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     ChemWiz Analyzer Development Kit

Full spectrum chemometric analysis for multiple components can now be performed using the ChemWiz® Analyzer Development Kit (ADK).  This software toolkit, when combined with StellarNet spectrometer instrumentation and SpectraWiz operating software, enables rapid development of complex analyzers needed to provide custom measurement solutions for many applications.


ChemWiz Analyzer Development Kit
Chemometric M
odel Builder
& Wizard Runtime Engine


StellarNet Spectrometer Hardware
UV-VIS Spectrometers (200-1100nm)
NIR Spectrometers (900-2500nm)
Light Sources, Fibers, Accessories

 
Applications
Food & Agriculture
Plastics &Polymers
Pharmaceutical & Supplement
Chemical & Industrial
 

 

ChemWiz Model Builder Software
& Wizard Runtime Engine

Full spectrum chemometric analysis for multiple components can now be performed using the ChemWiz® Analyzer Development Kit (ADK).  This software toolkit, when combined with StellarNet spectrometer instrumentation and SpectraWiz operating software, enables rapid development of complex analyzers needed to provide custom measurement solutions for many applications.

Real-time spectral data is used as input to measure concentrations of up to 6 components such as moisture, fat, protein, alcohols, acids, or chemicals such as pesticides.  Alternatively, the ChemWiz® ADK can be used to classify samples, such as the types of plastic.

The toolkit includes a model builder which is used to process spectra from a set of known component concentrations.  Here the spectral pre-processing techniques are selected such as multivariate scatter correction (MSC), smoothing, derivatives, and mean centering.  The multivariate analysis type is then selected such as partial least squares (PLS).  Finally a cross validation technique is chosen and used to improve the reported statistics indicating accuracy and fitness of the calibration model created.

The ADK includes a runtime engine that performs the analysis in real-time with little to no sample preparation.  The measurement results are displayed on the SpectraWiz Application panel for “Chemometric Predictor” which is also provided in our LabVIEW software program for OEM developers.

Each analyzer system can be tailored with sampling accessories to measure liquids, solids, and powders.  For liquids, absorbance is measured via flow cells, dip probes, or cuvettes.  For solids and powders, reflectance is typically used to measure sample absorbance.  Near infrared diode array spectrometers such as the DWARF-Star NIR-512 with TEC cooling are typically configured for analyzer development.

 

Flow Chart of Analyzer Development

 

1. Prepare a set of Standard Samples with known concentrations of the parameter of choice (moisture, fat, fiber, etc..). Generally the Standard samples will be prepared by the end user and sent to a laboratory for chemical analysis. (rtech labs).

2. Collect spectra of each Standard Sample using StellarNet Spectrometer Instrumentation.
 

3. Load collected Spectra into the chemometric model builder and select (a) desired wavelengths of calibration (b) spectral preprocessing (c) cross validation methods (d) and model of choice.

4. Once the calibration model is built it can be verified using
statistics indicating accuracy and fitness of the model. The end user may build many different models for different sample types and matrices (i.e. different types of cheese powders may require separate models for the highest accuracy of prediction).

5. Load model file into SpectraWiz and open ChemWiz Chemometric predictor panel to view calculation of your parameters of choice from each collected spectrum in real-time.
 

 


ChemWiz Analyzer Development Kit PDF


ChemWiz® Chemometric predictor panel in SpectraWiz displaying component concentration values in real-time.
 

ChemWiz ADK Features 

Ř       Multivariate algorithms for Quantitative analysis
Partial Least Squares PLS, Principle Component Regression PCR

Ř       Discriminant methods for Qualitative analysis
Principle Component Analysis PCA, and MDR

Ř       Preprocessing options to stabilize data
Sample averaging, Spectral smoothing,
First or second derivative with gap select,
Multiplicative scatter correction, Mean centering,
and lots more preprocessing options.

