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Article
Gold Nanorods as Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Rapid and Sensitive Analysis of Allura Red and Sunset Yellow in Beverages Yiming Ou, Xiaohui Wang, Keqiang Lai, Yiqun Huang, Barbara Rasco, and Yuxia Fan J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b00007 • Publication Date (Web): 28 Feb 2018 Downloaded from http://pubs.acs.org on March 2, 2018
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Journal of Agricultural and Food Chemistry
Gold Nanorods as Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Rapid and Sensitive Analysis of Allura Red and Sunset Yellow in Beverages Yiming Oua†, Xiaohui Wang a†, Keqiang Laia,b, Yiqun Huangc, , Barbara A Rascod, Yuxia Fana,b* a
College of Food Science and Technology, Shanghai Ocean University, No. 999 Hucheng Huan Road, LinGang New City, Shanghai, China 201306.
b
Engineering Research Center of Food Thermal Processing Technology, Shanghai Ocean University, No. 999 Hucheng Huan Road, LinGang New City, Shanghai 201306, China
c
School School of Chemistry & Biological Engineering, Changsha University of
Science & Technology, Changsha, Hunan 410076, China d
School of Food Science, Washington State University, Pullman, WA 99165, USA.
*Corresponding author: Telephone, (86-21)6190-0370; Fax, (86-21)6190-0365; E-mail, yxfan@ shou.edu.cn. †
These authors contributed equally to this work.
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Abstract
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Synthetic colorants in food can make a potential threat to the human health. In
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this study, surface-enhanced Raman spectroscopy (SERS) coupled with gold nanorods
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as substrates is proposed to analyze allura red and sunset yellow in beverages. The
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gold nanorods with different aspect ratios were synthesized and its long-term stability,
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SERS activity, and the effect of the different salts on SERS signal were investigated.
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The results demonstrate that gold nanorods have a satisfactory stability (stored up to 28
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days). SERS coupled with gold nanorods exhibit stronger sensitivity. MgSO4 was chosen to
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improve the SERS signal of sunset yellow and no salts could enhance the SERS signal
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of allura red. The lowest concentration was 0.10 mg/L for both colorant standard
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solutions. The successful prediction results using SERS were much closer to those
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obtained by HPLC for sample in beverages. SERS combined with gold nanorods
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shows potential for analyzing food colorants and other food additives as a rapid,
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convenient, and sensitive method.
15 16
Key words: surface-enhanced Raman spectroscopy; gold nanorods; beverages; colorant; rapid analysis
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Introduction
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Food colorants are essential to the food manufacturing industry, because they
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affect the product color and thus the acceptability of the final products. They are
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grouped into synthetic, natural, nature identical and caramel colors 1. Natural
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colorants usually come from animal or plants tissues, they are safe to humans but are
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more susceptible to fading and less stable to light and other chemicals. In
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comparison, synthetic colorants are most widely used because they are brighter,
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more stable, and more cost-efficient, however, some of them, such as azo-dyes,
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present a potential risk to human health, especially for children in the case of
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excessive consumption. Sunset yellow, known in the United States as FD&C Yellow
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No. 6 (Acceptable daily intake (ADI): 2.5 mg/kg bw) and allura red, known in the
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United States as FD&C Red No. 40 (ADI: 7 mg/kg bw), have been widely used as
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food and beverage additives 2. They have been studied to be associated with
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increased hyperactivity in children ages 8 – 9 and genotoxicity in murine models
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with memory and learning deficits of the offspring 3. The permissible concentrations
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of both colorants are from 20 – 500 mg/kg in China (GB/2760-2014) 4 or 25 – 400
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mg/kg by Codex Alimentarius Commission (CAC) depending on the type of food 5.
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High-performance
liquid
chromatography
(HPLC)
6-7
,
Liquid
8-9
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chromatography-mass spectrometry (LC-MS)
, column solid-phase extraction
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combined with UV–Vis spectrophotometry
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used to determine the colorants in food. However, they have many disadvantages,
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, and an electric method
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have been
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such as labor-intensive, time-consuming expensive, poor repeatability and accuracy,
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or complicated sample pretreatment 12-13.
