Science method

Near Infrared Spectroscopy - Science method

Near infrared spectroscopy is a spectroscopic method that uses the near infrared region of the electromagnetic spectrum (from about 800 nm to 2500 nm).
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Hi.. I am doing NIR analysis for rapid quantification of major compound in essential oils.
I am using PLS Regression with 10-folds cross validation. However, the value of coefficient correlation (R2) of calibration set was slightly higher compared to prediction set. Does it make sense?
Here is the result of using 1st derivative SG as data pre-processing method
PLS MSEC: 8.1189, PLS R²C: 0.8498 PLS MSECV: 10.0940, PLS R²CV: 0.8132 PLS MSEP: 6.6743, PLS R²P: 0.8907
Thanks!
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Yes, it is possible for the values of an NIR calibration model to be lower than the prediction. This can happen due to various factors, including: * Model Overfitting: If the calibration model is overfitted to the training data, it may not generalize well to new, unseen data. This can lead to predictions that are higher than the actual values. * Measurement Errors: Inaccurate measurements during the calibration process can introduce bias into the model, leading to underestimation or overestimation of predictions. * Sample Heterogeneity: If the samples used for calibration are not representative of the population being studied, the model may not accurately predict the values of new samples. * Data Preprocessing: Incorrect or inappropriate data preprocessing techniques can also affect the accuracy of the calibration model. To address this issue: * Careful Model Development: Ensure that the calibration model is developed using appropriate techniques and that it is not overfitted to the training data. * Rigorous Data Quality Control: Implement strict quality control measures to minimize measurement errors and ensure data accuracy. * Representative Sampling: Use a representative sample of the population being studied to develop the calibration model. * Appropriate Data Preprocessing: Use appropriate data preprocessing techniques to remove noise and improve model performance. By addressing these factors, it is possible to develop more accurate NIR calibration models that provide reliable predictions.
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Hi folks.
I am looking for alternative ways to study water distribution and mobility in my food sample. Typically time-domain NMR is employed to identify the T2 relaxation time corresponding to free, bound and immobilised water but we dont have the instrument here in my area. I've found a promising (and validated) method using NIR spectroscopy, however it is run on FTIR and requires wavenumber up to 5500 cm-1 to capture the water band. Again, the FTIR I have access to only provide information until 4000 cm-1.
Is there any way I can obtain this information other than the said methods?
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Dear Nursyafiqah,
If you have access to a "normal" NMR spectrometer, which is usually available at an analytical facility of a university, you can perform similar measurements like using time domain NMR. You can measure T2 time also here (maybe even better using pseudo 2d compare with just fitting the direct FID). Using software like "Dynamcis Center" (or others) Free of charge you can analize the data. In addition you can measure DOSY like Alfred Ross suggested.
Many Greetings,
Kristof
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Welcom my dear
I need for help me in this project and this project include the most important signal for the supplementary motor area (SMA) and primary motor cortex (MI) will be energized during motor execution and imagery. The collected real dataset will be analyzed using the fNIRS-SPM: Statistical Parametric Mapping for functional Near-Infrared Spectroscopy toolbox.
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Hi,
To calculate dataset features for fNIRS focused on the SMA and MI areas, first preprocess the data to remove noise and artefacts, bearing in mind that experiment design, data quality, and research questions can influence these preprocessing and analysis steps. Segment the cleaned data to isolate motor execution and imagery tasks. Optionally apply filters for further refinement. Then, utilise the fNIRS-SPM toolbox for statistical analysis and feature extraction, such as mean, variance, and functional connectivity metrics. Proper probe placement, signal quality, and correct statistical thresholds are crucial for accurate results.
Hope this helps.
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halllo,
I am trying to calculate the signal -noise ratio.
i do not know how to proceed.
there are 256 different wavelength and 420 scans from NIR spectrocopy.
please for suggestions :)
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SNR of every single point of your scan is hard to calculate. It depends on electronic, source stability, detector noises, integration time etc. etc. SNR will also change with wavelength. Fortunately, with 420 scans you can calculate 420 standard deviations and then use it to calculate your SNR :)
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We have an opportunity to outfit a new lab for rapid and low-waste diagnostics of agricultural plant and soil samples, primarily for macro- and micro-nutrients (although if more detailed analyses are possible that is nice, but not a priority). I am wondering from those who have extensive experience in the usage of XRF and/or NIRS what are, in your opinion, the best models on the market and why?
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I asked a similar question on Twitter and the answer was Olympus (at least here in Australia)
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Hi,
I have been trying to search for answer what is the best way to attach NIRS device to tibialis anterior muscle to prevent excess moving and light interference ?
If anyone have some practical advices I am more than happy.
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I need more information on NIR spectroscopy
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Near-infrared (NIR) spectroscopy is concerned with absorption, emission, reflection, and diffuse-reflection of light in the region of 800–2500 nm (12,500–4000 cm− 1).
you can find more details about NIR spectroscopy here:
Kind Regards
Qamar Ul Islam
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Comparing PLSR, PCR, SVMR and MLR, which one is better for the correlation between linear data (MIR and NIR spectroscopies) and chemical data (pH, peroxide value ...)? There is(or are) other tools better than the four ones cited former ?
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The type of modeling algorithm to be used is specific to the type of data you have and depends on the linearity or not, but for linear modelings you can apply the PLSR that can better fit this case, but also why not trying some machine learning tools (ANN, random forest...) as some experiences have proved that they led to better models. Another point is that care should be taken to the data preprocessing step.
Good luck
Issam
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A: Use actual values from NIRS
B: Use a margin of safety
C: Use stochastic programming
D: Do nothing about it
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Please give the proper answer and how it is performed. Provide a short demo video if as soon as possible.
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Thank you sir....
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We are a small Human Factors department working mainly on automobile/pedestrian research and sometimes support surgery studies. We plan to purchase a NIRS as a tool for workload measurement. It would be great if the software is easy to use, as I would love to use it in student courses.
If you have a NIRS and are happy with it or hate it - I would love to hear from you!
Thanks!
Gerald
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Traditionally, the Karl Fischer titration has been used for determining the moisture content in UO2 powder samples, for example, as described by Hibbits, 1953 on Google [Attached]. A Metrohm webinar has described the use of NIR spectroscopy for determining the moisture content in pharmaceutical chemicals [ https://www.youtube.com/watch?v=HSKaLZwaJvw ]. First, the moisture content is determined by NIR spectroscopy. Then the same samples are used for determining moisture by Karl Fishcher titration. Then a graph is drawn correlating the two sets of values. Using this graph, only NIR spectroscopy is used for moisture estimation of future samples, dispensing with the Karl Fischer method. Is NIR spectroscopy recommended for UO2 powder as a substitute for Karl Fishcher method?
