Design and characterization of protein films for modeling near-infrared spectra of human tissue

The Analyst ◽  
2015 ◽  
Vol 140 (12) ◽  
pp. 3981-3988 ◽  
Author(s):  
Sanjeewa R. Karunathilaka ◽  
Gary W. Small
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Human Tissue ◽  
Near Infrared ◽  
Laboratory Simulation ◽  
Protein Films ◽  
Near Infrared Spectra

Films of keratin and collagen proteins are fabricated for use in implementing a laboratory simulation of noninvasive glucose measurements based on transmission near-infrared spectroscopy of human tissue.

Curve fitting in Fourier transform near infrared spectroscopy used for the analysis of bacterial cells

2017 ◽  
Vol 25 (3) ◽  
pp. 151-164 ◽  
Author(s):  
Pavel Krepelka ◽  
Iveta Hynstova ◽  
Roman Pytel ◽  
Fernando Pérez-Rodríguez ◽  
Jean-Michel Roger ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Differential Evolution ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Curve Fitting ◽  
Near Infrared ◽  
Bacterial Species ◽  
Lower Sensitivity ◽  
Data Set ◽  
Near Infrared Spectra

Infrared spectroscopy is a prominent molecular technique for bacterial analysis. Within its context, near infrared spectroscopy in particular brings benefits over other vibrational approaches; these advantages include, for example, lower sensitivity to water, high penetration depth and low cost. However, near infrared spectroscopy is not popular within microbiology, because the spectra of organic samples are difficult to interpret. We propose a comparison of spectral curve-fitting methods, namely, techniques that facilitate the interpretation of most peaks, simplify the spectra and improve the prediction of bacterial species from the relevant near infrared spectra. The performances of three common curve-fitting algorithms and the technique based on the differential evolution were compared via a synthesized experimental spectrum. Utilizing the obtained results, the spectra of three different bacterial species were curve fit by optimized algorithm. The proposed algorithm decomposed the spectra to specific absorption peaks, whose parameters were estimated via the differential evolution approach initialized through Levenberg-Marquardt optimization; subsequently, the spectra were classified with conventional procedures and using the parameters of the revealed peaks. On a limited data set, the correct classification rate computed by partial least squares discriminant analysis was 95%. When we employed the peak parameters for the classification, the rate corresponded to 91.7%. According to the Gaussian formula, the parameters comprise the spectral peak position, amplitude and width. The most important peaks for bacterial discrimination were identified by analysis of variance and interpreted as N–H stretching bonds in proteins, cis bonds and CH2 absorption in fatty acids. We examined some aspects of the behaviour of standard curve-fitting algorithms and proposed differential evolution to optimize the fitting process. Based on the correct use of these algorithms, the near infrared spectra of bacteria can be interpreted and the full potential of near infrared spectroscopy in microbiology exploited.

The use of two-dimensional spectroscopy to interpret the effect of temperature on the near infrared spectra of whisky

2020 ◽  
Vol 28 (3) ◽  
pp. 148-152 ◽  
Author(s):  
Ishita Joshi ◽  
Vi Khanh Truong ◽  
J Chapman ◽  
D Cozzolino
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Infrared Region ◽  
Correlation Spectroscopy ◽  
Alcoholic Beverages ◽  
Effect Of Temperature ◽  
Two Dimensional ◽  
Near Infrared Spectra

The variations in temperature during the analysis of alcoholic beverages are of importance to develop protocols based on near infrared spectroscopy. The objective of this study was to evaluate the effect of increasing temperature on the near infrared spectra of whisky samples using two-dimensional correlation spectroscopy. Whisky samples from different commercial labels were analyzed at four different temperatures (25°C, 35°C, 45°C, and 55°C) using a UV–VIS–NIR instrument. Asynchronous and synchronous two-dimensional correlation spectroscopy was used to reveal the effect of temperature on the near infrared spectra of the samples. The results of this study indicated that temperatures between 40°C and 55°C alter absorption at specific wavelengths in the near infrared region of the whisky samples analyzed. The combination of near infrared spectroscopy with two-dimensional correlation spectroscopy has the potential to dramatically improve the efficiency of analytical laboratories, considering the range of data that can be collected.

scholarly journals Quality analysis of the near-infrared spectra of wheat samples

2012 ◽  
pp. 97-100
Author(s):  
Éva Kónya ◽  
Géza Kovács ◽  
Zoltán Győri
Keyword(s):  
Infrared Spectroscopy ◽  
Quantitative Analysis ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Quality Analysis ◽  
Sample Population ◽  
Non Invasive ◽  
Near Infrared Spectra ◽  
Calibration Equations

The near infrared spectroscopy is widely used in the different industries as a rapid, non-invasive analitical tool. It is suitable for identification, qualification and quantitative analysis as well. As this technique is indirect, to make accurate calibration equations we need a proper sample population. Before the quantitaive analysis, developing calibiration modells we have to collect and examine the spectra. In our study we examined wheat samples with known origins to find if there is any effect of the growing area on the NIR spectra.

