System and method for detecting contaminants in a sample using near-infrared spectroscopy
A system and method for detecting a contaminant in a sample. The contaminant may comprise melamine or a derivative thereof and the sample may comprise a feed material. The method may comprise illuminating a sample to thereby generate a first plurality of interacted photons, collecting the interacted photons, passing the interacted photons through a tunable filter, and detecting the interacted photons to generate a near infrared data set representative of the sample. This near infrared sample may comprise a hyperspectral near infrared image. The method may further comprise fusing said near infrared data set with a Raman data set representative of sample. A system may comprise an illumination source, one or more collection optics, a tunable filter, and a detector configured to generate a near infrared data set. The system may further comprise a second detector configured for generating a Raman data set representative of a sample.
1. A method comprising:
illuminating a sample to produce a first plurality of interacted photons;
collecting the first plurality of interacted photons;
passing the first plurality of interacted photons through a tunable filter to generate a first plurality and second plurality of filtered photons;
detecting the first plurality of filtered photons to generate a near infrared data set representative of the first plurality of filtered photons;
detecting the second plurality of filtered photons to generate a Raman data set representative of the second plurality of filtered photons; and
analyzing the near infrared data set and the Raman data set to determine one or more of the presence of a contaminant in the sample and the absence of a contaminant in the sample.
2. The method of claim 1 , wherein the sample comprises at least one feed material.
3. The method of claim 2 , wherein the feed material comprises one or more of wheat flour, corn gluten, soybean meal, and combinations thereof.
4. The method of claim 1 , wherein the tunable filter comprises one or more of a multi-conjugate liquid crystal tunable filter, a liquid crystal tunable filter, and combinations thereof.
5. The method of claim 1 , wherein the contaminant comprises one or more of melamine, cyanuric acid, ammeline, ammelide, and combinations thereof.
6. The method of claim 1 , wherein the near infrared data set comprises one or more of a near infrared spectrum, a spatially accurate wavelength resolved near infrared image, and combinations thereof.
7. The method of claim 1 , wherein the near infrared data set comprises at least one near infrared hyperspectral image.
8. The method of claim 1 , wherein the analyzing comprises comparing the near infrared data set to a reference data set.
9. The method of claim 8 , wherein the comparing comprises applying a chemometric technique.
10. The method of claim 1 , further comprising fusing the near infrared data set with a brightfield image representative of the sample.
11. The method of claim 1 , further comprising:
fusing the near infrared data set and the Raman data set to generate a fused data set; and
assessing the fused data set to determine one or more of the presence of a contaminant in a sample and the absence of a contaminant in a sample.
12. The method of claim 1 , wherein the Raman data set comprises one or more of a Raman spectrum, a spatially accurate wavelength resolved Raman image, and combinations thereof.
13. The method of claim 1 , wherein the Raman data set comprises at least one hyperspectral Raman image representative of the sample.
14. A system for determining the presence of a contaminant in a sample comprising:
an illumination source configured to illuminate a sample to generate a first plurality of interacted photons;
a collection optic configured to collect the first plurality of interacted photons;
a tunable filter configured to sequentially filter the first plurality of interacted photons and generate a first plurality and second plurality of filtered photons comprising a plurality of predetermined wavelength bands;
a first detector configured to detect the first plurality of filtered photons and generate at least one near infrared data set representative of the first plurality of filtered photons; and
a second detector configured to detect the second plurality of filtered photons and generate a Raman data set representative of the second plurality of filtered photons.
15. The system of claim 14 , wherein the sample comprises at least one feed material.
16. The system of claim 14 , wherein the contaminant comprises one or more of melamine, cyanuric acid, ammeline, ammelide, and combinations thereof.
17. The system of claim 14 , wherein the tunable filter comprises one or more of a multi-conjugate liquid crystal tunable filter, a liquid crystal tunable filter, and combinations thereof.
18. The system of claim 14 , wherein the near infrared data set comprises at least one near infrared hyperspectral image.
19. The system of claim 14 , wherein the near infrared data set comprises one or more of a near infrared spectrum, a spatially accurate wavelength resolved near infrared image, and combinations thereof.
20. The system of claim 14 , further comprising a reference database wherein the reference database comprises at least one reference data set associated with a known sample.
21. The system of claim 14 , wherein the Raman data set comprises one or more of a Raman spectrum, a spatially accurate wavelength resolved Raman image, and combinations thereof.
22. A method comprising:
illuminating a sample to produce a first plurality of interacted photons;
collecting the first plurality of interacted photons;
passing the first plurality of interacted photons through a tunable filter to generate a first plurality and second plurality of filtered photons;
detecting the first plurality of filtered photons to generate a near infrared data set representative of the first plurality of filtered photons;
detecting the second plurality of filtered photons to generate a Raman data set representative of the second plurality of filtered photons;
fusing the near infrared data set and the Raman data set to generate a fused data set; and
analyzing the fused data set to determine one or more of the presence of a contaminant in the sample and the absence of a contaminant in the sample.