopy for predicting the fat, crude protein, lactose, and urea content of raw milk online during milking was, therefore, investigated in this study. Two measurement modes (reflectance and transmittance) and different wavelength ranges for Vis/NIR spectroscopy were evaluated and their ability to measure the milk composition online was compared. The Vis/NIR reflectance measurements allowed for very accurate monitoring of the fat and crude protein content in raw milk (R(2)>0.95), but resulted in poor lactose predictions (R(2)<0.75). In contrast, Vis/NIR transmittance spectra of the milk samples gave accurate fat and crude protein predictions (R(2)>0.90) and useful lactose predictions (R(2)=0.88). Neither Vis/NIR reflectance nor transmittance spectroscopy lead to an acceptable prediction of the milk urea content. Transmittance spectroscopy can thus be used to predict the 3 major milk components, but with lower accuracy for fat and crude protein than the reflectance mode. Moreover, the small sample thickness (1mm) required for NIR transmittance measurement considerably complicates its online use. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy.

PubMed

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R; Tulchin-Francis, Kirsten; Shierk, Angela; Roberts, Heather; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2014-10-01

Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy

PubMed Central

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R.; Tulchin-Francis, Kirsten; Shierk, Angela; Roberts, Heather; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J.; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2014-01-01

Abstract. Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images. PMID:26157980

Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

PubMed

Huppert, Theodore J

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.

Comparative Variable Temperature Studies of Polyamide II with a Benchtop Fourier Transform and a Miniature Handheld Near-Infrared Spectrometer Using 2D-COS and PCMW-2D Analysis.

PubMed

Unger, Miriam; Pfeifer, Frank; Siesler, Heinz W

2016-07-01

The main objective of this communication is to compare the performance of a miniaturized handheld near-infrared (NIR) spectrometer with a benchtop Fourier transform near-infrared (FT-NIR) spectrometer. Generally, NIR spectroscopy is an extremely powerful analytical tool to study hydrogen-bonding changes of amide functionalities in solid and liquid materials and therefore variable temperature NIR measurements of polyamide II (PAII) have been selected as a case study. The information content of the measurement data has been further enhanced by exploiting the potential of two-dimensional correlation spectroscopy (2D-COS) and the perturbation correlation moving window two-dimensional (PCMW2D) evaluation technique. The data provide valuable insights not only into the changes of the hydrogen-bonding structure and the recrystallization of the hydrocarbon segments of the investigated PAII but also in their sequential order. Furthermore, it has been demonstrated that the 2D-COS and PCMW2D results derived from the spectra measured with the miniaturized NIR instrument are equivalent to the information extracted from the data obtained with the high-performance FT-NIR instrument. © The Author(s) 2016.

A comparative study of the use of powder X-ray diffraction, Raman and near infrared spectroscopy for quantification of binary polymorphic mixtures of piracetam.

PubMed

Croker, Denise M; Hennigan, Michelle C; Maher, Anthony; Hu, Yun; Ryder, Alan G; Hodnett, Benjamin K

2012-04-07

Diffraction and spectroscopic methods were evaluated for quantitative analysis of binary powder mixtures of FII(6.403) and FIII(6.525) piracetam. The two polymorphs of piracetam could be distinguished using powder X-ray diffraction (PXRD), Raman and near-infrared (NIR) spectroscopy. The results demonstrated that Raman and NIR spectroscopy are most suitable for quantitative analysis of this polymorphic mixture. When the spectra are treated with the combination of multiplicative scatter correction (MSC) and second derivative data pretreatments, the partial least squared (PLS) regression model gave a root mean square error of calibration (RMSEC) of 0.94 and 0.99%, respectively. FIII(6.525) demonstrated some preferred orientation in PXRD analysis, making PXRD the least preferred method of quantification. Copyright © 2012 Elsevier B.V. All rights reserved.

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory

PubMed Central

Keshmiri, Soheil; Sumioka, Hidenubo; Yamazaki, Ryuji; Ishiguro, Hiroshi

2018-01-01

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli. PMID:29922144

Age determination of bottled Chinese rice wine by VIS-NIR spectroscopy

NASA Astrophysics Data System (ADS)

Yu, Haiyan; Lin, Tao; Ying, Yibin; Pan, Xingxiang

2006-10-01

The feasibility of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining wine age (1, 2, 3, 4, and 5 years) of Chinese rice wine was investigated. Samples of Chinese rice wine were analyzed in 600 mL square brown glass bottles with side length of approximately 64 mm at room temperature. VIS-NIR spectra of 100 bottled Chinese rice wine samples were collected in transmission mode in the wavelength range of 350-1200 nm by a fiber spectrometer system. Discriminant models were developed based on discriminant analysis (DA) together with raw, first and second derivative spectra. The concentration of alcoholic degree, total acid, and °Brix was determined to validate the NIR results. The calibration result for raw spectra was better than that for first and second derivative spectra. The percentage of samples correctly classified for raw spectra was 98%. For 1-, 2-, and 3-year-old sample groups, the sample were all correctly classified, and for 4- and 5-year-old sample groups, the percentage of samples correctly classified was 92.9%, respectively. In validation analysis, the percentage of samples correctly classified was 100%. The results demonstrated that VIS-NIR spectroscopic technique could be used as a non-invasive, rapid and reliable method for predicting wine age of bottled Chinese rice wine.

Near Infrared Spectroscopy for On-line Monitoring of Alkali- Free Cloth/Phenolic Resin Prepreg During Manufacture

PubMed Central

Jiang, Bo; Huang, Yu Dong

2007-01-01

A NIR method was developed for the on-line monitoring of alkali-free cloth/phenolic resin prepreg during its manufacturing process. First, the sizing content of the alkali-free cloth was analyzed, and then the resin, soluble resin and volatiles content of the prepreg was analyzed simultaneously using the FT-NIR spectrometer. Partial least square (PLS) regression was used to develop the calibration models, which for the sizing content was preprocessed by 1stDER +MSC, for the volatile content by 1stDER +VN, for the soluble resin content by 1stDER +MSC and for the resin content by the VN spectral data preprocessing method. RMSEP of the prediction model for the sizing content was 0.732 %, for the resin content it was 0.605, for the soluble resin content it was 0.101 and for volatiles content it was 0.127. The results of the paired t-test revealed that there was no significant difference between the NIR method and the standard method. The NIR spectroscopy method could be used to predict the resin, soluble resin and the volatiles content of the prepreg simultaneously, as well as sizing content of alkali-free cloth. The processing parameters of the prepreg during manufacture could be adjusted quickly with the help of the NIR analysis results. The results indicated that the NIR spectroscopy method was sufficiently accurate and effective for the on-line monitoring of alkali-free cloth/phenolic resin prepreg.

Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS).

PubMed

Luo, Yu; Li, Wen-Long; Huang, Wen-Hua; Liu, Xue-Hua; Song, Yan-Gang; Qu, Hai-Bin

2017-05-01

A near infrared spectroscopy (NIRS) approach was established for quality control of the alcohol precipitation liquid in the manufacture of Codonopsis Radix. By applying NIRS with multivariate analysis, it was possible to build variation into the calibration sample set, and the Plackett-Burman design, Box-Behnken design, and a concentrating-diluting method were used to obtain the sample set covered with sufficient fluctuation of process parameters and extended concentration information. NIR data were calibrated to predict the four quality indicators using partial least squares regression (PLSR). In the four calibration models, the root mean squares errors of prediction (RMSEPs) were 1.22 μg/ml, 10.5 μg/ml, 1.43 μg/ml, and 0.433% for lobetyolin, total flavonoids, pigments, and total solid contents, respectively. The results indicated that multi-components quantification of the alcohol precipitation liquid of Codonopsis Radix could be achieved with an NIRS-based method, which offers a useful tool for real-time release testing (RTRT) of intermediates in the manufacture of Codonopsis Radix.

Surface plasmon resonance near-infrared spectroscopy.

PubMed

Ikehata, Akifumi; Itoh, Tamitake; Ozaki, Yukihiro

2004-11-01

Near-infrared (NIR) spectroscopy is ill-suited to microanalysis because of its low absorptivity. We have developed a highly sensitive detection method for NIR spectroscopy based on absorption-sensitive surface plasmon resonance (SPR). The newly named SPR-NIR spectroscopy, which may open the way for NIR spectroscopy in microanalysis and surface science, is realized by an attachment of the Kretschmann configuration equipped with a mechanism for fine angular adjustment of incident light. The angular sweep of incident light enables us to make a tuning of a SPR peak for an absorption band of sample medium. From the dependences of wavelength, incident angle, and thickness of a gold film on the intensity of the SPR peak, it has been found that the absorbance can be enhanced by approximately 100 times compared with the absorbance obtained without the gold film under optimum conditions. This article reports the details of the experimental setup and the characteristics of absorption-sensitive SPR in the NIR region, together with some experimental results obtained by using it.

NIRS Identification of Swietenia Macrophylla is Robust Across Specimens from 27 Countries

Treesearch

Maria C.J. Bergo; Tereza C.M. Pastore; Vera T.R. Coradin; Alex C. Wiedenhoeft; Jez W.B. Braga

2016-01-01

Big-leaf mahogany is the world’s most valuable widely traded tropical timber species and Near Infrared Spectroscopy (NIRS) has been applied as a tool for discriminating its wood from similar species using multivariate analysis. In this study four look-alike timbers of Swietenia macrophylla (mahogany or big-leaf mahogany), Carapa...

Strategy Effects on Word Searching in Japanese Letter Fluency Tests: Evidence from the NIRS Findings

ERIC Educational Resources Information Center

Hatta, Takeshi; Kanari, Ayano; Mase, Mitsuhito; Nagano, Yuko; Shirataki, Tatsuaki; Hibino, Shinji

2009-01-01

Strategy effects on word searching in the Japanese letter fluency test were investigated using the Near-infrared Spectroscopy (NIRS). Participants were given a Japanese letter fluency test and they were classified into two types of strategy users, based on analysis of their recorded verbal responses. One group, AIUEO-order strategy users, employed…

An Improved Weighted Partial Least Squares Method Coupled with Near Infrared Spectroscopy for Rapid Determination of Multiple Components and Anti-Oxidant Activity of Pu-Erh Tea.

PubMed

Liu, Ze; Xie, Hua-Lin; Chen, Lin; Huang, Jian-Hua

2018-05-02

Background: Pu-erh tea is a unique microbially fermented tea, which distinctive chemical constituents and activities are worthy of systematic study. Near infrared spectroscopy (NIR) coupled with suitable chemometrics approaches can rapidly and accurately quantitatively analyze multiple compounds in samples. Methods: In this study, an improved weighted partial least squares (PLS) algorithm combined with near infrared spectroscopy (NIR) was used to construct a fast calibration model for determining four main components, i.e., tea polyphenols, tea polysaccharide, total flavonoids, theanine content, and further determine the total antioxidant capacity of pu-erh tea. Results: The final correlation coefficients R square for tea polyphenols, tea polysaccharide, total flavonoids content, theanine content, and total antioxidant capacity were 0.8288, 0.8403, 0.8415, 0.8537 and 0.8682, respectively. Conclusions : The current study provided a comprehensive study of four main ingredients and activity of pu-erh tea, and demonstrated that NIR spectroscopy technology coupled with multivariate calibration analysis could be successfully applied to pu-erh tea quality assessment.

In-line NIR spectroscopy for the understanding of polymer-drug interaction during pharmaceutical hot-melt extrusion.

PubMed

Saerens, Lien; Dierickx, Lien; Quinten, Thomas; Adriaensens, Peter; Carleer, Robert; Vervaet, Chris; Remon, Jean Paul; De Beer, Thomas

2012-05-01

The aim was to evaluate near-infrared spectroscopy for the in-line determination of the drug concentration, the polymer-drug solid-state behaviour and molecular interactions during hot-melt extrusion. Kollidon® SR was extruded with varying metoprolol tartrate (MPT) concentrations (20%, 30% and 40%) and monitored using NIR spectroscopy. A PLS model allowed drug concentration determination. The correlation between predicted and real MPT concentrations was good (R(2)=0.97). The predictive performance of the model was evaluated by the root mean square error of prediction, which was 1.54%. Kollidon® SR with 40% MPT was extruded at 105°C and 135°C to evaluate NIR spectroscopy for in-line polymer-drug solid-state characterisation. NIR spectra indicated the presence of amorphous MPT and hydrogen bonds between drug and polymer in the extrudates. More amorphous MPT and interactions could be found in the extrudates produced at 135°C than at 105°C. Raman spectroscopy, DSC and ATR FT-IR were used to confirm the NIR observations. Due to the instability of the formulation, only in-line Raman spectroscopy was an adequate confirmation tool. NIR spectroscopy is a potential PAT-tool for the in-line determination of API concentration and for the polymer-drug solid-state behaviour monitoring during pharmaceutical hot-melt extrusion. Copyright © 2012 Elsevier B.V. All rights reserved.

Entropy analysis of muscular near-infrared spectroscopy (NIRS) signals during exercise programme of type 2 diabetic patients: quantitative assessment of muscle metabolic pattern.

PubMed

Molinari, Filippo; Acharya, U Rajendra; Martis, Roshan Joy; De Luca, Riccardo; Petraroli, Giuliana; Liboni, William

2013-12-01

Diabetes mellitus (DM) is a metabolic disorder that is widely rampant throughout the world population these days. The uncontrolled DM may lead to complications of eye, heart, kidney and nerves. The most common type of diabetes is the type 2 diabetes or insulin-resistant DM. Near-infrared spectroscopy (NIRS) technology is widely used in non-invasive monitoring of physiological signals. Three types of NIRS signals are used in this work: (i) variation in the oxygenated haemoglobin (O2Hb) concentration, (ii) deoxygenated haemoglobin (HHb), and (iii) ratio of oxygenated over the sum of the oxygenated and deoxygenated haemoglobin which is defined as: tissue oxygenation index (TOI) to analyze the effect of exercise on diabetes subjects. The NIRS signal has the characteristics of non-linearity and non-stationarity. Hence, the very small changes in this time series can be efficiently extracted using higher order statistics (HOS) method. Hence, in this work, we have used sample and HOS entropies to analyze these NIRS signals. These computer aided techniques will assist the clinicians to diagnose and monitor the health accurately and easily without any inter or intra observer variability. Results showed that after a one-year of physical exercise programme, all diabetic subjects increased the sample entropy of the NIRS signals, thus revealing a better muscle performance and an improved recruitment by the central nervous system. Moreover, after one year of physical therapy, diabetic subjects showed a NIRS muscular metabolic pattern that was not distinguished from that of controls. We believe that sample and bispectral entropy analysis is need when the aim is to compare the inner structure of the NIRS signals during muscle contraction, particularly when dealing with neuromuscular impairments. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Near infrared spectroscopic imaging assessment of cartilage composition: Validation with mid infrared imaging spectroscopy.

PubMed

Palukuru, Uday P; Hanifi, Arash; McGoverin, Cushla M; Devlin, Sean; Lelkes, Peter I; Pleshko, Nancy

2016-07-05

Disease or injury to articular cartilage results in loss of extracellular matrix components which can lead to the development of osteoarthritis (OA). To better understand the process of disease development, there is a need for evaluation of changes in cartilage composition without the requirement of extensive sample preparation. Near infrared (NIR) spectroscopy is a chemical investigative technique based on molecular vibrations that is increasingly used as an assessment tool for studying cartilage composition. However, the assignment of specific molecular vibrations to absorbance bands in the NIR spectrum of cartilage, which arise from overtones and combinations of primary absorbances in the mid infrared (MIR) spectral region, has been challenging. In contrast, MIR spectroscopic assessment of cartilage is well-established, with many studies validating the assignment of specific bands present in MIR spectra to specific molecular vibrations. In the current study, NIR imaging spectroscopic data were obtained for compositional analysis of tissues that served as an in vitro model of OA. MIR spectroscopic data obtained from the identical tissue regions were used as the gold-standard for collagen and proteoglycan (PG) content. MIR spectroscopy in transmittance mode typically requires a much shorter pathlength through the sample (≤10 microns thick) compared to NIR spectroscopy (millimeters). Thus, this study first addressed the linearity of small absorbance bands in the MIR region with increasing tissue thickness, suitable for obtaining a signal in both the MIR and NIR regions. It was found that the linearity of specific, small MIR absorbance bands attributable to the collagen and PG components of cartilage (at 1336 and 856 cm(-1), respectively) are maintained through a thickness of 60 μm, which was also suitable for NIR data collection. MIR and NIR spectral data were then collected from 60 μm thick samples of cartilage degraded with chondroitinase ABC as a model of OA. Partial least squares (PLS) regression using NIR spectra as input predicted the MIR-determined compositional parameters of PG/collagen within 6% of actual values. These results indicate that NIR spectral data can be used to assess molecular changes that occur with cartilage degradation, and further, the data provide a foundation for future clinical studies where NIR fiber optic probes can be used to assess the progression of cartilage degradation. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of different classification methods for the diagnosis of schizophrenia based on functional near-infrared spectroscopy.

PubMed

Li, Zhaohua; Wang, Yuduo; Quan, Wenxiang; Wu, Tongning; Lv, Bin

2015-02-15

Based on near-infrared spectroscopy (NIRS), recent converging evidence has been observed that patients with schizophrenia exhibit abnormal functional activities in the prefrontal cortex during a verbal fluency task (VFT). Therefore, some studies have attempted to employ NIRS measurements to differentiate schizophrenia patients from healthy controls with different classification methods. However, no systematic evaluation was conducted to compare their respective classification performances on the same study population. In this study, we evaluated the classification performance of four classification methods (including linear discriminant analysis, k-nearest neighbors, Gaussian process classifier, and support vector machines) on an NIRS-aided schizophrenia diagnosis. We recruited a large sample of 120 schizophrenia patients and 120 healthy controls and measured the hemoglobin response in the prefrontal cortex during the VFT using a multichannel NIRS system. Features for classification were extracted from three types of NIRS data in each channel. We subsequently performed a principal component analysis (PCA) for feature selection prior to comparison of the different classification methods. We achieved a maximum accuracy of 85.83% and an overall mean accuracy of 83.37% using a PCA-based feature selection on oxygenated hemoglobin signals and support vector machine classifier. This is the first comprehensive evaluation of different classification methods for the diagnosis of schizophrenia based on different types of NIRS signals. Our results suggested that, using the appropriate classification method, NIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

In-line multipoint near-infrared spectroscopy for moisture content quantification during freeze-drying.

PubMed

Kauppinen, Ari; Toiviainen, Maunu; Korhonen, Ossi; Aaltonen, Jaakko; Järvinen, Kristiina; Paaso, Janne; Juuti, Mikko; Ketolainen, Jarkko

2013-02-19

During the past decade, near-infrared (NIR) spectroscopy has been applied for in-line moisture content quantification during a freeze-drying process. However, NIR has been used as a single-vial technique and thus is not representative of the entire batch. This has been considered as one of the main barriers for NIR spectroscopy becoming widely used in process analytical technology (PAT) for freeze-drying. Clearly it would be essential to monitor samples that reliably represent the whole batch. The present study evaluated multipoint NIR spectroscopy for in-line moisture content quantification during a freeze-drying process. Aqueous sucrose solutions were used as model formulations. NIR data was calibrated to predict the moisture content using partial least-squares (PLS) regression with Karl Fischer titration being used as a reference method. PLS calibrations resulted in root-mean-square error of prediction (RMSEP) values lower than 0.13%. Three noncontact, diffuse reflectance NIR probe heads were positioned on the freeze-dryer shelf to measure the moisture content in a noninvasive manner, through the side of the glass vials. The results showed that the detection of unequal sublimation rates within a freeze-dryer shelf was possible with the multipoint NIR system in use. Furthermore, in-line moisture content quantification was reliable especially toward the end of the process. These findings indicate that the use of multipoint NIR spectroscopy can achieve representative quantification of moisture content and hence a drying end point determination to a desired residual moisture level.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

NASA Astrophysics Data System (ADS)

Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri

2018-02-01

Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.

Underwater near-infrared spectroscopy can measure training adaptations in adolescent swimmers

PubMed Central

Parry, Dave; Cooper, Chris E.

2018-01-01

The development of an underwater near-infrared spectroscopy (uNIRS) device has enabled previously unattainable measurements of peripheral muscle hemodynamics and oxygenation to be taken within the natural aquatic environment. The purposes of this study were (i) to trial the use of uNIRS, in a real world training study, and (ii) to monitor the effects of a swim training program upon muscle oxygenation status in short distance swimming. A total of 14 junior club level swimmers completed a repeated swim sprint test before and after an eight week endurance training program. A waterproof, portable Near-Infrared Spectroscopy device was attached to the vastus lateralis. uNIRS successfully measured changes in muscle oxygenation and blood volume in all individuals; rapid sub-second time resolution of the device was able to demonstrate muscle oxygenation changes during the characteristic swim movements. Post training heart rate recovery and swim performance time were significantly improved. uNIRS data also showed significant changes. A larger rise in deoxyhemoglobin during individual sprints suggested training induced an increase in muscle oxygen extraction; a faster recovery time for muscle oxygenation suggested positive training induced changes and significant changes in muscle blood flow also occur. As a strong correlation was seen between an increased reoxygenation rate and an improved swim performance time, these findings support the use of uNIRS as a new performance analysis tool in swimming. PMID:29692951

Underwater near-infrared spectroscopy can measure training adaptations in adolescent swimmers.

PubMed

Jones, Ben; Parry, Dave; Cooper, Chris E

2018-01-01

The development of an underwater near-infrared spectroscopy (uNIRS) device has enabled previously unattainable measurements of peripheral muscle hemodynamics and oxygenation to be taken within the natural aquatic environment. The purposes of this study were (i) to trial the use of uNIRS, in a real world training study, and (ii) to monitor the effects of a swim training program upon muscle oxygenation status in short distance swimming. A total of 14 junior club level swimmers completed a repeated swim sprint test before and after an eight week endurance training program. A waterproof, portable Near-Infrared Spectroscopy device was attached to the vastus lateralis . uNIRS successfully measured changes in muscle oxygenation and blood volume in all individuals; rapid sub-second time resolution of the device was able to demonstrate muscle oxygenation changes during the characteristic swim movements. Post training heart rate recovery and swim performance time were significantly improved. uNIRS data also showed significant changes. A larger rise in deoxyhemoglobin during individual sprints suggested training induced an increase in muscle oxygen extraction; a faster recovery time for muscle oxygenation suggested positive training induced changes and significant changes in muscle blood flow also occur. As a strong correlation was seen between an increased reoxygenation rate and an improved swim performance time, these findings support the use of uNIRS as a new performance analysis tool in swimming.

Characterising protein, salt and water interactions with combined vibrational spectroscopic techniques.

PubMed

Perisic, Nebojsa; Afseth, Nils Kristian; Ofstad, Ragni; Hassani, Sahar; Kohler, Achim

2013-05-01

In this paper a combination of NIR spectroscopy and FTIR and Raman microspectroscopy was used to elucidate the effects of different salts (NaCl, KCl and MgSO(4)) on structural proteins and their hydration in muscle tissue. Multivariate multi-block technique Consensus Principal Component Analysis enabled integration of different vibrational spectroscopic techniques: macroscopic information obtained by NIR spectroscopy is directly related to microscopic information obtained by FTIR and Raman microspectroscopy. Changes in protein secondary structure observed at different concentrations of salts were linked to changes in protein hydration affinity. The evidence for this was given by connecting the underlying FTIR bands of the amide I region (1700-1600 cm(-1)) and the water region (3500-3000 cm(-1)) with water vibrations obtained by NIR spectroscopy. In addition, Raman microspectroscopy demonstrated that different cations affected structures of aromatic amino acid residues differently, which indicates that cation-π interactions play an important role in determination of the final structure of protein molecules. Copyright © 2012 Elsevier Ltd. All rights reserved.

Determination of polyphenolic compounds of red wines by UV-VIS-NIR spectroscopy and chemometrics tools.

PubMed

Martelo-Vidal, M J; Vázquez, M

2014-09-01

Spectral analysis is a quick and non-destructive method to analyse wine. In this work, trans-resveratrol, oenin, malvin, catechin, epicatechin, quercetin and syringic acid were determined in commercial red wines from DO Rías Baixas and DO Ribeira Sacra (Spain) by UV-VIS-NIR spectroscopy. Calibration models were developed using principal component regression (PCR) or partial least squares (PLS) regression. HPLC was used as reference method. The results showed that reliable PLS models were obtained to quantify all polyphenols for Rías Baixas wines. For Ribeira Sacra, feasible models were obtained to determine quercetin, epicatechin, oenin and syringic acid. PCR calibration models showed worst reliable of prediction than PLS models. For red wines from mencía grapes, feasible models were obtained for catechin and oenin, regardless the geographical origin. The results obtained demonstrate that UV-VIS-NIR spectroscopy can be used to determine individual polyphenolic compounds in red wines. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rapid monitoring of the fermentation process for Korean traditional rice wine 'Makgeolli' using FT-NIR spectroscopy

NASA Astrophysics Data System (ADS)

Kim, Dae-Yong; Cho, Byoung-Kwan

2015-11-01

The quality parameters of the Korean traditional rice wine "Makgeolli" were monitored using Fourier transform near-infrared (FT-NIR) spectroscopy with multivariate statistical analysis (MSA) during fermentation. Alcohol, reducing sugar, and titratable acid were the parameters assessed to determine the quality index of fermentation substrates and products. The acquired spectra were analyzed with partial least squares regression (PLSR). The best prediction model for alcohol was obtained with maximum normalization, showing a coefficient of determination (Rp2) of 0.973 and a standard error of prediction (SEP) of 0.760%. In addition, the best prediction model for reducing sugar was obtained with no data preprocessing, with a Rp2 value of 0.945 and a SEP of 1.233%. The prediction of titratable acidity was best with mean normalization, showing a Rp2 value of 0.882 and a SEP of 0.045%. These results demonstrate that FT-NIR spectroscopy can be used for rapid measurements of quality parameters during Makgeolli fermentation.

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

PubMed

Moriguchi, Yoshiya; Noda, Takamasa; Nakayashiki, Kosei; Takata, Yohei; Setoyama, Shiori; Kawasaki, Shingo; Kunisato, Yoshihiko; Mishima, Kazuo; Nakagome, Kazuyuki; Hanakawa, Takashi

2017-10-01

Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Cross-Correlation of Motor Activity Signals from dc-Magnetoencephalography, Near-Infrared Spectroscopy, and Electromyography

PubMed Central

Sander, Tilmann H.; Leistner, Stefanie; Wabnitz, Heidrun; Mackert, Bruno-Marcel; Macdonald, Rainer; Trahms, Lutz

2010-01-01

Neuronal and vascular responses due to finger movements were synchronously measured using dc-magnetoencephalography (dcMEG) and time-resolved near-infrared spectroscopy (trNIRS). The finger movements were monitored with electromyography (EMG). Cortical responses related to the finger movement sequence were extracted by independent component analysis from both the dcMEG and the trNIRS data. The temporal relations between EMG rate, dcMEG, and trNIRS responses were assessed pairwise using the cross-correlation function (CCF), which does not require epoch averaging. A positive lag on a scale of seconds was found for the maximum of the CCF between dcMEG and trNIRS. A zero lag is observed for the CCF between dcMEG and EMG. Additionally this CCF exhibits oscillations at the frequency of individual finger movements. These findings show that the dcMEG with a bandwidth up to 8 Hz records both slow and faster neuronal responses, whereas the vascular response is confirmed to change on a scale of seconds. PMID:20145717

Cross-correlation of motor activity signals from dc-magnetoencephalography, near-infrared spectroscopy, and electromyography.

PubMed

Sander, Tilmann H; Leistner, Stefanie; Wabnitz, Heidrun; Mackert, Bruno-Marcel; Macdonald, Rainer; Trahms, Lutz

2010-01-01

Neuronal and vascular responses due to finger movements were synchronously measured using dc-magnetoencephalography (dcMEG) and time-resolved near-infrared spectroscopy (trNIRS). The finger movements were monitored with electromyography (EMG). Cortical responses related to the finger movement sequence were extracted by independent component analysis from both the dcMEG and the trNIRS data. The temporal relations between EMG rate, dcMEG, and trNIRS responses were assessed pairwise using the cross-correlation function (CCF), which does not require epoch averaging. A positive lag on a scale of seconds was found for the maximum of the CCF between dcMEG and trNIRS. A zero lag is observed for the CCF between dcMEG and EMG. Additionally this CCF exhibits oscillations at the frequency of individual finger movements. These findings show that the dcMEG with a bandwidth up to 8 Hz records both slow and faster neuronal responses, whereas the vascular response is confirmed to change on a scale of seconds.

Numerical modeling of polymorphic transformation of oleic acid via near-infrared spectroscopy and factor analysis.

PubMed

Liu, Ling; Cheng, Yuliang; Sun, Xiulan; Pi, Fuwei

2018-05-15

Near-infrared (NIR) spectroscopy as a tool for direct and quantitatively screening the minute polymorphic transitions of bioactive fatty acids was assessed basing on a thermal heating process of oleic acid. Temperature-dependent NIR spectral profiles indicate that dynamical variances of COOH group dominate its γ → α phase transition, while the transition from active α to β phase mainly relates to the conformational transfer of acyl chain. Through operating multivariate curve resolution-alternating least squares with factor analysis, instantaneous contribution of each active polymorph during the transition process was illustrated for displaying the progressive evolutions of functional groups. Calculated contributions reveal that the α phase of oleic acid initially is present at around -18 °C, but sharply grows up around -2.2 °C from the transformation of γ phase and finally disappears at the melting point. On the other hand, the β phase of oleic acid is sole self-generation after melt even it embryonically appears at -2.2 °C. Such mathematical approach based on NIR spectroscopy and factor analysis calculation provides a volatile strategy in quantitatively exploring the transition processes of bioactive fatty acids; meanwhile, it maintains promising possibility for instantaneous quantifying each active polymorph of lipid materials. Copyright © 2018 Elsevier B.V. All rights reserved.

Numerical modeling of polymorphic transformation of oleic acid via near-infrared spectroscopy and factor analysis

NASA Astrophysics Data System (ADS)

Liu, Ling; Cheng, Yuliang; Sun, Xiulan; Pi, Fuwei

2018-05-01

Near-infrared (NIR) spectroscopy as a tool for direct and quantitatively screening the minute polymorphic transitions of bioactive fatty acids was assessed basing on a thermal heating process of oleic acid. Temperature-dependent NIR spectral profiles indicate that dynamical variances of COOH group dominate its γ → α phase transition, while the transition from active α to β phase mainly relates to the conformational transfer of acyl chain. Through operating multivariate curve resolution-alternating least squares with factor analysis, instantaneous contribution of each active polymorph during the transition process was illustrated for displaying the progressive evolutions of functional groups. Calculated contributions reveal that the α phase of oleic acid initially is present at around -18 °C, but sharply grows up around -2.2 °C from the transformation of γ phase and finally disappears at the melting point. On the other hand, the β phase of oleic acid is sole self-generation after melt even it embryonically appears at -2.2 °C. Such mathematical approach based on NIR spectroscopy and factor analysis calculation provides a volatile strategy in quantitatively exploring the transition processes of bioactive fatty acids; meanwhile, it maintains promising possibility for instantaneous quantifying each active polymorph of lipid materials.

Quantifying the cerebral metabolic rate of oxygen by combining diffuse correlation spectroscopy and time-resolved near-infrared spectroscopy.

PubMed

Verdecchia, Kyle; Diop, Mamadou; Lee, Ting-Yim; St Lawrence, Keith

2013-02-01

Preterm infants are highly susceptible to ischemic brain injury; consequently, continuous bedside monitoring to detect ischemia before irreversible damage occurs would improve patient outcome. In addition to monitoring cerebral blood flow (CBF), assessing the cerebral metabolic rate of oxygen (CMRO2) would be beneficial considering that metabolic thresholds can be used to evaluate tissue viability. The purpose of this study was to demonstrate that changes in absolute CMRO2 could be measured by combining diffuse correlation spectroscopy (DCS) with time-resolved near-infrared spectroscopy (TR-NIRS). Absolute CBF was determined using bolus-tracking TR-NIRS to calibrate the DCS measurements. Cerebral venous blood oxygenation (SvO2) was determined by multiwavelength TR-NIRS measurements, the accuracy of which was assessed by directly measuring the oxygenation of sagittal sinus blood. In eight newborn piglets, CMRO2 was manipulated by varying the anesthetics and by injecting sodium cyanide. No significant differences were found between the two sets of SvO2 measurements obtained by TR-NIRS or sagittal sinus blood samples and the corresponding CMRO2 measurements. Bland-Altman analysis showed a mean CMRO2 difference of 0.0268 ± 0.8340 mLO2/100 g/min between the two techniques over a range from 0.3 to 4 mL O2/100 g/min.

Quantifying the cerebral metabolic rate of oxygen by combining diffuse correlation spectroscopy and time-resolved near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Verdecchia, Kyle; Diop, Mamadou; Lee, Ting-Yim; St. Lawrence, Keith

2013-02-01

Preterm infants are highly susceptible to ischemic brain injury; consequently, continuous bedside monitoring to detect ischemia before irreversible damage occurs would improve patient outcome. In addition to monitoring cerebral blood flow (CBF), assessing the cerebral metabolic rate of oxygen (CMRO2) would be beneficial considering that metabolic thresholds can be used to evaluate tissue viability. The purpose of this study was to demonstrate that changes in absolute CMRO2 could be measured by combining diffuse correlation spectroscopy (DCS) with time-resolved near-infrared spectroscopy (TR-NIRS). Absolute CBF was determined using bolus-tracking TR-NIRS to calibrate the DCS measurements. Cerebral venous blood oxygenation (SvO2) was determined by multiwavelength TR-NIRS measurements, the accuracy of which was assessed by directly measuring the oxygenation of sagittal sinus blood. In eight newborn piglets, CMRO2 was manipulated by varying the anesthetics and by injecting sodium cyanide. No significant differences were found between the two sets of SvO2 measurements obtained by TR-NIRS or sagittal sinus blood samples and the corresponding CMRO2 measurements. Bland-Altman analysis showed a mean CMRO2 difference of 0.0268±0.8340 mL O2/100 g/min between the two techniques over a range from 0.3 to 4 mL O2/100 g/min.

Statistical analysis of fNIRS data: a comprehensive review.

PubMed

Tak, Sungho; Ye, Jong Chul

2014-01-15

Functional near-infrared spectroscopy (fNIRS) is a non-invasive method to measure brain activities using the changes of optical absorption in the brain through the intact skull. fNIRS has many advantages over other neuroimaging modalities such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), or magnetoencephalography (MEG), since it can directly measure blood oxygenation level changes related to neural activation with high temporal resolution. However, fNIRS signals are highly corrupted by measurement noises and physiology-based systemic interference. Careful statistical analyses are therefore required to extract neuronal activity-related signals from fNIRS data. In this paper, we provide an extensive review of historical developments of statistical analyses of fNIRS signal, which include motion artifact correction, short source-detector separation correction, principal component analysis (PCA)/independent component analysis (ICA), false discovery rate (FDR), serially-correlated errors, as well as inference techniques such as the standard t-test, F-test, analysis of variance (ANOVA), and statistical parameter mapping (SPM) framework. In addition, to provide a unified view of various existing inference techniques, we explain a linear mixed effect model with restricted maximum likelihood (ReML) variance estimation, and show that most of the existing inference methods for fNIRS analysis can be derived as special cases. Some of the open issues in statistical analysis are also described. Copyright © 2013 Elsevier Inc. All rights reserved.

Near-infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Parching Process of Traditional Chinese Medicine Based on Two Kinds of Chemical Indicators.

PubMed

Li, Kaiyue; Wang, Weiying; Liu, Yanping; Jiang, Su; Huang, Guo; Ye, Liming

2017-01-01

The active ingredients and thus pharmacological efficacy of traditional Chinese medicine (TCM) at different degrees of parching process vary greatly. Near-infrared spectroscopy (NIR) was used to develop a new method for rapid online analysis of TCM parching process, using two kinds of chemical indicators (5-(hydroxymethyl) furfural [5-HMF] content and 420 nm absorbance) as reference values which were obviously observed and changed in most TCM parching process. Three representative TCMs, Areca ( Areca catechu L.), Malt ( Hordeum Vulgare L.), and Hawthorn ( Crataegus pinnatifida Bge.), were used in this study. With partial least squares regression, calibration models of NIR were generated based on two kinds of reference values, i.e. 5-HMF contents measured by high-performance liquid chromatography (HPLC) and 420 nm absorbance measured by ultraviolet-visible spectroscopy (UV/Vis), respectively. In the optimized models for 5-HMF, the root mean square errors of prediction (RMSEP) for Areca, Malt, and Hawthorn was 0.0192, 0.0301, and 0.2600 and correlation coefficients ( R cal ) were 99.86%, 99.88%, and 99.88%, respectively. Moreover, in the optimized models using 420 nm absorbance as reference values, the RMSEP for Areca, Malt, and Hawthorn was 0.0229, 0.0096, and 0.0409 and R cal were 99.69%, 99.81%, and 99.62%, respectively. NIR models with 5-HMF content and 420 nm absorbance as reference values can rapidly and effectively identify three kinds of TCM in different parching processes. This method has great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online analysis and quality control in TCM industrial manufacturing process. Near-infrared spectroscopy.(NIR) was used to develop a new method for online analysis of traditional Chinese medicine.(TCM) parching processCalibration and validation models of Areca, Malt, and Hawthorn were generated by partial least squares regression using 5.(hydroxymethyl) furfural contents and 420.nm absorbance as reference values, respectively, which were main indicator components during parching process of most TCMThe established NIR models of three TCMs had low root mean square errors of prediction and high correlation coefficientsThe NIR method has great promise for use in TCM industrial manufacturing processes for rapid online analysis and quality control. Abbreviations used: NIR: Near-infrared Spectroscopy; TCM: Traditional Chinese medicine; Areca: Areca catechu L.; Hawthorn: Crataegus pinnatifida Bge.; Malt: Hordeum vulgare L.; 5-HMF: 5-(hydroxymethyl) furfural; PLS: Partial least squares; D: Dimension faction; SLS: Straight line subtraction, MSC: Multiplicative scatter correction; VN: Vector normalization; RMSECV: Root mean square errors of cross-validation; RMSEP: Root mean square errors of validation; R cal : Correlation coefficients; RPD: Residual predictive deviation; PAT: Process analytical technology; FDA: Food and Drug Administration; ICH: International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use.

Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy.

PubMed

Maltesen, Morten Jonas; van de Weert, Marco; Grohganz, Holger

2012-09-01

Moisture content and aerodynamic particle size are critical quality attributes for spray-dried protein formulations. In this study, spray-dried insulin powders intended for pulmonary delivery were produced applying design of experiments methodology. Near infrared spectroscopy (NIR) in combination with preprocessing and multivariate analysis in the form of partial least squares projections to latent structures (PLS) were used to correlate the spectral data with moisture content and aerodynamic particle size measured by a time of flight principle. PLS models predicting the moisture content were based on the chemical information of the water molecules in the NIR spectrum. Models yielded prediction errors (RMSEP) between 0.39% and 0.48% with thermal gravimetric analysis used as reference method. The PLS models predicting the aerodynamic particle size were based on baseline offset in the NIR spectra and yielded prediction errors between 0.27 and 0.48 μm. The morphology of the spray-dried particles had a significant impact on the predictive ability of the models. Good predictive models could be obtained for spherical particles with a calibration error (RMSECV) of 0.22 μm, whereas wrinkled particles resulted in much less robust models with a Q (2) of 0.69. Based on the results in this study, NIR is a suitable tool for process analysis of the spray-drying process and for control of moisture content and particle size, in particular for smooth and spherical particles.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Objective. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. Approach. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. Main results. The results showed that 86.0% (p<0.001 ) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. Significance. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Soil texture and organic carbon fractions predicted from near-infrared spectroscopy and geostatistics

USDA-ARS?s Scientific Manuscript database

Field-specific management could help achieve agricultural sustainability by increasing production and decreasing environmental impacts. Near-infrared spectroscopy (NIRS) and geostatistics are relatively unexplored tools that could reduce time, labor, and costs of soil analysis. Our objective was to ...

Effective Identification of Low-Gliadin Wheat Lines by Near Infrared Spectroscopy (NIRS): Implications for the Development and Analysis of Foodstuffs Suitable for Celiac Patients

PubMed Central

García-Molina, María Dolores; García-Olmo, Juan; Barro, Francisco

2016-01-01

Scope The aim of this work was to assess the ability of Near Infrared Spectroscopy (NIRS) to distinguish wheat lines with low gliadin content, obtained by RNA interference (RNAi), from non-transgenic wheat lines. The discriminant analysis was performed using both whole grain and flour. The transgenic sample set included 409 samples for whole grain sorting and 414 samples for flour experiments, while the non-transgenic set consisted of 126 and 156 samples for whole grain and flour, respectively. Methods and Results Samples were scanned using a Foss-NIR Systems 6500 System II instrument. Discrimination models were developed using the entire spectral range (400–2500 nm) and ranges of 400–780 nm, 800–1098 nm and 1100–2500 nm, followed by analysis of means of partial least square (PLS). Two external validations were made, using samples from the years 2013 and 2014 and a minimum of 99% of the flour samples and 96% of the whole grain samples were classified correctly. Conclusions The results demonstrate the ability of NIRS to successfully discriminate between wheat samples with low-gliadin content and wild types. These findings are important for the development and analysis of foodstuff for celiac disease (CD) patients to achieve better dietary composition and a reduction in disease incidence. PMID:27018786

Test-retest reliability of the prefrontal response to affective pictures based on functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Yuxia; Mao, Mengchai; Zhang, Zong; Zhou, Hui; Zhao, Yang; Duan, Lian; Kreplin, Ute; Xiao, Xiang; Zhu, Chaozhe

2017-01-01

Functional near-infrared spectroscopy (fNIRS) is being increasingly applied to affective and social neuroscience research; however, the reliability of this method is still unclear. This study aimed to evaluate the test-retest reliability of the fNIRS-based prefrontal response to emotional stimuli. Twenty-six participants viewed unpleasant and neutral pictures, and were simultaneously scanned by fNIRS in two sessions three weeks apart. The reproducibility of the prefrontal activation map was evaluated at three spatial scales (mapwise, clusterwise, and channelwise) at both the group and individual levels. The influence of the time interval was also explored and comparisons were made between longer (intersession) and shorter (intrasession) time intervals. The reliabilities of the activation map at the group level for the mapwise (up to 0.88, the highest value appeared in the intersession assessment) and clusterwise scales (up to 0.91, the highest appeared in the intrasession assessment) were acceptable, indicating that fNIRS may be a reliable tool for emotion studies, especially for a group analysis and under larger spatial scales. However, it should be noted that the individual-level and the channelwise fNIRS prefrontal responses were not sufficiently stable. Future studies should investigate which factors influence reliability, as well as the validity of fNIRS used in emotion studies.

[Applications and prospects of on-line near infrared spectroscopy technology in manufacturing of Chinese materia medica].

PubMed

Li, Yang; Wu, Zhi-Sheng; Pan, Xiao-Ning; Shi, Xin-Yuan; Guo, Ming-Ye; Xu, Bing; Qiao, Yan-Jiang

2014-10-01

The quality of Chinese materia medica (CMM) is affected by every process in CMM manufacturing. According to multi-unit complex features in the production of CMM, on-line near infrared spectroscopy (NIR) is used as an evaluating technology with its rapid, non-destructive and non-pollution etc. advantages. With the research in institutions, the on-line NIR applied in process analysis and control of CMM was described systematically, and the on-line NIR platform building was used as an example to clarify the feasibility of on-line NIR technology in CMM manufacturing process. Then, from the point of application by pharmaceutical companies, the current on-line NIR research on CMM and its production in pharmaceutical companies was relatively comprehensively summarized. Meanwhile, the types of CMM productions were classified in accordance with two formulations (liquid and solid dosage formulations). The different production processes (extraction, concentration and alcohol precipitation, etc. ) were used as liquid formulation diacritical points; the different types (tablets, capsules and plasters, etc.) were used as solid dosage formulation diacritical points, and the reliability of on-line NIR used in the whole process in CMM production was proved in according to the summary of literatures in recent 10 years, which could support the modernization of CMM production.

Do radio frequencies of medical instruments common in the operating room interfere with near-infrared spectroscopy signals?

NASA Astrophysics Data System (ADS)

Shadgan, Babak; Molavi, Behnam; Reid, W. D.; Dumont, Guy; Macnab, Andrew J.

2010-02-01

Background: Medical and diagnostic applications of near infrared spectroscopy (NIRS) are increasing, especially in operating rooms (OR). Since NIRS is an optical technique, radio frequency (RF) interference from other instruments is unlikely to affect the raw optical data, however, NIRS data processing and signal output could be affected. Methods: We investigated the potential for three common OR instruments: an electrical cautery, an orthopaedic drill and an imaging system, to generate electromagnetic interference (EMI) that could potentially influence NIRS signals. The time of onset and duration of every operation of each device was recorded during surgery. To remove the effects of slow changing physiological variables, we first used a lowpass filter and then selected 2 windows with variable lengths around the moment of device onset. For each instant, variances (energy) and means of the signals in the 2 windows were compared. Results: Twenty patients were studied during ankle surgery. Analysis shows no statistically significant difference in the means and variance of the NIRS signals (p < 0.01) during operation of any of the three devices for all surgeries. Conclusion: This method confirms the instruments evaluated caused no significant interference. NIRS can potentially be used without EMI in clinical environments such as the OR.

Analysis of protein glycation in human fingernail clippings with near-infrared (NIR) spectroscopy as an alternative technique for the diagnosis of diabetes mellitus.

PubMed

Monteyne, Tinne; Coopman, Renaat; Kishabongo, Antoine S; Himpe, Jonas; Lapauw, Bruno; Shadid, Samyah; Van Aken, Elisabeth H; Berenson, Darja; Speeckaert, Marijn M; De Beer, Thomas; Delanghe, Joris R

2018-05-11

Glycated keratin allows the monitoring of average tissue glucose exposure over previous weeks. In the present study, we wanted to explore if near-infrared (NIR) spectroscopy could be used as a non-invasive diagnostic tool for assessing glycation in diabetes mellitus. A total of 52 patients with diabetes mellitus and 107 healthy subjects were enrolled in this study. A limited number (n=21) of nails of healthy subjects were glycated in vitro with 0.278 mol/L, 0.556 mol/L and 0.833 mol/L glucose solution to study the effect of glucose on the nail spectrum. Consequently, the nail clippings of the patients were analyzed using a Thermo Fisher Antaris II Near-IR Analyzer Spectrometer and near infrared (NIR) chemical imaging. Spectral classification (patients with diabetes mellitus vs. healthy subjects) was performed using partial least square discriminant analysis (PLS-DA). In vitro glycation resulted in peak sharpening between 4300 and 4400 cm-1 and spectral variations at 5270 cm-1 and between 6600 and 7500 cm-1. Similar regions encountered spectral deviations during analysis of the patients' nails. Optimization of the spectral collection parameters was necessary in order to distinguish a large dataset. Spectra had to be collected at 16 cm-1, 128 scans, region 4000-7500 cm-1. Using standard normal variate, Savitsky-Golay smoothing (7 points) and first derivative preprocessing allowed for the prediction of the test set with 100% correct assignments utilizing a PLS-DA model. Analysis of protein glycation in human fingernail clippings with NIR spectroscopy could be an alternative affordable technique for the diagnosis of diabetes mellitus.

Food Safety Evaluation Based on Near Infrared Spectroscopy and Imaging: A Review.

PubMed

Fu, Xiaping; Ying, Yibin

2016-08-17

In recent years, due to the increasing consciousness of food safety and human health, much progress has been made in developing rapid and nondestructive techniques for the evaluation of food hazards, food authentication, and traceability. Near infrared (NIR) spectroscopy and imaging techniques have gained wide acceptance in many fields because of their advantages over other analytical techniques. Following a brief introduction of NIR spectroscopy and imaging basics, this review mainly focuses on recent NIR spectroscopy and imaging applications for food safety evaluation, including (1) chemical hazards detection; (2) microbiological hazards detection; (3) physical hazards detection; (4) new technology-induced food safety concerns; and (5) food traceability. The review shows NIR spectroscopy and imaging to be effective tools that will play indispensable roles for food safety evaluation. In addition, on-line/real-time applications of these techniques promise to be a huge growth field in the near future.

Quantitative analysis of bayberry juice acidity based on visible and near-infrared spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao Yongni; He Yong; Mao Jingyuan

Visible and near-infrared (Vis/NIR) reflectance spectroscopy has been investigated for its ability to nondestructively detect acidity in bayberry juice. What we believe to be a new, better mathematic model is put forward, which we have named principal component analysis-stepwise regression analysis-backpropagation neural network (PCA-SRA-BPNN), to build a correlation between the spectral reflectivity data and the acidity of bayberry juice. In this model, the optimum network parameters,such as the number of input nodes, hidden nodes, learning rate, and momentum, are chosen by the value of root-mean-square (rms) error. The results show that its prediction statistical parameters are correlation coefficient (r) ofmore » 0.9451 and root-mean-square error of prediction(RMSEP) of 0.1168. Partial least-squares (PLS) regression is also established to compare with this model. Before doing this, the influences of various spectral pretreatments (standard normal variate, multiplicative scatter correction, S. Golay first derivative, and wavelet package transform) are compared. The PLS approach with wavelet package transform preprocessing spectra is found to provide the best results, and its prediction statistical parameters are correlation coefficient (r) of 0.9061 and RMSEP of 0.1564. Hence, these two models are both desirable to analyze the data from Vis/NIR spectroscopy and to solve the problem of the acidity prediction of bayberry juice. This supplies basal research to ultimately realize the online measurements of the juice's internal quality through this Vis/NIR spectroscopy technique.« less

Rapid and quantitative detection of the microbial spoilage in chicken meat by diffuse reflectance spectroscopy (600-1100 nm).

PubMed

Lin, M; Al-Holy, M; Mousavi-Hesary, M; Al-Qadiri, H; Cavinato, A G; Rasco, B A

2004-01-01

To evaluate the feasibility of visible and short-wavelength near-infrared (SW-NIR) diffuse reflectance spectroscopy (600-1100 nm) to quantify the microbial loads in chicken meat and to develop a rapid methodology for monitoring the onset of spoilage. Twenty-four prepackaged fresh chicken breast muscle samples were prepared and stored at 21 degrees C for 24 h. Visible and SW-NIR was used to detect and quantify the microbial loads in chicken breast muscle at time intervals of 0, 2, 4, 6, 8, 10, 12 and 24 h. Spectra were collected in the diffuse reflectance mode (600-1100 nm). Total aerobic plate count (APC) of each sample was determined by the spread plate method at 32 degrees C for 48 h. Principal component analysis (PCA) and partial least squares (PLS) based prediction models were developed. PCA analysis showed clear segregation of samples held 8 h or longer compared with 0-h control. An optimum PLS model required eight latent variables for chicken muscle (R = 0.91, SEP = 0.48 log CFU g(-1)). Visible and SW-NIR combined with PCA is capable of perceiving the change of the microbial loads in chicken muscle once the APC increases slightly above 1 log cycle. Accurate quantification of the bacterial loads in chicken muscle can be calculated from the PLS-based prediction method. Visible and SW-NIR spectroscopy is a technique with a considerable potential for monitoring food safety and food spoilage. Visible and SW-NIR can acquire a metabolic snapshot and quantify the microbial loads of food samples rapidly, accurately, and noninvasively. This method would allow for more expeditious applications of quality control in food industries.

Identification of Medicinal Mugua Origin by Near Infrared Spectroscopy Combined with Partial Least-squares Discriminant Analysis.

PubMed

Han, Bangxing; Peng, Huasheng; Yan, Hui

2016-01-01

Mugua is a common Chinese herbal medicine. There are three main medicinal origin places in China, Xuancheng City Anhui Province, Qijiang District Chongqing City, Yichang City, Hubei Province, and suitable for food origin places Linyi City Shandong Province. To construct a qualitative analytical method to identify the origin of medicinal Mugua by near infrared spectroscopy (NIRS). Partial least squares discriminant analysis (PLSDA) model was established after the Mugua derived from five different origins were preprocessed by the original spectrum. Moreover, the hierarchical cluster analysis was performed. The result showed that PLSDA model was established. According to the relationship of the origins-related important score and wavenumber, and K-mean cluster analysis, the Muguas derived from different origins were effectively identified. NIRS technology can quickly and accurately identify the origin of Mugua, provide a new method and technology for the identification of Chinese medicinal materials. After preprocessed by D1+autoscale, more peaks were increased in the preprocessed Mugua in the near infrared spectrumFive latent variable scores could reflect the information related to the origin place of MuguaOrigins of Mugua were well-distinguished according to K. mean value clustering analysis. Abbreviations used: TCM: Traditional Chinese Medicine, NIRS: Near infrared spectroscopy, SG: Savitzky-Golay smoothness, D1: First derivative, D2: Second derivative, SNV: Standard normal variable transformation, MSC: Multiplicative scatter correction, PLSDA: Partial least squares discriminant analysis, LV: Latent variable, VIP scores: Important score.

Gastric cancer differentiation using Fourier transform near-infrared spectroscopy with unsupervised pattern recognition

NASA Astrophysics Data System (ADS)

Yi, Wei-song; Cui, Dian-sheng; Li, Zhi; Wu, Lan-lan; Shen, Ai-guo; Hu, Ji-ming

2013-01-01

The manuscript has investigated the application of near-infrared (NIR) spectroscopy for differentiation gastric cancer. The 90 spectra from cancerous and normal tissues were collected from a total of 30 surgical specimens using Fourier transform near-infrared spectroscopy (FT-NIR) equipped with a fiber-optic probe. Major spectral differences were observed in the CH-stretching second overtone (9000-7000 cm-1), CH-stretching first overtone (6000-5200 cm-1), and CH-stretching combination (4500-4000 cm-1) regions. By use of unsupervised pattern recognition, such as principal component analysis (PCA) and cluster analysis (CA), all spectra were classified into cancerous and normal tissue groups with accuracy up to 81.1%. The sensitivity and specificity was 100% and 68.2%, respectively. These present results indicate that CH-stretching first, combination band and second overtone regions can serve as diagnostic markers for gastric cancer.

Melamine detection in infant formula powder using near- and mid-infrared spectroscopy.

PubMed

Mauer, Lisa J; Chernyshova, Alona A; Hiatt, Ashley; Deering, Amanda; Davis, Reeta

2009-05-27

Near- and mid-infrared spectroscopy methods (NIR, FTIR-ATR, FTIR-DRIFT) were evaluated for the detection and quantification of melamine in infant formula powder. Partial least-squares (PLS) models were established for correlating spectral data to melamine concentration: R(2) > 0.99, RMSECV ≤ 0.9, and RPD ≥ 12. Factorization analysis of spectra was able to differentiate unadulterated infant formula powder from samples containing 1 ppm melamine with no misclassifications, a confidence level of 99.99%, and selectivity > 2. These nondestructive methods require little or no sample preparation. The NIR method has an assay time of 1 min, and a 2 min total time to detection. The FTIR methods require up to 5 min for melamine detection. Therefore, NIR and FTIR methods enable rapid detection of 1 ppm melamine in infant formula powder.

A novel approach to comparing reproductive stage serum profiles in mares using near infrared spectroscopy (NIR) and aquaphotomics

USDA-ARS?s Scientific Manuscript database

The capability of near infrared spectroscopy (NIR) to detect biomolecules in aqueous solutions, a sub-field of NIR called Aquaphotomics, has yet to be fully explored. Aquaphotomics references water absorbance patterns and wavelength shifts in the 1st overtone of the water spectrum as they change pat...

In vivo real time non invasive monitoring of brain penetration of chemicals with near-infrared spectroscopy: Concomitant PK/PD analysis.

PubMed

Crespi, Francesco; Cattini, Stefano; Donini, Maurizio; Bandera, Andrea; Rovati, Luigi

2016-01-30

Near-infrared spectroscopy (NIRS) is a non-invasive technique that monitors changes in oxygenation of haemoglobin. The absorption spectra of near-infrared light differ for the oxygenation-deoxygenation states of haemoglobin (oxygenate (HbO2) and deoxygenate (Hb), respectively) so that these two states can be directly monitored. Different methodologies report different basal values of HbO2 and Hb absolute concentrations in brain. Here, we attempt to calculate basal HbO2 levels in rat CNS via evaluation of the influence of exogenous oxygen or exogenous carbon dioxide on the NIRS parameters measured in vivo. Furthermore the possibility that changes of haemoglobin oxygenation in rat brain as measured by NIRS might be a useful index of brain penetration of chemical entities has been investigated. Different compounds from different chemical classes were selected on the basis of parallel ex vivo and in vivo pharmacokinetic (PK/PD) studies of brain penetration and overall pharmacokinetic profile. It appeared that NIRS might contribute to assess brain penetration of chemical entities, i.e. significant changes in NIRS signals could be related to brain exposure, conversely the lack of significant changes in relevant NIRS parameters could be indicative of low brain exposure. This work is proposing a further innovation on NIRS preclinical applications i.e. a "chemical" NIRS [chNIRS] approach for determining penetration of drugs in animal brain. Therefore, chNIRS could became a non invasive methodology for studies on neurobiological processes and psychiatric diseases in preclinical but also a translational strategy from preclinical to clinical investigations. Copyright © 2015 Elsevier B.V. All rights reserved.

