Oxidase-mimicking activity of ultrathin MnO2 nanosheets in a colorimetric assay of chlorothalonil in food samples

Article abstract of DOI:10.1016/j.foodchem.2020.127090

Chlorothalonil is a class of 2B carcinogen which is widely used in the prevention and treatment of fungal diseases in food samples. Its residual problem has been increasingly concerned by society. In this paper, a fast and simple colorimetric assay based on Manganese dioxide nanosheets (MnO₂ NSs)-oxidize 3,3′,5,5′-tetramethylbenzidine (TMB) platform was used to detect residual pesticide chlorothalonil in food samples. Under optimal conditions, the half maximal inhibitory concentration and the limit of detection of chlorothalonil were 3.27 and 0.024 ng/mL. There were no obvious cross-reactivity between chlorothalonil and interference substances. The recoveries shown the satisfactory results. The results of colorimetric assay for the authentic samples were largely consistent with gas chromatography. Therefore, the proposed method would be convenient and satisfactory analytical methods for the monitoring of chlorothalonil. Furthermore, the MnO₂ – TMB system was used to produce test strips for quick and convenient visual detection of chlorothalonil with good performance.

Full text of DOI:10.1016/j.foodchem.2020.127090

Food Chemistry 331 (2020) 127090
Contents lists available at ScienceDirect
Food Chemistry
journal homepage: www.elsevier.com/locate/foodchem
Oxidase-mimicking activity of ultrathin MnO nanosheets in a colorimetric
2
assay of chlorothalonil in food samples
a,1
a,1
b
a
a
a,⁎
Enze Sheng , Yuxiao Lu , Yuting Tan , Yue Xiao , Zhenxi Li , Zhihui Dai
a
Jiangsu Collaborative Innovation Center of Biomedical Functional Materials and Jiangsu Key Laboratory of Biofunctional Materials, School of Chemistry and Materials
Science, Nanjing Normal University, Nanjing 210023, PR China
b
Department of Pesticide Science, College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, PR China
A R T I C L E I N F O
A B S T R A C T
Keywords:
Chlorothalonil is a class of 2B carcinogen which is widely used in the prevention and treatment of fungal diseases
in food samples. Its residual problem has been increasingly concerned by society. In this paper, a fast and simple
Chlorothalonil
2
MnO nanosheets
colorimetric assay based on Manganese dioxide nanosheets (MnO NSs)-oxidize 3,3′,5,5′-tetramethylbenzidine
2
Colorimetric assay
Oxidase-mimicking
Food samples analysis
(
TMB) platform was used to detect residual pesticide chlorothalonil in food samples. Under optimal conditions,
the half maximal inhibitory concentration and the limit of detection of chlorothalonil were 3.27 and 0.024 ng/
mL. There were no obvious cross-reactivity between chlorothalonil and interference substances. The recoveries
shown the satisfactory results. The results of colorimetric assay for the authentic samples were largely consistent
with gas chromatography. Therefore, the proposed method would be convenient and satisfactory analytical
methods for the monitoring of chlorothalonil. Furthermore, the MnO – TMB system was used to produce test
2
strips for quick and convenient visual detection of chlorothalonil with good performance.
1
. Introduction
chlorothalonil as a class 2B carcinogen. So, it is necessary to establish a
rapid, sensitive and economical detection method to detect residual
chlorothalonil.
Recently people pay more and more attention to their own health,
and the requirements for food quality are becoming higher and higher
In recent years, many strategies detection of chlorothalonil residues
have been explored, including chromatographic analysis, chemilumi-
nescence, enzyme-linked immunosorbent assay, and fluorescence
(
Najafi, Khalilzadeh, & Karimi-maleh, 2014). The analytical methods
used to analyze and detect the content of different substances in food
have gradually attracted people's attention, and more and more de-
tection methods have been developed by researchers (Baghizadeh &
methods (Catalá-Icardo, Gómez-Benito, Simó-Alfonso,
& Herrero-
Martínez, 2017; dos Santos et al., 2019; Hirakawa et al., 2015; Hou,
Zhao, & Liu, 2016; Kurz et al., 2008; Yuan, Wang, Cheng, Kong, & Che,
2019; Sheng, Du, Yang, Hua, & Wang, 2018). However, the traditional
methods still exist some disadvantages, such as low detection sensi-
tivity, complex and long operation time and many of them require
expensive instruments (Bettencourt Da Silva, Dias, & Camões, 2012;
Drabova et al., 2019; López-Blanco et al., 2018; Yang et al., 2018).