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I think that NIR can be considered to be a promising candidate to predict the water content of UO2 samples. However, as required with any analytical method, you will need the right amount of knowledge to make it work. There are many challenges to overcome in order to leverage the potential of a near-infrared based solution!
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Hello All,
Please, I want to know how to use Landsat 8 imagery to generate the soil texture map after correlating the outcomes of the laboratory analysis with the cell values at the desired wavelengths (VIS: 350-700 nm: Bands 1 to 4) and (NIRS: 701-2500 nm: Bands 5 to 7).
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You can use the Multi-criteria decision model
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We are looking for a spectrophotometer and fluorometer to record absorption and fluorescence within the NIR-II optical window (900 - 1800 nm). What are the best ones in terms of quality/price? Thank you.
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How about fiber optic spectroscopic solutions? They are pretty flexible in terms of the optical setup. (e.g. https://www.oceaninsight.com/products/spectrometers/near-infrared/ )
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Is Raman-Spectroscopy equaly limited in the detection dark/black materials as NIR-Spectroscopy?
Are there already Raman-Spectrometers with HSI (Hyperspectral Imaging) like possibilities available?
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Is Raman-Spectroscopy equaly limited in the detection dark/black materials as NIR-Spectroscopy?
Indeed, black samples are often problematic in Raman spectroscopy. Nevertheless we must always try because it is not systematic.
Are there already Raman-Spectrometers with HSI (Hyperspectral Imaging) like possibilities available?
As of this date, there is no hyperspectral imaging system. It's hard to believe that there will ever be one because Raman spectroscopy is really not efficient and we often have to make long acquisitions to get a sufficient signal-to-noise ratio.
Best regards,
Ludovic.
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To design a proper experiment given the fNIRS signal characteristics, should one follow the fMRI experimental design recommendations (both signals present the hemodynamic delay), or are there specific recommendations for fNIRS experimental design one should care about as well? (relevant references on this?)
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Hi, interesting question. Could you provide more information for the search of the mentioned articles (ciftni et al 2008 and kamran et al 2015 , kamran et al 2016 )?,
Thanks
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Hi i am a Medical Physics PhD student, im interested in Radiolysis and production of free radicals, i am very curious is to collect information is there any possibility to measure the free radicals, singlet oxygen in vivo and vitro. My idea is to measure the spectral changes.I would appreciate suggestions or possibilities if any.
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You can use some chemical probes such as APF (aminophenyl fluorescein) or SOSG (singlet oxygen sensor green). You measure probes' fluorescence before and at the end of the irradiation. Fluorescence enhancement will indicate ROS or signlet oxygen generation.
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Hello, everyone.
We have some questions about our fNIRS data. Here is the detail information on our data collection and processing.
1) This is a fast event-related design experiment.
2) There are six piuture, data of the left side piture are raw data without filter, the right side was process by NIRS_SPM with filter.
3) We show fnirs data (only oxy) from three different channel, the horizontal axis means time-serial of the round one of task, the lontidudial axis means oxy concentration.
My questions are as below:
1) Which CHANNEL of fnirs data is better (CH01 or CH11)? why?
2) Why the raw data of CH07 (LEFT picture) droped sharply in the middle of the task? Is this a bad signal?
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Michael M Plichta thank you very much~
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Why are concrete and red-brick buildings cyan in infrared false color (IRFC) images?
Most building materials are made of soil (e.g. red tile roofs or concrete), thus most urban areas have the spectral signature of a soil.
Nevertheless, in IRFC satellite images we usually see bright urban areas in Bright Cyan instead of Dark Brown/LightBrown to Orange or Whitish. why is that?
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Hi @Matteo Biondi
This is because the buildings exhibit shorter wavelength that corresponds to red colour indication
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Drinking water is heterogeneous and of variable quality. I would like to examine their mineral contents and other water quality parameters themselves. How can spectral changes in the visible and NIR light spectra be monitored? What measures will help me deal with the variability of the water solution rule?
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Dear Nativ,
Yes you can use spectroscopic methods to evaluate water quality. However, its depends with the method you going to follow and the concentrations in your samples. Refer APHA methods for more details and optimized your machine with calibrations.
Yohan
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Traditional and non-immersive computerised methods incorporate the employment of static and simple stimuli within a highly sterilized environment, while the ecologically valid tests which are currently in use do not adequately reflect the complexity of real-life situations. In contrast, immersive virtual reality (VR) enables the implementation of dynamic stimuli and interactions within a realistic environment, offers a high degree of control over the environment and the procedures involved. However, there is a scarcity of implementing immersive VR in conjunction with established neuroscientific tools such as neuroimaging tools (e.g., magnetoencephalography, electroencephalography, transcranial magnetic stimulation, and functional near-infrared spectroscopy) and physiological measurements (e.g., thermal camera, galvanic skin response, electromyography, and eye-tracking). I would like to request from researchers, who have already implemented any of the aforementioned neuroscientific tools in conjunction with immersive VR, to share their insights regarding their advantages and disadvantages of using these tools in immersive VR research paradigms.
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Confounding Factors
Head-mounted devices (HMDs) are implemented to achieve a highly immersive virtual reality (VR). However, the VR may induce adverse symptoms and effects (VRISE; cybersickness) such as nausea, disorientation, dizziness, instability, and fatigue. The presence of VRISE has modulated substantial decline in reaction times and overall cognitive performance, as well as increase body temperature and heart rates. Also, the presence of VRISE robustly increases cerebral blood flow and oxyhemoglobin concentration, the power of brain signals, and the connectivity between stimulus-response brain regions and nausea-processing brain regions. Thus, VRISE could be considered confounding variables, which significantly undermine the reliability of neuropsychological, physiological, and neuroimaging data. VRISE are frequently derivatives of VR hardware and/or software inadequacies, e.g., an HMD with a low refresh rate < 75Hz, or a low resolution < 960 x 1080 sub-pixels per eye; while a VR software should have an ergonomic navigation and interactions systems. So, do you have considered the confounding effect of VRISE? Do/did you intend to provide data pertinent to the intensity of VRISE in your population?
p.s.: the confounding effect of VRISE was studied in our recent technological review and meta-analysis of neuroscientific/psychological studies. https://www.frontiersin.org/articles/10.3389/fnhum.2019.00342/abstract
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I want to analyze the honey quality including adulteration by FT-NIR(Fourier transform near infrared )spectroscopy diffuse refelectance measurement mode .please i need information by any one of you who have experience on this area ?
