scholarly journals Effect of Sample Complexity on Quantification of Analytes in Aqueous Samples by Near-Infrared Spectroscopy

2000 ◽  
Vol 54 (2) ◽  
pp. 255-261 ◽  
Author(s):  
Mark R. Riley ◽  
Mark A. Arnold ◽  
David W. Murhammer
Keyword(s):  
Infrared Spectroscopy ◽  
Small Molecules ◽  
Near Infrared Spectroscopy ◽  
Standard Error ◽  
Measurement Errors ◽  
Near Infrared ◽  
Small Degree ◽  
Sample Complexity ◽  
Aqueous Samples ◽  
The Impact

This study was undertaken to quantitate the impact of increasing sample complexity on near-infrared spectroscopic (NIRS) measurements of small molecules in aqueous solutions with varying numbers of components. Samples with 2, 6, or 10 varying components were investigated. Within the 10-component samples, three analytes were quantified with errors below 6% and seven of the analytes were quantified with errors below 10%. An increase in the number of varying components can substantially increase the error associated with measurement. A comparison of measurement errors across sample sets, as gauged by the standard error of prediction (SEP), reveals that an increase in the number of varying components from 2 to 6 increases the SEP by approximately 50%. An increase from 2 to 10 varying components increases the SEP by approximately 340%. While there appear to be no substantial correlations between the presence of a specific analyte and the errors associated with quantification of another analyte, several analytes do display a small degree of sensitivity to varying concentrations of certain background components. The analysis also demonstrates that calibrations containing an overestimation of the numbers of varying components can substantially increase measurement errors and so calibrations must be constructed with an accurate understanding of the number of varying components that are likely to be encountered.

scholarly journals Ability of near-infrared spectroscopy and chemometrics to predict the age of mosquitoes reared under different conditions

2020 ◽  
Author(s):  
Oselyne Ong ◽  
Elise Kho ◽  
Pedro Esperança ◽  
Chris Freebairn ◽  
Floyd Dowell ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Field Application ◽  
Machine Learning Techniques ◽  
Island Population ◽  
Natural Environments ◽  
Pls Regression ◽  
Field Methods ◽  
The Impact

Abstract Background: Practical, field-ready age-grading tools for mosquito vectors of disease are urgently needed because of the impact that daily survival has on vectorial capacity. Previous studies have shown that near-infrared spectroscopy (NIRS), in combination with chemometrics and predictive modeling, can forecast the age of laboratory-reared mosquitoes with moderate to high accuracy. It remains unclear whether the technique has utility for identifying shifts in the age structure of wild-caught mosquitoes. Here we investigate whether models derived from the laboratory strain of mosquitoes can be used to predict the age of mosquitoes grown from pupae collected in the field. Methods: NIR spectra from adult female Aedes albopictus mosquitoes reared in the laboratory (2, 5, 8, 12 and 15 days old) were compared to spectra from mosquitoes emerging from wild-caught pupae (1, 7 and 14 days old). Different partial least squares (PLS) regression methods trained on spectra from laboratory mosquitoes were evaluated on their ability to predict the age of mosquitoes from more natural environments. Results: Models trained on spectra from laboratory-reared material were able to predict the age of other laboratory-reared mosquitoes with moderate accuracy and successfully differentiated all day 2 and 15 mosquitoes. Models derived with laboratory mosquitoes could not differentiate between field-derived age groups, with age predictions relatively indistinguishable for day 1-14. Pre-processing of spectral data and improving the PLS regression framework to avoid overfitting can increase accuracy, but predictions of mosquitoes reared in different environments remained poor. Principle component analysis confirms substantial spectral variations between laboratory and field-derived mosquitoes despite both originating from the same island population. Conclusions: Models trained on laboratory mosquitoes were able to predict ages of laboratory mosquitoes with good sensitivity and specificity though they were unable to predict age of field-derived mosquitoes. This study suggests that laboratory-reared mosquitoes do not capture enough environmental variation to accurately predict the age of the same species reared under different conditions. Further research is needed to explore alternative pre-processing methods and machine learning techniques, and to understand factors that affect absorbance in mosquitoes before field application using NIRS.