Screening Pap Smears with Near-Infrared Spectroscopy

1995 ◽  
Vol 49 (4) ◽  
pp. 432-436 ◽  
Author(s):  
Zhengfang Ge ◽  
Chris W. Brown ◽  
Harold J. Kisner
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Principal Component ◽  
Diagnostic Value ◽  
Clinical Analysis ◽  
Pap Smears ◽  
Human Tissues ◽  
Near Infrared Spectra

A rapid method for the analysis of Pap smears has been developed with the use of near-infrared spectroscopy. Spectra of Pap smears from 50 female patients including 30 with normal cells, 9 with atypical cells, and 11 with cervical cancer were measured in the near-IR region of 4000 to 10,000 cm−1. Both the original spectra and the second-derivative spectra of Pap smears were subjected to data analysis. The malignant samples displayed abnormal spectra compared with the corresponding normal cervical samples; the atypical samples have spectral features characteristic of both normal and abnormal samples. With the use of principal component analysis (PCA) and discriminant analysis, the samples were grouped in patterns that were consistent with clinical analysis. Since obtaining near-infrared spectra of human tissues is a rapid and inexpensive process, the results suggest that the near-infrared spectra of human tissues may be of diagnostic value for cancer diagnosis.

Using blood near infrared spectra from steers to classify fat and meat samples with low or high levels of vaccenic acid

NIR news ◽  
2018 ◽  
Vol 29 (2) ◽  
pp. 10-13
Author(s):  
N Prieto ◽  
MER Dugan ◽  
P Vahmani ◽  
DC Rolland ◽  
JL Aalhus
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Whole Blood ◽  
Near Infrared ◽  
Vaccenic Acid ◽  
Subcutaneous Fat ◽  
Near Infrared Spectra ◽  
Discriminant Analyses

Near infrared spectroscopy on steer blood was tested to discriminate between subcutaneous fat and longissimus thoracis samples with low or high levels of vaccenic acid. One day prior slaughter, blood samples from steers were harvested and near infrared spectra were collected on both whole blood and red blood cells. At slaughter, samples of subcutaneous fat and longissimus thoracis were collected and vaccenic acid content was analyzed by gas chromatography. Partial least squares discriminant analyses based on whole blood and red blood cell near infrared spectra were applied to classify subcutaneous fat and longissimus thoracis samples according to their content of vaccenic acid (low or high). Based on the results from the partial least squares discriminant analyses, subcutaneous fat and longissimus thoracis samples with low or high content of vaccenic acid could be discriminated from the blood near infrared spectra with accuracy from 74 to 95%. Application of near infrared spectroscopy technology on steer blood may have potential as early screening of live animals based on low or high levels of vaccenic acid in subcutaneous fat or longissimus thoracis.

scholarly journals Sample selection, calibration and validation of models developed from a large dataset of near infrared spectra of tree leaves

2020 ◽  
Vol 28 (4) ◽  
pp. 186-203
Author(s):  
Jessie Au ◽  
Kara N Youngentob ◽  
William J Foley ◽  
Ben D Moore ◽  
Tom Fearn
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Reference Values ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Research Groups ◽  
Available Nitrogen ◽  
Near Infrared Spectra ◽  
Formylated Phloroglucinol Compounds ◽  
Chemical Traits

