Method for detecting deoxynivalenol based on surface enhanced infrared spectroscopy

Abstract

The invention relates to the field of food detection, and discloses a method for detecting deoxynivalenol based on surface enhanced infrared spectroscopy. The method comprises the following steps: (1) dropwise adding a sample to be detected or an extract of the sample to be detected onto a silver nanoparticle-zinc selenide substrate, and collecting an SEIRAS spectrogram; and (2) comparing the SEIRAS spectrogram collected in the step (1) with the characteristic peak of deoxynivalenol, and determining whether the sample to be detected contains deoxynivalenol or not. The method provided by the invention can be used for detecting trace DON in food, and achieves the effects of rapidness, sensitivity and accuracy; compared with the prior art, the method has the advantages that pretreatment and chemical reagent treatment are hardly needed, the detection limit of DON in the flour can reach 0.75 ppm, the detection cost is greatly reduced, the purpose of field detection can be achieved, and the method has a good application prospect.

Description

Technical Field

[0001] The present invention relates to the field of food detection, and specifically to a method for detecting deoxynivalenol based on surface-enhanced infrared spectroscopy. Background Art

[0002] Deoxynivalenol (DON) is a secondary metabolite of Fusarium graminearum and Fusarium culmorum, and is a vomitoxin. When animals and humans ingest contaminated food, exposure to DON is extremely harmful, and can cause acute and chronic effects such as vomiting, anorexia, weight loss, skin irritation, bleeding, diarrhea, gastroenteritis, neurotoxicity, embryotoxicity, teratogenicity and immunosuppression. Therefore, due to its numerous toxic effects, food contamination by DON is a thorny problem for consumers in every country.

[0003] As the main processed product of wheat, wheat flour is one of the most important staple foods in the world and accounts for a large proportion in people's diet. However, there are more and more cases of wheat contaminated by DON. In order to reduce exposure to DON from food, the European Union has set a maximum limit for DON concentration, which is 0.75 mg / kg for cereal products and 1.25 mg / kg for cereals. The maximum limit specified in China is the same. The US Food and Drug Administration (FDA) allows a maximum of 1.00 mg / kg of DON in finished wheat flour products for human consumption.

[0004] The detection technology of DON requires high selectivity and sensitivity. At present, there are various detection methods for DON and other mycotoxins in food. Existing technologies for detecting DON mainly include thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), etc. Although these technologies have high selectivity and sensitivity and have achieved good detection results for the analysis of mycotoxins in food samples,

[0005] However, most of these methods require complex sample pretreatment and long detection time, and also require skilled manpower, which has become a bottleneck in their practical applications. There are also immunoassay methods such as enzyme-linked immunosorbent assay (ELISA) and colloidal gold immunochromatography (GICA) that can detect DON. Although these methods can achieve rapid on-site detection, false positives are likely to occur during the detection process, which greatly limits the detection applications of these methods.

[0006] Infrared spectroscopy has the advantages of non-destructive and rapid detection, no need for complex pretreatment, and saving manpower and material resources. It can provide more effective information for the detection of DON. However, the content of DON in general cereal products such as wheat or flour is very trace, the infrared spectral absorption intensity is not high, and the detection sensitivity cannot meet the detection requirements.

[0007] Therefore, there is an urgent need to develop a new, efficient, rapid, accurate and convenient method for the accurate and rapid detection of DON in foods such as wheat or flour to ensure the food safety of the people. Summary of the Invention

[0008] The present invention aims to provide a method for the rapid detection of deoxynivalenol (DON), which can be used for the detection of DON in foods; the foods include grains and their products, especially wheat flour and its products.

[0009] The solution of the present invention is as follows:

[0010] A method for detecting deoxynivalenol based on surface-enhanced infrared absorption spectroscopy (SEIRAS) includes the following steps:

[0011] (1) A sample to be tested or an extract of the sample to be tested is dropped onto a silver nanoparticle-zinc selenide substrate, and an SEIRAS spectrum is collected;

[0012] (2) The SEIRAS spectrum collected in step (1) is compared with the characteristic peaks of deoxynivalenol.

[0013] The sample to be tested is a food, including grains and their products. In an example of the present invention, it is flour.

[0014] The preparation method of the extract of the sample to be tested is as follows: the sample to be tested is dispersed in water, centrifuged to obtain the supernatant, or the supernatant is dried and then redissolved in water.

[0015] The SEIRAS spectrum collected in step (1) is pretreated. The pretreatment includes baseline correction, smoothing and normalization.