Bilateral connectivity in the somatosensory region using near-infrared spectroscopy (NIRS) by wavelet coherence

NASA Astrophysics Data System (ADS)

Fernandez Rojas, Raul; Huang, Xu; Ou, Keng-Liang

2016-12-01

Near-infrared spectroscopy (NIRS) has been used in medical imaging to obtain oxygenation and hemodynamic response in the cerebral cortex. This technique has been applied in cortical activation detection and functional connectivity in brain research. Despite some advances in functional connectivity, most of the studies have focused on the prefrontal cortex and little has been done to study the somatosensory region (S1). For that reason, the aim of our present study is to assess bilateral connectivity in the somatosensory region by using NIRS and noxious stimulation. Eleven healthy subjects were investigated using near-infrared spectroscopy during an acupuncture stimulation procedure to safely induce pain in subjects. A multiscale analysis based on wavelet transform coherence (WTC) was designed to assess the functional connectivity of corresponding channel pairs within the left and right s1 region. The cortical activation in the somatosensory region was higher after the acupuncture stimulation, which was consistent with similar studies. The coherence in time-frequency domain between homologous signals generated by contralateral channel pairs revealed two main periods (3.2 s and 12.8 s) with high coherence. Based on the WTC analysis, it was also found that the coherence increase in these periods was task-related. This study contributes to the research field to investigate cerebral hemodynamic response of pain perception using NIRS and demonstrates the use of wavelet transform as a method to investigate functional lateralization in the cerebral cortex.

Maturation of the cytochrome cd1 nitrite reductase NirS from Pseudomonas aeruginosa requires transient interactions between the three proteins NirS, NirN and NirF

PubMed Central

Nicke, Tristan; Schnitzer, Tobias; Münch, Karin; Adamczack, Julia; Haufschildt, Kristin; Buchmeier, Sabine; Kucklick, Martin; Felgenträger, Undine; Jänsch, Lothar; Riedel, Katharina; Layer, Gunhild

2013-01-01

The periplasmic cytochrome cd1 nitrite reductase NirS occurring in denitrifying bacteria such as the human pathogen Pseudomonas aeruginosa contains the essential tetrapyrrole cofactors haem c and haem d1. Whereas the haem c is incorporated into NirS by the cytochrome c maturation system I, nothing is known about the insertion of the haem d1 into NirS. Here, we show by co-immunoprecipitation that NirS interacts with the potential haem d1 insertion protein NirN in vivo. This NirS–NirN interaction is dependent on the presence of the putative haem d1 biosynthesis enzyme NirF. Further, we show by affinity co-purification that NirS also directly interacts with NirF. Additionally, NirF is shown to be a membrane anchored lipoprotein in P. aeruginosa. Finally, the analysis by UV–visible absorption spectroscopy of the periplasmic protein fractions prepared from the P. aeruginosa WT (wild-type) and a P. aeruginosa ΔnirN mutant shows that the cofactor content of NirS is altered in the absence of NirN. Based on our results, we propose a potential model for the maturation of NirS in which the three proteins NirS, NirN and NirF form a transient, membrane-associated complex in order to achieve the last step of haem d1 biosynthesis and insertion of the cofactor into NirS. PMID:23683062

Time- and Space-Resolved Spectroscopic Investigation on Pi-Conjugated Nanostructures - 2

DTIC Science & Technology

2016-01-12

15. SUBJECT TERMS Materials Characterization, Materials Chemistry, Nonlinear Optical Materials, Spectroscopy 16. SECURITY CLASSIFICATION...nanostructures will translate into new ground-breaking developments that not only allow the structure-property relationships to be probed in greater detail... spectroscopy . I. Experimental method 1. Steady-state Spectroscopy - UV-Vis-NIR Absorption & Emission Steady-state Spectroscopy - NIR

Infrared and NIR Raman spectroscopy in medical microbiology

NASA Astrophysics Data System (ADS)

Naumann, Dieter

1998-04-01

FTIR and FT-NIR Raman spectra of intact microbial cells are highly specific, fingerprint-like signatures which can be used to (i) discriminate between diverse microbial species and strains, (ii) detect in situ intracellular components or structures such as inclusion bodies, storage materials or endospores, (iii) detect and quantify metabolically released CO2 in response to various different substrate, and (iv) characterize growth-dependent phenomena and cell-drug interactions. The characteristic information is extracted from the spectral contours by applying resolution enhancement techniques, difference spectroscopy, and pattern recognition methods such as factor-, cluster-, linear discriminant analysis, and artificial neural networks. Particularly interesting applications arise by means of a light microscope coupled to the spectrometer. FTIR spectra of micro-colonies containing less than 103 cells can be obtained from colony replica by a stamping technique that transfers micro-colonies growing on culture plates to a special IR-sample holder. Using a computer controlled x, y- stage together with mapping and video techniques, the fundamental tasks of microbiological analysis, namely detection, enumeration, and differentiation of micro- organisms can be integrated in one single apparatus. FTIR and NIR-FT-Raman spectroscopy can also be used in tandem to characterize medically important microorganisms. Currently novel methodologies are tested to take advantage of the complementary information of IR and Raman spectra. Representative examples on medically important microorganisms will be given that highlight the new possibilities of vibrational spectroscopies.

A comprehensive quality evaluation method by FT-NIR spectroscopy and chemometric: Fine classification and untargeted authentication against multiple frauds for Chinese Ganoderma lucidum

NASA Astrophysics Data System (ADS)

Fu, Haiyan; Yin, Qiaobo; Xu, Lu; Wang, Weizheng; Chen, Feng; Yang, Tianming

2017-07-01

The origins and authenticity against frauds are two essential aspects of food quality. In this work, a comprehensive quality evaluation method by FT-NIR spectroscopy and chemometrics were suggested to address the geographical origins and authentication of Chinese Ganoderma lucidum (GL). Classification for 25 groups of GL samples (7 common species from 15 producing areas) was performed using near-infrared spectroscopy and interval-combination One-Versus-One least squares support vector machine (IC-OVO-LS-SVM). Untargeted analysis of 4 adulterants of cheaper mushrooms was performed by one-class partial least squares (OCPLS) modeling for each of the 7 GL species. After outlier diagnosis and comparing the influences of different preprocessing methods and spectral intervals on classification, IC-OVO-LS-SVM with standard normal variate (SNV) spectra obtained a total classification accuracy of 0.9317, an average sensitivity and specificity of 0.9306 and 0.9971, respectively. With SNV or second-order derivative (D2) spectra, OCPLS could detect at least 2% or more doping levels of adulterants for 5 of the 7 GL species and 5% or more doping levels for the other 2 GL species. This study demonstrates the feasibility of using new chemometrics and NIR spectroscopy for fine classification of GL geographical origins and species as well as for untargeted analysis of multiple adulterants.

[Near-infrared reflectance spectroscopy predicts protein, moisture and ash in beans].

PubMed

Gao, Huiyu; Wang, Guodong; Men, Jianhua; Wang, Zhu

2017-05-01

To explore the potential of near-infrared reflectance( NIR)spectroscopy to determine macronutrient contents in beans. NIR spectra and analytical measurements of protein, moisture and ash were collected from 70 kinds of beans. Reference methods were used to analyze all the ground beans samples. NIR spectra on intact and ground beans samples were registered. Partial least-squares( PLS)regression models were developed with principal components analysis( PCA) to assign 49 bean accessions to a calibration data set and 21 accessions to an external validation set. For intact beans, the relative predictive determinant( RPD) values for protein and ash( 3. 67 and 3. 97, respectively) were good for screening. RPD value for moisture was only 1. 39, which was not recommended. For ground beans, the RPD values for protein, moisture and ash( 6. 63, 5. 25 and 3. 57, respectively) were good enough for screening. The protein, moisture and ash levels for intact and ground beans were all significantly correlated( P < 0. 001) between the NIR and reference method and there was no statistically significant difference in the mean with these three traits. This research demonstrates that NIR is a promising technique for simultaneous sorting ofmultiple traits in beans with no or easy sample preparation.

Recovering fNIRS brain signals: physiological interference suppression with independent component analysis

NASA Astrophysics Data System (ADS)

Zhang, Y.; Shi, M.; Sun, J.; Yang, C.; Zhang, Yajuan; Scopesi, F.; Makobore, P.; Chin, C.; Serra, G.; Wickramasinghe, Y. A. B. D.; Rolfe, P.

2015-02-01

Brain activity can be monitored non-invasively by functional near-infrared spectroscopy (fNIRS), which has several advantages in comparison with other methods, such as flexibility, portability, low cost and fewer physical restrictions. However, in practice fNIRS measurements are often contaminated by physiological interference arising from cardiac contraction, breathing and blood pressure fluctuations, thereby severely limiting the utility of the method. Hence, further improvement is necessary to reduce or eliminate such interference in order that the evoked brain activity information can be extracted reliably from fNIRS data. In the present paper, the multi-distance fNIRS probe configuration has been adopted. The short-distance fNIRS measurement is treated as the virtual channel and the long-distance fNIRS measurement is treated as the measurement channel. Independent component analysis (ICA) is employed for the fNIRS recordings to separate the brain signals and the interference. Least-absolute deviation (LAD) estimator is employed to recover the brain activity signals. We also utilized Monte Carlo simulations based on a five-layer model of the adult human head to evaluate our methodology. The results demonstrate that the ICA algorithm has the potential to separate physiological interference in fNIRS data and the LAD estimator could be a useful criterion to recover the brain activity signals.

Comparative NMR and NIRS analysis of oxygen-dependent metabolism in exercising finger flexor muscles.

PubMed

Bendahan, David; Chatel, Benjamin; Jue, Thomas

2017-12-01

Muscle contraction requires the physiology to adapt rapidly to meet the surge in energy demand. To investigate the shift in metabolic control, especially between oxygen and metabolism, researchers often depend on near-infrared spectroscopy (NIRS) to measure noninvasively the tissue O 2 Because NIRS detects the overlapping myoglobin (Mb) and hemoglobin (Hb) signals in muscle, interpreting the data as an index of cellular or vascular O 2 requires deconvoluting the relative contribution. Currently, many in the NIRS field ascribe the signal to Hb. In contrast, 1 H NMR has only detected the Mb signal in contracting muscle, and comparative NIRS and NMR experiments indicate a predominant Mb contribution. The present study has examined the question of the NIRS signal origin by measuring simultaneously the 1 H NMR, 31 P NMR, and NIRS signals in finger flexor muscles during the transition from rest to contraction, recovery, ischemia, and reperfusion. The experiment results confirm a predominant Mb contribution to the NIRS signal from muscle. Given the NMR and NIRS corroborated changes in the intracellular O 2 , the analysis shows that at the onset of muscle contraction, O 2 declines immediately and reaches new steady states as contraction intensity rises. Moreover, lactate formation increases even under quite aerobic condition. Copyright © 2017 the American Physiological Society.

Determination of geographical origin and icariin content of Herba Epimedii using near infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Yang, Yue; Wu, Yongjiang; Li, Weili; Liu, Xuesong; Zheng, Jiyu; Zhang, Wentao; Chen, Yong

2018-02-01

Near infrared (NIR) spectroscopy coupled with chemometrics was used to discriminate the geographical origin of Herba Epimedii in this work. Four different classification models, namely discriminant analysis (DA), back propagation neural network (BPNN), K-nearest neighbor (KNN), and support vector machine (SVM), were constructed, and their performances in terms of recognition accuracy were compared. The results indicated that the SVM model was superior over the other models in the geographical origin identification of Herba Epimedii. The recognition rates of the optimum SVM model were up to 100% for the calibration set and 94.44% for the prediction set, respectively. In addition, the feasibility of NIR spectroscopy with the CARS-PLSR calibration model in prediction of icariin content of Herba Epimedii was also investigated. The determination coefficient (RP2) and root-mean-square error (RMSEP) for prediction set were 0.9269 and 0.0480, respectively. It can be concluded that the NIR spectroscopy technique in combination with chemometrics has great potential in determination of geographical origin and icariin content of Herba Epimedii. This study can provide a valuable reference for rapid quality control of food products.

Identifying Plant Part Composition of Forest Logging Residue Using Infrared Spectral Data and Linear Discriminant Analysis

PubMed Central

Acquah, Gifty E.; Via, Brian K.; Billor, Nedret; Fasina, Oladiran O.; Eckhardt, Lori G.

2016-01-01

As new markets, technologies and economies evolve in the low carbon bioeconomy, forest logging residue, a largely untapped renewable resource will play a vital role. The feedstock can however be variable depending on plant species and plant part component. This heterogeneity can influence the physical, chemical and thermochemical properties of the material, and thus the final yield and quality of products. Although it is challenging to control compositional variability of a batch of feedstock, it is feasible to monitor this heterogeneity and make the necessary changes in process parameters. Such a system will be a first step towards optimization, quality assurance and cost-effectiveness of processes in the emerging biofuel/chemical industry. The objective of this study was therefore to qualitatively classify forest logging residue made up of different plant parts using both near infrared spectroscopy (NIRS) and Fourier transform infrared spectroscopy (FTIRS) together with linear discriminant analysis (LDA). Forest logging residue harvested from several Pinus taeda (loblolly pine) plantations in Alabama, USA, were classified into three plant part components: clean wood, wood and bark and slash (i.e., limbs and foliage). Five-fold cross-validated linear discriminant functions had classification accuracies of over 96% for both NIRS and FTIRS based models. An extra factor/principal component (PC) was however needed to achieve this in FTIRS modeling. Analysis of factor loadings of both NIR and FTIR spectra showed that, the statistically different amount of cellulose in the three plant part components of logging residue contributed to their initial separation. This study demonstrated that NIR or FTIR spectroscopy coupled with PCA and LDA has the potential to be used as a high throughput tool in classifying the plant part makeup of a batch of forest logging residue feedstock. Thus, NIR/FTIR could be employed as a tool to rapidly probe/monitor the variability of forest biomass so that the appropriate online adjustments to parameters can be made in time to ensure process optimization and product quality. PMID:27618901

Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

NASA Astrophysics Data System (ADS)

Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

2018-05-01

In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

[Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

PubMed

Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

2015-09-01

At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.

Clinical application of near-infrared spectroscopy in patients with traumatic brain injury: a review of the progress of the field.

PubMed

Sen, Anish N; Gopinath, Shankar P; Robertson, Claudia S

2016-07-01

Near-infrared spectroscopy (NIRS) is a technique by which the interaction between light in the near-infrared spectrum and matter can be quantitatively measured to provide information about the particular chromophore. Study into the clinical application of NIRS for traumatic brain injury (TBI) began in the 1990s with early reports of the ability to detect intracranial hematomas using NIRS. We highlight the advances in clinical applications of NIRS over the past two decades as they relate to TBI. We discuss recent studies evaluating NIRS techniques for intracranial hematoma detection, followed by the clinical application of NIRS in intracranial pressure and brain oxygenation measurement, and conclude with a summary of potential future uses of NIRS in TBI patient management.

In line NIR quantification of film thickness on pharmaceutical pellets during a fluid bed coating process.

PubMed

Lee, Min-Jeong; Seo, Da-Young; Lee, Hea-Eun; Wang, In-Chun; Kim, Woo-Sik; Jeong, Myung-Yung; Choi, Guang J

2011-01-17

Along with the risk-based approach, process analytical technology (PAT) has emerged as one of the key elements to fully implement QbD (quality-by-design). Near-infrared (NIR) spectroscopy has been extensively applied as an in-line/on-line analytical tool in biomedical and chemical industries. In this study, the film thickness on pharmaceutical pellets was examined for quantification using in-line NIR spectroscopy during a fluid-bed coating process. A precise monitoring of coating thickness and its prediction with a suitable control strategy is crucial to the quality assurance of solid dosage forms including dissolution characteristics. Pellets of a test formulation were manufactured and coated in a fluid-bed by spraying a hydroxypropyl methylcellulose (HPMC) coating solution. NIR spectra were acquired via a fiber-optic probe during the coating process, followed by multivariate analysis utilizing partial least squares (PLS) calibration models. The actual coating thickness of pellets was measured by two separate methods, confocal laser scanning microscopy (CLSM) and laser diffraction particle size analysis (LD-PSA). Both characterization methods gave superb correlation results, and all determination coefficient (R(2)) values exceeded 0.995. In addition, a prediction coating experiment for 70min demonstrated that the end-point can be accurately designated via NIR in-line monitoring with appropriate calibration models. In conclusion, our approach combining in-line NIR monitoring with CLSM and LD-PSA can be applied as an effective PAT tool for fluid-bed pellet coating processes. Copyright © 2010 Elsevier B.V. All rights reserved.

Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms.

PubMed

Gonzalez Viejo, Claudia; Fuentes, Sigfredo; Torrico, Damir; Howell, Kate; Dunshea, Frank R

2018-01-01

Beer quality is mainly defined by its colour, foamability and foam stability, which are influenced by the chemical composition of the product such as proteins, carbohydrates, pH and alcohol. Traditional methods to assess specific chemical compounds are usually time-consuming and costly. This study used rapid methods to evaluate 15 foam and colour-related parameters using a robotic pourer (RoboBEER) and chemical fingerprinting using near infrared spectroscopy (NIR) from six replicates of 21 beers from three types of fermentation. Results from NIR were used to create partial least squares regression (PLS) and artificial neural networks (ANN) models to predict four chemometrics such as pH, alcohol, Brix and maximum volume of foam. The ANN method was able to create more accurate models (R 2  = 0.95) compared to PLS. Principal components analysis using RoboBEER parameters and NIR overtones related to protein explained 67% of total data variability. Additionally, a sub-space discriminant model using the absorbance values from NIR wavelengths resulted in the successful classification of 85% of beers according to fermentation type. The method proposed showed to be a rapid system based on NIR spectroscopy and RoboBEER outputs of foamability that can be used to infer the quality, production method and chemical parameters of beer with minimal laboratory equipment. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Detection of urinary estrogen conjugates and creatinine using near infrared spectroscopy in Bornean orangutans (Pongo Pygmaeus).

PubMed

Kinoshita, Kodzue; Kuze, Noko; Kobayashi, Toshio; Miyakawa, Etsuko; Narita, Hiromitsu; Inoue-Murayama, Miho; Idani, Gen'ichi; Tsenkova, Roumiana

2016-01-01

For promoting in situ conservation, it is important to estimate the density distribution of fertile individuals, and there is a need for developing an easy monitoring method to discriminate between physiological states. To date, physiological state has generally been determined by measuring hormone concentration using radioimmunoassay or enzyme immunoassay (EIA) methods. However, these methods have rarely been applied in situ because of the requirements for a large amount of reagent, instruments, and a radioactive isotope. In addition, the proper storage of the sample (including urine and feces) on site until analysis is difficult. On the other hand, near infrared (NIR) spectroscopy requires no reagent and enables rapid measurement. In the present study, we attempted urinary NIR spectroscopy to determine the estrogen levels of orangutans in Japanese zoos and in the Danum Valley Conservation Area, Sabah, Malaysia. Reflectance NIR spectra were obtained from urine stored using a filter paper. Filter paper is easy to use to store dried urine, even in the wild. Urinary estrogen and creatinine concentrations measured by EIA were used as the reference data of partial least square (PLS) regression of urinary NIR spectra. High accuracies (R(2) > 0.68) were obtained in both estrogen and creatinine regression models. In addition, the PLS regressions in both standards showed higher accuracies (R(2) > 0.70). Therefore, the present study demonstrates that urinary NIR spectra have the potential to estimate the estrogen and creatinine concentrations.

A Brief Review on the Use of Functional Near-Infrared Spectroscopy (fNIRS) for Language Imaging Studies in Human Newborns and Adults

ERIC Educational Resources Information Center

Quaresima, Valentina; Bisconti, Silvia; Ferrari, Marco

2012-01-01

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have…

Near infrared spectroscopy and aquaphotomics analysis of serum from mares exposed to the fungal mycotoxin zearalenone

USDA-ARS?s Scientific Manuscript database

Aquaphotomics is a branch of near infrared spectroscopy (NIR) in which bond vibrations from organic molecules and water create unique spectral absorbance patterns to profile complex aqueous mixtures. Aquaphotomics has been shown to detect virus infected soybean plants from extracts, classify probiot...

Study on fast measurement of sugar content of yogurt using Vis/NIR spectroscopy techniques

NASA Astrophysics Data System (ADS)

He, Yong; Feng, Shuijuan; Wu, Di; Li, Xiaoli

2006-09-01

In order to measuring the sugar content of yogurt rapidly, a fast measurement of sugar content of yogurt using Vis/NIR-spectroscopy techniques was established. 25 samples selected separately from five different brands of yogurt were measured by Vis/NIR-spectroscopy. The sugar content of yogurt on positions scanned by spectrum were measured by a sugar content meter. The mathematical model between sugar content and Vis/NIR spectral measurements was established and developed based on partial least squares (PLS). The correlation coefficient of sugar content based on PLS model is more than 0.894, and standard error of calibration (SEC) is 0.356, standard error of prediction (SEP) is 0.389. Through predicting the sugar content quantitatively of 35 samples of yogurt from 5 different brands, the correlation coefficient between predictive value and measured value of those samples is more than 0.934. The results show the good to excellent prediction performance. The Vis/NIR spectroscopy technique had significantly greater accuracy for determining the sugar content. It was concluded that the Vis/NIRS measurement technique seems reliable to assess the fast measurement of sugar content of yogurt, and a new method for the measurement of sugar content of yogurt was established.

Melamine detection by mid- and near-infrared (MIR/NIR) spectroscopy: a quick and sensitive method for dairy products analysis including liquid milk, infant formula, and milk powder.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-07-15

Melamine (2,4,6-triamino-1,3,5-triazine) is a nitrogen-rich chemical implicated in the pet and human food recalls and in the global food safety scares involving milk products. Due to the serious health concerns associated with melamine consumption and the extensive scope of affected products, rapid and sensitive methods to detect melamine's presence are essential. We propose the use of spectroscopy data-produced by near-infrared (near-IR/NIR) and mid-infrared (mid-IR/MIR) spectroscopies, in particular-for melamine detection in complex dairy matrixes. None of the up-to-date reported IR-based methods for melamine detection has unambiguously shown its wide applicability to different dairy products as well as limit of detection (LOD) below 1 ppm on independent sample set. It was found that infrared spectroscopy is an effective tool to detect melamine in dairy products, such as infant formula, milk powder, or liquid milk. ALOD below 1 ppm (0.76±0.11 ppm) can be reached if a correct spectrum preprocessing (pretreatment) technique and a correct multivariate (MDA) algorithm-partial least squares regression (PLS), polynomial PLS (Poly-PLS), artificial neural network (ANN), support vector regression (SVR), or least squares support vector machine (LS-SVM)-are used for spectrum analysis. The relationship between MIR/NIR spectrum of milk products and melamine content is nonlinear. Thus, nonlinear regression methods are needed to correctly predict the triazine-derivative content of milk products. It can be concluded that mid- and near-infrared spectroscopy can be regarded as a quick, sensitive, robust, and low-cost method for liquid milk, infant formula, and milk powder analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

Detection and identification of bacteria in a juice matrix with Fourier transform-near infrared spectroscopy and multivariiate analysis.

PubMed

Rodriguez-Saona, L E; Khambaty, F M; Fry, F S; Dubois, J; Calvey, E M

2004-11-01

The use of Fourier transform-near infrared (FT-NIR) spectroscopy combined with multivariate pattern recognition techniques was evaluated to address the need for a fast and senisitive method for the detection of bacterial contamination in liquids. The complex cellular composition of bacteria produces FT-NIR vibrational transitions (overtone and combination bands), forming the basis for identification and subtyping. A database including strains of Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Bacillus cereus, and Bacillus thuringiensis was built, with special care taken to optimize sample preparation. The bacterial cells were treated with 70% (vol/vol) ethanolto enhance safe handling of pathogenic strains and then concentrated on an aluminum oxide membrane to obtain a thin bacterial film. This simple membrane filtration procedure generated reproducible FT-NIR spectra that allowed for the rapid discrimination among closely related strains. Principal component analysis and soft independent modeling of class analogy of transformed spectra in the region 5,100 to 4,400 cm(-1) were able to discriminate between bacterial species. Spectroscopic analysis of apple juices inoculated with different strains of E. coli at approximately 10(5) CFU/ml showed that FT-NIR spectralfeatures are consistent with bacterial contamination and soft independent modeling of class analogy correctly predicted the identity of the contaminant as strains of E. coli. FT-NIR in conjunction with multivariate techniques can be used for the rapid and accurate evaluation of potential bacterial contamination in liquids with minimal sample manipulation, and hence limited exposure of the laboratory worker to the agents.

Near infrared and Raman spectroscopy as Process Analytical Technology tools for the manufacturing of silicone-based drug reservoirs.

PubMed

Mantanus, J; Rozet, E; Van Butsele, K; De Bleye, C; Ceccato, A; Evrard, B; Hubert, Ph; Ziémons, E

2011-08-05

Using near infrared (NIR) and Raman spectroscopy as PAT tools, 3 critical quality attributes of a silicone-based drug reservoir were studied. First, the Active Pharmaceutical Ingredient (API) homogeneity in the reservoir was evaluated using Raman spectroscopy (mapping): the API distribution within the industrial drug reservoirs was found to be homogeneous while API aggregates were detected in laboratory scale samples manufactured with a non optimal mixing process. Second, the crosslinking process of the reservoirs was monitored at different temperatures with NIR spectroscopy. Conformity tests and Principal Component Analysis (PCA) were performed on the collected data to find out the relation between the temperature and the time necessary to reach the crosslinking endpoints. An agreement was found between the conformity test results and the PCA results. Compared to the conformity test method, PCA had the advantage to discriminate the heating effect from the crosslinking effect occurring together during the monitored process. Therefore the 2 approaches were found to be complementary. Third, based on the HPLC reference method, a NIR model able to quantify the API in the drug reservoir was developed and thoroughly validated. Partial Least Squares (PLS) regression on the calibration set was performed to build prediction models of which the ability to quantify accurately was tested with the external validation set. The 1.2% Root Mean Squared Error of Prediction (RMSEP) of the NIR model indicated the global accuracy of the model. The accuracy profile based on tolerance intervals was used to generate a complete validation report. The 95% tolerance interval calculated on the validation results indicated that each future result will have a relative error below ±5% with a probability of at least 95%. In conclusion, 3 critical quality attributes of silicone-based drug reservoirs were quickly and efficiently evaluated by NIR and Raman spectroscopy. Copyright © 2011 Elsevier B.V. All rights reserved.

Using near infrared spectroscopy to classify soybean oil according to expiration date.

PubMed

da Costa, Gean Bezerra; Fernandes, David Douglas Sousa; Gomes, Adriano A; de Almeida, Valber Elias; Veras, Germano

2016-04-01

A rapid and non-destructive methodology is proposed for the screening of edible vegetable oils according to conservation state expiration date employing near infrared (NIR) spectroscopy and chemometric tools. A total of fifty samples of soybean vegetable oil, of different brands andlots, were used in this study; these included thirty expired and twenty non-expired samples. The oil oxidation was measured by peroxide index. NIR spectra were employed in raw form and preprocessed by offset baseline correction and Savitzky-Golay derivative procedure, followed by PCA exploratory analysis, which showed that NIR spectra would be suitable for the classification task of soybean oil samples. The classification models were based in SPA-LDA (Linear Discriminant Analysis coupled with Successive Projection Algorithm) and PLS-DA (Discriminant Analysis by Partial Least Squares). The set of samples (50) was partitioned into two groups of training (35 samples: 15 non-expired and 20 expired) and test samples (15 samples 5 non-expired and 10 expired) using sample-selection approaches: (i) Kennard-Stone, (ii) Duplex, and (iii) Random, in order to evaluate the robustness of the models. The obtained results for the independent test set (in terms of correct classification rate) were 96% and 98% for SPA-LDA and PLS-DA, respectively, indicating that the NIR spectra can be used as an alternative to evaluate the degree of oxidation of soybean oil samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Diffuse Optical Tomography for Brain Imaging: Continuous Wave Instrumentation and Linear Analysis Methods

NASA Astrophysics Data System (ADS)

Giacometti, Paolo; Diamond, Solomon G.

Diffuse optical tomography (DOT) is a functional brain imaging technique that measures cerebral blood oxygenation and blood volume changes. This technique is particularly useful in human neuroimaging measurements because of the coupling between neural and hemodynamic activity in the brain. DOT is a multichannel imaging extension of near-infrared spectroscopy (NIRS). NIRS uses laser sources and light detectors on the scalp to obtain noninvasive hemodynamic measurements from spectroscopic analysis of the remitted light. This review explains how NIRS data analysis is performed using a combination of the modified Beer-Lambert law (MBLL) and the diffusion approximation to the radiative transport equation (RTE). Laser diodes, photodiode detectors, and optical terminals that contact the scalp are the main components in most NIRS systems. Placing multiple sources and detectors over the surface of the scalp allows for tomographic reconstructions that extend the individual measurements of NIRS into DOT. Mathematically arranging the DOT measurements into a linear system of equations that can be inverted provides a way to obtain tomographic reconstructions of hemodynamics in the brain.

Development of a near-infrared spectroscopy instrument for applications in urology.

PubMed

Macnab, Andrew J; Stothers, Lynn

2008-10-01

Near infrared spectroscopy (NIRS) is an established technology using photons of light in the near infrared spectrum to monitor changes in tissue of naturally occurring chromophores, including oxygenated and deoxygenated hemoglobin. Technology and methodology have been validated for measurement of a range of physiologic parameters. NIRS has been applied successfully in urology research; however current instruments are designed principally for brain and muscle study. To describe development of a NIRS instrument specifically designed for monitoring changes in chromophore concentration in the bladder detrusor in real time, to facilitate research to establish the role of this non-invasive technology in the evaluation of patients with voiding dysfunction The portable continuous wave NIRS instrument has a 3 laser diode light source (785, 808 and 830 nanometers), fiber optic cables for light transmission, a self adhesive patient interface patch with an emitter and sensor, and software to detect the difference between the light transmitted and received by the instrument. Software incorporated auto-attenuates the optical signals and converts raw optical data into chromophore concentrations displayed graphically. The prototype was designed, tested, and iteratively developed to achieve optimal suprapubic transcutaneous monitoring of the detrusor in human subjects during bladder filling and emptying. Evaluation with simultaneous invasive urodynamic measurement in men and women indicates good specificity and sensitivity of NIRS chromophore concentration changes by receiver operator curve analysis, and correlation between NIRS data and urodynamic pressures. Urological monitoring with this NIRS instrument is feasible and generates data of potential diagnostic value.

Rheo-optical two-dimensional (2D) near-infrared (NIR) correlation spectroscopy for probing strain-induced molecular chain deformation of annealed and quenched Nylon 6 films

NASA Astrophysics Data System (ADS)

Shinzawa, Hideyuki; Mizukado, Junji

2018-04-01

A rheo-optical characterization technique based on the combination of a near-infrared (NIR) spectrometer and a tensile testing machine is presented here. In the rheo-optical NIR spectroscopy, tensile deformations are applied to polymers to induce displacement of ordered or disordered molecular chains. The molecular-level variation of the sample occurring on short time scales is readily captured as a form of strain-dependent NIR spectra by taking an advantage of an acousto-optic tunable filter (AOTF) equipped with the NIR spectrometer. In addition, the utilization of NIR with much less intense absorption makes it possible to measure transmittance spectra of relatively thick samples which are often required for conventional tensile testing. An illustrative example of the rheo-optical technique is given with annealed and quenched Nylon 6 samples to show how this technique can be utilized to derive more penetrating insight even from the seemingly simple polymers. The analysis of the sets of strain-dependent NIR spectra suggests the presence of polymer structures undergoing different variations during the tensile elongation. For instance, the tensile deformation of the semi-crystalline Nylon 6 involves a separate step of elongation of the rubbery amorphous chains and subsequent disintegration of the rigid crystalline structure. Excess amount of crystalline phase in Nylon 6, however, results in the retardation of the elastic deformation mainly achieved by the amorphous structure, which eventually leads to the simultaneous orientation of both amorphous and crystalline structures.

Rapid evaluation and quantitative analysis of thyme, origano and chamomile essential oils by ATR-IR and NIR spectroscopy

NASA Astrophysics Data System (ADS)

Schulz, Hartwig; Quilitzsch, Rolf; Krüger, Hans

2003-12-01

The essential oils obtained from various chemotypes of thyme, origano and chamomile species were studied by ATR/FT-IR as well as NIR spectroscopy. Application of multivariate statistics (PCA, PLS) in conjunction with analytical reference data leads to very good IR and NIR calibration results. For the main essential oil components (e.g. carvacrol, thymol, γ-terpinene, α-bisabolol and β-farnesene) standard errors are in the range of the applied GC reference method. In most cases the multiple coefficients of determination ( R2) are >0.97. Using the IR fingerprint region (900-1400 cm -1) a qualitative discrimination of the individual chemotypes is possible already by visual judgement without to apply any chemometric algorithms.The described rapid and non-destructive methods can be applied in industry to control very easily purifying, blending and redistillation processes of the mentioned essential oils.

Noninvasive detection of intracerebral hemorrhage using near-infrared spectroscopy (NIRS)

NASA Astrophysics Data System (ADS)

Hennes, Hans-Juergen; Lott, Carsten; Windirsch, Michael; Hanley, Daniel F.; Boor, Stephan; Brambrink, Ansgar; Dick, Wolfgang

1998-01-01

Intracerebral Hemorrhage (IH) is an important cause of secondary brain injury in neurosurgical patients. Early identification and treatment improve neurologic outcome. We have tested Near Infrared Spectroscopy (NIRS) as an alternative noninvasive diagnostic tool compared to CT-Scans to detect IH. We prospectively studied 212 patients with neurologic symptoms associated with intracranial pathology before performing a CT-scan. NIRS signals indicated pathologies in 181 cases (sensitivity 0.96; specificity 0.29). In a subgroup of subdural hematomas NIRS detected 45 of 46 hematomas (sensitivity 0.96; specificity 0.79). Identification of intracerebral hemorrhage using NIRS has the potential to allow early treatment, thus possibly avoiding further injury.

Noninvasive detection of intracerebral hemorrhage using near-infrared spectroscopy (NIRS)

NASA Astrophysics Data System (ADS)

Hennes, Hans J.; Lott, C.; Windirsch, Michael; Hanley, Daniel F.; Boor, Stephan; Brambrink, Ansgar; Dick, Wolfgang

1997-12-01

Intracerebral Hemorrhage (IH) is an important cause of secondary brain injury in neurosurgical patients. Early identification and treatment improve neurologic outcome. We have tested Near Infrared Spectroscopy (NIRS) as an alternative noninvasive diagnostic tool compared to CT-Scans to detect IH. We prospectively studied 212 patients with neurologic symptoms associated with intracranial pathology before performing a CT-scan. NIRS signals indicated pathologies in 181 cases (sensitivity 0.96; specificity 0.29). In a subgroup of subdural hematomas NIRS detected 45 of 46 hematomas (sensitivity 0.96; specificity 0.79). Identification of intracerebral hemorrhage using NIRS has the potential to allow early treatment, thus possibly avoiding further injury.

Near-Infrared (NIR) Spectroscopy of Synthetic Hydroxyapatites and Human Dental Tissues.

PubMed

Kolmas, Joanna; Marek, Dariusz; Kolodziejski, Waclaw

2015-08-01

Near-infrared spectroscopy (NIR) was used to analyze synthetic hydroxyapatite calcined at various temperatures, synthetic carbonated hydroxyapatite, and human hard dental tissues (enamel and dentin). The NIR bands of those materials in the combination, first-overtone, and second-overtone spectral regions were assigned and evaluated for structural characterization. They were attributed to adsorbed and structural water, structural hydroxyl (OH) groups and surface P-OH groups. The NIR spectral features were quantitatively discussed in view of proton solid-state magic-angle spinning nuclear magnetic resonance ((1)H MAS NMR) results. We conclude that the NIR spectra of apatites are useful in the structural characterization of synthetic and biogenic apatites.

Rapid and non-invasive analysis of deoxynivalenol in durum and common wheat by Fourier-Transform Near Infrared (FT-NIR) spectroscopy.

PubMed

De Girolamo, A; Lippolis, V; Nordkvist, E; Visconti, A

2009-06-01

Fourier transform near-infrared spectroscopy (FT-NIR) was used for rapid and non-invasive analysis of deoxynivalenol (DON) in durum and common wheat. The relevance of using ground wheat samples with a homogeneous particle size distribution to minimize measurement variations and avoid DON segregation among particles of different sizes was established. Calibration models for durum wheat, common wheat and durum + common wheat samples, with particle size <500 microm, were obtained by using partial least squares (PLS) regression with an external validation technique. Values of root mean square error of prediction (RMSEP, 306-379 microg kg(-1)) were comparable and not too far from values of root mean square error of cross-validation (RMSECV, 470-555 microg kg(-1)). Coefficients of determination (r(2)) indicated an "approximate to good" level of prediction of the DON content by FT-NIR spectroscopy in the PLS calibration models (r(2) = 0.71-0.83), and a "good" discrimination between low and high DON contents in the PLS validation models (r(2) = 0.58-0.63). A "limited to good" practical utility of the models was ascertained by range error ratio (RER) values higher than 6. A qualitative model, based on 197 calibration samples, was developed to discriminate between blank and naturally contaminated wheat samples by setting a cut-off at 300 microg kg(-1) DON to separate the two classes. The model correctly classified 69% of the 65 validation samples with most misclassified samples (16 of 20) showing DON contamination levels quite close to the cut-off level. These findings suggest that FT-NIR analysis is suitable for the determination of DON in unprocessed wheat at levels far below the maximum permitted limits set by the European Commission.

NirN Protein from Pseudomonas aeruginosa is a Novel Electron-bifurcating Dehydrogenase Catalyzing the Last Step of Heme d1 Biosynthesis*

PubMed Central

Adamczack, Julia; Hoffmann, Martin; Papke, Ulrich; Haufschildt, Kristin; Nicke, Tristan; Bröring, Martin; Sezer, Murat; Weimar, Rebecca; Kuhlmann, Uwe; Hildebrandt, Peter; Layer, Gunhild

2014-01-01

Heme d1 plays an important role in denitrification as the essential cofactor of the cytochrome cd1 nitrite reductase NirS. At present, the biosynthesis of heme d1 is only partially understood. The last step of heme d1 biosynthesis requires a so far unknown enzyme that catalyzes the introduction of a double bond into one of the propionate side chains of the tetrapyrrole yielding the corresponding acrylate side chain. In this study, we show that a Pseudomonas aeruginosa PAO1 strain lacking the NirN protein does not produce heme d1. Instead, the NirS purified from this strain contains the heme d1 precursor dihydro-heme d1 lacking the acrylic double bond, as indicated by UV-visible absorption spectroscopy and resonance Raman spectroscopy. Furthermore, the dihydro-heme d1 was extracted from purified NirS and characterized by UV-visible absorption spectroscopy and finally identified by high-resolution electrospray ionization mass spectrometry. Moreover, we show that purified NirN from P. aeruginosa binds the dihydro-heme d1 and catalyzes the introduction of the acrylic double bond in vitro. Strikingly, NirN uses an electron bifurcation mechanism for the two-electron oxidation reaction, during which one electron ends up on its heme c cofactor and the second electron reduces the substrate/product from the ferric to the ferrous state. On the basis of our results, we propose novel roles for the proteins NirN and NirF during the biosynthesis of heme d1. PMID:25204657

A rapid method for detection of fumonisins B1 and B2 in corn meal using Fourier transform near infrared (FT-NIR) spectroscopy implemented with integrating sphere.

PubMed

Gaspardo, B; Del Zotto, S; Torelli, E; Cividino, S R; Firrao, G; Della Riccia, G; Stefanon, B

2012-12-01

Fourier transform near infrared (FT-NIR) spectroscopy is an analytical procedure generally used to detect organic compounds in food. In this work the ability to predict fumonisin B(1)+B(2) contents in corn meal using an FT-NIR spectrophotometer, equipped with an integration sphere, was assessed. A total of 143 corn meal samples were collected in Friuli Venezia Giulia Region (Italy) and used to define a 15 principal components regression model, applying partial least square regression algorithm with full cross validation as internal validation. External validation was performed to 25 unknown samples. Coefficients of correlation, root mean square error and standard error of calibration were 0.964, 0.630 and 0.632, respectively and the external validation confirmed a fair potential of the model in predicting FB(1)+FB(2) concentration. Results suggest that FT-NIR analysis is a suitable method to detect FB(1)+FB(2) in corn meal and to discriminate safe meals from those contaminated. Copyright © 2012 Elsevier Ltd. All rights reserved.

High resolution scanning of radial strips cut from increment cores by near infrared spectroscopy

Treesearch

P. David Jones; Laurence R. Schimleck; Chi-Leung So; Alexander III Clark; Richard F. Daniels

2007-01-01

Near infrared (NIR) spectroscopy provides a rapid method for the determination of wood properties of radial strips. The spatial resolution of the NIR measurements has generally been limited to sections 10 mm wide and as a consequence the estimation of wood properties of individual rings or within rings has not been possible. Many different NIR instruments can be used...

Comparison of time-gated surface-enhanced Raman spectroscopy (TG-SERS) and classical SERS based monitoring of Escherichia coli cultivation samples.

PubMed

Kögler, Martin; Paul, Andrea; Anane, Emmanuel; Birkholz, Mario; Bunker, Alex; Viitala, Tapani; Maiwald, Michael; Junne, Stefan; Neubauer, Peter

2018-06-08

The application of Raman spectroscopy as a monitoring technique for bioprocesses is severely limited by a large background signal originating from fluorescing compounds in the culture media. Here we compare time-gated Raman (TG-Raman)-, continuous wave NIR-process Raman (NIR-Raman) and continuous wave micro-Raman (micro-Raman) approaches in combination with surface enhanced Raman spectroscopy (SERS) for their potential to overcome this limit. For that purpose, we monitored metabolite concentrations of Escherichia coli bioreactor cultivations in cell-free supernatant samples. We investigated concentration transients of glucose, acetate, AMP and cAMP at alternating substrate availability, from deficiency to excess. Raman and SERS signals were compared to off-line metabolite analysis of carbohydrates, carboxylic acids and nucleotides. Results demonstrate that SERS, in almost all cases, led to a higher number of identifiable signals and better resolved spectra. Spectra derived from the TG-Raman were comparable to those of micro-Raman resulting in well-discernable Raman peaks, which allowed for the identification of a higher number of compounds. In contrast, NIR-Raman provided a superior performance for the quantitative evaluation of analytes, both with and without SERS nanoparticles when using multivariate data analysis. This article is protected by copyright. All rights reserved. © 2018 American Institute of Chemical Engineers.

Near-Infrared Spectroscopy and Imaging Studies of Fertilized Fish Eggs: In Vivo Monitoring of Egg Growth at the Molecular Level

NASA Astrophysics Data System (ADS)

Ishigaki, Mika; Kawasaki, Shoya; Ishikawa, Daitaro; Ozaki, Yukihiro

2016-01-01

In this work, the growth of fertilized Japanese medaka (Oryzias latipes) eggs was monitored in vivo at the molecular level using near-infrared (NIR) spectroscopy and NIR imaging. NIR spectra were recorded noninvasively for three major parts of a fertilized medaka egg, the embryonic body, the oil droplets, and the yolk, from the first day after fertilization to the day before hatching. Principal component analysis (PCA) revealed that water, protein, and lipid contents in the egg yolk and oil droplets changed significantly just before hatching. The ratio of the characteristic peaks due to proteins and lipids in the second derivative spectra suggested that the relative concentration of proteins to lipids was constant in the egg yolk, while it dramatically increased just before hatching in the oil droplets. Furthermore, linear discriminant analysis (LDA) predicted the hatching possibility on the next day with 100% and 99.3% accuracy for yolk and oil droplets data, respectively. Two types of NIR images were developed in situ using the band intensities of the lipids and proteins in the second derivative spectra. The egg’s protein and lipid content was successfully visualized noninvasively. This technique should enable noninvasive quality testing of fertilized eggs in the future.

Near-infrared spectroscopy (NIRS)-based eyes-closed brain-computer interface (BCI) using prefrontal cortex activation due to mental arithmetic

PubMed Central

Shin, Jaeyoung; Müller, Klaus-R; Hwang, Han-Jeong

2016-01-01

We propose a near-infrared spectroscopy (NIRS)-based brain-computer interface (BCI) that can be operated in eyes-closed (EC) state. To evaluate the feasibility of NIRS-based EC BCIs, we compared the performance of an eye-open (EO) BCI paradigm and an EC BCI paradigm with respect to hemodynamic response and classification accuracy. To this end, subjects performed either mental arithmetic or imagined vocalization of the English alphabet as a baseline task with very low cognitive loading. The performances of two linear classifiers were compared; resulting in an advantage of shrinkage linear discriminant analysis (LDA). The classification accuracy of EC paradigm (75.6 ± 7.3%) was observed to be lower than that of EO paradigm (77.0 ± 9.2%), which was statistically insignificant (p = 0.5698). Subjects reported they felt it more comfortable (p = 0.057) and easier (p < 0.05) to perform the EC BCI tasks. The different task difficulty may become a cause of the slightly lower classification accuracy of EC data. From the analysis results, we could confirm the feasibility of NIRS-based EC BCIs, which can be a BCI option that may ultimately be of use for patients who cannot keep their eyes open consistently. PMID:27824089

Near-infrared spectroscopy (NIRS)-based eyes-closed brain-computer interface (BCI) using prefrontal cortex activation due to mental arithmetic.

PubMed

Shin, Jaeyoung; Müller, Klaus-R; Hwang, Han-Jeong

2016-11-08

We propose a near-infrared spectroscopy (NIRS)-based brain-computer interface (BCI) that can be operated in eyes-closed (EC) state. To evaluate the feasibility of NIRS-based EC BCIs, we compared the performance of an eye-open (EO) BCI paradigm and an EC BCI paradigm with respect to hemodynamic response and classification accuracy. To this end, subjects performed either mental arithmetic or imagined vocalization of the English alphabet as a baseline task with very low cognitive loading. The performances of two linear classifiers were compared; resulting in an advantage of shrinkage linear discriminant analysis (LDA). The classification accuracy of EC paradigm (75.6 ± 7.3%) was observed to be lower than that of EO paradigm (77.0 ± 9.2%), which was statistically insignificant (p = 0.5698). Subjects reported they felt it more comfortable (p = 0.057) and easier (p < 0.05) to perform the EC BCI tasks. The different task difficulty may become a cause of the slightly lower classification accuracy of EC data. From the analysis results, we could confirm the feasibility of NIRS-based EC BCIs, which can be a BCI option that may ultimately be of use for patients who cannot keep their eyes open consistently.

Handling of uncertainty due to interference fringe in FT-NIR transmittance spectroscopy - Performance comparison of interference elimination techniques using glucose-water system

NASA Astrophysics Data System (ADS)

Beganović, Anel; Beć, Krzysztof B.; Henn, Raphael; Huck, Christian W.

2018-05-01

The applicability of two elimination techniques for interferences occurring in measurements with cells of short pathlength using Fourier transform near-infrared (FT-NIR) spectroscopy was evaluated. Due to the growing interest in the field of vibrational spectroscopy in aqueous biological fluids (e.g. glucose in blood), aqueous solutions of D-(+)-glucose were prepared and split into a calibration set and an independent validation set. All samples were measured with two FT-NIR spectrometers at various spectral resolutions. Moving average smoothing (MAS) and fast Fourier transform filter (FFT filter) were applied to the interference affected FT-NIR spectra in order to eliminate the interference pattern. After data pre-treatment, partial least squares regression (PLSR) models using different NIR regions were constructed using untreated (interference affected) spectra and spectra treated with MAS and FFT filter. The prediction of the independent validation set revealed information about the performance of the utilized interference elimination techniques, as well as the different NIR regions. The results showed that the combination band of water at approx. 5200 cm-1 is of great importance since its performance was superior to the one of the so-called first overtone of water at approx. 6800 cm-1. Furthermore, this work demonstrated that MAS and FFT filter are fast and easy-to-use techniques for the elimination of interference fringes in FT-NIR transmittance spectroscopy.

Hemodynamic Response to Interictal Epileptiform Discharges Addressed by Personalized EEG-fNIRS Recordings

PubMed Central

Pellegrino, Giovanni; Machado, Alexis; von Ellenrieder, Nicolas; Watanabe, Satsuki; Hall, Jeffery A.; Lina, Jean-Marc; Kobayashi, Eliane; Grova, Christophe

2016-01-01

Objective: We aimed at studying the hemodynamic response (HR) to Interictal Epileptic Discharges (IEDs) using patient-specific and prolonged simultaneous ElectroEncephaloGraphy (EEG) and functional Near InfraRed Spectroscopy (fNIRS) recordings. Methods: The epileptic generator was localized using Magnetoencephalography source imaging. fNIRS montage was tailored for each patient, using an algorithm to optimize the sensitivity to the epileptic generator. Optodes were glued using collodion to achieve prolonged acquisition with high quality signal. fNIRS data analysis was handled with no a priori constraint on HR time course, averaging fNIRS signals to similar IEDs. Cluster-permutation analysis was performed on 3D reconstructed fNIRS data to identify significant spatio-temporal HR clusters. Standard (GLM with fixed HRF) and cluster-permutation EEG-fMRI analyses were performed for comparison purposes. Results: fNIRS detected HR to IEDs for 8/9 patients. It mainly consisted oxy-hemoglobin increases (seven patients), followed by oxy-hemoglobin decreases (six patients). HR was lateralized in six patients and lasted from 8.5 to 30 s. Standard EEG-fMRI analysis detected an HR in 4/9 patients (4/9 without enough IEDs, 1/9 unreliable result). The cluster-permutation EEG-fMRI analysis restricted to the region investigated by fNIRS showed additional strong and non-canonical BOLD responses starting earlier than the IEDs and lasting up to 30 s. Conclusions: (i) EEG-fNIRS is suitable to detect the HR to IEDs and can outperform EEG-fMRI because of prolonged recordings and greater chance to detect IEDs; (ii) cluster-permutation analysis unveils additional HR features underestimated when imposing a canonical HR function (iii) the HR is often bilateral and lasts up to 30 s. PMID:27047325

Subsequent development of fibroatheromas with inflamed fibrous caps can be predicted by intracoronary near infrared spectroscopy.

PubMed

Patel, Dhavalkumar; Hamamdzic, Damir; Llano, Raul; Patel, Daivesh; Cheng, Lan; Fenning, Robert S; Bannan, Khalid; Wilensky, Robert L

2013-02-01

To prospectively evaluate whether the development of fibroatheromas exhibiting features of potential instability can be detected and predicted by serial invasive imaging. Multivessel intravascular ultrasound and near infrared spectroscopy (NIRS) were performed in diabetic/hypercholesterolemic pigs 3, 6, and 9 months after induction. Animals were euthanized at 9 months and histological/immunohistochemical evaluation of the arteries was performed (n=304 arterial segments). Intravascular ultrasound demonstrated, over time, a progressive increase in plaque + media and necrotic core areas and positive vascular remodeling. By histology, NIRS+ lesions were significantly more likely to be a high-risk fibroatheroma (P=0.0001) containing larger plaque (P<0.0001) and necrotic core areas (P<0.0019) and thinner fibrous caps (P=0.04). NIRS + fibroatheromas possessed a greater concentration of inflammatory cells demonstrating protease activity (P=0.006), and proliferating (P=0.016), and apoptotic cells (P=0.04) within the fibrous cap. Eighty-eight percent of NIRS+ lesions at 3 and 6 months subsequently developed into a fibroatheroma at 9 months (P<0.01). By multivariate analysis NIRS positivity at 6 months predicted the subsequent presence of a fibroatheroma at 9 months (P=0.005; odds ratio, 2.71). The future development of inflamed fibroatheromas with thinner fibrous caps, greater plaque, and necrotic core areas, and posessing characteristics of increased plaque instability were detected by intravascular ultrasound/NIRS imaging.

Evaluation of portable near-infrared spectroscopy for organic milk authentication.

PubMed

Liu, Ningjing; Parra, Hector Aya; Pustjens, Annemieke; Hettinga, Kasper; Mongondry, Philippe; van Ruth, Saskia M

2018-07-01

Organic products are vulnerable to fraud due to their premium price. Analytical methodology helps to manage the risk of fraud and due to the miniaturization of equipment, tests may nowadays even be rapidly applied on-site. The current study aimed to evaluate portable near infrared spectroscopy (NIRS) in combination with chemometrics to distinguish organic milk from other types of milk, and compare its performance with benchtop NIRS and fatty acid profiling by gas chromatography. The sample set included 37 organic retail milks and 50 non-organic retail milks (of which 36 conventional and 14 green 'pasture' milks). Partial least squares discriminant analysis was performed to build classification models and kernel density estimation (KDE) functions were calculated to generate non-parametric distributions for samples' class probabilities. These distributions showed that portable NIRS was successful to distinguish organic milks from conventional milks, and so were benchtop NIRS and fatty acid profiling procedures. However, it was less successful when 'pasture' milks were considered too, since their patterns occasionally resembled those of the organic milk group. Fatty acid profiling was capable of distinguishing organic milks from both non-organic milks though, including the 'pasture' milks. This comparative study revealed that the classification performance of the portable NIRS for this application was similar to that of the benchtop NIRS. Copyright © 2018 Elsevier B.V. All rights reserved.

Cerebral oxygenation in traumatic brain injury; Can a non-invasive frequency domain near-infrared spectroscopy device detect changes in brain tissue oxygen tension as well as the established invasive monitor?

PubMed

Davies, David James; Clancy, Michael; Dehghani, Hamid; Lucas, Samuel John Edwin; Forcione, Mario; Yakoub, Kamal Makram; Belli, Antonio

2018-06-07

The cost and highly invasive nature of brain monitoring modality in traumatic brain injury patients currently restrict its utility to specialist neurological intensive care settings. We aim to test the abilities of a frequency domain near-infrared spectroscopy (FD-NIRS) device in predicting changes in invasively measured brain tissue oxygen tension. Individuals admitted to a United Kingdom specialist major trauma centre were contemporaneously monitored with an FD-NIRS device and invasively measured brain tissue oxygen tension probe. Area under the curve receiver operating characteristic (AUROC) statistical analysis was utilised to assess the predictive power of FD-NIRS in detecting both moderate and severe hypoxia (20 and 10 mmHg, respectively), as measured invasively. 16 individuals were prospectively recruited to the investigation. Severe hypoxic episodes were detected in 9 of these individuals, with the NIRS demonstrating a broad range of predictive abilities (AUROC 0.68-0.88) from relatively poor to good. Moderate hypoxic episodes were detected in seven individuals with similar predictive performance (AUROC 0.576 - 0.905). A variable performance in the predictive powers of this FD-NIRS device to detect changes in brain tissue oxygen was demonstrated. Consequently, this enhanced NIRS technology has not demonstrated sufficient ability to replace the established invasive measurement.

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes

PubMed Central

Funane, Tsukasa; Sato, Hiroki; Yahata, Noriaki; Takizawa, Ryu; Nishimura, Yukika; Kinoshita, Akihide; Katura, Takusige; Atsumori, Hirokazu; Fukuda, Masato; Kasai, Kiyoto; Koizumi, Hideaki; Kiguchi, Masashi

2015-01-01

Abstract. It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level–dependent signals was analyzed. A three-way analysis of variance (signal depth×Hb kind×task) indicated that the main effect of fNIRS signal depth on the correlation is significant [F(1,1286)=5.34, p<0.05]. This result indicates that the MD-ICA method successfully separates fNIRS signals into spatially deep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method. PMID:26157983

Dissolution assessment of allopurinol immediate release tablets by near infrared spectroscopy.

PubMed

Smetiško, Jelena; Miljanić, Snežana

2017-10-25

The purpose of this study was to develop a NIR spectroscopic method for assessment of drug dissolution from allopurinol immediate release tablets. Thirty three different batches of allopurinol immediate release tablets containing constant amount of the active ingredient, but varying in excipients content and physical properties were introduced in a PLS calibration model. Correlating allopurinol dissolution reference values measured by the routinely used UV/Vis method, with the data extracted from the NIR spectra, values of correlation coefficient, bias, slope, residual prediction determination and root mean square error of prediction (0.9632, 0.328%, 1.001, 3.58, 3.75%) were evaluated. The obtained values implied that the NIR diffuse reflectance spectroscopy could serve as a faster and simpler alternative to the conventional dissolution procedure, even for the tablets with a very fast dissolution rate (>85% in 15minutes). Apart from the possibility of prediction of the allopurinol dissolution rate, the other multivariate technique, PCA, provided additional data on the non-chemical characteristics of the product, which could not be obtained from the reference dissolution values. Analysis on an independent set of samples confirmed that a difference between the UV/Vis reference method and the proposed NIR method was not significant. According to the presented results, the proposed NIR method may be suitable for practical application in routine analysis and for continuously monitoring the product's chemical and physical properties responsible for expected quality. Copyright © 2017 Elsevier B.V. All rights reserved.

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex.

PubMed

Kirilina, Evgeniya; Yu, Na; Jelzow, Alexander; Wabnitz, Heidrun; Jacobs, Arthur M; Tachtsidis, Ilias

2013-01-01

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation processes on multiple time scales. The goal of the present study was to identify the main physiological noise contributions in fNIRS forehead signals and to develop a method for physiological de-noising of fNIRS data. To achieve this goal we combined concurrent time-domain fNIRS and peripheral physiology recordings with wavelet coherence analysis (WCA). Depth selectivity was achieved by analyzing moments of photon time-of-flight distributions provided by time-domain fNIRS. Simultaneously, mean arterial blood pressure (MAP), heart rate (HR), and skin blood flow (SBF) on the forehead were recorded. WCA was employed to quantify the impact of physiological processes on fNIRS signals separately for different time scales. We identified three main processes contributing to physiological noise in fNIRS signals on the forehead. The first process with the period of about 3 s is induced by respiration. The second process is highly correlated with time lagged MAP and HR fluctuations with a period of about 10 s often referred as Mayer waves. The third process is local regulation of the facial SBF time locked to the task-evoked fNIRS signals. All processes affect oxygenated haemoglobin concentration more strongly than that of deoxygenated haemoglobin. Based on these results we developed a set of physiological regressors, which were used for physiological de-noising of fNIRS signals. Our results demonstrate that proposed de-noising method can significantly improve the sensitivity of fNIRS to cerebral signals.

