Systems and methods for food safety detection

• US 7,956,997 B2
• Filed: 10/07/2008
• Issued: 06/07/2011
• Est. Priority Date: 05/27/2003
• Status: Expired due to Fees

• Current Assignee: OptoTrace Technologies, Inc.
• Original Assignee: OptoTrace Technologies, Inc.
• Inventors: Liu, Chunwei, Wang, Hong, Guo, Xun
• Primary Examiner(s): Geisel; Kara E
• Application Number:
  US12/246,616
• Publication Number:
  US 20090046284A1
• Time in Patent Office: 973 Days
• Field of Search: 356/301
• US Class Current: 356/301
• CPC Class Codes: G01J 3/02 Details
• CPC Class Codes: G01J 3/0208 using focussing or collimating elements, e.g. lenses or mirrors; performing aberration correction
• CPC Class Codes: G01J 3/021 using plane or convex mirrors, parallel phase plates, or particular reflectors
• CPC Class Codes: G01J 3/0218 using optical fibers
• CPC Class Codes: G01J 3/44 Raman spectrometry; Scattering spectrometry ; Fluorescence spectrometry
• CPC Class Codes: G01N 2021/656 Raman microprobe
• CPC Class Codes: G01N 21/15 Preventing contamination of the components of the optical system or obstruction of the light path
• CPC Class Codes: G01N 21/658 enhancement Raman, e.g. surface plasmons
• CPC Class Codes: G01N 21/94 Investigating contamination, e.g. dust G01N21/85 takes precedence

Abstract

A method for detecting an ingredient in a food product includes establishing a spectral signature in a Raman spectrum obtained from a chemical substance; allowing a food sample solution obtained from a food product to come to contact with a first nano-scale surface structure in a first sensor, wherein the first sensor comprises a substrate, wherein the nano-scale surface structure comprises a plurality of columns over the substrate or a plurality of holes in the substrate; illuminating the food sample solution and the first nano-scale surface structure on the first sensor by a laser beam; scattering the laser beam by the food sample solution and the first nano-scale surface structure to produce a scattered light; obtaining a first Raman spectrum from the scattered light using a spectral analyzer; and identifying the spectral signature in the first Raman spectrum to determine the existence of the chemical substance in the food product.

Claims

1. A method for detecting an ingredient in a food product, comprising:

establishing a spectral signature in a Raman spectrum obtained from a chemical substance;

allowing a food sample solution obtained from a food product to come into contact with a first nano-scale surface structure in a first sensor;

illuminating the food sample solution and the first nano-scale surface structure on the first sensor by a laser beam;

scattering the laser beam by the food sample solution and the first nano-scale surface structure to produce a scattered light;

obtaining a first Raman spectrum from the scattered light using a spectral analyzer; and

identifying the spectral signature around a predetermined wavelength in the first Raman spectrum to determine the existence of the chemical substance in the food product,

wherein the step of establishing comprises;

allowing a reference sample solution containing the chemical substance to come to contact with a second nano-scale surface structure in a second sensor; and

obtaining a second Raman spectrum from the reference solution and the nano surface to establish the spectral signature in the Raman spectrum for the chemical substance;

wherein the spectral signature includes at least one spectral peak around the predetermined wavelength in the first Raman spectrum; and

wherein the step of identifying comprises;

determining if the spectral peak in the first Raman spectrum or a signal-to-noise ratio for the spectral peak is above a pre-determined threshold value; and

positively identifying the chemical substance if the spectral peak or the signal-to-noise ratio is above the pre-determined threshold value.

2. The method of claim 1, wherein the first sensor and the second sensor have substantially the same nano surface structures.

3. The method of claim 1, wherein the sensor further comprises a conductive material on the substrate.

4. The method of claim 3, further comprising:

during the step of illuminating, applying an electric potential to the conductive material in the first nano-scale surface structure to enhance charge transfer between molecules of the conductive material and the conductive material in the first nano-scale surface structure.