Enhancing near infrared spectroscopy models to identify omega-3 fish oils used in the nutraceutical industry by means of calibration range extension

2018 ◽  
Vol 26 (4) ◽  
pp. 245-261 ◽  
Author(s):  
Sanette van der Merwe ◽  
Marena Manley ◽  
Merrill Wicht
Keyword(s):  
Fatty Acids ◽  
Gas Chromatography ◽  
Infrared Spectroscopy ◽  
Polyunsaturated Fatty Acids ◽  
Near Infrared Spectroscopy ◽  
Standard Error ◽  
Near Infrared ◽  
Fish Oils ◽  
Omega 3 ◽  
Alternative Method

The high demand for omega-3 fish oil nutraceuticals (dietary supplements) is due to the numerous health benefits contributed by the polyunsaturated fatty acids. The nutraceutical industry is required to follow good manufacturing practice standards in order to ensure label claims and prevent adulteration. It is vital that the quality control procedures will be able to detect adulterated products. It is thus necessary to ensure that the analytical techniques are adequate by using validated methods. The qualification or identification of natural fish oils is a difficult task due to overlapping concentration ranges of polyunsaturated fatty acids and other similar properties. Gas chromatography is the prescribed technique in the nutraceutical industry for analysis of omega-3 fatty acids, but it is time-consuming and costly. Near infrared spectroscopy is a rapid and cost-effective technique which can replace the prescribed method if it is proven to be equivalent, through validation, to the criteria as prescribed by the pharmacopoeias and other industry guidelines. In this study, near infrared spectroscopy in combination with chemometrics was considered as an alternative method to gas chromatography to identify various commercial fish oils and to quantify the polyunsaturated fatty acids. Identification methods were developed for nine commercial omega-3 fish oils by using spectral libraries. Quantitative near infrared methods were developed for arachidonic acid, docosahexaenoic acid and eicosapentaenoic acid in fish oils expressed as mg.g−1 as well as % area using partial least squares regression and independent validation by superimposing datasets with mutual properties. Based on the statistics in terms of standard error of calibration, R2, standard error of prediction and r of the polyunsaturated fatty acid models, the near infrared method was equivalent to the prescribed gas chromatography methods, and precision results obtained were also within the prescribed criteria. Near infrared spectroscopy and chemometrics can be used for conclusive identification and quantification of omega-3 fish oils, thereby minimizing the risk of adulteration. The method also complied with the prescribed pharmaceutical method validation criteria, and therefore was proven as an alternative method to gas chromatography for the nutraceutical industry.

scholarly journals Acute ingestion of rosemary water: Evidence of cognitive and cerebrovascular effects in healthy adults

2018 ◽  
Vol 32 (12) ◽  
pp. 1319-1329 ◽  
Author(s):  
Mark Moss ◽  
Ellen Smith ◽  
Matthew Milner ◽  
Jemma McCready
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Cognitive Task ◽  
Testing Procedure ◽  
Healthy Adults ◽  
Cognitive Testing ◽  
Western Society ◽  
Acute Ingestion ◽  
The Impact

Background: The use of herbal extracts and supplements to enhance health and wellbeing is increasing in western society. Aims: This study investigated the impact of the acute ingestion of a commercially available water containing an extract and hydrolat of rosemary ( Rosmarinus officinalis L. syn. Salvia rosmarinus Schleid.). Aspects of cognitive functioning, mood and cerebrovascular response measured by near-infrared spectroscopy provided the dependent variables. Methods: Eighty healthy adults were randomly allocated to consume either 250 mL of rosemary water or plain mineral water. They then completed a series of computerised cognitive tasks, followed by subjective measures of alertness and fatigue. Near-infrared spectroscopy monitored levels of total, oxygenated and deoxygenated haemoglobin at baseline and throughout the cognitive testing procedure. Results: Analysis of the data revealed a number of statistically significant, small, beneficial effects of rosemary water on cognition, consistent with those found previously for the inhalation of the aroma of rosemary essential oil. Of particular interest here are the cerebrovascular effects noted for deoxygenated haemoglobin levels during cognitive task performance that were significantly higher in the rosemary water condition. This represents a novel finding in this area, and may indicate a facilitation of oxygen extraction at times of cognitive demand. Conclusion: Taken together the data suggest potential beneficial properties of acute consumption of rosemary water. The findings are discussed in terms of putative metabolic and cholinergic mechanisms.

Rapid determination of oil content in dried-ground oil palm mesocarp and kernel using near infrared spectroscopy

2017 ◽  
Vol 25 (5) ◽  
pp. 338-347 ◽  
Author(s):  
Sudarno ◽  
Divo D Silalahi ◽  
Tauvik Risman ◽  
Baiq L Widyastuti ◽  
F Davrieux ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Oil Palm ◽  
Standard Error ◽  
Oil Content ◽  
Near Infrared ◽  
Cross Validation ◽  
Calibration Model ◽  
Reliable Technique

Near infrared spectroscopy calibrations for rapid oil content determination of dried-ground oil palm mesocarp and kernel were developed. Samples were analyzed, one set using the Soxhlet extraction method for reference analysis and the other set scanned by near infrared spectroscopy instrument for calibration. Successful calibrations were obtained with good accuracy and precision for mesocarp and kernel, based on statistical models. Math treatment and scatter correction had significant effects on the fitting of the calibration model. The best obtained calibration models were demonstrated by multiple correlation coefficient (R2), standard error of calibration, standard error of cross validation, coefficient of determination in cross validation (1-VR) and relative predictive deviation of calibration, which respectively were 0.997, 1.21%, 1.23%, 0.997 and 17.89 for mesocarp and 0.952, 0.47%, 0.53%, 0.94 and 4.00 for kernel. The correlations between reference and predicted values for samples in the validation sets were in agreement with high linearity, high ratio performance to deviation of prediction (≥4.00) and low standard error of prediction samples for both samples. The results demonstrated that near infrared spectroscopy can be used as an alternative and reliable technique to estimate the mesocarp and kernel oil contents in dry matter basis accurately and rapidly.