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A quick search for "honey" "ftir" "adulteration" in Google Scholar returns over 1000 results, the first one is the following paper, dating from 2001:
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There is plenty of NIR spectrometers with up to 2.5u spectral range (upper limit is set by InGaAs detector arrays). There is also a variety of FTIR spectrometers that typically cover up to 3-20 um range and usually very expensive. But there are almost no spectrometers on the market in the SWIR range 2-5um. Is it because they are not so useful for spectroscopists? We are developing a family of cost efficient NIR/SWIR spectrometers with spectral range that can cover 1-2.5 um or 2-5 um depending on the detector used. The NIR 1-2.5um spectrometers are very popular and there are plenty of applications in this range. But we are wondering if there would be any applications and demand in the 2-5 um range?
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Thank you very much!
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I am performing a PLS regression analysis on NIR spectroscopy data to predict a continuous Y-variable using PLS toolbox. As the figures in PLS toolbox are not looking nice, I would like to make the scatterplots of the PLS model myself (scatterplot of Y measured vs. Y predicted, including a 1:1 fit line and the model line). I am wondering how I can calculate the 'model line' using the obtained scores and loadings. For clarity, the raw data were pre-processed before the actual PLS regression analysis. Did somebody already try to do this?
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I usually carry out my data analysis in The Unscrambler software from CAMO (I do PLS to predict rice constituents using NIR spectra) and I do my own scatter plot using the Reference and Predicted values from the PLS output. I do it using Microsoft Excel. I think, I am able to help you, but what do you meant with "model line"? could you upload an example?
Looking forward,
All the best
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Does anybody know a database on fluorescent properties of chemical compounds?
There are many papers describing flurescent properties of various compounds. Is there any database on fluorescent properties with a structure search function?
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fNIRS is an interesting tool to investigate neural mechanisms of movement control. Does fNIRS reveal sufficient spatial resolution to identify cortical areas associated to e.g. leg or arm function? I.e. is it possible to differentiate between cortical activities that control upper vs. lower extremity movements using fNIRS?
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Hi Deepak,
thank you for checking on this. I am not only interested in the attention resources that are associated with leg and arm movements, but rather in the motor areas that control movements of the upper and lower extremity. But your answer would probably apply to both (attention and motor) resources.
Thanks a lot and cheers,
Linard
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I have the data of total dissolved soilds of apple as references (y-variable).
I also have near-infared spectra data as predictors (x-variables).
I have the StatSoft Statistica software for the analysis.
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Different related software's can be used for building ANN predictive model using NIR spectra. My suggestion are Unscrambler and IBM modeler. Before ANN modeling, PCA should be done to reduce large spectra variables to PC1, PC2 .... . after calibrating ANN, you have predicted values by calibrated model and you have also reference values for each sample. Now use RPD index to realizing the goodness of your calibrated model.
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I am doing a study on classifying fruits on visible region taking spectra with Vis-NIR spectroscopy. I want to classify the fruit based on maturity in terms of skin color. I am trying to use SVMC, SIMCA and KNN with PLS toolbox. I went to the wiki site of the eigenvector, but the procedure described there is a bit blurry to me. It would be great if somebody could tell me the stepwise procedure on how to perform these on PLStoolbox using Matlab.
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For classification, you can perform the PCA (Principal Component Analysis)
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Near-infrared spectroscopy (NIRS) is a spectroscopic method that uses the near-infrared region of the electromagnetic spectrum (from about 700 nm to 2500 nm). Typical applications include pharmaceutical, medical diagnostics (including blood sugar and pulse oximetry), food and agrochemical.
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Sure
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Near-infrared Spectroscopy (NIRS)
For a clinician, it is important to understand the basic principles of NIRS, to know the limits of use and to interpret them correctly. NIRS is a technique in which the amount of absorption by which chromium molecules [oxyhemoglobin (O2Hb) and deoxyhemoglobin (HHb), cytochrome-c oxidase (CCO), myoglobin)] is measured as NIR light passes through the tissues. Chromophore can also absorb NIR light in tissues. There are molecules called. These molecules have specific absorption rates which vary according to the oxygen concentration in the tissue. The amount of light absorbed by the tissues is directly dependent on the chromophore concentration. At least two different wavelengths for comparison of chromophore concentration in NIRS measurements should be used. These two wavelengths are commonly used in measurements as O2Hb and HHb used in the measurements show the greatest difference in absorption at light of 700 to 850 nm wavelength. While two wavelengths are used in the first produced devices, the accuracy rate of the measurements is increased by using multiple wavelengths in the devices used today. The basis of the NIRS working principle is the Beer-Lambert law, an optical physics law. According to this law, the light is absorbed according to the material it passes through. Spectral resolution spectroscopy, frequency have developed techniques for dependent spectroscopy and time-dependent spectroscopy. Determining the chromophore concentration level in benign and malignant nodules in thyroid nodules has become simpler with these methods. I am hopeful that a non-invasive diagnostic method will be developed by the departments that support this hypothesis without being done in the future.
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i agree with Wang Fupeng
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I'm trying to get my hands on a glass panel with a high solar factor g (SHGC). As almost all panels are coated with this anti-NIR coating straight from the factory, I need to find a way to remove the coating either mechanically (without changing the surface texture) or preferably chemically.
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Sir, we use Zn powder with 2M HCl on the specified area to remove transparent conductive oxide coatings in glass slides . Hope this dissolve anti NIR coatings in Glass.
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There are many papers used ga-pls in near infrared spectroscopy
what are the advantages of using pls instead of other multivariate models?
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Hello Hasan ,
For answering why using PLS, please check out:
Indeed, PLS may be powered by many methods, depending on applicative needs and requirements. Follow:
Finally, linking PLS to CCA is of first-rate interest:
Regards
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Hello, I work with FOSS WinISI 2 (windows 7)for NIRS scans and considering an upgrade to WinISI 4. Does anyone who works with version 4 recommend it? how different it is from the old version?
