This document summarizes research progress at China Agricultural University (CAU) in pesticide residue analytical methodology and risk management. It describes the research group's work developing new multi-residue extraction and cleanup methods like dispersive solid phase extraction using multiwalled carbon nanotubes and multi-plug filtration cartridges. It also discusses applying these new methods to analyze pesticide residues in foods like tomatoes, soybeans, and citrus using GC-MS/MS and LC-MS/MS. Finally, it provides an overview of challenges in China's pesticide residue management system including establishing thousands of maximum residue limits for agricultural products and processed foods.
Regulatory guidelines for conducting toxicity studies by ichAnimatedWorld
ICH is the “International Conference on Harmonization of
Technical Requirements for Registration of Pharmaceuticals for
Human Use”
ICH is a joint initiative involving both regulators and research based industry representatives of the EU, Japan and the US in
scientific and technical discussions of the testing procedures required
to assess and ensure the safety, quality and efficacy of medicines
Open Access ToxCast/Tox21, Toxicological Priority Index (ToxPi) and Integrate...Premier Publishers
Three open access computational tools were used on pesticides with well-characterized toxicological profiles to determine concordance between modeled predictions and measured acute in vivo toxicity (most→least: chlorpyrifos-oxon/chlorpyrifos (CPFO/CPF), carbaryl (CB), endosulfan (ENDO), propyzamide (PZ)). Tools included 1) Toxicity Forecaster (ToxCast) and Tox21 (ToxCast/Tox21) assays (AC50s µM) to identify biological targets associated with modes of action; 2) Toxicological Prioritization Index (ToxPi) incorporating AC50s to rank and score toxicity; 3) Integrated Chemical Environment (ICE) tool for in vitro to in vivo extrapolation one-, three-, and multi-compartment models to predict human equivalent administered dose (EADHuman). ToxPi toxicity ranking was predictive for CPFO, CB and PZ but not for CPF or ENDO. Qualitative graphical visualizations and quantitative fold differences between EADHumans and acute oral in vivo endpoints for each pesticide were most predictive in the three-compartment model. Qualitative modeled toxicity rank among AChE inhibitors (CPFO>CPF>CB) was 100% predictive. Brain AChE inhibition endpoints (EADHuman vs. ADJBMD10) had better predictions (lower fold difference) than those with RBC AChE inhibition endpoints. Overall, the computational tools in this study could be useful in not only prioritizing pesticides for risk assessment but also providing insights into mechanistic data often lacking in traditional testing.
Regulatory guidelines for conducting toxicity studies by ichAnimatedWorld
ICH is the “International Conference on Harmonization of
Technical Requirements for Registration of Pharmaceuticals for
Human Use”
ICH is a joint initiative involving both regulators and research based industry representatives of the EU, Japan and the US in
scientific and technical discussions of the testing procedures required
to assess and ensure the safety, quality and efficacy of medicines
Open Access ToxCast/Tox21, Toxicological Priority Index (ToxPi) and Integrate...Premier Publishers
Three open access computational tools were used on pesticides with well-characterized toxicological profiles to determine concordance between modeled predictions and measured acute in vivo toxicity (most→least: chlorpyrifos-oxon/chlorpyrifos (CPFO/CPF), carbaryl (CB), endosulfan (ENDO), propyzamide (PZ)). Tools included 1) Toxicity Forecaster (ToxCast) and Tox21 (ToxCast/Tox21) assays (AC50s µM) to identify biological targets associated with modes of action; 2) Toxicological Prioritization Index (ToxPi) incorporating AC50s to rank and score toxicity; 3) Integrated Chemical Environment (ICE) tool for in vitro to in vivo extrapolation one-, three-, and multi-compartment models to predict human equivalent administered dose (EADHuman). ToxPi toxicity ranking was predictive for CPFO, CB and PZ but not for CPF or ENDO. Qualitative graphical visualizations and quantitative fold differences between EADHumans and acute oral in vivo endpoints for each pesticide were most predictive in the three-compartment model. Qualitative modeled toxicity rank among AChE inhibitors (CPFO>CPF>CB) was 100% predictive. Brain AChE inhibition endpoints (EADHuman vs. ADJBMD10) had better predictions (lower fold difference) than those with RBC AChE inhibition endpoints. Overall, the computational tools in this study could be useful in not only prioritizing pesticides for risk assessment but also providing insights into mechanistic data often lacking in traditional testing.