These insufficiencies clearly limit the wide application of these
methods. Therefore, it was necessary to establish new methods with
high sensitivity and quantitatively detect the residue of chlorothalonil
to meet the increasing needs of food monitoring. Due to its environ-
mental friendliness, inherent simplicity, and high sensitivity, new ma-
terials based on biosensing strategies have been paid attention to the
field detections design (Yan, Li, Zheng, & Su, 2015). The analysis
method based on 3,3′,5,5′-tetramethylbenzidine (TMB) can be used to
Karimi-maleh, 2015; Eren, Atar, Lütfi,
& Karimi-maleh, 2015;
Shamsadin, Mohammad, Somaye, & Maleh, 2019). Pesticides widely
used to ensure crop yields have also attracted people's attention because
of their residual problems.
Chlorothalonil is a kind of non-systemic fungicide developed by the
Diamond Alkli (Fermenta) company (Van Scoy & Tjeerdema, 2014). As
the world’s second most produced fungicide, it is widely used in the
cultivation of fruits and vegetables (Simões et al., 2019). Chlorothalonil
has significant toxicity, and it is highly toxic to fish and aquatic in-
vertebrates (Guerreiro, Rola, Rovani, Costa, & Sandrini, 2017). It was
found that chlorothalonil had a significant carcinogenic effect on the
kidneys of rats and had mutagenic effects on their offspring (Guerreiro
et al., 2017). Therefore, on October 27, 2017, the World Health Orga-
nization, an international Agency for Research on Cancer, listed
⁎
Corresponding author.
E-mail address: daizhihuii@njnu.edu.cn (Z. Dai).
1
The two authors contribute equally to this article.
https://doi.org/10.1016/j.foodchem.2020.127090
Received 19 December 2019; Received in revised form 3 May 2020; Accepted 16 May 2020
Available online 18 June 2020
0308-8146/ © 2020 Elsevier Ltd. All rights reserved.

E. Sheng, et al.
Food Chemistry 331 (2020) 127090
quantify analytes quickly and easily without complicated instruments
and expensive biological reagents (Hizir et al., 2016; Yan et al., 2018).
verified by UV–vis spectroscopy at 653 nm for analysis.
Manganese oxide nanosheets (MnO
2
NSs) is a nanomaterial with per-
2.4. Preparation for chlorothalonil sensing
oxide mimic enzyme activity, which has good biocompatibility (Yan
2
+
et al., 2017). It can be reduced to Mn by TMB, and can oxidize large
numbers of reducing substrates, providing a promising opportunity for
the advanced development of colorimetric assays. It avoids any oxi-
When GAPD and NAD were added, PGAL could be catalytically
hydrolyzed to produce diphosphoglycerate, which could not initiate the
decomposition of MnO NSs. Due to action of chlorothalonil, the GAPD
2
dants (H
2
O
2
) participating in the TMB-based reaction, making handling
was decomposed, preventing the decomposition of PGAL and causing
easier and less time consuming (Yan et al., 2016). Therefore, MnO
2
-
the decrease of absorbance. Different concentrations (25 µL) of chlor-
TMB-based strategies can be used as promising platform in chemical/
othalonil and GAPD were mixed at 37 ℃ for 30 min. Then NAD and
biosensing applications (Peng et al., 2019).
PAGL in PB buffer were added at 37 ℃. Next, 20 µL MnO NSs, 25 µL
2
Until now, there are few reports about MnO
2
-catalyzed analysis
TMB solution, and 100 µL NaAc buffer were added. Finally, the mixed
methods for pesticide residues. In this research, a simple and quick
colorimetric analysis method for detecting the chlorothalonil residues
in food samples was designed. This method not only improved the
qualitative and quantitative of the colorimetric sensor but also provided
a new design of an enzyme sensor. TMB (colorless) can be oxidized by
solution was diluted to 500 µL with ultrapure water. After incubating at
37 °C for 15 min, the UV–vis spectra were detected.