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i using isi scan version 4 but winisi i still using old version since i just need to upload the spectra, i think winISI 4 got provide new features in terms of calibration, may be it depend on your need
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Hello, everyone,
Now I am considering nonlinearity detection of near-infrared data, that is, to confirm whether is it better to use nonlinear model instead of linear model for calibration. I found that Durbin-Waston test had been introduced to address the problem and I am confused of the following questions?
1. Is D-W test designed for univariate regression? If so, what should I pay attention if I used it to multivariate regression?
2. If so, is the result of D-W test related to the number of independent variables ( explanatory variables) ?
3.If I want to use D-W test with the principle variables (PCA preprocessed) of NIR matrix, which PC or PCs should be selected?
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D-W test is a test of residual correlation. It is not only for univariate but also for multivariate regression and is not dependent on the number of variables involved. If the D-W statistic d = 2 the residuals are uncorrelated which is an indication of model adequacy. If d<2 the residuals are positively correlated. If d>2 they are negatively correlated. If you are using principal components ( PCs) the first PC which accounts for most of the variance may be used.
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Hello everyone
I have developed a compact spectrometer (photo attached) and working towards developing it into a milk analyzer. I will be using 600-1100nm, based on literature, where researchers have used this range to quantify the fat% in milk. 
Before beginning, I would like to make sure how the calibration could be transferred from one device to another. There are some products available already in the market like Foss Milkoscan, but they use mid-infrared wavelength range, making it less challenging to transfer calibration. Others like Fatscan, haven't yet made it to the market.
Is it impossible? Can someone please elucidate the actual challenge in scale up while transferring calibration? Any leads would be appreciated.
Thanks.
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yes, it is possible by using "calibration transfer".
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Near Infrared Spectroscopy
High germinative capability
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Thank you..
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we are coming up with an innovation that uses a non- invasive way to determine the triglyceride levels in the body. So far, we have decided to use spectroscopy ( via infrared). We are still clueless as to how triglyceride is measured.
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What is the most suitable software tool for data processing and chemometrics applied to NIR/IR, Raman, X-Ray hyperspectral imaging? Please could you share your experience.
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As  Edgar says MATLAB, Python and R are all softwares where programmes are available for spectral analysis. The research group who are world leaders in spectral processing including NIR and Raman are based in Umea university and have pretty much developed the field of Chemometrics. They use a commercial software package (SIMCA) as well as R/Python but their software algorithms are often published. If you take a look at the webpage of Johan Trygg who is the head of the department (http://www.chemistry.umu.se/english/research/group-leaders/johan-trygg) you will find lots of articles on how to process and model these types of spectra. They are an extremely friendly group and welcome interactions with scientists.
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I could only find the wavelength for Doxycycline Hyclate (273nm). Does this apply for monohydrate also? Because I'm getting very high values (around 3.2 for just the clear plate) which I think deviates from Beer-Lambert law. Any ideas on this?
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Hi, I am working on muscle oxygen consumption and I would like to assess this parameter with near-infrared spectroscopy. I recently came across on the Binzoni and al.'s publication (in attachement) which provide a new method to measure mVO2 during a dynamic exercice. I would like to apply this approach with the Portamon device (Artinis) but I don't know how to apply the equations described in the publication with the collected data by Portamon (Text file in attachement)
Thanks
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I have no experiance with that
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Any other information anyone can offer about NIRS systems would be much appreciated.
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Hi Peter,
There are several NIRS systems commercially available that can measure real time oxygen saturation. Companies use different names for oxygen saturation, for example Tissue Saturation Index (TSI), Tissue Oxygenation Index (TOI), regional oxygen saturation (rSO2) or others. A google search on those terms will yield multiple commercially available devices. 
If you want to measure the absolute lactate levels you will need a blood analysis device. There are scientific articles (e.g. Guodong Xu et al. titled "Relationship between muscle oxygenation by NIRS and blood lactate") wherein NIRS is used to estimate the lactate threshold. 
If you have any questions about our Artinis devices or want further information I would suggest you to contact askforsales@artinis.com.
Regards,
Mathijs Bronkhorst
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I am working on noninvasive blood glucose monitoring method based on four near infrared spectrums and double artificial neural network analysis.We choose four near infrared wavelengths, 820 nm, 875 nm, 945 nm, 1050 nm, as transmission spectrums, and capture four fingers transmission PPG signals simultaneously.
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Yes you need cooperation with hospital or any doctor who interested diabet to take data actually labeled data
because data is taken by  permission of ethics committee form computer center of hospital 
but they must be labeled by doctor/doctors
see u
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Can we use sensors with wavelength range from 600nm to 900 nm in NIR spectrometers to analyze soil moisture?  They are so cheap comparing to those with range beyond 1000nm.
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Dear researcher,
NIR are often used as "discriminatory" band for differentiate water-non water bodies in remotely sensed imagery (satellite). I am sure the NIR band in Landsat 8 (851-879nm) has been used for wide areas soil moisture estimation.
However, spectrometer analysis of soil samples using NIR "should" use wavelenghts beyond the range of your low-cost spectrometer. Please find attached a document about VIS and NIR spectroscopy in soil science. The author states:
"Bands near 1900 nm has been found to be better for quantitative estimation of soil moisture content than bands near 1400 nm (Bowers and Hanks, 1965; Dalal and Henry, 1986)"
I hope this helped a bit,
Nic
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Dear all,
Why NIR fluorescent probes are widely used for in vivo imaging ?
Visible range under 650nm is impossible for in vivo imaging ?
I'm really wonder that...
Thank you.
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It is not only the scattering (but it is the most important part), but also the absorbtion of blood that makes NIR more feasible for in vivo Imaging. On the other side you will get  absorption of water, if you are using longer wavelength above 1µm.
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Hi Research Gate NIRS community,
I have a simple question. Why do you choose to report oxy or deoxy when you report for a paper/poster? 
I have heard both sides of the story and this has been discussed quite heavily recently in my lab. I am curious as to why some people choose to pick one or the other outside of my little world, i.e. my lab. Having done NIRS analysis for awhile, I find it funny sometimes how different my story could be if I reported just oxy or just deoxy because they can be very different stories sometimes. While I understand it is good practice to report both, I find it quite common to pick one or the other.
I look forward to your responses!
Andrew 
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Dear Sir
Andrew Benjamin Gundra,
I am working on fNIR for almost 2 years. Once upon a time I also seek this question. As far I learnt from my research and the other literature based on fNIR, everyone uses oxy, de-oxy, or total oxygenation change or both oxy and deoxy data. But in all case, they used the data that gave them significant result or significant difference. By ANOVA or U test you may not get any significant differences in case of oxy data, then you must try for deoxy or total change in oxygenation or deoxygenation. Some times both results are combined to make the information meaningful. I think this is just to convince and make the research meaningful.