5. The method of claim 1, wherein the first sensor comprises a substrate, wherein the nano-scale surface structure comprises a plurality of columns over the substrate or a plurality of holes in the substrate.

6. The method of claim 5, wherein the plurality of columns or the plurality of holes have an average neighboring distance in a range from 10 nanometers to 1000 nanometers.

7. The method of claim 1, further comprising introducing nano particles on a surface of the first sensor, wherein the first nano-scale surface structure includes the nano particles on the surface of the first sensor.

8. The method of claim 7, further comprising:

suspending the nano particles in the food sample solution; and

introducing the food sample solution to the surface of the first sensor.

9. The method of claim 1, further comprising determining a concentration of the chemical substance using the spectral signature if the chemical substance is determined to exist in the food product.

10. The method of claim 1, wherein the food product includes dairy products, candies, drinks, alcohol, meat, seafood, tea, fresh or canned vegetables, fruits, grain products, cereals, corn chips, potato chips, or protein containing food.

11. The method of claim 10, wherein the dairy products comprise milk, milk powders, cheese, cheese-containing cakes, yogurts, ice creams, or milk containing candies.

12. The method of claim 1, wherein the chemical substance comprises melamine, sodium cyclamate, sodium cyclohexylsulfamate, cane sugar, starch, nitrite, nitrate, Sudan I, II, III and IV, malachite green, methomidophos, acephate, DDT, DDV, malathion, fenitrothion, deltamethrin, cypermethrin, methyl parathion, phosmet, dimethoate, nitrofuran, furanzolidole, chloramphenicol, chlortetracycline, ciprofloxacin, clenbuterol, or enorfloxacin.

13. The method of claim 1, wherein the product comprises a dairy product, wherein the chemical substance includes melamine, wherein the spectral signature comprises one or more of spectral peaks at about 678 cm⁻

1, 698 cm<sup>−

1</sup>, or 712 cm<sup>−

1</sup>, or at about 1648 cm<sup>−

1</sup>.

14. The method of claim 1, wherein the chemical substance includes protein, wherein the spectral signature comprises one or more of spectral peaks at about 1658 cm ⁻

1.

15. The method of claim 1, wherein the chemical substance includes starch, wherein the spectral signature comprises one or more of spectral peaks at about 473 cm⁻

1.

16. A method for detecting an ingredient in a food product, comprising:

allowing a reference sample solution containing the chemical substance to come into contact with a first nano-scale surface structure in a first sensor;

obtaining a first Raman spectrum from the reference solution and the nano surface to establish a spectral signature in the first Raman spectrum for the chemical substance;

allowing a food sample solution obtained from a food product to come to contact with a second nano-scale surface structure in a second sensor;

illuminating the food sample solution and the second nano-scale surface structure on the second sensor by a laser beam;

scattering the laser beam by the food sample solution and the second nano-scale surface structure to produce a scattered light;

obtaining a second Raman spectrum from the scattered light using a spectral analyzer;

and

identifying the spectral signature around a predetermined wavelength in the second Raman spectrum to determine the existence of the chemical substance in the food product;

wherein the spectral signature includes at least one spectral peak around the predetermined wavelength in the first Raman spectrum;

wherein the step of identifying comprises;

determining if the spectral peak in the second Raman spectrum or a signal-to-noise ratio for the spectral peak is above a pre-determined threshold value; and

positively identifying the chemical substance if the spectral peak or the signal-to-noise ratio is above the pre-determined threshold value.

17. The method of claim 16, wherein the first sensor and the second sensor have substantially the same nano surface structures.

18. The method of claim 16, further comprising determining a concentration of the chemical substance using the spectral signature if the chemical substance is determined to exist in the food product.

19. The method of claim 16, wherein the food product includes dairy products, candies, drinks, alcohol, meat, seafood, tea, fresh or canned vegetables, fruits, grain products, cereals, corn chips, potato chips, or protein containing food.