Near-Infrared Spectroscopic Measurement of Lactate in Human Plasma

2000 ◽  
Vol 54 (2) ◽  
pp. 300-304 ◽  
Author(s):  
Denis Lafrance ◽  
Larry C. Lands ◽  
Laura Hornby ◽  
David H. Burns
Keyword(s):  
Infrared Spectroscopy ◽  
Human Plasma ◽  
Near Infrared Spectroscopy ◽  
Standard Error ◽  
Near Infrared ◽  
Rapid Analysis ◽  
Spectroscopic Measurement ◽  
Physiological Status ◽  
Clinical Use ◽  
Plasma Samples

A method based on near-infrared spectroscopy (NIRS) is presented, which provides a rapid analysis of lactate in plasma. In order to test the technique, NIRS analysis and enzymatic measurements were made on plasma samples taken from exercising humans. A correlation coefficient of 0.995 and a standard error of 0.51 mmol/L were found between the enzymatic and the NIR results. This standard error is within the range needed for real-time monitoring of lactate in plasma for exercising studies. In the future, this technique may provide a valuable tool to assess physiological status for research and clinical use.

scholarly journals THE IMPACT OF LIPID-CONTAINING PLAQUE COMPOSITION MEASURED BY NEAR-INFRARED SPECTROSCOPY ON CORONARY ARTERIAL REMODELING

2015 ◽  
Vol 65 (10) ◽  
pp. A1917
Author(s):  
Hideaki Ota ◽  
Marco Magalhaes Pereira ◽  
Smita Negi ◽  
Thibault Lhermusier ◽  
Ricardo Escarcega Alarcon ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Arterial Remodeling ◽  
Plaque Composition ◽  
The Impact

scholarly journals Detection of malaria in insectary-reared Anopheles gambiae using near-infrared spectroscopy

2019 ◽  
Author(s):  
Marta F. Maia ◽  
Melissa Kapulu ◽  
Michelle Muthui ◽  
Martin G. Wagah ◽  
Heather M. Ferguson ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Anopheles Gambiae ◽  
Near Infrared Spectroscopy ◽  
Large Scale ◽  
Near Infrared ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Human Malaria ◽  
The Impact

AbstractLarge-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-effective and high-throughput tools for mass-screening of vectors. This study demonstrates proof-of-concept that near-infrared spectroscopy (NIRS) is capable of rapidly identifying laboratory strains of human malaria infection in African mosquito vectors. By using partial least square regression models based on malaria-infected and uninfected Anopheles gambiae mosquitoes, we showed that NIRS can detect oocyst- and sporozoite-stage Plasmodium falciparum infections with 88% and 95% accuracy, respectively. Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS could revolutionize surveillance and elimination strategies for the most important human malaria parasite in its primary African vector species. Further research is needed to evaluate how the method performs in the field following adjustments in the training datasets to include data from wild-caught infected and uninfected mosquitoes.

scholarly journals Direct constraints on the impact of TP-AGB stars on the SED of galaxies from near-infrared spectroscopy

2011 ◽  
Vol 7 (S284) ◽  
pp. 63-65 ◽  
Author(s):  
Stefano Zibetti ◽  
Anna Gallazzi ◽  
Stéphane Charlot ◽  
Anna Pasquali ◽  
Daniele Pierini
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Spectral Region ◽  
Stellar Population ◽  
Near Infrared ◽  
Agb Stars ◽  
Population Synthesis ◽  
Stellar Population Synthesis ◽  
Evolutionary Phase ◽  
The Impact

AbstractWe present new spectro-photometric NIR observations of 16 post-starburst galaxies especially designed to test for the presence of strong carbon features of thermally pulsing AGB (TP-AGB) stars, as predicted by recent models of stellar population synthesis. Selection based on clear spectroscopic optical features indicating the strong predominance of stellar populations with ages between 0.5 and 1.5 Gyr and redshift around 0.2 allows us to probe the spectral region that is most affected by the carbon features of TP-AGB stars (unaccessible from the ground for z ~ 0 galaxies) in the evolutionary phase when their impact on the IR luminosity is maximum. Nevertheless, none of the observed galaxies display such features. Moreover the NIR fluxes relative to optical are consistent with those predicted by the original Bruzual & Charlot (2003) models, where the impact of TP-AGB stars is much lower than has been recently advocated.

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