Ř       Visual graphs and Model cross validation  

Ř       Applications  include:
Food Safety
Packaging / Process
Beverage QC
Agriculture Feed
Pharmaceutical
Oil & Chemical
Plastics


The panel shown is the SpectraWiz software Application for chemometric model prediction, that uses reflectance to measure percent composition of Amino Acid in sample powders. Application is only enabled when the Wizard detects a model and the Wizard Runtime chemometric prediction engine is installed.  Save sample, review log, spectral reference, and model selection are accessible.
 

 


ChemWiz Chemometric Model Builder

-
Spectral Import and Wavelength Selection

- Pre-processing with Display
(Centering, , Scaling, MSC, Smoothing, Derivatizing)

- Model Cross Validation
(Venetian Blinds, Leave one out, Contiguous)
 

- Samples/Scores Plots
 


 

 
 
 
 
 

       Price List and Specifications

Item

Description

Price

ChemWiz-ADK

Chemometric model builder plus runtime engine

$3500*

Wizard-runtime

Runtime engine for chemometric models – one license only

$1500*

  * Contact StellarNet application scientist as price will vary with choice of 3rd party vendor for model and predictor engine   

Specifications

Operating System

WinXP, Vista, Win 7

Runtime speed

3Hz max

Runtime

SpectraWiz v5.0 or higher

Full Spectrum Measures

Concentrations or Classification

Spectral range

190 – 2500nm

Analysis (typical)

PLS or PCA/MDR


     StellarNet Spectrometer Instrumentation


StellarNet's wide range of miniature spectrometer instrumentation and complete line of light sources, optical fibers, and sampling accessories combine with the new ChemWiz® Analyzer Development Kit (ADK) to allow end user's to build their own custom analyzers.

StellarNet’s newest NIR spectrometer, the DWARF-Star, is small, robust, and equipped with high performance InGaAs detector array for the 900-1700nm wavelength range and achieves resolving resolutions to 1.25nm. The DWARF-Star features no moving parts and is packaged in a small rugged metal enclosure (5”x3”x2”) for portable & process.  Advancements in electronic and optical design have allowed for size reduction never before achieved in a NIR spectrometer. Go to DWARF-Star webpage.


The BLUE-Wave spectrometers are the standard choice for UV-VIS-NIR spectroscopy from 200-1100nm.  Wavelength range and resolution requirements can be easily selected from the table below.  BLUE-Wave spectrometers are recommended for  process monitoring applications where throughput and collection speed are top priority. New and improved electronics with a high speed 16-bit digitizer allow for fast data acquisition and signal to noise of 1000:1. Additionally, the compact size (25 x 75 x 125mm) makes system integration easy! Any BLUE-Wave spectrometer can be custom configured for specific wavelength ranges. Contact a StellarNet sales engineer to discuss your specific requirements.


The BLACK-Comet Concave Grating spectrometer is also recommended for use with ChemWiz.  This unit provides flat field detector imaging for continuous focus and uniform resolution across the wavelength range while minimizing stray light. No other miniature spectrometer on the market offers the advantages of the BLACK-Comet Concave Grating PDF.  This unit is slightly larger in size (69 x 100 x150mm) than the BLUE-Wave and offers options for an integrated thermoelectric cooler. 
 

StellarNet RED-Wave near infrared spectrometers provide the high sensitivity and resolution over the 900-2300nm wavelength range using InGaAs PDA technology. The units are exceptionally robust and are packaged in small rugged metal enclosures for portable, process, and lab applications.  Compact size (69 x 100 x 150mm) allows easy integration.

The InGaAs detector is linear photo diode array with 512 pixels (1024 optional) 25μm by 500μm tall to provide maximum sensitivity.  The detector has an integrated thermo electric cooler (TEC) maintained at –10 °C, stabilized within +/-0.1 °C.  The unit requires external 5V power supply.

* Please note all NIRX spectrometers use an extended range InGaAs detector array. This detector required special consideration when choosing light source and accessory components. Please ContactUs@StellarNet.us for configuration support.