The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy.

PubMed

Kirilina, Evgeniya; Jelzow, Alexander; Heine, Angela; Niessing, Michael; Wabnitz, Heidrun; Brühl, Rüdiger; Ittermann, Bernd; Jacobs, Arthur M; Tachtsidis, Ilias

2012-05-15

A major methodological challenge of functional near-infrared spectroscopy (fNIRS) is its high sensitivity to haemodynamic fluctuations in the scalp. Superficial fluctuations contribute on the one hand to the physiological noise of fNIRS, impairing the signal-to-noise ratio, and may on the other hand be erroneously attributed to cerebral changes, leading to false positives in fNIRS experiments. Here we explore the localisation, time course and physiological origin of task-evoked superficial signals in fNIRS and present a method to separate them from cortical signals. We used complementary fNIRS, fMRI, MR-angiography and peripheral physiological measurements (blood pressure, heart rate, skin conductance and skin blood flow) to study activation in the frontal lobe during a continuous performance task. The General Linear Model (GLM) was applied to analyse the fNIRS data, which included an additional predictor to account for systemic changes in the skin. We found that skin blood volume strongly depends on the cognitive state and that sources of task-evoked systemic signals in fNIRS are co-localized with veins draining the scalp. Task-evoked superficial artefacts were mainly observed in concentration changes of oxygenated haemoglobin and could be effectively separated from cerebral signals by GLM analysis. Based on temporal correlation of fNIRS and fMRI signals with peripheral physiological measurements we conclude that the physiological origin of the systemic artefact is a task-evoked sympathetic arterial vasoconstriction followed by a decrease in venous volume. Since changes in sympathetic outflow accompany almost any cognitive and emotional process, we expect scalp vessel artefacts to be present in a wide range of fNIRS settings used in neurocognitive research. Therefore a careful separation of fNIRS signals originating from activated brain and from scalp is a necessary precondition for unbiased fNIRS brain activation maps. Copyright © 2012 Elsevier Inc. All rights reserved.

Analysis of Flavonoid in Medicinal Plant Extract Using Infrared Spectroscopy and Chemometrics

PubMed Central

Retnaningtyas, Yuni; Nuri; Lukman, Hilmia

2016-01-01

Infrared (IR) spectroscopy combined with chemometrics has been developed for simple analysis of flavonoid in the medicinal plant extract. Flavonoid was extracted from medicinal plant leaves by ultrasonication and maceration. IR spectra of selected medicinal plant extract were correlated with flavonoid content using chemometrics. The chemometric method used for calibration analysis was Partial Last Square (PLS) and the methods used for classification analysis were Linear Discriminant Analysis (LDA), Soft Independent Modelling of Class Analogies (SIMCA), and Support Vector Machines (SVM). In this study, the calibration of NIR model that showed best calibration with R 2 and RMSEC value was 0.9916499 and 2.1521897, respectively, while the accuracy of all classification models (LDA, SIMCA, and SVM) was 100%. R 2 and RMSEC of calibration of FTIR model were 0.8653689 and 8.8958149, respectively, while the accuracy of LDA, SIMCA, and SVM was 86.0%, 91.2%, and 77.3%, respectively. PLS and LDA of NIR models were further used to predict unknown flavonoid content in commercial samples. Using these models, the significance of flavonoid content that has been measured by NIR and UV-Vis spectrophotometry was evaluated with paired samples t-test. The flavonoid content that has been measured with both methods gave no significant difference. PMID:27529051

Effects of the density and homogeneity in NIRS crop moisture estimation

NASA Astrophysics Data System (ADS)

Lenzini, Nicola; Rovati, Luigi; Ferrari, Luca

2017-06-01

Near-infrared spectroscopy (NIRS) is widely used in fruits and vegetables quality evaluation. This technique is also used for the analysis of alfalfa, a crop that occupies a position of great importance in the agricultural field. In particular for the storage, moisture content is a key parameter for the crops and for this reason its monitoring is very important during the harvesting phase. Usually optical methods like NIRS are well suitable in laboratory frameworks where the specimen is properly prepared, while their application during the harvesting phase presents several diffculties. A lot of influencing factors, such as density and degree of homogeneity can affect the moisture evaluation. In this paper we present the NIRS analysis of alfalfa specimens with different values of moisture and density, as well as the obtained results. To study scattering and absorption phenomena, the forward and backward scattered light from the sample have been spectrally analyzed.

Analysis of Total Oil and Fatty Acids Composition by Near Infrared Reflectance Spectroscopy in Edible Nuts

USDA-ARS?s Scientific Manuscript database

Near Infrared (NIR) Reflectance spectroscopy has established itself as an important tool in quantifying water and oil present in various food materials. It is rapid and nondestructive, easier to use, and does not require processing the samples with corrosive chemicals that would render them non-edib...

Classification of broiler breast fillets according to storage and to freeze-thaw treatment using near infrared spectroscopy and multivariate analysis

USDA-ARS?s Scientific Manuscript database

Visible/near-infrared (NIR) spectroscopy has shown potential for successfully classifying broiler breast fillets according to their texture properties. Freshness and shelf life are also important quality characteristics of boneless skinless chicken breast products in the marketplace. This study deal...

Detection of pit fragments in fresh cherries using near infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

NIR spectroscopy in the wavelength region from 900nm to 2600nm was evaluated as the basis for a rapid, non-destructive method for the detection of pits and pit fragments in fresh cherries. Partial Least Squares discriminant analysis (PLS-DA) following various spectral pretreatments was applied to sp...

Complementary analysis of tissue homogenates composition obtained by Vis and NIR laser excitations and Raman spectroscopy.

PubMed

Staniszewska-Slezak, Emilia; Malek, Kamilla; Baranska, Malgorzata

2015-08-05

Raman spectroscopy and four excitation lines in the visible (Vis: 488, 532, 633 nm) and near infrared (NIR: 785 nm) were used for biochemical analysis of rat tissue homogenates, i.e. myocardium, brain, liver, lung, intestine, and kidney. The Vis Raman spectra are very similar for some organs (brain/intestines and kidney/liver) and dominated by heme signals when tissues of lung and myocardium were investigated (especially with 532 nm excitation). On the other hand, the NIR Raman spectra are specific for each tissue and more informative than the corresponding ones collected with the Vis excitations. The spectra analyzed without any special pre-processing clearly illustrate different chemical composition of each tissue and give information about main components e.g. lipids or proteins, but also about the content of some specific compounds such as amino acid residues, nucleotides and nucleobases. However, in order to obtain the whole spectral information about tissues complex composition the spectra of Vis and NIR excitations should be collected and analyzed together. A good agreement of data gathered from Raman spectra of the homogenates and those obtained previously from Raman imaging of the tissue cross-sections indicates that the presented here approach can be a method of choice for an investigation of biochemical variation in animal tissues. Moreover, the Raman spectral profile of tissue homogenates is specific enough to be used for an investigation of potential pathological changes the organism undergoes, in particular when supported by the complementary FTIR spectroscopy. Copyright © 2015 Elsevier B.V. All rights reserved.

Courtney E. Payne | NREL

Science.gov Websites

improved and higher throughput methods for analysis of biomass feedstocks Agronomics-using NIR spectroscopy in-house and external client training. She has also developed improved and high-throughput methods

LED-based near infrared sensor for cancer diagnostics

NASA Astrophysics Data System (ADS)

Bogomolov, Andrey; Ageev, Vladimir; Zabarylo, Urszula; Usenov, Iskander; Schulte, Franziska; Kirsanov, Dmitry; Belikova, Valeria; Minet, Olaf; Feliksberger, E.; Meshkovsky, I.; Artyushenko, Viacheslav

2016-03-01

Optical spectroscopic technologies are increasingly used for cancer diagnostics. Feasibility of differentiation between malignant and healthy samples of human kidney using Fluorescence, Raman, MIR and NIR spectroscopy has been recently reported . In the present work, a simplification of NIR spectroscopy method has been studied. Traditional high-resolution NIR spectrometry was replaced by an optical sensor based on a set of light-emitting diodes at selected wavelengths as light sources and a photodiode. Two prototypes of the sensor have been developed and tested using 14 in-vitro samples of seven kidney tumor patients. Statistical evaluation of results using principal component analysis and partial least-squares discriminant analysis has been performed. Despite only partial discrimination between tumor and healthy tissue achieved by the presented new technique, the results evidence benefits of LED-based near-infrared sensing used for oncological diagnostics. Publisher's Note: This paper, originally published on 4 March, 2016, was replaced with a corrected/revised version on 7 April, 2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.

Non-destructive geographical traceability of sea cucumber (Apostichopus japonicus) using near infrared spectroscopy combined with chemometric methods

PubMed Central

Cai, Rui; Wang, Shisheng; Tang, Bo; Li, Yueqing; Zhao, Weijie

2018-01-01

Sea cucumber is the major tonic seafood worldwide, and geographical origin traceability is an important part of its quality and safety control. In this work, a non-destructive method for origin traceability of sea cucumber (Apostichopus japonicus) from northern China Sea and East China Sea using near infrared spectroscopy (NIRS) and multivariate analysis methods was proposed. Total fat contents of 189 fresh sea cucumber samples were determined and partial least-squares (PLS) regression was used to establish the quantitative NIRS model. The ordered predictor selection algorithm was performed to select feasible wavelength regions for the construction of PLS and identification models. The identification model was developed by principal component analysis combined with Mahalanobis distance and scaling to the first range algorithms. In the test set of the optimum PLS models, the root mean square error of prediction was 0.45, and correlation coefficient was 0.90. The correct classification rates of 100% were obtained in both identification calibration model and test model. The overall results indicated that NIRS method combined with chemometric analysis was a suitable tool for origin traceability and identification of fresh sea cucumber samples from nine origins in China. PMID:29410795

Development, validation and comparison of NIR and Raman methods for the identification and assay of poor-quality oral quinine drops.

PubMed

Mbinze, J K; Sacré, P-Y; Yemoa, A; Mavar Tayey Mbay, J; Habyalimana, V; Kalenda, N; Hubert, Ph; Marini, R D; Ziemons, E

2015-01-01

Poor quality antimalarial drugs are one of the public's major health problems in Africa. The depth of this problem may be explained in part by the lack of effective enforcement and the lack of efficient local drug analysis laboratories. To tackle part of this issue, two spectroscopic methods with the ability to detect and to quantify quinine dihydrochloride in children's oral drops formulations were developed and validated. Raman and near infrared (NIR) spectroscopy were selected for the drug analysis due to their low cost, non-destructive and rapid characteristics. Both of the methods developed were successfully validated using the total error approach in the range of 50-150% of the target concentration (20%W/V) within the 10% acceptance limits. Samples collected on the Congolese pharmaceutical market were analyzed by both techniques to detect potentially substandard drugs. After a comparison of the analytical performance of both methods, it has been decided to implement the method based on NIR spectroscopy to perform the routine analysis of quinine oral drop samples in the Quality Control Laboratory of Drugs at the University of Kinshasa (DRC). Copyright © 2015 Elsevier B.V. All rights reserved.

Non-destructive geographical traceability of sea cucumber (Apostichopus japonicus) using near infrared spectroscopy combined with chemometric methods.

PubMed

Guo, Xiuhan; Cai, Rui; Wang, Shisheng; Tang, Bo; Li, Yueqing; Zhao, Weijie

2018-01-01

Sea cucumber is the major tonic seafood worldwide, and geographical origin traceability is an important part of its quality and safety control. In this work, a non-destructive method for origin traceability of sea cucumber ( Apostichopus japonicus ) from northern China Sea and East China Sea using near infrared spectroscopy (NIRS) and multivariate analysis methods was proposed. Total fat contents of 189 fresh sea cucumber samples were determined and partial least-squares (PLS) regression was used to establish the quantitative NIRS model. The ordered predictor selection algorithm was performed to select feasible wavelength regions for the construction of PLS and identification models. The identification model was developed by principal component analysis combined with Mahalanobis distance and scaling to the first range algorithms. In the test set of the optimum PLS models, the root mean square error of prediction was 0.45, and correlation coefficient was 0.90. The correct classification rates of 100% were obtained in both identification calibration model and test model. The overall results indicated that NIRS method combined with chemometric analysis was a suitable tool for origin traceability and identification of fresh sea cucumber samples from nine origins in China.

Citrus species and hybrids depicted by near- and mid-infrared spectroscopy.

PubMed

Páscoa, Ricardo Nmj; Moreira, Silvana; Lopes, João A; Sousa, Clara

2018-01-31

Citrus trees are among the most cultivated plants in the world, with a high economic impact. The wide sexual compatibility among relatives gave rise to a large number of hybrids that are difficult to discriminate. This work sought to explore the ability of infrared spectroscopy to discriminate among Citrus species and/or hybrids and to contribute to the elucidation of its relatedness. Adult leaves of 18 distinct Citrus plants were included in this work. Near- and mid-infrared (NIR and FTIR) spectra were acquired from leaves after harvesting and a drying period of 1 month. Spectra were modelled by principal component analysis and partial least squares discriminant analysis. Both techniques revealed a high discrimination potential (78.5-95.9%), being the best results achieved with NIR spectroscopy and air-dried leaves (95.9%). Infrared spectroscopy was able to successfully discriminate several Citrus species and/or hybrids. Our results contributed also to enhance insights regarding the studied Citrus species and/or hybrids. Despite the benefit of including additional samples, the results herein obtained clearly pointed infrared spectroscopy as a reliable technique for Citrus species and/or hybrid discrimination. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Recent advances in the use of non-destructive near infrared spectroscopy on intact olive fruits

USDA-ARS?s Scientific Manuscript database

The objective of this review is to illustrate the state of the art in the use of non-destructive near infrared (NIR) spectroscopy for quality evaluation of intact fruit in the olive industry. First, the most recent studies regarding the application of non-destructive NIR spectroscopy methods to asse...

Spatially extended versus frontal cerebral near-infrared spectroscopy during cardiac surgery: a case series identifying potential advantages

NASA Astrophysics Data System (ADS)

Rummel, Christian; Basciani, Reto; Nirkko, Arto; Schroth, Gerhard; Stucki, Monika; Reineke, David; Eberle, Balthasar; Kaiser, Heiko A.

2018-01-01

Stroke due to hypoperfusion or emboli is a devastating adverse event of cardiac surgery, but early detection and treatment could protect patients from an unfavorable postoperative course. Hypoperfusion and emboli can be detected with transcranial Doppler of the middle cerebral artery (MCA). The measured blood flow velocity correlates with cerebral oxygenation determined clinically by near-infrared spectroscopy (NIRS) of the frontal cortex. We tested the potential advantage of a spatially extended NIRS in detecting critical events in three cardiac surgery patients with a whole-head fiber holder of the FOIRE-3000 continuous-wave NIRS system. Principle components analysis was performed to differentiate between global and localized hypoperfusion or ischemic territories of the middle and anterior cerebral arteries. In one patient, we detected a critical hypoperfusion of the right MCA, which was not apparent in the frontal channels but was accompanied by intra- and postoperative neurological correlates of ischemia. We conclude that spatially extended NIRS of temporal and parietal vascular territories could improve the detection of critically low cerebral perfusion. Even in severe hemispheric stroke, NIRS of the frontal lobe may remain normal because the anterior cerebral artery can be supplied by the contralateral side directly or via the anterior communicating artery.

Determination of persimmon leaf chloride contents using near-infrared spectroscopy (NIRS).

PubMed

de Paz, José Miguel; Visconti, Fernando; Chiaravalle, Mara; Quiñones, Ana

2016-05-01

Early diagnosis of specific chloride toxicity in persimmon trees requires the reliable and fast determination of the leaf chloride content, which is usually performed by means of a cumbersome, expensive and time-consuming wet analysis. A methodology has been developed in this study as an alternative to determine chloride in persimmon leaves using near-infrared spectroscopy (NIRS) in combination with multivariate calibration techniques. Based on a training dataset of 134 samples, a predictive model was developed from their NIR spectral data. For modelling, the partial least squares regression (PLSR) method was used. The best model was obtained with the first derivative of the apparent absorbance and using just 10 latent components. In the subsequent external validation carried out with 35 external data this model reached r(2) = 0.93, RMSE = 0.16% and RPD = 3.6, with standard error of 0.026% and bias of -0.05%. From these results, the model based on NIR spectral readings can be used for speeding up the laboratory determination of chloride in persimmon leaves with only a modest loss of precision. The intermolecular interaction between chloride ions and the peptide bonds in leaf proteins through hydrogen bonding, i.e. N-H···Cl, explains the ability for chloride determinations on the basis of NIR spectra.

Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals

NASA Astrophysics Data System (ADS)

Akın, Ata

2017-12-01

A theoretical framework, a partial correlation-based functional connectivity (PC-FC) analysis to functional near-infrared spectroscopy (fNIRS) data, is proposed. This is based on generating a common background signal from a high passed version of fNIRS data averaged over all channels as the regressor in computing the PC between pairs of channels. This approach has been employed to real data collected during a Stroop task. The results show a strong significance in the global efficiency (GE) metric computed by the PC-FC analysis for neutral, congruent, and incongruent stimuli (NS, CS, IcS; GEN=0.10±0.009, GEC=0.11±0.01, GEIC=0.13±0.015, p=0.0073). A positive correlation (r=0.729 and p=0.0259) is observed between the interference of reaction times (incongruent-neutral) and interference of GE values (GEIC-GEN) computed from [HbO] signals.

The estimation of recovery time of calf muscle oxygen saturation during exercise by using functional near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Ansari, M. A.; Shojaeifar, M.; Mohajerani, E.

2014-08-01

Several methods of near infrared spectroscopy such as functional near infrared spectroscopy (fNIRS) and pulse oximetry have been applied for monitoring of tissue oxygenation or arterial oxygen saturation. Some vascular diseases can be diagnosed through measurements of tissue oxygenation. In this study, the temporal variation of oxygenation of calf muscle after exercise is studied by fNIRS. First, the accuracy of a low-cost fNIRS system is studied by measuring the oxygenation of a lipid phantom. Moreover, in-vivo study is performed to evaluate the precision of this system. Then, the variation of muscle oxygenation of four persons during exercise is measured and also the recovery time after walking/running is measured by this fNIRS system.

Variability comparison of simultaneous brain near-infrared spectroscopy (NIRS) and functional MRI (fMRI) during visual stimulation

PubMed Central

Minati, Ludovico; Visani, Elisa; Dowell, Nick G; Medford, Nick; Critchley, Hugo D

2011-01-01

Brain near-infrared spectroscopy (NIRS) is emerging as a potential alternative to functional MRI (fMRI). To date, no study has explicitly compared the two techniques in terms of measurement variability, a key parameter dictating attainable statistical power. Here, NIRS and fMRI were simultaneously recorded during event-related visual stimulation. Inter-subject coefficients of variation (CVs) for peak response amplitude were considerably larger for NIRS than fMRI, but inter-subject CVs for response latency and intra-subject CVs for response amplitude were overall comparable. Our results may represent an optimistic estimate of the CVs of NIRS measurements, as optode positioning was guided by structural MRI, which is normally unavailable. We conclude that fMRI may be preferable to NIRS for group comparisons, but NIRS is equally powerful when comparing conditions within participants. The discrepancy between inter- and intra-subject CVs is likely related to variability in head anatomy and tissue properties which may be better accounted for by emerging NIRS technology. PMID:21780948

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

NASA Astrophysics Data System (ADS)

Schelkanova, Irina; Toronov, Vladislav

2011-07-01

Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

Determination of double bond conversion in dental resins by near infrared spectroscopy.

PubMed

Stansbury, J W; Dickens, S H

2001-01-01

This study determined the validity and practicality of near infrared (NIR) spectroscopic techniques for measurement of conversion in dental resins. Conversion measurements by NIR and mid-IR were compared using two techniques: (1) The conversion of 3mm thick photopolymerized Bis-GMA/TEGDMA resin specimens was determined by transmission NIR. Specimens were then ground and reanalyzed in KBr pellet form by mid-IR. (2) As further verification, thin resin films were photocured and analyzed by mid-IR. Multiple thin films were then compressed into a thick pellet for examination by NIR. Conversion values obtained by NIR and mid-IR techniques did not differ significantly. A correction for changing specimen thickness due to polymerization shrinkage was applied to NIR conversion measurements since an internal standard reference peak was not employed. Sensitivity of the NIR technique was superior to those based on the mid-IR. The nondestructive analysis of conversion in dental resins by NIR offers advantages of convenience, practical specimen dimensions and precision compared with standard mid-IR analytical procedures. Because glass is virtually transparent in the NIR spectrum, this technique has excellent potential for use with filled dental resins as well.

Relationships between NIR spectra and sensory attributes of Thai commercial fish sauces.

PubMed

Ritthiruangdej, Pitiporn; Suwonsichon, Thongchai

2007-07-01

Twenty Thai commercial fish sauces were characterized by sensory descriptive analysis and near-infrared (NIR) spectroscopy. The main objectives were i) to investigate the relationships between sensory attributes and NIR spectra of samples and ii) to characterize the sensory characteristics of fish sauces based on NIR data. A generic descriptive analysis with 12 trained panels was used to characterize the sensory attributes. These attributes consisted of 15 descriptors: brown color, 5 aromatics (sweet, caramelized, fermented, fishy, and musty), 4 tastes (sweet, salty, bitter, and umami), 3 aftertastes (sweet, salty and bitter) and 2 flavors (caramelized and fishy). The results showed that Thai fish sauce samples exhibited significant differences in all of sensory attribute values (p < 0.05). NIR transflectance spectra were obtained from 1100 to 2500 nm. Prior to investigation of the relationships between sensory attributes and NIR spectra, principal component analysis (PCA) was applied to reduce the dimensionality of the spectral data from 622 wavelengths to two uncorrelated components (NIR1 and NIR2) which explained 92 and 7% of the total variation, respectively. NIR1 was highly correlated with the wavelength regions of 1100 - 1544, 1774 - 2062, 2092 - 2308, and 2358 - 2440 nm, while NIR2 was highly correlated with the wavelength regions of 1742 - 1764, 2066 - 2088, and 2312 - 2354 nm. Subsequently, the relationships among these two components and all sensory attributes were also investigated by PCA. The results showed that the first three principal components (PCs) named as fishy flavor component (PC1), sweet component (PC2) and bitterness component (PC3), respectively, explained a total of 66.86% of the variation. NIR1 was mainly correlated to the sensory attributes of fishy aromatic, fishy flavor and sweet aftertaste on PC1. In addition, the PCA using only the factor loadings of NIR1 and NIR2 could be used to classify samples into three groups which showed high, medium and low degrees of fishy aromatic, fishy flavor and sweet aftertaste.

Portable NIR-AOTF spectroscopy combined with winery FTIR spectroscopy for an easy, rapid, in-field monitoring of Sangiovese grape quality.

PubMed

Barnaba, Federico Emanuele; Bellincontro, Andrea; Mencarelli, Fabio

2014-04-01

A near infrared acousto-optically tunable filter (NIR-AOTF) spectrophotometer was tested for three seasons on four different vineyards with the aim of monitoring the ripening evolution of the Italian red wine grape variety Sangiovese. Predictive models for the estimation of several enological parameters were carried out applying the partial least squares chemometric approach. Reference analysis was conducted using Fourier transform infrared spectroscopy (FTIR). Spectral detections were obtained working on whole grape berries. A global set of 96 samples (n = 76 in 2009, and n = 20 in 2010) each one represented by 100 intact grape berries was tested. Finally, in 2011, an external validation on an independent data set of 25 samples (50 grape berries per set) was carried out. Coupling the two spectroscopic applications, the following enological parameters were tested: °Brix, °Babo, total sugars (g L(-1)), glucose (g L(-1)), fructose (g L(-1)), density (g mL(-1)), titratable acidity (g L(-1)), tartaric acid (g L(-1)), pH, malic acid (g L(-1)), gluconic acid (g L(-1)), assumable nitrogen (mg L(-1) ), anthocyanins (mg L(-1)), and total phenols (mg L(-1)). NIR-AOTF spectroscopy was able to predict with a high correlation versus the measured data: °Brix, °Babo, total sugars, glucose, fructose and density. The coefficient of determination (R(2)) and the standard error in prediction were: 0.93 and 0.73 for °Brix; 0.93 and 0.62 for °Babo; 0.94 and 7.39 g L(-1) for total sugars; 0.93 and 5.39 g L(-1) for glucose; 0.92 and 5.07 g L(-1) for fructose; and 0.91 and 0.004 g mL(-1) for density, respectively. Significant correlations were found in prediction for tartaric acid and pH value. Promising validation results were recorded for anthocyanins and total phenols, even though predictive models were affected by the method of sample preparation in compound extraction. This study shows how NIR-AOTF spectroscopy can be used in viticulture to investigate, directly in-field, the most significant markers of ripening evolution and of Sangiovese grape quality definition. The use of the vinery FTIR spectroscopy provided the reduction of the time required by reference analysis, with the big advantage of obtaining many different parameters in just a few seconds and allowing easier calibration of the NIR spectrometer. © 2013 Society of Chemical Industry.

A validated near-infrared spectroscopic method for methanol detection in biodiesel

NASA Astrophysics Data System (ADS)

Paul, Andrea; Bräuer, Bastian; Nieuwenkamp, Gerard; Ent, Hugo; Bremser, Wolfram

2016-06-01

Biodiesel quality control is a relevant issue as biodiesel properties influence diesel engine performance and integrity. Within the European metrology research program (EMRP) ENG09 project ‘Metrology for Biofuels’, an on-line/at-site suitable near-infrared spectroscopy (NIRS) method has been developed in parallel with an improved EN14110 headspace gas chromatography (GC) analysis method for methanol in biodiesel. Both methods have been optimized for a methanol content of 0.2 mass% as this represents the maximum limit of methanol content in FAME according to EN 14214:2009. The NIRS method is based on a mobile NIR spectrometer equipped with a fiber-optic coupled probe. Due to the high volatility of methanol, a tailored air-tight adaptor was constructed to prevent methanol evaporation during measurement. The methanol content of biodiesel was determined from evaluation of NIRS spectra by partial least squares regression (PLS). Both GC analysis and NIRS exhibited a significant dependence on biodiesel feedstock. The NIRS method is applicable to a content range of 0.1% (m/m) to 0.4% (m/m) of methanol with uncertainties at around 6% relative for the different feedstocks. A direct comparison of headspace GC and NIRS for samples of FAMEs yielded that the results of both methods are fully compatible within their stated uncertainties.

Development of NIRS method for quality control of drug combination artesunate–azithromycin for the treatment of severe malaria

PubMed Central

Boyer, Chantal; Gaudin, Karen; Kauss, Tina; Gaubert, Alexandra; Boudis, Abdelhakim; Verschelden, Justine; Franc, Mickaël; Roussille, Julie; Boucher, Jacques; Olliaro, Piero; White, Nicholas J.; Millet, Pascal; Dubost, Jean-Pierre

2012-01-01

Near infrared spectroscopy (NIRS) methods were developed for the determination of analytical content of an antimalarial-antibiotic (artesunate and azithromycin) co-formulation in hard gelatin capsule (HGC). The NIRS consists of pre-processing treatment of spectra (raw spectra and first-derivation of two spectral zones), a unique principal component analysis model to ensure the specificity and then two partial least-squares regression models for the determination content of each active pharmaceutical ingredient. The NIRS methods were developed and validated with no reference method, since the manufacturing process of HGC is basically mixed excipients with active pharmaceutical ingredients. The accuracy profiles showed β-expectation tolerance limits within the acceptance limits (±5%). The analytical control approach performed by reversed phase (HPLC) required two different methods involving two different preparation and chromatographic methods. NIRS offers advantages in terms of lower costs of equipment and procedures, time saving, environmentally friendly. PMID:22579599

[NIR Fingerprints of Different Medicinal Parts of Angelicae Sinensis Radix].

PubMed

Zhang, Ya-ya; Gu, Zhi-rong; Ding, Jun-xia; Wang, Yao-peng; Sun, Yu-jing; Wang, Ya-li

2015-07-01

To investigate the spectrum characteristics of near-intrared dittuse retlectance spectroscopy (NIR) fingerprint of different medicinal parts of Angelicae Sinensis Radix. 96 batches of samples were collected from 14 counties of Gansu Province and Yunnan Province. The NIR fingerprints were collected by integrated sphere. Similarity analysis and partial least square discriminant analysis(PLS-DA) were used to analyze the fingerprint. The average spectrum of NIR fingerprint of different medicinal parts of Angelicae Sinensis Radix showed some differences; the absorbance in characteristic absorption was in a decreasing order of body > tail > head > whole. Most NIR fingerprint similarities of different medicinal parts of Angelicae Sinensis Radix exceeded 0. 95. The established model of PLS-DA could be used to accurately classify the medicinal parts of Angelicae Sinensis Radix. The differences of NIR fingerprints of different medicinal parts of Angelicae Sinensis Radix were mainly existing in the wave number ranges of 8,443 - 8,284 cm -1, 7,003 - 6,896 cm-1, 6,102 - 5,864 cm-1, 4,847 - 4,674 cm-1, and 4,386 - 4,208 cm-1. The different medicinal parts of Angelicae Sinensis Radix have some differences in chemical components.

Review of functional near-infrared spectroscopy in neurorehabilitation

PubMed Central

Mihara, Masahito; Miyai, Ichiro

2016-01-01

Abstract. We provide a brief overview of the research and clinical applications of near-infrared spectroscopy (NIRS) in the neurorehabilitation field. NIRS has several potential advantages and shortcomings as a neuroimaging tool and is suitable for research application in the rehabilitation field. As one of the main applications of NIRS, we discuss its application as a monitoring tool, including investigating the neural mechanism of functional recovery after brain damage and investigating the neural mechanisms for controlling bipedal locomotion and postural balance in humans. In addition to being a monitoring tool, advances in signal processing techniques allow us to use NIRS as a therapeutic tool in this field. With a brief summary of recent studies investigating the clinical application of NIRS using motor imagery task, we discuss the possible clinical usage of NIRS in brain–computer interface and neurofeedback. PMID:27429995

Quantification of betaglucans, lipid and protein contents in whole oat groats (Avena sativa L.) using near infrared reflectance spectroscopy

USDA-ARS?s Scientific Manuscript database

Whole oat has been described as an important healthy food for humans due to its beneficial nutritional components. Near infrared reflectance spectroscopy (NIRS) is a powerful, fast, accurate and non-destructive analytical tool that can be substituted for some traditional chemical analysis. A total o...

Application of near-infrared spectroscopy to preservative-treated wood

Treesearch

Chi-Leung So; Stan T. Lebow; Thomas L. Eberhardt; Leslie H. Groom; Todd F. Shupe

2009-01-01

Near infrared (NIR) spectroscopy is now a widely-used technique in the field of forest products, especially for physical and mechanical property determinations. This technique is also ideal for the chemical analysis of wood. There has been a growing need to find a rapid, inexpensive and reliable method to distinguish between preservative-treated and untreated waste...

Multivariate analysis of nystatin and metronidazole in a semi-solid matrix by means of diffuse reflectance NIR spectroscopy and PLS regression.

PubMed

Baratieri, Sabrina C; Barbosa, Juliana M; Freitas, Matheus P; Martins, José A

2006-01-23

A multivariate method of analysis of nystatin and metronidazole in a semi-solid matrix, based on diffuse reflectance NIR measurements and partial least squares regression, is reported. The product, a vaginal cream used in the antifungal and antibacterial treatment, is usually, quantitatively analyzed through microbiological tests (nystatin) and HPLC technique (metronidazole), according to pharmacopeial procedures. However, near infrared spectroscopy has demonstrated to be a valuable tool for content determination, given the rapidity and scope of the method. In the present study, it was successfully applied in the prediction of nystatin (even in low concentrations, ca. 0.3-0.4%, w/w, which is around 100,000 IU/5g) and metronidazole contents, as demonstrated by some figures of merit, namely linearity, precision (mean and repeatability) and accuracy.

A quick method based on SIMPLISMA-KPLS for simultaneously selecting outlier samples and informative samples for model standardization in near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Li, Li-Na; Ma, Chang-Ming; Chang, Ming; Zhang, Ren-Cheng

2017-12-01

A novel method based on SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) and Kernel Partial Least Square (KPLS), named as SIMPLISMA-KPLS, is proposed in this paper for selection of outlier samples and informative samples simultaneously. It is a quick algorithm used to model standardization (or named as model transfer) in near infrared (NIR) spectroscopy. The NIR experiment data of the corn for analysis of the protein content is introduced to evaluate the proposed method. Piecewise direct standardization (PDS) is employed in model transfer. And the comparison of SIMPLISMA-PDS-KPLS and KS-PDS-KPLS is given in this research by discussion of the prediction accuracy of protein content and calculation speed of each algorithm. The conclusions include that SIMPLISMA-KPLS can be utilized as an alternative sample selection method for model transfer. Although it has similar accuracy to Kennard-Stone (KS), it is different from KS as it employs concentration information in selection program. This means that it ensures analyte information is involved in analysis, and the spectra (X) of the selected samples is interrelated with concentration (y). And it can be used for outlier sample elimination simultaneously by validation of calibration. According to the statistical data results of running time, it is clear that the sample selection process is more rapid when using KPLS. The quick algorithm of SIMPLISMA-KPLS is beneficial to improve the speed of online measurement using NIR spectroscopy.

Near infrared spectroscopy and chemometrics analysis of complex traits in animal physiology

USDA-ARS?s Scientific Manuscript database

Near infrared reflectance (NIR) applications have been expanding from the traditional framework of small molecule chemical purity and composition (as defined by spectral libraries) to complex system analysis and holistic exploratory approaches to questions in biochemistry, biophysics and environment...

Application of NIR spectroscopy in the assessment of diabetic foot disorders

NASA Astrophysics Data System (ADS)

Schleicher, Eckhard; Hampel, Uwe; Freyer, Richard

2001-10-01

Diabetic foot syndrome (DFS) is a common sequel of long-term diabetes mellitus. There is a urgent need of noninvasive, objective and quantitative diagnostic tools to assess tissue viability and perfusion for a successful therapy. NIR spectroscopy seems to be qualified to measure local capillary hemoglobin saturation of the outer extremities in patients with progressive diabetic disorders. We investigate how NIR spectroscopy can be applied to the assessment of diabetic foot problems such as neuropathy and angiopathy. Thereby we use spatially resolved spectroscopy in conjunction with a specially developed continuous-wave laser spectrometer. Comparison of intra- and interindividual measurements is expected to yield quantitative measures of local tissue viability which is a prerequisite for a successful therapy.

Dissolution testing of isoniazid, rifampicin, pyrazinamide and ethambutol tablets using near-infrared spectroscopy (NIRS) and multivariate calibration.

PubMed

de Oliveira Neves, Ana Carolina; Soares, Gustavo Mesquita; de Morais, Stéphanie Cavalcante; da Costa, Fernanda Saadna Lopes; Porto, Dayanne Lopes; de Lima, Kássio Michell Gomes

2012-01-05

This work utilized the near-infrared spectroscopy (NIRS) and multivariate calibration to measure the percentage drug dissolution of four active pharmaceutical ingredients (APIs) (isoniazid, rifampicin, pyrazinamide and ethambutol) in finished pharmaceutical products produced in the Federal University of Rio Grande do Norte (Brazil). The conventional analytical method employed in quality control tests of the dissolution by the pharmaceutical industry is high-performance liquid chromatography (HPLC). The NIRS is a reliable method that offers important advantages for the large-scale production of tablets and for non-destructive analysis. NIR spectra of 38 samples (in triplicate) were measured using a Bomen FT-NIR 160 MB in the range 1100-2500nm. Each spectrum was the average of 50 scans obtained in the diffuse reflectance mode. The dissolution test, which was initially carried out in 900mL of 0.1N hydrochloric acid at 37±0.5°C, was used to determine the percentage a drug that dissolved from each tablet measured at the same time interval (45min) at pH 6.8. The measurement of the four API was performed by HPLC (Shimadzu, Japan) in the gradiente mode. The influence of various spectral pretreatments (Savitzky-Golay smoothing, Multiplicative Scatter Correction (MSC), and Savitzky-Golay derivatives) and multivariate analysis using the partial least squares (PLS) regression algorithm was calculated by the Unscrambler 9.8 (Camo) software. The correlation coefficient (R(2)) for the HPLC determination versus predicted values (NIRS) ranged from 0.88 to 0.98. The root-mean-square error of prediction (RMSEP) obtained from PLS models were 9.99%, 8.63%, 8.57% and 9.97% for isoniazid, rifampicin, ethambutol and pyrazinamide, respectively, indicating that the NIR method is an effective and non-destructive tool for measurement of drug dissolution from tablets. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Patent foramen ovale detected by near-infrared spectroscopy in patients suffering from migraine with aura.

PubMed

Liboni, William; Molinari, Filippo; Allais, Giovanni Battista; Mana, Ornella; Negri, Emanuela; D'Andrea, Giovanni; Bussone, Gennaro; Benedetto, Chiara

2008-05-01

There is an increased prevalence of patent foramen ovale (PFO) in women with migraine with aura (MwA) compared to controls, but the role of PFO in triggering aura is still debated. The aim of this study was to test a group of women suffering from MwA with near-infrared spectroscopy (NIRS), to assess the NIRS capability of discriminating between subjects with and without PFO. Eighty-eight MwA patients (mean age 37.4+/-10.7 years, range 16-62 years) underwent NIRS measurement of the cerebral variations of the oxygenated (O2Hb) and reduced haemoglobin (HHb) during breath-holding. The prevalence of O2Hb vs. HHb was used to assess the presence of PFO. As a gold standard, the presence of PFO was assessed by transcranial Doppler sonography (TCD). At the TCD analysis 48 patients (55%) showed PFOs, 32 of which were permanent. NIRS correctly detected 36 subjects out of 40 without PFO, and 38 subjects out of 48 having PFO: sensitivity was 79%; specificity was 90%. All the false negatives were permanent shunts. MwA patients with PFO showed a delayed increase in the O2Hb concentration and a reduced oxygenation with respect to subjects without PFO. NIRS is effective in identifying the presence of PFO in a MwA population, but TCD achieves better diagnostic performances. The NIRS provides additional information about the cerebral vasoreactivity and highlights substantial differences between patients with latent and permanent shunts that warrant further studies.

Near-Infrared Spectroscopy Assay of Key Quality-Indicative Ingredients of Tongkang Tablets.

PubMed

Pan, Wenjie; Ma, Jinfang; Xiao, Xue; Huang, Zhengwei; Zhou, Huanbin; Ge, Fahuan; Pan, Xin

2017-04-01

The objective of this paper is to develop an easy and fast near-infrared spectroscopy (NIRS) assay for the four key quality-indicative active ingredients of Tongkang tablets by comparing the true content of the active ingredients measured by high performance liquid chromatography (HPLC) and the NIRS data. The HPLC values for the active ingredients content of Cimicifuga glycoside, calycosin glucoside, 5-O-methylvisamminol and hesperidin in Tongkang tablets were set as reference values. The NIRS raw spectra of Tongkang tablets were processed using first-order convolution method. The iterative optimization method was chosen to optimize the band for Cimicifuga glycoside and 5-O-methylvisamminol, and correlation coefficient method was used to determine the optimal band of calycosin glucoside and hesperidin. A near-infrared quantitative calibration model was established for each quality-indicative ingredient by partial least-squares method on the basis of the contents detected by HPLC and the obtained NIRS spectra. The correlation coefficient R 2 values of the four models of Cimicifuga glycoside, calycosin glucoside, 5-O-methylvisamminol and hesperidin were 0.9025, 0.8582, 0.9250, and 0.9325, respectively. It was demonstrated that the accuracy of the validation values was approximately 90% by comparison of the predicted results from NIRS models and the HPLC true values, which suggested that NIRS assay was successfully established and validated. It was expected that the quantitative analysis models of the four indicative ingredients could be used to rapidly perform quality control in industrial production of Tongkang tablets.

Authenticity identification and classification of Rhodiola species in traditional Tibetan medicine based on Fourier transform near-infrared spectroscopy and chemometrics analysis.

PubMed

Li, Tao; Su, Chen

2018-06-02

Rhodiola is an increasingly widely used traditional Tibetan medicine and traditional Chinese medicine in China. The composition profiles of bioactive compounds are somewhat jagged according to different species, which makes it crucial to identify authentic Rhodiola species accurately so as to ensure clinical application of Rhodiola. In this paper, a nondestructive, rapid, and efficient method in classification of Rhodiola was developed by Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics analysis. A total of 160 batches of raw spectra were obtained from four different species of Rhodiola by FT-NIR, such as Rhodiola crenulata, Rhodiola fastigiata, Rhodiola kirilowii, and Rhodiola brevipetiolata. After excluding the outliers, different performances of 3 sample dividing methods, 12 spectral preprocessing methods, 2 wavelength selection methods, and 2 modeling evaluation methods were compared. The results indicated that this combination was superior than others in the authenticity identification analysis, which was FT-NIR combined with sample set partitioning based on joint x-y distances (SPXY), standard normal variate transformation (SNV) + Norris-Williams (NW) + 2nd derivative, competitive adaptive reweighted sampling (CARS), and kernel extreme learning machine (KELM). The accuracy (ACCU), sensitivity (SENS), and specificity (SPEC) of the optimal model were all 1, which showed that this combination of FT-NIR and chemometrics methods had the optimal authenticity identification performance. The classification performance of the partial least squares discriminant analysis (PLS-DA) model was slightly lower than KELM model, and PLS-DA model results were ACCU = 0.97, SENS = 0.93, and SPEC = 0.98, respectively. It can be concluded that FT-NIR combined with chemometrics analysis has great potential in authenticity identification and classification of Rhodiola, which can provide a valuable reference for the safety and effectiveness of clinical application of Rhodiola. Copyright © 2018 Elsevier B.V. All rights reserved.

Feasibility of field portable near infrared (NIR) spectroscopy to determine cyanide concentrations in soil

NASA Astrophysics Data System (ADS)

Sut, Magdalena; Fischer, Thomas; Repmann, Frank; Raab, Thomas

2013-04-01

In Germany, at more than 1000 sites, soil is polluted with an anthropogenic contaminant in form of iron-cyanide complexes. These contaminations are caused by former Manufactured Gas Plants (MGPs), where electricity for lighting was produced in the process of coal gasification. The production of manufactured gas was restrained in 1950, which caused cessation of MGPs. Our study describes the application of Polychromix Handheld Field Portable Near-Infrared (NIR) Analyzer to predict the cyanide concentrations in soil. In recent times, when the soil remediation is of major importance, there is a need to develop rapid and non-destructive methods for contaminant determination in the field. In situ analysis enables determination of 'hot spots', is cheap and time saving in comparison to laboratory methods. This paper presents a novel usage of NIR spectroscopy, where a calibration model was developed, using multivariate calibration algorithms, in order to determine NIR spectral response to the cyanide concentration in soil samples. As a control, the contaminant concentration was determined using conventional Flow Injection Analysis (FIA). The experiments revealed that portable near-infrared spectrometers could be a reliable device for identification of contamination 'hot spots', where cyanide concentration are higher than 2400 mg kg-1 in the field and >1750 mg kg-1 after sample preparation in the laboratory, but cannot replace traditional laboratory analyses due to high limits of detection.

Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study.

PubMed

Catelani, Tiago A; Santos, João Rodrigo; Páscoa, Ricardo N M J; Pezza, Leonardo; Pezza, Helena R; Lopes, João A

2018-03-01

This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T 2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time. Copyright © 2017 Elsevier B.V. All rights reserved.

Use of near-infrared spectroscopy and multipoint measurements for quality control of pharmaceutical drug products.

PubMed

Boiret, Mathieu; Chauchard, Fabien

2017-01-01

Near-infrared (NIR) spectroscopy is a non-destructive analytical technique that enables better-understanding and optimization of pharmaceutical processes and final drug products. The use in line is often limited by acquisition speed and sampling area. This work focuses on performing a multipoint measurement at high acquisition speed at the end of the manufacturing process on a conveyor belt system to control both the distribution and the content of active pharmaceutical ingredient within final drug products, i.e., tablets. A specially designed probe with several collection fibers was developed for this study. By measuring spectral and spatial information, it provides physical and chemical knowledge on the final drug product. The NIR probe was installed on a conveyor belt system that enables the analysis of a lot of tablets. The use of these NIR multipoint measurement probes on a conveyor belt system provided an innovative method that has the potential to be used as a new paradigm to ensure the drug product quality at the end of the manufacturing process and as a new analytical method for the real-time release control strategy. Graphical abstract Use of near-infrared spectroscopy and multipoint measurements for quality control of pharmaceutical drug products.

Near infrared (NIR) spectroscopy for in-line monitoring of polymer extrusion processes.

PubMed

Rohe, T; Becker, W; Kölle, S; Eisenreich, N; Eyerer, P

1999-09-13

In recent years, near infrared (NIR) spectroscopy has become an analytical tool frequently used in many chemical production processes. In particular, on-line measurements are of interest to increase process stability and to document constant product quality. Application to polymer processing e.g. polymer extrusion, could even increase product quality. Interesting parameters are composition of the processed polymer, moisture, or reaction status in reactive extrusion. For this issue a transmission sensor was developed for application of NIR spectroscopy to extrusion processes. This sensor includes fibre optic probes and a measuring cell to be adapted to various extruders for in-line measurements. In contrast to infrared sensors, it only uses optical quartz components. Extrusion processes at temperatures up to 300 degrees C and pressures up to 37 MPa have been investigated. Application of multivariate data analysis (e.g. partial least squares, PLS) demonstrated the performance of the system with respect to process monitoring: in the case of polymer blending, deviations between predicted and actual polymer composition were quite low (in the range of +/-0.25%). So the complete system is suitable for harsh industrial environments and could lead to improved polymer extrusion processes.

Hydrogen/deuterium (H/D) exchange of gelatinized starch studied by two-dimensional (2D) near-infrared (NIR) correlation spectroscopy

NASA Astrophysics Data System (ADS)

Shinzawa, Hideyuki; Mizukado, Junji

2018-05-01

Hydrogen/deuterium (H/D) exchange of gelatinized starch was probed by in-situ near-infrared (NIR) monitoring coupled with two-dimensional (2D) correlation spectroscopy. Gelatinized starch undergoes spontaneous H/D exchange in D2O. During the substitution, the exchange rate essentially becomes different depending on solvent accessibility of various parts of the molecule. Thus, by analyzing the change in the NIR feature observed during the substitution, it becomes possible to sort out local structure and dynamics of the system. 2D correlation analysis of the time-dependent NIR spectra reveals the presence of different local structure of the starch, each having different solvent accessibility. For example, during the H/D exchange, the D2O is first absorbed by starch molecules especially around the surface area between the starch and water, where the water molecules are weakly interacted with the starch molecules. This absorption is quickly followed by the development of HDO species. Further absorption of the D2O results in the penetration of the molecules inside the starch and eventually develops the relatively strong interaction between the HDO and starch molecules because of the presence of dominant starch molecules.

[Prediction of the side-cut product yield of atmospheric/vacuum distillation unit by NIR crude oil rapid assay].

PubMed

Wang, Yan-Bin; Hu, Yu-Zhong; Li, Wen-Le; Zhang, Wei-Song; Zhou, Feng; Luo, Zhi

2014-10-01

In the present paper, based on the fast evaluation technique of near infrared, a method to predict the yield of atmos- pheric and vacuum line was developed, combined with H/CAMS software. Firstly, the near-infrared (NIR) spectroscopy method for rapidly determining the true boiling point of crude oil was developed. With commercially available crude oil spectroscopy da- tabase and experiments test from Guangxi Petrochemical Company, calibration model was established and a topological method was used as the calibration. The model can be employed to predict the true boiling point of crude oil. Secondly, the true boiling point based on NIR rapid assay was converted to the side-cut product yield of atmospheric/vacuum distillation unit by H/CAMS software. The predicted yield and the actual yield of distillation product for naphtha, diesel, wax and residual oil were compared in a 7-month period. The result showed that the NIR rapid crude assay can predict the side-cut product yield accurately. The near infrared analytic method for predicting yield has the advantages of fast analysis, reliable results, and being easy to online operate, and it can provide elementary data for refinery planning optimization and crude oil blending.

Development of a near-infrared spectroscopy method (NIRS) for fast analysis of total, indolic, aliphatic and individual glucosinolates in new bred open pollinating genotypes of broccoli (Brassica oleracea convar. botrytis var. italica).

PubMed

Sahamishirazi, Samira; Zikeli, Sabine; Fleck, Michael; Claupein, Wilhelm; Graeff-Hoenninger, Simone

2017-10-01

This study describes the development of near-infrared spectroscopy (NIRS) calibration to determine individual and total glucosinolates (GSLs) content of 12 new-bred open-pollinating genotypes of broccoli (Brassica oleracea convar. botrytis var. italica). Six individual GSLs were identified using high-performance-liquid chromatography (HPLC). The NIRS calibration was established based on modified partial least squares regression with reference values of HPLC. The calibration was analyzed using coefficient of determination in prediction (R 2 ) and ratio of preference of determination (RPD). Large variation occurred in the calibrations, R 2 and RPD due to the variability of the samples. Derived calibrations for total-GSLs, aliphatic-GSLs, glucoraphanin and 4-methoxyglucobrassicin were quantitative with a high accuracy (RPD=1.36, 1.65, 1.63, 1.11) while, for indole-GSLs, glucosinigrin, glucoiberin, glucobrassicin and 1-methoxyglucobrassicin were more qualitative (RPD=0.95, 0.62, 0.67, 0.81, 0.56). Overall, the results indicated NIRS has a good potential to determine different GSLs in a large sample pool of broccoli quantitatively and qualitatively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of near infrared spectroscopy (NIRS) to non-destructive internal quality inspection of tomatoes

NASA Astrophysics Data System (ADS)

Tao, Xuemei; He, Yong

2006-09-01

The internal quality of tomato such as acidity and sugar content is important to its taste thus influences the market. The objective of this paper was to demonstrate the feasibility of using a near-infrared spectroscopy (NIRS) to investigate the relationship between sugar content and acidity of tomato and absorption spectra. The N1RS reflectance of nondestructive tomatoes was measured with a Visible/NJR spectrophotometer in 325-1075 nm range. The sugar content and acidity of tomato were obtained with a handhold sugar content meter and a PH meter. The reflectance data set was recorded and analyzed with some mathematic methods. The PLS (Partial least squares) calibration method was developed for converting the NIRS reflectance of tomato into the data which determined the acidity value. BP (Back propagation) neural network was used to set up the relationship between the NIRS reflectance of tomato and sugar content. The acidity values were detected with an accuracy of 9O% and the sugar contents determined by the BP network were also very close to the measurements (coefficient of correlation r2=0.8764). NW spectra analysis would be very useful in the nondestructive internal quality inspecting of tomato.

[Determination of wine original regions using information fusion of NIR and MIR spectroscopy].

PubMed

Xiang, Ling-Li; Li, Meng-Hua; Li, Jing-Mingz; Li, Jun-Hui; Zhang, Lu-Da; Zhao, Long-Lian

2014-10-01

Geographical origins of wine grapes are significant factors affecting wine quality and wine prices. Tasters' evaluation is a good method but has some limitations. It is important to discriminate different wine original regions quickly and accurately. The present paper proposed a method to determine wine original regions based on Bayesian information fusion that fused near-infrared (NIR) transmission spectra information and mid-infrared (MIR) ATR spectra information of wines. This method improved the determination results by expanding the sources of analysis information. NIR spectra and MIR spectra of 153 wine samples from four different regions of grape growing were collected by near-infrared and mid-infrared Fourier transform spe trometer separately. These four different regions are Huailai, Yantai, Gansu and Changli, which areall typical geographical originals for Chinese wines. NIR and MIR discriminant models for wine regions were established using partial least squares discriminant analysis (PLS-DA) based on NIR spectra and MIR spectra separately. In PLS-DA, the regions of wine samples are presented in group of binary code. There are four wine regions in this paper, thereby using four nodes standing for categorical variables. The output nodes values for each sample in NIR and MIR models were normalized first. These values stand for the probabilities of each sample belonging to each category. They seemed as the input to the Bayesian discriminant formula as a priori probability value. The probabilities were substituteed into the Bayesian formula to get posterior probabilities, by which we can judge the new class characteristics of these samples. Considering the stability of PLS-DA models, all the wine samples were divided into calibration sets and validation sets randomly for ten times. The results of NIR and MIR discriminant models of four wine regions were as follows: the average accuracy rates of calibration sets were 78.21% (NIR) and 82.57% (MIR), and the average accuracy rates of validation sets were 82.50% (NIR) and 81.98% (MIR). After using the method proposed in this paper, the accuracy rates of calibration and validation changed to 87.11% and 90.87% separately, which all achieved better results of determination than individual spectroscopy. These results suggest that Bayesian information fusion of NIR and MIR spectra is feasible for fast identification of wine original regions.

Predicting cotton stelometer fiber strength by fourier transform infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

The strength of cotton fibers is one of several important end-use characteristics. In routine programs, it has been mostly assessed by automation-oriented high volume instrument (HVI) system. An alternative method for cotton strength is near infrared (NIR) spectroscopy. Although previous NIR models ...

Spectral fiber sensors for cancer diagnostics in vitro

NASA Astrophysics Data System (ADS)

Artyushenko, V.; Schulte, F.; Zabarylo, U.; Berlien, H.-P.; Usenov, I.; Saeb Gilani, T.; Eichler, H.; Pieszczek, Ł.; Bogomolov, A.; Krause, H.; Minet, O.

2015-07-01

Cancer is one of the leading causes for morbidity and mortality worldwide. Therefore, efforts are concentrated on cancer detection in an early stage to enhance survival rates for cancer patients. A certain intraoperative navigation in the tumor border zone is also an essential task to lower the mortality rate after surgical treatment. Molecular spectroscopy methods proved to be powerful tools to differentiate cancerous and healthy tissue. Within our project comparison of different vibration spectroscopy methods were tested to select the better one or to reach synergy from their combination. One key aspect was in special fiber probe development for each technique. Using fiber optic probes in Raman, MIR and NIR spectroscopy is a very powerful method for non-invasive in vivo applications. Miniaturization of Raman probes was achieved by deposition of dielectric filters directly onto the silica fiber end surfaces. Raman, NIR and MIR spectroscopy were used to analyze samples from kidney tumors. The differentiation between cancer and healthy samples was successfully obtained by multivariate data analysis.

Rapid and Accurate Evaluation of the Quality of Commercial Organic Fertilizers Using Near Infrared Spectroscopy

PubMed Central

Wang, Chang; Huang, Chichao; Qian, Jian; Xiao, Jian; Li, Huan; Wen, Yongli; He, Xinhua; Ran, Wei; Shen, Qirong; Yu, Guanghui

2014-01-01

The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers. PMID:24586313

Rapid and accurate evaluation of the quality of commercial organic fertilizers using near infrared spectroscopy.

PubMed

Wang, Chang; Huang, Chichao; Qian, Jian; Xiao, Jian; Li, Huan; Wen, Yongli; He, Xinhua; Ran, Wei; Shen, Qirong; Yu, Guanghui

2014-01-01

The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers.

Identification of coffee leaves using FT-NIR spectroscopy and SIMCA.

PubMed

Mees, Corenthin; Souard, Florence; Delporte, Cedric; Deconinck, Eric; Stoffelen, Piet; Stévigny, Caroline; Kauffmann, Jean-Michel; De Braekeleer, Kris

2018-01-15

Abundant literature has been devoted to coffee beans (green or roasted) chemical description but relatively few studies have been devoted to coffee leaves. Given the fact that coffee leaves are used for food and medicinal consumption, it was of interest to develop a rapid screening method in order to identify coffee leaves taxa. Investigation by Fourier - Transform near infrared spectroscopy (FT-NIRS) was performed on nine Coffea taxa leaves harvested over one year in a tropical greenhouse of the Botanic Garden Meise (Belgium). The only process after leaves harvesting was an effective drying and a homogeneous leaves grinding. FT-NIRS with SIMCA analysis allowed to discriminate the spectral profiles across taxon, aging stage (mature and senescence coffee leaves) and harvest period. This study showed that it was possible (i) to classify the different taxa, (ii) to identify their aging stage and (iii) to identify the harvest period for the mature stage with a correct classification rate of 99%, 100% and 90%, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

Radial basis function neural networks in non-destructive determination of compound aspirin tablets on NIR spectroscopy.

PubMed

Dou, Ying; Mi, Hong; Zhao, Lingzhi; Ren, Yuqiu; Ren, Yulin

2006-09-01

The application of the second most popular artificial neural networks (ANNs), namely, the radial basis function (RBF) networks, has been developed for quantitative analysis of drugs during the last decade. In this paper, the two components (aspirin and phenacetin) were simultaneously determined in compound aspirin tablets by using near-infrared (NIR) spectroscopy and RBF networks. The total database was randomly divided into a training set (50) and a testing set (17). Different preprocessing methods (standard normal variate (SNV), multiplicative scatter correction (MSC), first-derivative and second-derivative) were applied to two sets of NIR spectra of compound aspirin tablets with different concentrations of two active components and compared each other. After that, the performance of RBF learning algorithm adopted the nearest neighbor clustering algorithm (NNCA) and the criterion for selection used a cross-validation technique. Results show that using RBF networks to quantificationally analyze tablets is reliable, and the best RBF model was obtained by first-derivative spectra.

Brain-machine interfaces for assistive smart homes: A feasibility study with wearable near-infrared spectroscopy.

