Advance in Detection Technique of Lean Meat Powder Residues in Meat Using SERS: A Review
Abstract
:1. Introduction
2. Physical and Chemical Properties of LMP
2.1. Types of LMP
2.2. Molecular Structure of LMP
2.3. Mechanisms of Action
3. Raman Spectroscopy and Surface-Enhanced Raman Scattering Techniques
3.1. Raman Spectroscopy
3.2. Surface-Enhanced Raman Scattering Spectroscopy
3.2.1. Enhancement Mechanism of EM
3.2.2. Enhancement Mechanism of CM
3.3. Procedure for the Detection of LMP Residues in Meats by SERS Technology
4. Applications for LMP Detection
4.1. Raman Spectroscopy without Enhancement
4.2. Application of SERS Spectroscopy for Detecting LMP Residues in Meat
4.2.1. Common Metal Nanoparticle Substrates
4.2.2. Metal Nanoparticles Bound to Adsorbent Materials
4.2.3. Metal Nanoparticles Bound to Chemical Substances
4.3. Application of SERS in Combination with Related Techniques for Detecting LMP in Meat
4.3.1. SERS Combined with Immunochromatography
4.3.2. SERS in Combination with Other Techniques
5. Conclusions and Future Trends
- (1)
- Development of novel enhancement substrates with larger SERS enhancement factors and stabilized SERS signals will greatly enhance the SERS signal.
- (2)
- Deposition of metal nanoparticles on a densely ordered solid substrate results in a more uniform “hot spot” produced by the metal nanoparticles.
- (3)
- Combining metal nanoparticles with physically or chemically adsorbent materials allows for better adsorption of target molecules on the surface of the nanoparticles, resulting in higher SERS intensities and stable signals.
- (4)
- Development of solid transparent substrates to reduce the extraction process of LMP residues in meat and to detect them directly on the meat, thus realizing non-destructive and rapid detection.
- (5)
- The combination of two or more nanoparticles for the simultaneous detection of target molecules can greatly enhance the SERS signal of target molecules.
- (6)
- More information on SERS spectra should be mined. Currently, it has been reported that the characteristic bands of SERS signals are mainly selected to establish a ULR, MLR, or PLSR model with the concentration of substances, and the modeling process is relatively simple. The information on the characteristic bands is underutilized, such as the shape of the characteristic bands, the area, etc. The prediction of residual concentrations of target molecules using neural network modeling will be the future direction.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Method | Enhanced Substrate | Material | Target Molecule | Quantitative Range | LOD | References |
---|---|---|---|---|---|---|
SERS | - | Rat meat | Clenbuterol | 5–10,000 ppb | – | [67] |
SERS | MAgNPs | Water | Salbutamol | 0–1000 ng/µL | 1.25 ng/μL | [68] |
SERS | Au NPs | Water | Clenbuterol, salbutamol, terbutaline | 0–10−4 mol/L | 35, 765, 55 ng/mL | [69] |
SERS | Au NPs | Water | Clenbuterol, ractopamine | 0.1–5 mg/L | 0.1 mg/L | [70] |
SERS | Au NPs | Standard solution | Clenbuterol, ractopamine, salbutamol, | 1–20 mg/L | 0.002, 0.1, 0.002 mg/L | [71] |
SERS | Gold-plated Klarite | Swine urine | Ractopamine, | 0.4–8 µg/mL | 0.4 μg/mL | [72] |
SERS | Ag NPs | Saliva, urine | Clenbuterol | 2.5–1000 ng/mL | 25 ng/mL | [73] |
SERS | Ag NPs | Standard solution | Salbutamol | 0.2−1 mg/L | 0.2 mg/L | [74] |