If I become wrong in my opinion, I beg your pardon in advance.
Thanks
Md. Asadur Rahman
BME, KUET, Khulna, Bangladesh.
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1) Suggest a method for calculation of Critical Micelle concentration (CMC) value from peak wavelength obtained from Absorption v/s wavelength plot generated using Near Infrared Spectroscopy
2) For measuring surfactant under NIR Spectroscopy. I am considering wavelength range of 1400-2200 nm based on previous work. Please comment
3) Please have a look at the plot for better understanding of question
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 Important to choose the right range of wavelength for  calculation.
Don"t you satisfied by results? It is  good.
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It will be great for sharing any experience in conducting this line of research
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Dear Shu-Shih,
we have a lot of experience in this domain, please see our webpage http://www.artinis.com/nirs-eeg-package/ and for example the listed papers. If you specify your goal and current status of the research, I am sure that we (and others) can also be more specific on this matter.
In general, however, the combination of NIRS with any other modality is really great, as the optical measurements are not influenced by the other measures and vice versa. Thus, this way you can for example do EEG/NIRS measurements without any artifacts in the NIRS or in the EEG signal. This is in great contrast to, for example, EEG/fMRI measurements where the magnetic gradient is hugely distorting the EEG signal. Combining NIRS with brain stimulation techniques such as tACS or tDCS is also doable without any issues.
There is a recent paper on combined EEG/fMRI/fNIRS using our system, maybe that is interesting for you as well:
The predecessor of this paper can be found here:
For fNIRS and tDCS see e.g. here:
If you have more specific questions, feel free to contact me.
Best,
Jörn
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I want to combine fNIRS and eye tracking to study autism, but since they have a different sample rates, and eye tracking is much more faster, so how to synchronise them?
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Our software package, EventIDE (www.okazolab.com) can alone handle all functions that you need. That would include stimulus presentation, eye-tracking recording (with any eye-tracker mode) and synchronization with fNIRS (up to millisecond precision).  In addition, you can monitor and process eye-tracking data and brain signals in real-time, for example, allowing stimulus adjustment based on instant brain-eye coherence, as Adam suggested.
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NIRS to detect sleep patterns.
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Thanks!
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I am doing a project where I need to create a portable device that can detect just whether pesticides are present or not in food. Since there are smart phone attachable portable spectrophotometers, I was wondering if I could exploit this to test for pesticide residues
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Issues to overcome.
1) Sensitivity. The quantity of pesticide on surface will be minute. You may be looking at detecting parts per billion or parts per trillion on a few square centimeters of surface. I mix a pesticide at 1 gram ai per liter. This is 1000 ppm. I spray the solution to run-off. The apple is round, and only a surface film remains. The film is 100 microns thick and uniform (again, optimistic and unrealistic). A square centimeter will contain 1010 cubic micrometers or 0.01 ml. There are 100 ml/liter so a ml has 0.001 grams, and there were 0.01 ml, so you are trying to detect 0.00001 grams per square centimeter. This example is a bit generous. Admire Pro (550 g ai/liter) applied to blueberries at 1.4oz/acre in 20 gal/acre is the application of 22.77 g ai/acre. If the acre is perfectly flat, then this is equivalent to 0.5627 micrograms/cm2. Vegetation of any type will make the surface area greater and further dilute the sample. The problem is further complicated in that the pesticide is never uniformly distributed over all surface areas. Inevitably some parts are not sprayed, while others get more than their fair share.  
2) Some pesticides are translocated and would appear internally and not on the surface.
3) Other chemicals on the surface might include dust, bacteria/fungi, and a mixture of many compounds produced by the plant. All of this is potential interference.
4) You might not know the pesticide. Your job just got infinitely harder if the pesticide could be anything from DDT, chlordane, imidacloprid, cypermethrin, endrin, neem, spinosad, or strobilurin (yes, the last is a fungicide mixed in with a bunch of insecticides).
5) Is there a post-harvest treatment that is applied? Do apples and cucumbers get waxed to improve storage? Such treatments will impair your ability to detect the pesticide.
6) Degradation. This might be an issue depending on your research question: scientific, consumer safety, regulatory issues. In some cases the degradation products from the pesticide are more toxic than the original pesticide.
7) If the issues are consumer safety (all consumers have this device) or regulatory compliance, then I might be concerned with the skill these people have in using the device and maintaining its calibration. Scientific equipment that is taken into the field often has to be calibrated more often to insure accuracy.
While it would be nice to have a simple, fast, accurate, and inexpensive method for detecting pesticides on produce, I just don't see that this approach has a great chance for success.
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A colleague and I have been trying to decide which NIRS system to purchase and hope to get advice from those with experience. We have no experience with NIRS and have lots of ideas for how it may be used in our psychology/behavioral neuroscience department (we are not purchasing it for one particular research goal). We’d like to be able to record from any area of cortex (not just prefrontal) and we’d like something flexible and modular so that we can scale up when we get more funds. We think we’ll have 75 - 100k to work with for now. Do you have suggestions based on your own experiences with particular vendors and systems? Thank you.
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If you have the ability to spend that amount of money, have a look at the Antaris FT-IR instrument from Thermo. Why? Because it is very versatile, and from you question, I think that is exactly what you need! You can measure powders, liquids, solids, even tablets in transmission. And the instrument provides you with some good quality spectra. 
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Hello, maybe someone know where I could find MNI coordinates for fNIR400 or fNIR100 probe? Or maybe data converter for NIRS-SPM or Homer? Thank you a lot!
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Dear Mam,
As far I know, the series of NIRS-SPM give their specification to convert the fNIR data to their format. I think you should read the manual carefully. If the problem arise again, I can try to help you.
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I am working on a milk analyzer device. We have made a flowcell (pipe) made up of aluminum, in which milk will run in one direction, and light will be passed through it in perpendicular direction (we have place glass slides in pipe to make a transparent container for passing light).
Problem is whenever we try to take readings at some intervals, the fat residue from previous test interferes with the next. Hence, we are considering using a super-hydrophobic coating (Any other suggestion is welcome!).
Does anyone has data on the absorption spectrum of the coating in the range 400-1100nm?
Please share experience in using such kind of coating on metal and transparent acrylic. 
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Thanks for you detailed answer Sir.