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Surface-enhanced Raman spectroscopy (SERS), which enhances the Raman
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signals by molecules adsorbed on rough metallic nanostructured surface based on
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electromagnetic and chemical theory
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as 1010 to 1011 or higher 17-18. Rapid development of SERS has been achieved during
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the last five years as evidenced by the explosive development of nanoscience and
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nanotechnology. However, whether SERS can achieve a much broader application
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depends greatly on the sensitivity of SERS and the reproducibility of the substrate 19.
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SERS, a potential detection technique, has been applied as an attractive alternative
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method to analyze biological and chemical target compounds due to its high
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sensitivity and specificity 20-22.
14-16
. The enhancement factor can be as much
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Gold nanorods, which have anisotropic optical properties, have recently
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attracted a lot of attention due to their distinctive optical properties and long-term
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stability at room temperature
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plasmon bands, they are very sensitive to the aspect ratio (AR) of nanorods, and
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have been explored to increase the contribution of electromagnetic enhancement
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mechanisms at a desired wavelength
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with ARs of 2.4, 5.8, and 16, and then used crystal violet as the probe to investigate
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their SERS activity. Au-Ag nanorods were synthesized and proved to possess SERS
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activity using sodium salicylate as an adsorbate probe
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factors that affect the reproducibility of Au NRs and the long term and the short-term
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. Gold nanorods show longitudinal and transverse
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. Smitha et al.
25
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synthesized Au nanorods
. John et al.
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studied the
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stability of Au NRs in various conditions with UV-Vis spectroscopy. Under the
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optimum conditions, the Au NR samples were stable for at least nine months.
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Nguyen et al. 28 used gold nanorods and graphene as key materials to fabricate SERS
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substrates for the detection standard solution system of pesticides. Alsammarraie et
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al.29 and Zhang et al.
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substrates for detection pesticides in fruit juice and milk. However, few studies have
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been published that use Au nanorods to determine these two colorants at a series of
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concentrations or in food samples. Reports of the Au nanorods stability characterized
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by the SERS intensity of the probe molecule were also limited.
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reported using standing gold nanorod arrays as SERS
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The main purpose of this work was to develop a sensitive, rapid and convenient
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SERS method coupled with gold nanorods for detection and determination of allura
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red and sunset yellow in beverages. Au nanorods with different ARs as the substrates
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were prepared, and its SERS activity, long-term stability, and the effect of the
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different salts on SERS signal were investigated. Allura red and sunset yellow
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standard solution and actual beverage samples can be detected directly or after
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simply dilution, filtration. Partial least squares (PLS) models and the linear
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relationship of SERS intensity of some characteristic peaks with the actual
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concentrations were developed for quantitative analyses of allura red and sunset
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yellow in standard solution and beverage samples.
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2. Materials and methods
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2.1 Preparation and characterization of gold nanorods
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2.1.1 Seed preparation Gold nanorods with different ARs were synthesized via a seed-mediated 24
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surfactant-directed approach described by Murphy
. In a typical procedure,
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spherical gold seed with diameter of 3.5 – 4 nm were prepared by reducing 2.5 × 10-4
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M chloroauric acid in 10 mL, 0.1 M CTAB (Hexadecyl trimethyl ammonium
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Bromide, 99%, J&K) with 600 µL ice-cold 0.01 M NaBH4 (99%, Aldrich). After the
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addition of this strong reducing agent, the color of the gold seed solution turned
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brown, and the solution was stirred vigorously for 10 min before being transferred to
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the incubator at 25°C for 2.5 h of aging.
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2.1.2 Growth of the gold nanorods
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For the synthesis of the nanorods, the as-prepared gold seed (12 µL) was added
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to the growth solution containing CTAB (9.5 mL, 0.1 M), AgNO3 (20, 50 or 80 µL,
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0.01 M), HAuCl4 (0.5 mL, 0.01 M), and ascorbic acid (55 µL, 0.1 M) under stirring.
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The CTAB acted as a soft bilayer template for the nanorods growth with the aid of
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AgNO3, then ascorbic acid as a mild reducing agent made it possible for the Au3+ to
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be reduced to Au+; finally, the gold seed initiated the reaction of Au+ to Au0
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mixture was left undisturbed overnight (14 – 16 h) at 27 °C, during which the
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colorless solution turned blue, green, or brown depending on the amount of the
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AgNO3 added.