The mean values of Inhibition Efficiency (IE) were calculated: IE
= (A
inhibitor
Ano inhibitor )/(A0
Ano inhibitor ) × 100%.
MnO NSs to oxTMB (blue), which had a characteristic absorption peak
2
A
inhibitor: the absorbance of MnO
2
-TMB/PGAL/GAPD with chlor-
at 653 nm. 3-phosphoglyceraldehyde (PGAL) can reduce MnO NSs to
2
2
+
othalonil.
generate Mn , then TMB cannot be oxidized. Under phosphoric acid
A
no inhibitor: the absorbance of MnO -TMB/PGAL/GAPD without
2
conditions, PGAL can be decomposed by glyceraldehyde-3-phosphate
chlorothalonil.
dehydrogenase (GAPD) and coenzyme I (NAD), so that MnO NSs
2
A
0
: the absorbance of MnO -TMB.
2
cannot be decomposed and TMB can be oxidized. After the addition of
chlorothalonil, as an active inhibitor of GAPD, chlorothalonil can de-
The inhibitory concentration (IC50 and IC10) were obtained from a
four-parameter logistic equation of the sigmoidal curves using Origin
Pro 8.0 software (Sheng et al., 2016).
compose GAPD. Without GAPD, PGAL can oxidize the MnO NSs.
2
Therefore, the sensor platform can show an obvious color change when
the concentration of the added chlorothalonil had been changed. What
is more, the sensor platform could be made into a test strip of paper to
quickly and visually detect the residue of chlorothalonil during on-site
testing.
2.5. Assay optimization
As an important component of the sensor, GAPD reduced the sen-
sitivity of the sensor if its concentration was too high, while a low
concentration could cause a high system background. At the same time,
the catalytic activity of GAPD was related to many conditions, such as
pH, reaction temperature, and incubation time. In order to improve the
sensitivity of the system to detect chlorothalonil, the parameters of the
system were optimized.
2
. Materials and methods
2.1. Materials and instruments
The standards of chlorothalonil (99.3%) and its interfering sub-
stances were supplied by the Jiangsu Pesticide Research Institute
(
Jiangsu, China). NAD, KMnO
4
, TMB, PGAL, 4-morpholineethane sul-
2.6. Gas chromatographic analysis and validation
fonic acid (SDBS), GAPD, bovine serum albumin (BSA), and other
analytical chemicals were obtained from Sigma-Aldrich Corporation.
The transmission electron microscopy (TEM) images were obtained on a
JEOL-2100F apparatus (Japan). X-ray photoelectron spectra (XPS) were
20 g of sample (wheat, rice, apple, pear, grape, tomato, cucumber
and cabbage), 10 mL of water and 60 mL of acetonitrile were mixed
together and shaken for 1 h. Then the organic phase was dehydrated
and concentrated, the samples were diluted with 2 mL of acetone and
further analyzed by GC-ECD (Bettencourt Da Silva et al., 2012). A DB-1
fused silica capillary column (30 m × 0.32 mm × 0.25 µm) was used
for the detection. The column temperature was initially held at 150 °C
in 2 min, then raised to 210 °C by 6 °C/min, and finally raised to 270 °C
by 30 °C/min, and held at this value for 6 min. Nitrogen was used as the
carrier gas (58 mL/min). The detector was an ECD at a temperature of
320 °C. The measured results were compared with the colorimetric
assay.
obtained using
a scanning X-ray microprobe (PHI 5000 Versa,
ULACPHI, Inc. Japan). A Cary 60 UV–Vis spectrometer (Agilent, USA)
was used to carry out UV–Vis absorbance measurements. The Fourier
transform infrared spectroscopy (FTIR) images were obtained on a
Lambda 950 (USA). The colorimetric assay was validated with an
Agilent 7890A gas chromatography (GC) (Agilent, USA).