PubMed

Ogawa, Takeshi; Hirayama, Jun-Ichiro; Gupta, Pankaj; Moriya, Hiroki; Yamaguchi, Shumpei; Ishikawa, Akihiro; Inoue, Yoshihiro; Kawanabe, Motoaki; Ishii, Shin

2015-08-01

Smart houses for elderly or physically challenged people need a method to understand residents' intentions during their daily-living behaviors. To explore a new possibility, we here developed a novel brain-machine interface (BMI) system integrated with an experimental smart house, based on a prototype of a wearable near-infrared spectroscopy (NIRS) device, and verified the system in a specific task of controlling of the house's equipments with BMI. We recorded NIRS signals of three participants during typical daily-living actions (DLAs), and classified them by linear support vector machine. In our off-line analysis, four DLAs were classified at about 70% mean accuracy, significantly above the chance level of 25%, in every participant. In an online demonstration in the real smart house, one participant successfully controlled three target appliances by BMI at 81.3% accuracy. Thus we successfully demonstrated the feasibility of using NIRS-BMI in real smart houses, which will possibly enhance new assistive smart-home technologies.

Evaluation of light detector surface area for functional Near Infrared Spectroscopy.

PubMed

Wang, Lei; Ayaz, Hasan; Izzetoglu, Meltem; Onaral, Banu

2017-10-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neuroimaging technique that utilizes near infrared light to detect cortical concentration changes of oxy-hemoglobin and deoxy-hemoglobin non-invasively. Using light sources and detectors over the scalp, multi-wavelength light intensities are recorded as time series and converted to concentration changes of hemoglobin via modified Beer-Lambert law. Here, we describe a potential source for systematic error in the calculation of hemoglobin changes and light intensity measurements. Previous system characterization and analysis studies looked into various fNIRS parameters such as type of light source, number and selection of wavelengths, distance between light source and detector. In this study, we have analyzed the contribution of light detector surface area to the overall outcome. Results from Monte Carlo based digital phantoms indicated that selection of detector area is a critical system parameter in minimizing the error in concentration calculations. The findings here can guide the design of future fNIRS sensors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Near-Infrared Spectroscopy as an Analytical Process Technology for the On-Line Quantification of Water Precipitation Processes during Danhong Injection.

PubMed

Liu, Xuesong; Wu, Chunyan; Geng, Shu; Jin, Ye; Luan, Lianjun; Chen, Yong; Wu, Yongjiang

2015-01-01

This paper used near-infrared (NIR) spectroscopy for the on-line quantitative monitoring of water precipitation during Danhong injection. For these NIR measurements, two fiber optic probes designed to transmit NIR radiation through a 2 mm flow cell were used to collect spectra in real-time. Partial least squares regression (PLSR) was developed as the preferred chemometrics quantitative analysis of the critical intermediate qualities: the danshensu (DSS, (R)-3, 4-dihydroxyphenyllactic acid), protocatechuic aldehyde (PA), rosmarinic acid (RA), and salvianolic acid B (SAB) concentrations. Optimized PLSR models were successfully built and used for on-line detecting of the concentrations of DSS, PA, RA, and SAB of water precipitation during Danhong injection. Besides, the information of DSS, PA, RA, and SAB concentrations would be instantly fed back to site technical personnel for control and adjustment timely. The verification experiments determined that the predicted values agreed with the actual homologic value.

Near-infrared spectroscopy monitoring and control of the fluidized bed granulation and coating processes-A review.

PubMed

Liu, Ronghua; Li, Lian; Yin, Wenping; Xu, Dongbo; Zang, Hengchang

2017-09-15

The fluidized bed granulation and pellets coating technologies are widely used in pharmaceutical industry, because the particles made in a fluidized bed have good flowability, compressibility, and the coating thickness of pellets are homogeneous. With the popularization of process analytical technology (PAT), real-time analysis for critical quality attributes (CQA) was getting more attention. Near-infrared (NIR) spectroscopy, as a PAT tool, could realize the real-time monitoring and control during the granulating and coating processes, which could optimize the manufacturing processes. This article reviewed the application of NIR spectroscopy in CQA (moisture content, particle size and tablet/pellet thickness) monitoring during fluidized bed granulation and coating processes. Through this review, we would like to provide references for realizing automated control and intelligent production in fluidized bed granulation and pellets coating of pharmaceutical industry. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition.

PubMed

Basati, Zahra; Jamshidi, Bahareh; Rasekh, Mansour; Abbaspour-Gilandeh, Yousef

2018-05-30

The presence of sunn pest-damaged grains in wheat mass reduces the quality of flour and bread produced from it. Therefore, it is essential to assess the quality of the samples in collecting and storage centers of wheat and flour mills. In this research, the capability of visible/near-infrared (Vis/NIR) spectroscopy combined with pattern recognition methods was investigated for discrimination of wheat samples with different percentages of sunn pest-damaged. To this end, various samples belonging to five classes (healthy and 5%, 10%, 15% and 20% unhealthy) were analyzed using Vis/NIR spectroscopy (wavelength range of 350-1000 nm) based on both supervised and unsupervised pattern recognition methods. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) as the unsupervised techniques and soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) as supervised methods were used. The results showed that Vis/NIR spectra of healthy samples were correctly clustered using both PCA and HCA. Due to the high overlapping between the four unhealthy classes (5%, 10%, 15% and 20%), it was not possible to discriminate all the unhealthy samples in individual classes. However, when considering only the two main categories of healthy and unhealthy, an acceptable degree of separation between the classes can be obtained after classification with supervised pattern recognition methods of SIMCA and PLS-DA. SIMCA based on PCA modeling correctly classified samples in two classes of healthy and unhealthy with classification accuracy of 100%. Moreover, the power of the wavelengths of 839 nm, 918 nm and 995 nm were more than other wavelengths to discriminate two classes of healthy and unhealthy. It was also concluded that PLS-DA provides excellent classification results of healthy and unhealthy samples (R 2  = 0.973 and RMSECV = 0.057). Therefore, Vis/NIR spectroscopy based on pattern recognition techniques can be useful for rapid distinguishing the healthy wheat samples from those damaged by sunn pest in the maintenance and processing centers. Copyright © 2018 Elsevier B.V. All rights reserved.

Near Infra-Red Spectroscopy to Reduce Prophylactic Fasciotomies for and Missed Cases of Acute Compartment Syndrome in Soldiers Injured in OEF/OIF

DTIC Science & Technology

2013-10-01

demonstrated that NIRS measurement of hemoglobin oxygen saturation in the tibial compartment provided reliable and sensitive correlation to increases...on 60 healthy participants. Our results indicated that NIRS was able to detect changes in oxygen saturation of muscle with exercise in all 60...Model 41 Introduction 42 Over the last two decades, tissue oxygenation saturation (StO2) measured by near infrared 43 spectroscopy (NIRS) has

A Proof of Concept Study of Function-Based Statistical Analysis of fNIRS Data: Syntax Comprehension in Children with Specific Language Impairment Compared to Typically-Developing Controls.

PubMed

Fu, Guifang; Wan, Nicholas J A; Baker, Joseph M; Montgomery, James W; Evans, Julia L; Gillam, Ronald B

2016-01-01

Functional near infrared spectroscopy (fNIRS) is a neuroimaging technology that enables investigators to indirectly monitor brain activity in vivo through relative changes in the concentration of oxygenated and deoxygenated hemoglobin. One of the key features of fNIRS is its superior temporal resolution, with dense measurements over very short periods of time (100 ms increments). Unfortunately, most statistical analysis approaches in the existing literature have not fully utilized the high temporal resolution of fNIRS. For example, many analysis procedures are based on linearity assumptions that only extract partial information, thereby neglecting the overall dynamic trends in fNIRS trajectories. The main goal of this article is to assess the ability of a functional data analysis (FDA) approach for detecting significant differences in hemodynamic responses recorded by fNIRS. Children with and without SLI wore two, 3 × 5 fNIRS caps situated over the bilateral parasylvian areas as they completed a language comprehension task. FDA was used to decompose the high dimensional hemodynamic curves into the mean function and a few eigenfunctions to represent the overall trend and variation structures over time. Compared to the most popular GLM, we did not assume any parametric structure and let the data speak for itself. This analysis identified significant differences between the case and control groups in the oxygenated hemodynamic mean trends in the bilateral inferior frontal and left inferior posterior parietal brain regions. We also detected significant group differences in the deoxygenated hemodynamic mean trends in the right inferior posterior parietal cortex and left temporal parietal junction. These findings, using dramatically different approaches, experimental designs, data sets, and foci, were consistent with several other reports, confirming group differences in the importance of these two areas for syntax comprehension. The proposed FDA was consistent with the temporal characteristics of fNIRS, thus providing an alternative methodology for fNIRS analyses.

Selection of the NIR region for a regression model of the ethanol concentration in fermentation process by an online NIR and mid-IR dual-region spectrometer and 2D heterospectral correlation spectroscopy.

PubMed

Nishii, Takashi; Genkawa, Takuma; Watari, Masahiro; Ozaki, Yukihiro

2012-01-01

A new selection procedure of an informative near-infrared (NIR) region for regression model building is proposed that uses an online NIR/mid-infrared (mid-IR) dual-region spectrometer in conjunction with two-dimensional (2D) NIR/mid-IR heterospectral correlation spectroscopy. In this procedure, both NIR and mid-IR spectra of a liquid sample are acquired sequentially during a reaction process using the NIR/mid-IR dual-region spectrometer; the 2D NIR/mid-IR heterospectral correlation spectrum is subsequently calculated from the obtained spectral data set. From the calculated 2D spectrum, a NIR region is selected that includes bands of high positive correlation intensity with mid-IR bands assigned to the analyte, and used for the construction of a regression model. To evaluate the performance of this procedure, a partial least-squares (PLS) regression model of the ethanol concentration in a fermentation process was constructed. During fermentation, NIR/mid-IR spectra in the 10000 - 1200 cm(-1) region were acquired every 3 min, and a 2D NIR/mid-IR heterospectral correlation spectrum was calculated to investigate the correlation intensity between the NIR and mid-IR bands. NIR regions that include bands at 4343, 4416, 5778, 5904, and 5955 cm(-1), which result from the combinations and overtones of the C-H group of ethanol, were selected for use in the PLS regression models, by taking the correlation intensity of a mid-IR band at 2985 cm(-1) arising from the CH(3) asymmetric stretching vibration mode of ethanol as a reference. The predicted results indicate that the ethanol concentrations calculated from the PLS regression models fit well to those obtained by high-performance liquid chromatography. Thus, it can be concluded that the selection procedure using the NIR/mid-IR dual-region spectrometer combined with 2D NIR/mid-IR heterospectral correlation spectroscopy is a powerful method for the construction of a reliable regression model.

Correction of motion artifacts and serial correlations for real-time functional near-infrared spectroscopy

PubMed Central

Barker, Jeffrey W.; Rosso, Andrea L.; Sparto, Patrick J.; Huppert, Theodore J.

2016-01-01

Abstract. Functional near-infrared spectroscopy (fNIRS) is a relatively low-cost, portable, noninvasive neuroimaging technique for measuring task-evoked hemodynamic changes in the brain. Because fNIRS can be applied to a wide range of populations, such as children or infants, and under a variety of study conditions, including those involving physical movement, gait, or balance, fNIRS data are often confounded by motion artifacts. Furthermore, the high sampling rate of fNIRS leads to high temporal autocorrelation due to systemic physiology. These two factors can reduce the sensitivity and specificity of detecting hemodynamic changes. In a previous work, we showed that these factors could be mitigated by autoregressive-based prewhitening followed by the application of an iterative reweighted least squares algorithm offline. This current work extends these same ideas to real-time analysis of brain signals by modifying the linear Kalman filter, resulting in an algorithm for online estimation that is robust to systemic physiology and motion artifacts. We evaluated the performance of the proposed method via simulations of evoked hemodynamics that were added to experimental resting-state data, which provided realistic fNIRS noise. Last, we applied the method post hoc to data from a standing balance task. Overall, the new method showed good agreement with the analogous offline algorithm, in which both methods outperformed ordinary least squares methods. PMID:27226974

[NIR and XRD analysis of drill-hole samples from Zhamuaobao iron-graphite deposit, Inner Mongolia].

PubMed

Li, Ying-kui; Cao, Jian-jin; Wu, Zheng-quan; Dai, Dong-le; Lin, Zu-xu

2015-01-01

The author analyzed the 4202 drill-hole samples from Zhamuaobao iron-graphite deposit by using near infrared spectroscopy(NIR) and X-ray diffraction(XRD) measuring and testing techniques, and then compared and summarized the results of two kinds of testing technology. The results indicate that some difference of the mineral composition exists among different layers, the lithology from upper to deeper is the clay gravel layer of tertiary and quaternary, mudstone, mica quartz schist, quartz actinolite scarn, skarnization marble, iron ore deposits, graphite deposits and mica quartz schist. The petrogenesis in different depth also shows difference, which may indicate the geological characteristic to some extent. The samples had mainly undergone such processes as oxidization, carbonation, chloritization and skarn alteration. The research results can not only improve the geological feature of the mining area, but also have great importance in ore exploration, mining, mineral processing and so on. What's more, as XRD can provide preliminary information about the mineral composition, NIR can make further judgement on the existence of the minerals. The research integrated the advantages of both NIR and XRD measuring and testing techniques, put forward a method with two kinds of modern testing technology combined with each other, which may improve the accuracy of the mineral composition identification. In the meantime, the NIR will be more wildly used in geography on the basis of mineral spectroscopy.

A Near Infrared Spectroscopy (NIRS) and Chemometric Approach to Improve Apple Fruit Quality Management: A Case Study on the Cultivars "Cripps Pink" and "Braeburn".

PubMed

Eisenstecken, Daniela; Panarese, Alessia; Robatscher, Peter; Huck, Christian W; Zanella, Angelo; Oberhuber, Michael

2015-07-24

The potential of near infrared spectroscopy (NIRS) in the wavelength range of 1000-2500 nm for predicting quality parameters such as total soluble solids (TSS), acidity (TA), firmness, and individual sugars (glucose, fructose, sucrose, and xylose) for two cultivars of apples ("Braeburn" and "Cripps Pink") was studied during the pre- and post-storage periods. Simultaneously, a qualitative investigation on the capability of NIRS to discriminate varieties, harvest dates, storage periods and fruit inhomogeneity was carried out. In order to generate a sample set with high variability within the most relevant apple quality traits, three different harvest time points in combination with five different storage periods were chosen, and the evolution of important quality parameters was followed both with NIRS and wet chemical methods. By applying a principal component analysis (PCA) a differentiation between the two cultivars, freshly harvested vs. long-term stored apples and, notably, between the sun-exposed vs. shaded side of apples could be found. For the determination of quality parameters effective prediction models for titratable acid (TA) and individual sugars such as fructose, glucose and sucrose by using partial least square (PLS) regression have been developed. Our results complement earlier reports, highlighting the versatility of NIRS as a fast, non-invasive method for quantitative and qualitative studies on apples.

Predicting water-holding capacity of intact chicken broiler breast fillets with Vis/NIR spectroscopy

USDA-ARS?s Scientific Manuscript database

The ability of using visible and near-infrared (Vis/NIR) spectroscopy to predict water-holding capacity (WHC) of intact chicken broiler breast fillets (pectoralis major) was assessed in this study. Boneless and skinless chicken fillets (214 in total) were procured from a commercial processing plant ...

Near-infrared muscle functional monitoring

NASA Astrophysics Data System (ADS)

Ferrari, Marco; De Blasi, Roberto A.; Ferrari, Adriano; Pizzi, Assunta; Quaresima, Valentina

1994-01-01

The oxygenation of human muscle tissue can be investigated using near IR spectroscopy (NIRS). Oxy and deoxy hemoglobin changes can be quantified combining attenuation measurements with pathlength data obtained by time resolved spectroscopy. This study reports the application of NIRS to non- invasive measurements of quadriceps oxygenation on muscular dystrophy patients during treadmill exercise.

Detection of starch adulteration in onion powder by FT-NIR and FT-IR spectroscopy

USDA-ARS?s Scientific Manuscript database

Adulteration of onion powder with cornstarch was identified by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra of 180 pure and adulterated samples (1–35 wt% starch) were collected and preprocessed to generate calibration and predi...

Potential prospects in archaeological research by using optical spectroscopy through a black glass ocular

NASA Astrophysics Data System (ADS)

Cosyns, P.; Meulebroeck, W.; Thienpont, H.; Nys, K.

The aim of this paper is to draw attention to the potential usefulness of optical spectroscopy within the archaeological discourse. We therefore use the standardized color coordinates and the transmittance spectra in the region between 350- 1650 nm of nine fragmented Roman black glass artifacts from archaeological contexts in Avenches (Switzerland) and an intact piece from Tongeren (Belgium). Firstly, we demonstrate how the use of UV-Vis-NIR spectroscopy can help the archaeologist in understanding the various excavated features containing glass artifacts. The analysis of the optical spectra of Roman black glass artifacts demonstrates in the first place that an object has a very homogenous composition. The clustering of the different fragments with characteristic spectra permits to connect the pieces from various areas of an excavation to one single object or to several objects from the same batch. These results provide the archaeologist the possibility to merge recognized layers or to connect different features in the surrounding area. Secondly, we demonstrate how the use of UV-Vis-NIR spectroscopy can help improve the analysis process. This inexpensive method can facilitate a more convenient and purposive sampling by means of a preliminary inquiry, selecting the most interesting pieces out of a large group of artifacts suitable for chemical analysis.

Anesthetic-dependent changes in the chain-melting phase transition of DPPG liposomes studied using near-infrared spectroscopy supported by PCA

NASA Astrophysics Data System (ADS)

Kuć, Marta; Cieślik-Boczula, Katarzyna; Rospenk, Maria

2017-11-01

The effect of inhalation anesthetics (enflurane, isoflurane, sevoflurane or halothane) on the lipid chain-melting phase transition of negatively charged phospholipid membranes was studied using near-infrared (NIR) spectroscopy supported by Principal Component Analysis (PCA). NIR spectra of anesthetics-mixed dipalmitoylphosphatidylglycerol (DPPG) membranes were recorded in a range of the first overtone of the symmetric and antisymmetric stretching vibrations of CH2 groups of lipid aliphatic chains as a function of increasing temperature. Anesthetic-dependent changes in the trans to gauche conformers ratio of CH2 groups in the hydrocarbon lipid chains were characterized in detail and compared with the zwitterionic lipid membranes, which were built of dipalmitoylphosphatidylcholine (DPPC) molecules.

Time-Frequency Characterization of Cerebral Hemodynamics of Migraine Sufferers as Assessed by NIRS Signals

NASA Astrophysics Data System (ADS)

Molinari, Filippo; Rosati, Samanta; Liboni, William; Negri, Emanuela; Mana, Ornella; Allais, Gianni; Benedetto, Chiara

2010-12-01

Near-infrared spectroscopy (NIRS) is a noninvasive system for the real-time monitoring of the concentration of oxygenated ([InlineEquation not available: see fulltext.]) and reduced (HHb) hemoglobin in the brain cortex. [InlineEquation not available: see fulltext.] and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls) performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20-40 mHz) and of the low frequencies (LF: 40-140 mHz). Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.

Noncontact analysis of the fiber weight per unit area in prepreg by near-infrared spectroscopy.

PubMed

Jiang, B; Huang, Y D

2008-05-26

The fiber weight per unit area in prepreg is an important factor to ensure the quality of the composite products. Near-infrared spectroscopy (NIRS) technology together with a noncontact reflectance sources has been applied for quality analysis of the fiber weight per unit area. The range of the unit area fiber weight was 13.39-14.14mgcm(-2). The regression method was employed by partial least squares (PLS) and principal components regression (PCR). The calibration model was developed by 55 samples to determine the fiber weight per unit area in prepreg. The determination coefficient (R(2)), root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were 0.82, 0.092, 0.099, respectively. The predicted values of the fiber weight per unit area in prepreg measured by NIRS technology were comparable to the values obtained by the reference method. For this technology, the noncontact reflectance sources focused directly on the sample with neither previous treatment nor manipulation. The results of the paired t-test revealed that there was no significant difference between the NIR method and the reference method. Besides, the prepreg could be analyzed one time within 20s without sample destruction.

Noninvasive detection of change in skeletal muscle oxygenation during incremental exercise with near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Fang; Luo, Qingming; Xu, Guodong; Li, Pengcheng

2003-12-01

Near infrared spectroscopy (NIRS) has been developed as a non-invasive method to assess O2 delivery, O2 consumption and blood flow, in diverse local muscle groups at rest and during exercise. The aim of this study was to investigate local O2 consumption in exercising muscle by use of near-infrared spectroscopy (NIRS). Ten elite athletes of different sport items were tested in rest and during step incremental load exercise. Local variations of quadriceps muscles were investigated with our wireless NIRS blood oxygen monitor system. The results show that the changes of blood oxygen relate on the sport items, type of muscle, kinetic capacity et al. These results indicate that NIRS is a potential useful tool to detect local muscle oxygenation and blood flow profiles; therefore it might be easily applied for evaluating the effect of athletes training.

Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

PubMed

Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

2013-01-01

Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

Analysis of protein structures and interactions in complex food by near-infrared spectroscopy. 2. Hydrated gluten.

PubMed

Bruun, Susanne Wrang; Søndergaard, Ib; Jacobsen, Susanne

2007-09-05

Hydrated gluten, treated with various salts, was analyzed by near-infrared (NIR) spectroscopy to assess the ability of this method to reveal protein structure and interaction changes in perturbed food systems. The spectra were pretreated with second-derivative transformation and extended multiplicative signal correction for improving the band resolution and removing physical and quantitative spectral variations. Principal component analysis of the preprocessed spectra showed spectral effects that depended on salt type and concentration. Although both gluten texture and the NIR spectra were little influenced by treatment with salt solutions of low concentrations (0.1-0.2 M), they were significantly and diversely affected by treatment with 1.0 M salt solutions. Compared to hydration in water, hydration in 1.0 M sulfate salts caused spectral effects similar to a drying-out effect, which could be explained by salting-out.

NIR and UV-vis spectroscopy, artificial nose and tongue: comparison of four fingerprinting techniques for the characterisation of Italian red wines.

PubMed

Casale, M; Oliveri, P; Armanino, C; Lanteri, S; Forina, M

2010-06-04

Four rapid and low-cost vanguard analytical systems (NIR and UV-vis spectroscopy, a headspace-mass based artificial nose and a voltammetric artificial tongue), together with chemometric pattern recognition techniques, were applied and compared in addressing a food authentication problem: the distinction between wine samples from the same Italian oenological region, according to the grape variety. Specifically, 59 certified samples belonging to the Barbera d'Alba and Dolcetto d'Alba appellations and collected from the same vintage (2007) were analysed. The instrumental responses, after proper data pre-processing, were used as fingerprints of the characteristics of the samples: the results from principal component analysis and linear discriminant analysis were discussed, comparing the capability of the four analytical strategies in addressing the problem studied. Copyright 2010 Elsevier B.V. All rights reserved.

Assessment of hyaline cartilage matrix composition using near infrared spectroscopy.

PubMed

Palukuru, Uday P; McGoverin, Cushla M; Pleshko, Nancy

2014-09-01

Changes in the composition of the extracellular matrix (ECM) are characteristic of injury or disease in cartilage tissue. Various imaging modalities and biochemical techniques have been used to assess the changes in cartilage tissue but lack adequate sensitivity, or in the case of biochemical techniques, result in destruction of the sample. Fourier transform near infrared (FT-NIR) spectroscopy has shown promise for the study of cartilage composition. In the current study NIR spectroscopy was used to identify the contributions of individual components of cartilage in the NIR spectra by assessment of the major cartilage components, collagen and chondroitin sulfate, in pure component mixtures. The NIR spectra were obtained using homogenous pellets made by dilution with potassium bromide. A partial least squares (PLS) model was calculated to predict composition in bovine cartilage samples. Characteristic absorbance peaks between 4000 and 5000 cm(-1) could be attributed to components of cartilage, i.e. collagen and chondroitin sulfate. Prediction of the amount of collagen and chondroitin sulfate in tissues was possible within 8% (w/dw) of values obtained by gold standard biochemical assessment. These results support the use of NIR spectroscopy for in vitro and in vivo applications to assess matrix composition of cartilage tissues, especially when tissue destruction should be avoided. Copyright © 2014. Published by Elsevier B.V.

Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia

PubMed Central

Selb, Juliette; Boas, David A.; Chan, Suk-Tak; Evans, Karleyton C.; Buckley, Erin M.; Carp, Stefan A.

2014-01-01

Abstract. Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) are two diffuse optical technologies for brain imaging that are sensitive to changes in hemoglobin concentrations and blood flow, respectively. Measurements for both modalities are acquired on the scalp, and therefore hemodynamic processes in the extracerebral vasculature confound the interpretation of cortical hemodynamic signals. The sensitivity of NIRS to the brain versus the extracerebral tissue and the contrast-to-noise ratio (CNR) of NIRS to cerebral hemodynamic responses have been well characterized, but the same has not been evaluated for DCS. This is important to assess in order to understand their relative capabilities in measuring cerebral physiological changes. We present Monte Carlo simulations on a head model that demonstrate that the relative brain-to-scalp sensitivity is about three times higher for DCS (0.3 at 3 cm) than for NIRS (0.1 at 3 cm). However, because DCS has higher levels of noise due to photon-counting detection, the CNR is similar for both modalities in response to a physiologically realistic simulation of brain activation. Even so, we also observed higher CNR of the hemodynamic response during graded hypercapnia in adult subjects with DCS than with NIRS. PMID:25453036

Intraoperative near-infrared fluorescence imaging and spectroscopy identifies residual tumor cells in wounds

NASA Astrophysics Data System (ADS)

Holt, David; Parthasarathy, Ashwin B.; Okusanya, Olugbenga; Keating, Jane; Venegas, Ollin; Deshpande, Charuhas; Karakousis, Giorgos; Madajewski, Brian; Durham, Amy; Nie, Shuming; Yodh, Arjun G.; Singhal, Sunil

2015-07-01

Surgery is the most effective method to cure patients with solid tumors, and 50% of all cancer patients undergo resection. Local recurrences are due to tumor cells remaining in the wound, thus we explore near-infrared (NIR) fluorescence spectroscopy and imaging to identify residual cancer cells after surgery. Fifteen canines and two human patients with spontaneously occurring sarcomas underwent intraoperative imaging. During the operation, the wounds were interrogated with NIR fluorescence imaging and spectroscopy. NIR monitoring identified the presence or absence of residual tumor cells after surgery in 14/15 canines with a mean fluorescence signal-to-background ratio (SBR) of ˜16. Ten animals showed no residual tumor cells in the wound bed (mean SBR<2, P<0.001). None had a local recurrence at >1-year follow-up. In five animals, the mean SBR of the wound was >15, and histopathology confirmed tumor cells in the postsurgical wound in four/five canines. In the human pilot study, neither patient had residual tumor cells in the wound bed, and both remain disease free at >1.5-year follow up. Intraoperative NIR fluorescence imaging and spectroscopy identifies residual tumor cells in surgical wounds. These observations suggest that NIR imaging techniques may improve tumor resection during cancer operations.

Intraoperative near-infrared fluorescence imaging and spectroscopy identifies residual tumor cells in wounds

PubMed Central

Holt, David; Parthasarathy, Ashwin B.; Okusanya, Olugbenga; Keating, Jane; Venegas, Ollin; Deshpande, Charuhas; Karakousis, Giorgos; Madajewski, Brian; Durham, Amy; Nie, Shuming; Yodh, Arjun G.; Singhal, Sunil

2015-01-01

Abstract. Surgery is the most effective method to cure patients with solid tumors, and 50% of all cancer patients undergo resection. Local recurrences are due to tumor cells remaining in the wound, thus we explore near-infrared (NIR) fluorescence spectroscopy and imaging to identify residual cancer cells after surgery. Fifteen canines and two human patients with spontaneously occurring sarcomas underwent intraoperative imaging. During the operation, the wounds were interrogated with NIR fluorescence imaging and spectroscopy. NIR monitoring identified the presence or absence of residual tumor cells after surgery in 14/15 canines with a mean fluorescence signal-to-background ratio (SBR) of ∼16. Ten animals showed no residual tumor cells in the wound bed (mean SBR<2, P<0.001). None had a local recurrence at >1-year follow-up. In five animals, the mean SBR of the wound was >15, and histopathology confirmed tumor cells in the postsurgical wound in four/five canines. In the human pilot study, neither patient had residual tumor cells in the wound bed, and both remain disease free at >1.5-year follow up. Intraoperative NIR fluorescence imaging and spectroscopy identifies residual tumor cells in surgical wounds. These observations suggest that NIR imaging techniques may improve tumor resection during cancer operations. PMID:26160347

FT-NIR: A Tool for Process Monitoring and More.

PubMed

Martoccia, Domenico; Lutz, Holger; Cohen, Yvan; Jerphagnon, Thomas; Jenelten, Urban

2018-03-30

With ever-increasing pressure to optimize product quality, to reduce cost and to safely increase production output from existing assets, all combined with regular changes in terms of feedstock and operational targets, process monitoring with traditional instruments reaches its limits. One promising answer to these challenges is in-line, real time process analysis with spectroscopic instruments, and above all Fourier-Transform Near Infrared spectroscopy (FT-NIR). Its potential to afford decreased batch cycle times, higher yields, reduced rework and minimized batch variance is presented and application examples in the field of fine chemicals are given. We demonstrate that FT-NIR can be an efficient tool for improved process monitoring and optimization, effective process design and advanced process control.

Classification and quantification analysis of peach kernel from different origins with near-infrared diffuse reflection spectroscopy

PubMed Central

Liu, Wei; Wang, Zhen-Zhong; Qing, Jian-Ping; Li, Hong-Juan; Xiao, Wei

2014-01-01

Background: Peach kernels which contain kinds of fatty acids play an important role in the regulation of a variety of physiological and biological functions. Objective: To establish an innovative and rapid diffuse reflectance near-infrared spectroscopy (DR-NIR) analysis method along with chemometric techniques for the qualitative and quantitative determination of a peach kernel. Materials and Methods: Peach kernel samples from nine different origins were analyzed with high-performance liquid chromatography (HPLC) as a reference method. DR-NIR is in the spectral range 1100-2300 nm. Principal component analysis (PCA) and partial least squares regression (PLSR) algorithm were applied to obtain prediction models, The Savitzky-Golay derivative and first derivative were adopted for the spectral pre-processing, PCA was applied to classify the varieties of those samples. For the quantitative calibration, the models of linoleic and oleinic acids were established with the PLSR algorithm and the optimal principal component (PC) numbers were selected with leave-one-out (LOO) cross-validation. The established models were evaluated with the root mean square error of deviation (RMSED) and corresponding correlation coefficients (R2). Results: The PCA results of DR-NIR spectra yield clear classification of the two varieties of peach kernel. PLSR had a better predictive ability. The correlation coefficients of the two calibration models were above 0.99, and the RMSED of linoleic and oleinic acids were 1.266% and 1.412%, respectively. Conclusion: The DR-NIR combined with PCA and PLSR algorithm could be used efficiently to identify and quantify peach kernels and also help to solve variety problem. PMID:25422544

Determination of the Characteristics and Classification of Near-Infrared Spectra of Patchouli Oil (Pogostemon Cablin Benth.) from Different Origin

NASA Astrophysics Data System (ADS)

Diego, M. C. R.; Purwanto, Y. A.; Sutrisno; Budiastra, I. W.

2018-05-01

Research related to the non-destructive method of near-infrared (NIR) spectroscopy in aromatic oil is still in development in Indonesia. The objectives of the study were to determine the characteristics of the near-infrared spectra of patchouli oil and classify it based on its origin. The samples were selected from seven different places in Indonesia (Bogor and Garut from West Java, Aceh, and Jambi from Sumatra and Konawe, Masamba and Kolaka from Sulawesi Island). The spectral data of patchouli oil was obtained by FT-NIR spectrometer at the wavelength of 1000-2500 nm, and after that, the samples were subjected to composition analysis using Gas Chromatography-Mass Spectrometry. The transmittance and absorbance spectra were analyzed and then principal component analysis (PCA) was carried out. Discriminant analysis (DA) of the principal component was developed to classify patchouli oil based on its origin. The result shows that the data of both spectra (transmittance and absorbance spectra) by the PC analysis give a similar result for discriminating the seven types of patchouli oil due to their distribution and behavior. The DA of the three principal component in both data processed spectra could classify patchouli oil accurately. This result exposed that NIR spectroscopy can be successfully used as a correct method to classify patchouli oil based on its origin.

2D Vis/NIR correlation spectroscopy of cooked chicken meats

NASA Astrophysics Data System (ADS)

Liu, Yongliang; Chen, Yud-Ren; Ozaki, Yukihiro

2000-03-01

Cooking of chicken meats was investigated by the generalized two-dimensional visible/near-infrared (2D Vis/NIR) correlation spectroscopy. Synchronous and asynchronous spectra in the 400-700 nm visible region suggested that the 445 and 560 nm bands be ascribed to deoxymyoglobin and oxymyoglobin, and at least one of the 475, 520, and 585 nm bands is assignable to the denatured species (metmyoglobin). The asynchronous 2D NIR correlation spectrum showed that CH bands change their spectral intensities before the OH/NH groups during the cooking process, indicating that CH fractions are easily oxidized and degraded. In addition, strong correlation peaks were observed correlating the bands in the visible and NIR spectral regions.

Correlation of near-infrared spectroscopy and direct pressure monitoring in an acute porcine compartmental syndrome model.

PubMed

Cathcart, Curtis C; Shuler, Michael S; Freedman, Brett A; Reno, Lisa R; Budsberg, Steven C

2014-06-01

To correlate near-infrared spectroscopy (NIRS) and the tibial intracompartmental perfusion pressure (TIPP) in an acute limb compartmental syndrome. Landrace swine were subdivided into 2 groups: plasma infusion (n = 16) and blunt trauma plus plasma infusion (n = 15). NIRS sensors were placed over the craniolateral muscle compartment of proximal both tibiae. Albumin infusion elevated tibial intracompartmental pressures (TICP). Time-synchronized measures of systolic, diastolic, and mean arterial pressures, TICP, and percent oxygenation from each leg were collected. For the blunt trauma group, trauma was induced by dropping a 2-kg weight 30 times from 100 cm directly on the muscle compartment. For each group, a repeated-measures analysis of variance model was used to test differences in the TICP, TIPP, and oxygenation values. Pearson correlations were calculated between TICP and oxygenation and between TIPP and oxygenation. Both models created reproducible increases in TICP and decreases in TIPP. Trauma did not alter TICP, TIPP, or percent oxygenation in the model. NIRS was able to detect significant changes in tissue oxygenation at all the same time points. NIRS was able to detect decreased oxygenation at every TIPP decrease and subsequent increase after fasciotomies. An increase in percent oxygenation was seen in all cases once fasciotomy was performed and TICP was reduced. NIRS provided a sensitive measure correlating to both an increase and decrease in TICP and TIPP, respectively, in this infusion model. The addition of blunt trauma to the model did not alter the correlations of NIRS values with TICP and TIPP. Fasciotomy produced a rebound in oxygenation values.

Visible and Near-Infrared Spectroscopy Analysis of a Polycyclic Aromatic Hydrocarbon in Soils

PubMed Central

Okparanma, Reuben N.; Mouazen, Abdul M.

2013-01-01

Visible and near-infrared (VisNIR) spectroscopy is becoming recognised by soil scientists as a rapid and cost-effective measurement method for hydrocarbons in petroleum-contaminated soils. This study investigated the potential application of VisNIR spectroscopy (350–2500 nm) for the prediction of phenanthrene, a polycyclic aromatic hydrocarbon (PAH), in soils. A total of 150 diesel-contaminated soil samples were used in the investigation. Partial least-squares (PLS) regression analysis with full cross-validation was used to develop models to predict the PAH compound. Results showed that the PAH compound was predicted well with residual prediction deviation of 2.0–2.32, root-mean-square error of prediction of 0.21–0.25 mg kg−1, and coefficient of determination (r 2) of 0.75–0.83. The mechanism of prediction was attributed to covariation of the PAH with clay and soil organic carbon. Overall, the results demonstrated that the methodology may be used for predicting phenanthrene in soils utilizing the interrelationship between clay and soil organic carbon. PMID:24453798

Application of NIR reflectance spectroscopy on rapid determination of moisture content of wood pellets

USDA-ARS?s Scientific Manuscript database

NIR spectroscopy was used to measure the moisture concentration of wood pellets. Pellets were conditioned to various moisture levels between 0.63and 14.16percent (wet basis) and the moisture concentration was verified using a standard oven method. Samples from the various moisture levels were separa...

Rapid determination of acetic acid, furfural and 5-hydroxymethylfurfural in biomass hydrolysate using near-infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Near infrared spectroscopy (NIR) is a rapid detection technique that has been used to characterize biomass. The objective of this study was to develop suitable NIR models to predict the acetic acid, furfural, and 5-hydroxymethylfurfural (HMF) contents in biomass hydrolysates. Using a uniform distrib...

Cerebrovascular pattern improved by ozone autohemotherapy: an entropy-based study on multiple sclerosis patients.

PubMed

Molinari, Filippo; Rimini, Daniele; Liboni, William; Acharya, U Rajendra; Franzini, Marianno; Pandolfi, Sergio; Ricevuti, Giovanni; Vaiano, Francesco; Valdenassi, Luigi; Simonetti, Vincenzo

2017-08-01

Ozone major autohemotherapy is effective in reducing the symptoms of multiple sclerosis (MS) patients, but its effects on brain are still not clear. In this work, we have monitored the changes in the cerebrovascular pattern of MS patients and normal subjects during major ozone autohemotherapy by using near-infrared spectroscopy (NIRS) as functional and vascular technique. NIRS signals are analyzed using a combination of time, time-frequency analysis and nonlinear analysis of intrinsic mode function signals obtained from empirical mode decomposition technique. Our results show that there is an improvement in the cerebrovascular pattern of all subjects indicated by increasing the entropy of the NIRS signals. Hence, we can conclude that the ozone therapy increases the brain metabolism and helps to recover from the lower activity levels which is predominant in MS patients.

Application of a voltammetric electronic tongue and near infrared spectroscopy for a rapid umami taste assessment.

PubMed

Bagnasco, Lucia; Cosulich, M Elisabetta; Speranza, Giovanna; Medini, Luca; Oliveri, Paolo; Lanteri, Silvia

2014-08-15

The relationships between sensory attribute and analytical measurements, performed by electronic tongue (ET) and near-infrared spectroscopy (NIRS), were investigated in order to develop a rapid method for the assessment of umami taste. Commercially available umami products and some aminoacids were submitted to sensory analysis. Results were analysed in comparison with the outcomes of analytical measurements. Multivariate exploratory analysis was performed by principal component analysis (PCA). Calibration models for prediction of the umami taste on the basis of ET and NIR signals were obtained using partial least squares (PLS) regression. Different approaches for merging data from the two different analytical instruments were considered. Both of the techniques demonstrated to provide information related with umami taste. In particular, ET signals showed the higher correlation with umami attribute. Data fusion was found to be slightly beneficial - not so significantly as to justify the coupled use of the two analytical techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

Near-Infrared Spectroscopy Enhances Intravascular Ultrasound Assessment of Vulnerable Coronary Plaque: A Combined Pathological and In Vivo Study.

PubMed

Puri, Rishi; Madder, Ryan D; Madden, Sean P; Sum, Stephen T; Wolski, Kathy; Muller, James E; Andrews, Jordan; King, Karilane L; Kataoka, Yu; Uno, Kiyoko; Kapadia, Samir R; Tuzcu, E Murat; Nissen, Steven E; Virmani, Renu; Maehara, Akiko; Mintz, Gary S; Nicholls, Stephen J

2015-11-01

Pathological studies demonstrate the dual significance of plaque burden (PB) and lipid composition for mediating coronary plaque vulnerability. We evaluated relationships between intravascular ultrasound (IVUS)-derived PB and arterial remodeling with near-infrared spectroscopy (NIRS)-derived lipid content in ex vivo and in vivo human coronary arteries. Ex vivo coronary NIRS and IVUS imaging was performed through blood in 116 coronary arteries of 51 autopsied hearts, followed by 2-mm block sectioning (n=2070) and histological grading according to modified American Heart Association criteria. Lesions were defined as the most heavily diseased 2-mm block per imaged artery on IVUS. IVUS-derived PB and NIRS-derived lipid core burden index (LCBI) of each block and lesion were analyzed. Block-level analysis demonstrated significant trends of increasing PB and LCBI across more complex atheroma (Ptrend <0.001 for both LCBI and PB). Lesion-based analyses demonstrated the highest LCBI and remodeling index within coronary fibroatheroma (Ptrend <0.001 and 0.02 versus all plaque groups, respectively). Prediction models demonstrated similar abilities of PB, LCBI, and remodeling index for discriminating fibroatheroma (c indices: 0.675, 0.712, and 0.672, respectively). A combined PB+LCBI analysis significantly improved fibroatheroma detection accuracy (c index 0.77, P=0.028 versus PB; net-reclassification index 43%, P=0.003), whereas further adding remodeling index did not (c index 0.80, P=0.27 versus PB+LCBI). In vivo comparisons of 43 age- and sex-matched patients (to the autopsy cohort) undergoing combined NIRS-IVUS coronary imaging yielded similar associations to those demonstrated ex vivo. Adding NIRS to conventional IVUS-derived PB imaging significantly improves the ability to detect more active, potentially vulnerable coronary atheroma. © 2015 American Heart Association, Inc.

Measurements of coherent hemodynamics to enrich the physiological information provided by near-infrared spectroscopy (NIRS) and functional MRI

NASA Astrophysics Data System (ADS)

Sassaroli, Angelo; Tgavalekos, Kristen; Pham, Thao; Krishnamurthy, Nishanth; Fantini, Sergio

2018-02-01

Hemodynamic-based neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) sense hemoglobin concentration in cerebral tissue. The local concentration of hemoglobin, which is differentiated into oxy- and deoxy-hemoglobin by NIRS, features spontaneous oscillations over time scales of 10-100 s in response to a number of local and systemic physiological processes. If one of such processes becomes the dominant source of cerebral hemodynamics, there is a high coherence between this process and the associated hemodynamics. In this work, we report a method to identify such conditions of coherent hemodynamics, which may be exploited to study and quantify microvasculature and microcirculation properties. We discuss how a critical value of significant coherence may depend on the specific data collection scheme (for example, the total acquisition time) and the nature of the hemodynamic data (in particular, oxy- and deoxy-hemoglobin concentrations measured with NIRS show an intrinsic level of correlation that must be taken into account). A frequency-resolved study of coherent hemodynamics is the basis for the new technique of coherent hemodynamics spectroscopy (CHS), which aims to provide measures of cerebral blood flow and cerebral autoregulation. While these concepts apply in principle to both fMRI and NIRS data, in this article we focus on NIRS data.

Cropland Field Monitoring: MMV Page 1 Montana Cropland Enrolled Farm Fields Carbon Sequestration Field Sampling, Measurement, Monitoring, and Verification: Application of Visible-Near Infrared Diffuse Reflectance Spectroscopy (VNIR) and Laser-induced Breakdown Spectroscopy (LIBS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee Spangler; Ross Bricklemyer; David Brown

2012-03-15

There is growing need for rapid, accurate, and inexpensive methods to measure, and verify soil organic carbon (SOC) change for national greenhouse gas accounting and the development of a soil carbon trading market. Laboratory based soil characterization typically requires significant soil processing, which is time and resource intensive. This severely limits application for large-region soil characterization. Thus, development of rapid and accurate methods for characterizing soils are needed to map soil properties for precision agriculture applications, improve regional and global soil carbon (C) stock and flux estimates and efficiently map sub-surface metal contamination, among others. The greatest gains for efficientmore » soil characterization will come from collecting soil data in situ, thus minimizing soil sample transportation, processing, and lab-based measurement costs. Visible and near-infrared diffuse reflectance spectroscopy (VisNIR) and laser-induced breakdown spectroscopy (LIBS) are two complementary, yet fundamentally different spectroscopic techniques that have the potential to meet this need. These sensors have the potential to be mounted on a soil penetrometer and deployed for rapid soil profile characterization at field and landscape scales. Details of sensor interaction, efficient data management, and appropriate statistical analysis techniques for model calibrations are first needed. In situ or on-the-go VisNIR spectroscopy has been proposed as a rapid and inexpensive tool for intensively mapping soil texture and organic carbon (SOC). While lab-based VisNIR has been established as a viable technique for estimating various soil properties, few experiments have compared the predictive accuracy of on-the-go and lab-based VisNIR. Eight north central Montana wheat fields were intensively interrogated using on-the-go and lab-based VisNIR. Lab-based spectral data consistently provided more accurate predictions than on-the-go data. However, neither in situ nor lab-based spectroscopy yielded even semi-quantitative SOC predictions. There was little SOC variability to explain across the eight fields, and on-the-go VisNIR was not able to capture the subtle SOC variability in these Montana soils. With more variation in soil clay content compared to SOC, both lab and on-the-go VisNIR showed better explanatory power. There are several potential explanations for poor on-the-go predictive accuracy: soil heterogeneity, field moisture, consistent sample presentation, and a difference between the spatial support of on-the-go measurements and soil samples collected for laboratory analyses. Though the current configuration of a commercially available on-the-go VisNIR system allows for rapid field scanning, on-the-go soil processing (i.e. drying, crushing, and sieving) could improve soil carbon predictions. Laser-induced breakdown spectroscopy (LIBS) is an emerging elemental analysis technology with the potential to provide rapid, accurate and precise analysis of soil constituents, such as carbon, in situ across landscapes. The research team evaluated the accuracy of LIBS for measuring soil profile carbon in field-moist, intact soil cores simulating conditions that might be encountered by a probe-mounted LIBS instrument measuring soil profile carbon in situ. Over the course of three experiments, more than120 intact soil cores from eight north central Montana wheat fields and the Washington State University (WSU) Cook Agronomy Farm near Pullman, WA were interrogated with LIBS for rapid total carbon (TC), inorganic carbon (IC), and SOC determination. Partial least squares regression models were derived and independently validated at field- and regional scales. Researchers obtained the best LIBS validation predictions for IC followed by TC and SOC. Laser-induced breakdown spectroscopy is fundamentally an elemental analysis technique, yet LIBS PLS2 models appeared to discriminate IC from TC. Regression coefficients from initial models suggested a reliance upon stoichiometric relationships between carbon (247.8 nm) and other elements related to total and inorganic carbon in the soil matrix [Ca (210.2 nm, 211.3 nm, and 220.9 nm), Mg (279.55-280.4 nm, 285.26 nm), and Si (251.6 nm, 288.1 nm)]. Expanding the LIBS spectral range to capture emissions from a broader range of elements related to soil organic matter was explored using two spectrometer systems to improve SOC predictions. Results for increasing the spectral range of LIBS to the full 200-800 nm found modest gains in prediction accuracy for IC, but no gains for predicting TC or SOC. Poor SOC predictions are likely a function of (1) the lack of a consistent/definable molecular composition of SOC, (2) relatively little variation in SOC across field sites, and (3) inorganic carbon constituting the primary form of soil carbon, particularly for Montana soils.« less

Validating the absolute reliability of a fat free mass estimate equation in hemodialysis patients using near-infrared spectroscopy.

PubMed

Kono, Kenichi; Nishida, Yusuke; Moriyama, Yoshihumi; Taoka, Masahiro; Sato, Takashi

2015-06-01

The assessment of nutritional states using fat free mass (FFM) measured with near-infrared spectroscopy (NIRS) is clinically useful. This measurement should incorporate the patient's post-dialysis weight ("dry weight"), in order to exclude the effects of any change in water mass. We therefore used NIRS to investigate the regression, independent variables, and absolute reliability of FFM in dry weight. The study included 47 outpatients from the hemodialysis unit. Body weight was measured before dialysis, and FFM was measured using NIRS before and after dialysis treatment. Multiple regression analysis was used to estimate the FFM in dry weight as the dependent variable. The measured FFM before dialysis treatment (Mw-FFM), and the difference between measured and dry weight (Mw-Dw) were independent variables. We performed Bland-Altman analysis to detect errors between the statistically estimated FFM and the measured FFM after dialysis treatment. The multiple regression equation to estimate the FFM in dry weight was: Dw-FFM = 0.038 + (0.984 × Mw-FFM) + (-0.571 × [Mw-Dw]); R(2)  = 0.99). There was no systematic bias between the estimated and the measured values of FFM in dry weight. Using NIRS, FFM in dry weight can be calculated by an equation including FFM in measured weight and the difference between the measured weight and the dry weight. © 2015 The Authors. Therapeutic Apheresis and Dialysis © 2015 International Society for Apheresis.

Improvement of near infrared spectroscopic (NIRS) analysis of caffeine in roasted Arabica coffee by variable selection method of stability competitive adaptive reweighted sampling (SCARS).

PubMed

Zhang, Xuan; Li, Wei; Yin, Bin; Chen, Weizhong; Kelly, Declan P; Wang, Xiaoxin; Zheng, Kaiyi; Du, Yiping

2013-10-01

Coffee is the most heavily consumed beverage in the world after water, for which quality is a key consideration in commercial trade. Therefore, caffeine content which has a significant effect on the final quality of the coffee products requires to be determined fast and reliably by new analytical techniques. The main purpose of this work was to establish a powerful and practical analytical method based on near infrared spectroscopy (NIRS) and chemometrics for quantitative determination of caffeine content in roasted Arabica coffees. Ground coffee samples within a wide range of roasted levels were analyzed by NIR, meanwhile, in which the caffeine contents were quantitative determined by the most commonly used HPLC-UV method as the reference values. Then calibration models based on chemometric analyses of the NIR spectral data and reference concentrations of coffee samples were developed. Partial least squares (PLS) regression was used to construct the models. Furthermore, diverse spectra pretreatment and variable selection techniques were applied in order to obtain robust and reliable reduced-spectrum regression models. Comparing the respective quality of the different models constructed, the application of second derivative pretreatment and stability competitive adaptive reweighted sampling (SCARS) variable selection provided a notably improved regression model, with root mean square error of cross validation (RMSECV) of 0.375 mg/g and correlation coefficient (R) of 0.918 at PLS factor of 7. An independent test set was used to assess the model, with the root mean square error of prediction (RMSEP) of 0.378 mg/g, mean relative error of 1.976% and mean relative standard deviation (RSD) of 1.707%. Thus, the results provided by the high-quality calibration model revealed the feasibility of NIR spectroscopy for at-line application to predict the caffeine content of unknown roasted coffee samples, thanks to the short analysis time of a few seconds and non-destructive advantages of NIRS. Copyright © 2013 Elsevier B.V. All rights reserved.

Improvement of near infrared spectroscopic (NIRS) analysis of caffeine in roasted Arabica coffee by variable selection method of stability competitive adaptive reweighted sampling (SCARS)

NASA Astrophysics Data System (ADS)

Zhang, Xuan; Li, Wei; Yin, Bin; Chen, Weizhong; Kelly, Declan P.; Wang, Xiaoxin; Zheng, Kaiyi; Du, Yiping

2013-10-01

Coffee is the most heavily consumed beverage in the world after water, for which quality is a key consideration in commercial trade. Therefore, caffeine content which has a significant effect on the final quality of the coffee products requires to be determined fast and reliably by new analytical techniques. The main purpose of this work was to establish a powerful and practical analytical method based on near infrared spectroscopy (NIRS) and chemometrics for quantitative determination of caffeine content in roasted Arabica coffees. Ground coffee samples within a wide range of roasted levels were analyzed by NIR, meanwhile, in which the caffeine contents were quantitative determined by the most commonly used HPLC-UV method as the reference values. Then calibration models based on chemometric analyses of the NIR spectral data and reference concentrations of coffee samples were developed. Partial least squares (PLS) regression was used to construct the models. Furthermore, diverse spectra pretreatment and variable selection techniques were applied in order to obtain robust and reliable reduced-spectrum regression models. Comparing the respective quality of the different models constructed, the application of second derivative pretreatment and stability competitive adaptive reweighted sampling (SCARS) variable selection provided a notably improved regression model, with root mean square error of cross validation (RMSECV) of 0.375 mg/g and correlation coefficient (R) of 0.918 at PLS factor of 7. An independent test set was used to assess the model, with the root mean square error of prediction (RMSEP) of 0.378 mg/g, mean relative error of 1.976% and mean relative standard deviation (RSD) of 1.707%. Thus, the results provided by the high-quality calibration model revealed the feasibility of NIR spectroscopy for at-line application to predict the caffeine content of unknown roasted coffee samples, thanks to the short analysis time of a few seconds and non-destructive advantages of NIRS.

On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals.

PubMed

Aydöre, Sergül; Mihçak, M Kivanç; Ciftçi, Koray; Akin, Ata

2010-03-01

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus (IS), congruent stimulus (CS), and neutral stimulus (NS), respectively. We introduce a new measure, called "information transfer metric" (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.

A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application.

PubMed

Ferrari, Marco; Quaresima, Valentina

2012-11-01

This review is aimed at celebrating the upcoming 20th anniversary of the birth of human functional near-infrared spectroscopy (fNIRS). After the discovery in 1992 that the functional activation of the human cerebral cortex (due to oxygenation and hemodynamic changes) can be explored by NIRS, human functional brain mapping research has gained a new dimension. fNIRS or optical topography, or near-infrared imaging or diffuse optical imaging is used mainly to detect simultaneous changes in optical properties of the human cortex from multiple measurement sites and displays the results in the form of a map or image over a specific area. In order to place current fNIRS research in its proper context, this paper presents a brief historical overview of the events that have shaped the present status of fNIRS. In particular, technological progresses of fNIRS are highlighted (i.e., from single-site to multi-site functional cortical measurements (images)), introduction of the commercial multi-channel systems, recent commercial wireless instrumentation and more advanced prototypes. Copyright © 2012 Elsevier Inc. All rights reserved.

A brief review on the use of functional near-infrared spectroscopy (fNIRS) for language imaging studies in human newborns and adults.

PubMed

Quaresima, Valentina; Bisconti, Silvia; Ferrari, Marco

2012-05-01

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have a time resolution of 1-10 Hz, a depth sensitivity of about 1.5 cm, and a spatial resolution of about 1cm. The goal of this brief review is to report infants, children and adults fNIRS language studies. Since 1998, 60 studies have been published on cortical activation in the brain's classic language areas in children/adults as well as newborns using fNIRS instrumentations of different complexity. In addition, the basic principles of fNIRS including features, strengths, advantages, and limitations are summarized in terms that can be understood even by non specialists. Future prospects of fNIRS in the field of language processing imaging are highlighted. Copyright © 2011 Elsevier Inc. All rights reserved.

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Development of motion resistant instrumentation for ambulatory near-infrared spectroscopy

PubMed Central

Zhang, Quan; Yan, Xiangguo; Strangman, Gary E.

2011-01-01

Ambulatory near-infrared spectroscopy (aNIRS) enables recording of systemic or tissue-specific hemodynamics and oxygenation during a person's normal activities. It has particular potential for the diagnosis and management of health problems with unpredictable and transient hemodynamic symptoms, or medical conditions requiring continuous, long-duration monitoring. aNIRS is also needed in conditions where regular monitoring or imaging cannot be applied, including remote environments such as during spaceflight or at high altitude. One key to the successful application of aNIRS is reducing the impact of motion artifacts in aNIRS recordings. In this paper, we describe the development of a novel prototype aNIRS monitor, called NINscan, and our efforts to reduce motion artifacts in aNIRS monitoring. Powered by 2 AA size batteries and weighting 350 g, NINscan records NIRS, ECG, respiration, and acceleration for up to 14 h at a 250 Hz sampling rate. The system's performance and resistance to motion is demonstrated by long term quantitative phantom tests, Valsalva maneuver tests, and multiparameter monitoring during parabolic flight and high altitude hiking. To the best of our knowledge, this is the first report of multiparameter aNIRS monitoring and its application in parabolic flight. PMID:21895335

What we can and cannot (yet) do with functional near infrared spectroscopy

PubMed Central

Strait, Megan; Scheutz, Matthias

2014-01-01

Functional near infrared spectroscopy (NIRS) is a relatively new technique complimentary to EEG for the development of brain-computer interfaces (BCIs). NIRS-based systems for detecting various cognitive and affective states such as mental and emotional stress have already been demonstrated in a range of adaptive human–computer interaction (HCI) applications. However, before NIRS-BCIs can be used reliably in realistic HCI settings, substantial challenges oncerning signal processing and modeling must be addressed. Although many of those challenges have been identified previously, the solutions to overcome them remain scant. In this paper, we first review what can be currently done with NIRS, specifically, NIRS-based approaches to measuring cognitive and affective user states as well as demonstrations of passive NIRS-BCIs. We then discuss some of the primary challenges these systems would face if deployed in more realistic settings, including detection latencies and motion artifacts. Lastly, we investigate the effects of some of these challenges on signal reliability via a quantitative comparison of three NIRS models. The hope is that this paper will actively engage researchers to acilitate the advancement of NIRS as a more robust and useful tool to the BCI community. PMID:24904261

Applications of Functional Near-Infrared Spectroscopy (fNIRS) in Studying Cognitive Development: The Case of Mathematics and Language.