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22
. The
2.1.3 Au nanorod characterization
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UV-Vis absorbance spectroscopy (UV3000PC, MAPADA Instruments Ltd.,
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Shanghai, China) was applied to analyze the optical properties of the Au nanorods
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with different ARs. Transmission electron microscopy (TEM, JEM-2100F, JEOL
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Ltd., Tokyo, Japan) was used to analyze particle size (statistic results from average
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diameter of 100 particles) and surface morphology.
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2.2 Preparation of the standard solution
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Sudan IV (≥96%, Sigma-Aldrich) was dissolved in a mixture of water and
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acetonitrile (1:1, v/v) (HPLC reagent; Sigma-Aldrich) to prepare a series of standard
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solutions ranging from 0.08 – 5.00 mg/L. Allura red yellow (≥96%, Sigma-Aldrich)
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or sunset yellow (≥96%, Sigma-Aldrich) were dissolved in the deionized water to
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prepare a series of standard solutions ranging from 0.1 – 10.00 mg/L.
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2.3 Beverage sample preparation and HPLC detection
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Thirteen types of beverages were purchased from a local supermarket in
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Shanghai. For allura red, five beverages (cocktail with peach flavor, energy drink,
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pulpy strawberry juice, cranberry juice, and cranberry wine) contained the colorant.
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The no-colored cocktail with mixed fruit flavor, red-colored vitamin water and grape
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fruit juice were chosen as the controls. For sunset yellow, five beverages (orange
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sprite, apple vinegar, pulp mango juice, pulp orange juice, orange vodka) contained
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the colorant and the non-colored cocktail with mixed fruit flavor was chosen as the
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control. Transparent samples could directly be analyzed by SERS and those pulpy
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beverages should be passed through a 0.22 µm polytetrafluoroethylene (PTFE)
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microporous film (SCAA-114) before the SERS measurement. Dilution is necessary
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if the matrix interfered with the target signal to some extent. HPLC detection was
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referenced to the regulation released by the China entry-exit inspection and
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quarantine 31.
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2.4 Spectral measurement
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A Nicolet DXR microscopy Raman spectrometer (Thermo Fisher Scientific Inc.
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Waltham, MA) with a He-Ne 633 nm laser source was used to collect SERS spectra
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(400 – 2000 cm-1; resolution 4.7 cm-1) of Sudan IV, allura red, and sunset yellow.
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The laser power used for collection was 5 mW. The accumulation of five scans with
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two seconds for each scan was applied.
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To obtain the SERS spectra, as-prepared Au nanorods were firstly centrifuged
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for 10 min at 12000 rpm for twice to remove redundant CTAB and redispersed in
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deionized water. Then, the nanorods were mixed with the standard solution of the
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colorants or beverages sample in the ratio of 1:1 for Sudan IV and sunset yellow, 1:2
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for allura red. The mixture was vortexed for six seconds to ensure of full interaction
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of the colorants with the Au nanorods surface. Finally, 5 µL of the mixture was
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placed onto a microscope glass slide and dried at 50°C to evaporate the solvent. For
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the study of the influence of the salts on the SERS intensity, sulfate salts Al2(SO4)3,
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K2SO4, MgSO4 and the chlorine salts CaCl2 and MgCl2 were added immediately
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after the colorant was added in the Au nanorods in the ratio of 10:10:1 (substrate:
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colorant: salts). To make sure of representative measurement, 40 spectra from
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random points of four baths (10 for each one) of substrates were recorded and
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averaged.
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2.5 Data analysis
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OMINIC software (Thermo Nicolet Corp., Madison, WI, USA) was used for
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spectral acquisition. Delight 3.2.1 (Dsquared Development Inc., LaGrande, OR,
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USA) was then used for quantitative analysis of the data. Four batches of substrate
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were used to respectively collect ten spectra at random locations, and then the ten
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spectra were averaged as one spectrum, that is, four averaged spectra for each
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concentration (0.1 – 10.0 mg/L) were used to build the partial least squares (PLS)
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model or to determine whether there were linear relationships between Raman
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intensities of characteristic peaks and colorant concentrations of the standard
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solutions or the beverage samples. PLS regression was employed to established
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linear regression models between the spectra data and the actual concentration of the
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allura red and sunset yellow in standard solutions or in the beverage samples. The
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predictability of the model can be evaluated by the coefficient of determination (R2),
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the root mean square errors (RMSE), and the ratio of performance to deviation (RPD)
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of leave-one-out cross-validation.
