Food and Agriculture
From compositional analysis to
process
optimization and quality control, our
robust NIR systems will allow you to determine multiple
parameters simultane ously. 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 NIR
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) |
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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. Ethanol14, 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
sof tware 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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