Presentation on ICH guidelines Q5A (R1) and Q4B Annex 2 (R1)HadiaNaz1
EXECUTIVE SUMMARY OF ICH GUIDELINES Q5A (R1) AND Q4B ANNEX 2 (R1)
VIRAL SAFETY EVALUATION OF BIOTECHNOLOGY PRODUCTS DERIVED FROM CELL LINES OF HUMAN OR ANIMAL ORIGIN – Q4B ANNEX 2 (R1):
This document is concerned with testing and evaluation of the viral safety of biotechnology products derived from characterized cell lines of human or animal origin. The scope of the document covers products derived from cell cultures initiated from characterized cell banks. It covers products derived from in vitro cell cultures, recombinant DNA – derived products and also includes products derived from hybridoma cells grown in vivo.
Three principal approaches have evolved to control the potential viral contamination of biotechnology products:
a) Selecting & testing cell lines and other raw materials, including media components, for the absence of undesirable viruses which may be infectious and/or pathogenic for humans.
b) Assessing the capacity of the production processes to clear infectious viruses.
c) Testing the product at appropriate steps of production for absence of contaminating infectious viruses.
The guideline suggests approaches for the evaluation of the risk of viral contamination and for the removal of virus from the product. Following are the recommended tests for the brief description of a general framework and philosophical background within which the manufacturer should justify the testing that was done;
1) Test for Retroviruses
2) In vitro Assay
3) In vivo Assay
4) Antibody Production Tests
TEST FOR EXTRACTABLE VOLUME OF PARENTRAL PREPARATIONS GENERAL CHAPTER – Q4B ANNEX 2 (R1):
This annex is the result of the Q4B process for the Test for Extractable Volume of Parenteral Preparations General Chapter. The proposed texts were submitted by the Pharmacopoeial Discussion Group (PDG). The acceptance criteria of this document are same in the three pharmacopoeias.
The annex contains the following considerations for the implementation;
1) General Consideration
2) FDA Consideration
3) EU Consideration
4) MHLW Consideration
ICH GUIDELINES, ICH, INTERNATIONAL CONFERENCE ON HARMONIZATION, B PHARMA 6TH SEM, PHARMACEUTICAL QUALITY ASSURANCE
ICH and ICH guidelines
Need
Origin of ICH
Evolution of ICH
ICH members
Steps of ICH
STEP 1: Building Scientific Consensus
STEP 2: Agreeing on Draft Text
STEP 3: Consulting Regional Regulatory Agencies
STEP 4: Adopting Harmonized Guidelines
STEP 5: Implementing Guidelines in ICH Regions
Categories of ICH guidelines
Topic explained as a M.Sc. Microbiology Student point of you. It contains general Properties of drug, its discovery process and Rational Drug Design Process using Bioinformatic Tools.
Presentation on ICH guidelines Q5A (R1) and Q4B Annex 2 (R1)HadiaNaz1
EXECUTIVE SUMMARY OF ICH GUIDELINES Q5A (R1) AND Q4B ANNEX 2 (R1)
VIRAL SAFETY EVALUATION OF BIOTECHNOLOGY PRODUCTS DERIVED FROM CELL LINES OF HUMAN OR ANIMAL ORIGIN – Q4B ANNEX 2 (R1):
This document is concerned with testing and evaluation of the viral safety of biotechnology products derived from characterized cell lines of human or animal origin. The scope of the document covers products derived from cell cultures initiated from characterized cell banks. It covers products derived from in vitro cell cultures, recombinant DNA – derived products and also includes products derived from hybridoma cells grown in vivo.
Three principal approaches have evolved to control the potential viral contamination of biotechnology products:
a) Selecting & testing cell lines and other raw materials, including media components, for the absence of undesirable viruses which may be infectious and/or pathogenic for humans.
b) Assessing the capacity of the production processes to clear infectious viruses.
c) Testing the product at appropriate steps of production for absence of contaminating infectious viruses.
The guideline suggests approaches for the evaluation of the risk of viral contamination and for the removal of virus from the product. Following are the recommended tests for the brief description of a general framework and philosophical background within which the manufacturer should justify the testing that was done;
1) Test for Retroviruses
2) In vitro Assay
3) In vivo Assay
4) Antibody Production Tests
TEST FOR EXTRACTABLE VOLUME OF PARENTRAL PREPARATIONS GENERAL CHAPTER – Q4B ANNEX 2 (R1):
This annex is the result of the Q4B process for the Test for Extractable Volume of Parenteral Preparations General Chapter. The proposed texts were submitted by the Pharmacopoeial Discussion Group (PDG). The acceptance criteria of this document are same in the three pharmacopoeias.