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3. Results and discussion
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3.1 Characterization and stability of Au nanorods
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Fig. 1 shows the UV-Vis spectra of the three gold nanorods, they all have two
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plasmon bands, transverse plasmon band around 520 nm and longitudinal plasmon
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bands red shifted from 624 nm to 715 nm with the amount of AgNO3 increasing
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from 20 μL to 80 μL. This shape and position of the plasmon bands has a
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relationship with the shape and size of the nanoparticles. The position of the
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longitudinal plasmon band red-shifts, and the transverse plasmon band position stay
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relatively constant at approximately 520 nm as the aspect ratio of the nanorods
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increases 24. The results showed the nanorods grew longitudinally as the amount of
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AgNO3 increased.
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The TEM images in Fig. 2 further confirmed this result, and all the nanorods
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were uniformly distributed except for very few nanospheres. The AR of the nanorods
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increased from 1.8 (40.1 ± 3.8 nm by 21.8 ± 2.1 nm), 2.4 (41.3 ± 2.6 nm by 17.5 ±
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1.6 nm) to 3.5 (46.2 ± 2.9 nm by 13.1 ± 1.1 nm) with increased amounts of AgNO3.
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This is probably due to the silver under potential deposition mechanism. The silver
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deposition rate on crystallographic facets varied; the facets which have faster silver
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deposition followed by strong CTAB binding and thus slower gold growth lead to
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preferential growth of gold at the ends 32.
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The stability of the nanorods with AR 1.8 was investigated. Fig. 1 shows that
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when the Au nanorods remained in the growth solution for seven days, both the
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absorption peak position and intensity changed significantly over times. The
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longitudinal plasmon band in UV-Vis spectra would blue-shift, only transverse
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plasmon remained and the intensity increased after seven days of storage if no
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treatment was performed after the synthesis. The reason for this change is that the
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nanorods continued to grow at a much lower rate because quantities of unreacted
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Au3+ and Ag+ remained in the solution. Therefore, for long-term stability, twice
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centrifugation was necessary to remove the subsequent nanorod growth. The
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nanorods could be kept as long as 28 days after the twice centrifugation at
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approximately 25°C. For the UV-Vis spectra recorded (Fig.1), there was no shift in
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the wavelength at the maximum peak position and no significant change in peak
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intensity.
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3.2 Activity of Au nanorods
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Fig. 3 (a) showed the SERS activity of the Au nanorods with Sudan IV as the
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probe molecule. The lowest concentration detected was 0.1 mg/L, which is slighter
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better than the 0.2 mg/L with Au@Ag nanospheres as the substrate
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characteristic bands at 456, 630, 989, 1099, 1200, 1232, 1386, 1487 and 1598 cm-1
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could be clearly identified. The substrate itself has two major characteristic bands at
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759 cm-1 and 1448 cm-1, which did not interfere with the signal of the Sudan IV
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molecule. Meanwhile, the stability of the SERS activity for the Au nanorods with
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AR 1.8 was investigated. Sudan IV was detected at 1 and 0.1 mg/L. SERS intensity
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of peaks at 1099 cm-1 for Sudan IV and 1448 cm-1 for the substrate was recorded to
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evaluate the sensitivity and stability change of the substrates as Fig. 3 (b) shows. Not
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much variation was found within the peak intensity of the probe molecule or the
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substrate. This is owing to the surfactant CTAB double layers around the gold
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nanorods, which keep it monodispersed and steady in the solution. The concentration
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of CTAB should not be too low in case of slight aggregation of Au NRs with less
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repulsive force and not too high in avoid of more susceptibility to crystallization
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when the room temperature dropped 23, 27.
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3.3 Optimal conditions for SERS detection of allura red and sunset yellow
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. All of the
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Fig. 4 (a) shows some representative SERS spectra of allura red at 10, 5 and 1
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mg/L with Au nanorods in AR 1.8, 2.4 and 3.5. At the concentration of 10 mg/L,
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there is no significant difference for the three gold nanorods, while as the
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concentration decreased, gold nanorods of AR 2.4 show an advantage. Then, the
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influence of sulfate salts Al2(SO4)3, K2SO4, MgSO4 and the chlorine salts CaCl2 and
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MgCl2 on the SERS intensity are investigated with gold nanorods of AR 2.4 at the
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allura red concentration of 5 mg/L. The result showed that when chlorine salts are
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added, the signal of the allura red (Fig. 4 (b)) disappeared, and with the sulfate salts,
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the colorants signal intensity remained the same or decreased compared with those to
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which no salts were added.