2
.2. Preparation of MnO
2
NSs
Ultrathin MnO NSs were prepared as previous described with some
2
modifications (Kai et al., 2012). In brief, 3.2 mL SDBS (0.5 mol/L),
.16 mL H SO solution (0.1 mol/L), 6.4 mL ethanol and 48 mL dis-
tilled water were mixed together and the mixture was stirred at 90 ℃
for 15 min. 0.64 mL of KMnO solution (0.05 mol/L) was added into the
solution and stirred for 60 min. Deionization water was used for
3. Results and discussion
0
2
4
3.1. The characterization of MnO NSs
2
4
In this study, the ultrathin MnO NSs were characterized by TEM,
2
washing three times to purify the synthesized MnO
2
NSs. Finally, for
XPS, FTIR and UV–Vis spectroscopy. A large two-dimensional structure
with an average transverse size of nearly 50 nm (Fig. 1A), indicated the
nanostructures provided a large surface area for the reaction with TMB.
further use, the MnO
powder.
2
NSs were freeze-dried forming a brownish black
The UV–Vis spectra of MnO NSs are 300–600 nm, and the character-
2
2.3. Assays for PGAL activity
istic absorption was near the 380 nm (Fig. 1B). In the FTIR spectrum,
−1
3
423 cm
was corresponded to OeH stretching modes of interlayer
5
0 µL PGAL, 20 µL MnO
2
NSs (0.5 mg/mL), 25 µL TMB (1 mg/mL)
water molecules and H-bonded OeH groups attributed to bending
−1
and 100 µL NaAc were mixed together, diluted to 500 µL by PB buffer
10 mmol/L) and incubated at 37 ℃ for 15 min. The conjugates were
mode of water molecules was observed near 1629 cm . The absorp-
(
tion peak at 1116 cm−1 was attributed to the OeH bending vibration
2

E. Sheng, et al.
Food Chemistry 331 (2020) 127090
Fig. 1. (A) The TEM images, (B) the UV–vis absorption spectra of MnO
2
NSs, (C) The FTIC spectra of MnO
2
NSs, (D) The XPS spectra of MnO NSs.
2
combined with Mn atmos. The peaks at 898 and 550 cm−1 were the
main characteristic absorption bands corresponding to stretching vi-
NSs had oxidase-like activity.
In order to value the oxidase-like properties of MnO
concentrations of MnO NSs were incubated with TMB and the ab-
sorption values of each system were measured. The results are shown in
2
NSs, different
−
1
bration of the MnO
2
. 550–900 cm
to the M-O, M-O-M and O-M-O
2
lattice vibrations (Fig. 1C). The XPS of the MnO NSs exhibited two
2
peaks centered at 642.0 eV and 653.9 eV, belonging to Mn2p3/2 and
Mn2p1/2 (Fig. 1D). All of the results demonstrate the successful pre-
Fig. 2B. With the concentration of MnO NSs increased, the absorbance
2
at 653 nm increased correspondingly, and the amount of oxTMB also
increased. At the same time, the color of the mixed solution changed
from colorless to dark blue (Fig. 2C). Therefore, the enzyme simulation
paration of ultrathin MnO NSs.
2
3.2. The catalytic performance of MnO
2
NSs
activity of MnO NSs changed the absorbance of the solution. Stability
2
was a important thing to evaluate the performance of the test methods.
The stability of the system was studied for more than 30 min (Fig. 2D).
The absorbance intensity kept unchanged, without obvious changes at
The colorimetric assay established in this study was based on the
color changing reaction of MnO
catalytic capacity of the MnO
2
2
-TMB as a signal output. Therefore, the
NSs was the key to construct colori-
653 nm, which indicated that the MnO -TMB system had good con-
2
metric analysis. To verify the catalytic performance, MnO
2
NSs were
sistency performance and could be used to manufacture sensor plat-
directly incubated with TMB to catalyze the colorimetric reactions. The
forms.