The annex contains the following considerations for the implementation;
1) General Consideration
2) FDA Consideration
3) EU Consideration
4) MHLW Consideration
ICH GUIDELINES, ICH, INTERNATIONAL CONFERENCE ON HARMONIZATION, B PHARMA 6TH SEM, PHARMACEUTICAL QUALITY ASSURANCE
ICH and ICH guidelines
Need
Origin of ICH
Evolution of ICH
ICH members
Steps of ICH
STEP 1: Building Scientific Consensus
STEP 2: Agreeing on Draft Text
STEP 3: Consulting Regional Regulatory Agencies
STEP 4: Adopting Harmonized Guidelines
STEP 5: Implementing Guidelines in ICH Regions
Categories of ICH guidelines
Topic explained as a M.Sc. Microbiology Student point of you. It contains general Properties of drug, its discovery process and Rational Drug Design Process using Bioinformatic Tools.
"qulak" customer satisfaction measurement system, allows you to see your business performance through your customer eyes. using qulak will help you measure your real customer satisfaction level at real-time. More information at www.qulak.com
Aportes tecnológicos de Embrapa a la seguridad alimentaria. Presentación realizada por Murillo Freire Junior (Embrapa Agroindústria de Alimentos), en el marco de la Consulta Regional a Expertos en Pérdidas y Desperdicios de Alimentos en América Latina y el Caribe, realizada los días 8, 9 y 10 de octubre de 2014 en Santiago de Chile.
Good Manufacturing Practice (GMP) 2day course Jo Havemann
The following topics were presented to the participants through lectures, group discussions and exercises during 16 hours:
- Core values and guidelines of Good Laboratory Practice (GLP)
- Factors that might lead to questionable research & manufacturing practices and their impact
- GMP compliance, national & international regulations, guidelines and authorities
- Quality Management and Assessment
- Digital GMP Solutions
In this slide contains pesticide used in grains, limits as per FSSAI , general detection method for pesticide in Grains and extraction procedures.
Presented by: P.Pavan Kalyan. (Department of pharmaceutical analysis).
RIPER, anantapur.
EU REACH regulation changed the way to do chemical risk assessment. All chemicals marketed or manufactured in the EU must have its own dossier. Non standard methods including alternatives to animal testing are accepted.
Half Italian, half English
To Study the Knowledge, Attitude and Practices of Staffs at several levels on...iosrjce
IOSR Journal of Dental and Medical Sciences is one of the speciality Journal in Dental Science and Medical Science published by International Organization of Scientific Research (IOSR). The Journal publishes papers of the highest scientific merit and widest possible scope work in all areas related to medical and dental science. The Journal welcome review articles, leading medical and clinical research articles, technical notes, case reports and others.
There are tens of thousands of man-made chemicals to which humans are exposed, but only a fraction of these have the extensive in vivo toxicity data used in most traditional risk assessments. This lack of data, coupled with concerns about testing costs and animal use, are driving the development of new methods for assessing the risk of toxicity. These methods include the use of in vitro high-throughput screening assays and computational models.
This presentation by Dr. Richard Judson reviewed a variety of high-throughput, non-animal methods being used at the U.S. EPA to screen chemicals for a variety of toxicity endpoints, including methods for providing mechanistic data like the Adverse Outcome Pathway.
EPA is committed to sound science, and we are proud to have some of the world's best scientists, many of whom are internationally recognized as leaders in their fields. Not only are EPA's scientific experts vital to achieving our mission, but they are dedicated to sharing knowledge and contributing to their the scientific communities, which helps further advance the science that protects human health and the environment. Part of this includes giving presentations to other members of the scientific community. We have posted some of these presentations here so that more people have access.
Learn more about Dr. Richard Judson - https://www.epa.gov/sciencematters/meet-epa-researcher-richard-judson
Learn more about EPA's Chemical Safety Research - https://www.epa.gov/chemical-research
Canadian Perspective on Problem Formulation for Biopesticides: Emma BabijOECD Environment
The seminar on Problem Formulation for the Risk Assessment of Biopesticides stemmed from a previous CRP-sponsored event on Innovating Microbial Pesticide Testing that identified the need for an overarching guidance document to determine when in vivo tests are necessary. Problem Formulation, a common practice in pesticide risk assessment, was highlighted as a useful approach for addressing uncertainties in data requirements for biopesticides.