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Fig. 4 (c) shows that the intensity of 10 mg/L sunset yellow was no more than
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1000 A.U, while the enhanced effect of Au nanorods (AR 1.8) was slight higher than
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the other two. Then, the above salts were also added to the Au nanorods of AR 1.8 to
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investigate whether the salts could improve or inhibit the SERS signal of sunset
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yellow. The results indicate that all the sulfate salts could improve the SERS signal
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in varying degrees and MgSO4 demonstrated the best results followed by Al2(SO4)3,
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K2SO4. The SERS intensity of sunset yellow with MgSO4 added into the
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colorant-substrate mixture was almost 10 times higher than that of without MgSO4.
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But the signal of sunset yellow disappeared with chlorine salts added. So MgSO4
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was chosen to improve the SERS signal of sunset yellow.
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The CTAB bilayer on the gold nanorods could interact with the analyte,
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allowing the analyte to enter the enhanced region of the gold nanorods surface.
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Through the hydrophobic interaction between the analyte and CTAB, the analyte
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could enter the hot spot region of one gold nanorod, the parallel superposition of two
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gold nanorods, or the end-to-end of two gold nanorods, or between the gold
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nanorods
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solution of metal colloid, ‘salt-induced aggregation’, is a common method to achieve
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aggregation and provide more ‘hot spots’. In this study, the different salts could
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improve or inhibit the SERS signal for the different colorants, which was related to
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the probable mechanism of interaction between the substrate and the analyte.
23, 34-35
, as schematically depicted in Fig. 5. The addition of salt to a
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Base on the mechanism of interaction between the substrate and the analyte,
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two different results could occur because of the salt added. One is that the colorants
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could disrupt part of the CTAB bilayer around the Au nanorods to get improved
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accessibility to the metal surface and thus obtain a desirable SERS signal 34, such as
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allura red molecule, which has strong affinity with gold nanorods through the azo
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group (C–N=N–C), thus resulting in an excellent SERS response on gold nanorods 36.
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On this condition, some types of salts added could cause gold nanorods colloidal
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aggregation, which might break the balance of allura red and gold nanorod soltuion,
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and also change the interaction of allura red with the metal surface. Thus, SERS
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signal could not improve or could get worse. By contrary, sunset yellow had limited
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ability to penetrate into or disturb the CTAB bilayer, which reduced sunset yellow
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molecules adsorbed on the metal surface from the CTAB bilayer. The choice of salts
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as aggregation-inducing agent
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appropriate way for SERS hot spots generation and prevented deactivation of local
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field enhancement. This function depends on the type of salts, amount of salts and
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the properties of the analyte molecule. From our results, sulfate salts are better than
37-39
could assist their interaction in a more
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chlorine salts, and the intensity varied depending on the metal cations of the salts.
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This indicates that it is the cations and the anions that play important roles in the
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SERS enhancement.
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3.4. Analysis standard solution of allura red and sunset yellow
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The allura red molecule contains different functional groups, such as N=N,
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naphthalene ring structure, SO3, and CH3, which have different vibration
262
characteristics. The most prominent peaks of allura red appeared at 1580 cm-1 and
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1495 cm-1 due to C-C stretching vibration and C=C stretching in the benzene ring.
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The other major characteristic peaks are attributed to the deformation vibration of
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N=N (1405 cm-1), the C-O plane stretching vibration of C-O on the naphthalene ring
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and benzene ring (1267 cm-1), the SO2 symmetrical stretching vibration (1219 cm-1),
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the benzene ring symmetrical breathing vibrations and stretching vibration of C-H
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(753 cm-1), and the rocking vibration of C-H (489 cm-1)
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substrate of AR 2.4, the SERS spectra of allura red standard solution at a series of
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concentrations are shown in Fig. 6 (a).
40
. With the optimal
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Sunset yellow possesses characteristic spectra at 1592 cm-1 (CC stretching
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vibration), 1497 cm-1 (C-H and N-H in plane bending), 1386 cm-1 (–OH and –SO3Na
273
in plane bending), 1224 cm-1 (CC in plane bending and C-N stretching vibration),
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and 1166 cm-1 (N=N stretching vibration)
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proper salts, Fig. 6 (b) shows the SERS spectra of the sunset yellow standard
276
solution at a series of concentrations.