 
 
     ChemWiz Analyzer Applications

Full spectrum chemometric analysis for identification of multiple component parameters has many applications. Currently the Food and Agricultural Industries have developed many methods for quality control and safety assurance. UV-VIS and NIR spectroscopy serve as a means for rapid non-contact analysis of samples, revolutionizing our current standards for product control. Other industries such as the polymer and plastic, chemical and industrial, pharmaceutical & and dietary supplement industries find useful applications with UV-VIS-NIR spectroscopy.

This section of the website serves to provide useful resources for applications requiring chemometrics models and UV-VIS & NIR spectroscopy to determine various parameters of choice.  Although other hardware and software may have been used to accomplish the measurements in the literature cited below, StellarNet spectroscopy instrumentation and development software may be used for similar applications.  StellarNet engineers are available to suggest configurations; however, StellarNet is not a consultant firm or R&D facility.  Please refer to the references for further information and/or guidance to determine feasibility of your project.  Below the parameters of choice are black and the references are listed below in blue and pink.
 

Food and Agriculture
From compositional analysis to process optimization and quality control, our robust NIR systems will allow you to determine multiple parameters simultaneously.  Incoming raw materials are easily measured to verify they meet all specifications certified by the vendor and batch ratios can be monitored for uniformity, ensuring a quality final product, avoid over-processing, and much more.
 

Forage & Feedstuffs
Since the explosion of N
IR spectroscopy in the 70's there have been more published studies on NIR applications in forages and feed analysis than any other agricultural commodity. NIRS is used to monitor certain parameters such as moisture, ash, protein, total nitrogen, fiber, lignin, and even certain parameters such as digestibility and energy content.  Water is the most dominant feature in the NIR spectra of most agricultural products because of the strong absorptions in the combination band (1870-1945nm) and the first overtone (1430-1450mn)1. Ash content represents the minerals both available and unavailable to the animal (it is the inverse of organic matter content). Crude Protein calibrations are usually accurate due to the strong -NH absorptions in the NIR with most reported squared correlation coefficients (R2) greater than 0.95.  Fiber can be estimated due to variations in -CH and -OH absorptions. Digestibility is a property usually predicted by regions around 1670nm (aromatic -CH) and 2270nm where cellulose and lignin strongly absorb2.

Alfalfa - Barley straw - Bromegrass - Corn - Timothy - Hays

1. Abrams, SM., J.S Shenk, and H.W. Harpster. 1988. Potential of near IR reflectance spectroscopy for analysis of silage composition. J. Dairy Sci. 71:1955-1959.

2. Agung, P., K. Mitsunori, N. Takehiro, T. Fuminori, A. Akira, and H. Tatsuo. 1997. Two methods of near infrared reflectance spectroscopy for digestibility and energy value feeds. Anim. Sci. Technol. 67:851-861

3. Pazdernik, D.L., A.S. Killam, and J.H. Orf. 1997. Analysis of amino and fatty acid composition in soybean seed. Agron. J. 89:679-685


Small Grain Crops
Like forages and feedstuffs, small grain crops and cereals, especially wheat, have also been examined extensively. Common analytes or parameters have been amino acids, ash, glucosamine, moisture, protein, and whole grain analysis.

Barley - Rice7 - Wheat

4. American Society of Brewing Chemists. 1998. Report of subcommittee on protein and moisture in whole-grain barley by near infrared spectroscopy. J. Am. Soc. Brew. Chem. 56:189-194.


5. Delwiche, S.R. and W.R. Hruschka. 2000. Protein content of bulk wheat from near infrared reflectance of individual kernels. Cereal Chem. 77:86-88.

7. Iwamoto, M., T. Suzuki, N. Kongseree, J. Uozumi, and O. Inatsu. 1986. Analysis of protein and amino acid contents in rice flour by near-infrared spectroscopy. Nippon Shokuhin kogyo Gakkaishi 33:848-853.

