WO2019200947A1 - 基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法 - Google Patents

基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法 Download PDF

Info

Publication number
WO2019200947A1
WO2019200947A1 PCT/CN2018/121001 CN2018121001W WO2019200947A1 WO 2019200947 A1 WO2019200947 A1 WO 2019200947A1 CN 2018121001 W CN2018121001 W CN 2018121001W WO 2019200947 A1 WO2019200947 A1 WO 2019200947A1
Authority
WO
WIPO (PCT)
Prior art keywords
pesticide
orbitrap
ion
mass
compound
Prior art date
Application number
PCT/CN2018/121001
Other languages
English (en)
French (fr)
Inventor
庞国芳
陈辉
常巧英
韩奎国
张紫娟
范春林
吴兴强
白若镔
Original Assignee
中国检验检疫科学研究院
北京合众恒星检测科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from CN201810337240.9A external-priority patent/CN108760909A/zh
Application filed by 中国检验检疫科学研究院, 北京合众恒星检测科技有限公司 filed Critical 中国检验检疫科学研究院
Priority to US16/314,599 priority Critical patent/US11169128B2/en
Publication of WO2019200947A1 publication Critical patent/WO2019200947A1/zh

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/04Preparation or injection of sample to be analysed
    • G01N30/06Preparation

Definitions

  • the invention designs an electronic identity database and a detection method for pesticide compounds in edible agricultural products based on LC ⁇ Q ⁇ Orbitrap, and the invention can realize non-target, multi-index and rapid screening for more than 500 pesticide residues in various edible agricultural products.
  • the analysis of pesticide residues is mainly based on gas chromatography, liquid chromatography, gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry.
  • These detection techniques first need to be qualitatively compared to pesticide standards. For example, the detection of 100 pesticides requires the preparation of the corresponding 100 pesticide standard controls, and these 100 pesticides will be missed. In the actual work of pesticide residue laboratories, most laboratories do not stock hundreds of pesticide standards. The reason is that pesticide standards are not only expensive, but also valid for only 2 or 3 years, requiring repeated investment. There are only a few dozen standard pesticide standards in the laboratory, and the number of pesticides that are routinely monitored is limited to these dozens, which leads to food safety monitoring loopholes.
  • the invention solves the problem that the simultaneous detection of multiple pesticides can not be realized in the current pesticide residue screening technology method, and develops a high-throughput high-resolution liquid chromatography-quadrupole-electrostatic field orbitrap mass spectrometry (LC- Q-Orbitrap) New technology for the electronic identity database and detection method of pesticides for edible agricultural products, which enables rapid screening and detection of more than 500 pesticide residues in agricultural products without the need for standard product comparison, meeting the high pesticide residues in current agricultural products. Urgent need for rapid flux detection.
  • LC- Q-Orbitrap liquid chromatography-quadrupole-electrostatic field orbitrap mass spectrometry
  • An electronic identity database of a pesticide compound based on LC-Q-Orbitrap comprising a plurality of pesticide compound electronic identification cards, including pesticide compound information, retention time, additive ion information, fragment ion information, collision energy, and Optimal full scan mass spectrum;
  • the pesticide compound information includes a compound name, a compound molecular formula
  • the retention time of the pesticide compound under specified chromatographic mass spectrometry conditions was measured by a LC-Q-Orbitrap instrument in a Full MS/ddMS 2 mode to determine the ionized form of the pesticide compound ESI source (+H, +NH 4 , + Na) and the molecular formula of the compound, obtaining the exact mass of the ion of the pesticide compound;
  • the full-scan mass spectrum of the fragment ions is collected under multiple different collision energies, and the optimal full-scan mass spectrum rich in ion information is selected.
  • the optimal full-scan mass spectrum means that the additive ion abundance ratio is 10%-20 %, selecting 3-5 fragment ions having the largest ion abundance ratio in the optimal full scan mass spectrum, and recording the collision energy value;
  • the fragment ion information is a theoretical accurate mass and abundance ratio of fragment ions under the optimal full scan mass spectrum
  • the abundance ratio refers to the signal intensity ratio of the ion to the strongest fragment ion of the signal in the mass spectrum.