I talked to NeverWet, and even they said the same- that it leaves a white hazy finish. They didn't comment on the infrared absorption data. 
I just want to keep the milk residues from sticking to the tube and interfering with the next reading. If only hydrohobic+oleophobic coating would work, it would be pretty amazing. I am working on a field-used device, hence it needs to be durable (>1year) or almost permanent.
Any suggestion? 
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I am computing O2 saturation levels as the rate between HbO and HbT (HbO/HbT) recorded through fNIRS. While most of the outputs range between 0-1, I have some negatives values and also some values > 1. Is it possible? How can it be interpretated? 
Thanks in advance
G.
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You cannot compute O2 saturation that way. From what I gathered, you are using the modified Lambert-Beer law to compute 'relative' changes in concentrations from the changes in light intensity. As the previous sentence implies, and Michael Nordine already correctly pointed out, These changes are always *relative* with respect to some moment in time. This means, you can add an arbitrary number to it, and still get the a valid 'relative' change (e.g. an increase of 1 a.u. in oxygenated hemoglobin, no matter if your values are 2 and 1, or 102 and 101). Computing the ratio between HbO and HbT (which is HbO+HbR) is dependent on the absolute values (because 1/2 is different than having added 100 to both, i.e. 101/102). This 'arbitrariness' is an inherit characteristic of the modified Lambert-Beer law and thus cannot be circumvented. Hence, there is no way to get the absolute oxygen saturation for these measurements (assuming this is what you did). For example, you can also get different HbX values if you pump up your laser power, resulting in more light reaching the receiver. In absolute terms, however, there should have been no change.
In order to measure absolute oxygenation, you need a different technique. We use the tissue saturation index (TSI), which for example our PortaLite devices can measure, but also our versatile, multichannel Oxymon devices are able to do. See e.g.
Feel free to contact me/us for more information.
Btw, I added the 'arbitrary value' example to answer your last question: No, HbO is not always smaller than HbT, because you can also subtract an arbitrary large offset from HbR, making the 'relative' change in HbR still valid, but leading to HbT being smaller than HbO. Most devices and/or toolboxes actually do baseline with respect to the first recorded sample.
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With the technology of 3d scanning, I was wondering if anyone in the NIRS or EEG research community has utilized it for acquiring 3d digitizer data aside from the Polhemus. My lab uses the Polhemus, but it is often prone to funny errors and data that doesn't look great when we use it for localizing channels. Was hoping to find an easier and faster way and if that is even out there.
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Hi Andrew,
At the Donders we have considered this for EEG rather than fNIRS. As alternative to the Polhemus, we tried a Fuel3D and as of very recently got ourselves a structure.io scanner. We did not like the Fuel3D for various reasons, but the structure.io appears to work quite well. We just added support for its data format in FieldTrip (see http://www.fieldtriptoolbox.org, it is in the ft_read_headshape function) and will continue working on this to get a good (EEG/MRI/headmodel) coregistration pipeline documented. I hope that our efforts will also be helpful for fNIRS, for which FieldTrip is also useful.  If you want to chime in in detail, please do so at http://bit.ly/1SPRkto
best regards,
Robert
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Now , I study about peat forest fire. From literature, I got some information that Near-infrared spectroscopy (NIRS), a kind of remote sensing product is ideally suited to gathering detailed data on carbon inventories and dynamics in peat-lands, as well as monitoring moisture levels that are critical in evaluating the risk of fire. My questions are, How to get Near-Infrared Spectroscopy (NIRS) data? Where?
Thank you
Sigit
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Hi Sigit,
Near Infrared spectroscopic data for a particular object can be collected either using a Spectroradiometer instrument on the ground (In situ) or it may be possible to extract through high resolution hyperspectral remote sensing data sets. Multispectral datasets may not be helpful in providing details. Another alternative is to check the JPL ASTER Spectral library for various minerals/vegetation spectra that you are interested in. They have a collection of more than 2000+ spectra of natural and human-made materials in the visible to thermal infrared wavelength region (0.4 µm to 25 µm).
Can you also share the details of the literature which you are referring to?
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Dear NIRS Community, 
I've just started working with NIR spectroscopy, I'm actually getting to know this technique and the OMNIC™ software which I'm using. 
I've been recommended to apply automatic baseline correction to pre-process spectra, although I'm wondering is it a reliable tool? Or should I use other methods to eliminate baseline shift variations as a part of chemometric processing of spectras? 
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Or at least I'm supposed to ;)
Thanks, Aurelio!
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As many of you know, reducing head motion is vital for analysis and integrity of data. I was curious to see if anyone else in the NIRS field has used an accelerometer for head motion as a covariate in analysis. Recently, our lab published on using smart phones. But I wanted to know if others used commercially available accelerometers do to this as well. Ease of extracting raw x,y,z data is particularly what I am interested in knowing before I dive head first into this search would be very valuable and appreciated. As usual, it's nice to hear directly from others than solely relying on the literature.
Thanks RG community!
Andrew 
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If anyone anyone was wondering, we just went with a super simple accelerometer with a raspberry pi/arduino setup. Works well and very informing, especially if you plan on doing things in the "real world." 
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I'm using the NIR-spectrometer model PT-IM100 from Pharma Test. The glass vial will be filled with the solid samples for measuring by NIRS. To perform a measurement with paste or liquid samples, the Aluminum stamp should be put in the glas vial.Why can't the liquid sample be measured without using the metal stamp (like the solid samples) ?
Thank you
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Dear Dr. Kuptsov,
Thank you very much for your clear and helpful explanation. As far as I've understood the Instrument measures the liquid samples by transmittance-reflectance mode. 
After measuring a sample, the plot of reflectance against wavelengths will be shown but it is also possible to change the parameters in the Software in order to get the plot of absorbance or transmittance against the wavelengths. In other words, I can get different plots ( different y-axis) according to adjusted parameters in software. When I have a Plot of for example absorbance against wavelengths, is the measuring mode  still reflectance ?
Regards
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How can I distinguish between the first stretching overtone N-H and O-H bands in NIR region as both of them show the adsorption in 1400–1500 nm?
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I understand that your aim is in analytic chemistry, for molecules or conglomerate of crystals of high molecular weight ?
So no hope with this mean of investigation. You must turn elsewhere to have the missing informations.
I suggest you to correct your "adsorption" into "absorption".
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hello community!