277
41
. With the optimal substrate and the
Based upon the major characteristic bands in SERS spectra of standard
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solutions, allura red and sunset yellow could be visually identified at as low as 0.1
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mg/L. In addition, the intensities of major characteristic peaks of SERS were
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dependent upon the concentration of colorants. A linear relationship was observed
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between amount of colorant and the spectral data within a certain range of
282
concentration. The PLS models were developed for allura red and sunset yellow
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standard solution at the concentration ranging from 0.1 – 5.00 mg/L and 0.1 – 10.00
284
mg/L, respectively (Table 1). The linear correlation between the actual and predicted
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concentrations of allura red (n=32) and sunset yellow (n=36) have obtained with R2
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ranging from 0.925 and 0.982, RMSE from 0.40 and 0.48 mg/L and RPD from 3.6
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and 7.4. The linear relationship between the analyte concentration and the intensity
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of some primary peaks was also established (four independent spectra for each
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concentration). Table 2 shows the results with R2 = 0.948 – 0.987, and RPD = 4.3 –
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9.1. The best relationship was obtained based on the strongest peak for allura red of
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1219 cm-1 and sunset yellow of 1592 cm-1, respectively. This indicated the
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possibility for quantitative analysis of allura red and sunset yellow with SERS in
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food samples.
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3.5. Analysis of allura red and sunset yellow in beverages
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Fig. 7 showed the representative SERS spectra of the colorants added into the
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non-colored cocktail with different concentrations and their comparison with those
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of standard solutions. For the allura red (a-d), the SERS intensity of non-colored
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cocktail with the colorant at 10 or 5 mg/L was almost 10% lower than the
299
corresponding standard solutions. This indicated that the matrix has little influence
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on the detection of the allura red. Thus, no dilution was made for the beverage
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sample containing allura red. For the sunset yellow (e – i), the matrix effect was
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obvious, and the signal for the 10 mg/L sunset yellow added into the no-colored
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cocktail was 70% lower than that of standard solution. If the concentration increased
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to the 20 mg/L, the SERS intensity was still lower because of the saturation effects.
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However, if the colorant at 10 and 5 mg/L were added after the dilution of the
306
beverage by the same amount of water (equal to 20 and 10 mg/L for the original
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beverage), the matrix influence would be decreased and a 1:1 dilution was necessary
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for the beverage sample containing sunset yellow before the analysis.
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Fig. 8 (a) presented the acquired representative spectra for the beverages with or
310
without allura red. All beverages that contained allura red could be detected. Also, no
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color or red-color control (vitamin water and grape fruit juice) did not show
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characteristic peaks of the colorant. The quantitative analysis allura red in actual
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beverages was achieved by the PLS model and best linear regression of standard
314
solution because of minimal matrix effects. Fig. 8 (b) shows that a similar result that
315
could also be obtained for sunset yellow. The samples need to be diluted before
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SERS analysis, so the new PLSR models and linear relationship was established for
317
determination of sunset yellow in beverages. The results exhibited good
318
predictability with R2 of 0.965 and 0.969, RMSE of 0.64 and 0.58 mg/L, and RPD
319
5.3 and 5.7 for PLSR model and linear regression, respectively.
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The actual concentration of colorants in thirteen beverages was determined by
321
HPLC. This SERS prediction results are compared with HPLC in Table 3. Except for
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three beverages (cranberry juice, cranberry wine and orange juice), the other
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predictions were much closer to those obtained by HPLC. T-test was used to evaluate
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the difference between SERS and HPLC prediction. P-values of 0.132 or 0.178 were
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calculated based on HPLC and each SERS prediction group, which was so much
326
higher than 0.05. The t-test results were not statistically significant. However, SERS
327
predictions for cranberry juice, cranberry wine and orange juice are significantly
328
different with HPLC results. For cranberry juice and cranberry wine, the natural
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pigment of raw material appears strong red, and there are pulps in orange juice. The
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matrix concentration or the natural pigment of the raw material could seriously
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interfere with the SERS detection, which might be the primary reason for the three
332
beverages detection inaccurate. Then, different multiple diluents were also studied.