Coffee, Tea, Tobacco, & Related Products
Commercial coffee is mainly made up of two main blends, Arabica and Robusta.  Main distinguishing absorptions can be found from water content (1466 and 1962nm) and lipids (1209, 2308, and 2346nm)8.  NIRS can be used for classification as well as blending. Also, caffeine and dry matter content can be determined.  Green9, black, and oolong tea can be analyzed for different different polyphenols, caffeine, and amino acids by using various wavelengths in the NIR thus allowing rapid determination of factors relating to tea taste and health parameters. Since the 70's NIRS has been used to predict the total reducing sugar content in tobacco and total alkaloids providing valuable information about the mildness and aroma of the smoke10.


Dual DSR- Reflectance Spectra of Folgers Caffeinated, Decaffeinated, & Half-Caffeinated coffees

8. Downey, G., and J. Boussion. 1996. Authentication of coffee bean variety  by near-infrared reflectance spectroscopy of dried extract. J. Sci. Food Agric. 71:41-49.

9. Ikegaya, K.,1990.
Determination of chemical constituents in processed green tea by near infrared analysis. JARQ 24:49-53.


10. Hamid, A., W.F. McClure, and W.W. Weeks. 1978. Rapid spectrophotometric analysis of chemical composition of tobacco. Part 2. Total alkaloids. Beitr. Tabakforsch. Int. 9:267-274.

Polymers and Plastics Production
StellarNet’s chemometrics toolkit speeds up decision making by equipping you with faster analytical results, shortening the time from raw material to final product.  This can be used to identify the presence of residual monomers and determine polymers ratios, saving time and operating costs.  Pilot scale-up pains can be minimized by improving quality and optimizing overall profit.


NIR Spectra of HDPE (high density polyethylene)


NIR spectra of PET (polyethylene terephthalate)

 

Fruits and Vegetables
Other fruits and vegetables can be monitored for percentage soluble solids, acids and sugar content and even ripeness. A sample table listed below provides some examples of parameters found in the literature on various sample types.

Sample

Parameter
Apple acid11, bruised tissue, dry matter, firmness, fructose, glucose11, moisture12 , pH, solube solids, sugar12
Cherry firmness13, pit detection, soluble solids
Date moisture, soluble solids
Orange citric acid, malic acid, fructose, glucose, purity
Papaya carotenoids, chlorophyll, maturity, soluble soids
Potato bruised tissue, discoloration, maturity, sorbitol, sucrose
Tomato acidity, maturity, soluble solids

11. Budiastra, I.W., Y. Ikeda, and T. Nishizu. 1998. Optical Methods for quality evaluation of fruits. Part 2. Prediction of individual sugars and malic acid concentrations of apples and mangoes by the developed NIR reflectance system. J. Jpn. Soc. Agric. Machin.60:117-127

12. Murakami, M., J Himoto, and K. Itoh. 1994.
Analysis of apple quality by near-infrared reflectance spectroscopy. J. Fac. Agric. Hokkaido Univ. Jpn. 66:51-61

13 Lu, R. 2001a.
Predicting firmness and sugar content of sweet cherries using near-infrared diffuse reflectance spectroscopy. Trans. ASAE 44:1265-1271

Beverages and Brewing
Beverage and wine industry use NIRS spectrometers to monitor the quality of incoming barley and hops and ethanol concentrations during brewing stages and distilling. Red grapes for winemaking have been analyzed for certain parameters such as anthocyanins, total soluble solids, and pH over the range 400-2500nm. Ethanol
14, fructose, and tartaric acid have been popular parameters of interest in final wine products.

14. Buchanan, B.R., D.E. Honigs, C.J. Lee, and Roth. 1988. Detection of ethanol in wines using optical-fiber measurements and near infrared analysis. Appl. Spectrosc.42(6):1106-1111.