20. The method of claim 16, wherein the chemical substance comprises melamine, sodium cyclamate, sodium cyclohexylsulfamate, cane sugar, starch, nitrite, nitrate, Sudan I, II, III and IV, malachite green, methomidophos, acephate, DDT, DDV, malathion, fenitrothion, deltamethrin, cypermethrin, methyl parathion, phosmet, dimethoate, nitrofuran, furanzolidole, chloramphenicol, chlortetracycline, ciprofloxacin, clenbuterol, or enorfloxacin.

21. The method of claim 16, wherein the product comprises a dairy product, wherein the chemical substance includes melamine, wherein the spectral signature comprises one or more of spectral peaks at about 678 cm⁻

1, 698 cm<sup>−

1</sup>, or 712 cm<sup>−

1</sup>, or at about 1648 cm<sup>−

1</sup>.

22. The method of claim 16, wherein the chemical substance includes protein, wherein the spectral signature comprises one or more of spectral peaks at about 1648 cm⁻

1.

23. The method of claim 16, wherein the chemical substance includes starch, wherein the spectral signature comprises one or more of spectral peaks at about 473 cm⁻

1.

24. The method of claim 16, wherein the first nano-scale surface structure in a first sensor includes a plurality of columns or a plurality of holes having an average neighboring distance in a range from 10 nanometers to 1000 nanometers.

25. The method of claim 16, further comprising:

introducing a first group of nano particles on a surface of the first sensor, wherein the first nano-scale surface structure includes the first group of nano particles on the surface of the first sensor; and

introducing a second group of nano particles on a surface of the second sensor, wherein the second nano-scale surface structure includes the second group of nano particles on the surface of the second sensor.

26. The method of claim 25, wherein the first group of nano particles and the second group of nano particles have substantially the same size distribution and material composition.

27. The method of claim 25, further comprising:

suspending the second group of nano particles in the food sample solution; and

introducing the food sample solution to the surface of the second sensor.

28. A method for detecting an ingredient in a food product, comprising:

allowing a reference sample solution containing a chemical substance to come into contact with a first nano-scale surface structure in a first sensor, wherein the first nano-scale surface structure includes a plurality of nano particles on a surface of the first sensor, or a plurality of columns or holes having an average neighboring distance in a range from 10 nanometers to 1000 nanometers;

obtaining a first Raman spectrum from the reference solution and the nano surface to establish a spectral signature around a predetermined wavelength in the first Raman spectrum for the chemical substance, wherein the spectral signature includes at least one spectral peak around the predetermined wavelength in the first Raman spectrum;

allowing a food sample solution obtained from a food product to come into contact with a second nano-scale surface structure in a second sensor, wherein the first sensor and the second sensor have substantially the same nano surface structures;

illuminating the food sample solution and the second nano-scale surface structure on the second sensor by a laser beam;

scattering the laser beam by the food sample solution and the second nano-scale surface structure to produce a scattered light;

obtaining a second Raman spectrum from the scattered light using a spectral analyzer;

identifying the spectral signature around the predetermined wavelength in the second Raman spectrum to determine the existence of the chemical substance in the food product, wherein the step of identifying comprises determining if the spectral peak in the second Raman spectrum or a signal-to-noise ratio for the spectral peak in the second Raman spectrum is above a pre-determined threshold value; and

positively identifying the chemical substance if the spectral peak or the signal-to-noise ratio is above the pre-determined threshold value.

29. The method of claim 28, wherein the product comprises a dairy product, wherein the chemical substance includes melamine, wherein the spectral signature comprises one or more of spectral peaks at about 678 cm⁻

1, 698 cm<sup>−

1</sup>, or 712 cm<sup>−

1</sup>, or at about 1648 cm<sup>−

1</sup>.

30. The method of claim 28, wherein the chemical substance includes protein, wherein the spectral signature comprises one or more of spectral peaks at about 1648 cm⁻

1.