The seminar featured presentations from various perspectives, including industry, regulatory bodies, and academia. Topics included the history and principles of Problem Formulation, industry perspectives on Problem Formulation and how it is applied internally for microbial pesticides, regulatory approaches, and specific case studies. The seminar provided an overview of the challenges, considerations, and potential solutions in harmonising Problem Formulation for biopesticide risk assessment. It emphasised the need for collaboration and discussion to develop Problem Formulation guidance for biopesticides.
1. Research Progress at CAU-China in
Pesticide Residue Analytical MethodologyPesticide Residue Analytical Methodology
and Risk Management
Canping PAN (China AgriculturalCanping PAN (China Agriculturalp g ( gp g ( g
University, CAU)University, CAU)
EE--mail: panc@cau.edu.cnmail: panc@cau.edu.cn
2. I. Brief Introduction to:
R h G f P ti id R id Ch i tResearch Group of Pesticide Residue Chemistry,
China Agricultural University (CAU)
Pesticide Analysis and Environmental Toxicology Laboratory,Pesticide Analysis and Environmental Toxicology Laboratory,
China Agricultural University, P R China
3. PAET LAB StaffsPAET LAB Staffs
• Prof Chuanfan Qian (Retired)
P f Sh Ji (R i d)• Prof Shuren Jiang, (Retired)
• Prof Zhiqiang Zhou: Chiral Pesticides
• Prof Canping Pan: MRM methods risk assessment• Prof. Canping Pan: MRM methods, risk assessment,
• Prof. Fengmao Liu, 5 batch analysis, Residue analysis
• Prof. Shungen Min: IR, NIR etcg ,
• Prof. Haixiang Gao, ionic liquids
• Dr Yongqiang Ma, nano-materials
D W P hi l ti id• Dr Wang Peng, chiral pesticides
• Vice-Professor Hongyan Zhang,
• Vice-professor Lijun Han• Vice-professor Lijun Han
• Other Staffs: 12
• PhD students: > 20
• Master students: >30
4. Overview of Pesticide Analysis and
Dietary Risk Assessment
• Sampling -> Bulk SampleSampling Bulk Sample
• Sample preparation: ->laboratory sample
• Sample processing: to get the “analytical portion”
Pesticide
• Extraction stability? Recovery/efficacy?
• Cleanup -> false positive/negative? Matrix effects
est c de
Analysisp p g
• Instrumental Analysis -> LOD?/RSD?
• Residue calculation
• Reporting of results > uncertainty?• Reporting of results -> uncertainty?
• Other/Related issues: Dietary Risk
MRL setting,
Monitoring(including MRL compliance),
Environment monitoring
y
Assessment
Environment monitoring……
5. International efforts on Pesticide
residue managements
JMPS: pesticide specification (new procedure), CIPAC:
methods
• CCPR:
GL th d f it i ( i WG)- GL on method performance criteria (ongoing eWG)
- Risk analysis principle (46th CCPR)
MRL i i i i- MRL settings: minor crop, crop grouping, representative
crop, mrl calculator……
• CCMAS
GL idi di t (C C G G S O- GL on avoiding disrupts (CAC GL 70: GUIDELINES FOR
SETTLING DISPUTES OVER ANALYTICAL (TEST) RESULTS )
6. Challenges in Pesticide Residue
Management
• Residue trial:• Residue trial:
- Addressed problems: crop group and representative crop; data requirements
Minor crop/minor use problem
MRM th d iti li bl i l it hi h d i• MRM methods: more sensitive, more applicable, simple, on-site, high speed screeing
(simple cleanup and fast detection)
• MRL setting : based on food, edible portion, also processed food;
Food dietary data need to be updated
• Precise risk dietary assessment:y
ADI/ARfd and risk analysis for different group of population, actual dietary risk
Aggregate residue risks and accumulative risks
• Global issues: risk analysis principles, disrupts in international trade (methods, limits),
Globe data review, … …
6
7. China status on pesticide
residue managements
• Background
• MRL management• MRL management
• Status
• Challenges
8. Background of ChinaBackground of China
1. China's population : >1.3billion, around 21%
of world population;p p
2. China has a territory of 9.6 million sq km;y q ;
3. China's farmland is around 121.7 million ha.
(7% of world farm field);
9. Pesticide is the major tool in controlling diseases,
insects weeds and ratsinsects, weeds and rats
• The controlling area is around 200 million ha. in China;
1 illi t f ti id f l ti d (400 000• 1 million tons of pesticide formulation are used (400,000-
500 000 tons of technical materials ) each year in China500,000 tons of technical materials.) each year in China.
