INSTITUTE OF SPECTROSCOPY RUSSIAN ACADEMY OF SCIENCES

1. INSTITUTE OF SPECTROSCOPY RUSSIAN ACADEMY OF SCIENCES The study of dispersed systems using NIR spectroscopy and PLS regression technique A. Kalinin, А. Potapov,S. Sadovsky 142090, ISAN, Troitsk city, Moscow region, Russia, Tel. 7(495)334-0235, fax 7(495)334-0886 kalinin@isan.troitsk.ru VI Winter Symposium on Chemometrics February 18—22 , 2008, Kazan, Russia

2. Multi-component calibration (construction of calibration models) a spectrometer for the quantitative analysis of multiphase materials includes: • -choice of a spectral method and spectral “hardware”- spectrometers. This defined by the physical and chemical properties of object and by a specific task of definition; • -creation or accumulation of the reference sample sets that meets well known requirements (on representativeness, density of filling of an analyzed range, on absence of significant correlation between components of a mix, etc.); • -construction and testing of calibration models, its optimization. A choice and adaptation of tools for preprocessing of spectra and of the regression analysis. For the last step we have started up using the PLS program Quant 2 OPUS, manufactured by BRUKER OPTIC Ltd. But later it was unsatisfactory because of: 1) labour inputs for loading of greater sets of spectra and reference data, 2) has no some important intermediate interfaces, 3) it is inaccessible to modernization for current problems, 4) too expensive for the use in structure of our devices. PLS program ISCAP had been developed, tested by comparing with OPUS results, and certified at Federal Inspection on Industry Property, Russian Patent Committee. Now we use it for PLS calibration and prediction execution with our spectrometers and modify it for current problems.

3. WHAT’S TO DO:The leaders of Milk Institute of RAAS formulate for us the next tasks of dairyquality control : • Fat, protein and lactose contentprediction forraw milk. It’s obviously the most complex problem concerning of variability of physical and chemicalstructure of named object, • Definition of the nutritional value (fat, protein, lactose, saccharose, a dairy acid, calcium, cholesterol, etc.), in dairy produce and intermediate fractions (sour cream, concentrated milk, powder). • 3. Recognition of fakes of dairy fats and proteins in dairy produce or in the intermediate fractions. These problems were solved in several countries by well known producers, but (as can be seen at every year Milk Forums at Moscow) the applications of their instruments for Russian milk prediction isn’t successful till now. The specialtasks are: - to adapt the portable IR spectrometers for a prediction of quality parameters of Russian dairy; - to reduce cost of operational expenses.

4. Now we will show the selected results dealing with: Methods:NIR spectroscopy at transflectance and diffuse reflection modes, PLS regression, Laser correlation spectroscopy; Dispersions as objects for constituent and parameter prediction: -liquid and powdered milk, -hydrated reversed micelles (water-aerosol OT-octan) -water-ethanol-gasoline mixtures.

5. Calibration model with absorption spectra of 34 milk mixtures collected with spectrophotometer MC-75, described in: A.V.Kalinin, V.N.Krasheninnikov, V.M.Krivtsun, S.V.Sadovsky, in: Book of abstracts, International Congress on Analytical Sciences, 25-30 June, M., 1, 157, (2006).

6. Pre-production spectrometer BIKAN-K operating in transflectance mode for fat, protein, etc. prediction in liquid dairy Characteristics: • - Spectral range 800-1070 nm; • - The sizes 31X22X12 сm; • - Weight 4,6 kg; • - Time of definition of parameters in 10 samples - 6 minutes; • - A block design, simplicity of service; • - An opportunity of expansion of the basic models (for various a component, ranges of definition, products) A.Kalinin, V.Krasheninnikov, V.Krivtsun, S.Sadovsky, H.Denisovich, H.Yurova, JNIRS, Proceedings of NIR2007, accepted

7. 1-st der. cm-1 cm-1 65

8. Diffuse reflectionspectrometer BIKAN-CP for fat, protein, etc. prediction in powder on the basis of polychromator with a linerInGaAs-detector; Key characteristics: • - spectral range 1050-1650 nm, • - thermoresisted (<400Co) opto-fiber probe, • dimensions 31X22X12 sm, • weight of 4,5 kg; • - time of measurement is10 sec a sample; • - modular design, simplicity of service; • - an opportunity of expansion of bank calibration models (for defined components, their ranges, products, modes of measurement) A.Kalinin, V.Krasheninnikov, V.Krivtsun, S.Sadovsky, H.Denisovich, H.Yurova, JNIRS, Proceedings of NIR2007, accepted

