| Literature DB >> 35696145 |
Li Li1, Ming Zhang1, Wei Chen2.
Abstract
Lately, scandals associated with the illegal addition of poisonous chemicals to food for commercial interests have been gradually disclosed to the public. Problems related to food safety do not only harm public health but also affect the stability of economic and social development. Food safety has become a common issue in society, and strengthening the related regulations have become increasingly important. Although conventional techniques are accurate and sensitive in the detection of the vast majority of illegal food additives, they rely on time-consuming, labor-intensive procedures that depend on expensive instruments. Thus, efficient and rapid identification of poisonous, illegal additives in food is a crucial task in analytical chemistry. Recently, in this context, gold nanoparticles (GNPs) have attracted considerable attention because of their optical, electronic, catalytic, and chemical properties. Their excellent properties have facilitated the widespread use of GNPs in different sensors. This review covers the two most common GNP-based sensors with colorimetric and electrochemical responses, which have proven to be effective in the detection of illegal additives. The GNP-based sensors comply with the requirement of modern analysis, such as high selectivity, sensitivity, simplicity, rapidity, and portability. Thus, they have great potential as powerful sensing tools for food safety screening. This review elucidates the utility and advances of GNP-based colorimetric and electrochemical sensors for the detection of illegal additives in the food industry and in the supervision of food quality and safety. Additionally, an outlook of the trends and future development of research on these sensors is provided.Entities:
Year: 2020 PMID: 35696145 PMCID: PMC9261815 DOI: 10.38212/2224-6614.3114
Source DB: PubMed Journal: J Food Drug Anal Impact factor: 6.157
Fig. 1Systematic representation of application of GNP-based colorimetric and electrochemical sensors to detect illegal additives in food.
Fig. 2Systematic representation of application of GNP-based colorimetric and electrochemical sensors to detect illegal additives in food. Evolution of the number of publications concerning the keywords “gold nanoparticles”+“colorimetric sensors”+“additives” and “gold nanoparticles ”+“electrochemical sensors”+“additives” on indexed journals between 2015 and 2019. The insert pie graph exhibits the percentage of the available scientific reports which concerned the GNP-based sensors using colorimetric and electrochemical techniques from 2015 to 2019. The data comes from the research on “web of science”.
Fig. 3GNP-based colorimetric sensors for the detection of melamine and nitrite. (a) Bare GNP-based colorimetric sensors for the detection of melamine. (b) Modified GNP-based colorimetric sensors for the detection of melamine (or nitrite). (c) Sensing principle for melamine analysis during the synthesis of GNPs.
Typical applications of gold nanoparticle-based colorimetric and electrochemical sensors for the detection of illegal food additives.
| Sample source | Adulterant | Biosensors | Nanomaterials | Concentration range | Detection limit | Pretreatment to real samples | Ref. |
|---|---|---|---|---|---|---|---|
| infant formula | melamine | colorimetric | bare GNPs | 5.0 × 10−6 | 2.0 × 10−7 g/L | precipitate proteins by trichloroacetic solution, then collect the supernatant | [ |
| milk | melamine | colorimetric | 1,4-dithiothreitol modified GNPs | 8.0 × 10−8 | 2.4 × 10−8 M | dilute 1000 times with distilled water | [ |