15. Coventry, A.G., and M.J. Hunston. 1984.
Applications of near-infrared spectroscopy to the analysis of beer samples. Cereal Foods World 29:715, 717-718.



Meats
Meats, poultry, and fish are also monitored by NIRS. Certain parameters such as fat, moisture, and protein con
tent are some of the most important. Ground and frozen meats can be analyzed for quality and control and even factors such as meat tenderness can be acquired14!

Pork - Chicken - Turkey - Beef - Lamb - Fish - Ground Meats - Frozen

14. Hildrum, K.I., B.N. Nilsen, M. Mielnik, and T. Naes. 1994. Prediction of sensory characteristics of beef by near infrared spectroscopy. Meat sci. 38:67-80.

15. Windham, W.R., and W.H. Morrison. 1998. Prediction of fatty acid content in beef neck lean by near infrared reflectance analysis. J. Near Infrared Spectrosc. 6:229-234.

Dairy and Eggs Products

Our complete solution of combined hardware and software can help you to improve the productivity and efficiency of many dairy processing applications.  Milk is the first food for humans and mammals alike, and therefore quality control and analysis of Dairy products is of utmost importance. This is all in an effort to help you reduce costs while ultimately improving quality by monitoring parameters such as protein, fat, lactose, and much more.  Non-destructive sample testing ensures fast and low cost analysis whenever you need it.
 

Milk - Milk Powder - Cheese - Cheese Powders - Butter - Whey


16. Barabassy, S., and K. Kaffka. 1993. The application possibilities of the near infrared technique in the non destructive investigation of mixed milk powder products. J. Food Phys. 57:39-48.

17. Frank, J.F. and G.S. Birth. 1982. Application of near infrared reflectance spectroscopy to cheese analysis. J. Dairy Sci. 65:1110-1116.

 

Fats and Oils
Fats and oils constitute the main source of energy and essential fatty acids in the human an animal diet. All fatty acids display peaks of varying intensities at 1700nm due to a weak C-H modes. Also, weaker overtones can be found at 1200, 2200, and 2500nm.

Sample

Parameter
Soybean oil acid values, iodine, cis/trans FAs
Olive oil18 Free Fatty Acids, total polyphenols, K270, 235, 225 , moisture, a
Sunflower linoleic, palmitic, palmitoleic, stearic, & oleic acids
Sesame oil linoleic, palmitic, palmitoleic, stearic, & oleic acids
Butter moisture, fat, NaCl, nonfat solids, purity


18.  Garrido, A., C. Cobo, J. Garicia-Olmo, M.T. Sanchez-Pineda, R. Alcala, J.M. Horcas, and A. Jimenez. 2000. The feasibility of near infrared spectroscopy for olive oil quality control. p. 867-871. InA.M.C. Davies and R. Giangiacomo (ed.) Near Infrared spectroscopy: Proceedings of the 9th Int. Conference. NIR publications, Chichester, UK.
 
19. Perez-Vich, B., L Velasco, and J.M. Fernandez-Martinez. 1998. Determination of seed oil content and fatty acid composition in sunflower through the analysis of intact seeds, husked seeds, meal, and oil by near infrared reflectance spectroscopy. J. Am. Oil Chem. Soc. 75:547-555.

 

Chemical/ Industrial Applications
From pilot plants to full scale production, we have solutions to improve your products’ performance.  Reaction monitoring and end point determination can save valuable down time and optimize your formulations.  Our systems can be used to rapidly determine component analysis such as
moisture, active ingredients, blends, and mixing endpoints.


 

 

 


 

BioFuel Analysis
StellarNet NIR systems are keeping up with today’s demands for alternative energy by providing tools for many bio-fuel applications. Our chemometrics package can provide quick, non-destructive analysis at every stage with little to no sample prep.  By aiding in raw material selection and optimization of in-line process monitoring, you’ll be able to find the most cost-efficient production methods.

 
 
 
 
 

         

   
         
 

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