SERS | Au NPs | Standard solution | Clenbuterol, ractopamine | 0.1–1 µg/mL | 18 ng/mL, 24 ng/mL | [75] |
SERS | Au NPs | Pork | Clenbuterol | 1–10 µg/g | 1 µ g/g | [76] |
SERS | Au NPs | Pork | Clenbuterol | 0.5–15 µg/mL | 42 ng/g | [77] |
SERS | Ag NPs | Pork | Ractopamine | 10−8−10−4 M | 1.0 × 10−8 M | [78] |
SERS | GO/AuNP | Standard solution | Clenbuterol | 5 × 10−8–10−6 mol/L | 3.34 × 10−8 mol/L | [79] |
SERS | RoGO/AuNPs | Animal urine | Salbutamol | 1–20 ng/mL | 0.5 ng/mL | [80] |
SERS | Au NPs | Swine urine | Clenbuterol | 0.5–20 ng/mL | 0.5 ng/mL | [81] |
SERS | roGO/AuNPs | Animal urine | Clenbuterol | 1–20 ng/mL | 0.5 ng/mL | [82] |
SERS | GCA-Ab | Pork, pig liver, urine | Salbutamol, trombuterol | 0.005–100, 0.003–200 ng/mL | 1.0, 2.0 pg/mL | [83] |
SERS | Fe3O4@Ag | Pork | Salbutamol | 10−11–10−6 M | 1.0 × 10−10 M | [84] |
SERS | Au NPs | Standard solution | Clenbuterol | 0.0033–0.067 ng/mL | 0.68 pg mL | [85] |
SERS-IA | Fe3O4@Au@Ag | Pork | Clenbuterol | 0.01–10 ng/mL | 3 pg/mL | [86] |
SERS-IA | Fe3O4@Au-Ab | Standard solution | Clenbuterol, salbutamol | - | 17 fg/mL | [87] |
SERS-IA | Fe3O4@Au-Ab | Standard solution | Clenbuterol | 1–100 ng/mL | 0.22 fg/mL | [88] |
SERS-Elisa | Ag NPs | Swine urine | Ractopamine | - | 10−6 ng/mL | [89] |
SERS-IAC | AuMBA @Ag-Ab | Swine urine | Phenylethanolamine A | 0–100 ng/mL | 0.32 pg/mL | [90] |
SERS-ICA | AuMBA @Ag–Ab | Swine urine | Clenbuterol | 0–10 ng/mL | 0.24 pg/mL | [91] |
SERS-LFIA | AuNFsMBA@Ag-Ab | Pork, swine urine | Brombuterol | 0–100 ng/mL | 0.5 pg/mL | [92] |
SERS-LFIA | Au@Au nanostar | Standard solution | Clenbuterol | 0.05–1 ng/mL | 0.05 ng/mL | [93] |
SERS- | Ab–BPAuDP–Ab | Standard solution | Clenbuterol, ractopamine | 1–1000 pg/mL | 1 pg/mL | [94] |
SERS-IAC | Fe3O4@Au-Ab | Pork, beef, and lamb | Clenbuterol, ractopamine | 0–3 ng/mL | 7.8 pg/mL 3.5 pg/mL | [95] |
SERS-LFA | Fe3O4@Au@Ag | Pork, lake water | Ractopamine, clenbuterol | - | 2.5, 6.2 pg/mL | [96] |
SERS | AuMBA-Ab | Pig hair | Clenbuterol | 0.1–100 pg/mL | 0.1 pg/mL | [97] |
SERS | Ag NPs | Pig hair | clenbuterol, ractopamine, salbutamol | - | 20, 20, 30 ng/mL | [98] |
SERS-IA | Au NPs-Ab | Swine urine | Clenbuterol | 0.1–100 pg/mL | 0.1 pg/mL | [99] |
SERS | Au NPs | Pork, pig liver | Ractopamine | 20.0–200.0 μg/L | 3.1 μg/L | [100] |
SERS | Au/Ag NPs | Pig liver | Salbutamol, ractopamine, phenylethanolamine A | 0.002–200 0.001–200 0.005–100 ng/mL | 0.8, 0.4, 1.3 pg/mL | [101] |
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Guo, Q.; Peng, Y.; Qin, J.; Chao, K.; Zhao, X.; Yin, T. Advance in Detection Technique of Lean Meat Powder Residues in Meat Using SERS: A Review. Molecules 2023, 28, 7504. https://doi.org/10.3390/molecules28227504
Guo Q, Peng Y, Qin J, Chao K, Zhao X, Yin T. Advance in Detection Technique of Lean Meat Powder Residues in Meat Using SERS: A Review. Molecules. 2023; 28(22):7504. https://doi.org/10.3390/molecules28227504
Chicago/Turabian StyleGuo, Qinghui, Yankun Peng, Jianwei Qin, Kuanglin Chao, Xinlong Zhao, and Tianzhen Yin. 2023. "Advance in Detection Technique of Lean Meat Powder Residues in Meat Using SERS: A Review" Molecules 28, no. 22: 7504. https://doi.org/10.3390/molecules28227504
APA StyleGuo, Q., Peng, Y., Qin, J., Chao, K., Zhao, X., & Yin, T. (2023). Advance in Detection Technique of Lean Meat Powder Residues in Meat Using SERS: A Review. Molecules, 28(22), 7504. https://doi.org/10.3390/molecules28227504