[0016] The preparation method of the silver nanoparticle-zinc selenide substrate is as follows: the pretreated and cleaned zinc selenide window is placed in a silver nanoparticle solution for 0.5-2 h and then dried.

[0017] The particle size of the silver nanoparticles is 20-150 nm, preferably 50-150 nm, more preferably 55-120 nm.

[0018] The silver nanoparticle solution is prepared by the following method: sodium citrate is added to a boiling silver nitrate solution, stirred and continuously heated for 5-40 min, preferably 15-20 min.

[0019] The mass ratio of silver nitrate to trisodium citrate is 1:3 - 8, preferably 1:4 - 6.

[0020] The content of silver nitrate in the reaction system is 0.1 - 0.3 mg / mL, preferably 0.15 - 0.2 mg / mL.

[0021] The silver nanoparticle - zinc selenide substrate can be used for detecting deoxynivalenol.

[0022] For the said silver nanoparticle - zinc selenide substrate, the particle size of the silver nanoparticles is 20 - 150 nm. Preferably, the particle size of the silver nanoparticles is 50 - 120 nm, and more preferably 55 - 120 nm.

[0023] The present invention uses surface - enhanced infrared absorption spectroscopy (SEIRAS) for detection. By plating silver nanoparticles on the surface of the substrate and utilizing the surface plasmon resonance effect of the silver nanoparticles, the absorption of infrared light by the detected molecules is increased, which can greatly enhance the signal intensity of the infrared spectrum detection. The highest enhancement factor of the SEIRAS substrate can reach 1000. Compared with the ordinary infrared spectrum detection method, the signal can be enhanced by 20 times, improving the sensitivity; the detection limit of DON in flour can reach 0.75 ppm, which is lower than the current specified limit standard.

[0024] The beneficial effects of the present invention are as follows:

[0025] 1. The method of the present invention can be used for detecting trace DON in food, and achieves the effects of non - destructive, fast, sensitive and accurate detection; almost no pretreatment and chemical reagent treatment are required, which not only greatly reduces the detection cost, but also can achieve the purpose of on - site detection;

[0026] 2. This method utilizes the surface plasmon resonance field - enhancement characteristic of silver nanoparticles to enhance the infrared signal. Its detection limit reaches the ppb level, which is much lower than that of ordinary infrared spectra, and at the same time can greatly improve the signal - to - noise ratio of detection; in terms of the integrity of the peaks and the discrimination of the peak groups, this method is superior to infrared spectrum detection, making up for the disadvantages of low infrared absorption intensity and insufficient detection sensitivity of infrared spectra;

[0027] 3. The silver nanoparticle - zinc selenide substrate prepared by the present invention has good infrared signal enhancement performance and high substrate stability. The citrate - capped silver nanoparticles are synthesized by a one - step chemical reduction method, and the substrate preparation method is economical and simple;

[0028] 4. The detection method of the present invention is applicable to food, especially grains and their products, such as flour and flour products, and has broad application value and application prospects in the rapid detection of bulk grains and facilitating the rapid customs clearance of imported grain crops. Description of the Drawings

[0029] Figure 1 UV-Vis spectrum of silver nanoparticles in Example 1;

[0030] Figure 2 Particle size (A) and Zeta potential (B) of silver nanoparticles in Example 1;

[0031] Figure 3 SEM images of silver nanoparticle-ZnSe substrates prepared under different conditions;

[0032] Figure 4 Standard infrared spectrum of DON;

[0033] Figure 5 Comparison of SEIRAS spectrum (A) with standard infrared spectrum of DON (B) and blank control;

[0034] Figure 6 Normal infrared detection spectra of samples with different concentration gradients, blank control and DON standard sample;

[0035] Figure 7 Comparison of SEIRAS one-dimensional spectrum of 5 ppm DON flour with normal infrared one-dimensional spectrum (IR) of 50 ppm DON flour;

[0036] Figure 8 SEIRAS surface-enhanced infrared spectral detection effect of substrates with different substrate compositions for DON;

[0037] Figure 9 SEIRAS surface-enhanced infrared spectral detection effect of silver nanoparticles-ZnSe substrates with different particle sizes for DON. Detailed implementation manners

[0038] Preparation and characterization of silver nanoparticles in Example 1

[0039] Take 45 mg of silver nitrate and add it to a beaker containing 250 mL of ultrapure water, and continuously stir magnetically at 100 °C; after heating until the solution boils for 5 - 10 min, add 5 mL of 5% trisodium citrate solution, stir rapidly, and continue heating for 15 min to obtain a silver nanoparticle solution.