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When the dilution ratio was respectively two times, fifteen times, and ten times for
334
cranberry juice, cranberry wine, and orange juice, the SERS predicted concentration
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(2.88, 24.01, 19.28 mg/L) was close to that obtained by HPLC (3.55, 24.98, 21.12
336
mg/L). The results showed that the sample preparation was dependent on whether
337
the juice was pulpy and the type of the colorant. However, the SERS technique is
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desirable for quantitative analysis of the colorants in beverages and has broad
339
potential application in the field of food safety.
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4. Conclusions
341
In this study, gold nanorods with three different ARs were compared to achieve
342
the strongest enhancement effect for allura red and sunset yellow, and the influence
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of the sulfate and chlorine salts were investigated. Gold nanorods show high
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sensitivity and stability. The AR 2.4 or 1.8 of gold nanorods was selected as the
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optimal substrate for allura red or sunset yellow. MgSO4 was chosen to improve the
346
SERS signal of sunset yellow. Quantitative analyses of allura red and sunset yellow
347
in beverages could be realized by this method with no or little sample preparation,
348
which has a higher prediction accuracy. The whole process was convenient, cost
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efficient and quick. The methodology here could extend to similar studies on other
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limited or prohibited food additives in food and may serve as the basis for further
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investigation of determining ultra-traces of specific species in complex systems.
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Acknowledgement
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This research was supported by the National Natural Science Foundation of
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China (No. 31501558), the Training Program for College Teachers in Shanghai
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(A1-2061-17-000117), and the Agricultural Research Center, Washington State
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University.
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nanoshells-based SERS method for detection of sunset yellow and chrysoidine.
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Figure captions
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Figure 1. UV-Vis spectra of the Gold nanorods synthesized with (a) 20, (b) 50 and (c)
485
80 μL AgNO3.
486
Figure 2. The TEM images of Au nanorods with different aspect ratio: (a) and (b) AR
487
1.8 , (c) and (d) AR 2.4 , (e) and (f) AR 3.5.
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Figure 3. (a)Representative SERS spectra of Sudan IV with Au nanorods of AR 1.8 as
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the substrate; (b) the intensity of 1099 cm-1peak in the SERS spectra of 1 and 0.1
490
mg/L Sudan IV standard solution and the intensity of 1444 cm-1 peak in the SERS
491
spectra for the substrate stored for different days.
492
Figure 4. Representative SERS spectra of (a) 10, 5 and 1 mg/L allura red standard
493
solution with different gold nanorods as the substrate; (b) the influence of salts on the
494
detection of 5 mg/L allura red standard solution; (c) the influence of different gold
495
nanorods and salts on the detection of 10 mg/L sunset yellow standard solution.
496
Figure 5. Probable mechanism of interaction between the substrate and the analyte.
497
Figure 6. Representative SERS spectra of (a) allura red standard solution at a series of
498
concentrations with the optimal Au nanorods; (b) sunset yellow standard solution at a
499
series of concentrations with the optimal Au nanorods and the salts of MgSO4.
500
Figure 7. Representative SERS spectra of (a) allura red standard solution (10 mg/L);
501
(b) allura red in the no-colored cocktail (10 mg/L); (c) allura red standard solution (5
502
mg/L); (d) allura red in the no-colored cocktail (5 mg/L); (e) sunset yellow standard
503
solution (10 mg/L); (f) sunset yellow in the no-colored cocktail (10 mg/L); (g) sunset
504
yellow in the 1:1 diluted no-colored cocktail (5 mg/L); (h) sunset yellow in the
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no-colored cocktail (20 mg/L); (i) sunset yellow in the 1:1 diluted no-colored cocktail
506
(10 mg/L).
507
Figure 8. Representative SERS spectra of (a) allura red in actual beverage samples; (b)
508
sunset yellow in actual beverage samples.