  • the database is sorted by retention time in the electronic ID card.
  • the electronic identity further comprises a smart matching model database, adding intelligence matching model matching value P m in the electronic ID card, which is a calculation model:
  • M b is the theoretical exact mass of the additive ion
  • M i is the exact mass of the i-th fragment ion
  • W i is the weight of the i-th fragment ion
  • I i is the ion abundance ratio of the i-th fragment ion
  • the order of the fragment ions is from the largest to the smallest of the ion abundance ratio
  • W b is the weight of the additive ions
  • W q is the integrated weight of the fragment ions
  • n is the number of fragment ions.
  • X i is the mass of the i-th fragment ion element
  • n is the number of elements of the fragment ion
  • y i is the number of elements corresponding to the i-th fragment ion.
  • X 1 , X 2 ... X n is the mass of the fragment ion element
  • y' 1 , y′ 2 , ... y′ n are the number of corresponding elements of the preferred fragment ion element composition.
  • chromatographic mass spectrometry conditions are:
  • Chromatographic conditions separation by liquid chromatography system with reversed-phase chromatography column (Accucore aQ 150 ⁇ 2.1 mm, 2.6 ⁇ m); mobile phase A was 5 mM ammonium acetate-0.1% formic acid-water; mobile phase B was 0.1% Formic acid-methanol; gradient elution procedure, 0 min: 1% B, 3 min: 30% B, 6 min: 40% B, 9 min: 40% B, 15 min: 60% B, 19 min: 90% B, 23 min: 90% B , 23.01min: 1% B, after running for 4 min; flow rate is 0.4 mL / min; column temperature: 40 ° C; injection amount: 5 ⁇ L;
  • Mass spectrometry conditions Scan mode: Full MS-ddMS 2 ; Full MS scan range: 70-1050 m/z; Resolution: 70,000, Full MS; 17,500, MS/MS; AGC: Full MS, 1e6; MS/MS, 1e5; IT: Full MS, 200ms; MS/MS, 60ms; Loop count: 1; MSX count: 1; Isolation width: 2.0m/z; NCE (Stepped NCE): 40 (50%); Under fill ratio: 1%; Apex trigger: 2-6s; Dynamic Exclusion: 5s; collection and processing of mass spectrometry results by TraceFinder software.
  • a method for detecting pesticide compounds in edible agricultural products based on LC-Q-Orbitrap comprising:
  • the sample to be tested is acidified and acetonitrile is homogenized and extracted, dehydrated, centrifuged, concentrated, and then purified by solid phase extraction column (SPE), and the residual pesticide is eluted by acetonitrile + toluene solution, and concentrated and filtered to prepare a sample solution;
  • SPE solid phase extraction column
  • ⁇ T is the absolute value of the difference between the retention time of the unknown and the retention time of any pesticide compound in the database
  • P c is the intelligent matching value of the unknown, and the intelligent matching value of any pesticide compound in the P i database.
  • sample further includes the following pretreatment:
  • the LC-Q-Orbitrap residue screening technique established by the present invention can correspond to the compound in the electronic identity database of the pesticide compound according to the retention time, the exact mass number, the ion abundance ratio, the collision energy and the like of the target compound.
  • the alignment is searched to give the matching degree of the target compound.
  • Qualitative screening of pesticides is achieved based on the matching of target compounds.
  • the collision energy is innovatively increased, and the acquisition and data extraction of the optimal full-scan mass spectrum are realized by the adjustment of the collision energy, which improves the accuracy of the data.
  • the additive ion is selected.
  • the mass spectrum with a ratio of 10%-20% is the optimal mass spectrum, which ensures that the additive ions are produced after the collision of the ions, and the presence of the additive ions is also ensured.
  • the LC-Q-Orbitrap residue screening technology method established by the invention adopts Full MS/dd MS2 mode injection analysis, and can obtain chromatograms of specified pesticides under the specified chromatographic mass spectrometry by one injection analysis. Mass spectrometry shortens sample analysis time and improves sample detection efficiency.
  • the LC-Q-Orbitrap residue screening technology established by the present invention and more than 80% of the more than 500 pesticides screened at the same time have a pesticide screening sensitivity lower than the standard of 10 ⁇ g/kg, which satisfies the pesticides of various countries. Residual MRL level screening requirements, the quality accuracy of this screening technology is less than 5ppm, greatly reducing the false positive detection results, and better meet the multi-residue, high-precision pesticide residue screening requirements.
