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InfraLum FT - 10 NEAR-IR FT SPECTROMETER Near Infrared Analyzer CERTIFICATION.

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Presentation on theme: "InfraLum FT - 10 NEAR-IR FT SPECTROMETER Near Infrared Analyzer CERTIFICATION."— Presentation transcript:

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2 InfraLum FT - 10 NEAR-IR FT SPECTROMETER Near Infrared Analyzer CERTIFICATION

3 DEVICE LAYOUT Light Source Interferometer Optical Unit Sample Compartment Detector Elrctronic Processing system

4 ADVANTAGES  Simultaneous determination of several components in a couple of minutes  No consumption of reagents  Simple in use  No sample preparation  Non-destructive analysis  Development. transfer, and modification of calibration models

5 CALIBRATION Input the reference data Measure the reference spectra Take a Sample Fill a Cell Place the Cell Define a project Analyzer settings Calculate the calibration Define the analysis method Test the calibration  Training data set is collected, and the parameters of interest are measured using reference methods  Near infrared spectra of the samples from the training data set are recorded  Using the spectral responses of the samples and the reference data, calibration models are built suing chemometic algorithms  The parameters of interest of unknown samples are determined using the spectral data of the sample against the calibration model

6 ROUTINE MEASUREMENT Take a Sample Fill a Cell Place the Cell Measure Complete a Report Take a Sample

7 ROUTINE MEASUREMENT Take a Sample Fill a Cell Place the Cell Measure Complete a Report Fill a Cell

8 ROUTINE MEASUREMENT Take a Sample Fill a Cell Place the Cell Measure Complete a Report Place the Cell

9 ROUTINE MEASUREMENT Take a Sample Fill a Cell Place the Cell Measure Complete a Report Measure

10 ROUTINE MEASUREMENT Take a Sample Fill a Cell Place the Cell Measure Complete a Report

11 MAIN APPLICATIONS  Whole grain analysis (wheat)  Mixed feed analysis (different types)  Whole grain analysis (barley)

12 MAIN APPLICATIONS Agriculture and food industry  fast determinationof quality control parameters of agricultural products  Quality control of raw materials, finished products, and waste  Monitoring of technological processes Veterinary monitoring  control of composition and quality of feed and fodder Fertilizers  determination of composition of raw materials Scientific research  control of hardness of cellulose and whiteness and quality of paper in technological processes Pulp and paper industry  determination of composition of raw materials Metallurgy

13 ANALYSIS EXAMPLE The NIR spectrum of a fish flour sample

14 PARAMETER SamplewheatryeCornSoy beans and flour grainflourgrainflour Protein Moisture Fat Gluten Ashes Glassiness Whiteness Sort Size Sugar Starch

15 PARAMETER SamleMixed FodderWheat, barley, oats, oilcake, meat-meal Fish flour Raw protein Moisture Raw fat Metabolic energy Raw ash Acidity Phosphorus Calcium Fiber Protein Ash Lipides

16 PARAMETER SampleBrewing barleyDry milkCurd Protein Moisture Acidity Extract content Protein Ash Fat

17 HARDWEAR NamesSpecification Optical SystemSingle Beam Optics Interferometer“Double Cats Eye” interferometer, Sealed and Desiccated Beam SplitterMulti-layer coated quartz plate Light SourceTungsten halogen lamp DetectorSilicon photodiode Size580х515х295 mm Weight37 kg Power Requirements110/220Vac, 60/50 Hz Operating ConditionsTemperature: 10 o C to 35 o C, Humidity: Below 80%

18 SPECIFICATIONS NamesSpecification Spectral resolution0.8 – 1.6 nm Spectral range800 – 1163 nm (12500 – 8600 cm -1 ) Wavenumber accuracy< 0.1 nm Noise level of 100% line< 0.1 % (peak to peak) Photometric accuracy0.1 % T Spectral

19 SPECIFICATIONS Analytical NamesSpecification Typical analysis time 2  3 min Number of measured pointsUp to 30 Cell volume 3  60 cm 3 (depending on type) Cell pathlengths1.5 to 27 mm Accuracy (systematic relative error of the control sample parameters)  2.0 % Long-term scatter (relative, r.m.s.)0.1% Short-term scatter (relative, r.m.s.)0.05%


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