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Table 1. PLS models developed by standard solution of two colorants Samples
Concentration range a
n
LV b
R2CV c
RMSE d
RPD
Allura red
0.10 – 5.00
32
4
0.925
0.45
3.6
Sunset yellow
0.10 – 10.00
36
4
0.982
0.48
7.4
510
a
The unit is mg/L ;b LV:Latent variable;c R2CV refers to correlation coefficient for cross-validation;
511
d
The unit for RMSE is mg/L
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Table 2. Linear correlation between the colorant concentration with some specific peaks
Allura red
Sunset yellow
Raman shifta
LEb
R2
RMSE c
RPD
1219
y=921.46x+392.25
0.955
0.35
4.7
1267
y=867.43x+405.29
0.954
0.35
4.7
1495
y=896.84x+378.36
0.948
0.38
4.3
1580
y=816.8x+0.0939
0.950
0.37
4.5
1166
y=392.53x+49.447
0.984
0.48
8.1
1386
y=829.34x+93.903
0.983
0.49
7.8
1497
y=494.76x+176.13
0.976
0.59
6.5
1592
y=913.62x+131.96
0.987
0.43
9.1
513
a
The unit is cm-1;b LE, Linear equation; x, concentration of allura red standard solution; y, the
514
Raman intensity of allura red at the specific wavenumber;c The unit for RMSE is mg/L
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Table 3. SERS and HPLC prediction of allura red or sunset yellow concentration in beverages
a
Beverage name
Colorant
HPLC (mg/L)
PLS model (mg/L)
Linear regression (mg/L)
Peach cocktail
allura red
2.07±0.03
2.98
2.23
Energy drink
allura red
1.93±0.06
1.25
1.56
Strawberry juice
allura red
2.22±0.13
1.99
1.40
Cranberry juice a
allura red
3.55± ±0.10
1.22
1.49
Cranberry wine
allura red
38.28± ±0.06
-0.58
-0.15
Vitamin water
n.d.
n.d.
n.d.
n.d.
Grape fruit juice
n.d.
n.d.
n.d.
n.d.
Cocktail (no colour)
n.d.
n.d.
n.d.
n.d.
Orange sprite
sunset yellow
24.98±0.08
18.89
18.11
Apple vinegar
sunset yellow
10.38±0.07
8.99
10.97
Mango juice
sunset yellow
11.00±0.11
10.58
12.89
Orange juice
sunset yellow
21.12± ±0.07
10.18
9.63
Orange vodka
sunset yellow
15.55±0.04
8.18
12.26
There had a quite different between SERS and HPLC prediction.
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Figure 1. UV-Vis spectra of the gold nanorods synthesized with (a) 20, (b) 50 and (c)
519
80 μL AgNO3.
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520 521 522
Figure 2. TEM images of Au nanorods with different aspect ratios (ARs): (a) and (b)
523
AR 1.8, (c) and (d) AR 2.4 , (e) and (f) AR 3.5.
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Figure 3. (a) Representative SERS spectra of Sudan IV with Au nanorods of AR 1.8
526
as the substrate; (b) the intensity of the 1099 cm-1 peak in the SERS spectra of 1 and
527
0.1 mg/L Sudan IV standard solution and the intensity of the 1444 cm-1 peak in the
528
SERS spectra for the substrate stored for different days.
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530
531 532
Figure 4. Representative SERS spectra of (a) 10, 5 and 1 mg/L allura red standard
533
solution with different gold nanorods as the substrate; (b) the influence of salts on the
534
detection of 5 mg/L allura red standard solution; (c) the influence of different gold
535
nanorods and salts on the detection of 10 mg/L sunset yellow standard solution.
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Figure 5. Probable mechanism of interaction between the substrate and the analyte.
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Figure 6. Representative SERS spectra of (a) allura red standard solution at a series of
540
concentrations with the optimal Au nanorods; (b) sunset yellow standard solution at a
541
series of concentrations with the optimal Au nanorods and the salts of MgSO4.
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Figure 7. Representative SERS spectra of (a) allura red standard solution (10 mg/L);
544
(b) non-colored cocktail spiked with allura red (10 mg/L); (c) allura red standard
545
solution (5 mg/L); (d) non-colored cocktail spiked with allura red (5 mg/L); (e) sunset
546
yellow standard solution (10 mg/L); (f) non-colored cocktail spiked with sunset
547
yellow (10 mg/L); (g) 1:1 diluted non-colored cocktail spiked with sunset yellow (5
548
mg/L); (h) non-colored cocktail spiked with sunset yellow (20 mg/L); (i) 1:1 diluted
549
non-colored cocktail spiked with sunset yellow (10 mg/L).
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Figure 8. Representative SERS spectra of (a) allura red in actual beverage samples; (b)
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sunset yellow in actual beverage samples.
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Graphic for table of contents
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