PubMed

Soltanlou, Mojtaba; Sitnikova, Maria A; Nuerk, Hans-Christoph; Dresler, Thomas

2018-01-01

In this review, we aim to highlight the application of functional near-infrared spectroscopy (fNIRS) as a useful neuroimaging technique for the investigation of cognitive development. We focus on brain activation changes during the development of mathematics and language skills in schoolchildren. We discuss how technical limitations of common neuroimaging techniques such as functional magnetic resonance imaging (fMRI) have resulted in our limited understanding of neural changes during development, while fNIRS would be a suitable and child-friendly method to examine cognitive development. Moreover, this technique enables us to go to schools to collect large samples of data from children in ecologically valid settings. Furthermore, we report findings of fNIRS studies in the fields of mathematics and language, followed by a discussion of the outlook of fNIRS in these fields. We suggest fNIRS as an additional technique to track brain activation changes in the field of educational neuroscience.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) in Studying Cognitive Development: The Case of Mathematics and Language

PubMed Central

Soltanlou, Mojtaba; Sitnikova, Maria A.; Nuerk, Hans-Christoph; Dresler, Thomas

2018-01-01

In this review, we aim to highlight the application of functional near-infrared spectroscopy (fNIRS) as a useful neuroimaging technique for the investigation of cognitive development. We focus on brain activation changes during the development of mathematics and language skills in schoolchildren. We discuss how technical limitations of common neuroimaging techniques such as functional magnetic resonance imaging (fMRI) have resulted in our limited understanding of neural changes during development, while fNIRS would be a suitable and child-friendly method to examine cognitive development. Moreover, this technique enables us to go to schools to collect large samples of data from children in ecologically valid settings. Furthermore, we report findings of fNIRS studies in the fields of mathematics and language, followed by a discussion of the outlook of fNIRS in these fields. We suggest fNIRS as an additional technique to track brain activation changes in the field of educational neuroscience. PMID:29666589

Development of near infrared spectrometer for gem materials study

NASA Astrophysics Data System (ADS)

Jindata, W.; Meesiri, W.; Wongkokua, W.

2015-07-01

Most of gem materials can be characterized by infrared absorption spectroscopy. Normally, mid infrared absorption technique has been applied for investigating fundamental vibrational modes. However, for some gem materials, such as tourmaline, NIR is a better choice due to differentiation. Most commercial NIR spectrometers employ complicated dispersive grating or Fourier transform techniques. In this work, we developed a filter type NIR spectrometer with the availability of high efficiency and low-cost narrow bandpass NIR interference filters to be taught in a physics laboratory. The instrument was designed for transmission-mode configuration. A 50W halogen lamp was used as NIR source. There were fourteen NIR filters mounted on a rotatory wheel for wavelength selection ranging from 1000-1650 nm with steps of 50 nm. A 1.0 mm diameter of InGaAs photodiode was used as the detector for the spectrometer. Hence, transparent gem materials can be used as samples for experiment. Student can learn vibrational absorption spectroscopy as well as Beer-Lambert law from the development of this instrument.

[Variable selection methods combined with local linear embedding theory used for optimization of near infrared spectral quantitative models].

PubMed

Hao, Yong; Sun, Xu-Dong; Yang, Qiang

2012-12-01

Variables selection strategy combined with local linear embedding (LLE) was introduced for the analysis of complex samples by using near infrared spectroscopy (NIRS). Three methods include Monte Carlo uninformation variable elimination (MCUVE), successive projections algorithm (SPA) and MCUVE connected with SPA were used for eliminating redundancy spectral variables. Partial least squares regression (PLSR) and LLE-PLSR were used for modeling complex samples. The results shown that MCUVE can both extract effective informative variables and improve the precision of models. Compared with PLSR models, LLE-PLSR models can achieve more accurate analysis results. MCUVE combined with LLE-PLSR is an effective modeling method for NIRS quantitative analysis.

Prediction of pH of cola beverage using Vis/NIR spectroscopy and least squares-support vector machine

NASA Astrophysics Data System (ADS)

Liu, Fei; He, Yong

2008-02-01

Visible and near infrared (Vis/NIR) transmission spectroscopy and chemometric methods were utilized to predict the pH values of cola beverages. Five varieties of cola were prepared and 225 samples (45 samples for each variety) were selected for the calibration set, while 75 samples (15 samples for each variety) for the validation set. The smoothing way of Savitzky-Golay and standard normal variate (SNV) followed by first-derivative were used as the pre-processing methods. Partial least squares (PLS) analysis was employed to extract the principal components (PCs) which were used as the inputs of least squares-support vector machine (LS-SVM) model according to their accumulative reliabilities. Then LS-SVM with radial basis function (RBF) kernel function and a two-step grid search technique were applied to build the regression model with a comparison of PLS regression. The correlation coefficient (r), root mean square error of prediction (RMSEP) and bias were 0.961, 0.040 and 0.012 for PLS, while 0.975, 0.031 and 4.697x10 -3 for LS-SVM, respectively. Both methods obtained a satisfying precision. The results indicated that Vis/NIR spectroscopy combined with chemometric methods could be applied as an alternative way for the prediction of pH of cola beverages.

Evaluation of cerebral ischemia using near-infrared spectroscopy with oxygen inhalation

NASA Astrophysics Data System (ADS)

Ebihara, Akira; Tanaka, Yuichi; Konno, Takehiko; Kawasaki, Shingo; Fujiwara, Michiyuki; Watanabe, Eiju

2012-09-01

Conventional methods presently used to evaluate cerebral hemodynamics are invasive, require physical restraint, and employ equipment that is not easily transportable. Therefore, it is difficult to take repeated measurements at the patient's bedside. An alternative method to evaluate cerebral hemodynamics was developed using near-infrared spectroscopy (NIRS) with oxygen inhalation. The bilateral fronto-temporal areas of 30 normal volunteers and 33 patients with cerebral ischemia were evaluated with the NIRS system. The subjects inhaled oxygen through a mask for 2 min at a flow rate of 8 L/min. Principal component analysis (PCA) was applied to the data, and a topogram was drawn using the calculated weights. NIRS findings were compared with those of single-photon-emission computed tomography (SPECT). In normal volunteers, no laterality of the PCA weights was observed in 25 of 30 cases (83%). In patients with cerebral ischemia, PCA weights in ischemic regions were lower than in normal regions. In 28 of 33 patients (85%) with cerebral ischemia, NIRS findings agreed with those of SPECT. The results suggest that transmission of the changes in systemic SpO2 were attenuated in ischemic regions. The method discussed here should be clinically useful because it can be used to measure cerebral ischemia easily, repeatedly, and noninvasively.

Development and Validation of a Near-Infrared Spectroscopy Method for the Prediction of Acrylamide Content in French-Fried Potato.

PubMed

Adedipe, Oluwatosin E; Johanningsmeier, Suzanne D; Truong, Van-Den; Yencho, G Craig

2016-03-02

This study investigated the ability of near-infrared spectroscopy (NIRS) to predict acrylamide content in French-fried potato. Potato flour spiked with acrylamide (50-8000 μg/kg) was used to determine if acrylamide could be accurately predicted in a potato matrix. French fries produced with various pretreatments and cook times (n = 84) and obtained from quick-service restaurants (n = 64) were used for model development and validation. Acrylamide was quantified using gas chromatography-mass spectrometry, and reflectance spectra (400-2500 nm) of each freeze-dried sample were captured on a Foss XDS Rapid Content Analyzer-NIR spectrometer. Partial least-squares (PLS) discriminant analysis and PLS regression modeling demonstrated that NIRS could accurately detect acrylamide content as low as 50 μg/kg in the model potato matrix. Prediction errors of 135 μg/kg (R(2) = 0.98) and 255 μg/kg (R(2) = 0.93) were achieved with the best PLS models for acrylamide prediction in Russet Norkotah French-fried potato and multiple samples of unknown varieties, respectively. The findings indicate that NIRS can be used as a screening tool in potato breeding and potato processing research to reduce acrylamide in the food supply.

Characterizing and authenticating Montilla-Moriles PDO vinegars using near infrared reflectance spectroscopy (NIRS) technology.

PubMed

De la Haba, María-José; Arias, Mar; Ramírez, Pilar; López, María-Isabel; Sánchez, María-Teresa

2014-02-20

This study assessed the potential of near infrared (NIR) spectroscopy as a non-destructive method for characterizing Protected Designation of Origin (PDO) "Vinagres de Montilla-Moriles" wine vinegars and for classifying them as a function of the manufacturing process used. Three spectrophotometers were evaluated for this purpose: two monochromator instruments (Foss NIRSystems 6500 SY-I and Foss NIRSystems 6500 SY-II; spectral range 400-2,500 nm in both cases) and a diode-array instrument (Corona 45 VIS/NIR; spectral range 380-1,700 nm). A total of 70 samples were used to predict major chemical quality parameters (total acidity, fixed acidity, volatile acidity, pH, dry extract, ash, acetoin, methanol, total polyphenols, color (tonality and intensity), and alcohol content), and to construct models for the classification of vinegars as a function of the manufacturing method used. The results obtained indicate that this non-invasive technology can be used successfully by the vinegar industry and by PDO regulators for the routine analysis of vinegars in order to authenticate them and to detect potential fraud. Slightly better results were achieved with the two monochromator instruments. The findings also highlight the potential of these NIR instruments for predicting the manufacturing process used, this being of particular value for the industrial authentication of traditional wine vinegars.

Correspondence of electroencephalography and near-infrared spectroscopy sensitivities to the cerebral cortex using a high-density layout

PubMed Central

Giacometti, Paolo; Diamond, Solomon G.

2014-01-01

Abstract. This study investigates the correspondence of the cortical sensitivity of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). EEG forward model sensitivity to the cerebral cortex was calculated for 329 EEG electrodes following the 10-5 EEG positioning system using a segmented structural magnetic resonance imaging scan of a human subject. NIRS forward model sensitivity was calculated for the same subject using 156 NIRS source-detector pairs selected from 32 source and 32 detector optodes positioned on the scalp using a subset of the 10-5 EEG positioning system. Sensitivity correlations between colocalized NIRS source-detector pair groups and EEG channels yielded R=0.46±0.08. Groups of NIRS source-detector pairs with maximum correlations to EEG electrode sensitivities are tabulated. The mean correlation between the point spread functions for EEG and NIRS regions of interest (ROI) was R=0.43±0.07. Spherical ROIs with radii of 26 mm yielded the maximum correlation between EEG and NIRS averaged across all cortical mesh nodes. These sensitivity correlations between EEG and NIRS should be taken into account when designing multimodal studies of neurovascular coupling and when using NIRS as a statistical prior for EEG source localization. PMID:25558462

Using near-infrared spectroscopy to resolve the species, gender, age, and the presence of Wolbachia infection in laboratory-reared Drosophila

USDA-ARS?s Scientific Manuscript database

The aim of the study was to determine the accuracy of near-infrared spectroscopy (NIRS) in determining species, gender, age and the presence of the common endosymbiont Wolbachia in laboratory reared Drosophila. NIRS measures absorption of light by organic molecules. Initially, a calibration model wa...

The effects of water and lipids on NIR optical breast measurements

NASA Astrophysics Data System (ADS)

Cerussi, Albert E.; Bevilacqua, Frederic; Shah, Natasha; Jakubowski, Dorota B.; Berger, Andrew J.; Lanning, Ryan M.; Tromberg, Bruce J.

2001-06-01

Near infrared diffuse optical spectroscopy and imaging may enhance existing technologies for breast cancer screening, diagnosis, and treatment. NIR spectroscopy yields quantitative functional information that cannot be obtained with other non-invasive radiological techniques. In this study we focused upon the origins of this contrast in healthy breast, especially from water and lipids.

Hemodynamic and Electrophysiological Connectivity in the Language System: Simultaneous Near-Infrared Spectroscopy and Electrocorticography Recordings during Cortical Stimulation

ERIC Educational Resources Information Center

Sato, Yosuke; Oishi, Makoto; Fukuda, Masafumi; Fujii, Yukihiko

2012-01-01

We applied near-infrared spectroscopy (NIRS) and electrocorticography (ECoG) recordings during cortical stimulation to a temporal lobe epilepsy patient who underwent subdural electrode implantation. Using NIRS, changes in blood concentrations of oxyhemoglobin (HbO[subscript 2]) and deoxyhemoglobin (HbR) during cortical stimulation of the left…

Functional Near-Infrared Spectroscopy for the Assessment of Speech Related Tasks

ERIC Educational Resources Information Center

Dieler, A. C.; Tupak, S. V.; Fallgatter, A. J.

2012-01-01

Over the past years functional near-infrared spectroscopy (fNIRS) has substantially contributed to the understanding of language and its neural correlates. In contrast to other imaging techniques, fNIRS is well suited to study language function in healthy and psychiatric populations due to its cheap and easy application in a quiet and natural…

Evaluating preservation methods for identifying Anopheles gambiae s.s. and Anopheles arabiensis complex mosquitoes species using near infra-red spectroscopy

USDA-ARS?s Scientific Manuscript database

Near infra-red spectroscopy (NIRS) has been successfully used on fresh and RNAlater® preserved Anopheles gambiae complex to identify sibling species and age. No preservation methods other than RNAlater® have been tested to preserve mosquitoes for species identification using NIRS. However, RNAlater®...

“Self-absorption” phenomenon in near-infrared Fourier transform Raman spectroscopy of cellulosic and lignocellulosic materials

Treesearch

Umesh P. Agarwal; Nancy Kawai

2005-01-01

While cellulosic and lignocellulosic materials have been studied using conventional Raman spectroscopy, availability of near-infrared (NIR) Fourier transform (FT) Raman instrumentation has made studying these materials much more convenient. This is especially true because the problem of laser-induced fluorescence can be avoided or minimized in FT- Raman (NIR Raman)...

Fiber micronaire, fineness and maturity predictions using NIR spectroscopy instruments on seed cotton and cotton fiber, in and outside of the laboratory

USDA-ARS?s Scientific Manuscript database

Micronaire is an important fiber quality parameter in the cotton industry. Micronaire is a function of maturity (the degree of the fiber secondary wall development) and fineness (linear density). Bench-top near infrared (NIR) spectroscopy has the ability to measure micronaire, maturity and fineness,...

Prediction of olive quality using FT-NIR spectroscopy in reflectance and transmittance modes

USDA-ARS?s Scientific Manuscript database

The objective of this research was to use FT-NIR spectroscopy to predict the firmness, oil content and color of two olive (Olea europaea L) varieties (‘Ayvalik’ and ‘Gemlik’). Spectral measurements were performed on the intact olives for the wavelengths of 780-2500 nm in reflectance and for 800-1725...

A Brief Review of OPT101 Sensor Application in Near-Infrared Spectroscopy Instrumentation for Intensive Care Unit Clinics

PubMed Central

Li, Ting; Zhong, Fulin; Pan, Boan; Li, Zebin; Huang, Chong; Deng, Zishan

2017-01-01

The optoelectronic sensor OPT101 have merits in advanced optoelectronic response characteristics at wavelength range for medical near-infrared spectroscopy and small-size chip design with build-in trans-impedance amplifier. Our lab is devoted to developing a series of portable near-infrared spectroscopy (NIRS) devices embedded with OPT101 for applications in intensive care unit clinics, based on NIRS principle. Here we review the characteristics and advantages of OPT101 relative to clinical NIRS instrumentation, and the most recent achievements, including early-diagnosis and therapeutic effect evaluation of thrombus, noninvasive monitoring of patients' shock severity, and fatigue evaluation. The future prospect on OPT101 improvements in noninvasive clinical applications is also discussed. PMID:28757564

Automated system for the on-line monitoring of powder blending processes using near-infrared spectroscopy. Part I. System development and control.

PubMed

Hailey, P A; Doherty, P; Tapsell, P; Oliver, T; Aldridge, P K

1996-03-01

An automated system for the on-line monitoring of powder blending processes is described. The system employs near-infrared (NIR) spectroscopy using fibre-optics and a graphical user interface (GUI) developed in the LabVIEW environment. The complete supervisory control and data analysis (SCADA) software controls blender and spectrophotometer operation and performs statistical spectral data analysis in real time. A data analysis routine using standard deviation is described to demonstrate an approach to the real-time determination of blend homogeneity.

Rapid discrimination and determination of antibiotics drugs in plastic syringes using near infrared spectroscopy with chemometric analysis: Application to amoxicillin and penicillin.

PubMed

Lê, Laetitia Minh Mai; Eveleigh, Luc; Hasnaoui, Ikram; Prognon, Patrice; Baillet-Guffroy, Arlette; Caudron, Eric

2017-05-10

The aim of this study was to investigate near infrared spectroscopy (NIRS) combined to chemometric analysis to discriminate and quantify three antibiotics by direct measurement in plastic syringes.Solutions of benzylpenicillin (PENI), amoxicillin (AMOX) and amoxicillin/clavulanic acid (AMOX/CLAV) were analyzed at therapeutic concentrations in glass vials and plastic syringes with NIR spectrometer by direct measurement. Chemometric analysis using partial least squares regression and discriminative analysis was conducted to develop qualitative and quantitative calibration models. Discrimination of the three antibiotics was optimal for concentrated solutions with 100% of accuracy. For quantitative analysis, the three antibiotics furnished a linear response (R²>0.9994) for concentrations ranging from 0.05 to 0.2 g/mL for AMOX, 0.1 to 1.0 MUI/mL for PENI and 0.005 to 0.05 g/mL for AMOX/CLAV with excellent repeatability (maximum 1.3%) and intermediate precision (maximum of 3.2%). Based on proposed models, 94.4% of analyzed AMOX syringes, 80.0% of AMOX/CLAV syringes and 85.7% of PENI syringes were compliant with a relative error including the limit of ± 15%.NIRS as rapid, non-invasive and non-destructive analytical method represents a potentially powerful tool to further develop for securing the drug administration circuit of healthcare institutions to ensure that patients receive the correct product at the right dose. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of communicative head movements on the quality of functional near-infrared spectroscopy signals: negligible effects for affirmative and negative gestures and consistent artifacts related to raising eyebrows

NASA Astrophysics Data System (ADS)

Balardin, Joana Bisol; Morais, Guilherme Augusto Zimeo; Furucho, Rogério Akira; Trambaiolli, Lucas Romualdo; Sato, João Ricardo

2017-04-01

Functional near-infrared spectroscopy (fNIRS) is currently one of the most promising tools in the neuroscientific research to study brain hemodynamics during naturalistic social communication. The application of fNIRS by studies in this field of knowledge has been widely justified by its strong resilience to motion artifacts, including those that might be generated by communicative head and facial movements. Previous studies have focused on the identification and correction of these artifacts, but a quantification of the differential contribution of common communicative movements on the quality of fNIRS signals is still missing. We assessed the impact of four movements (nodding head up and down, reading aloud, nodding head sideways, and raising eyebrows) performed during rest and task conditions on two metrics of signal quality control: an estimative of signal-to-noise performance and the negative correlation between oxygenated and deoxygenated hemoglobin (oxy-Hb and deoxy-Hb). Channel-wise group analysis confirmed the robustness of the fNIRS technique to head nodding movements but showed a large effect of raising eyebrows in both signal quality control metrics, both during task and rest conditions. Reading aloud did not disrupt the expected anticorrelation between oxy-Hb and deoxy-Hb but had a relatively large effect on signal-to-noise performance. These findings may have implications to the interpretation of fNIRS studies examining communicative processes.

Near-Infrared Spectroscopy Using a Supercontinuum Laser: Application to Long Wavelength Transmission Spectra of Barley Endosperm and Oil.

PubMed

Ringsted, Tine; Dupont, Sune; Ramsay, Jacob; Jespersen, Birthe Møller; Sørensen, Klavs Martin; Keiding, Søren Rud; Engelsen, Søren Balling

2016-07-01

The supercontinuum laser is a new type of light source, which combines the collimation and intensity of a laser with the broad spectral region of a lamp. Using such a source therefore makes it possible to focus the light onto small sample areas without losing intensity and thus facilitate either rapid or high-intensity measurements. Single seed transmission analysis in the long wavelength (LW) near-infrared (NIR) region is one area that might benefit from a brighter light source such as the supercontinuum laser. This study is aimed at building an experimental spectrometer consisting of a supercontinuum laser source and a dispersive monochromator in order to investigate its capability to measure the barley endosperm using transmission experiments in the LW NIR region. So far, barley and wheat seeds have only been studied using NIR transmission in the short wavelength region up to 1100 nm. However, the region in the range of 2260-2380 nm has previously shown to be particularly useful in differentiating barley phenotypes using NIR spectroscopy in reflectance mode. In the present study, 350 seeds (consisting of 70 seeds from each of five barley genotypes) in 1 mm slices were measured by NIR transmission in the range of 2235-2381 nm and oils from the same five barley genotypes were measured in a cuvette with a 1 mm path length in the range of 2003-2497 nm. The spectra of the barley seeds could be classified according to genotypes by principal component analysis; and spectral covariances with reference analysis of moisture, β-glucan, starch, protein and lipid were established. The spectral variations of the barley oils were compared to the fatty acid compositions as measured using gas chromotography-mass spectrometry (GC-MS). © The Author(s) 2016.

Impaired cerebral autoregulation and brain injury in newborns with hypoxic-ischemic encephalopathy treated with hypothermia.

PubMed

Massaro, An N; Govindan, R B; Vezina, Gilbert; Chang, Taeun; Andescavage, Nickie N; Wang, Yunfei; Al-Shargabi, Tareq; Metzler, Marina; Harris, Kari; du Plessis, Adre J

2015-08-01

Impaired cerebral autoregulation may contribute to secondary injury in newborns with hypoxic-ischemic encephalopathy (HIE). Continuous, noninvasive assessment of cerebral pressure autoregulation can be achieved with bedside near-infrared spectroscopy (NIRS) and systemic mean arterial blood pressure (MAP) monitoring. This study aimed to evaluate whether impaired cerebral autoregulation measured by NIRS-MAP monitoring during therapeutic hypothermia and rewarming relates to outcome in 36 newborns with HIE. Spectral coherence analysis between NIRS and MAP was used to quantify changes in the duration [pressure passivity index (PPI)] and magnitude (gain) of cerebral autoregulatory impairment. Higher PPI in both cerebral hemispheres and gain in the right hemisphere were associated with neonatal adverse outcomes [death or detectable brain injury by magnetic resonance imaging (MRI), P < 0.001]. NIRS-MAP monitoring of cerebral autoregulation can provide an ongoing physiological biomarker that may help direct care in perinatal brain injury. Copyright © 2015 the American Physiological Society.

VIS-NIR spectroscopy as a process analytical technology for compositional characterization of film biopolymers and correlation with their mechanical properties.

PubMed

Barbin, Douglas Fernandes; Valous, Nektarios A; Dias, Adriana Passos; Camisa, Jaqueline; Hirooka, Elisa Yoko; Yamashita, Fabio

2015-11-01

There is an increasing interest in the use of polysaccharides and proteins for the production of biodegradable films. Visible and near-infrared (VIS-NIR) spectroscopy is a reliable analytical tool for objective analyses of biological sample attributes. The objective is to investigate the potential of VIS-NIR spectroscopy as a process analytical technology for compositional characterization of biodegradable materials and correlation to their mechanical properties. Biofilms were produced by single-screw extrusion with different combinations of polybutylene adipate-co-terephthalate, whole oat flour, glycerol, magnesium stearate, and citric acid. Spectral data were recorded in the range of 400-2498nm at 2nm intervals. Partial least square regression was used to investigate the correlation between spectral information and mechanical properties. Results show that spectral information is influenced by the major constituent components, as they are clustered according to polybutylene adipate-co-terephthalate content. Results for regression models using the spectral information as predictor of tensile properties achieved satisfactory results, with coefficients of prediction (R(2)C) of 0.83, 0.88 and 0.92 (calibration models) for elongation, tensile strength, and Young's modulus, respectively. Results corroborate the correlation of NIR spectra with tensile properties, showing that NIR spectroscopy has potential as a rapid analytical technology for non-destructive assessment of the mechanical properties of the films. Copyright © 2015 Elsevier B.V. All rights reserved.

Study of Vis/NIR spectroscopy measurement on acidity of yogurt

NASA Astrophysics Data System (ADS)

He, Yong; Feng, Shuijuan; Wu, Di; Li, Xiaoli

2006-09-01

A fast measurement of pH of yogurt using Vis/NIR-spectroscopy techniques was established in order to measuring the acidity of yogurt rapidly. 27 samples selected separately from five different brands of yogurt were measured by Vis/NIR-spectroscopy. The pH of yogurt on positions scanned by spectrum was measured by a pH meter. The mathematical model between pH and Vis/NIR spectral measurements was established and developed based on partial least squares (PLS) by using Unscramble V9.2. Then 25 unknown samples from 5 different brands were predicted based on the mathematical model. The result shows that The correlation coefficient of pH based on PLS model is more than 0.890, and standard error of calibration (SEC) is 0.037, standard error of prediction (SEP) is 0.043. Through predicting the pH of 25 samples of yogurt from 5 different brands, the correlation coefficient between predictive value and measured value of those samples is more than 0918. The results show the good to excellent prediction performances. The Vis/NIR spectroscopy technique had a significant greater accuracy for determining the value of pH. It was concluded that the VisINIRS measurement technique can be used to measure pH of yogurt fast and accurately, and a new method for the measurement of pH of yogurt was established.

Near-infrared spectroscopy (NIRS) as a new tool for neuroeconomic research

PubMed Central

Kopton, Isabella M.; Kenning, Peter

2014-01-01

Over the last decade, the application of neuroscience to economic research has gained in importance and the number of neuroeconomic studies has grown extensively. The most common method for these investigations is fMRI. However, fMRI has limitations (particularly concerning situational factors) that should be countered with other methods. This review elaborates on the use of functional Near-Infrared Spectroscopy (fNIRS) as a new and promising tool for investigating economic decision making both in field experiments and outside the laboratory. We describe results of studies investigating the reliability of prototype NIRS studies, as well as detailing experiments using conventional and stationary fNIRS devices to analyze this potential. This review article shows that further research using mobile fNIRS for studies on economic decision making outside the laboratory could be a fruitful avenue helping to develop the potential of a new method for field experiments outside the laboratory. PMID:25147517

Dynamic changes in near-infrared spectroscopy (NIRS) findings in first-episode schizophrenia: a case report.

PubMed

Hatakeyama, Tsuyoshi; Kunii, Yasuto; Miura, Itaru; Itagaki, Shuntaro; Kono, Soichi; Shiga, Tetsuya; Oshima, Sachie; Nozaki, Keiko; Suzuki, Rieko; Yabe, Hirooki

2017-04-28

The clinical course of schizophrenia is characterized by recurrence and chronicity and has a large burden on society.　Nevertheless, diagnosis of schizophrenia is based only on distinctive symptoms and the disease course.　Near-infrared spectroscopy (NIRS) is a useful method for measuring changes in the hemoglobin concentration in the cortical surface area and reflects brain function.　We measured NIRS four times during the clinical course in a patient with first-episode schizophrenia.A 17-year-old woman admitted to our hospital because of hallucinations, delusions and appetite loss. After treatment with low-dose antipsychotics, NIRS findings showed a prompt increase in the cerebral blood volume in the frontal region.　On the basis of the clinical course of this patient, we introduce a new point of view, namely, that NIRS findings may be useful as a state marker that indicates the severity of schizophrenia in some cases.

Dynamic changes in near-infrared spectroscopy (NIRS) findings in first-episode schizophrenia: a case report

PubMed Central

Hatakeyama, Tsuyoshi; Kunii, Yasuto; Miura, Itaru; Itagaki, Shuntaro; Kono, Soichi; Shiga, Tetsuya; Oshima, Sachie; Nozaki, Keiko; Suzuki, Rieko; Yabe, Hirooki

2017-01-01

Abstract The clinical course of schizophrenia is characterized by recurrence and chronicity and has a large burden on society. Nevertheless, diagnosis of schizophrenia is based only on distinctive symptoms and the disease course. Near-infrared spectroscopy (NIRS) is a useful method for measuring changes in the hemoglobin concentration in the cortical surface area and reflects brain function. We measured NIRS four times during the clinical course in a patient with first-episode schizophrenia. A 17-year-old woman admitted to our hospital because of hallucinations, delusions and appetite loss. After treatment with low-dose antipsychotics, NIRS findings showed a prompt increase in the cerebral blood volume in the frontal region. On the basis of the clinical course of this patient, we introduce a new point of view, namely, that NIRS findings may be useful as a state marker that indicates the severity of schizophrenia in some cases. PMID:28420824

Use of near infrared spectroscopy for the clinical monitoring of adult brain

NASA Astrophysics Data System (ADS)

Kirkpatrick, Peter J.; Smielewski, P.; Lam, J. M.; Al-Rawi, P.

1996-10-01

Adult near infrared spectroscopy (NIRS) is a potential method for noninvasively assessing changes in cerebral oxygenation. Unlike neonatal NIRS, access of light to the adult rain requires penetration through thick extracranial tissues, and hence detection of changed in cerebral chromophore concentration can only be achieved by using NIRS in the reflectance mode. This adds variables that are difficult to control. They include the effects of a different intraoptode distance, intersubject anatomical variation, and the influence of a pathological extra- to intracranial collateral blood supply. Although studies showing movements of oxyhemoglobin concentration following specific cerebral stimuli have been published, the separation of changes occurring in the extracranial and intracranial compartments remains a challenge. Experience with NIRS in the three adult clinical scenarios of carotid endarterectomy, head injury, and carbon dioxide stress testing is presented. The influence of extracranial contamination is demonstrated, as are the methods adopted to help control for extracranial blood flow changes. Provisional experience with spatially responded spectroscopy technology is also discussed.

Calibration sets selection strategy for the construction of robust PLS models for prediction of biodiesel/diesel blends physico-chemical properties using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Palou, Anna; Miró, Aira; Blanco, Marcelo; Larraz, Rafael; Gómez, José Francisco; Martínez, Teresa; González, Josep Maria; Alcalà, Manel

2017-06-01

Even when the feasibility of using near infrared (NIR) spectroscopy combined with partial least squares (PLS) regression for prediction of physico-chemical properties of biodiesel/diesel blends has been widely demonstrated, inclusion in the calibration sets of the whole variability of diesel samples from diverse production origins still remains as an important challenge when constructing the models. This work presents a useful strategy for the systematic selection of calibration sets of samples of biodiesel/diesel blends from diverse origins, based on a binary code, principal components analysis (PCA) and the Kennard-Stones algorithm. Results show that using this methodology the models can keep their robustness over time. PLS calculations have been done using a specialized chemometric software as well as the software of the NIR instrument installed in plant, and both produced RMSEP under reproducibility values of the reference methods. The models have been proved for on-line simultaneous determination of seven properties: density, cetane index, fatty acid methyl esters (FAME) content, cloud point, boiling point at 95% of recovery, flash point and sulphur.

Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces

NASA Astrophysics Data System (ADS)

Hwang, Han-Jeong; Lim, Jeong-Hwan; Kim, Do-Won; Im, Chang-Hwan

2014-07-01

A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a promising neuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS-based BCI studies have focused on enhancing the accuracy of the classification of different mental tasks. In the present study, we evaluated the performances of a variety of mental task combinations in order to determine the mental task pairs that are best suited for customized NIRS-based BCIs. To this end, we recorded event-related hemodynamic responses while seven participants performed eight different mental tasks. Classification accuracies were then estimated for all possible pairs of the eight mental tasks (C=28). Based on this analysis, mental task combinations with relatively high classification accuracies frequently included the following three mental tasks: "mental multiplication," "mental rotation," and "right-hand motor imagery." Specifically, mental task combinations consisting of two of these three mental tasks showed the highest mean classification accuracies. It is expected that our results will be a useful reference to reduce the time needed for preliminary tests when discovering individual-specific mental task combinations.

Component Analysis and Identification of Black Tahitian Cultured Pearls From the Oyster Pinctada margaritifera Using Spectroscopic Techniques

NASA Astrophysics Data System (ADS)

Shi, L.; Wang, Y.; Liu, X.; Mao, J.

2018-03-01

Raman spectroscopy, ultraviolet, visible, and near infrared (UV-Vis-NIR) reflectance spectroscopy, and X-ray fluorescence (XRF) spectroscopy were used to characterize black Tahitian cultured pearls and imitations of these saltwater cultured pearls produced by γ-irradiation, and by coloring of cultured pearls with silver nitrate or organic dyes. Raman spectra indicated that aragonite was the major constituent of these four types of pearl. Using Raman spectroscopy at an excitation wavelength of 514 nm, black Tahitian cultured pearls exhibited characteristic 1100-1700 cm-1 bands. These bands were attributed to various organic components, including conchiolin and other black biological pigments. The peaks shown by saltwater cultured pearls colored with organic dyes varied with the type of dye used. Tahitian cultured and organic-dye-treated saltwater cultured pearls were easily identified by Raman spectroscopy. UV-Vis-NIR reflectance spectra showed bands at 408, 497, and 700 nm derived from porphyrin pigment and other black pigments. The spectra of dye-treated black saltwater pearls showed absorption peaks at 216, 261, 300, and 578 nm. The 261-nm absorption band disappeared from the spectra of γ-irradiated saltwater cultured pearls. This suggests the degradation of conchiolin in the γ-irradiated saltwater cultured pearls. XRF analysis revealed the presence of Ag on the surface of silver nitrate-dyed saltwater cultured pearls.

A "NIRS" death experience: a reduction in cortical oxygenation by time-resolved near-infrared spectroscopy preceding cardiac arrest.

PubMed

Lanks, C; Kim, C B; Rossiter, H B

2017-09-08

Near-infrared spectroscopy (NIRS) has been used effectively post-cardiac-arrest to gauge adequacy of resuscitation and predict the likelihood of achieving a return of spontaneous circulation. However, preempting hemodynamic collapse is preferable to achieving ROSC through advanced cardiac life support. Minimizing "time down" without end-organ perfusion has always been a central pillar of ACLS. In many critically ill patients there is a prolonged phase of end-organ hypoperfusion preceding loss of palpable pulses and initiation of ACLS. Due to the relative infrequency of in-hospital cardiac arrest, NIRS has not previously evaluated the period immediately prior to hemodynamic collapse. Here we report a young man who suffered a pulseless electrical activity (PEA) arrest while cortical oxygenation was monitored using time-resolved near-infrared spectroscopy. The onset of cortical deoxygenation preceded the loss of palpable pulses by 15 min, suggesting that TRS-NIRS monitoring might provide a means of preempting PEA arrest. Our experience with this patient represents a promising new direction for continuous NIRS monitoring and has the potential to not only predict clinical outcomes, but affect them to the patient's benefit as well.

New NIR Calibration Models Speed Biomass Composition and Reactivity Characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-09-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. This highlight describes NREL's work to use near-infrared (NIR) spectroscopy and partial least squares multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. This highlight is being developed for the September 2015 Alliance S&T Board meeting.

Independent component analysis-based source-level hyperlink analysis for two-person neuroscience studies

NASA Astrophysics Data System (ADS)

Zhao, Yang; Dai, Rui-Na; Xiao, Xiang; Zhang, Zong; Duan, Lian; Li, Zheng; Zhu, Chao-Zhe

2017-02-01

Two-person neuroscience, a perspective in understanding human social cognition and interaction, involves designing immersive social interaction experiments as well as simultaneously recording brain activity of two or more subjects, a process termed "hyperscanning." Using newly developed imaging techniques, the interbrain connectivity or hyperlink of various types of social interaction has been revealed. Functional near-infrared spectroscopy (fNIRS)-hyperscanning provides a more naturalistic environment for experimental paradigms of social interaction and has recently drawn much attention. However, most fNIRS-hyperscanning studies have computed hyperlinks using sensor data directly while ignoring the fact that the sensor-level signals contain confounding noises, which may lead to a loss of sensitivity and specificity in hyperlink analysis. In this study, on the basis of independent component analysis (ICA), a source-level analysis framework is proposed to investigate the hyperlinks in a fNIRS two-person neuroscience study. The performance of five widely used ICA algorithms in extracting sources of interaction was compared in simulative datasets, and increased sensitivity and specificity of hyperlink analysis by our proposed method were demonstrated in both simulative and real two-person experiments.

Simultaneous determination of the impurity and radial tensile strength of reduced glutathione tablets by a high selective NIR-PLS method.

PubMed

Li, Juan; Jiang, Yue; Fan, Qi; Chen, Yang; Wu, Ruanqi

2014-05-05

This paper establishes a high-throughput and high selective method to determine the impurity named oxidized glutathione (GSSG) and radial tensile strength (RTS) of reduced glutathione (GSH) tablets based on near infrared (NIR) spectroscopy and partial least squares (PLS). In order to build and evaluate the calibration models, the NIR diffuse reflectance spectra (DRS) and transmittance spectra (TS) for 330 GSH tablets were accurately measured by using the optimized parameter values. For analyzing GSSG or RTS of GSH tablets, the NIR-DRS or NIR-TS were selected, subdivided reasonably into calibration and prediction sets, and processed appropriately with chemometric techniques. After selecting spectral sub-ranges and neglecting spectrum outliers, the PLS calibration models were built and the factor numbers were optimized. Then, the PLS models were evaluated by the root mean square errors of calibration (RMSEC), cross-validation (RMSECV) and prediction (RMSEP), and by the correlation coefficients of calibration (R(c)) and prediction (R(p)). The results indicate that the proposed models have good performances. It is thus clear that the NIR-PLS can simultaneously, selectively, nondestructively and rapidly analyze the GSSG and RTS of GSH tablets, although the contents of GSSG impurity were quite low while those of GSH active pharmaceutical ingredient (API) quite high. This strategy can be an important complement to the common NIR methods used in the on-line analysis of API in pharmaceutical preparations. And this work expands the NIR applications in the high-throughput and extraordinarily selective analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

NIR detection of pits and pit fragments in fresh cherries (abstract)

USDA-ARS?s Scientific Manuscript database

The feasibility of using near infrared (NIR) diffuse reflectance spectroscopy for the detection of pits and pit fragments in cherries was demonstrated. For detection of whole pits, 300 cherries were obtained locally and pits were removed from half. NIR reflectance spectra were obtained in triplicate...

Comparison of NIR and FT-IR spectral models in the prediction of cotton fiber strength

USDA-ARS?s Scientific Manuscript database

Strength quality in cotton fibers is one of several important end-use characteristics. In routine programs, it has been mostly assessed by automation-oriented high volume instrument (HVI) system. An alternative method for cotton strength is near infrared (NIR) spectroscopy. Although previous NIR mod...

Cotton micronaire measurements by small portable near infrared (nir) analyzers

USDA-ARS?s Scientific Manuscript database

A key quality and processing parameter for cotton fiber is micronaire, which is a function of the fiber’s maturity and fineness. Near Infrared (NIR) spectroscopy has previously shown the ability to measure micronaire, primarily in the laboratory and using large, research-grade laboratory NIR instru...

Effects of slash-and-burn land management on soil spectral properties estimated with VIS-NIR-SWIR spectroscopy

NASA Astrophysics Data System (ADS)

Rosero-Vlasova, Olga Alexandra; Vlassova, Lidia; Rosero Tufiño, Pedro; Pérez-Cabello, Fernando; Montorio Llovería, Raquel

2017-04-01

Slash-and-burn land management is typical for low-income tropical countries, such as Ecuador. It involves conversion of forest into areas used for agriculture. At first trees are cut and the wood debris is burnt. After initial clearing, biomass burning is performed after each production cycle. Usually, cultivation cycles are followed by the fallow period. In the medium and long term, these practices have negative effect on soil fertility and there is the need for clearing more forest for agricultural use. This is one of the reasons for continuing deforestation with the consequent loss of biodiversity. Changes in physico-chemical properties due to periodic burning are accompanied by changes in soil spectral properties and can be determined using VIS-NIR-SWIR spectroscopy, which can be a cost-effective alternative for traditional methods of soil analysis. The purpose of the study is to assess the viability of VIS-NIR-SWIR spectroscopy for characterization of soils from land areas under slash-and-burn management system. Eighteen samples from soil surface layer were collected from two corn fields in the province of Los Rios, Ecuador, in September 2015. One of the areas has experienced six slash-and-burn cycles, while in the other the samples were collected at the end of the first corn cultivation cycle. Spectral measurements of sieved and air-dried samples were performed in the laboratory of the University of Zaragoza using ASD Fieldspec®4 spectroradiometer (350-2500nm spectral range) and ASD Illuminator Lamp as a light source. Statistically significant differences were observed between soil spectra of the samples from two soil groups. Reflectance of repeatedly burnt soils was 20% higher (mean value for the entire spectrum) for 65% of the samples, being especially important in VIS (>45%) and NIR ( 35%), probably due to the lower organic matter (OM) content. OM models built using Partial least Squares Regression demonstrated high predictive capacity (R2>0.8). Thus, the study confirms VIS-NIR-SWIR soil spectroscopy can be used as a tool for monitoring changes in soils in areas of slash-and-burn land management systems.

Ability of near infrared spectroscopy to monitor air-dry density distribution and variation of wood

Treesearch

Brian K. Via; Chi-Leung So; Todd F. Shupe; Michael Stine; Leslie H. Groom

2005-01-01

Process control of wood density with near infrared spectroscopy (NIR) would be useful for pulp mills that need to maximize pulp yield without compromising paper strength properties. If models developed from the absorbance at wavelengths in the NIR region could provide density histograms, fiber supply personnel could monitor chip density variation as the chips enter the...

Regional calibration models for predicting loblolly pine tracheid properties using near-infrared spectroscopy

Treesearch

Mohamad Nabavi; Joseph Dahlen; Laurence Schimleck; Thomas L. Eberhardt; Cristian Montes

2018-01-01

This study developed regional calibration models for the prediction of loblolly pine (Pinus taeda) tracheid properties using near-infrared (NIR) spectroscopy. A total of 1842 pith-to-bark radial strips, aged 19–31 years, were acquired from 268 trees from 109 stands across the southeastern USA. Diffuse reflectance NIR spectra were collected at 10-mm...

Applications of NIR spectroscopy to monitoring and analyzing the solid state during industrial crystallization processes.

PubMed

Févotte, G; Calas, J; Puel, F; Hoff, C

2004-04-01

Fiber-optic near infrared (NIR) spectroscopy was used to investigate several key features of the polymorphic transitions observed during the crystallization and the filtration of SaC, an Active Pharmaceutical Ingredient (API) produced by Sanofi-Synthelabo. Using few samples, the spectroscopic data were calibrated to provide measurements of the polymorphic composition of the solid product which is likely to appear in two crystalline forms or in the amorphous state. Both qualitative and quantitative methods were successfully evaluated to characterize the API. The NIR spectroscopy measurement was then applied to investigate the kinetic behavior of the phase transition phenomena against various operating conditions. From the viewpoint of industrial process development several applications are presented. The effects of temperature and seed crystal habits on the rate of transition of filtration cakes are briefly investigated; and a study of the effect of residual water in the solvent on the transition occurring during filtration is more deeply analyzed. The experimental results demonstrate that highly valuable information can be provided by the NIR spectroscopy measurements, when one aims at understanding more deeply and optimizing the consequences of various and complex phenomena involved during the solid processing chain.

Predictive value of early near-infrared spectroscopy monitoring of patients with traumatic brain injury.

PubMed

Vilkė, Alina; Bilskienė, Diana; Šaferis, Viktoras; Gedminas, Martynas; Bieliauskaitė, Dalia; Tamašauskas, Arimantas; Macas, Andrius

2014-01-01

Traumatic brain injury (TBI) is the leading cause of death and disability in young adults. Study aimed to define the predictive value of early near-infrared spectroscopy (NIRS) monitoring of TBI patients in a Lithuanian clinical setting. Data of 61 patients was analyzed. Predictive value of early NIRS monitoring, computed tomography data and regular intensive care unit (ICU) parameters was investigated. Twenty-six patients expressed clinically severe TBI; 14 patients deceased. Patients who survived expressed higher NIRS values at the periods of admission to operative room (75.4%±9.8% vs. 71.0%±20.5%; P=0.013) and 1h after admission to ICU (74.7%±1.5% vs. 61.9%±19.4%; P=0.029). The NIRS values discriminated hospital mortality groups more accurately than admission GCS score, blood sugar or hemoglobin levels. Admission INR value and NIRS value at 1h after admission to ICU were selected by discriminant analysis into the optimal set of features when classifying hospital mortality groups. Average efficiency of classification using this method was 88.9%. When rsO2 values at 1h after admission to ICU did not exceed 68.0% in the left hemisphere and 68.3% in the right hemisphere, the hazard ratio for death increased by 17.7 times (P<0.01) and 5.1 times (P<0.05), respectively. NIRS plays an important role in the clinical care of TBI patients. Regional brain saturation monitoring provides accurate predictive data, which can improve the allocation of scarce medical resources, set the treatment goals and alleviate the early communication with patients' relatives. Copyright © 2014 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Simulated In Situ Determination of Soil Profile Organic and Inorganic Carbon With LIBS and VisNIR

NASA Astrophysics Data System (ADS)

Bricklemyer, R. S.; Brown, D. J.; Clegg, S. M.; Barefield, J. E.

2008-12-01

There is growing need for rapid, accurate, and inexpensive methods to measure, and verify soil organic carbon (SOC) change for national greenhouse gas accounting and the development of a soil carbon trading market. Laser Induced Breakdown Spectroscopy (LIBS) and Visible and Near Infrared Spectroscopy (VisNIR) are complementary analytical techniques that have the potential to fill that need. The LIBS method provides precise elemental analysis of soils, but generally cannot distinguish between organic C and inorganic C. VisNIR has been established as a viable technique for measuring soil properties including SOC and inorganic carbon (IC). As part of the Big Sky Carbon Sequestration Regional Partnership, 240 intact core samples (3.8 x 50 cm) have been collected from six agricultural fields in north central Montana, USA. Each of these core samples were probed concurrently with LIBS and VisNIR at 2.5, 7.5, 12.5, 17.5, 22.5, 27.5, 35 and 45 cm (+/- 1.5 cm) depths. VisNIR measurements were taken using an Analytical Spectral Devices (ASD, Boulder, CO, USA) Agrispec spectrometer to determine the partition of SOC vs. IC in the samples. The LIBS scans were collected with the LANL LIBS Core Scanner Instrument which collected the entire 200 - 900 nm plasma emission including the 247.8 nm carbon emission line. This instrument also collected the emission from the elements typically found in inorganic carbon (Ca and Mg) and organic carbon (H, O, and N). Subsamples of soil (~ 4 g) were taken from interrogation points for laboratory determination of SOC and IC. Using this analytical data, we constructed several full spectrum multivariate VisNIR/LIBS calibration models for SOC and IC. These models were then applied to independent validation cores for model evaluation.

Fast gas spectroscopy using pulsed quantum cascade lasers

NASA Astrophysics Data System (ADS)

Beyer, T.; Braun, M.; Lambrecht, A.

2003-03-01

Laser spectroscopy has found many industrial applications, e.g., control of automotive exhaust and process monitoring. The midinfrared region is of special interest because it has stronger absorption lines compared to the near infrared (NIR). However, in the NIR high quality reliable laser sources, detectors, and passive optical components are available. A quantum cascade laser could change this situation if fundamental advantages can be exploited with compact and reliable systems. It will be shown that, using pulsed lasers and available fast detectors, lower residual sensitivity levels than in corresponding NIR systems can be achieved. The stability is sufficient for industrial applications.

A Review on the Role of Vibrational Spectroscopy as An Analytical Method to Measure Starch Biochemical and Biophysical Properties in Cereals and Starchy Foods

PubMed Central

Cozzolino, D.; Degner, S.; Eglinton, J.

2014-01-01

Starch is the major component of cereal grains and starchy foods, and changes in its biophysical and biochemical properties (e.g., amylose, amylopectin, pasting, gelatinization, viscosity) will have a direct effect on its end use properties (e.g., bread, malt, polymers). The use of rapid and non-destructive methods to study and monitor starch properties, such as gelatinization, retrogradation, water absorption in cereals and starchy foods, is of great interest in order to improve and assess their quality. In recent years, near infrared reflectance (NIR) and mid infrared (MIR) spectroscopy have been explored to predict several quality parameters, such as those generated by instrumental methods commonly used in routine analysis like the rapid visco analyser (RVA) or viscometers. In this review, applications of both NIR and MIR spectroscopy to measure and monitor starch biochemical (amylose, amylopectin, starch) and biophysical properties (e.g., pasting properties) will be presented and discussed. PMID:28234340

Fourier transform near-infrared spectroscopy application for sea salt quality evaluation.

PubMed

Galvis-Sánchez, Andrea C; Lopes, João Almeida; Delgadillo, Ivonne; Rangel, António O S S

2011-10-26

Near-infrared (NIR) spectroscopy in diffuse reflectance mode was explored with the objective of discriminating sea salts according to their quality type (traditional salt vs "flower of salt") and geographical origin (Atlantic vs Mediterranean). Sea salts were also analyzed in terms of Ca(2+), Mg(2+), K(+), alkalinity, and sulfate concentrations to support spectroscopic results. High concentrations of Mg(2+) and K(+) characterized Atlantic samples, while a high Ca(2+) content was observed in traditional sea salts. A partial least-squares discriminant analysis model considering the 8500-7500 cm(-1) region permitted the discrimination of salts by quality types. The regions 4650-4350 and 5900-5500 cm(-1) allowed salts classification according to their geographical origin. It was possible to classify correctly 85.3 and 94.8% of the analyzed samples according to the salt type and to the geographical origin, respectively. These results demonstrated that NIR spectroscopy is a suitable and very efficient tool for sea salt quality evaluation.

UV Raman detection of 2,4-DNT in contact with sand particles

NASA Astrophysics Data System (ADS)

Blanco, Alejandro; Pacheco-Londoño, Leonardo C.; Peña-Quevedo, Alvaro J.; Hernández-Rivera, Samuel P.

2006-05-01

Deep Ultra Violet Raman Spectroscopy (DUV-RS) is an emerging tool for vibrational spectroscopy analysis and can be used in Point Detection mode to detect explosive components of landmines and Improvised Explosive Devices (IED). Interactions of explosives with different substrates can be measured by using quantitative vibrational signal shift information of scattered Raman light associated with these interactions. In this research, grounds were laid for detection of explosives using UV-Raman Spectroscopy equipped with 244 nm laser excitation line from a 488 nm frequency doubled Coherent FreD laser. In other experiments, samples of 2,4-DNT were allowed to interact with Ottawa Sand and were studied using DUV-RS. Characteristic vibrational signals of energetic compounds were analyzed in the ranges: 400-1200 cm -1, 1200-1800 cm -1, and 2800-3500 cm -1. In addition these Raman spectra were compared with dispersive spectra that were acquired using Raman Microscopy equipped with 514.5 nm (VIS) 785 nm (NIR) and 1064 nm (NIR) excitation lasers.

Prediction of Cortisol and Progesterone Concentrations in Cow Hair Using Near-Infrared Reflectance Spectroscopy (NIRS).

PubMed

Tallo-Parra, Oriol; Albanell, Elena; Carbajal, Annais; Monclús, Laura; Manteca, Xavier; Lopez-Bejar, Manel

2017-08-01

Concentrations of different steroid hormones have been used in cows as a measure of adrenal or gonadal activity and, thus, as indicators of stress or reproductive state. Detecting cortisol and progesterone in cow hair provides a long-term integrative value of retrospective adrenal or gonadal/placental activity, respectively. Current techniques for steroid detection require a hormone-extraction procedure that involves time, several types of equipment, management of reagents, and some assay procedures (which can also be time-consuming and can destroy the samples). In contrast, near-infrared reflectance spectroscopy (NIRS) is a multi-component predictor technique, characterized as rapid, nondestructive for the sample, and reagent-free. However, as a predictor technique, NIRS needs to be calibrated and validated for each matrix, hormone, and species. The main objective of this study was to evaluate the predictive value of the NIRS technique for hair cortisol and progesterone quantification in cows by using specific enzyme immunoassay as a reference method. Hair samples from 52 adult Friesian lactating cows from a commercial dairy farm were used. Reflectance spectra of hair samples were determined with a NIR reflectance spectrophotometer before and after trimming them. Although similar results were obtained, a slightly better relationship between the reference data and NIRS predicted values was found using trimmed samples. Near infrared reflectance spectroscopy demonstrated its ability to predict cortisol and progesterone concentrations with certain accuracy (R 2  = 0.90 for cortisol and R 2  = 0.87 for progesterone). Although NIRS is far from being a complete alternative to current methodologies, the proposed equations can offer screening capability. Considering the advantages of both fields, our results open the possibility for future work on the combination of hair steroid measurement and NIRS methodology.

Adaptable Near-Infrared Spectroscopy Fiber Array for Improved Coupling to Different Breast Sizes During Clinical MRI

PubMed Central

Mastanduno, Michael A.; El-Ghussein, Fadi; Jiang, Shudong; DiFlorio-Alexander, Roberta; Junqing, Xu; Hong, Yin; Pogue, Brian W.; Paulsen, Keith D.

2016-01-01

Rationale and Objectives Near-infrared spectroscopy (NIRS) of breast can provide functional information on the vascular and structural compartments of tissues in regions identified during simultaneous magnetic resonance imaging (MRI). NIRS can be acquired during dynamic contrast-enhanced MRI (DCE-MRI) to accomplish image-guided spectroscopy of the enhancing regions, potentially increasing the diagnostic specificity of the examination and reducing the number of biopsies performed as a result of inconclusive MRI breast imaging studies. Materials and Methods We combine synergistic attributes of concurrent DCE-MRI and NIRS with a new design of the clinical NIRS breast interface that couples to a standard MR breast coil and allows imaging of variable breast sizes. Spectral information from healthy volunteers and cancer patients is recovered, providing molecular information in regions defined by the segmented MR image volume. Results The new coupling system significantly improves examination utility by allowing improved coupling of the NIR fibers to breasts of all cup sizes and lesion locations. This improvement is demonstrated over a range of breast sizes (cup size A through D) and normal tissue heterogeneity using a group of eight healthy volunteers and two cancer patients. Lesions located in the axillary region and medial-posterior breast are now accessible to NIRS optodes. Reconstructed images were found to have biologically plausible hemoglobin content, oxygen saturation, and water and lipid fractions. Conclusions In summary, a new NIRS/MRI breast interface was developed to accommodate the variation in breast sizes and lesion locations that can be expected in clinical practice. DCE-MRI–guided NIRS quantifies total hemoglobin, oxygenation, and scattering in MR-enhancing regions, increasing the diagnostic information acquired from MR examinations. PMID:24439327

Utilization of functional near infrared spectroscopy for non-invasive evaluation

NASA Astrophysics Data System (ADS)

Halim, A. A. A.; Laili, M. H.; Aziz, N. A.; Laili, A. R.; Salikin, M. S.; Rusop, M.

2016-07-01

The goal of this brief review is to report the techniques of functional near infrared spectroscopy for non-invasive evaluation in human study. The development of functional near infrared spectroscopy (fNIRS) technologies has advanced quantification signal using multiple wavelength and detector to solve the propagation of light inside the tissues including the absorption, scattering coefficient and to define the light penetration into tissues multilayers. There are a lot of studies that demonstrate signal from fNIRS which can be used to evaluate the changes of oxygenation level and measure the limitation of muscle performance in human brain and muscle tissues. Comprehensive reviews of diffuse reflectance based on beer lambert law theory were presented in this paper. The principle and development of fNIRS instrumentation is reported in detail.

Detection of Cell Wall Chemical Variation in Zea Mays Mutants Using Near-Infrared Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buyck, N.; Thomas, S.

Corn stover is regarded as the prime candidate feedstock material for commercial biomass conversion in the United States. Variations in chemical composition of Zea mays cell walls can affect biomass conversion process yields and economics. Mutant lines were constructed by activating a Mu transposon system. The cell wall chemical composition of 48 mutant families was characterized using near-infrared (NIR) spectroscopy. NIR data were analyzed using a multivariate statistical analysis technique called Principal Component Analysis (PCA). PCA of the NIR data from 349 maize leaf samples reveals 57 individuals as outliers on one or more of six Principal Components (PCs) atmore » the 95% confidence interval. Of these, 19 individuals from 16 families are outliers on either PC3 (9% of the variation) or PC6 (1% of the variation), the two PCs that contain information about cell wall polymers. Those individuals for which altered cell wall chemistry is confirmed with wet chemical analysis will then be subjected to fermentation analysis to determine whether or not biomass conversion process kinetics, yields and/or economics are significantly affected. Those mutants that provide indications for a decrease in process cost will be pursued further to identify the gene(s) responsible for the observed changes in cell wall composition and associated changes in process economics. These genes will eventually be incorporated into maize breeding programs directed at the development of a truly dual use crop.« less

Rapid and simultaneous analysis of five alkaloids in four parts of Coptidis Rhizoma by near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Jintao, Xue; Yufei, Liu; Liming, Ye; Chunyan, Li; Quanwei, Yang; Weiying, Wang; Yun, Jing; Minxiang, Zhang; Peng, Li

2018-01-01

Near-Infrared Spectroscopy (NIRS) was first used to develop a method for rapid and simultaneous determination of 5 active alkaloids (berberine, coptisine, palmatine, epiberberine and jatrorrhizine) in 4 parts (rhizome, fibrous root, stem and leaf) of Coptidis Rhizoma. A total of 100 samples from 4 main places of origin were collected and studied. With HPLC analysis values as calibration reference, the quantitative analysis of 5 marker components was performed by two different modeling methods, partial least-squares (PLS) regression as linear regression and artificial neural networks (ANN) as non-linear regression. The results indicated that the 2 types of models established were robust, accurate and repeatable for five active alkaloids, and the ANN models was more suitable for the determination of berberine, coptisine and palmatine while the PLS model was more suitable for the analysis of epiberberine and jatrorrhizine. The performance of the optimal models was achieved as follows: the correlation coefficient (R) for berberine, coptisine, palmatine, epiberberine and jatrorrhizine was 0.9958, 0.9956, 0.9959, 0.9963 and 0.9923, respectively; the root mean square error of validation (RMSEP) was 0.5093, 0.0578, 0.0443, 0.0563 and 0.0090, respectively. Furthermore, for the comprehensive exploitation and utilization of plant resource of Coptidis Rhizoma, the established NIR models were used to analysis the content of 5 active alkaloids in 4 parts of Coptidis Rhizoma and 4 main origin of places. This work demonstrated that NIRS may be a promising method as routine screening for off-line fast analysis or on-line quality assessment of traditional Chinese medicine (TCM).

Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Virtanen, Jaakko; Noponen, Tommi; Kotilahti, Kalle; Virtanen, Juha; Ilmoniemi, Risto J.