[0040] Extract 10 mL of the silver nanoparticle solution and place it in a centrifuge tube, store it at room temperature for two hours for standby, measure the UV-Vis spectrum, and use a Malvern laser particle size analyzer (Mastersizer) for characterization.

[0041] The UV-Vis spectrum of silver nanoparticles is as Figure 1As shown, the surface plasmon resonance peak of silver nanoparticles can be observed at 425 nm, thus proving the existence of silver nanoparticles. The particle size of the silver nanoparticles measured by Mastersizer and the Zeta potential diagram are as Figure 2 , and the prepared nanoparticles have a uniform particle size and good solution stability.

[0042] Synthesis, Preparation and SEM Characterization of Silver Nanoparticle-Zinc Selenide Substrate in Example 2

[0043] After the zinc selenide window was ultrasonically cleaned in ethanol for 15 min to remove possible impurities, the zinc selenide window was rinsed with water several times and placed in the silver nanoparticle solution prepared in step (1) for 1 h. Then they were taken out and placed in an oven at 100 °C for 10 minutes until the solvent evaporated, leaving a thin layer of silver nanoparticles deposited on the surface of the glass slide. SEM was used to characterize the surface morphology of the prepared silver nanoparticle-zinc selenide substrate. Most of the nanoparticles on the substrate are spherical, with a particle size of about 60 nm; the shapes are uniform and the dispersion is uniform, as Figure 3 .

[0044] Substrates Prepared under Different Conditions in Example 3

[0045] After adding trisodium citrate, the detection results of the Malvern particle size of silver nanoparticles (AgNPs) obtained at different heating times are shown in Table 1, and the ultraviolet-visible light spectrum is as Figure 1 shown, and silver nanoparticles exist in all cases. The SEM comparison diagram of the prepared silver nanoparticle-zinc selenide substrate is as Figure 3 shown.

[0046] Under the condition of a shorter heating time, the morphology of the silver nanoparticles is not uniform and they have not yet formed. For too long a heating time, cubic silver nanoparticles with too large a particle size are formed; the morphology of the silver nanoparticles prepared under the 15-min heating condition is the most uniform, forming spherical silver nanoparticles with a size of about 60 nm. Zeta potential is used to characterize the stability and anti-aggregation properties of nanoparticles.

[0047] Table 1 Detection Results of Malvern Particle Size of AgNPs Prepared at Different Heating Times

[0048] Different heating times for preparing AgNPs Particle size (nm) Zeta potential 8 min 19.35 -33.51 10 min 23 -45.72 15 min 59.386 -48.09 20 min 114.086 -39.47

[0049] Detection of DON in Wheat Flour (Flour) Samples in Example 4

[0050] DON was mixed with flour in proportion, and the concentration range of DON in the experimental group of flour was enhanced to 0.5 ppm, 0.75 ppm, 1 ppm, 2 ppm, 3 ppm, 4 ppm, 5 ppm, 10 ppm.

[0051] Sample Pretreatment: The flour sample to be tested is passed through a 150-mesh sieve. Weigh 5 g of the uniformly mixed flour into a 50-mL centrifuge tube, add 20 mL of ultrapure water respectively, centrifuge at 8000 rpm / min for 10 min, take the supernatant, dry it, and then redissolve it in 50 μL of ultrapure water.

[0052] SEIRAS Detection: The pretreated sample to be tested is dropped onto the substrate prepared in Example 2 for infrared spectrum detection. Using a Fourier transform infrared spectrometer, such as the PerkinElmer Spotlight 400 (PerkinElmer Spotlight 400, Nicolet iS5 Fourier transform infrared spectrometer in the United States), collect the SEIRAS infrared spectrum; adopt the single-point ATR accessory test mode, with a scanning range of 4000 - 650 cm -1 , the scanning signal is accumulated 32 times, and the resolution is ±4 cm -1 .

[0053] EIRAS / FT-IR Spectrum Analysis: The SEIRAS spectrum of the sample to be tested obtained from the detection is pretreated (such as baseline correction, smoothing, normalization), and then compared with the DON standard infrared spectrum (see Figure 4) and the ordinary infrared spectra of SEIRAS samples with different concentration gradients (see Figure 6 ); The characteristic peaks of the DON infrared spectrum are determined (Table 2). The detection limit of DON in flour can reach 0.75 ppm, which is lower than the current specified limit standard.