10. China's pesticide industry
1. There are over 2,000 pesticide manufacturers or
formulators in China over 20 are of large scale andformulators in China, over 20 are of large scale and
around 300 have manufacture capacity of technical
materials
Wheat
materials.
2 Around 20 000 products with nearly 600 a i have been
Potato
2. Around 20,000 products with nearly 600 a.i. have been
registered, including public health pesticides, bio-
pesticides; espesticides;
3 The production capacity of pesticide formulations is3. The production capacity of pesticide formulations is
around 1-1.4 million tons.
11. ChineseChinese Food safety related laws and regulationsFood safety related laws and regulations
L th Q lit d S f t
Diagram of legal basis
Law on the Quality and Safety
of Agricultural ProductsFood Safety LawPesticide Management Regulations
Pesticide registration
Data requirements for pesticide
Pesticide MRLs
Data requirements:
Potatoe
s
Data requirements for pesticide
registration (residue):
Metablic mechanism in plants and
animals; Methods of analysis; Field
Data requirements:
Toxicology
Residue data
s
trial; GAP; Storage stability;
Processing study
Pesticide registration
Labeling
Prescribed use frequency and PHI
Release MRLs
and analysis method
12. Management and establishment of Chinese MRLsManagement and establishment of Chinese MRLs
National Standard Review Committee of Food Safety (20
Jan. 2010)
• Sub-committees: 10 specialized sub-committees were
established under the committee namely sub committeesestablished under the committee, namely sub-committees
for food production, microorganisms, codes of production
and operation, nutrition and special dietary foods, methodsp , p y ,
and protocols of inspection, pollutants, food additives,
food-related products, pesticide residues and residues of
i dveterinary drugs;
• Sub-committees for pesticide residues and veterinary drug• Sub-committees for pesticide residues and veterinary drug
residues were set up within MOA;
Institute for the Control of Agrochemicals MOAInstitute for the Control of Agrochemicals MOA
13. National Review Committee of Pesticide Residue StandardsNational Review Committee of Pesticide Residue Standards
(Since 2010.4.12)
Composition: 42 members from departments of
agriculture, health, industry and information, commerce,
quality inspection, food and drug, etc and 7 agency
members.
Responsibility: review national standards of pesticide
residues, review plan for the establishment and revision of
national pesticide residue standards and long-termp g
program, put forward suggestions concerning the
implementation of policies of pesticide residue standards
and technical measures and provide consultation to majorand technical measures, and provide consultation to major
issues related to national pesticide residue standards.
The Secretariat: set up within ICAMA is responsibleThe Secretariat: set up within ICAMA, is responsible
for routine management of the committee.
14. Challenges of Chinese MRL system
1. Thousands of agricultural commodities and even more
g y
g
processed products;
2. Complex and diversified farming system and cultivatingp g y g
practices ;
3. A huge number of pesticide applicators and disparity ing p pp p y
equipment and skills;
4. Increasing of International Trade of food;4. Increasing of International Trade of food;
5. Lack of basic data and good communication with pubic ;
6 People pay more and more attention on food safety6. People pay more and more attention on food safety.
15. Accelerate establishment of MRL in agricultural commodities
• By the end of the Twelfth Five-Year
Plan period 7 000 MRLs will be 2014: GB 2763: 3650 MRLs
7000
8000
Plan period, 7,000 MRLs will be
established, basically covering all
agricultural commodities.
2014: GB 2763: 3650 MRLs
4000
5000
6000
7000
量数量
• Straighten up, integrate, research to
develop national MRLs system;
1000
2000
3000
4000
残留限量
• Synchronize registration review and
MRLs establishment.
2005 2010 2013 2017
MRL数量 478 807 2293 7000
0
1000
16. Research progress on pesticide residue
l ti l th d l d di t i kanalytical methodology and dietary risk
assessment (at CAU)
1 dSPE and m-PFC cleanup method and application
2 LC ASAP-MS/MS evaluation, DART-MS, IMS, Raman
17. 1. dSPE and m-PFC cleanup method
and application
Cleanup: false positive; false negative; incorrect
quantitation(matrix effects)quantitation(matrix effects)
• dSPE (MWCNTs)
• DPX
• m-PFC
and Applications
18. MWCNTs in r-dSPE （Tea samples）
J. Agric. Food Chem. 2012, 60, 4026− 4033
19. MWCNTs as r-DSPE cleanup material for
bb i hcabbage, spinach,grape, orange
Without
r-DSPE
r-DSPE
(PSA)
r-DSPE
(MWCNTs)r-DSPE (PSA) (MWCNTs)
J. Chromatogr. A 1225J. Chromatogr. A 1225
(2012) 17–25. IF=4.612
25. The applications of m-PFC-
icomparison
Comparison of color (left is the performance of d-SPE, right is
the performance of m PFC): (a): spinach sample; (b): wheatthe performance of m-PFC): (a): spinach sample; (b): wheat
sample; (c): citrus sample; (d): peanut sample; (e): apple
sample; (f): carrot sample.