2011-08-01

In medical near-infrared spectroscopy (NIRS), movements of the subject often cause large step changes in the baselines of the measured light attenuation signals. This prevents comparison of hemoglobin concentration levels before and after movement. We present an accelerometer-based motion artifact removal (ABAMAR) algorithm for correcting such baseline motion artifacts (BMAs). ABAMAR can be easily adapted to various long-term monitoring applications of NIRS. We applied ABAMAR to NIRS data collected in 23 all-night sleep measurements and containing BMAs from involuntary movements during sleep. For reference, three NIRS researchers independently identified BMAs from the data. To determine whether the use of an accelerometer improves BMA detection accuracy, we compared ABAMAR to motion detection based on peaks in the moving standard deviation (SD) of NIRS data. The number of BMAs identified by ABAMAR was similar to the number detected by the humans, and 79% of the artifacts identified by ABAMAR were confirmed by at least two humans. While the moving SD of NIRS data could also be used for motion detection, on average 2 out of the 10 largest SD peaks in NIRS data each night occurred without the presence of movement. Thus, using an accelerometer improves BMA detection accuracy in NIRS.

Saphenous vein graft near-infrared spectroscopy imaging insights from the lipid core plaque association with clinical events near-infrared spectroscopy (ORACLE-NIRS) registry.

PubMed

Danek, Barbara A; Karatasakis, Aris; Alame, Aya J; Nguyen-Trong, Phuong-Khanh J; Karacsonyi, Judit; Rangan, Bavana; Roesle, Michele; Atwell, Amy; Resendes, Erica; Martinez-Parachini, Jose Roberto; Iwnetu, Rahel; Kalsaria, Pratik; Siddiqui, Furqan; Muller, James E; Banerjee, Subhash; Brilakis, Emmanouil

2017-05-01

We sought to examine near-infrared spectroscopy (NIRS) imaging findings of aortocoronary saphenous vein grafts (SVGs). SVGs are prone to develop atherosclerosis similar to native coronary arteries. They have received little study using NIRS. We examined the clinical characteristics and imaging findings from 43 patients who underwent NIRS imaging of 45 SVGs at our institution between 2009 and 2016. The mean patient age was 67 ± 7 years and 98% were men, with high prevalence of diabetes mellitus (56%), hypertension (95%), and dyslipidemia (95%). Mean SVG age was 7 ± 7 years, mean SVG lipid core burden index (LCBI) was 53 ± 60 and mean maxLCBI 4 mm was 194 ± 234. Twelve SVGs (27%) had lipid core plaques (2 yellow blocks on the block chemogram), with a higher prevalence in SVGs older than 5 years (46% vs. 5%, P = 0.002). Older SVG age was associated with higher LCBI (r = 0.480, P < 0.001) and higher maxLCBI 4 mm (r = 0.567, P < 0.001). On univariate analysis, greater annual total cholesterol exposure was associated with higher SVG LCBI (r = 0.30, P = 0.042) and annual LDL-cholesterol and triglyceride exposure were associated with higher SVG maxLCBI 4 mm (LDL-C: r = 0.41, P = 0.020; triglycerides: r = 0.36, P = 0.043). On multivariate analysis, the only independent predictor of SVG LCBI and maxLCBI 4mm was SVG age. SVG percutaneous coronary intervention was performed in 63% of the patients. An embolic protection device was used in 96% of SVG PCIs. Periprocedural myocardial infarction occurred in one patient. Older SVG age and greater lipid exposure are associated with higher SVG lipid burden. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

VIS/NIR reflectance and fluorescence spectrometric studies of minerals, water, organics and biomarkers in MoonMars analogue samples

NASA Astrophysics Data System (ADS)

Vos, Heleen; Foing, Bernard; Kołodziejczyk, Agata; Vago, Jorge; Harasymczuk, Matt

2017-04-01

This study focuses on the detection and characterisation of elements, minerals, volatiles and organics using reflectance spectrometry. The goal is to create a calibration method to enable the use of spectrometers on analogue Moon/Mars missions and on a lander. For this study we use measurements that are done in the VIS and NIR spectrum, as well as fluorescence using different spectrometers. The first part of the study consists of measurements that are performed in a laboratory to create a calibration method. Different rock samples and soils are analysed and the reflectance and absorption of minerals, water, organics and biomarkers are measured. Also the influence of the grain size, light source and surroundings is being determined. An experiment on the reflectance spectra of plant growth in different soils is also done to determine the possibilities of detecting the presence of chlorophyll and other biomarkers, and to diagnose the growth and health of a plant. This analysis can result in a monitoring method for a Moon greenhouse, but also for general surface analysis. Using VIS and NIR spectrometry has a couple of advantages, one being the fact that measurements require no sample preparation, and also the small size of the spectrometer makes it an easy tool for different analyses on board space missions. However, VIS and NIR spectroscopy have detection limits which makes only certain characteristics detectable. Besides laboratory measurements, the different spectroscopy methods are tested during a field campaign in the Eifel, Germany. During this campaign we can determine the functionality of the spectrometer in the field and on a lander and the problems that can rise when a spectrometer is controlled from a distant or by a person who is not trained in using spectroscopy. These laboratory and field measurements can help in the scientific preparation for instruments on ExoMars rover, future MoonMars lander missions and for the MoonVillage.

Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering

PubMed Central

Zhang, Xian; Noah, Jack Adam; Hirsch, Joy

2016-01-01

Abstract. Global systemic effects not specific to a task can be prominent in functional near-infrared spectroscopy (fNIRS) signals and the separation of task-specific fNIRS signals and global nonspecific effects is challenging due to waveform correlations. We describe a principal component spatial filter algorithm for separation of the global and local effects. The effectiveness of the approach is demonstrated using fNIRS signals acquired during a right finger-thumb tapping task where the response patterns are well established. Both the temporal waveforms and the spatial pattern consistencies between oxyhemoglobin and deoxyhemoglobin signals are significantly improved, consistent with the basic physiological basis of fNIRS signals and the expected pattern of activity associated with the task. PMID:26866047

Near-infrared Spectroscopy in the Brewing Industry.

PubMed

Sileoni, Valeria; Marconi, Ombretta; Perretti, Giuseppe

2015-01-01

This article offers an exhaustive description of the use of Near-Infrared (NIR) Spectroscopy in the brewing industry. This technique is widely used for quality control testing of raw materials, intermediates, and finished products, as well as process monitoring during malting and brewing. In particular, most of the reviewed works focus on the assessment of barley properties, aimed at quickly selecting the best barley varieties in order to produce a high-quality malt leading to high-quality beer. Various works concerning the use of NIR in the evaluation of raw materials, such as barley, malt, hop, and yeast, are also summarized here. The implementation of NIR sensors for the control of malting and brewing processes is also highlighted, as well as the use of NIR for quality assessment of the final product.

Multipoint NIR spectroscopy for gross composition analysis of powdered infant formula under various motion conditions.

PubMed

Cama-Moncunill, Raquel; Markiewicz-Keszycka, Maria; Dixit, Yash; Cama-Moncunill, Xavier; Casado-Gavalda, Maria P; Cullen, Patrick J; Sullivan, Carl

2016-07-01

Powdered infant formula (PIF) is a worldwide, industrially produced, human milk substitute. Manufacture of PIF faces strict quality controls in order to ensure that the product meets all compositional requirements. Near-infrared (NIR) spectroscopy is a rapid, non-destructive and well-qualified technique for food quality assessments. The use of fibre-optic NIR sensors allows measuring in-line and at real-time, and can record spectra from different stages of the process. The non-contact character of fibre-optic sensors can be enhanced by fitting collimators, which allow operation at various distances. The system, based on a Fabry-Perot interferometer, records four spectra concurrently, rather than consecutively as in the "quasi-simultaneous" multipoint NIR systems. In the present study, a novel multipoint NIR spectroscopy system equipped with four fibre-optic probes with collimators was assessed to determine carbohydrate and protein contents of PIF samples under static and motion conditions (0.02, 0.15 and 0.30m/s) to simulate possible industrial scenarios. Best results were obtained under static conditions providing a R(2) of calibration of 0.95 and RMSEP values of 1.89%. Yet, considerably low values of RMSEP, for instance 2.70% at 0.15m/s, were provided with the in-motion predictions, demonstrating the system's potential for in/on-line applications at various levels of speed. The current work also evaluated the viability of using general off-line calibrations developed under static conditions for on/in-line applications subject to motion. To this end, calibrations in both modes were developed and compared. Best results were obtained with specific calibrations; however, reasonably accurate models were obtained with the general calibration. Furthermore, this work illustrated independency of the collimator-probe setup by characterizing PIF samples simultaneously recorded according to their carbohydrate content, even when measured under different conditions. Therefore, the improved multipoint NIR approach constitutes a potential in/on-line tool for quality evaluation of PIF over the manufacturing process. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of silage composition by near-infrared reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Reeves, James B., III; Blosser, Timothy H.; Colenbrander, V. F.

1991-02-01

Two studies were performed to investigate the feasibility of using near infrared reflectance spectroscopy (NIRS) with undried silages. In the first study silages were analyzed for major components (e. g. dry matter crude protein and other forms of nitrogen fiber and in vitro digestible dry matter) and short chain fatty acids (SCFA). NIRS was found to operate satisfactorily except for some forms of nitrogen and SCFA. In study two various methods of grinding spectral regions and sample presentation were examined. Undried Wiley ground samples in a rectangular cell gave the best overall results for non-dry ice undried grinds with wavelengths between 1100 and 2498 nm. Silages scanned after drying however produced the best results. Intact samples did not perform as well as ground samples and wavelengths below 1100 nm were of little use. 2 .

Application of visible and near-infrared spectroscopy to classification of Miscanthus species

DOE PAGES

Jin, Xiaoli; Chen, Xiaoling; Xiao, Liang; ...

2017-04-03

Here, the feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validationmore » results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.« less

Mapping cerebrovascular reactivity using concurrent fMRI and near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tong, Yunjie; Bergethon, Peter R.; Frederick, Blaise d.

2011-02-01

Cerebrovascular reactivity (CVR) reflects the compensatory dilatory capacity of cerebral vasculature to a dilatory stimulus and is an important indicator of brain vascular reserve. fMRI has been proven to be an effective imaging technique to obtain the CVR map when the subjects perform CO2 inhalation or the breath holding task (BH). However, the traditional data analysis inaccurately models the BOLD using a boxcar function with fixed time delay. We propose a novel way to process the fMRI data obtained during a blocked BH by using the simultaneously collected near infrared spectroscopy (NIRS) data as regressor1. In this concurrent NIRS and fMRI study, 6 healthy subjects performed a blocked BH (5 breath holds with 20s durations intermitted by 40s of regular breathing). A NIRS probe of two sources and two detectors separated by 3 cm was placed on the right side of prefrontal area of the subjects. The time course of changes in oxy-hemoglobin (Δ[HbO]) was calculated from NIRS data and shifted in time by various amounts, and resampled to the fMRI acquisition rate. Each shifted time course was used as regressor in FEAT (the analysis tool in FSL). The resulting z-statistic maps were concatenated in time and the maximal value was taken along the time for all the voxels to generate a 3-D CVR map. The new method produces more accurate and thorough CVR maps; moreover, it enables us to produce a comparable baseline cerebral vascular map if applied to resting state (RS) data.

Tracking the dehydration process of raw honey by synchronous two-dimensional near infrared correlation spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Guiyun; Sun, Xin; Huang, Yuping; Chen, Kunjie

2014-11-01

Though much attention is paid to honey quality assessment, few reports on characteristic of manually dehydrated honey have been found. The aim of this investigation is to track the dehydration process of raw honey using synchronous two-dimensional (2D) near infrared correlation spectroscopy. To minimize the impact of dehydration to honey quality, seventy-two honey samples from six different dehydration stages were obtained using drum wind drying method with temperature controlled at 40 °C. Their dynamic short-wave NIR spectra from 600 to 1100 nm were collected in the transmission mode from 10 to 50 °C with an increment of 5 °C and were analyzed using synchronous two-dimensional correlation method. Short-wave NIR spectral data has been exploited less than other NIR region for its weaker signal especially for water absorption's interference with useful information. The investigation enlarged the signal at this band using synchronous 2D correlation analysis, revealing the fingerprinting feature of rape honey and chaste honey during the artificial dehydration process. The results have shown that, with the help of 2D correlation analysis, this band can detect the variation of the second overtone of O-H and N-H groups vibration upon their H-bonds forming or collapsing resulted from the interactions between water and solute. The results have also shown that 2D-NIRS method is able to convert the tiny changes in honey constituents into the detectable fingerprinting difference, which provides a new method for assessing honey quality.

Application of visible and near-infrared spectroscopy to classification of Miscanthus species

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Xiaoli; Chen, Xiaoling; Xiao, Liang

Here, the feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validationmore » results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.« less

Application of visible and near-infrared spectroscopy to classification of Miscanthus species.

PubMed

Jin, Xiaoli; Chen, Xiaoling; Xiao, Liang; Shi, Chunhai; Chen, Liang; Yu, Bin; Yi, Zili; Yoo, Ji Hye; Heo, Kweon; Yu, Chang Yeon; Yamada, Toshihiko; Sacks, Erik J; Peng, Junhua

2017-01-01

The feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validation results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.

Application of visible and near-infrared spectroscopy to classification of Miscanthus species

PubMed Central

Shi, Chunhai; Chen, Liang; Yu, Bin; Yi, Zili; Yoo, Ji Hye; Heo, Kweon; Yu, Chang Yeon; Yamada, Toshihiko; Sacks, Erik J.; Peng, Junhua

2017-01-01

The feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validation results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species. PMID:28369059

Analysis of ecstasy tablets: comparison of reflectance and transmittance near infrared spectroscopy.

PubMed

Schneider, Ralph Carsten; Kovar, Karl-Artur

2003-07-08

Calibration models for the quantitation of commonly used ecstasy substances have been developed using near infrared spectroscopy (NIR) in diffuse reflectance and in transmission mode by applying seized ecstasy tablets for model building and validation. The samples contained amphetamine, N-methyl-3,4-methylenedioxy-amphetamine (MDMA) and N-ethyl-3,4-methylenedioxy-amphetamine (MDE) in different concentrations. All tablets were analyzed using high performance liquid chromatography (HPLC) with diode array detection as reference method. We evaluated the performance of each NIR measurement method with regard to its ability to predict the content of each tablet with a low root mean square error of prediction (RMSEP). Best calibration models could be generated by using NIR measurement in transmittance mode with wavelength selection and 1/x-transformation of the raw data. The models build in reflectance mode showed higher RMSEPs using as data pretreatment, wavelength selection, 1/x-transformation and a second order Savitzky-Golay derivative with five point smoothing was applied to obtain the best models. To estimate the influence of inhomogeneities in the illegal tablets, a calibration of the destroyed, i.e. triturated samples was build and compared to the corresponding data of the whole tablets. The calibrations using these homogenized tablets showed lower RMSEPs. We can conclude that NIR analysis of ecstasy tablets in transmission mode is more suitable than measurement in diffuse reflectance to obtain quantification models for their active ingredients with regard to low errors of prediction. Inhomogeneities in the samples are equalized when measuring the tablets as powdered samples.

[Influence of sample surface roughness on mathematical model of NIR quantitative analysis of wood density].

PubMed

Huang, An-Min; Fei, Ben-Hua; Jiang, Ze-Hui; Hse, Chung-Yun

2007-09-01

Near infrared spectroscopy is widely used as a quantitative method, and the main multivariate techniques consist of regression methods used to build prediction models, however, the accuracy of analysis results will be affected by many factors. In the present paper, the influence of different sample roughness on the mathematical model of NIR quantitative analysis of wood density was studied. The result of experiments showed that if the roughness of predicted samples was consistent with that of calibrated samples, the result was good, otherwise the error would be much higher. The roughness-mixed model was more flexible and adaptable to different sample roughness. The prediction ability of the roughness-mixed model was much better than that of the single-roughness model.

A correlative study on data from pork carcass and processed meat (Bauernspeck) for automatic estimation of chemical parameters by means of near-infrared spectroscopy.

PubMed

Boschetti, Lucio; Ottavian, Matteo; Facco, Pierantonio; Barolo, Massimiliano; Serva, Lorenzo; Balzan, Stefania; Novelli, Enrico

2013-11-01

The use of near-infrared spectroscopy (NIRS) is proposed in this study for the characterization of the quality parameters of a smoked and dry-cured meat product known as Bauernspeck (originally from Northern Italy), as well as of some technological traits of the pork carcass used for its manufacturing. In particular, NIRS is shown to successfully estimate several key quality parameters (including water activity, moisture, dry matter, ash and protein content), suggesting its suitability for real time application in replacement of expensive and time consuming chemical analysis. Furthermore, a correlative approach based on canonical correlation analysis was used to investigate the spectral regions that are mostly correlated to the characteristics of interest. The identification of these regions, which can be linked to the absorbance of the main functional chemical groups, is intended to provide a better understanding of the chemical structure of the substrate under investigation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Neuroimaging with functional near infrared spectroscopy: From formation to interpretation

NASA Astrophysics Data System (ADS)

Herrera-Vega, Javier; Treviño-Palacios, Carlos G.; Orihuela-Espina, Felipe

2017-09-01

Functional Near Infrared Spectroscopy (fNIRS) is gaining momentum as a functional neuroimaging modality to investigate the cerebral hemodynamics subsequent to neural metabolism. As other neuroimaging modalities, it is neuroscience's tool to understand brain systems functions at behaviour and cognitive levels. To extract useful knowledge from functional neuroimages it is critical to understand the series of transformations applied during the process of the information retrieval and how they bound the interpretation. This process starts with the irradiation of the head tissues with infrared light to obtain the raw neuroimage and proceeds with computational and statistical analysis revealing hidden associations between pixels intensities and neural activity encoded to end up with the explanation of some particular aspect regarding brain function.To comprehend the overall process involved in fNIRS there is extensive literature addressing each individual step separately. This paper overviews the complete transformation sequence through image formation, reconstruction and analysis to provide an insight of the final functional interpretation.

Comparison of near infrared spectra within broiler breast fillets deboned at different postmortem time

USDA-ARS?s Scientific Manuscript database

Near infrared (NIR) spectroscopy has been used to predict texture quality of broiler breast fillets. Sampling is an important issue in NIR measurements to obtain accurate results. There are no research papers about sampling of chicken breast fillet for NIR measurement. The objective of this study wa...

Mental stress assessment using simultaneous measurement of EEG and fNIRS

PubMed Central

Al-Shargie, Fares; Kiguchi, Masashi; Badruddin, Nasreen; Dass, Sarat C.; Hani, Ahmad Fadzil Mohammad; Tang, Tong Boon

2016-01-01

Previous studies reported mental stress as one of the major contributing factors leading to various diseases such as heart attack, depression and stroke. An accurate stress assessment method may thus be of importance to clinical intervention and disease prevention. We propose a joint independent component analysis (jICA) based approach to fuse simultaneous measurement of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) on the prefrontal cortex (PFC) as a means of stress assessment. For the purpose of this study, stress was induced by using an established mental arithmetic task under time pressure with negative feedback. The induction of mental stress was confirmed by salivary alpha amylase test. Experiment results showed that the proposed fusion of EEG and fNIRS measurements improves the classification accuracy of mental stress by +3.4% compared to EEG alone and +11% compared to fNIRS alone. Similar improvements were also observed in sensitivity and specificity of proposed approach over unimodal EEG/fNIRS. Our study suggests that combination of EEG (frontal alpha rhythm) and fNIRS (concentration change of oxygenated hemoglobin) could be a potential means to assess mental stress objectively. PMID:27867700

Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial

PubMed Central

Aasted, Christopher M.; Yücel, Meryem A.; Cooper, Robert J.; Dubb, Jay; Tsuzuki, Daisuke; Becerra, Lino; Petkov, Mike P.; Borsook, David; Dan, Ippeita; Boas, David A.

2015-01-01

Abstract. Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that is used to noninvasively measure cerebral hemoglobin concentration changes induced by brain activation. Using structural guidance in fNIRS research enhances interpretation of results and facilitates making comparisons between studies. AtlasViewer is an open-source software package we have developed that incorporates multiple spatial registration tools to enable structural guidance in the interpretation of fNIRS studies. We introduce the reader to the layout of the AtlasViewer graphical user interface, the folder structure, and user files required in the creation of fNIRS probes containing sources and detectors registered to desired locations on the head, evaluating probe fabrication error and intersubject probe placement variability, and different procedures for estimating measurement sensitivity to different brain regions as well as image reconstruction performance. Further, we detail how AtlasViewer provides a generic head atlas for guiding interpretation of fNIRS results, but also permits users to provide subject-specific head anatomies to interpret their results. We anticipate that AtlasViewer will be a valuable tool in improving the anatomical interpretation of fNIRS studies. PMID:26157991

Classification of plum spirit drinks by synchronous fluorescence spectroscopy.

PubMed

Sádecká, J; Jakubíková, M; Májek, P; Kleinová, A

2016-04-01

Synchronous fluorescence spectroscopy was used in combination with principal component analysis (PCA) and linear discriminant analysis (LDA) for the differentiation of plum spirits according to their geographical origin. A total of 14 Czech, 12 Hungarian and 18 Slovak plum spirit samples were used. The samples were divided in two categories: colorless (22 samples) and colored (22 samples). Synchronous fluorescence spectra (SFS) obtained at a wavelength difference of 60 nm provided the best results. Considering the PCA-LDA applied to the SFS of all samples, Czech, Hungarian and Slovak colorless samples were properly classified in both the calibration and prediction sets. 100% of correct classification was also obtained for Czech and Hungarian colored samples. However, one group of Slovak colored samples was classified as belonging to the Hungarian group in the calibration set. Thus, the total correct classifications obtained were 94% and 100% for the calibration and prediction steps, respectively. The results were compared with those obtained using near-infrared (NIR) spectroscopy. Applying PCA-LDA to NIR spectra (5500-6000 cm(-1)), the total correct classifications were 91% and 92% for the calibration and prediction steps, respectively, which were slightly lower than those obtained using SFS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nondestructive estimation of tracheid length from sections of radial wood strips by near infrared spectroscopy

Treesearch

Laurence R. Schimleck; P. David Jones; Gary F. Peter; F. Daniels; Alexander Clarklll

2004-01-01

The use of calibrated near infrared (NIR) spectroscopy for predicting tracheid length of Pinus taeda L. (loblolly pine) wood samples is described. Ten-mm sections of 14 P. taeda radial strips were selected and NIR spectra obtained from the radial longitudinal face of each section. The fibers in these sections were characterized in terms of arithmetic and length-...

Near infrared spectroscopy for the nondestructive estimation of clear wood properties of Pinus taeda L. from the southern United States

Treesearch

Laurence R. Schimleck; P. David Jones; Alexander Clark; Richard F. Daniels; Gary F. Peter

2005-01-01

The estimation of specific gravity (SG), modulus of elasticity (MOE), and modulus of rupture (MOR) of loblolly pine (Pinus taeda L.) clear wood samples from a diverse range of sites across the southern United States was investigated using near infrared (NIR) spectroscopy. NIR spectra were obtained from the radial and cross sectional (original, rough...

Feasibility of using near-infrared (NIR) spectroscopy for quantitative detection of Kojic Acid in wheat flour

USDA-ARS?s Scientific Manuscript database

The possibility of using NIR spectroscopy technology to detect kojic acid (KA) added in wheat flour was studied. Three common types of white flour samples, i.e. high-gluten flour, plain flour and low-gluten flour were added with different contents of KA (0.0%, 0.5%, 1.0%, 3.0%, 5.0%, and 10.0%) resp...

Growth of near-infrared spectroscopy in pharmaceutical and medical sciences

NASA Astrophysics Data System (ADS)

Ciurczak, Emil W.

2002-06-01

Near-IR Spectroscopy (NIRS) is used extensively in the health services industries: medical research, pharmaceutical production, and bioprocessing. NIRS Is rugged, simple to operate, flexible, and relatively inexpensive. It may be used to monitor the progress biochemical reactions. It is used to control mixing, blending, drying, and coating in pharmaceutical production and is used for imaging and chemical determinations in living patients.

Extinction coefficients and purity of single-walled carbon nanotubes.

PubMed

Zhao, B; Itkis, M E; Niyogi, S; Hu, H; Perea, D E; Haddon, R C

2004-11-01

Single-walled carbon nanotubes (SWNTs) hold great promise for advanced applications in aerospace, electronics and medicine, yet these industries require materials with rigorous quality control. There are currently no accepted standards for quality assurance or quality control among the commercial suppliers of SWNTs. We briefly discuss the applicability of various techniques to measure SWNT purity and review, in detail, the advantages of near infrared (NIR) spectroscopy for the quantitative assessment of the bulk carbonaceous purity of SWNTs. We review the use of solution phase NIR spectroscopy for the analysis and characterization of a variety of carbon materials, emphasizing SWNTs produced by the electric arc (EA), laser oven (LO) and HiPco (HC) methods. We consider the applicability of Beer's law to carbon materials dispersed in dimethylformamide (DMF) and the effective extinction coefficients that are obtained from such dispersions. Analysis of the areal absorptivities of the second interband transition of semiconducting EA-produced SWNTs for a number of samples of differing purities has lead to an absolute molar extinction coefficient for the carbonaceous impurities in EA-produced SWNT samples. We conclude that NIR spectroscopy is the clear method of choice for the assessment of the bulk carbonaceous purity of EA-produced SWNTs, and we suggest that an absolute determination of the purity of SWNTs is within reach. Continued work in this area is expected to lead to a universal method for the assessment of the absolute bulk purity of SWNTs from all sources--such a development will be of great importance for nanotube science and for future customers for this product.

NIR analysis of cellulose and lactose--application to ecstasy tablet analysis.

PubMed

Baer, Ines; Gurny, Robert; Margot, Pierre

2007-04-11

Cellulose and lactose are the most frequently used excipients in illicit ecstasy production. The aim of this project was to use near infrared reflectance spectroscopy (NIRS) for the determination of the different chemical forms of these two substances, as well as for the differentiation of their origin (producer). It was possible to distinguish between the different chemical forms of both compounds, as well as between their origins (producers), although within limits. Furthermore, the possibilities to apply NIR for the analysis of substances such as found in illicit tablets were studied. First, a few cellulose and lactose samples were chosen to make mixtures with amphetamine at three degrees of purity (5, 10 and 15%), in order to study the resulting changes in the spectra as well as to simultaneously quantify amphetamine and identify the excipient. A PLS2 model could be build to predict concentrations and excipient. Secondarily, the technique was to be applied to real ecstasy tablets. About 40 ecstasy seizures were analysed with the aim to determine the excipient and to check them against each other. Identification of the excipients was not always obvious, especially when more than one excipient were present. However, a comparison between tablets appeared to give groups of similar samples. NIR analysis results in spectra representing the tablet blend as a whole taking into account all absorbing compounds. Although NIRS seems to be an appropriate method for ecstasy profiling, little is known about intra- and intervariability of compression batches.

Compensation of spectral artifacts in dual-modality intravascular optical coherence tomography and near-infrared spectroscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Fard, Ali M.; Gardecki, Joseph A.; Ughi, Giovanni J.; Hyun, Chulho; Tearney, Guillermo J.

2016-02-01

Intravascular optical coherence tomography (OCT) is a high-resolution catheter-based imaging method that provides three-dimensional microscopic images of coronary artery in vivo, facilitating coronary artery disease treatment decisions based on detailed morphology. Near-infrared spectroscopy (NIRS) has proven to be a powerful tool for identification of lipid-rich plaques inside the coronary walls. We have recently demonstrated a dual-modality intravascular imaging technology that integrates OCT and NIRS into one imaging catheter using a two-fiber arrangement and a custom-made dual-channel fiber rotary junction. It therefore enables simultaneous acquisition of microstructural and composition information at 100 frames/second for improved diagnosis of coronary lesions. The dual-modality OCT-NIRS system employs a single wavelength-swept light source for both OCT and NIRS modalities. It subsequently uses a high-speed photoreceiver to detect the NIRS spectrum in the time domain. Although use of one light source greatly simplifies the system configuration, such light source exhibits pulse-to-pulse wavelength and intensity variation due to mechanical scanning of the wavelength. This can be in particular problematic for NIRS modality and sacrifices the reliability of the acquired spectra. In order to address this challenge, here we developed a robust data acquisition and processing method that compensates for the spectral variations of the wavelength-swept light source. The proposed method extracts the properties of the light source, i.e., variation period and amplitude from a reference spectrum and subsequently calibrates the NIRS datasets. We have applied this method on datasets obtained from cadaver human coronary arteries using a polygon-scanning (1230-1350nm) OCT system, operating at 100,000 sweeps per second. The results suggest that our algorithm accurately and robustly compensates the spectral variations and visualizes the dual-modality OCT-NIRS images. These findings are therefore crucial for the practical application and clinical translation of dual-modality intravascular OCT-NIRS imaging when the same swept sources are used for both OCT and spectroscopy.

Comparison of spectroscopy technologies for improved monitoring of cell culture processes in miniature bioreactors

PubMed Central

van den Berg, Frans; Racher, Andrew J.; Martin, Elaine B.; Jaques, Colin

2017-01-01

Cell culture process development requires the screening of large numbers of cell lines and process conditions. The development of miniature bioreactor systems has increased the throughput of such studies; however, there are limitations with their use. One important constraint is the limited number of offline samples that can be taken compared to those taken for monitoring cultures in large‐scale bioreactors. The small volume of miniature bioreactor cultures (15 mL) is incompatible with the large sample volume (600 µL) required for bioanalysers routinely used. Spectroscopy technologies may be used to resolve this limitation. The purpose of this study was to compare the use of NIR, Raman, and 2D‐fluorescence to measure multiple analytes simultaneously in volumes suitable for daily monitoring of a miniature bioreactor system. A novel design‐of‐experiment approach is described that utilizes previously analyzed cell culture supernatant to assess metabolite concentrations under various conditions while providing optimal coverage of the desired design space. Multivariate data analysis techniques were used to develop predictive models. Model performance was compared to determine which technology is more suitable for this application. 2D‐fluorescence could more accurately measure ammonium concentration (RMSECV 0.031 g L−1) than Raman and NIR. Raman spectroscopy, however, was more robust at measuring lactate and glucose concentrations (RMSECV 1.11 and 0.92 g L−1, respectively) than the other two techniques. The findings suggest that Raman spectroscopy is more suited for this application than NIR and 2D‐fluorescence. The implementation of Raman spectroscopy increases at‐line measuring capabilities, enabling daily monitoring of key cell culture components within miniature bioreactor cultures. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:337–346, 2017 PMID:28271638

Development of a hybrid proximal sensing method for rapid identification of petroleum contaminated soils.

PubMed

Chakraborty, Somsubhra; Weindorf, David C; Li, Bin; Ali Aldabaa, Abdalsamad Abdalsatar; Ghosh, Rakesh Kumar; Paul, Sathi; Nasim Ali, Md

2015-05-01

Using 108 petroleum contaminated soil samples, this pilot study proposed a new analytical approach of combining visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS) and portable X-ray fluorescence spectrometry (PXRF) for rapid and improved quantification of soil petroleum contamination. Results indicated that an advanced fused model where VisNIR DRS spectra-based penalized spline regression (PSR) was used to predict total petroleum hydrocarbon followed by PXRF elemental data-based random forest regression was used to model the PSR residuals, it outperformed (R(2)=0.78, residual prediction deviation (RPD)=2.19) all other models tested, even producing better generalization than using VisNIR DRS alone (RPD's of 1.64, 1.86, and 1.96 for random forest, penalized spline regression, and partial least squares regression, respectively). Additionally, unsupervised principal component analysis using the PXRF+VisNIR DRS system qualitatively separated contaminated soils from control samples. Fusion of PXRF elemental data and VisNIR derivative spectra produced an optimized model for total petroleum hydrocarbon quantification in soils. Copyright © 2015 Elsevier B.V. All rights reserved.

High-throughput prediction of tablet weight and trimethoprim content of compound sulfamethoxazole tablets for controlling the uniformity of dosage units by NIR.

PubMed

Dong, Yanhong; Li, Juan; Zhong, Xiaoxiao; Cao, Liya; Luo, Yang; Fan, Qi

2016-04-15

This paper establishes a novel method to simultaneously predict the tablet weight (TW) and trimethoprim (TMP) content of compound sulfamethoxazole tablets (SMZCO) by near infrared (NIR) spectroscopy with partial least squares (PLS) regression for controlling the uniformity of dosage units (UODU). The NIR spectra for 257 samples were measured using the optimized parameter values and pretreated using the optimized chemometric techniques. After the outliers were ignored, two PLS models for predicting TW and TMP content were respectively established by using the selected spectral sub-ranges and the reference values. The TW model reaches the correlation coefficient of calibration (R(c)) 0.9543 and the TMP content model has the R(c) 0.9205. The experimental results indicate that this strategy expands the NIR application in controlling UODU, especially in the high-throughput and rapid analysis of TWs and contents of the compound pharmaceutical tablets, and may be an important complement to the common NIR on-line analytical method for pharmaceutical tablets. Copyright © 2016 Elsevier B.V. All rights reserved.

Use of UV-vis-NIR spectroscopy to monitor label-free interaction between molecular recognition elements and erythropoietin on a gold-coated polycarbonate platform.

PubMed

Citartan, Marimuthu; Gopinath, Subash C B; Tominaga, Junji; Chen, Yeng; Tang, Thean-Hock

2014-08-01

Label-free-based detection is pivotal for real-time monitoring of biomolecular interactions and to eliminate the need for labeling with tags that can occupy important binding sites of biomolecules. One simplest form of label-free-based detection is ultraviolet-visible-near-infrared (UV-vis-NIR) spectroscopy, which measure changes in reflectivity as a means to monitor immobilization and interaction of biomolecules with their corresponding partners. In biosensor development, the platform used for the biomolecular interaction should be suitable for different molecular recognition elements. In this study, gold (Au)-coated polycarbonate was used as a platform and as a proof-of-concept, erythropoietin (EPO), a doping substance widely abused by the athletes was used as the target. The interaction of EPO with its corresponding molecular recognition elements (anti-EPO monoclonal antibody and anti-EPO DNA aptamer) is monitored by UV-vis-NIR spectroscopy. Prior to this, to show that UV-vis-NIR spectroscopy is a suitable method for measuring biomolecular interaction, the interaction between biotin and streptavidin was demonstrated via this strategy and reflectivity of this interaction decreased by 25%. Subsequent to this, interaction of the EPO with anti-EPO monoclonal antibody and anti-EPO DNA aptamer resulted in the decrease of reflectivity by 5% and 10%, respectively. The results indicated that Au-coated polycarbonate could be an ideal biosensor platform for monitoring biomolecular interactions using UV-vis-NIR spectroscopy. A smaller version of the Au-coated polycarbonate substrates can be derived from the recent set-up, to be applied towards detecting EPO abuse among atheletes. Copyright © 2014 Elsevier B.V. All rights reserved.

Characterizing and Authenticating Montilla-Moriles PDO Vinegars Using Near Infrared Reflectance Spectroscopy (NIRS) Technology

PubMed Central

De la Haba, María-José; Arias, Mar; Ramírez, Pilar; López, María-Isabel; Sánchez, María-Teresa

2014-01-01

This study assessed the potential of near infrared (NIR) spectroscopy as a non-destructive method for characterizing Protected Designation of Origin (PDO) “Vinagres de Montilla-Moriles” wine vinegars and for classifying them as a function of the manufacturing process used. Three spectrophotometers were evaluated for this purpose: two monochromator instruments (Foss NIRSystems 6500 SY-I and Foss NIRSystems 6500 SY-II; spectral range 400–2,500 nm in both cases) and a diode-array instrument (Corona 45 VIS/NIR; spectral range 380–1,700 nm). A total of 70 samples were used to predict major chemical quality parameters (total acidity, fixed acidity, volatile acidity, pH, dry extract, ash, acetoin, methanol, total polyphenols, color (tonality and intensity), and alcohol content), and to construct models for the classification of vinegars as a function of the manufacturing method used. The results obtained indicate that this non-invasive technology can be used successfully by the vinegar industry and by PDO regulators for the routine analysis of vinegars in order to authenticate them and to detect potential fraud. Slightly better results were achieved with the two monochromator instruments. The findings also highlight the potential of these NIR instruments for predicting the manufacturing process used, this being of particular value for the industrial authentication of traditional wine vinegars. PMID:24561402

Optimizing the general linear model for functional near-infrared spectroscopy: an adaptive hemodynamic response function approach

PubMed Central

Uga, Minako; Dan, Ippeita; Sano, Toshifumi; Dan, Haruka; Watanabe, Eiju

2014-01-01

Abstract. An increasing number of functional near-infrared spectroscopy (fNIRS) studies utilize a general linear model (GLM) approach, which serves as a standard statistical method for functional magnetic resonance imaging (fMRI) data analysis. While fMRI solely measures the blood oxygen level dependent (BOLD) signal, fNIRS measures the changes of oxy-hemoglobin (oxy-Hb) and deoxy-hemoglobin (deoxy-Hb) signals at a temporal resolution severalfold higher. This suggests the necessity of adjusting the temporal parameters of a GLM for fNIRS signals. Thus, we devised a GLM-based method utilizing an adaptive hemodynamic response function (HRF). We sought the optimum temporal parameters to best explain the observed time series data during verbal fluency and naming tasks. The peak delay of the HRF was systematically changed to achieve the best-fit model for the observed oxy- and deoxy-Hb time series data. The optimized peak delay showed different values for each Hb signal and task. When the optimized peak delays were adopted, the deoxy-Hb data yielded comparable activations with similar statistical power and spatial patterns to oxy-Hb data. The adaptive HRF method could suitably explain the behaviors of both Hb parameters during tasks with the different cognitive loads during a time course, and thus would serve as an objective method to fully utilize the temporal structures of all fNIRS data. PMID:26157973

Evaluation of Pleasure-Displeasure Induced by Use of Lipsticks with Near-Infrared Spectroscopy (NIRS): Usefulness of 2-Channel NIRS in Neuromarketing.

PubMed

Tanida, M; Okabe, M; Tagai, K; Sakatani, K

2017-01-01

In order to examine whether near-infrared spectroscopy (NIRS) would be a useful neuromarketing tool, we employed NIRS to evaluate the difference of pleasure-displeasure in women, induced by the use of different types of lipsticks. The subjects used lipsticks A and B; A is softer than B. Concentration changes of oxy-Hb were measured in the bilateral prefrontal cortex (PFC) during use of lipsticks A and B. We evaluated the right and left dominancy of PFC activity by calculating the Laterality Index (LI) (LI = leftΔoxy-Hb - rightΔoxy-Hb); positive LI indicates left-dominant activity while negative LI indicate right-dominant activity. We found a significant interaction between the use of lipsticks A and B, using a two-way factorial analysis of variance [F(1,13) = 9.63, p < 0.01]; Δoxy-Hb in the left PFC was larger than that in the right PFC during the use of lipstick A, while Δoxy-Hb in the right PFC tended to be larger than that in the left PFC during the use of lipstick B (p < 0.1). The LI of lipstick A was larger than that of lipstick B (paired T-test, p = 0.0083). We suggest that lipstick A caused a more positive emotional response than lipstick B, since greater left than right frontal cortical activity is associated with positive affect. These results suggest that 2-channel NIRS may be a useful neuromarketing tool, since it allows objective assessment of pleasure-unpleasure.

Functional near infrared spectroscopy as a probe of brain function in people with prolonged disorders of consciousness.

PubMed

Kempny, Agnieszka M; James, Leon; Yelden, Kudret; Duport, Sophie; Farmer, Simon; Playford, E Diane; Leff, Alexander P

2016-01-01

Near infrared spectroscopy (NIRS) is a non-invasive technique which measures changes in brain tissue oxygenation. NIRS has been used for continuous monitoring of brain oxygenation during medical procedures carrying high risk of iatrogenic brain ischemia and also has been adopted by cognitive neuroscience for studies on executive and cognitive functions. Until now, NIRS has not been used to detect residual cognitive functions in patients with prolonged disorders of consciousness (pDOC). In this study we aimed to evaluate the brain function of patients with pDOC by using a motor imagery task while recording NIRS. We also collected data from a group of age and gender matched healthy controls while they carried out both real and imagined motor movements to command. We studied 16 pDOC patients in total, split into two groups: five had a diagnosis of Vegetative state/Unresponsive Wakefulness State, and eleven had a diagnosis of Minimally Conscious State. In the control subjects we found a greater oxy-haemoglobin (oxyHb) response during real movement compared with imagined movement. For the between group comparison, we found a main effect of hemisphere, with greater depression of oxyHb signal in the right > left hemisphere compared with rest period for all three groups. A post-hoc analysis including only the two pDOC patient groups was also significant suggesting that this effect was not just being driven by the control subjects. This study demonstrates for the first time the feasibility of using NIRS for the assessment of brain function in pDOC patients using a motor imagery task.

PAT-Based Control of Fluid Bed Coating Process Using NIR Spectroscopy to Monitor the Cellulose Coating on Pharmaceutical Pellets.

PubMed

Naidu, Venkata Ramana; Deshpande, Rucha S; Syed, Moinuddin R; Deoghare, Piyush; Singh, Dharamvir; Wakte, Pravin S

2017-08-01

Current endeavor was aimed towards monitoring percent weight build-up during functional coating process on drug-layered pellets. Near-infrared (NIR) spectroscopy is an emerging process analytical technology (PAT) tool which was employed here within quality by design (QbD) framework. Samples were withdrawn after spraying every 15-Kg cellulosic coating material during Wurster coating process of drug-loaded pellets. NIR spectra of these samples were acquired using cup spinner assembly of Thermoscientific Antaris II, followed by multivariate analysis using partial least squares (PLS) calibration model. PLS model was built by selecting various absorption regions of NIR spectra for Ethyl cellulose, drug and correlating the absorption values with actual percent weight build up determined by HPLC. The spectral regions of 8971.04 to 8250.77 cm -1 , 7515.24 to 7108.33 cm -1 , and 5257.00 to 5098.87 cm -1 were found to be specific to cellulose, where as the spectral region of 6004.45 to 5844.14 cm -1 was found to be specific to drug. The final model gave superb correlation co-efficient value of 0.9994 for calibration and 0.9984 for validation with low root mean square of error (RMSE) values of 0.147 for calibration and 0.371 for validation using 6 factors. The developed correlation between the NIR spectra and cellulose content is useful in precise at-line prediction of functional coat value and can be used for monitoring the Wurster coating process.

NIR and Py-mbms coupled with multivariate data analysis as a high-throughput biomass characterization technique: a review

PubMed Central

Xiao, Li; Wei, Hui; Himmel, Michael E.; Jameel, Hasan; Kelley, Stephen S.

2014-01-01

Optimizing the use of lignocellulosic biomass as the feedstock for renewable energy production is currently being developed globally. Biomass is a complex mixture of cellulose, hemicelluloses, lignins, extractives, and proteins; as well as inorganic salts. Cell wall compositional analysis for biomass characterization is laborious and time consuming. In order to characterize biomass fast and efficiently, several high through-put technologies have been successfully developed. Among them, near infrared spectroscopy (NIR) and pyrolysis-molecular beam mass spectrometry (Py-mbms) are complementary tools and capable of evaluating a large number of raw or modified biomass in a short period of time. NIR shows vibrations associated with specific chemical structures whereas Py-mbms depicts the full range of fragments from the decomposition of biomass. Both NIR vibrations and Py-mbms peaks are assigned to possible chemical functional groups and molecular structures. They provide complementary information of chemical insight of biomaterials. However, it is challenging to interpret the informative results because of the large amount of overlapping bands or decomposition fragments contained in the spectra. In order to improve the efficiency of data analysis, multivariate analysis tools have been adapted to define the significant correlations among data variables, so that the large number of bands/peaks could be replaced by a small number of reconstructed variables representing original variation. Reconstructed data variables are used for sample comparison (principal component analysis) and for building regression models (partial least square regression) between biomass chemical structures and properties of interests. In this review, the important biomass chemical structures measured by NIR and Py-mbms are summarized. The advantages and disadvantages of conventional data analysis methods and multivariate data analysis methods are introduced, compared and evaluated. This review aims to serve as a guide for choosing the most effective data analysis methods for NIR and Py-mbms characterization of biomass. PMID:25147552

Light shift from ultraviolet to near infrared light: Cerenkov luminescence with gold nanocluster - near infrared (AuNc-NIR) conjugates

NASA Astrophysics Data System (ADS)

Yoo, Su Woong; Mun, Hyoyoung; Oh, Gyungseok; Ryu, Youngjae; Kim, Min-Gon; Chung, Euiheon

2015-03-01

Cerenkov luminescence (CL) is generated when a charged particle moves faster than the speed of light in dielectric media. Recently CL imaging becomes an emerging technique with the use of radioisotopes. However, due to relatively weak blue light production and massive tissue attenuation, CL has not been applied widely. Therefore, we attempted to shift the CL emission to more near infrared (NIR) spectrum for better tissue penetration by using Cerenkov Radiation Energy Transfer (CRET). Gold nanoclusters were conjugated with NIR dye molecules (AuNc-IR820 and AuNc-ICG) to be activated with ultraviolet light. We found optimal conjugate concentrations of AuNc-NIR conjugates by spectroscopy system to generate maximal photon emission. When exposed by ultraviolet light, the emission of NIR light from the conjugates were verified. In quantitative analysis, AuNc-NIR conjugates emit brighter light signal than pure AuNc. This result implies that NIR fluorescent dyes (both IR820 and ICG) can be excited by the emission from AuNc. Following the above baseline experiment, we mixed F-18 fluorodeoxyglucose (F-18 FDG) radioisotope to the AuNc- NIR conjugates, to confirm NIR emission induced from Cerenkov radiation. Long pass filter was used to block Cerenkov luminescence and to collect the emission from AuNc-NIR conjugates. Instead of one long exposure imaging with CCD, we used multiple frame scheme to eliminate gamma radiation strike in each frame prior to combination. In summary, we obtained NIR emission light from AuNc-NIR conjugated dyes that is induced from CL. We plan to perform in vivo small animal imaging with these conjugates to assess better tissue penetration.

Near-infrared spectroscopy for burning plasma diagnostic applications.

PubMed

Soukhanovskii, V A

2008-10-01

Ultraviolet and visible (UV-VIS, 200-750 nm) atomic spectroscopy of neutral and ionized fuel species (H, D, T, and Li) and impurities (e.g., He, Be, C, and W) is a key element of plasma control and diagnosis on International Thermonuclear Experimental Reactor and future magnetically confined burning plasma experiments (BPXs). Spectroscopic diagnostic implementation and performance issues that arise in the BPX harsh nuclear environment in the UV-VIS range, e.g., degradation of first mirror reflectivity under charge-exchange atom bombardment (erosion) and impurity deposition, permanent and dynamic loss of window, and optical fiber transmission under intense neutron and gamma-ray fluxes, are either absent or not as severe in the near-infrared (NIR, 750-2000 nm) range. An initial survey of NIR diagnostic applications has been undertaken on the National Spherical Torus Experiment. It is demonstrated that NIR spectroscopy can be used for machine protection and plasma control applications, as well as contribute to plasma performance evaluation and physics studies. Emission intensity estimates demonstrate that NIR measurements are possible in the BPX plasma operating parameter range. Complications in the NIR range due to the parasitic background emissions are expected to occur at very high plasma densities, low impurity densities, and at high plasma-facing component temperatures.

Prediction of Caffeine Content in Java Preanger Coffee Beans by NIR Spectroscopy Using PLS and MLR Method

NASA Astrophysics Data System (ADS)

Budiastra, I. W.; Sutrisno; Widyotomo, S.; Ayu, P. C.

2018-05-01

Caffeine is one of important components in coffee that contributes to the coffee beverages flavor. Caffeine concentration in coffee bean is usually determined by chemical method which is time consuming and destructive method. A nondestructive method using NIR spectroscopy was successfully applied to determine the caffeine concentration of Arabica gayo coffee bean. In this study, NIR Spectroscopy was assessed to determine the caffeine concentration of java preanger coffee bean. A hundred samples, each consist of 96 g coffee beans were prepared for reflectance and chemical measurement. Reflectance of the sample was measured by FT-NIR spectrometer in the wavelength of 1000-2500 nm (10000-4000 cm-1) followed by determination of caffeine content using LCMS method. Calibration of NIR spectra and the caffeine content was carried out using PLS and MLR methods. Several spectra data processing was conducted to increase the accuracy of prediction. The result of the study showed that caffeine content could be determined by PLS model using 7 factors and spectra data processing of combination of the first derivative and MSC of spectra absorbance (r = 0.946; CV = 1.54 %; RPD = 2.28). A lower accuracy was obtained by MLR model consisted of three caffeine and other four absorption wavelengths (r = 0.683; CV = 3.31%; RPD = 1.18).

In-line monitoring of extraction process of scutellarein from Erigeron breviscapus (vant.) Hand-Mazz based on qualitative and quantitative uses of near-infrared spectroscopy.

PubMed

Wu, Yongjiang; Jin, Ye; Ding, Haiying; Luan, Lianjun; Chen, Yong; Liu, Xuesong

2011-09-01

The application of near-infrared (NIR) spectroscopy for in-line monitoring of extraction process of scutellarein from Erigeron breviscapus (vant.) Hand-Mazz was investigated. For NIR measurements, two fiber optic probes designed to transmit NIR radiation through a 2 mm pathlength flow cell were utilized to collect spectra in real-time. High performance liquid chromatography (HPLC) was used as a reference method to determine scutellarein in extract solution. Partial least squares regression (PLSR) calibration model of Savitzky-Golay smoothing NIR spectra in the 5450-10,000 cm(-1) region gave satisfactory predictive results for scutellarein. The results showed that the correlation coefficients of calibration and cross validation were 0.9967 and 0.9811, respectively, and the root mean square error of calibration and cross validation were 0.044 and 0.105, respectively. Furthermore, both the moving block standard deviation (MBSD) method and conformity test were used to identify the end point of extraction process, providing real-time data and instant feedback about the extraction course. The results obtained in this study indicated that the NIR spectroscopy technique provides an efficient and environmentally friendly approach for fast determination of scutellarein and end point control of extraction process. Copyright © 2011 Elsevier B.V. All rights reserved.

[State Recognition of Solid Fermentation Process Based on Near Infrared Spectroscopy with Adaboost and Spectral Regression Discriminant Analysis].

PubMed

Yu, Shuang; Liu, Guo-hai; Xia, Rong-sheng; Jiang, Hui

2016-01-01

In order to achieve the rapid monitoring of process state of solid state fermentation (SSF), this study attempted to qualitative identification of process state of SSF of feed protein by use of Fourier transform near infrared (FT-NIR) spectroscopy analysis technique. Even more specifically, the FT-NIR spectroscopy combined with Adaboost-SRDA-NN integrated learning algorithm as an ideal analysis tool was used to accurately and rapidly monitor chemical and physical changes in SSF of feed protein without the need for chemical analysis. Firstly, the raw spectra of all the 140 fermentation samples obtained were collected by use of Fourier transform near infrared spectrometer (Antaris II), and the raw spectra obtained were preprocessed by use of standard normal variate transformation (SNV) spectral preprocessing algorithm. Thereafter, the characteristic information of the preprocessed spectra was extracted by use of spectral regression discriminant analysis (SRDA). Finally, nearest neighbors (NN) algorithm as a basic classifier was selected and building state recognition model to identify different fermentation samples in the validation set. Experimental results showed as follows: the SRDA-NN model revealed its superior performance by compared with other two different NN models, which were developed by use of the feature information form principal component analysis (PCA) and linear discriminant analysis (LDA), and the correct recognition rate of SRDA-NN model achieved 94.28% in the validation set. In this work, in order to further improve the recognition accuracy of the final model, Adaboost-SRDA-NN ensemble learning algorithm was proposed by integrated the Adaboost and SRDA-NN methods, and the presented algorithm was used to construct the online monitoring model of process state of SSF of feed protein. Experimental results showed as follows: the prediction performance of SRDA-NN model has been further enhanced by use of Adaboost lifting algorithm, and the correct recognition rate of the Adaboost-SRDA-NN model achieved 100% in the validation set. The overall results demonstrate that SRDA algorithm can effectively achieve the spectral feature information extraction to the spectral dimension reduction in model calibration process of qualitative analysis of NIR spectroscopy. In addition, the Adaboost lifting algorithm can improve the classification accuracy of the final model. The results obtained in this work can provide research foundation for developing online monitoring instruments for the monitoring of SSF process.

Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset.

PubMed

Shin, Jaeyoung; von Lühmann, Alexander; Kim, Do-Won; Mehnert, Jan; Hwang, Han-Jeong; Müller, Klaus-Robert

2018-02-13

We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for 'target' versus 'non-target' (dataset A) and symbol 'O' versus symbol 'X' (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques.

Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset

PubMed Central

Shin, Jaeyoung; von Lühmann, Alexander; Kim, Do-Won; Mehnert, Jan; Hwang, Han-Jeong; Müller, Klaus-Robert

2018-01-01

We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for ‘target’ versus ‘non-target’ (dataset A) and symbol ‘O’ versus symbol ‘X’ (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques. PMID:29437166

Rapid screening astaxanthin-hyperproducing Haematococcus pluvialis mutants through near-infrared spectroscopy.

PubMed

Liu, J H; Song, L; Huang, Q

2016-02-01

The unicellular freshwater green microalga Haematococcus pluvialis is the richest source of natural astaxanthin. Since accumulation of astaxanthin differs significantly among various algal strains at different stages, it is therefore critical to develop an effective high-throughput assay for rapid screening astaxanthin-hyperproducing strains. In the present study, near-infrared spectroscopy (NIRS) in combination with biochemical assay was employed for evaluation of the wide-type H. Pluvialis strains. The partial least squares (PLS) models of total biomass, astaxanthin content and astaxanthin expressed as a percentage of dry weight (DW) were developed with the R(2) values as 0·959, 0·982 and 0·952, the prediction correlation factor (r) values as 0·979, 0·988 and 0·966, and the residual predictive deviation (RPD) values as 4·88, 6·22 and 3·86, respectively. Furthermore, the PLS models were employed to evaluate H. pluvialis mutants, with the r values as 0·973, 0·983 and 0·976, and the RPD values as 3·45, 7·59 and 4·07, respectively. This work thus demonstrates that NIRS is an easy, fast and non-invasive approach that can be applied in high-throughput screening of astaxanthin-hyperproducing algal mutants. Haematococcus pluvialis has potential application for its ability to accumulate natural antioxidant astaxanthin. In this study, we initiated the application of near-infrared spectroscopy (NIRS) in the analysis of total biomass and astaxanthin content of different mutant strains, demonstrating that NIRS can be very useful in the screening of axataxanthin-hyperproducing mutant strains. © 2015 The Society for Applied Microbiology.

Comparison of visible and near infrared reflectance spectroscopy on fat to authenticate dietary history of lambs.

PubMed

Huang, Y; Andueza, D; de Oliveira, L; Zawadzki, F; Prache, S

2015-11-01

Since consumers are showing increased interest in the origin and method of production of their food, it is important to be able to authenticate dietary history of animals by rapid and robust methods used in the ruminant products. Promising breakthroughs have been made in the use of spectroscopic methods on fat to discriminate pasture-fed and concentrate-fed lambs. However, questions remained on their discriminatory ability in more complex feeding conditions, such as concentrate-finishing after pasture-feeding. We compared the ability of visible reflectance spectroscopy (Vis RS, wavelength range: 400 to 700 nm) with that of visible-near-infrared reflectance spectroscopy (Vis-NIR RS, wavelength range: 400 to 2500 nm) to differentiate between carcasses of lambs reared with three feeding regimes, using partial least square discriminant analysis (PLS-DA) as a classification method. The sample set comprised perirenal fat of Romane male lambs fattened at pasture (P, n = 69), stall-fattened indoors on commercial concentrate and straw (S, n = 55) and finished indoors with concentrate and straw for 28 days after pasture-feeding (PS, n = 65). The overall correct classification rate was better for Vis-NIR RS than for Vis RS (99.0% v. 95.1%, P < 0.05). Vis-NIR RS allowed a correct classification rate of 98.6%, 100.0% and 98.5% for P, S and PS lambs, respectively, whereas Vis RS allowed a correct classification rate of 98.6%, 94.5% and 92.3% for P, S and PS lambs, respectively. This study suggests the likely implication of molecules absorbing light in the non-visible part of the Vis-NIR spectra (possibly fatty acids), together with carotenoid and haem pigments, in the discrimination of the three feeding regimes.

[Determination of soluble solids content in Nanfeng Mandarin by Vis/NIR spectroscopy and UVE-ICA-LS-SVM].

PubMed

Sun, Tong; Xu, Wen-Li; Hu, Tian; Liu, Mu-Hua

2013-12-01

The objective of the present research was to assess soluble solids content (SSC) of Nanfeng mandarin by visible/near infrared (Vis/NIR) spectroscopy combined with new variable selection method, simplify prediction model and improve the performance of prediction model for SSC of Nanfeng mandarin. A total of 300 Nanfeng mandarin samples were used, the numbers of Nanfeng mandarin samples in calibration, validation and prediction sets were 150, 75 and 75, respectively. Vis/NIR spectra of Nanfeng mandarin samples were acquired by a QualitySpec spectrometer in the wavelength range of 350-1000 nm. Uninformative variables elimination (UVE) was used to eliminate wavelength variables that had few information of SSC, then independent component analysis (ICA) was used to extract independent components (ICs) from spectra that eliminated uninformative wavelength variables. At last, least squares support vector machine (LS-SVM) was used to develop calibration models for SSC of Nanfeng mandarin using extracted ICs, and 75 prediction samples that had not been used for model development were used to evaluate the performance of SSC model of Nanfeng mandarin. The results indicate t hat Vis/NIR spectroscopy combinedwith UVE-ICA-LS-SVM is suitable for assessing SSC o f Nanfeng mandarin, and t he precision o f prediction ishigh. UVE--ICA is an effective method to eliminate uninformative wavelength variables, extract important spectral information, simplify prediction model and improve the performance of prediction model. The SSC model developed by UVE-ICA-LS-SVM is superior to that developed by PLS, PCA-LS-SVM or ICA-LS-SVM, and the coefficient of determination and root mean square error in calibration, validation and prediction sets were 0.978, 0.230%, 0.965, 0.301% and 0.967, 0.292%, respectively.