[0054] As Figure 5 shown, the DON, blank control, and samples with different concentration gradients are compared using ordinary infrared spectrum (A) and SEIRAS (B) respectively. The results show that SEIRAS has higher sensitivity.

[0055] As Figure 6 shown, the overall infrared signal of the ordinary infrared spectrum (with a relatively high detection limit, and the one-dimensional spectrum can only reach 5 ppm) is enhanced by 20 times.

[0056] As Figure 7 shown, the one-dimensional SEIRAS spectrum of flour containing 5 ppm DON is compared with the ordinary infrared one-dimensional spectrum of flour containing 50 ppm DON. The sensitivity of the SEIRAS detection method is higher.

[0057] Table 2

[0058] Peak position Group and vibration mode Absorption intensity 1685-1682 Ester C=O stretching vibration, conjugated stretching vibration Strong 1068 <![CDATA[v s (RCH-OH)]]> Medium 1031 <![CDATA[v s ((O)C-O)]]> Medium 1047-1043 <![CDATA[V(-CH2OH)]]> Strong 951,971 Epoxy ring stretching Medium

[0059] Using different substrates, according to the method of Example 2, prepare a substrate with the silver nanoparticles obtained in Example 1, and use infrared spectrum to detect DON (10 ppm) in flour.

[0060] The effects of detecting DON by surface-enhanced infrared spectroscopy on substrates prepared by combining silver nanoparticles with different substrates such as zinc selenide windows, aluminum, and glass are as follows Figure 8 . The results show that the combined detection spectrum of silver nanoparticles - zinc selenide window has the highest similarity with the DON standard spectrum. Among them, the absorption intensities of the infrared characteristic absorption peaks of DON such as 1685 cm -1 , 1027 cm -1 , and 951 cm -1 have the best enhancement effect compared with the detection of other combinations.

[0061] The effects of surface-enhanced infrared spectroscopy detection method using silver nanoparticles with different particle sizes and zinc selenide windows on the detection of DON are as follows Figure 9 . The results show that when the DON content is 10 ppm, the IR detection method only shows peaks at 951 cm -1 and 971 cm -1 , and no peak appears at 1695 cm -1 , which is not sufficient to detect DON. When silver nanoparticles - zinc selenide with a particle size of about 59 - 60 nm is used as the substrate, the detection effect and sensitivity are the highest. When silver nanoparticles - zinc selenide with a particle size of about 114 - 115 nm is used as the substrate, the detection effect is close to it. Therefore, when using silver nanoparticles - zinc selenide with a particle size of 55 - 120 nm as the substrate, compared with the silver nanoparticles - zinc selenide substrate with a particle size of 15 - 25 nm and the infrared spectroscopy detection method of the existing technology, the sensitivity, accuracy, and detection effect are better.

Claims

1. A method for detecting deoxynivalenol based on surface enhanced infrared spectroscopy, characterized in that: The steps include: (1) The sample to be tested or the extract of the sample to be tested is dripped onto the silver nanoparticle-zinc selenide substrate, and a SEIRAS spectrum is collected; (2) Compare the SEIRAS spectrum collected in step (1) with the characteristic peak of deoxynivalenol to determine whether the sample to be tested contains deoxynivalenol.

2. The method according to claim 1, characterized in that The method comprises the following steps: the preparation method of the silver nanoparticle-zinc selenide substrate is as follows: placing the pre-treated and cleaned zinc selenide window in a silver nanoparticle solution for 0.5-2 hours and drying.

3. The method according to claim 1 or 2, characterized in that: The particle size of the silver nanoparticles is 20-150nm.

4. The method according to claim 1 or 2, characterized in that: The particle size of the silver nanoparticles is 55-120nm.

5. The method according to claim 2, characterized in that: The silver nanoparticle solution is prepared by the following method: Add trisodium citrate to the boiling silver nitrate solution, stir and continue heating for 15-20 minutes.

6. The method according to claim 5, characterized in that The content of silver nitrate in the reaction system is 0.1-0.3 mg / mL, and the mass ratio of silver nitrate to trisodium citrate is 1:3-8.

7. The method according to claim 6, characterized in that The mass ratio of silver nitrate to trisodium citrate is 1:4-6.

8. Application of silver nanoparticle-zinc selenide substrate in the detection of deoxynivalenol.

9. The use according to claim 8, characterized in that: The silver nanoparticle-zinc selenide substrate has a particle size of 20-150 nm.

10. The use according to claim 9, characterized in that: The particle size of the silver nanoparticles is 50-120 nm.

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