26. The applications of m-PFC-
comparison
ChromatogramChromatogram
for citrus extract
after different
l h dcleanup methods:
(a) Full scan
chromatogram forg
a typical blank
citrus sample with
d SPE ld-SPE cleanup;
(b) Full scan
chromatogram forg
a typical blank
citrus sample with
m PFC cleanupm-PFC cleanup.
27. The applications of m-PFC-
comparison
Average recoveries (%) and RSDs at three spiked levels in 6 matrices using the m-PFC
methodmethod.
The recoveries of m-PFC method are more stable, RSDs(<10%) lower than d-
SPE’s(<20%).
28. Multi-residue analysis by m-PFC method – LCMS application
J. Sep. Sci. Published online.
DOI: 10.1002/jssc.201300411
Patented
29.
30. 187 pesticides residue analysis by m-PFC method
(tomato products, GC-MS/MS)
Group 1 :
93 pesticides
Group 2 :
94 pesticidesp
34. 2 LC ASAP-MS/MS evaluation,
DART-MS, IMS, Raman
Atmospheric Solids Analysis Probe
IMS: ion mobility spectroscopyIMS: ion mobility spectroscopy
Direct Analysis in Real Time
Raman
35. Introduction
Ops
Introduction
Acetone or MeCN extraction
detection
methods
GC-FPD?
enzymatic
chromatography/MASS
inhibition method
f l iti?
Complicated operation:
cleanup, time
false positive?
DART-MS , ASAP-MS , IMS, Raman?
Rapid M-PFC based cleanup
36. a: NH2 b: PSA c: GCB d: C18
40
蘸取进样 Dip in 移液枪进样 With pipette 内标法 By internal standard
20
25
30
35
RSD,%
Degas rates/temp
0
5
10
15
le
n
fos
on
n
im
id
n
id
an
te
nil
im
Difenoconazole
PyridabenChlorpyrifosDiflubenzuronChlorbenzuron
PhoximIm
idacloprid
3-HydroxycarbofuranAcetam
iprid
Carbofuran
Om
ethoatePyrim
ethanilCarbendazim
ASAP-MS/MS
39. Instrument condition
Method for the determination of OPs in fruits and vegetables by DART-MS
MS
Instrument condition
MS：
• Agilent6410B Triple-
DART:
DART+
g p
Quadrupole MS
• +， MRM
• Dry gas temperature: 350 ℃
DART+
Helium flow: 2.9 L/min (Ionization )
Nitrogen flow: 3.0 L/min
• Dry gas temperature: 350 ℃
• Dry gas flow: 3 L/min
• Nebulizer: 5 Psi
g
Charge needle voltage：3000 V
Ceramic tube：4mm i.d, 8.3cm length
helium temperature: 300 ℃ grid electrode:
• Capillary voltage: 4000 V
helium temperature: 300 ℃，grid electrode:
200 V
The distance between the orifice DART
source and ceramic tube is 8mm andsource and ceramic tube is 8mm and
between the ceramic tube and the orifice
of MS is 2mm
Sample were manually introduced to thep y
DART，while keeping it in the helium
stream for about 5s.
41. Recovery experiment
Method for the determination of OPs in fruits and vegetables by DART-MS
Recovery experiment
Cherry tomato CK Cherr tomato spiked sampleCherry tomato-CK Cherry tomato- spiked sample
Apple -CK Apple - spiked sample
42. Methods for the determination of OPs in 7 commercial agrochemicals by DART-MS
• Determination of OPs in commercial agrochemicals
70% Acetamiprid WDG, CK
DART+
Positive mode
70% A t i id WDG ik d ith OP70% Acetamiprid WDG spiked with OPs
DART+
44. The applications of IMS in analysis of pesticides
Mass-mobility correlation
There were some deviations in this correlation for dimethomorph, diazinon and
methamidophos The deviation could be attributed to the influence of the compactmethamidophos. The deviation could be attributed to the influence of the compact
molecular structure for the three pesticides.