Determination of Hemicellulose, Cellulose and Lignin in Moso Bamboo by Near Infrared Spectroscopy

PubMed Central

Li, Xiaoli; Sun, Chanjun; Zhou, Binxiong; He, Yong

2015-01-01

The contents of hemicellulose, cellulose and lignin are important for moso bamboo processing in biomass energy industry. The feasibility of using near infrared (NIR) spectroscopy for rapid determination of hemicellulose, cellulose and lignin was investigated in this study. Initially, the linear relationship between bamboo components and their NIR spectroscopy was established. Subsequently, successive projections algorithm (SPA) was used to detect characteristic wavelengths for establishing the convenient models. For hemicellulose, cellulose and lignin, 22, 22 and 20 characteristic wavelengths were obtained, respectively. Nonlinear determination models were subsequently built by an artificial neural network (ANN) and a least-squares support vector machine (LS-SVM) based on characteristic wavelengths. The LS-SVM models for predicting hemicellulose, cellulose and lignin all obtained excellent results with high determination coefficients of 0.921, 0.909 and 0.892 respectively. These results demonstrated that NIR spectroscopy combined with SPA-LS-SVM is a useful, nondestructive tool for the determinations of hemicellulose, cellulose and lignin in moso bamboo. PMID:26601657

Online monitoring of P(3HB) produced from used cooking oil with near-infrared spectroscopy.

PubMed

Cruz, Madalena V; Sarraguça, Mafalda Cruz; Freitas, Filomena; Lopes, João Almeida; Reis, Maria A M

2015-01-20

Online monitoring process for the production of polyhydroxyalkanoates (PHA), using cooking oil (UCO) as the sole carbon source and Cupriavidus necator, was developed. A batch reactor was operated and hydroxybutyrate homopolymer was obtained. The biomass reached a maximum concentration of 11.6±1.7gL(-1) with a polymer content of 63±10.7% (w/w). The yield of product on substrate was 0.77±0.04gg(-1). Near-infrared (NIR) spectroscopy was used for online monitoring of the fermentation, using a transflectance probe. Partial least squares regression was applied to relate NIR spectra with biomass, UCO and PHA concentrations in the broth. The NIR predictions were compared with values obtained by offline reference methods. Prediction errors to these parameters were 1.18, 2.37 and 1.58gL(-1) for biomass, UCO and PHA, respectively, which indicate the suitability of the NIR spectroscopy method for online monitoring and as a method to assist bioreactor control. Copyright © 2014 Elsevier B.V. All rights reserved.

Nondestructive determination of the modulus of elasticity of Fraxinus mandschurica using near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Yu, Huiling; Liang, Hao; Lin, Xue; Zhang, Yizhuo

2018-04-01

A nondestructive methodology is proposed to determine the modulus of elasticity (MOE) of Fraxinus mandschurica samples by using near-infrared (NIR) spectroscopy. The test data consisted of 150 NIR absorption spectra of the wood samples obtained using an NIR spectrometer, with the wavelength range of 900 to 1900 nm. To eliminate the high-frequency noise and the systematic variations on the baseline, Savitzky-Golay convolution combined with standard normal variate and detrending transformation was applied as data pretreated methods. The uninformative variable elimination (UVE), improved by the evolutionary Monte Carlo (EMC) algorithm and successive projections algorithm (SPA) selected three characteristic variables from full 117 variables. The predictive ability of the models was evaluated concerning the root-mean-square error of prediction (RMSEP) and coefficient of determination (Rp2) in the prediction set. In comparison with the predicted results of all the models established in the experiments, UVE-EMC-SPA-LS-SVM presented the best results with the smallest RMSEP of 0.652 and the highest Rp2 of 0.887. Thus, it is feasible to determine the MOE of F. mandschurica using NIR spectroscopy accurately.

NIR remission spectroscopy of turbid media

NASA Astrophysics Data System (ADS)

Krauter, P.; Foschum, F.; Kienle, A.

2013-06-01

We present a method for the determination of absorption spectra in VIS and NIR spectra of turbid media without the need for calibration. Measurements of the absorption spectra of a phantom and butter are presented.

Functional Near Infrared Spectroscopy: Watching the Brain in Flight

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neurological sensing technique applicable to optimizing human performance in transportation operations, such as commercial aviation. Cognitive state can be determined via pattern classification of functional activations measured with fNIRS. Operational application calls for further development of algorithms and filters for dynamic artifact removal. The concept of using the frequency domain phase shift signal to tune a Kalman filter is introduced to improve the quality of fNIRS signals in realtime. Hemoglobin concentration and phase shift traces were simulated for four different types of motion artifact to demonstrate the filter. Unwanted signal was reduced by at least 43%, and the contrast of the filtered oxygenated hemoglobin signal was increased by more than 100% overall. This filtering method is a good candidate for qualifying fNIRS signals in real time without auxiliary sensors

Functional Near Infrared Spectroscopy: Watching the Brain in Flight

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan A.

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neurological sensing technique applicable to optimizing human performance in transportation operations, such as commercial aviation. Cognitive state can be determined via pattern classification of functional activations measured with fNIRS. Operational application calls for further development of algorithms and filters for dynamic artifact removal. The concept of using the frequency domain phase shift signal to tune a Kalman filter is introduced to improve the quality of fNIRS signals in real-time. Hemoglobin concentration and phase shift traces were simulated for four different types of motion artifact to demonstrate the filter. Unwanted signal was reduced by at least 43%, and the contrast of the filtered oxygenated hemoglobin signal was increased by more than 100% overall. This filtering method is a good candidate for qualifying fNIRS signals in real time without auxiliary sensors.

Motion tracking and electromyography assist the removal of mirror hand contributions to fNIRS images acquired during a finger tapping task performed by children with cerebral palsy

NASA Astrophysics Data System (ADS)

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R.; Tulchin-Francis, Kirsten; Shierk, Angela; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J.; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2013-03-01

Functional neurological imaging has been shown to be valuable in evaluating brain plasticity in children with cerebral palsy (CP). In recent studies it has been demonstrated that functional near-infrared spectroscopy (fNIRS) is a viable and sensitive method for imaging motor cortex activities in children with CP. However, during unilateral finger tapping tasks children with CP often exhibit mirror motions (unintended motions in the non-tapping hand), and current fNIRS image formation techniques do not account for this. Therefore, the resulting fNIRS images contain activation from intended and unintended motions. In this study, cortical activity was mapped with fNIRS on four children with CP and five controls during a finger tapping task. Finger motion and arm muscle activation were concurrently measured using motion tracking cameras and electromyography (EMG). Subject-specific regressors were created from motion capture and EMG data and used in a general linear model (GLM) analysis in an attempt to create fNIRS images representative of different motions. The analysis provided an fNIRS image representing activation due to motion and muscle activity for each hand. This method could prove to be valuable in monitoring brain plasticity in children with CP by providing more consistent images between measurements. Additionally, muscle effort versus cortical effort was compared between control and CP subjects. More cortical effort was required to produce similar muscle effort in children with CP. It is possible this metric could be a valuable diagnostic tool in determining response to treatment.

Using an optimal CC-PLSR-RBFNN model and NIR spectroscopy for the starch content determination in corn

NASA Astrophysics Data System (ADS)

Jiang, Hao; Lu, Jiangang

2018-05-01

Corn starch is an important material which has been traditionally used in the fields of food and chemical industry. In order to enhance the rapidness and reliability of the determination for starch content in corn, a methodology is proposed in this work, using an optimal CC-PLSR-RBFNN calibration model and near-infrared (NIR) spectroscopy. The proposed model was developed based on the optimal selection of crucial parameters and the combination of correlation coefficient method (CC), partial least squares regression (PLSR) and radial basis function neural network (RBFNN). To test the performance of the model, a standard NIR spectroscopy data set was introduced, containing spectral information and chemical reference measurements of 80 corn samples. For comparison, several other models based on the identical data set were also briefly discussed. In this process, the root mean square error of prediction (RMSEP) and coefficient of determination (Rp2) in the prediction set were used to make evaluations. As a result, the proposed model presented the best predictive performance with the smallest RMSEP (0.0497%) and the highest Rp2 (0.9968). Therefore, the proposed method combining NIR spectroscopy with the optimal CC-PLSR-RBFNN model can be helpful to determine starch content in corn.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm

NASA Astrophysics Data System (ADS)

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV = 0.0776, Rc = 0.9777, RMSEP = 0.0963, and Rp = 0.9686 for pH model; RMSECV = 1.3544% w/w, Rc = 0.8871, RMSEP = 1.4946% w/w, and Rp = 0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry.

Determination of melamine of milk based on two-dimensional correlation infrared spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Ren-jie; Liu, Rong; Xu, Kexin

2012-03-01

The adulteration of milk with harmful substances is a threat to public health and beyond question a serious crime. In order to develop a rapid, cost-effective, high-throughput analysis method for detecting of adulterants in milk, the discriminative analysis of melamine is established in milk based on the two-dimensional (2D) correlation infrared spectroscopy in present paper. Pure milk samples and adulterated milk samples with different content of melamine were prepared. Then the Fourier Transform Infrared spectra of all samples were measured at room temperature. The characteristics of pure milk and adulterated milk were studied by one-dimensional spectra. The 2D NIR and 2D IR correlation spectroscopy were calculated under the perturbation of adulteration concentration. In the range from 1400 to 1800 cm-1, two strong autopeaks were aroused by melamine in milk at 1464 cm-1 and 1560 cm-1 in synchronous spectrum. At the same time, the 1560 cm-1 band does not share cross peak with the 1464 cm-1 band, which further confirm that the two bands have the same origin. Also in the range from 4200 to 4800 cm-1, the autopeak was shown at 4648 cm-1 in synchronous spectrum of melamine in milk. 2D NIR-IR hetero-spectral correlation analysis confirmed that the bands at 1464, 1560 and 4648 cm-1 had the same origin. The results demonstrated that the adulterant can be discriminated correctly by 2D correlation infrared spectroscopy.

Integrated Mueller-matrix near-infrared imaging and point-wise spectroscopy improves colonic cancer detection

PubMed Central

Wang, Jianfeng; Zheng, Wei; Lin, Kan; Huang, Zhiwei

2016-01-01

We report the development and implementation of a unique integrated Mueller-matrix (MM) near-infrared (NIR) imaging and Mueller-matrix point-wise diffuse reflectance (DR) spectroscopy technique for improving colonic cancer detection and diagnosis. Point-wise MM DR spectra can be acquired from any suspicious tissue areas indicated by MM imaging. A total of 30 paired colonic tissue specimens (normal vs. cancer) were measured using the integrated MM imaging and point-wise MM DR spectroscopy system. Polar decomposition algorithms are employed on the acquired images and spectra to derive three polarization metrics including depolarization, diattentuation and retardance for colonic tissue characterization. The decomposition results show that tissue depolarization and retardance are significantly decreased (p<0.001, paired 2-sided Student’s t-test, n = 30); while the tissue diattentuation is significantly increased (p<0.001, paired 2-sided Student’s t-test, n = 30) associated with colonic cancer. Further partial least squares discriminant analysis (PLS-DA) and leave-one tissue site-out, cross validation (LOSCV) show that the combination of the three polarization metrics provide the best diagnostic accuracy of 95.0% (sensitivity: 93.3%, and specificity: 96.7%) compared to either of the three polarization metrics (sensitivities of 93.3%, 83.3%, and 80.0%; and specificities of 90.0%, 96.7%, and 80.0%, respectively, for the depolarization, diattentuation and retardance metrics) for colonic cancer detection. This work suggests that the integrated MM NIR imaging and point-wise MM NIR diffuse reflectance spectroscopy has the potential to improve the early detection and diagnosis of malignant lesions in the colon. PMID:27446640

Visible-near infrared spectroscopy as a tool to improve mapping of soil properties

NASA Astrophysics Data System (ADS)

Evgrafova, Alevtina; Kühnel, Anna; Bogner, Christina; Haase, Ina; Shibistova, Olga; Guggenberger, Georg; Tananaev, Nikita; Sauheitl, Leopold; Spielvogel, Sandra

2017-04-01

Spectroscopic measurements, which are non-destructive, precise and rapid, can be used to predict soil properties and help estimate the spatial variability of soil properties at the pedon scale. These estimations are required for quantifying soil properties with higher precision, identifying the changes in soil properties and ecosystem response to climate change as well as increasing the estimation accuracy of soil-related models. Our objectives were to (i) predict soil properties for nested samples (n = 296) using the laboratory-based visible-near infrared (vis-NIR) spectra of air-dried (<2 mm) soil samples and values of measured soil properties for gridded samples (n = 174) as calibration and validation sets; (ii) estimate the precision and predictive accuracy of an empirical spectral model using (a) our own spectral library and (b) the global spectral library; (iii) support the global spectral library with obtained vis-NIR spectral data on permafrost-affected soils. The soil samples were collected from three permafrost-affected soil profiles underlain by permafrost at various depths between 23 cm to 57.5 cm below the surface (Cryosols) and one soil profile with no presence of permafrost within the upper 100 cm layer (Cambisol) in order to characterize the spatial distribution and variability of soil properties. The gridded soil samples (n = 174) were collected using an 80 cm wide grid with a mesh size of 10 cm on both axes. In addition, 300 nested soil samples were collected using a grid of 12 cm by 12 cm (25 samples per grid) from a hole of 1 cm in a diameter with a distance from the next sample of 1 cm. Due to a small amount of available soil material (< 1.5 g), 296 nested soil samples were analyzed only using vis-NIR spectroscopy. The air-dried mineral gridded soil samples (n = 174) were sieved through a 2-mm sieve and ground with an agate mortar prior to the elemental analysis. The soil organic carbon and total nitrogen concentrations (in %) were determined using a dry combustion method on the Vario EL cube analyzer (Elementar Analysensysteme GmbH, Germany). Inorganic C was removed from the mineral soil samples with pH values higher than 7 prior to the elemental analysis using the volatilization method (HCl, 6 hours). The pH of soil samples was measured in 0.01 M CaCl2 using a 1:2 soil:solution ratio. However, for soil sample with a high in organic matter content, a 1:10 ratio was applied. We also measured oxalate and dithionite extracted iron, aluminum and manganese oxides and hydroxides using inductively coupled plasma optical emission spectroscopy (Varian Vista MPX ICP-OES, Agilent Technologies, USA). We predicted the above-mentioned soil properties for all nested samples using partial least squares regression, which was performed using R program. We can conclude that vis-NIR spectroscopy can be used effectively in order to describe, estimate and further map the spatial patterns of soil properties using geostatistical methods. This research could also help to improve the global soil spectral library taking into account that only few previous applications of vis-NIR spectroscopy were conducted on permafrost-affected soils of Northern Siberia. Keywords: Visible-near infrared spectroscopy, vis-NIR, permafrost-affected soils, Siberia, partial least squares regression.

Nontargeted, Rapid Screening of Extra Virgin Olive Oil Products for Authenticity Using Near-Infrared Spectroscopy in Combination with Conformity Index and Multivariate Statistical Analyses.

PubMed

Karunathilaka, Sanjeewa R; Kia, Ali-Reza Fardin; Srigley, Cynthia; Chung, Jin Kyu; Mossoba, Magdi M

2016-10-01

A rapid tool for evaluating authenticity was developed and applied to the screening of extra virgin olive oil (EVOO) retail products by using Fourier-transform near infrared (FT-NIR) spectroscopy in combination with univariate and multivariate data analysis methods. Using disposable glass tubes, spectra for 62 reference EVOO, 10 edible oil adulterants, 20 blends consisting of EVOO spiked with adulterants, 88 retail EVOO products and other test samples were rapidly measured in the transmission mode without any sample preparation. The univariate conformity index (CI) and the multivariate supervised soft independent modeling of class analogy (SIMCA) classification tool were used to analyze the various olive oil products which were tested for authenticity against a library of reference EVOO. Better discrimination between the authentic EVOO and some commercial EVOO products was observed with SIMCA than with CI analysis. Approximately 61% of all EVOO commercial products were flagged by SIMCA analysis, suggesting that further analysis be performed to identify quality issues and/or potential adulterants. Due to its simplicity and speed, FT-NIR spectroscopy in combination with multivariate data analysis can be used as a complementary tool to conventional official methods of analysis to rapidly flag EVOO products that may not belong to the class of authentic EVOO. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Semi-quantitative prediction of a multiple API solid dosage form with a combination of vibrational spectroscopy methods.

PubMed

Hertrampf, A; Sousa, R M; Menezes, J C; Herdling, T

2016-05-30

Quality control (QC) in the pharmaceutical industry is a key activity in ensuring medicines have the required quality, safety and efficacy for their intended use. QC departments at pharmaceutical companies are responsible for all release testing of final products but also all incoming raw materials. Near-infrared spectroscopy (NIRS) and Raman spectroscopy are important techniques for fast and accurate identification and qualification of pharmaceutical samples. Tablets containing two different active pharmaceutical ingredients (API) [bisoprolol, hydrochlorothiazide] in different commercially available dosages were analysed using Raman- and NIR Spectroscopy. The goal was to define multivariate models based on each vibrational spectroscopy to discriminate between different dosages (identity) and predict their dosage (semi-quantitative). Furthermore the combination of spectroscopic techniques was investigated. Therefore, two different multiblock techniques based on PLS have been applied: multiblock PLS (MB-PLS) and sequential-orthogonalised PLS (SO-PLS). NIRS showed better results compared to Raman spectroscopy for both identification and quantitation. The multiblock techniques investigated showed that each spectroscopy contains information not present or captured with the other spectroscopic technique, thus demonstrating that there is a potential benefit in their combined use for both identification and quantitation purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Characterization of mammalian cell culture raw materials by combining spectroscopy and chemometrics

PubMed Central

Trunfio, Nicholas; Lee, Haewoo; Starkey, Jason; Agarabi, Cyrus; Liu, Jay

2017-01-01

Two of the primary issues with characterizing the variability of raw materials used in mammalian cell culture, such as wheat hydrolysate, is that the analyses of these materials can be time consuming, and the results of the analyses are not straightforward to interpret. To solve these issues, spectroscopy can be combined with chemometrics to provide a quick, robust and easy to understand methodology for the characterization of raw materials; which will improve cell culture performance by providing an assessment of the impact that a given raw material will have on final product quality. In this study, four spectroscopic technologies: near infrared spectroscopy, middle infrared spectroscopy, Raman spectroscopy, and fluorescence spectroscopy were used in conjunction with principal component analysis to characterize the variability of wheat hydrolysates, and to provide evidence that the classification of good and bad lots of raw material is possible. Then, the same spectroscopic platforms are combined with partial least squares regressions to quantitatively predict two cell culture critical quality attributes (CQA): integrated viable cell density and IgG titer. The results showed that near infrared (NIR) spectroscopy and fluorescence spectroscopy are capable of characterizing the wheat hydrolysate's chemical structure, with NIR performing slightly better; and that they can be used to estimate the raw materials’ impact on the CQAs. These results were justified by demonstrating that of all the components present in the wheat hydrolysates, six amino acids: arginine, glycine, phenylalanine, tyrosine, isoleucine and threonine; and five trace elements: copper, phosphorus, molybdenum, arsenic and aluminum, had a large, statistically significant effect on the CQAs, and that NIR and fluorescence spectroscopy performed the best for characterizing the important amino acids. It was also found that the trace elements of interest were not characterized well by any of the spectral technologies used; however, the trace elements were also shown to have a less significant effect on the CQAs than the amino acids. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers, 33:1127–1138, 2017 PMID:28393480

Simultaneous signal reconstruction from both superficial and deep tissue for fNIRS using depth-selective filtering method

NASA Astrophysics Data System (ADS)

Fujii, M.

2017-07-01

Two variations of a depth-selective back-projection filter for functional near-infrared spectroscopy (fNIRS) systems are introduced. The filter comprises a depth-selective algorithm that uses inverse problems applied to an optically diffusive multilayer medium. In this study, simultaneous signal reconstruction of both superficial and deep tissue from fNIRS experiments of the human forehead using a prototype of a CW-NIRS system is demonstrated.

Determination of origin and sugars of citrus fruits using genetic algorithm, correspondence analysis and partial least square combined with fiber optic NIR spectroscopy

NASA Astrophysics Data System (ADS)

Tewari, Jagdish C.; Dixit, Vivechana; Cho, Byoung-Kwan; Malik, Kamal A.

2008-12-01

The capacity to confirm the variety or origin and the estimation of sucrose, glucose, fructose of the citrus fruits are major interests of citrus juice industry. A rapid classification and quantification technique was developed and validated for simultaneous and nondestructive quantifying the sugar constituent's concentrations and the origin of citrus fruits using Fourier Transform Near-Infrared (FT-NIR) spectroscopy in conjunction with Artificial Neural Network (ANN) using genetic algorithm, Chemometrics and Correspondences Analysis (CA). To acquire good classification accuracy and to present a wide range of concentration of sucrose, glucose and fructose, we have collected 22 different varieties of citrus fruits from the market during the entire season of citruses. FT-NIR spectra were recorded in the NIR region from 1100 to 2500 nm using the fiber optic probe and three types of data analysis were performed. Chemometrics analysis using Partial Least Squares (PLS) was performed in order to determine the concentration of individual sugars. Artificial Neural Network analysis was performed for classification, origin or variety identification of citrus fruits using genetic algorithm. Correspondence analysis was performed in order to visualize the relationship between the citrus fruits. To compute a PLS model based upon the reference values and to validate the developed method, high performance liquid chromatography (HPLC) was performed. Spectral range and the number of PLS factors were optimized for the lowest standard error of calibration (SEC), prediction (SEP) and correlation coefficient ( R2). The calibration model developed was able to assess the sucrose, glucose and fructose contents in unknown citrus fruit up to an R2 value of 0.996-0.998. Numbers of factors from F1 to F10 were optimized for correspondence analysis for relationship visualization of citrus fruits based on the output values of genetic algorithm. ANN and CA analysis showed excellent classification of citrus according to the variety to which they belong and well-classified citrus according to their origin. The technique has potential in rapid determination of sugars content and to identify different varieties and origins of citrus in citrus juice industry.

Determination of origin and sugars of citrus fruits using genetic algorithm, correspondence analysis and partial least square combined with fiber optic NIR spectroscopy.

PubMed

Tewari, Jagdish C; Dixit, Vivechana; Cho, Byoung-Kwan; Malik, Kamal A

2008-12-01

The capacity to confirm the variety or origin and the estimation of sucrose, glucose, fructose of the citrus fruits are major interests of citrus juice industry. A rapid classification and quantification technique was developed and validated for simultaneous and nondestructive quantifying the sugar constituent's concentrations and the origin of citrus fruits using Fourier Transform Near-Infrared (FT-NIR) spectroscopy in conjunction with Artificial Neural Network (ANN) using genetic algorithm, Chemometrics and Correspondences Analysis (CA). To acquire good classification accuracy and to present a wide range of concentration of sucrose, glucose and fructose, we have collected 22 different varieties of citrus fruits from the market during the entire season of citruses. FT-NIR spectra were recorded in the NIR region from 1,100 to 2,500 nm using the fiber optic probe and three types of data analysis were performed. Chemometrics analysis using Partial Least Squares (PLS) was performed in order to determine the concentration of individual sugars. Artificial Neural Network analysis was performed for classification, origin or variety identification of citrus fruits using genetic algorithm. Correspondence analysis was performed in order to visualize the relationship between the citrus fruits. To compute a PLS model based upon the reference values and to validate the developed method, high performance liquid chromatography (HPLC) was performed. Spectral range and the number of PLS factors were optimized for the lowest standard error of calibration (SEC), prediction (SEP) and correlation coefficient (R(2)). The calibration model developed was able to assess the sucrose, glucose and fructose contents in unknown citrus fruit up to an R(2) value of 0.996-0.998. Numbers of factors from F1 to F10 were optimized for correspondence analysis for relationship visualization of citrus fruits based on the output values of genetic algorithm. ANN and CA analysis showed excellent classification of citrus according to the variety to which they belong and well-classified citrus according to their origin. The technique has potential in rapid determination of sugars content and to identify different varieties and origins of citrus in citrus juice industry.

A case study of real-time monitoring of solid-state phase transformations in acoustically levitated particles using near infrared and Raman spectroscopy.

PubMed

Rehder, Sönke; Wu, Jian X; Laackmann, Julian; Moritz, Hans-Ulrich; Rantanen, Jukka; Rades, Thomas; Leopold, Claudia S

2013-01-23

The objective of this study was to monitor the amorphous-to-crystalline solid-state phase transformation kinetics of the model drug ibuprofen with spectroscopic methods during acoustic levitation. Chemical and physical information was obtained by real-time near infrared (NIRS) and Raman spectroscopy measurements. The recrystallisation kinetic parameters (overall recrystallisation rate constant β and the time needed to reach 50% of the equilibrated level t(50)), were determined using a multivariate curve resolution approach. The acoustic levitation device coupled with non-invasive spectroscopy enabled monitoring of the recrystallisation process of the difficult-to-handle (adhesive) amorphous sample. The application of multivariate curve resolution enabled isolation of the underlying pure spectra, which corresponded well with the reference spectra of amorphous and crystalline ibuprofen. The recrystallisation kinetic parameters were estimated from the recrystallisation profiles. While the empirical recrystallisation rate constant determined by NIR and Raman spectroscopy were comparable, the lag time for recrystallisation was significantly lower with Raman spectroscopy as compared to NIRS. This observation was explained by the high energy density of the Raman laser beam, which might have led to local heating effects of the sample and thus reduced the recrystallisation onset time. It was concluded that acoustic levitation with NIR and Raman spectroscopy combined with multivariate curve resolution allowed direct determination of the recrystallisation kinetics of amorphous drugs and thus is a promising technique for monitoring solid-state phase transformations of adhesive small-sized samples during the early phase of drug development. Copyright © 2012 Elsevier B.V. All rights reserved.

Chemometric compositional analysis of phenolic compounds in fermenting samples and wines using different infrared spectroscopy techniques.

PubMed

Aleixandre-Tudo, Jose Luis; Nieuwoudt, Helene; Aleixandre, Jose Luis; du Toit, Wessel

2018-01-01

The wine industry requires reliable methods for the quantification of phenolic compounds during the winemaking process. Infrared spectroscopy appears as a suitable technique for process control and monitoring. The ability of Fourier transform near infrared (FT-NIR), attenuated total reflectance mid infrared (ATR-MIR) and Fourier transform infrared (FT-IR) spectroscopies to predict compositional phenolic levels during red wine fermentation and aging was investigated. Prediction models containing a large number of samples collected over two vintages from several industrial fermenting tanks as well as wine samples covering a varying number of vintages were validated. FT-NIR appeared as the most accurate technique to predict the phenolic content. Although slightly less accurate models were observed, ATR-MIR and FT-IR can also be used for the prediction of the majority of phenolic measurements. Additionally, the slope and intercept test indicated a systematic error for the three spectroscopies which seems to be slightly more pronounced for HPLC generated phenolics data than for the spectrophotometric parameters. However, the results also showed that the predictions made with the three instruments are statistically comparable. The robustness of the prediction models was also investigated and discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Combining near-infrared spectroscopy with electroencephalography and repetitive transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Näsi, Tiina; Kotilahti, Kalle; Mäki, Hanna; Nissilä, Ilkka; Meriläinen, Pekka

2009-07-01

The objective of the study was to assess the usability of a near-infrared spectroscopy (NIRS) device in multimodal measurements. We combined NIRS with electroencephalography (EEG) to record hemodynamic responses and evoked potentials simultaneously, and with transcranial magnetic stimulation (TMS) to investigate hemodynamic responses to repetitive TMS (rTMS). Hemodynamic responses and visual evoked potentials (VEPs) to 3, 6, and 12 s stimuli consisting of pattern-reversing checkerboards were successfully recorded in the NIRS/EEG measurement, and ipsi- and contralateral hemodynamic responses to 0.5, 1, and 2 Hz rTMS in the NIRS/TMS measurement. In the NIRS/EEG measurements, the amplitudes of the hemodynamic responses increased from 3- to 6-s stimulus, but not from 6- to 12-s stimulus, and the VEPs showed peaks N75, P100, and N135. In the NIRS/TMS measurements, the 2-Hz stimulus produced the strongest hemodynamic responses compared to the 0.5- and 1-Hz stimuli. In two subjects oxyhemoglobin concentration decreased and in one increased as a consequence of the 2-Hz rTMS. To locate the origin of the measured NIRS responses, methods have to be developed to investigate TMS-induced scalp muscle contractions. In the future, multimodal measurements may prove useful in monitoring or treating diseases such as stroke or Alzheimer's disease.

Lack of irrefutable validation does not negate clinical utility of near-infrared spectroscopy monitoring: learning to trust new technology.

PubMed

Kane, Jason M; Steinhorn, David M

2009-09-01

Reliance on new monitoring device technology is based upon an understanding of how the device operates and its reliability in a specific clinical setting. The introduction of new monitoring devices will therefore elicit either distrust of the new technology and the data presented or adoption of new devices. The use of near-infrared spectroscopy (NIRS) technology to monitor vital organs in postoperative pediatric cardiac surgery patients has been extensively described yet controversy remains as to the use of this monitoring device. The following retrospective case series demonstrates how learning from trends in data elicited from 2-site NIRS monitoring provided important bedside insights. These insights led to changes in clinician behavior and reliance on NIRS monitoring for early recognition of clinically silent deteriorations. Disregard for the NIRS data may have led to a fatal outcome in an unstable patient who might have received more timely intervention if the NIRS data had been acknowledged earlier. This case series demonstrates that 2-site NIRS monitoring accurately reflects situations in which poor clinical outcomes may occur when declining trends in somatic tissue oxygen saturations are not corrected. Physician management of the postoperative pediatric cardiac surgery patient can change based upon the insights gained through the application of NIRS monitoring.

Resting-state functional connectivity assessed with two diffuse optical tomographic systems.

PubMed

Niu, Haijing; Khadka, Sabin; Tian, Fenghua; Lin, Zi-Jing; Lu, Chunming; Zhu, Chaozhe; Liu, Hanli

2011-04-01

Functional near-infrared spectroscopy (fNIRS) is recently utilized as a new approach to assess resting-state functional connectivity (RSFC) in the human brain. For any new technique or new methodology, it is necessary to be able to replicate similar experiments using different instruments in order to establish its liability and reproducibility. We apply two different diffuse optical tomographic (DOT) systems (i.e., DYNOT and CW5), with various probe arrangements to evaluate RSFC in the sensorimotor cortex by utilizing a previously published experimental protocol and seed-based correlation analysis. Our results exhibit similar spatial patterns and strengths in RSFC between the bilateral motor cortexes. The consistent observations are obtained from both DYNOT and CW5 systems, and are also in good agreement with the previous fNIRS study. Overall, we demonstrate that the fNIRS-based RSFC is reproducible by various DOT imaging systems among different research groups, enhancing the confidence of neuroscience researchers and clinicians to utilize fNIRS for future applications.

Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

USDA-ARS?s Scientific Manuscript database

A greater understanding of the age-structure of mosquito populations, especially malaria vectors such as Anopheles gambiae, is important for assessing the risk of infectious mosquitoes, and how vector control interventions may affect this structure. The use of near-infrared spectroscopy (NIRS) for a...

Spectral Characterization of H2020/PTAL Mineral Samples: Implications for In Situ Martian Exploration and Mars Sample Selection

NASA Astrophysics Data System (ADS)

Lantz, C.; Pilorget, C.; Poulet, F.; Riu, L.; Dypvik, H.; Hellevang, H.; Rull Perez, F.; Veneranda, M.; Cousin, A.; Viennet, J.-C.; Werner, S. C.

2018-04-01

We present combined analysis performed in the framework of the Planetary Terrestrial Analogues Library (H2020 project). XRD, NIR, Raman, and LIBS spectroscopies are used to characterise samples to prepare ExoMars/ESA and Mars2020/NASA observations.

Combined data mining/NIR spectroscopy for purity assessment of lime juice

NASA Astrophysics Data System (ADS)

Shafiee, Sahameh; Minaei, Saeid

2018-06-01

This paper reports the data mining study on the NIR spectrum of lime juice samples to determine their purity (natural or synthetic). NIR spectra for 72 pure and synthetic lime juice samples were recorded in reflectance mode. Sample outliers were removed using PCA analysis. Different data mining techniques for feature selection (Genetic Algorithm (GA)) and classification (including the radial basis function (RBF) network, Support Vector Machine (SVM), and Random Forest (RF) tree) were employed. Based on the results, SVM proved to be the most accurate classifier as it achieved the highest accuracy (97%) using the raw spectrum information. The classifier accuracy dropped to 93% when selected feature vector by GA search method was applied as classifier input. It can be concluded that some relevant features which produce good performance with the SVM classifier are removed by feature selection. Also, reduced spectra using PCA do not show acceptable performance (total accuracy of 66% by RBFNN), which indicates that dimensional reduction methods such as PCA do not always lead to more accurate results. These findings demonstrate the potential of data mining combination with near-infrared spectroscopy for monitoring lime juice quality in terms of natural or synthetic nature.

Turbo-Satori: a neurofeedback and brain-computer interface toolbox for real-time functional near-infrared spectroscopy.

PubMed

Lührs, Michael; Goebel, Rainer

2017-10-01

Turbo-Satori is a neurofeedback and brain-computer interface (BCI) toolbox for real-time functional near-infrared spectroscopy (fNIRS). It incorporates multiple pipelines from real-time preprocessing and analysis to neurofeedback and BCI applications. The toolbox is designed with a focus in usability, enabling a fast setup and execution of real-time experiments. Turbo-Satori uses an incremental recursive least-squares procedure for real-time general linear model calculation and support vector machine classifiers for advanced BCI applications. It communicates directly with common NIRx fNIRS hardware and was tested extensively ensuring that the calculations can be performed in real time without a significant change in calculation times for all sampling intervals during ongoing experiments of up to 6 h of recording. Enabling immediate access to advanced processing features also allows the use of this toolbox for students and nonexperts in the field of fNIRS data acquisition and processing. Flexible network interfaces allow third party stimulus applications to access the processed data and calculated statistics in real time so that this information can be easily incorporated in neurofeedback or BCI presentations.

Shed a light in fatigue detection with near-infrared spectroscopy during long-lasting driving

NASA Astrophysics Data System (ADS)

Gao, Yuan; Pan, Boan; Li, Kai; Li, Ting

2016-03-01

Fatigue driving is one of the leading roles to induce traffic accident and injury, which urgently desires a novel technique to monitor the fatigue level at driving. Functional near infrared spectroscopy (fNIRS) is capable of noninvasive monitoring brain-activities-related hemodynamic responses. Here, we developed a fINRS imager and setup a classic psychological experiment to trigger visual divided attention which varied responding to driving fatigue, and attempted to record the drive-fatigue-level correlated hemodynamic response in the prefrontal cortex. 7 volunteers were recruited to take 7 hours driving and the experimental test was repeated every 1 hour and 8 times in total. The hemodynamic response were extracted and graphed with pseudo image. The analysis on the relationship between the fNIRS-measured hemodynamic response and fatigue level finally displayed that the oxyhemoglobin concentration in one channel of left prefrontal lobe increased with driving duration in significant correlation. And the spatial pattern of hemodynamic response in the prefrontal lobe varied with driving duration as well. The findings indicated the potential of fNIRSmeasured hemodynamic index in some sensitive spot of prefrontal lobe as a driving fatigue indicator and the promising use of fNIRS in traffic safety field.

Feasibility of FT–Raman spectroscopy for rapid screening for DON toxin in ground wheat and barley.

PubMed

Liu, Y; Delwiche, S R; Dong, Y

2009-10-01

Rapid detection of deoxynivalenol (DON) in cereal-based food and feed has long been the goal of regulators and manufacturers. As non-destructive approaches, infrared (IR) and near-infrared (NIR) spectroscopic techniques have been used for the prediction and classification of contaminated single-kernel and ground grain without any DON extraction steps. These methods, however, are hindered by the intense and broad spectral bands attributed to naturally occurring moisture. Raman spectroscopy could be an alternative to IR and NIR due to its insensitivity to water and fewer overlapped bands. This study explored the feasibility of the Raman technique for rapid and non-destructive screening of DON-contaminated wheat and barley meal. The advantages of this technique include the use of a 1064-nm NIR excitation laser that reduces interference from fluorescence of biological compounds in wheat and barley, the use of a simple intensity-intensity algorithm at two unique frequencies, plus the technique's ease of sample preparation. The results indicate that the simple algorithm, as well as principal component analysis applied to the Raman spectra, can be used to classify low from high DON grain.

Analysis of multiple soybean phytonutrients by near-infrared reflectance spectroscopy.

PubMed

Zhang, Gaoyang; Li, Penghui; Zhang, Wenfei; Zhao, Jian

2017-05-01

Improvement of the nutritional quality of soybean is usually facilitated by a vast range of soybean germplasm with enough information about their multiple phytonutrients. In order to acquire this essential information from a huge number of soybean samples, a rapid analytic method is urgently required. Here, a nondestructive near-infrared reflectance spectroscopy (NIRS) method was developed for rapid and accurate measurement of 25 nutritional components in soybean simultaneously, including fatty acids palmitic acid, stearic acid, oleic acid, linoleic acid, and linolenic acid, vitamin E (VE), α-VE, γ-VE, δ-VE, saponins, isoflavonoids, and flavonoids. Modified partial least squares regression and first, second, third, and fourth derivative transformation was applied for the model development. The 1 minus variance ratio (1-VR) value of the optimal model can reach between the highest 0.95 and lowest 0.64. The predicted values of phytonutrients in soybean using NIRS technology are comparable to those obtained from using the traditional spectrum or chemical methods. A robust NIRS can be adopted as a reliable method to evaluate complex plant constituents for screening large-scale samples of soybean germplasm resources or genetic populations for improvement of nutritional qualities. Graphical Abstract ᅟ.

Crop/weed discrimination using near-infrared reflectance spectroscopy (NIRS)

NASA Astrophysics Data System (ADS)

Zhang, Yun; He, Yong

2006-09-01

The traditional uniform herbicide application often results in an over chemical residues on soil, crop plants and agriculture produce, which have imperiled the environment and food security. Near-infrared reflectance spectroscopy (NIRS) offers a promising means for weed detection and site-specific herbicide application. In laboratory, a total of 90 samples (30 for each species) of the detached leaves of two weeds, i.e., threeseeded mercury (Acalypha australis L.) and fourleafed duckweed (Marsilea quadrfolia L.), and one crop soybean (Glycine max) was investigated for NIRS on 325- 1075 nm using a field spectroradiometer. 20 absorbance samples of each species after pretreatment were exported and the lacked Y variables were assigned independent values for partial least squares (PLS) analysis. During the combined principle component analysis (PCA) on 400-1000 nm, the PC1 and PC2 could together explain over 91% of the total variance and detect the three plant species with 98.3% accuracy. The full-cross validation results of PLS, i.e., standard error of prediction (SEP) 0.247, correlation coefficient (r) 0.954 and root mean square error of prediction (RMSEP) 0.245, indicated an optimum model for weed identification. By predicting the remaining 10 samples of each species in the PLS model, the results with deviation presented a 100% crop/weed detection rate. Thus, it could be concluded that PLS was an available alternative of for qualitative weed discrimination on NTRS.

NIR spectroscopy as a tool for discriminating between lichens exposed to air pollution.

PubMed

Casale, Monica; Bagnasco, Lucia; Giordani, Paolo; Mariotti, Mauro Giorgio; Malaspina, Paola

2015-09-01

Lichens are used as biomonitors of air pollution because they are extremely sensitive to the presence of substances that alter atmospheric composition. Fifty-one thalli of two different varieties of Pseudevernia furfuracea (var. furfuracea and var. ceratea) were collected far from local sources of air pollution. Twenty-six of these thalli were then exposed to the air for one month in the industrial port of Genoa, which has high levels of environmental pollution. The possibility of using Near-infrared spectroscopy (NIRS) for generating a 'fingerprint' of lichens was investigated. Chemometric methods were successfully applied to discriminate between samples from polluted and non-polluted areas. In particular, Principal Component Analysis (PCA) was applied as a multivariate display method on the NIR spectra to visualise the data structure. This showed that the difference between samples of different varieties was not significant in comparison to the difference between samples exposed to different levels of environmental pollution. Then Linear Discriminant Analysis (LDA) was carried out to discriminate between lichens based on their exposure to pollutants. The distinction between control samples (not exposed) and samples exposed to the air in the industrial port of Genoa was evaluated. On average, 95.2% of samples were correctly classified, 93.0% of total internal prediction (5 cross-validation groups) and 100.0% of external prediction (on the test set) was achieved. Copyright © 2015 Elsevier Ltd. All rights reserved.

Classification of functional near-infrared spectroscopy signals corresponding to the right- and left-wrist motor imagery for development of a brain-computer interface.

PubMed

Naseer, Noman; Hong, Keum-Shik

2013-10-11

This paper presents a study on functional near-infrared spectroscopy (fNIRS) indicating that the hemodynamic responses of the right- and left-wrist motor imageries have distinct patterns that can be classified using a linear classifier for the purpose of developing a brain-computer interface (BCI). Ten healthy participants were instructed to imagine kinesthetically the right- or left-wrist flexion indicated on a computer screen. Signals from the right and left primary motor cortices were acquired simultaneously using a multi-channel continuous-wave fNIRS system. Using two distinct features (the mean and the slope of change in the oxygenated hemoglobin concentration), the linear discriminant analysis classifier was used to classify the right- and left-wrist motor imageries resulting in average classification accuracies of 73.35% and 83.0%, respectively, during the 10s task period. Moreover, when the analysis time was confined to the 2-7s span within the overall 10s task period, the average classification accuracies were improved to 77.56% and 87.28%, respectively. These results demonstrate the feasibility of an fNIRS-based BCI and the enhanced performance of the classifier by removing the initial 2s span and/or the time span after the peak value. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

On-line application of near-infrared spectroscopy for monitoring water levels in parts per million in a manufacturing-scale distillation process.

PubMed

Lambertus, Gordon; Shi, Zhenqi; Forbes, Robert; Kramer, Timothy T; Doherty, Steven; Hermiller, James; Scully, Norma; Wong, Sze Wing; LaPack, Mark

2014-01-01

An on-line analytical method based on transmission near-infrared spectroscopy (NIRS) for the quantitative determination of water concentrations (in parts per million) was developed and applied to the manufacture of a pharmaceutical intermediate. Calibration models for water analysis, built at the development site and applied at the manufacturing site, were successfully demonstrated during six manufacturing runs at a 250-gallon scale. The water measurements will be used as a forward-processing control point following distillation of a toluene product solution prior to use in a Grignard reaction. The most significant impact of using this NIRS-based process analytical technology (PAT) to replace off-line measurements is the significant reduction in the risk of operator exposure through the elimination of sampling of a severely lachrymatory and mutagenic compound. The work described in this report illustrates the development effort from proof-of-concept phase to manufacturing implementation.

Near-infrared autofluorescence spectroscopy of in vivo soft tissue sarcomas

PubMed Central

Nguyen, John Quan; Gowani, Zain; O'Connor, Maggie; Pence, Isaac; Nguyen, The-Quyen; Holt, Ginger; Mahadevan-Jansen, Anita

2016-01-01

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated via surgical resection. Inadequate resection can lead to local recurrence and decreased survival rates. In this study, we investigate the hypothesis that near-infrared (NIR) autofluorescence can be utilized for tumor margin analysis by differentiating STS from the surrounding normal tissue. Intraoperative in vivo measurements were acquired from 30 patients undergoing STS resection and were characterized to differentiate between normal tissue and STS. Overall, normal muscle and fat were observed to have the highest and lowest autofluorescence intensities, respectively, with STS falling in between. With the exclusion of well-differentiated liposarcomas, the algorithm's accuracy for classifying muscle, fat, and STS was 93%, 92%, and 88%, respectively. These findings suggest that NIR autofluorescence spectroscopy has potential as a rapid and nondestructive surgical guidance tool that can inform surgeons of suspicious margins in need of immediate re-excision. PMID:26625035

Hemodynamic signals in fNIRS.

PubMed

Hoshi, Y

Near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, and it has also been developed into a useful tool in neuroimaging studies, with the so-called functional NIRS (fNIRS). With NIRS, cerebral activation is detected by measuring the cerebral hemoglobin (Hb), where however, the precise correlation between NIRS signal and neural activity remains to be fully understood. This can in part be attributed to the situation that NIRS signals are inherently subject to contamination by signals arising from extracerebral tissue. In recent years, several approaches have been investigated to distinguish between NIRS signals originating in cerebral tissue and signals originating in extracerebral tissue. Selective measurements of cerebral Hb will enable a further evolution of fNIRS. This chapter is divided into six sections: first a summary of the basic theory of NIRS, NIRS signals arising in the activated areas, correlations between NIRS signals and fMRI signals, correlations between NIRS signals and neural activities, and the influence of a variety of extracerebral tissue on NIRS signals and approaches to this issue are reviewed. Finally, future prospects of fNIRS are described. © 2016 Elsevier B.V. All rights reserved.

Mid-infrared and near-infrared spectroscopy for rapid detection of Gardeniae Fructus by a liquid-liquid extraction process.

PubMed

Tao, Lingyan; Lin, Zhonglin; Chen, Jiashan; Wu, Yongjiang; Liu, Xuesong

2017-10-25

Gardeniae Fructus is widely used in the pharmaceutical industry, and many studies have confirmed its medical and economic value. In this study, samples collected from different liquid-liquid extraction batches of Gardeniae Fructus were detected by mid-infrared (MIR) and near-infrared (NIR) spectroscopy. Seven analytes, neochlorogenic acid (5-CQA), cryptochlorogenic acid (4-CQA), chlorogenic acid (3-CQA), geniposidic acid (GEA), deacetyl-asperulosidic acid methyl ester (DAAME), genipin-gentiobioside (GGB), and gardenoside (GA), were chosen as quality property indexes of Gardeniae Fructus. The two kinds of spectra were each used to build models by single partial least squares (PLS). Additionally, both spectral data were combined and modeled by multiblock PLS. For single spectroscopy modeling results, NIR had a better prediction for high-concentration analytes (3-CQA, DAAME, GGB, and GA) whereas MIR performed better for low-concentration analytes (5-CQA, 4-CQA, and GEA). The multiblock methodology was found to be better compared to single spectroscopy models for all seven analytes. Specifically, the coefficients of determination (R 2 ) of the NIR, MIR, and multiblock PLS calibration models of all seven components were higher than 0.95. Relative standard errors of prediction (RSEP) were all less than 7%, except for models of GGB, which were 10.36%, 13.24%, and 8.15% for the NIR-PLS, MIR-PLS, and multiblock models, respectively. These results indicate that MIR and NIR spectrographic techniques could provide a new choice for quality control in industrial production of Gardeniae Fructus. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis–NIR Spectroscopy

PubMed Central

Xu, Shengxiang; Shi, Xuezheng; Wang, Meiyan; Zhao, Yongcun

2016-01-01

Assessment and monitoring of soil organic matter (SOM) quality are important for understanding SOM dynamics and developing management practices that will enhance and maintain the productivity of agricultural soils. Visible and near-infrared (Vis–NIR) diffuse reflectance spectroscopy (350–2500 nm) has received increasing attention over the recent decades as a promising technique for SOM analysis. While heterogeneity of sample sets is one critical factor that complicates the prediction of soil properties from Vis–NIR spectra, a spectral library representing the local soil diversity needs to be constructed. The study area, covering a surface of 927 km2 and located in Yujiang County of Jiangsu Province, is characterized by a hilly area with different soil parent materials (e.g., red sandstone, shale, Quaternary red clay, and river alluvium). In total, 232 topsoil (0–20 cm) samples were collected for SOM analysis and scanned with a Vis–NIR spectrometer in the laboratory. Reflectance data were related to surface SOM content by means of a partial least square regression (PLSR) method and several data pre-processing techniques, such as first and second derivatives with a smoothing filter. The performance of the PLSR model was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to parent materials). The results showed that the models based on the global calibrations can only make approximate predictions for SOM content (RMSE (root mean squared error) = 4.23–4.69 g kg−1; R2 (coefficient of determination) = 0.80–0.84; RPD (ratio of standard deviation to RMSE) = 2.19–2.44; RPIQ (ratio of performance to inter-quartile distance) = 2.88–3.08). Under the local calibrations, the individual PLSR models for each parent material improved SOM predictions (RMSE = 2.55–3.49 g kg−1; R2 = 0.87–0.93; RPD = 2.67–3.12; RPIQ = 3.15–4.02). Among the four different parent materials, the largest R2 and the smallest RMSE were observed for the shale soils, which had the lowest coefficient of variation (CV) values for clay (18.95%), free iron oxides (15.93%), and pH (1.04%). This demonstrates the importance of a practical subsetting strategy for the continued improvement of SOM prediction with Vis–NIR spectroscopy. PMID:26974821

Within-subject reproducibility of near-infrared spectroscopy signals in sensorimotor activation after 6 months

NASA Astrophysics Data System (ADS)

Sato, Hiroki; Kiguchi, Masashi; Maki, Atsushi; Fuchino, Yutaka; Obata, Akiko; Yoro, Takeshi; Koizumi, Hideaki

2006-01-01

Near-infrared spectroscopy (NIRS) can measure the product of the optical path length and the concentration change in oxygenated hemoglobin (ΔC‧oxy), deoxygenated hemoglobin (ΔC‧deoxy), and their sum (ΔC‧total) in the human cerebral cortex, and it has been used for noninvasive investigation of human brain functions. We evaluate the within-subject reproducibility of the NIRS signals by repeated measurement of the sensorimotor cortex in healthy adults taken over a period of about 6 months using near-infrared (NIR) topography. The maximum signal amplitudes and the location of activation centers are compared between two sessions for each subject. The signal amplitudes vary between sessions and no consistent tendency in the changes is found among subjects. However, the distance between the activation centers identified in two sessions is relatively small, within 20 mm on average across subjects, which is comparable to the smallest distance between measurement positions in the NIR topography (21 mm). Moreover, within-subject comparisons of signal time courses show high correlation coefficients (>0.8) between the two sessions. This result, demonstrating a high within-subject reproducibility of the temporal information in NIRS signals, particularly contributes to the development of a new application of NIRS.

Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development

PubMed Central

Ayaz, Hasan; Onaral, Banu; Izzetoglu, Kurtulus; Shewokis, Patricia A.; McKendrick, Ryan; Parasuraman, Raja

2013-01-01

Functional near infrared spectroscopy (fNIRS) is a non-invasive, safe, and portable optical neuroimaging method that can be used to assess brain dynamics during skill acquisition and performance of complex work and everyday tasks. In this paper we describe neuroergonomic studies that illustrate the use of fNIRS in the examination of training-related brain dynamics and human performance assessment. We describe results of studies investigating cognitive workload in air traffic controllers, acquisition of dual verbal-spatial working memory skill, and development of expertise in piloting unmanned vehicles. These studies used conventional fNIRS devices in which the participants were tethered to the device while seated at a workstation. Consistent with the aims of mobile brain imaging (MoBI), we also describe a compact and battery-operated wireless fNIRS system that performs with similar accuracy as other established fNIRS devices. Our results indicate that both wired and wireless fNIRS systems allow for the examination of brain function in naturalistic settings, and thus are suitable for reliable human performance monitoring and training assessment. PMID:24385959

NIR light propagation in a digital head model for traumatic brain injury (TBI)

PubMed Central

Francis, Robert; Khan, Bilal; Alexandrakis, George; Florence, James; MacFarlane, Duncan

2015-01-01

Near infrared spectroscopy (NIRS) is capable of detecting and monitoring acute changes in cerebral blood volume and oxygenation associated with traumatic brain injury (TBI). Wavelength selection, source-detector separation, optode density, and detector sensitivity are key design parameters that determine the imaging depth, chromophore separability, and, ultimately, clinical usefulness of a NIRS instrument. We present simulation results of NIR light propagation in a digital head model as it relates to the ability to detect intracranial hematomas and monitor the peri-hematomal tissue viability. These results inform NIRS instrument design specific to TBI diagnosis and monitoring. PMID:26417498

Optical measurement of cerebral hemodynamics and oxygen metabolism in neonates with congenital heart defects

NASA Astrophysics Data System (ADS)

Durduran, Turgut; Zhou, Chao; Buckley, Erin M.; Kim, Meeri N.; Yu, Guoqiang; Choe, Regine; Gaynor, J. William; Spray, Thomas L.; Durning, Suzanne M.; Mason, Stefanie E.; Montenegro, Lisa M.; Nicolson, Susan C.; Zimmerman, Robert A.; Putt, Mary E.; Wang, Jiongjiong; Greenberg, Joel H.; Detre, John A.; Yodh, Arjun G.; Licht, Daniel J.

2010-05-01

We employ a hybrid diffuse correlation spectroscopy (DCS) and near-infrared spectroscopy (NIRS) monitor for neonates with congenital heart disease (n=33). The NIRS-DCS device measured changes during hypercapnia of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations; cerebral blood flow (rCBFDCS); and oxygen metabolism (rCMRO2). Concurrent measurements with arterial spin-labeled magnetic resonance imaging (rCBFASL-MRI, n=12) cross-validate rCBFDCS against rCBFASL-MRI, showing good agreement (R=0.7, p=0.01). The study demonstrates use of NIRS-DCS on a critically ill neonatal population, and the results indicate that the optical technology is a promising clinical method for monitoring this population.

Use telecommunications for real-time process control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zilberman, I.; Bigman, J.; Sela, I.

1996-05-01

Process operators design real-time accurate information to monitor and control product streams and to optimize unit operations. The challenge is how to cost-effectively install sophisticated analytical equipment in harsh environments such as process areas and maintain system reliability. Incorporating telecommunications technology with near infrared (NIR) spectroscopy may be the bridge to help operations achieve their online control goals. Coupling communications fiber optics with NIR analyzers enables the probe and sampling system to remain in the field and crucial analytical equipment to be remotely located in a general purpose area without specialized protection provisions. The case histories show how two refineriesmore » used NIR spectroscopy online to track octane levels for reformate streams.« less

Simultaneous fNIRS and thermal infrared imaging during cognitive task reveal autonomic correlates of prefrontal cortex activity

NASA Astrophysics Data System (ADS)

Pinti, Paola; Cardone, Daniela; Merla, Arcangelo

2015-12-01

Functional Near Infrared-Spectroscopy (fNIRS) represents a powerful tool to non-invasively study task-evoked brain activity. fNIRS assessment of cortical activity may suffer for contamination by physiological noises of different origin (e.g. heart beat, respiration, blood pressure, skin blood flow), both task-evoked and spontaneous. Spontaneous changes occur at different time scales and, even if they are not directly elicited by tasks, their amplitude may result task-modulated. In this study, concentration changes of hemoglobin were recorded over the prefrontal cortex while simultaneously recording the facial temperature variations of the participants through functional infrared thermal (fIR) imaging. fIR imaging provides touch-less estimation of the thermal expression of peripheral autonomic. Wavelet analysis revealed task-modulation of the very low frequency (VLF) components of both fNIRS and fIR signals and strong coherence between them. Our results indicate that subjective cognitive and autonomic activities are intimately linked and that the VLF component of the fNIRS signal is affected by the autonomic activity elicited by the cognitive task. Moreover, we showed that task-modulated changes in vascular tone occur both at a superficial and at larger depth in the brain. Combined use of fNIRS and fIR imaging can effectively quantify the impact of VLF autonomic activity on the fNIRS signals.

Body fat of stock-type horses predicted by rump fat thickness and deuterium oxide dilution and validated by near-infrared spectroscopy of dissected tissues.

PubMed

Ferjak, E N; Cavinder, C A; Burnett, D D; Argo, C Mc; Dinh, T T N

2017-10-01

Body condition score and percent body fat (BF; %) of horses are positively correlated with reproductive efficiency and are indicative of metabolic issues. However, BF in horses may be poorly predicted because current procedures are either subjective or dependent on one anatomical location. Therefore, the objectives of the current study were to compare 2 methods of predicting BF using rump fat thickness (RFT) and deuterium oxide (DO) dilution with actual tissue fat analysis by near-infrared spectroscopy (NIRS) in stock-type horses and to identify the relationship between BF and BCS. Twenty-four stock-type horses were selected to be humanely euthanized based on 3 primary criteria: geriatric, crippled, and/or unsafe. Approximately 20 h before slaughter, horses were weighed and BCS assessed to be 1 ( = 1; 433 kg), 2 ( = 1; 415 kg), 3 ( = 1; 376 kg), 4 ( = 7; 468 ± 13 kg), 5 ( = 10; 455 ± 11 kg), and 6 ( = 4; 493 ± 12 kg) and RFT was measured using ultrasonography. Blood samples were collected immediately before and 4 h after DO infusion (0.12 g/kg BW). Deuterium oxide concentration of plasma was determined by gas isotope ratio mass spectrometry. Horses were housed in a dry lot overnight before being individually sedated (1.1 mg xylazine/kg BW) and anesthetized using a jugular venipuncture (2.2 mg ketamine/kg BW), and potassium chloride (KCl) solution was administered to cease cardiac function before exsanguination. After euthanasia, horse carcasses were processed and dissected and tissues were collected for NIRS analysis. Body fat predicted by DO dilution was correlated with BF measured by NIRS analysis on various weight bases ( = 0.76 to 0.81, < 0.001), whereas no correlation was observed for BF predicted by RFT. A paired -test indicated that both DO dilution and RFT overestimated BF by 2.48 to 3.26% ( < 0.001) and 5.81 to 6.59% ( < 0.001), respectively, compared with NIRS analysis. Body condition scores affected BF measured by NIRS analysis ( ≤ 0.038) and predicted by DO dilution ( < 0.001) and RFT ( = 0.042). The current study provided evidence that DO dilution was a better prediction method for BF than RFT and that BCS may serve as a BF predictor in stock-type horses.