I've a handheld spectral analyzer (microPHAZIRNIR) and I need measure a lot samples of honey but these are crystallized. I read many articles, some propose;
- heat the sample
- liquefy the sample 
- measured immediately after harvest
But, there aren't consensus
Anybody know any protocol... 
Thanks in advance
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Dear Jorge,
I hope that this information will be helpful.
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As well as Calcium and Phosphorus? How can I get the metabolizable energy in NIR.
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Without prejudice to the company and its analysis, P determination by NIR is not easy.    To date, we are not certain of our calibrations and hence the results of NIR determinations of P.  
You may wish to contact Prof G. Batten, Editor in Chief, Journal of Near Infrared Spectroscopy.   He is a very helpful person.
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I would like compare two ECM using a Near Infrared spectroscopy, but I want use a non-treated ECM as a control. How can I compare? Which band I can use as reference?
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Hi Ana,
Thank you very much. The treatment consist in decellularization witu SDS. My focus is find collagen, elastin and laminin conservation after decellularization process. Do you have any experience with ECM proteins bands?
Kind regards 
Gabriel
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I'm doing pre/post measurements in the upper limbs during controlled exposure of human subjects.   After that, I'd really like to take the device and run around the hospital with it (assuming ethics approval of course).  I don't think I need a very sensitive device, just something durable and reliable.  
Two questions: 
  • How do I assess the literature comparing NIRS devices? 
  • How much can I expect to spend? 
Does anyone have any recommendations? I liked the look of this device 
-Van Haren, R. M., Ryan, M. L., Thorson, C. M., Namias, N., Livingstone, A. S., & Proctor, K. G. (2013). Bilateral near-infrared spectroscopy for detecting traumatic vascular injury. journal of surgical research, 184(1), 526-532. link
Or the Artinis Portamon but that seems more like a Lexus :)
Thanks!
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The kind of measurement that you want to do is one of the easier ones to perform by near infrared spectroscopy because of the intensity of the signals involved. Still, multivariate calibration would be helpful in achieving the best accuracy and precision. A very simple instrument is capable of measuring tissue oxygenation and you won't need to spend much money unless you want imaging capability.
A number of characteristics can be used to define the utility of every analytical method or instrument; among these characteristics are the dynamic range, the typical signal-to-noise ratio, the sensitivity, and the selectivity associated with an instrument or technique. The hypothetical "ideal analytical method" can be described using these characteristics as well as others of a practical nature. The performance of a real analytical method such as NIR spectroscopy can be compared to the characteristics of the ideal method to establish the relative power of the real method in each characteristic area. An analyst can then weight each characteristic area according to his or her needs and capabilities to determine the best method to employ in a given analysis.
A convenient breakdown of the characteristics useful in describing an analytical method includes:
1. Wide dynamic range. The ability to determine concentrations from 10^-18 to 10^2 M would be a valuable asset on the resume of any method. Low detection limits and high sensitivity are important, but ideally a method should be able to count single atoms or molecules of a substance as well as determine concentrations of the substance ranging up to 100%. Analyses would be greatly simplified if every analytical signal were linear over this entire range.
2. Great Flexibility. Virtually every conceivable analyte and property could be determined using the ideal analytical instrument. Furthermore, these analytes and properties could be determined simultaneously and in any combination from the same sample of a substance. Any sort of sample, solid, liquid, or gas, could be directly analyzed with the instrument. The ideal analytical instrument would be the only instrument in every laboratory.
3. Durability. The ideal instrument is simple, rugged, and easy to maintain. Anyone can operate or repair it with little or no training. The results are reproducible and validated over time, different operators, different equipment instruments, and different chemical lots. The device could act as a virtual "black box" that always produces the correct result regardless of the skill of the operator.
4. Accuracy and Precision. Measurements made with the technique would be free of systematic bias and highly reproducible (low relative standard deviation, or RSD).
5. Freedom from Interferences. The highest selectivity means that no characteristic of the sample or the environment will interfere with the measurement of any analyte or sample property. Furthermore, as an instrument approaches the "ideal analytical black box" it will need more and more "false-sample" detection capability; that is, the instrument will need to be able to recognize that it is examining a sample unlike any it has ever examined before, and will need to be able to respond appropriately. This response could take the form of a request for operator assistance, more samples of the same type, a "second opinion" analysis by another technique, or a library search for the best step to take.
6. Noninvasiveness and Nondestructiveness. The ideal method and instrument do not disturb the sample under analysis. Little or no sample preparation is required to use the technique. Very small sample sizes can be employed. The sample can be used for its originally intended purpose following the analysis, or it can be examined using another analytical technique.
7. Low cost. The ideal instrument and method are inexpensive in terms of the equipment, supplies, and personnel required to implement the technique.
8. Rapid. The ideal method is a fast one, resulting in increased sample throughput and cost savings.
Do a little Requirements Analysis on your proposed application and then see how a few instruments measure up on these ideal characteristics.
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How to measure blood glucose level of a human using NIR? I there any relationship between glucose level and pressure of blood?
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Dear Prabodhi, some times ago you asked this question on non-invasive glucose measurement. But from your side, there were no further answers, questions or comments. Is this project still running? It would be interesting to know whether and how the project is running. Kind regards.
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I want to do measurement using two different NIR instrument and FT-IR for a same sample (oil). What i've been observe when a sample is used for measurement, sometimes it got a bit hotter. I've read on sample temperature that a few degrees difference can change the spectral data.If the same sample is used for three different measurement, does this sample deteriorate? I am please to hear opinions on this matter. Thanks.
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Thank you mr jayanta for your opinion. At this stage I try to do data clustering using SIMCA.
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I want to set up Cluster Calibration by NIR  (qualitative calibration) for one Chemical that includes so many classes. Two Classes do not appear well separated from each other. In spite of that the Calibration's Protocol was satisfactory.
I tried to do Offline prediction to test the calibration with spectra that I didn't used in my Calibration. All spectra were identified correctly but the "Status" was "Not Ok". I guess, it could be because of these two classes that are not well separated.
According to the Manual the message "NOT OK" appears, when the actual residual is bigger than allowed residual or when the spectrum is not within the cluster limits.
Thank you so much in advance
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To magnify differences between very similar spectra, first calculate the derivatives. Try first derivative and if still not separated try second derivative. the Savitsky-Golay polynomials are a good way of calculating derivatives. Then use the derivative spectra for cluster analysis
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Hi!
How many samples are necessary for make a good calibration of NIRS DS2500 F for Pennisetum clandestinum and supplements of ration for dairy cow? It is the first time to use NIRS.