45. IMS operation parameters
Application of IMS in the pesticide residue analysis —IMS-KS-100
Number Standard solutions K0(cm2/V•s) Drift time(T/ms)
Table 1.The K0 and drift times of the pesticides investigated
IMS operation parameters
Ion source: pulse glow discharge ionization source;
Injection temperature:200 ℃;
The drift tube temperature: 60 ℃;
Signal acquisition time 60 s, cleaning time 90 s;
1 Imidacloprid 1.40 14.6
2 Diflubenzuron 1.30 15.7
3 Acetamiprid 1.44 14.2
4 Thiacloprid 1.40 14.6
5 Thiamethoxam 1.36 15.0
6 Buprofezin 1.26 16.3
7 Nitenpyram 1.37 14.9
8 C b l 1 53 14 0
g q , g ;
Discharge time 676 µs, leads to an initial time 728
µs, lead time 1534 µs;
IMS ion mode :positive ion mode.
8 Carbaryl 1.53
1.44
14.0
14.8
9 Carbofuran 1.52 14.0
10 Methomyl 1.53 14.0
11 Diethofencarb 1.34 15.9
12 Isoprocarb 1.51
1.42
14.1
15.1
13 Ni l id 1 28 16 313 Niclosamide 1.28 16.3
14 Simazine 1.54 13.4
15 Irgarol 1051 1.34 15.1
16 Ametryn 1.42 14.4
17 Trifluralin 1.27 15.9
18 Propyzamide 1.37 15.0
19 Pretilachlor 1.29 16.0
20 alachlor 1 35 14 720 alachlor 1.35 14.7
21 Imidaclothiz 1.38 14.5
22 kresoxim-methyl 1.26 15.7
23 Diazinon 1.26 15.7
24 tribenuron-methyl 1.71
1.56
12.1
13.2
25 Nicosulfuron 1.71 11.8
26 thifensulfuron methyl 1.73 11.96 t e su u o et y 1.73
1.54
11.9
13.4
27 diflubenzuron 1.29
1.78
15.7
11.4
28 Azodrin 1.49 13.9
29 phosphamidon 1.36 15.2
30 parathion-methyl 1.40 14.6
31 methamidophos 1.43 14.4p
32 isofenphos-methyl 1.28 16.2
33 phosmet 1.36 15.1
34 dimethoate 1.57 13.6
35 isocarbophos 1.45 14.2
36 Sumithion 1.38 14.8
37 Methoxyclor 1.32 15.5
38 omethoate 1.57 12.8
Fig1 The ion mobility spectra of cowpea blank and 39 DDVP 1.52 13.2
40 myclobutanil 1.27 16.2
41 tebuconazole 1.29 15.5
42 triazophos 1.27 15.7
43 triadimenol 1.25 15.9
44 lythidathion 1.39 14.5
Fig1 The ion mobility spectra of cowpea blank and
spiked Oxygen dimethoate, isocarbophos,
monocrotophos standard (0.2 mg/kg for all analytes).
46. Application of IMS in the pesticide residue analysis —IONRADAR IMS
Table 2 The basic informations drift times and experimentalTable 2. The basic informations, drift times and experimental
reduced mobilities (K0) of the pesticides investigated.