Reflectance spectroscopy: a tool for predicting the risk of iron chlorosis in soils

NASA Astrophysics Data System (ADS)

Cañasveras, J. C.; Barrón, V.; Del Campillo, M. C.; Viscarra Rossel, R. A.

2012-04-01

Chlorosis due to iron (Fe) deficiency is the most important nutritional problem a plant can have in calcareous soils. The most characteristic symptom of Fe chlorosis is internervial yellowing in the youngest leaves due to a lack of chlorophyll caused by a disorder in Fe nutrition. Fe chlorosis is related with calcium carbonate equivalent (CCE), clay content and Fe extracted with oxalate (Feo). The conventional technique for determining these properties and others, based on laboratory analysis, are time-consuming and costly. Reflectance spectroscopy (RS) is a rapid, non-destructive, less expensive alternative tool that can be used to enhance or replace conventional methods of soil analysis. The aim of this work was to assess the usefulness of RS for the determination of some properties of Mediterranean soils including clay content, CCE, Feo, cation exchange capacity (CEC), organic matter (OM) and pHw, with emphasis on those with a specially marked influence on the risk of Fe chlorosis. To this end, we used partial least-squares regression (PLS) to construct calibration models, leave-one-out cross-validation and an independent validation set. Our results testify to the usefulness of qualitative soil interpretations based on the variable importance for projection (VIP) as derived by PLS decomposition. The accuracy of predictions in each of the Vis-NIR, MIR and combined spectral regions differed considerably between properties. The R2adj and root mean square error (RMSE) for the external validation predictions were as follows: 0.83 and 37 mg kg-1 for clay content in the Vis-NIR-MIR range; 0.99 and 25 mg kg-1 for CCE, 0.80 and 0.1 mg kg-1 for Feo in the MIR range; 0.93 and 3 cmolc kg-1 for CEC in the Vis-NIR range; 0.87 and 2 mg kg-1 for OM in the Vis-NIR-MIR range, 0.61 and 0.2 for pHw in the MIR range. These results testify to the potential of RS in the Vis, NIR and MIR ranges for efficient soil analysis, the acquisition of soil information and the assessment of the risk of Fe chlorosis in soils.

Analysis for Distinctive Activation Patterns of Pain and Itchy in the Human Brain Cortex Measured Using Near Infrared Spectroscopy (NIRS)

PubMed Central

Kataoka, Aiko; Kudo, Ayako; Fujino, Fukue; Chen, Yu-Wen; Mitsuyama, Yuki; Nomura, Shinobu; Yoshioka, Tohru

2013-01-01

Pain and itch are closely related sensations, yet qualitatively quite distinct. Despite recent advances in brain imaging techniques, identifying the differences between pain and itch signals in the brain cortex is difficult due to continuous temporal and spatial changes in the signals. The high spatial resolution of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) has substantially advanced research of pain and itch, but these are uncomfortable because of expensiveness, importability and the limited operation in the shielded room. Here, we used near infrared spectroscopy (NIRS), which has more conventional usability. NIRS can be used to visualize dynamic changes in oxygenated hemoglobin and deoxyhemoglobin concentrations in the capillary networks near activated neural circuits in real-time as well as fMRI. We observed distinct activation patterns in the frontal cortex for acute pain and histamine-induced itch. The prefrontal cortex exhibited a pain-related and itch-related activation pattern of blood flow in each subject. Although it looked as though that activation pattern for pain and itching was different in each subject, further cross correlation analysis of NIRS signals between each channels showed an overall agreement with regard to prefrontal area involvement. As a result, pain-related and itch-related blood flow responses (delayed responses in prefrontal area) were found to be clearly different between pain (τ = +18.7 sec) and itch (τ = +0.63 sec) stimulation. This is the first pilot study to demonstrate the temporal and spatial separation of a pain-induced blood flow and an itch-induced blood flow in human cortex during information processing. PMID:24098378

Robust new NIRS coupled with multivariate methods for the detection and quantification of tallow adulteration in clarified butter samples.

PubMed

Mabood, Fazal; Abbas, Ghulam; Jabeen, Farah; Naureen, Zakira; Al-Harrasi, Ahmed; Hamaed, Ahmad M; Hussain, Javid; Al-Nabhani, Mahmood; Al Shukaili, Maryam S; Khan, Alamgir; Manzoor, Suryyia

2018-03-01

Cows' butterfat may be adulterated with animal fat materials like tallow which causes increased serum cholesterol and triglycerides levels upon consumption. There is no reliable technique to detect and quantify tallow adulteration in butter samples in a feasible way. In this study a highly sensitive near-infrared (NIR) spectroscopy combined with chemometric methods was developed to detect as well as quantify the level of tallow adulterant in clarified butter samples. For this investigation the pure clarified butter samples were intentionally adulterated with tallow at the following percentage levels: 1%, 3%, 5%, 7%, 9%, 11%, 13%, 15%, 17% and 20% (wt/wt). Altogether 99 clarified butter samples were used including nine pure samples (un-adulterated clarified butter) and 90 clarified butter samples adulterated with tallow. Each sample was analysed by using NIR spectroscopy in the reflection mode in the range 10,000-4000 cm -1 , at 2 cm -1 resolution and using the transflectance sample accessory which provided a total path length of 0.5 mm. Chemometric models including principal components analysis (PCA), partial least-squares discriminant analysis (PLSDA), and partial least-squares regressions (PLSR) were applied for statistical treatment of the obtained NIR spectral data. The PLSDA model was employed to differentiate pure butter samples from those adulterated with tallow. The employed model was then externally cross-validated by using a test set which included 30% of the total butter samples. The excellent performance of the model was proved by the low RMSEP value of 1.537% and the high correlation factor of 0.95. This newly developed method is robust, non-destructive, highly sensitive, and economical with very minor sample preparation and good ability to quantify less than 1.5% of tallow adulteration in clarified butter samples.

Application of Functional Near-Infrared Spectroscopy to the Study of Brain Function in Humans and Animal Models

PubMed Central

Kim, Hak Yeong; Seo, Kain; Jeon, Hong Jin; Lee, Unjoo; Lee, Hyosang

2017-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical imaging technique that indirectly assesses neuronal activity by measuring changes in oxygenated and deoxygenated hemoglobin in tissues using near-infrared light. fNIRS has been used not only to investigate cortical activity in healthy human subjects and animals but also to reveal abnormalities in brain function in patients suffering from neurological and psychiatric disorders and in animals that exhibit disease conditions. Because of its safety, quietness, resistance to motion artifacts, and portability, fNIRS has become a tool to complement conventional imaging techniques in measuring hemodynamic responses while a subject performs diverse cognitive and behavioral tasks in test settings that are more ecologically relevant and involve social interaction. In this review, we introduce the basic principles of fNIRS and discuss the application of this technique in human and animal studies. PMID:28835022

Use of near-infrared spectroscopy (NIRS) in cerebral tissue oxygenation monitoring in neonates.

PubMed

Gumulak, Rene; Lucanova, Lucia Casnocha; Zibolen, Mirko

2017-06-01

Near-infrared spectroscopy (NIRS) is a technology capable of non-invasive, continuous measuring of regional tissue oxygen saturation (StO 2 ). StO 2 represents a state of hemodynamic stability, which is influenced by many factors. Extensive research has been done in the field of measuring StO 2 of various organs. The current clinical availability of several NIRS-based devices reflects an important development in prevention, detection and correction of discrepancy in oxygen delivery to the brain and vital organs. Managing cerebral ischemia remains a significant issue in the neonatal intensive care units (NICU). Cerebral tissue oxygenation (cStO 2 ) and cerebral fractional tissue extraction (cFTOE) are reported in a large number of clinical studies. This review provides a summary of the concept of function, current variability of NIRS-based devices used in neonatology, clinical applications in continuous cStO 2 monitoring, limitations, disadvantages, and the potential of current technology.

Rapid, noninvasive detection of Zika virus in Aedes aegypti mosquitoes by near-infrared spectroscopy.

PubMed

Fernandes, Jill N; Dos Santos, Lílha M B; Chouin-Carneiro, Thaís; Pavan, Márcio G; Garcia, Gabriela A; David, Mariana R; Beier, John C; Dowell, Floyd E; Maciel-de-Freitas, Rafael; Sikulu-Lord, Maggy T

2018-05-01

The accelerating global spread of arboviruses, such as Zika virus (ZIKV), highlights the need for more proactive mosquito surveillance. However, a major challenge during arbovirus outbreaks has been the lack of rapid and affordable tests for pathogen detection in mosquitoes. We show for the first time that near-infrared spectroscopy (NIRS) is a rapid, reagent-free, and cost-effective tool that can be used to noninvasively detect ZIKV in heads and thoraces of intact Aedes aegypti mosquitoes with prediction accuracies of 94.2 to 99.3% relative to quantitative reverse transcription polymerase chain reaction (RT-qPCR). NIRS involves simply shining a beam of light on a mosquito to collect a diagnostic spectrum. We estimated in this study that NIRS is 18 times faster and 110 times cheaper than RT-qPCR. We anticipate that NIRS will be expanded upon for identifying potential arbovirus hotspots to guide the spatial prioritization of vector control.

Hemodynamic signal changes during saliva and water swallowing: a near-infrared spectroscopy study

NASA Astrophysics Data System (ADS)

Kober, Silvia Erika; Wood, Guilherme

2018-01-01

Here, we compared the hemodynamic response observed during swallowing of water or saliva using near-infrared spectroscopy (NIRS). Sixteen healthy adults swallowed water or saliva in a randomized order. Relative concentration changes in oxygenated and deoxygenated hemoglobin during swallowing were assessed. Both swallowing tasks led to the strongest NIRS signal change over the bilateral inferior frontal gyrus. Water swallowing led to a stronger activation over the right hemisphere while the activation focus for saliva swallowing was stronger left lateralized. The NIRS time course also differed between both swallowing tasks especially at the beginning of the tasks, which might be a sign of differences in task effort. Our results show that NIRS is a sensitive measure to reveal differences in the topographical distribution and time course of the hemodynamic response between distinct swallowing tasks and might be therefore an adequate diagnostic and therapy tool for swallowing difficulties.

[Construction of NIRS-based process analytical system for production of salvianolic acid for injection and relative discussion].

PubMed

Zhang, Lei; Yue, Hong-Shui; Ju, Ai-Chun; Ye, Zheng-Liang

2016-10-01

Currently, near infrared spectroscopy (NIRS) has been considered as an efficient tool for achieving process analytical technology(PAT) in the manufacture of traditional Chinese medicine (TCM) products. In this article, the NIRS based process analytical system for the production of salvianolic acid for injection was introduced. The design of the process analytical system was described in detail, including the selection of monitored processes and testing mode, and potential risks that should be avoided. Moreover, the development of relative technologies was also presented, which contained the establishment of the monitoring methods for the elution of polyamide resin and macroporous resin chromatography processes, as well as the rapid analysis method for finished products. Based on author's experience of research and work, several issues in the application of NIRS to the process monitoring and control in TCM production were then raised, and some potential solutions were also discussed. The issues include building the technical team for process analytical system, the design of the process analytical system in the manufacture of TCM products, standardization of the NIRS-based analytical methods, and improving the management of process analytical system. Finally, the prospect for the application of NIRS in the TCM industry was put forward. Copyright© by the Chinese Pharmaceutical Association.

Application of near infrared reflectance (NIR) spectroscopy to identify potential PSE meat.

PubMed

Li, Xiao; Feng, Fang; Gao, Runze; Wang, Lu; Qian, Ye; Li, Chunbao; Zhou, Guanghong

2016-07-01

Pale, soft and exudative (PSE) meat is a quality problem that causes a large economic loss to the pork industry. In the present work, near infrared (NIR) quantification and identification methods were used to investigate the feasibility of differentiating potential PSE meat from normal meat. NIR quantification models were developed to estimate meat pH and colour attributes (L*, a*, b*). Promising results were reported for prediction of muscle pH (R(2) CV  = 70.10%, RPDCV = 1.83) and L* (R(2) CV  = 77.18%, RPDCV = 1.91), but it is still hard to promote to practical application at this level. The Factorisation Method applied to NIR spectra could differentiate potential PSE meat from normal meat at 3 h post-mortem. Correlation analysis showed significant relationship between NIR data and LF-NMR T2 components that were indicative of water distribution and mobility in muscle. PSE meat had unconventionally faster energy metabolism than normal meat, which caused greater water mobility. NIR spectra coupled with the Factorisation Method could be a promising technology to identify potential PSE meat. The difference in the intensity of H2 O absorbance peaks between PSE and normal meat might be the basis of this identification method. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

NIR studies of cholesterol-dependent structural modification of the model lipid bilayer doped with inhalation anesthetics

NASA Astrophysics Data System (ADS)

Kuć, Marta; Cieślik-Boczula, Katarzyna; Rospenk, Maria

2018-06-01

The influence of cholesterol on the structure of the model lipid bilayers treated with inhalation anesthetics (enflurane, isoflurane, sevoflurane and halothane) was investigated employing near-infrared (NIR) spectroscopy combined with the Principal Component Analysis (PCA). The conformational changes occurring in the hydrophobic area of the lipid bilayers were analyzed using the first overtones of symmetric (2νs) and antisymmetric (2νas) stretching vibrations of the CH2 groups of lipid aliphatic chains. The temperature values of chain-melting phase transition (Tm) of anesthetic-mixed dipalmitoylphosphatidylcholine (DPPC)/cholesterol and dipalmitoylphosphatidylglycerol (DPPG)/cholesterol membranes, which were obtained from the PCA analysis, were compared with cholesterol-free DPPC and DPPG bilayers mixed with inhalation anesthetics.

Analyses in Support of the WFIRST Supernova Survey

NASA Astrophysics Data System (ADS)

Rubin, David; Aldering, Greg Scott; Charles, Baltay; Barbary, Kyle H.; Currie, Miles; Deustua, Susana E.; Fagrelius, Parker; Dosovitz Fox, Ori; Fruchter, Andrew S.; Law, David R.; Perlmutter, Saul; Pontoppidan, Klaus; Rabinowitz, David L.; Sako, Masao

2017-01-01

The Wide-Field Infrared Survey Telescope (WFIRST) is a future optical-NIR space telescope with science spanning astrophysics and cosmology. The combination of wide-field IR imaging and optical-NIR integral-field spectroscopy enables a SN cosmology experiment with excellent systematics control. The Science Definition Team (SDT) presented a first concept of such a survey with 2700 SNe to z=1.7. We make several key improvements to the SDT analysis, including a significantly improved exposure-time calculator, evaluations of host-galaxy background light, supernova typing simulations, all combined with spectrophotometric cosmology analysis built on a Bayesian hierarchal model. Our work will be useful for deriving accurate cosmological forecasts, optimizing the survey, and the evaluation of calibration, resolution, and stability requirements.

Unlocking interpretation in near infrared multivariate calibrations by orthogonal partial least squares.

PubMed

Stenlund, Hans; Johansson, Erik; Gottfries, Johan; Trygg, Johan

2009-01-01

Near infrared spectroscopy (NIR) was developed primarily for applications such as the quantitative determination of nutrients in the agricultural and food industries. Examples include the determination of water, protein, and fat within complex samples such as grain and milk. Because of its useful properties, NIR analysis has spread to other areas such as chemistry and pharmaceutical production. NIR spectra consist of infrared overtones and combinations thereof, making interpretation of the results complicated. It can be very difficult to assign peaks to known constituents in the sample. Thus, multivariate analysis (MVA) has been crucial in translating spectral data into information, mainly for predictive purposes. Orthogonal partial least squares (OPLS), a new MVA method, has prediction and modeling properties similar to those of other MVA techniques, e.g., partial least squares (PLS), a method with a long history of use for the analysis of NIR data. OPLS provides an intrinsic algorithmic improvement for the interpretation of NIR data. In this report, four sets of NIR data were analyzed to demonstrate the improved interpretation provided by OPLS. The first two sets included simulated data to demonstrate the overall principles; the third set comprised a statistically replicated design of experiments (DoE), to demonstrate how instrumental difference could be accurately visualized and correctly attributed to Wood's anomaly phenomena; the fourth set was chosen to challenge the MVA by using data relating to powder mixing, a crucial step in the pharmaceutical industry prior to tabletting. Improved interpretation by OPLS was demonstrated for all four examples, as compared to alternative MVA approaches. It is expected that OPLS will be used mostly in applications where improved interpretation is crucial; one such area is process analytical technology (PAT). PAT involves fewer independent samples, i.e., batches, than would be associated with agricultural applications; in addition, the Food and Drug Administration (FDA) demands "process understanding" in PAT. Both these issues make OPLS the ideal tool for a multitude of NIR calibrations. In conclusion, OPLS leads to better interpretation of spectrometry data (e.g., NIR) and improved understanding facilitates cross-scientific communication. Such improved knowledge will decrease risk, with respect to both accuracy and precision, when using NIR for PAT applications.

Determination of zinc oxide content of mineral medicine calamine using near-infrared spectroscopy based on MIV and BP-ANN algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Chen, Long; Sun, Yangbo; Bai, Yu; Huang, Bisheng; Chen, Keli

2018-03-01

Near-infrared (NIR) spectroscopy has been widely used in the analysis fields of traditional Chinese medicine. It has the advantages of fast analysis, no damage to samples and no pollution. In this research, a fast quantitative model for zinc oxide (ZnO) content in mineral medicine calamine was explored based on NIR spectroscopy. NIR spectra of 57 batches of calamine samples were collected and the first derivative (FD) method was adopted for conducting spectral pretreatment. The content of ZnO in calamine sample was determined using ethylenediaminetetraacetic acid (EDTA) titration and taken as reference value of NIR spectroscopy. 57 batches of calamine samples were categorized into calibration and prediction set using the Kennard-Stone (K-S) algorithm. Firstly, in the calibration set, to calculate the correlation coefficient (r) between the absorbance value and the ZnO content of corresponding samples at each wave number. Next, according to the square correlation coefficient (r2) value to obtain the top 50 wave numbers to compose the characteristic spectral bands (4081.8-4096.3, 4188.9-4274.7, 4335.4, 4763.6,4794.4-4802.1, 4809.9, 4817.6-4875.4 cm- 1), which were used to establish the quantitative model of ZnO content using back propagation artificial neural network (BP-ANN) algorithm. Then, the 50 wave numbers were operated by the mean impact value (MIV) algorithm to choose wave numbers whose absolute value of MIV greater than or equal to 25, to obtain the optimal characteristic spectral bands (4875.4-4836.9, 4223.6-4080.9 cm- 1). And then, both internal cross and external validation were used to screen the number of hidden layer nodes of BP-ANN. Finally, the number 4 of hidden layer nodes was chosen as the best. At last, the BP-ANN model was found to enjoy a high accuracy and strong forecasting capacity for analyzing ZnO content in calamine samples ranging within 42.05-69.98%, with relative mean square error of cross validation (RMSECV) of 1.66% and coefficient of determination (R2) of 95.75% in internal cross and relative mean square error of prediction (RMSEP) of 1.98%, R2 of 97.94% and ratio of performance to deviation (RPD) of 6.11 in external validation.

Combined bio-engineering and neurophysiological in vivo technologies allow studying rat brain metabolism and neuronal activities in vivo in real time

NASA Astrophysics Data System (ADS)

Crespi, F.; Donini, M.; Bandera, A.; Congestri, F.; Heidbreder, C.; Rovati, L.

2006-04-01

Franz Joebsis first used near infrared spectroscopy (NIRS) as a tool for the in vivo monitoring of tissue oxygenation. Today, NIRS instruments are more and more used in clinical environments since these systems are now easy to use, sensitive, robust, give rapid analysis and have multiple measuring points. In the present work, optic fibre probes were used as optical head of a CW-NIR instrument adapted for in vivo NIRS measurements in the brain of rodents. This prototype was designed for non-invasive analysis of the two main forms of haemoglobin: oxy-haemoglobin (HbO II) and deoxy-haemoglobin (Hb), chromophores present in biological tissues. In the present experiments it was applied to measure non- invasively HbO II and Hb levels in the rat brain; that are markers of the degree of tissue oxygenation, thus providing an index of blood levels and therefore of brain metabolism. In addition, the same animals set for central NIRS studies, were also surgically prepared for electrophysiological monitoring of cell firing in discrete brain areas. These are raphe dorsalis nucleus, locus coeruleus, ventral tegmental area that are defined as main serotoninergic, noradrenergic and dopaminergic cell containing regions of the CNS and therefore involved in the major cerebral syndromes. Then, following a control recording period, exogenous oxygen (O2, 0.1bar, 2min) or carbon dioxide (CO2 0.1bar, 20min) was inflated orally. The data gathered indicate an original relationship between NIRS analysis of brain metabolism and electrical changes in three major nuclei of CNS involved in neurophysiologic and pathologic activities.

Near-infrared spectroscopy versus magnetic resonance imaging to study brain perfusion in newborns with hypoxic-ischemic encephalopathy treated with hypothermia.

PubMed

Wintermark, P; Hansen, A; Warfield, S K; Dukhovny, D; Soul, J S

2014-01-15

The measurement of brain perfusion may provide valuable information for assessment and treatment of newborns with hypoxic-ischemic encephalopathy (HIE). While arterial spin labeled perfusion (ASL) magnetic resonance imaging (MRI) provides noninvasive and direct measurements of regional cerebral blood flow (CBF) values, it is logistically challenging to obtain. Near-infrared spectroscopy (NIRS) might be an alternative, as it permits noninvasive and continuous monitoring of cerebral hemodynamics and oxygenation at the bedside. The purpose of this study is to determine the correlation between measurements of brain perfusion by NIRS and by MRI in term newborns with HIE treated with hypothermia. In this prospective cohort study, ASL-MRI and NIRS performed during hypothermia were used to assess brain perfusion in these newborns. Regional cerebral blood flow (CBF) values, measured from 1-2 MRI scans for each patient, were compared to mixed venous saturation values (SctO2) recorded by NIRS just before and after each MRI. Analysis included groupings into moderate versus severe HIE based on their initial background pattern of amplitude-integrated electroencephalogram. Twelve concomitant recordings were obtained of seven neonates. Strong correlation was found between SctO2 and CBF in asphyxiated newborns with severe HIE (r=0.88; p value=0.0085). Moreover, newborns with severe HIE had lower CBF (likely lower oxygen supply) and extracted less oxygen (likely lower oxygen demand or utilization) when comparing SctO2 and CBF to those with moderate HIE. NIRS is an effective bedside tool to monitor and understand brain perfusion changes in term asphyxiated newborns, which in conjunction with precise measurements of CBF obtained by MRI at particular times, may help tailor neuroprotective strategies in term newborns with HIE. Copyright © 2013 Elsevier Inc. All rights reserved.

Near-Infrared Spectroscopy versus Magnetic Resonance Imaging To Study Brain Perfusion in Newborns with Hypoxic-Ischemic Encephalopathy Treated with Hypothermia

PubMed Central

Wintermark, P.; Hansen, A.; Warfield, SK.; Dukhovny, D.; Soul, JS.

2014-01-01

Background The measurement of brain perfusion may provide valuable information for assessment and treatment of newborns with hypoxic-ischemic encephalopathy (HIE). While arterial spin labeled perfusion (ASL) magnetic resonance imaging (MRI) provides noninvasive and direct measurements of regional cerebral blood flow (CBF) values, it is logistically challenging to obtain. Near-infrared spectroscopy (NIRS) might be an alternative, as it permits noninvasive and continuous monitoring of cerebral hemodynamics and oxygenation at the bedside. Objective The purpose of this study is to determine the correlation between measurements of brain perfusion by NIRS and by MRI in term newborns with HIE treated with hypothermia. Design/Methods In this prospective cohort study, ASL-MRI and NIRS performed during hypothermia were used to assess brain perfusion in these newborns. Regional cerebral blood flow values (CBF), measured from 1–2 MRI scans for each patient, were compared to mixed venous saturation values (SctO2) recorded by NIRS just before and after each MRI. Analysis included groupings into moderate versus severe HIE based on their initial background pattern of amplitude-integrated electroencephalogram. Results Twelve concomitant recordings were obtained of seven neonates. Strong correlation was found between SctO2 and CBF in asphyxiated newborns with severe HIE (r = 0.88; p value = 0.0085). Moreover, newborns with severe HIE had lower CBF (likely lower oxygen supply) and extracted less oxygen (likely lower oxygen demand or utilization) when comparing SctO2 and CBF to those with moderate HIE. Conclusions NIRS is an effective bedside tool to monitor and understand brain perfusion changes in term asphyxiated newborns, which in conjunction with precise measurements of CBF obtained by MRI at particular times, may help tailor neuroprotective strategies in term newborns with HIE. PMID:23631990

Rapid on-line detection and grading of wooden breast myopathy in chicken fillets by near-infrared spectroscopy.

PubMed

Wold, Jens Petter; Veiseth-Kent, Eva; Høst, Vibeke; Løvland, Atle

2017-01-01

The main objective of this work was to develop a method for rapid and non-destructive detection and grading of wooden breast (WB) syndrome in chicken breast fillets. Near-infrared (NIR) spectroscopy was chosen as detection method, and an industrial NIR scanner was applied and tested for large scale on-line detection of the syndrome. Two approaches were evaluated for discrimination of WB fillets: 1) Linear discriminant analysis based on NIR spectra only, and 2) a regression model for protein was made based on NIR spectra and the estimated concentrations of protein were used for discrimination. A sample set of 197 fillets was used for training and calibration. A test set was recorded under industrial conditions and contained spectra from 79 fillets. The classification methods obtained 99.5-100% correct classification of the calibration set and 100% correct classification of the test set. The NIR scanner was then installed in a commercial chicken processing plant and could detect incidence rates of WB in large batches of fillets. Examples of incidence are shown for three broiler flocks where a high number of fillets (9063, 6330 and 10483) were effectively measured. Prevalence of WB of 0.1%, 6.6% and 8.5% were estimated for these flocks based on the complete sample volumes. Such an on-line system can be used to alleviate the challenges WB represents to the poultry meat industry. It enables automatic quality sorting of chicken fillets to different product categories. Manual laborious grading can be avoided. Incidences of WB from different farms and flocks can be tracked and information can be used to understand and point out main causes for WB in the chicken production. This knowledge can be used to improve the production procedures and reduce today's extensive occurrence of WB.

Determination of alcohol and extract concentration in beer samples using a combined method of near-infrared (NIR) spectroscopy and refractometry.

PubMed

Castritius, Stefan; Kron, Alexander; Schäfer, Thomas; Rädle, Matthias; Harms, Diedrich

2010-12-22

A new approach of combination of near-infrared (NIR) spectroscopy and refractometry was developed in this work to determine the concentration of alcohol and real extract in various beer samples. A partial least-squares (PLS) regression, as multivariate calibration method, was used to evaluate the correlation between the data of spectroscopy/refractometry and alcohol/extract concentration. This multivariate combination of spectroscopy and refractometry enhanced the precision in the determination of alcohol, compared to single spectroscopy measurements, due to the effect of high extract concentration on the spectral data, especially of nonalcoholic beer samples. For NIR calibration, two mathematical pretreatments (first-order derivation and linear baseline correction) were applied to eliminate light scattering effects. A sample grouping of the refractometry data was also applied to increase the accuracy of the determined concentration. The root mean squared errors of validation (RMSEV) of the validation process concerning alcohol and extract concentration were 0.23 Mas% (method A), 0.12 Mas% (method B), and 0.19 Mas% (method C) and 0.11 Mas% (method A), 0.11 Mas% (method B), and 0.11 Mas% (method C), respectively.

Application of Fourier transform near-infrared spectroscopy to optimization of green tea steaming process conditions.

PubMed

Ono, Daiki; Bamba, Takeshi; Oku, Yuichi; Yonetani, Tsutomu; Fukusaki, Eiichiro

2011-09-01

In this study, we constructed prediction models by metabolic fingerprinting of fresh green tea leaves using Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression analysis to objectively optimize of the steaming process conditions in green tea manufacture. The steaming process is the most important step for manufacturing high quality green tea products. However, the parameter setting of the steamer is currently determined subjectively by the manufacturer. Therefore, a simple and robust system that can be used to objectively set the steaming process parameters is necessary. We focused on FT-NIR spectroscopy because of its simple operation, quick measurement, and low running costs. After removal of noise in the spectral data by principal component analysis (PCA), PLS regression analysis was performed using spectral information as independent variables, and the steaming parameters set by experienced manufacturers as dependent variables. The prediction models were successfully constructed with satisfactory accuracy. Moreover, the results of the demonstrated experiment suggested that the green tea steaming process parameters could be predicted on a larger manufacturing scale. This technique will contribute to improvement of the quality and productivity of green tea because it can objectively optimize the complicated green tea steaming process and will be suitable for practical use in green tea manufacture. Copyright © 2011 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

NIR spectroscopic sensing for point-of-need freshness assessment of meat, fish, vegetables and fruits

NASA Astrophysics Data System (ADS)

Lee, Seoho; Noh, Tae Gyoon; Choi, Jun Hoe; Han, Jeongsu; Ha, Joo Young; Lee, Ji Young; Park, Yongjong

2017-05-01

Foodborne illness represents a significant health burden worldwide. While monitoring the freshness of food before consumption could significantly improve the current predicament, there is a lack of a simple system that one can use to accurately assess the freshness of their food. Currently, the most common practice for food quality determination is by visual or odor inspection which lacks objectivity, accuracy and precision. Near infrared (NIR) spectroscopic techniques can help address this problem by providing rapid and non-destructive means to estimate the freshness state of various foods based on the changes to their characteristic spectra in the NIR region. Recent advancements in the development of portable NIR spectrometers are also enabling the realization of this technique at the point-of-need. In this study, we have evaluated the feasibility of using NIR spectroscopy at the point-of-need to estimate the freshness of various foods including: beef sirloin, beef eyeround, pork sirloin, bass, salmon, corvina, tomato and watermelon. Using a commercial portable NIR spectrometer, we periodically scanned and collected NIR spectra from the food items that were stored at 4°C inside a refrigerator for up to 30 days. For these food items, we show that the NIR spectra can be classified by the foods' aging day as well as by the levels of chemical/microbial indicators (i.e., thiobarbituric acid, volatile basic nitrogen and bacteria levels) with high accuracy, which represents high prospects of NIR spectroscopy for point-of-need freshness assessment of meat, fish, vegetables and fruits.

[Comparative research on the NIR and MIR micro-imaging of two similar plastic materials].

PubMed

Wang, Dong; Ma, Zhi-Hong; Zhao, Liu; Pan, Li-Gang; Li, Xiao-Ting; Wang, Ji-Hua

2011-09-01

The NIR/MIR micro-imaging can supply not only the information of spectra, but also the information of spacial distribution of the sample, which is superior to the traditional NIR/MIR spectroscopy analysis. In the present paper, polyethylene and parafilm, with similar appearances, were regarded as the research objects, of which the NIR/MIR micro-imaging was collected. Chemical imaging (CI) and compare correlation imaging were carried out for the two materials respectively to discuss the imaging methods of the two materials. The result indicated that the differentiation of the CI values of the two materials in the NIR/MIR CI for material II was 0.004 8 and 0.254 8 respectively, while those in the NIR/MIR CI for material I were 0.002 6 and 0.326 5, respectively. Clear CI was acquired, and the two materials could be differentiated. The result of the compare correlation imagings indicated that the compare correlation imagings, in which the NIR/MIR spectra of the two materials were regarded as reference spectra respectively, can differentiate the two materials remarkably with clear imagings. In the compare correlation imagings of MIR micro-imaging, the difference of the correlation coefficients between the two materials' MIR spectra and the reference spectrum was more than 0.12, which showed a better imaging result; while a tiny difference of the correlation coefficients between the two materials' NIR spectra and the reference spectrum could be employed to show a clear imaging result for NIR compare correlation imaging so as to differentiate the two materials. This thesis, to some extent, can supply the reference to not only the rapid discrimination of the safety of the packaging material for agri-food, but also the imaging methods for NIR/MIR micro-imaging to differentiate the different materials.

Continuous monitoring of kidney transplant perfusion with near-infrared spectroscopy.

PubMed

Malakasioti, Georgia; Marks, Stephen D; Watson, Tom; Williams, Fariba; Taylor-Allkins, Mariesa; Mamode, Nizam; Morgan, Justin; Hayes, Wesley N

2018-05-11

Current reliance on clinical, laboratory and Doppler ultrasound (DUS) parameters for monitoring kidney transplant perfusion in the immediate post-operative period in children risks late recognition of allograft hypoperfusion and vascular complications. Near-infrared spectroscopy (NIRS) is a real-time, non-invasive technique for monitoring tissue oxygenation percutaneously. NIRS monitoring of kidney transplant perfusion has not previously been validated to the gold standard of DUS. We examined whether NIRS tissue oxygenation indices can reliably assess blood flow in established paediatric kidney transplants. Paediatric kidney transplant recipients ages 1-18 years with stable allograft function were eligible. Participants underwent routine DUS assessment of kidney transplant perfusion, including resistive index (RI) and peak systolic velocity at the upper and lower poles. NIRS data [tissue oxygenation index (TOI%)] were recorded for a minimum of 2 min with NIRS sensors placed on the skin over upper and lower allograft poles. Twenty-nine subjects with a median age of 13.3 (range 4.8-17.8) years and a median transplant vintage of 26.5 months participated. Thirteen (45%) were female and 20 (69%) were living donor kidney recipients. NIRS monitoring was well tolerated by all, with 96-100% valid measurements. Significant negative correlations were observed between NIRS TOI% and DUS RI at both the upper and lower poles (r = -0.4 and -0.6, P = 0.04 and 0.001, respectively). Systolic blood pressure but not estimated glomerular filtration rate also correlated with NIRS TOI% (P = 0.01). NIRS indices correlate well with DUS perfusion and haemodynamic parameters in established paediatric kidney transplant recipients. Further studies are warranted to extend NIRS use for continuous real-time monitoring of early post-transplant perfusion status.

Multi-Spectroscopic Analysis of Seed Quality and 13C-Stable-Iotopologue Monitoring in Initial Growth Metabolism of Jatropha curcas L.

PubMed Central

Komatsu, Takanori; Ohishi, Risa; Shino, Amiu; Akashi, Kinya; Kikuchi, Jun

2014-01-01

In the present study, we applied nuclear magnetic resonance (NMR), as well as near-infrared (NIR) spectroscopy, to Jatropha curcas to fulfill two objectives: (1) to qualitatively examine the seeds stored at different conditions, and (2) to monitor the metabolism of J. curcas during its initial growth stage under stable-isotope-labeling condition (until 15 days after seeding). NIR spectra could non-invasively distinguish differences in storage conditions. NMR metabolic analysis of water-soluble metabolites identified sucrose and raffinose family oligosaccharides as positive markers and gluconic acid as a negative marker of seed germination. Isotopic labeling patteren of metabolites in germinated seedlings cultured in agar-plate containg 13C-glucose and 15N-nitrate was analyzed by zero-quantum-filtered-total correlation spectroscopy (ZQF-TOCSY) and 13C-detected 1H-13C heteronuclear correlation spectroscopy (HETCOR). 13C-detected HETOCR with 13C-optimized cryogenic probe provided high-resolution 13C-NMR spectra of each metabolite in molecular crowd. The 13C-13C/12C bondmer estimated from 1H-13C HETCOR spectra indicated that glutamine and arginine were the major organic compounds for nitrogen and carbon transfer from roots to leaves. PMID:25401292

Measuring speaker–listener neural coupling with functional near infrared spectroscopy

PubMed Central

Liu, Yichuan; Piazza, Elise A.; Simony, Erez; Shewokis, Patricia A.; Onaral, Banu; Hasson, Uri; Ayaz, Hasan

2017-01-01

The present study investigates brain-to-brain coupling, defined as inter-subject correlations in the hemodynamic response, during natural verbal communication. We used functional near-infrared spectroscopy (fNIRS) to record brain activity of 3 speakers telling stories and 15 listeners comprehending audio recordings of these stories. Listeners’ brain activity was significantly correlated with speakers’ with a delay. This between-brain correlation disappeared when verbal communication failed. We further compared the fNIRS and functional Magnetic Resonance Imaging (fMRI) recordings of listeners comprehending the same story and found a significant relationship between the fNIRS oxygenated-hemoglobin concentration changes and the fMRI BOLD in brain areas associated with speech comprehension. This correlation between fNIRS and fMRI was only present when data from the same story were compared between the two modalities and vanished when data from different stories were compared; this cross-modality consistency further highlights the reliability of the spatiotemporal brain activation pattern as a measure of story comprehension. Our findings suggest that fNIRS can be used for investigating brain-to-brain coupling during verbal communication in natural settings. PMID:28240295

Quantitative Determination of Fluorine Content in Blends of Polylactide (PLA)–Talc Using Near Infrared Spectroscopy

PubMed Central

Tamburini, Elena; Tagliati, Chiara; Bonato, Tiziano; Costa, Stefania; Scapoli, Chiara; Pedrini, Paola

2016-01-01

Near-infrared spectroscopy (NIRS) has been widely used for quantitative and/or qualitative determination of a wide range of matrices. The objective of this study was to develop a NIRS method for the quantitative determination of fluorine content in polylactide (PLA)-talc blends. A blending profile was obtained by mixing different amounts of PLA granules and talc powder. The calibration model was built correlating wet chemical data (alkali digestion method) and NIR spectra. Using FT (Fourier Transform)-NIR technique, a Partial Least Squares (PLS) regression model was set-up, in a concentration interval of 0 ppm of pure PLA to 800 ppm of pure talc. Fluorine content prediction (R2cal = 0.9498; standard error of calibration, SEC = 34.77; standard error of cross-validation, SECV = 46.94) was then externally validated by means of a further 15 independent samples (R2EX.V = 0.8955; root mean standard error of prediction, RMSEP = 61.08). A positive relationship between an inorganic component as fluorine and NIR signal has been evidenced, and used to obtain quantitative analytical information from the spectra. PMID:27490548

Wearable functional near infrared spectroscopy (fNIRS) and transcranial direct current stimulation (tDCS): expanding vistas for neurocognitive augmentation

PubMed Central

McKendrick, Ryan; Parasuraman, Raja; Ayaz, Hasan

2015-01-01

Contemporary studies with transcranial direct current stimulation (tDCS) provide a growing base of evidence for enhancing cognition through the non-invasive delivery of weak electric currents to the brain. The main effect of tDCS is to modulate cortical excitability depending on the polarity of the applied current. However, the underlying mechanism of neuromodulation is not well understood. A new generation of functional near infrared spectroscopy (fNIRS) systems is described that are miniaturized, portable, and include wearable sensors. These developments provide an opportunity to couple fNIRS with tDCS, consistent with a neuroergonomics approach for joint neuroimaging and neurostimulation investigations of cognition in complex tasks and in naturalistic conditions. The effects of tDCS on complex task performance and the use of fNIRS for monitoring cognitive workload during task performance are described. Also explained is how fNIRS + tDCS can be used simultaneously for assessing spatial working memory. Mobile optical brain imaging is a promising neuroimaging tool that has the potential to complement tDCS for realistic applications in natural settings. PMID:25805976

Greater contribution of cerebral than extracerebral hemodynamics to near-infrared spectroscopy signals for functional activation and resting-state connectivity in infants.

PubMed

Funane, Tsukasa; Homae, Fumitaka; Watanabe, Hama; Kiguchi, Masashi; Taga, Gentaro

2014-10-01

While near-infrared spectroscopy (NIRS) has been increasingly applied to neuroimaging and functional connectivity studies in infants, it has not been quantitatively examined as to what extent the deep tissue (such as cerebral tissue) as opposed to shallow tissue (such as scalp), contributes to NIRS signals measured in infants. A method for separating the effects of deep- and shallow-tissue layers was applied to data of nine sleeping three-month-old infants who had been exposed to 3-s speech sounds or silence (i.e., resting state) and whose hemodynamic changes over their bilateral temporal cortices had been measured by using an NIRS system with multiple source-detector (S-D) distances. The deep-layer contribution was found to be large during resting [67% at S-D 20 mm, 78% at S-D 30 mm for oxygenated hemoglobin (oxy-Hb)] as well as during the speech condition (72% at S-D 20 mm, 82% at S-D 30 mm for oxy-Hb). A left-right connectivity analysis showed that correlation coefficients between left and right channels did not differ between original- and deep-layer signals under no-stimulus conditions and that of original- and deep-layer signals were larger than those of the shallow layer. These results suggest that NIRS signals obtained in infants with appropriate S-D distances largely reflected cerebral hemodynamic changes.

Greater contribution of cerebral than extracerebral hemodynamics to near-infrared spectroscopy signals for functional activation and resting-state connectivity in infants

PubMed Central

Funane, Tsukasa; Homae, Fumitaka; Watanabe, Hama; Kiguchi, Masashi; Taga, Gentaro

2014-01-01

Abstract. While near-infrared spectroscopy (NIRS) has been increasingly applied to neuroimaging and functional connectivity studies in infants, it has not been quantitatively examined as to what extent the deep tissue (such as cerebral tissue) as opposed to shallow tissue (such as scalp), contributes to NIRS signals measured in infants. A method for separating the effects of deep- and shallow-tissue layers was applied to data of nine sleeping three-month-old infants who had been exposed to 3-s speech sounds or silence (i.e., resting state) and whose hemodynamic changes over their bilateral temporal cortices had been measured by using an NIRS system with multiple source-detector (S-D) distances. The deep-layer contribution was found to be large during resting [67% at S-D 20 mm, 78% at S-D 30 mm for oxygenated hemoglobin (oxy-Hb)] as well as during the speech condition (72% at S-D 20 mm, 82% at S-D 30 mm for oxy-Hb). A left-right connectivity analysis showed that correlation coefficients between left and right channels did not differ between original- and deep-layer signals under no-stimulus conditions and that of original- and deep-layer signals were larger than those of the shallow layer. These results suggest that NIRS signals obtained in infants with appropriate S-D distances largely reflected cerebral hemodynamic changes. PMID:26157977

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

PubMed

Alamar, Priscila D; Caramês, Elem T S; Poppi, Ronei J; Pallone, Juliana A L

2016-07-01

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm.

PubMed

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV=0.0776, R(c)=0.9777, RMSEP=0.0963, and R(p)=0.9686 for pH model; RMSECV=1.3544% w/w, R(c)=0.8871, RMSEP=1.4946% w/w, and R(p)=0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry. Copyright © 2012 Elsevier B.V. All rights reserved.

Spectroscopic diagnosis of laryngeal carcinoma using near-infrared Raman spectroscopy and random recursive partitioning ensemble techniques.

PubMed

Teh, Seng Khoon; Zheng, Wei; Lau, David P; Huang, Zhiwei

2009-06-01

In this work, we evaluated the diagnostic ability of near-infrared (NIR) Raman spectroscopy associated with the ensemble recursive partitioning algorithm based on random forests for identifying cancer from normal tissue in the larynx. A rapid-acquisition NIR Raman system was utilized for tissue Raman measurements at 785 nm excitation, and 50 human laryngeal tissue specimens (20 normal; 30 malignant tumors) were used for NIR Raman studies. The random forests method was introduced to develop effective diagnostic algorithms for classification of Raman spectra of different laryngeal tissues. High-quality Raman spectra in the range of 800-1800 cm(-1) can be acquired from laryngeal tissue within 5 seconds. Raman spectra differed significantly between normal and malignant laryngeal tissues. Classification results obtained from the random forests algorithm on tissue Raman spectra yielded a diagnostic sensitivity of 88.0% and specificity of 91.4% for laryngeal malignancy identification. The random forests technique also provided variables importance that facilitates correlation of significant Raman spectral features with cancer transformation. This study shows that NIR Raman spectroscopy in conjunction with random forests algorithm has a great potential for the rapid diagnosis and detection of malignant tumors in the larynx.

Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy

NASA Astrophysics Data System (ADS)

Ying, Yibin; Yu, Haiyan; Pan, Xingxiang; Lin, Tao

2006-10-01

To evaluate the applicability of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining ethanol concentration of Chinese rice wine in square brown glass bottle, transmission spectra of 100 bottled Chinese rice wine samples were collected in the spectral range of 350-1200 nm. Statistical equations were established between the reference data and VIS-NIR spectra by partial least squares (PLS) regression method. Performance of three kinds of mathematical treatment of spectra (original spectra, first derivative spectra and second derivative spectra) were also discussed. The PLS models of original spectra turned out better results, with higher correlation coefficient in calibration (R cal) of 0.89, lower root mean standard error of calibration (RMSEC) of 0.165, and lower root mean standard error of cross validation (RMSECV) of 0.179. Using original spectra, PLS models for ethanol concentration prediction were developed. The R cal and the correlation coefficient in validation (R val) were 0.928 and 0.875, respectively; and the RMSEC and the root mean standard error of validation (RMSEP) were 0.135 (%, v v -1) and 0.177 (%, v v -1), respectively. The results demonstrated that VIS-NIR spectroscopy could be used to predict ethanol concentration in bottled Chinese rice wine.

Determination of Spatially Resolved Tablet Density and Hardness Using Near-Infrared Chemical Imaging (NIR-CI).

PubMed

Talwar, Sameer; Roopwani, Rahul; Anderson, Carl A; Buckner, Ira S; Drennen, James K

2017-08-01

Near-infrared chemical imaging (NIR-CI) combines spectroscopy with digital imaging, enabling spatially resolved analysis and characterization of pharmaceutical samples. Hardness and relative density are critical quality attributes (CQA) that affect tablet performance. Intra-sample density or hardness variability can reveal deficiencies in formulation design or the tableting process. This study was designed to develop NIR-CI methods to predict spatially resolved tablet density and hardness. The method was implemented using a two-step procedure. First, NIR-CI was used to develop a relative density/solid fraction (SF) prediction method for pure microcrystalline cellulose (MCC) compacts only. A partial least squares (PLS) model for predicting SF was generated by regressing the spectra of certain representative pixels selected from each image against the compact SF. Pixel selection was accomplished with a threshold based on the Euclidean distance from the median tablet spectrum. Second, micro-indentation was performed on the calibration compacts to obtain hardness values. A univariate model was developed by relating the empirical hardness values to the NIR-CI predicted SF at the micro-indented pixel locations: this model generated spatially resolved hardness predictions for the entire tablet surface.

An innovative approach to near-infrared spectroscopy using a standard mobile device and its clinical application in the real-time visualization of peripheral veins.

PubMed

Juric, Simon; Zalik, Borut

2014-11-25

Excessive venipunctures are a significant problem both in emergency rooms and during hospital stays. Near-infrared (NIR) illumination devices improve venipuncture success rate but their usage is limited by their availability and economic cost. The objectives of this study were to develop a low-cost NIR spectroscopy prototype from a standard mobile device, to evaluate its efficacy and acceptance as an educational tool, and in a clinical setting. Through a user-centric design process a prototype device was developed. Its educational efficacy was evaluated through a non-invasive, observational study (20 student clinicians, 25 subjects) and its acceptance was assessed using quantitative and qualitative analysis. A smaller clinical trial was performed by a group of 4 medical professionals over a period of 6 weeks that involved 64 patients. The prototype enables real-time visualization of peripheral veins on a variety of Android-based devices. The prototype was 35.2% more successful in visualizing and locating veins (n = 500 attempts) than the nursing students. The acceptance assessment revealed high perception of usefulness, satisfaction, and ease of use. In the clinical trial, 1.6 (SD 1.3) additional veins per patient were identified compared with the traditional visualization methods. To the best of our knowledge this is the first study that describes the design, feasibility and application of an NIR spectroscopy prototype developed on a standard mobile device.

Hyperspectral imaging using near infrared spectroscopy to monitor coat thickness uniformity in the manufacture of a transdermal drug delivery system.

PubMed

Pavurala, Naresh; Xu, Xiaoming; Krishnaiah, Yellela S R

2017-05-15

Hyperspectral imaging using near infrared spectroscopy (NIRS) integrates spectroscopy and conventional imaging to obtain both spectral and spatial information of materials. The non-invasive and rapid nature of hyperspectral imaging using NIRS makes it a valuable process analytical technology (PAT) tool for in-process monitoring and control of the manufacturing process for transdermal drug delivery systems (TDS). The focus of this investigation was to develop and validate the use of Near Infra-red (NIR) hyperspectral imaging to monitor coat thickness uniformity, a critical quality attribute (CQA) for TDS. Chemometric analysis was used to process the hyperspectral image and a partial least square (PLS) model was developed to predict the coat thickness of the TDS. The goodness of model fit and prediction were 0.9933 and 0.9933, respectively, indicating an excellent fit to the training data and also good predictability. The % Prediction Error (%PE) for internal and external validation samples was less than 5% confirming the accuracy of the PLS model developed in the present study. The feasibility of the hyperspectral imaging as a real-time process analytical tool for continuous processing was also investigated. When the PLS model was applied to detect deliberate variation in coating thickness, it was able to predict both the small and large variations as well as identify coating defects such as non-uniform regions and presence of air bubbles. Published by Elsevier B.V.

Multi-parameters monitoring during traditional Chinese medicine concentration process with near infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Liu, Ronghua; Sun, Qiaofeng; Hu, Tian; Li, Lian; Nie, Lei; Wang, Jiayue; Zhou, Wanhui; Zang, Hengchang

2018-03-01

As a powerful process analytical technology (PAT) tool, near infrared (NIR) spectroscopy has been widely used in real-time monitoring. In this study, NIR spectroscopy was applied to monitor multi-parameters of traditional Chinese medicine (TCM) Shenzhiling oral liquid during the concentration process to guarantee the quality of products. Five lab scale batches were employed to construct quantitative models to determine five chemical ingredients and physical change (samples density) during concentration process. The paeoniflorin, albiflorin, liquiritin and samples density were modeled by partial least square regression (PLSR), while the content of the glycyrrhizic acid and cinnamic acid were modeled by support vector machine regression (SVMR). Standard normal variate (SNV) and/or Savitzkye-Golay (SG) smoothing with derivative methods were adopted for spectra pretreatment. Variable selection methods including correlation coefficient (CC), competitive adaptive reweighted sampling (CARS) and interval partial least squares regression (iPLS) were performed for optimizing the models. The results indicated that NIR spectroscopy was an effective tool to successfully monitoring the concentration process of Shenzhiling oral liquid.

Breast tumor characterization using near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Kang, Kyung A.; Chance, Britton; Zhao, Shiyin; Srinivasan, Sudhakar; Patterson, E.; Troupin, R.

1993-09-01

NIR time resolved spectroscopy (TRS) is one of the most feasible methods which can be used for the characterization of biological systems, due to its non-invasive nature and safety features in measurement. Breast cancer is the leading cause of death in women ages 40 - 44 and accounts for 32% of all cancer diagnosis in women. The occurrence rate is as high as one out of nine women in the USA. Breast cancer is the most common form of cancer and the second leading cause of cancer death in North America. Therefore, it is natural for researchers in the field of NIR spectroscopy to have strong interest in optical properties of normal and abnormal breast tissue. One of the main interests of NIR spectroscopy in breast cancer is the localization of the tumor. Another important feature is to characterize an anomaly non- invasively since more than 75% of mammographical anomalies are found to be benign. This could reduce the anxiety that the patients would have, as well as lower the clinical expense for the biopsy and operation (approximately $4,000 per a case).

The application of nirvana to silvicultural studies

Treesearch

Chi-Leung So; Thomas Elder; Leslie Groom; John S. Kush; Jennifer Myszewski; Todd Shupe

2006-01-01

Previous results from this laboratory have shown that near infrared (NIR) spectroscopy, coupled with multivariate analysis, can be a powerful tool for the prediction of wood quality. While wood quality measurements are of utility, their determination can be both time and labor intensive, thus limiting their use where large sample sizes are concerned. This paper will...

Rapid analysis of the microfibril angle of loblolly pine from two test sites using near-infrared analysis

Treesearch

ChiLeung So; Jennifer Myszewski; Thomas Elder; Les Groom

2013-01-01

Abstract There have been several recent studies employing near infrared (NIR) spectroscopy for the rapid determination of microfibril angle (MFA). However, only a few have utilized samples cut from individual rings of increment cores, and none have been as large as this present study, sampling over 600 trees from two test sites producing over 3000 individual ring...

Fluorescent magnetic hybrid nanoprobe for multimodal bioimaging

PubMed Central

Bright, Vanessa

2011-01-01

A fluorescent magnetic hybrid imaging nanoprobe (HINP) was fabricated by conjugation of superparamagnetic Fe3O4 nanoparticles and visible light-emitting (~600 nm) fluorescent CdTe/CdS quantum dots (QDs). The assembly strategy used the covalent linking of the oxidized dextran shell of magnetic particles to the glutathione ligands of QDs. Synthesized HINP formed stable water-soluble colloidal dispersions. The structure and properties of the particles were characterized by transmission electron and atomic force microscopy, energy dispersive X-ray analysis and inductively coupled plasma optical emission spectroscopy, dynamic light scattering analysis, optical absorption and photoluminescence spectroscopy, and fluorescent imaging. The luminescence imaging region of the nanoprobe was extended to the near-infrared (NIR) (~800 nm) by conjugation of superparamagnetic nanoparticles with synthesized CdHgTe/CdS QDs. Cadmium, mercury based QDs in HINP can be easily replaced by novel water soluble glutathione stabilized AgInS2/ZnS QDs to present a new class of cadmium-free multimodal imaging agents. Observed NIR photoluminescence of fluorescent magnetic nanocomposites supports their use for bioimaging. The developed HINP provides dual-imaging channels for simultaneous optical and magnetic resonance imaging. PMID:21597146

Discrimination of premalignant lesions and cancer tissues from normal gastric tissues using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Luo, Shuwen; Chen, Changshui; Mao, Hua; Jin, Shaoqin

2013-06-01

The feasibility of early detection of gastric cancer using near-infrared (NIR) Raman spectroscopy (RS) by distinguishing premalignant lesions (adenomatous polyp, n=27) and cancer tissues (adenocarcinoma, n=33) from normal gastric tissues (n=45) is evaluated. Significant differences in Raman spectra are observed among the normal, adenomatous polyp, and adenocarcinoma gastric tissues at 936, 1003, 1032, 1174, 1208, 1323, 1335, 1450, and 1655 cm-1. Diverse statistical methods are employed to develop effective diagnostic algorithms for classifying the Raman spectra of different types of ex vivo gastric tissues, including principal component analysis (PCA), linear discriminant analysis (LDA), and naive Bayesian classifier (NBC) techniques. Compared with PCA-LDA algorithms, PCA-NBC techniques together with leave-one-out, cross-validation method provide better discriminative results of normal, adenomatous polyp, and adenocarcinoma gastric tissues, resulting in superior sensitivities of 96.3%, 96.9%, and 96.9%, and specificities of 93%, 100%, and 95.2%, respectively. Therefore, NIR RS associated with multivariate statistical algorithms has the potential for early diagnosis of gastric premalignant lesions and cancer tissues in molecular level.

ASTM clustering for improving coal analysis by near-infrared spectroscopy.

PubMed

Andrés, J M; Bona, M T

2006-11-15

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.

Near infrared spectroscopy combined with multivariate analysis for monitoring the ethanol precipitation process of fraction I + II + III supernatant in human albumin separation

NASA Astrophysics Data System (ADS)

Li, Can; Wang, Fei; Zang, Lixuan; Zang, Hengchang; Alcalà, Manel; Nie, Lei; Wang, Mingyu; Li, Lian

2017-03-01

Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I + II + III (FI + II + III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (Rp2), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501 g/L, 0.465 g/L and 5.57 for TP, and 0.969, 0.530 g/L, 0.341 g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI + II + III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS.

Near infrared spectroscopy combined with multivariate analysis for monitoring the ethanol precipitation process of fraction I+II+III supernatant in human albumin separation.

PubMed

Li, Can; Wang, Fei; Zang, Lixuan; Zang, Hengchang; Alcalà, Manel; Nie, Lei; Wang, Mingyu; Li, Lian

2017-03-15

Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I+II+III (FI+II+III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (R p 2 ), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501g/L, 0.465g/L and 5.57 for TP, and 0.969, 0.530g/L, 0.341g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI+II+III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS. Copyright © 2016 Elsevier B.V. All rights reserved.

Noise reduction in functional near-infrared spectroscopy signals by independent component analysis

NASA Astrophysics Data System (ADS)

Santosa, Hendrik; Jiyoun Hong, Melissa; Kim, Sung-Phil; Hong, Keum-Shik

2013-07-01

Functional near-infrared spectroscopy (fNIRS) is used to detect concentration changes of oxy-hemoglobin and deoxy-hemoglobin in the human brain. The main difficulty entailed in the analysis of fNIRS signals is the fact that the hemodynamic response to a specific neuronal activation is contaminated by physiological and instrument noises, motion artifacts, and other interferences. This paper proposes independent component analysis (ICA) as a means of identifying the original hemodynamic response in the presence of noises. The original hemodynamic response was reconstructed using the primary independent component (IC) and other, less-weighting-coefficient ICs. In order to generate experimental brain stimuli, arithmetic tasks were administered to eight volunteer subjects. The t-value of the reconstructed hemodynamic response was improved by using the ICs found in the measured data. The best t-value out of 16 low-pass-filtered signals was 37, and that of the reconstructed one was 51. Also, the average t-value of the eight subjects' reconstructed signals was 40, whereas that of all of their low-pass-filtered signals was only 20. Overall, the results showed the applicability of the ICA-based method to noise-contamination reduction in brain mapping.

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.