TMB solution had no obvious absorption peak (Fig. 2A, curve b) within
the range of 330–800 nm, while MnO
2
2
NSs had an absorption peak at
NSs and TMB were mixed, two
3.3. Feasibility verification of enzyme controlled MnO
2
-TMB platform
3
80 nm (Fig. 2A, curve a). When MnO
strong characteristic peaks appeared at 371 nm and 653 nm (Fig. 2A,
MnO NSs could oxidize TMB (colorless) to produce oxTMB (blue)
2
curve c) respectively, which corresponded to oxTMB, and the solution
(Fig. 3A, curve a). In the presence of PGAL, PGAL could induce cleavage
turned blue (inset photograph in Fig. 2A). This indicated that the MnO
2
of the MnO NSs and prevent oxidation of TMB (Fig. 3A, curve b).
2
3

E. Sheng, et al.
Food Chemistry 331 (2020) 127090
Fig. 2. (A) The UV–vis absorption spectra of MnO
2
NSs (a), TMB (b), and MnO
2
NSs + TMB (c). (B) The UV–vis absorption spectra of TMB with different con-
centrations of MnO
2
NSs. (C) The corresponding photographs of the probe solution taken under daylight. (D) The stability of the MnO -TMB system was system-
2
atically investigated with 30 min.
PGAL itself has an aldehyde group and will be oxidized to produce
phosphoglycerate (Wang & Alaupovic, 1980). The interaction between
3.4. Optimization
MnO
2
NSs and PGAL were verified by UV–vis spectroscopy. As shown in
The effect of pH on the system in the presence of 10 mU/mL GAPD
was studied, and the results are shown in Fig. S1A. The absorbance ratio
was obviously enhanced as the pH value increased from 4.5 to 6.5, and
then an apparent decrease in the absorbance ratio was observed in the
pH range of 7.5–9.5. These results showed that the hydrolysis efficiency
of GAPD had good performance in an acidic medium. As shown in Fig.
S1B, the absorbance ratio continuously increased with the increasing
temperature and reached a maximum at 37 °C. The enzymatic reactions
were consecutively monitored by UV–vis 5 min after adding different
concentrations of GAPD (5, 10 and 20 µU/mL) at 37 °C (Fig. S1C). The
absorbance intensity at an enzymolysis time point of 30 min was
plotted as a function of the GAPD activity. Due to the above results, we
chose pH 6.5 PB buffer as the optimal buffer, 37 °C as the reaction
temperature, and 30 min as the proper reaction time for hydrolyzing
PGAL by GAPD.
Fig. 3B, the curve a showed the UV absorption of MnO
addition of PGAL into the system, the characteristic peak of the MnO
NSs at 380 nm was reduced (Fig. 3B, curve b), indicating that PGAL
2
NSs, after the
2
could decompose the MnO NSs and prevent the oxidation of TMB.
2
When GAPD was introduced into the system, GAPD reacted with PGAL
to form 1,3-bisphosphoglyceric acid preferentially, which prevented the
cleavage of PGAL and MnO NSs, leading to the oxidation of TMB at
2
6
53 nm (Fig. 3A, curve c) (Dunham et al., 1983). However, after the
addition of chlorothalonil, the chlorothalonil inhibited the activity of
GAPD and the enzyme activity was inhibited so that the decomposition
reaction of PGAL and the MnO NSs was not prevented, thus reducing
2
the absorption peak. Therefore, a simple and economical method was
produced for the analysis of chlorothalonil.
In order to evaluate the feasibility of this method, the absorbance
intensity of the MnO
2
-TMB (curve a), GAPD-MnO
2
-TMB (curve b), CHL-
As shown in Fig. S1D, with the increase of GAPD concentration
(0–50 mU/mL), the absorbance at 653 nm decreased continuously, and
the color changed from colorless to blue (Fig. S1E). The absorbance of
the system under different concentrations of GAPD was shown in Fig.
S1D. There is a good linear relationship between the absorbance ratio of
the system and the concentration of GAPD. Finally, 20 mU/mL GAPD
was chosen for the assay to detect chlorothalonil.