Thanks!
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I agree that 100 samples can be considered a good start, but if you are using this forage in grazing conditions or with different harvest times, this number of samples may not be enough to ensure a good coefficient of determination for your equations. 
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We have chaged our poulty feed to wheat based product from corn based one.
Fat content also increased by around 2%. Now NIR results are not accurate for Fat, fibre and sometimes moisture. But protein results are correct. Can anybody explain this situation. 
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Dear Prabhani Nisansala
It is generally agreed that NIRS equations should be specific for the feedstuff or forage of interest. Thus, that will be the explanation for the situation you are describing, as you have replaced one big component of the diet (corn) for another (wheat).
This change in the ability of the NIRS to predict the nutrient composition of the new, wheat-based diet can specifically reside in two areas:
1. Particle size of the feed: Wheat products are very fine compared to corn products, that can have a more coarse particle distribution. This will directly affect the ability of the NIRS to predict accurately, as any change in particle size will affect the processes of light reflectance, for example, by changes in the percentage of diffraction. 
2. Chemical differences between the feedstuffs: This is more related to fatty acid composition in the case of fats or monosaccharide content in the case of fiber.
What to do?
1. If the change of corn for wheat is permanent, you might want to generate a new prediction equation for the feed.
2. A first step is to check the effect of particle size of your sample. Make sure you grind your samples uniformly
3. Generally, if an adequate range of nutrient contents is available, you can generate an initial new NIRS equation with some 100 samples,plus let´s say 20 more for cross validation. Other people have used as little as 20 samples to generate a new equation, but that will depend on the variability of the nutrients you want to predict.
4. The validity of this equation needs to be tested and the equation can always be improved, if you have the proper software (i.e. WINISI in the case of FOSS NIRS).
Hope you find an early solution to your problem. Kind regards, 
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Hi all,
In a first experiment we have been recording nirs data with a sampling frequency of 10 Hz. To correct from movement artefacts and so on we have applied the typical band pass filter [0-3]. In a new experiment, we ve doubled the sampling frequency (20 Hz) so we are going to work with a band pass filter [0-10]. Someone who has faced the same situation has a suggestion?
Thanks in advance =)
Guillermo
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It depends on the frequency of the signal output, which hasn't been mentioned. The centre frequency of the bandpass filter should be the same as the frequency of the signal. The sampling rate should be at least double the frequency of the signal. However, as I have not seen your experiment, your mileage may vary.
The link will explain sampling rate and why it needs to be 2.7 times greater than the frequncy of the signal. https://en.m.wikipedia.org/wiki/Sampling_(signal_processing)
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Hello everyone,
All is setup, but when I start the mesaurement it looks like this: http://tinypic.com/r/8wmluu/8 . I biased the graphs with the button in the OxySoft sotware, but there is still nothing happening.
Details from exported Excel file:
Optode template: PortaMon TSI QCF
Optode distance: 35.00
DPF: 5.94
Receivers: 1
Lasers: 6
ADC: 8
Laser wavelengths:
Laser 1 844 nm
Laser 2 755 nm
Laser 3 844 nm
Laser 4 755 nm
Laser 5 844 nm
Laser 6 755 nm
Anyone any idea? I am missing something or is something wrong with the DAQ setup?
Kind regards,
Marcin
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Yes, I am more than sure. After I had contact with support they told me that the light probes are damaged and we have to send them back. Still, thank you!
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We'd like to use the NIRS at line, but with 4 seconds for each mesure we don't have time to mesure all the products. We already tried to reduce the sample count average, but it didn't change a lot
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As Misra an Daniel had written, it depends about the phenomenon you're measuring itself, and the balance between resolution and precision you desire. You could use only certain wavelengths that you are of your interest, or simply reduce the number of samples for each measurement, but again, there is a balance between resolution and precision that fulfills your requirements.
Regards
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thanks in advance
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There are many factors on which non invasive blood glucose depends such as thickness of measurement site, skin color and many more. I would suggest you to use  differential measurement  to  minimize the effect of these factors. 
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Has anyone any experience/advice for measuring central/distal hemoglobin via NIRS (NIRO-200, Hamamatsu Photonics) during water immersion? Will the electrodes function underwater? Will immersion destroy the electrodes? Before I test this out, and potentially make a very expensive mistake, just wondering if anyone has tried this before.
Thanks
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If you just use fibre optics for source and detector should work
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My lab is looking into integrating the two systems and was curious to see if anyone had experience with combining the two methods? It is definitely present in the literature but I wanted to hear from people directly on what systems worked well together. Ideally, we'd want two portable systems that could potentially be wireless and not sensitive to some movement, since the project is geared towards driving and in a driving simulator. Also, I am trying to use eye tracking with it as well and leaning towards Tobii. If anyone has experiencing coupling eye tracking with NIRS or EEG that'd be helpful as well. Hope to hear from some of you.
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Hi Andrew, we developed custom sensors and also used biopac fnir devices sensors with Neuroscan EEG systems in our studies. Also, for eye tracking used SMI systems' goggle based version. Hope these help.
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Could anybody help me with some references or books on the pre-processing methods for spectroscopy, such like MSC (Multiplicative Scatter Correction)?
Thank you!
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HI, instead of MSC corection I often use more simple Standard Normal Variation (SNV) correction, which center each data point (i.e. substract mean value from individual value) and divide them by standard deviation of all spectral points. So this spectrum is centred and normalized to SD=1. SNV is used for correction  of scattering effect . It therefore allows normalise the spectrum originating from samples with different shift of baseline caused by different optical path of radiation in the sample (for diffusive reflectance NIR), which arises for example due to different particle sizes or different layer thickness measured. 
some articles:
Barnes, R. J., Dhanoa, M. S., Lister, S. J.: Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra, Applied Spectroscopy, 1989; 43, s.
772-777
Barnes, R. J., Dhanoa , M. S., Lister, S. J.: Correction of the description of Standard
Normal Variate (SNV) and De-Trend transformations in Practical Spectroscopy with
Applications in Food and Beverage Analysis, Journal of Near Infrared Spectroscopy, 1993; 1
s.185-186
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I am using MODIS surface reflectance product (250m spatial resolution, 8 day composite) which comprises two bands: one is visible band and another is NIR Band. Is it appropriate to use NIR band for identification of flooded water as the surface reflectance of water is low in this band. Can anybody say approximate range of reflectance value for flood water.
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