CAS
number
Molecular
formula
MW
Drift
time (ms)
Reduce
d
mobility,
K0
(cm2 V-1
s-1)
Drift
time (ms)
Reduce
d
mobility,
K0
(cm2 V-1
s-1)
Drift
time (ms)
Reduce
d
mobility,
K0
(cm2 V-1
s-1)
Drift
time (ms)
Reduce
d
mobility,
K0
(cm2 V-1
s-1)s ) s ) s ) s )
VUV positive VUV negative 63Ni positive 63Ni negative
Chlorpyrifos 2921-88-2
C9H11Cl3NO3P
S
350.6 8.89 3.29
6.68
9.12
4.38
3.21
8.72 3.36
9.60
13.08
3.05
2.24
Dimethoate 60-51-5 C5H12NO3PS2 229.3
7.36
10.92
3.98
2.68
8.56 3.42 11.44 2.56 10.56 2.77
Phosmet 732-11-6 C11H12NO4PS2 317.3 8.56 3.42 6.32 4.63 nd nd 9.08 3.22
Dichlorvos 62-73-7 C4H7Cl2O4P 221.0 8.12 3.61 nd nd 8.44 3.47 10.08 2.904 7 2 4
Malathion 121-75-5 C10H19O6PS2 330.3 9 3.25 6.36 4.60 9.32 3.14 9.04 3.24
Chlorothalonil 1897-45-6 C8Cl4N2 265.9 nd a nd 7.4 3.96 nd nd 10.48 2.79
Carbofuran 1563-66-2 C12H15NO3 221.3
7.68
11.36
3.81
2.58
7.65 3.83
8.08
11.88
3.62
2.46
11.23 2.61
Lambda-
cyhalothrin
91465-08-6 C23H19ClF3NO3 449.9 nd nd
8.32
11.88
3.52
2.46
nd nd 16.72 1.75
Fenvalerate 51630-58-1 C25H22ClNO3 419.9 nd nd nd nd nd nd 15.76 1.86
Imidacloprid 138261-41-3 C9H10ClN5O2 255.7 8.12 3.61 nd nd 9.4 3.12 12.12 2.42
Tebuconazole 107534-96-3 C16H22ClN3O 307.8 8.92 3.28 10.44 2.80 9.68 3.02 14.52 2.02
Triadimefon 43121-43-3 C14H16ClN3O2 293.8 9.2 3.18
8.24
9.92
3.5
2.95
10.64 2.75 13.24 2.21
8 95 3 27
Azoxystrobin 131860-33-8 C22H17N3O5 403.4
8.95
10.62
3.27
2.76
nd nd 9.44 3.10 8.52 3.44
Thiophanate-
methyl
23564-05-8 C12H14N4O4S2 342.4 9.32 3.14 nd nd nd nd
10.48
13.64
2.79
2.15
Carbendazim 10605-21-7 C9H9N3O2 191.2
7.04
8.08
4.16
3.62
nd nd 8.36 3.50 7.52, 8.48
3.89
3.45
Glufosinate
-
ammonium
77182-82-2 C5H15N2O4P 198.2
nd nd nd nd 6.76 4.33 nd nd
Glyphosate 1071-83-6 C3H8NO5P 169.1
d d d d d d d d
Glyphosate 1071 83 6 C3H8NO5P 169.1
nd nd nd nd nd nd nd nd
Nicosulfuro
n
111991-09-
4
C15H18N6O6
S
410.4
11.57 2.53 nd nd 7.32 4.00 7.56 3.87
2,4-D 94-75-7 C8H5Cl2O3 221.0
nd nd
7.84
11.08
3.73
2.64
9.4 3.12 nd nd
4-CPA 122-88-3 C8H7ClO3 186.6
nd nd
7.6
10.36
3.85
2.83
8.88 3.30
11.00
14.88
2.66
1.97
gibberellic 77-06-5 C19H22O6 365.4
nd nd nd nd nd nd nd nd
g
acid (GA3)
19 22 6
nd nd nd nd nd nd nd nd
Uniconazol
e
83657-22-1 C15H18ClN3
O
291.8
9.08 3.22 9.68 3.02 10.36 2.83 13.84 2.12
6-
benzylamin
opurine
1214-39-7 C12H11N5 225.3
nd nd nd nd 8.32 3.52 nd nd
Figure 3.Representative ion mobility spectra of
pesticides on/in apple, grape and Coca Cola matrixes
compared with the blank and the pesticide standard
spectrum
49. Fenthion in apple Fenthion in round lettuce
Flusilazole in apple Flusilazole in round lettuce
50. Summary and DiscussionSummary and Discussion
Pesticide use is an essential tool for agro-products: quality and
quantityquantity
MRL setting: a complex of data consideration
S f ? GAP h k? MRL Vi l ti ?-Safe? GAP check? MRL Violation reason?
-Chiral? Processing factor? Consumption? Minor crop/use?
-Harmonization?
Consideration of Pesticide Residue Results:
Sampling, The time for High resolution MS for servingg
Sample preparation,
sample processing,
extraction,
The time for High resolution MS for serving
pesticide residue analysis is coming! By
AOAC 2014 Harvey W. Wiley Awarder: Dr
Guofang Pangextraction,
cleanup,
instrumental analysis, (HR MS …….)
result calculation and express
g g
result calculation and express
51. Acknowledgements to:
Dr Guibiao Ye from ICAMA for providing information on MRL management
Prof. Wang Peng and Dr Fegnshou Dong for assisting chiral pesticide part
52. Thank you for kind attention!Thank you for kind attention!
E-mail: panc@cau.edu.cn@