9. Application of a portable near infra-red spectrometer of diffuse reflection БИКАН-СР with a high-temperature probe for the multicomponent analysis of damp powders and dispersed systems with uncontrollable temperature How to collect the diffuse reflection spectra of milk powder located in thermogravimetric moisture analyzer (TGA) with uncorrelated moisture and temperature value The set-up for spectra and moisture and temperature data acquisition A.Kalinin, V.Krasheninnikov, V.Krivtsun, S.Sadovsky, H.Denisovich, H.Yurova, JNIRS, Proceedings of NIR2007, accepted

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12. A compact photon-correlation spectrometer enables one to make absolute measurements of the sizes and evaluate the shape of particles suspended in liquids in the range from 0.001 to 10 μm. Themeasurements are fast, lasting usually from seconds to several minutes. laser correlation spectroscopy of scattered light rotator Лебедев А.Д.и др. Лазерная корреляционная спектроскопия в биологии. Киев, 1987.

13. laser correlation spectroscopy of scattered light The evaluation of nonsphericity Curve 1 – theoretical value for micelle radiusr, Curve 2 – the differenceΔR=Rh-rof experimental andtheoretical value for micelle radius, Curve 3 – parameterP defining the nonsphericity of micelle shape (Р=0 –for sphere) Potapov A.V., Saletsky A.M. Laser Physics Letters, 2005, v.2, №10, р.476-480

14. water-AOT-octane dispersion – the way for higher the sensitivity of NIR spectroscopy on water content prediction AOT- aerosol OT – dioctylsulfocuccein sodium – surface-active substance. It forms the micelles with water encapsulated in it of shown below structure if mass fractions of water and AOT content are related with “ratio of aquation”,w in the well known range: 20<w<70 There was prepared 10 samples with uncorrelated water and AOT mass fractions and was measured the size distributions with the use of LCS. The result were: - The scattered light level was sufficient to measure size distribution for 6 samples with w>20, - All distributions contained one single peak, and the value of average radius Rav shifted with w as R=(1.5w+.4+1.2) nm with the error not more than 10%. 1.2nm AOT molecule cavity filled by water R=.15w+.4 This result gave us the possibility to calculate the concentration of micelles for each dispersion and to build calibration on it and on diffuse reflection spectra collected with BIKAN-CP spectrometer. Potapov A.V., Saletsky A.M. Laser Physics Letters, 2005, v.2, №10, р.476-480

15. Calibration model built on diffuse reflection spectra collected with BIKAN-CP spectrometer of reversed micells in water-AOT-octane dispersions Cross validation Conc. of part. N of factors -1 Cross validation Water mass. fr. N of factors-4 This is the way for higher the sensitivity of NIR spectroscopy on water content prediction

16. The study of water-ethanol-gasoline dispersion was based on the model of water-ethanol scatters accordingly to A.M.Saletskii and others, Phys. Rev. Letters,1999, v.12, №1, р.124-127 We prepared 30 mixes, measured size distributions with the LCS and NIR spectra with the use of BIKAN-CP -The LCS size distribution typically had two, three and more peaks, - There is no any correlation between Rav and mass fractions of water and ethanol, So, it was not possible to define the value of scatter concentration and to look for correlation of spectra and scatter concentration variation

17. Calibration model is trivial: Ethanol content may be predicted, but not the water one.

18. Calibration model with unsatisfactory correlation of transflectance spectra and protein (globulin) content variations caused possibly by twenty fold less sizes of globulin molecular associations comparing with the casein ones Distribution on the sizes of associations of casein - a) and globulin–b) molecules in milk rav = 208 nm a rav = 8 nm b The useful result is: the spectrometer BIKAN-K isn’t sensible to fakes with serum protein concentrate

19. Conclusions: Automation of calibration model execution allows to consider at once a several models for each set of spectra and sample data, to compare their efficiency (reliability, complexity, an error, etc. qualities) and to estimate correctness of decisions on spectral technique and on calibration set design, Laser correlation spectrometry of nano-dispersive phase is useful tool of radiation-matter interaction research. • Aknowledgements: • - to ms Andrey Tretiyakov for preparation of dispersions, • to ms Alex Novosielov for operating with LSC, • to doctor Victor Krasheninnikov for operating with spectrometers and useful discussions Thank you for attention!