| processed raw milk | melamine | colorimetric | asymmetrically PEGylated GNPs | 1.05 × 10−3 | 1.05 × 10−3 μmol/L | precipitate proteins with 10% trichloroacetic acid and acetonitrile, then sonicate, centrifuge, and filtrate | [ |
| liquid milk | melamine | colorimetric | methanobactin-mediated synthesis of GNPs | 3.90 × 10−7 | 2.38 × 10−7 mol/L | precipitate proteins with 10% trichloroacetic acid, then shake, centrifuge, and filtrate | [ |
| food contact materials (plate or fruit tray) | melamine | electrochemical | GNPs/RGO/GCE | 5–50 nmol/L | 1.0 nmol/L | immerse in food simulants (water or 3% acetic acid) then heat and filtrate | [ |
| ketchup and chilly sauce | Sudan I | electrochemical | GNPs/GCE | 4.0 × 10−5 | 1.0 × 10−8 mol/L | ultrasonic extraction with ethanol and filtrate | [ |
| chili and ketchup sauce | Sudan II | electrochemical | treated pencilgraphite electrode with DNA, o-phenylenediamine, and GNP bioimprinted polymer | 1.0–20.0; 20.0 | 0.3 nmol/L | ultrasonic extraction with ethanol and filtrate | [ |
| chilli powder and ketchup sauce | Sudan I | electrochemical | GNPs/RGO/GCE | 0.01–70 μmol/L | 1 nmol/L | ultrasonic extraction with ethanol and filtrate | [ |
| chopped red chili, tomato sauce; the apple juice and grape juice | Sudan I | electrochemical | ILRGO@GNPs/GCE | 1.0 × 10−10 | 5.0 × 10−11 mol/L | for chopped red chili and tomato sauce, ultrasonic extraction with ethanol and filtrate; for the apple juice and grape juice, use directly without pretreatment | [ |
| beef | ractopamine | colorimetric | Apt–GNPs | 0–400 ng/mL | 10 ng/g | homogenize with acetate ammonium buffer (pH = 5.2), then enzymatically digest, centrifuge and filtrate | [ |
| pork | clenbuterol | electrochemical | MoS2–Au-PEI-hemin/GCE | 0.01–2 μg/mL | 0.00192 μg/mL | homogenize with 0.1 M HClO4 solution, then sonicate and centrifuge | [ |
| meat products including ham sausage and red-braised pork | nitrite | colorimetric/fluorescent/SERS triple sensing | GNRs-Azo-GNPs | 0.5–100 μmol/L | 0.05 μmol/L | cut into 1 cm disk and 2 × 2 cm square piece | [ |
| sausages | nitrite | colorimetric | Janus PEGylated GNP probe | 10.8–174 μmol/L | 10.8 μmol/L | shred, then dissolve with a saturated boric acid solution | [ |
| packaged drinking water, processed meats and aquatic products | nitrite | electrochemical | ERGO/GNPs/SPCE | 1–6000 μmol/L | 0.13 μmol/L | homogenize, then ultrasonication, heat, cool to room temperature, filtrate, centrifuge and filtrate again | [ |
| sausage | nitrite | electrochemical | GNP/p-ATP-modified gold electrode | 0.5–50 mg/L | 2.6 μmol/L | shred, add saturated borax solution, heat, precipitate proteins with 30% ZnSO4 solution, centrifuge and filtrate | [ |
| pickled radish | nitrite | electrochemical | GNPs/GO-SH nanocomposites | 5–1000 μmol/L | 0.25 μmol/L | flush with ultrapure water, then squeeze into juice, ultrasonic treatment, heat and filtrate | [ |
| milk | urea | colorimetric | GNPs–aptamer | 20–150 mmol/L | 20 mmol/L | precipitate proteins with methanol, vortex and centrifuge | [ |
| milk | anionic detergents | colorimetric | bare GNPs | 92–900 μg/mL | 92 μg/mL | precipitate proteins using ice-cold methanol supplemented with NaCl, then vortex and centrifuge | [ |
| fish | formalin | electrochemical | FDH/GNPs/[EMIM][Otf]/CHIT/GCE | 0.01–10 ppm | 0.1 ppm | thawed, then select the flesh to cut into small pieces, homogenize with Tris–HCl (pH 7, 0.5 M) and filtrate | [ |
Fig. 4Schematic representation of aptamer–GNPs based methods for the detection of RAC and urea. (a) Without RAC (or urea). (b) With RAC (or urea).
Fig. 5Sensing principle for ADs analysis based on anti-aggregation of GNPs.