MnO
2
-TMB (curve c), and CHL-GAPD-PGAL-MnO -TMB (curve d) sys-
2
tems were analyzed (Fig. 3C). The absorbance was not affected by
GAPD (50 µU/mL) or chlorothalonil (10 µg/mL) alone at 653 nm (curve
b and curve c were nearly same with curve a). When 50 µU/mL GAPD
and 10 µg/mL chlorothalonil were present in the system, the absor-
bance intensity decreased by nearly 73% (curve d). Furthermore, the
2
+
effects of Mn (the decomposition product of MnO NSs) on the TMB
2
solution were tested. No absorption peak was observed, and the color of
3.5. Sensitivities
2
+
the solution did not change regardless of whether Mn
Fig. 3D). In view of the results, a colorimetric assay for laboratory
detection of chlorothalonil was established by the oxidation reaction of
TMB catalyzed by MnO NSs.
was added
(
Under the optimal reaction conditions, the standard curves of
chlorothalonil were obtained by the colorimetric assay (Fig. 4). The
assay was shown to have an IC50 of 3.27 ng/mL, the IC10-IC90 was
2
0
.45–3430 ng/mL. More importantly, the sensor could directly detect
chlorothalonil down to 0.45 ng/mL, which was much lower than the
maximum residue limit (MRL) (0.01 mg/kg in USA) (Lin et al., 2019).
4

E. Sheng, et al.
Food Chemistry 331 (2020) 127090
Fig. 3. (A) The UV–vis absorption spectra of MnO
2
+ TMB (a), MnO
2
+ TMB + PGLA (b), and MnO
2
+ TMB + PGAL + GAPD (c). (B) The UV–vis absorption
spectra of MnO
2
NSs in the absence (a) and presence (b) of PGAL. (C) The UV–vis absorption spectra of MnO
2
+ TMB (a), MnO + TMB + GAPD (b), and
2
2+
MnO
2
+ TMB + PGAL + GAPD + chlorothalonil (c). (D) UV–vis absorption spectra of the TMB system in the absence (a) and presence (b) of Mn
.
residues, a paper-based sensor was constructed for chlorothalonil. The
MnO NSs were dispersed in ultrapure water, then sprayed on a qua-
2
litative filter paper and stored in the dark for 30 d. When “TYT” was
written on the paper with TMB as ink, the blue color was immediately
displayed on the test paper and the color remained unchanged for
3
0 min (Fig. 5A). Then, 50 µL of the mixed buffer (containing PGAL,
GAPD, TMB, and chlorothalonil (standard solution)) was dripped onto
one prepared piece of test paper. The color of the test paper was visually
observed as the concentration of chlorothalonil increased (X) (Fig. 5B).
The assay was shown to have a testing range from 0.001 to 0.5 µg/mL,
which was much lower than the MRL. These results showed that the
paper-based sensor was capable of visually indicating the residue of
different concentrations of chlorothalonil. This method was simple,
reliable, easy to operate, and fast in response.
3.7. Analytical figure of merit
Fig. 4. Standard inhibition curves for chlorothalonil using colorimetric assay by
the MnO NSs.
In order to evaluate the specificity of the detection method, we
2
tested the blank different varieties food samples and food samples
added with the same concentration of chlorothalonil. As shown in Fig.
S2A, the results of the blank food samples were almost the same, and
the results of food samples with chlorothalonil were also similar. This
indicated that these common interference substances could not sig-
nificantly interfere with chlorothalonil detection. In the use of chlor-
othalonil, it was usually mixed with some other pesticides. We selected
some common pesticides to evaluate the accuracy of the method. Al-
though these interfering substances were often used in combination
with chlorothalonil, but their bacteriostatic mechanism were different
from chlorothalonil and hardly reacts with PGAL and GAPD. The results
The lowest detectable concentration (LOD) for chlorothalonil was
0
.024 ng/mL, which was much lower than the existing reporting
methods (Table S1). Therefore, the system meets the requirements for
detecting chlorothalonil residues.