Near infrared spectroscopy is widely used to rapidly and cost-effectively collect chemical information from plant samples. Large datasets with hundreds to thousands of spectra and reference values are increasingly becoming more common as researchers accumulate data over many years or across research groups. These datasets potentially contain great spectral and chemical variation and could produce a broadly-applicable calibration model. In this study, partial least squares regression was used to model relationships between near infrared spectra and the foliar concentration of two ecologically-important chemical traits, available nitrogen and total formylated phloroglucinol compounds in Eucalyptus leaves. The nested spatial structure within the extensive dataset of spectra and reference values from 80 species of Eucalyptus was taken into account during calibration development and model validation. Geographic variation amongst samples influenced how well available nitrogen could be predicted. Predictive error of the model was greatest when tested against samples from different Australian states and local government areas to the calibration set. In addition, the results showed that simply relying on spectral variation (assessed by Mahalanobis distance) may mislead researchers into how many reference values are needed. The prediction accuracy of the model of available nitrogen differed little whether 300 or up to 987 calibration samples were included, which indicated that an excessive number of reference values were obtained. Lastly, a suitable multi-species calibration for formylated phloroglucinol compounds was produced and the difficulties associated with predicting complex chemical traits were discussed. Directing effort towards broadly applicable models will encourage sharing of calibration models across projects and research groups and facilitate the integration of near infrared spectroscopy in many research fields.

scholarly journals Near-Infrared Spectroscopy Study of Serpentine Minerals and Assignment of the OH Group

Crystals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1130
Author(s):  
Shaokun Wu ◽  
Mingyue He ◽  
Mei Yang ◽  
Biyao Zhang ◽  
Feng Wang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Bending Vibrations ◽  
Bending Vibration ◽  
Serpentine Minerals ◽  
Near Infrared Spectra ◽  
Stretching Vibration ◽  
Serpentine Mineral

Three different kinds of serpentine mineral samples were investigated using Fourier transform near-infrared spectroscopy (FTNIR). The results show that there are obvious differences in the characteristic infrared spectra of the three serpentine group minerals (lizardite, chrysotile, and antigorite), which can easily be used to identify these serpentine minerals. The combination of weak and strong peaks in the spectrum of lizardite appears at 3650 and 3690 cm−1, while the intensities of the peaks at 4281 and 4301 cm−1 (at 7233 and 7241 cm−1, respectively) are similar. A combination of weak and strong peaks in chrysotile appears at 3648 and 3689 cm−1 and at 4279 and 4302 cm−1, and a single strong peak appears at 7233 cm−1. In antigorite, there are strong single peaks at 3674, 4301, and 7231 cm−1, and the remaining peaks are shoulder peaks or are not obvious. The structural OH mainly appears as characteristic peaks in four regions, 500–720, 3600–3750, 4000–4600, and 7000–7600 cm−1, corresponding to the OH bending vibration, the OH stretching vibration, the OH secondary combination vibration, and the OH overtone vibration, respectively. In the combined frequency vibration region, the characteristic peak near 4300 cm−1 is formed by the combination of the internal and external stretching vibrations and bending vibrations of the structural OH group. The overtone vibrations of the OH stretching vibration appear near 7200 cm−1, and the practical factor is about 1.965. The near-infrared spectra of serpentine minerals are closely related to their structural differences and isomorphous substitutions. Therefore, near-infrared spectroscopy can be used to identify serpentine species and provides a basis for studies on the genesis and metallogenic environment of these minerals.

scholarly journals Near-infrared spectroscopy used to predict soybean seed germination and vigour

2018 ◽  
Vol 28 (3) ◽  
pp. 245-252 ◽  
Author(s):  
Maythem Al-Amery ◽  
Robert L. Geneve ◽  
Mauricio F. Sanches ◽  
Paul R. Armstrong ◽  
Elizabeth B. Maghirang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Seed Germination ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Soybean Seed ◽  
Seed Vigour ◽  
Near Infrared Spectra ◽  
High Germination ◽  
Qualitative Models

AbstractRapid, non-destructive methods for measuring seed germination and vigour are valuable. Standard germination and seed vigour were determined using 81 soybean seed lots. From these data, seed lots were separated into high and low germinating seed lots as well as high, medium and low vigour seed lots. Near-infrared spectra (950–1650 nm) were collected for training and validation samples for each seed category and used to create partial least squares (PLS) prediction models. For both germination and vigour, qualitative models provided better discrimination of high and low performing seed lots compared with quantitative models. The qualitative germination prediction models correctly identified low and high germination seed lots with an accuracy between 85.7 and 89.7%. For seed vigour, qualitative predictions for the 3-category (low, medium and high vigour) models could not adequately separate high and medium vigour seeds. However, the 2-category (low, medium plus high vigour) prediction models could correctly identify low vigour seed lots between 80 and 100% and the medium plus high vigour seed lots between 96.3 and 96.6%. To our knowledge, the current study is the first to provide near-infrared spectroscopy (NIRS)-based predictive models using agronomically meaningful cut-offs for standard germination and vigour on a commercial scale using over 80 seed lots.

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