3.6. Detection of chlorothalonil, using test strips
In order to meet the requirements of rapid detection of pesticide
5

E. Sheng, et al.
Food Chemistry 331 (2020) 127090
Fig.5. (A) Demonstrating the feasibility of test strips by handwriting on the paper using TMB solution as ink. (B) MnO
2
NSs-based test strips for visual detection of
chlorothalonil. The concentrations of chlorothalonil were 0.001, 0.0025, 0.005, 0.01, 0.05, 0.1, 0.5 µg/mL.
Table 1
The MnO
wide absorption range (300–600 nm), and were able to imitate oxidase
properties well. The MnO NSs catalytic reaction does not require the
participation of H , making detection simpler. Under the optimal
detection conditions, the linear range for chlorothalonil was
2
NSs prepared in this study were simple to prepare, have a
The recoveries of samples spiked with Chlorothalonil by colorimetric assay.
2
Sample
Chlorothalonil
O
2 2
Spiked
Found
Mean recovery ± SD
(% , n = 3)
concentration (ng/
g)
concentration (ng/
g)
0
.45–3430 ng/mL and LOD was 0.024 ng/mL. Compared with tradi-
tional detection methods and other detection methods, this colorimetric
assay has higher sensitivity, wider linear range, good stability, good
Wheat
Rice
10
9.27
92.7 ± 2.98
91.5 ± 3.45
85.3 ± 5.49
93.5 ± 3.69
86.3 ± 5.82
100.2 ± 3.23
96.1 ± 3.69
99.2 ± 5.62
95.3 ± 2.87
92.1 ± 4.69
100.3 ± 3.74
87.5 ± 3.96
98.4 ± 7.43
94.7 ± 3.65
100.5 ± 5.78
102.8 ± 4.52
98.4 ± 4.36
102.4 ± 3.56
89.7 ± 8.82
94.3 ± 5.89
93.4 ± 3.47
88.8 ± 5.27
93.6 ± 3.21
90.8 ± 2.82
1
1
00
91.52
853.41
9.35
selectivity and shorter detection time. In addition, the MnO -TMB
2
000
platform has been successfully established for manufacture paper-based
device for detecting chlorothalonil with qualitative and quantitative.
The two assays were implemented to measure chlorothalonil in food
samples with satisfactory results and good repeatability.
10
1
1
00
000
86.29
1002.21
9.61
Apple
10
1
1
00
000
99.21
952.87
9.21
CRediT authorship contribution statement
Pear
10
1
1
00
000
103.15
875.34
9.84
Enze Sheng: Conceptualization, Methodology, Formal analysis,
Visualization, Software, Writing - original draft. Yuxiao Lu: Validation,
Formal analysis, Visualization, Software. Yuting Tan: Validation,
Formal analysis, Visualization, Software. Yue Xiao: Formal analysis.
Zhenxi Li: Formal analysis. Zhihui Dai: Conceptualization,
Methodology, Resources, Writing - original draft, Writing - review &
editing, Supervision, Project administration, Funding acquisition.
Grape
10
1
1
00
000
94.66
1005.36
10.28
98.37
1024.78
8.97
Tomato
Cucumber
Cabbage
10
1
1
00
000
10
1
1
00
000
94.28
934.49
8.88
Declaration of Competing Interest
10
1
1
00
000
93.63
908.41
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influ-
ence the work reported in this paper.
showed that the pesticides often used in combination with CHL could
not significantly interfere with MnO -TMB (Fig. S2B). Combined with
2
Acknowledgement
the results, it indicated that our biosensor had a good specificity in
detecting chlorothalonil.
This work was supported by the Natural Science Foundation of
China for the project (Nos. 21625502 and 21974070).
The dilution was used to minimize matrix effects (Fig. S2). The re-
coveries of method were 85.3%–102.8% and the relative standard de-
viations (RSDs) were 2.82–8.82% (Table 1). The results met the re-
quirements of quantitative detection, which was according to the
guidelines on the pesticide residue trials of China (NY/T 788-2018).
These results indicated that the colorimetric assays were accurate and
reliable to determine if chlorothalonil was present in food samples.
The results of correlation between the colorimetric assay and GC for
analyses of samples with chlorothalonil (Table S2). Good correlations
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://
doi.org/10.1016/j.foodchem.2020.127090.
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