  • the present invention calculates an intelligent matching value for fast and automatic comparison for each compound.
  • the intelligent matching value takes into account the information of the exact mass and the ion abundance ratio, and the ion abundance according to the difference between the added ions and the different fragment ions. Compared with the influence of the ion fragment with a large difference, the introduction of the intelligent matching value changes the original deficiency based on human judgment, can achieve accurate braking matching, and truly realize the automation of detection.
  • Step NCE is a typical secondary mass spectrum at 20, 40, 60
  • Figure 1 shows the LC-Q-Orbitrap pesticide chemical contaminant mass spectrometry database establishment process. The content of the invention has been described in detail. The following is a detailed introduction of the establishment process of pesticide compound electronic ID card by Benalaxyl:
  • Chromatographic conditions separation by liquid chromatography system with reversed-phase chromatography column (Accucore aQ 150 ⁇ 2.1 mm, 2.6 ⁇ m); mobile phase A was 5 mM ammonium acetate-0.1% formic acid-water; mobile phase B was 0.1% Formic acid-methanol; gradient elution procedure, 0 min: 1% B, 3 min: 30% B, 6 min: 40% B, 9 min: 40% B, 15 min: 60% B, 19 min: 90% B, 23 min: 90% B , 23.01min: 1% B, after running for 4 min; flow rate is 0.4 mL / min; column temperature: 40 ° C; injection amount: 5 ⁇ L;
  • Mass spectrometry conditions Scan mode: Full MS-ddMS 2 ; Full MS scan range: 70-1050 m/z; Resolution: 70,000, Full MS; 17,500, MS/MS; AGC: Full MS, 1e6; MS/MS, 1e5; IT: Full MS, 200ms; MS/MS, 60ms; Loop count: 1; MSX count: 1; Isolation width: 2.0m/z; NCE (Stepped NCE): 40 (50%); Under fill ratio: 1%; Apex trigger: 2-6s; Dynamic Exclusion: 5s; collection and processing of mass spectrometry results by TraceFinder software.
  • the five actual measured secondary fragments are 148.11212, 91.05415, 121.08865, 208.13303 and 294.14871, thus combining structural information and
  • the molecular formula can determine the theoretical values of its five secondary fragments, which are 148.11208 (C 10 H 14 N, abundance ratio 100.00%), 91.05423 (C 7 H 7 , abundance ratio 85.34%), 121.0886 (C 8 H 11 N, abundance ratio 47.17%), 208.13364 (C 12 H 18 O 2 N, abundance ratio 13.40%) and 294.14886 (C 19 H 20 O 2 N, abundance ratio 5.65%).
  • Figure 7 shows the method for electronic detection of pesticides proposed by the present invention, which can simultaneously sample more than 500 kinds of pesticides by preparing samples at one time; canceling the reference of the standard products, and qualitatively identifying by electronic standards, realizing the use of electronic identification cards for real objects
  • the standard also achieves a leap-forward development from targeted detection to non-targeted screening. It saves resources, reduces pollution, improves analysis speed, and fully meets the requirements of green development, environmental friendliness, and clean and efficient.
  • Table 1 gives an example of five electronic ID cards representing pesticide compounds in the LC-Q-Orbitrap electronic identity database (without molecular formula), and Table 2 gives a list of more than 500 pesticides in the LC-Q-Orbitrap electronic identity database.
  • the chicken heart bottle with the sample was rinsed with 2 mL of acetonitrile-toluene solution, and the washing liquid was transferred to a purification column and repeated twice; the column was connected with a 25 mL reservoir and eluted with 25 mL of acetonitrile-toluene solution. After the collection was completed, the mixture was rotary evaporated to about 0.5 mL.
  • Nitrogen was blown to near dryness, added with 1 mL of acetonitrile-water solution, sonicated and filtered through a 0.22 ⁇ m nylon membrane for LC-Q-Orbitrap detection. .
  • the compound was separated by a liquid chromatography system equipped with a reverse phase chromatography column (Accucore aQ 150 x 2.1 mm, 2.6 ⁇ m); mobile phase A was 5 mM ammonium acetate-0.1% formic acid-water; mobile phase B was 0.1% formic acid- Methanol; gradient elution procedure, 0 min: 1% B, 3 min: 30% B, 6 min: 40% B, 9 min: 40% B, 15 min: 60% B, 19 min: 90% B, 23 min: 90% B, 23.01 Min: 1% B, after running for 4 min; flow rate was 0.4 mL/min; column temperature: 40 ° C; injection volume: 5 ⁇ L.
  • Mass spectrometry conditions Scan mode: Full MS-ddMS 2 ; Full MS scan range: 70-1050 m/z; Resolution: 70,000, Full MS; 17,500, MS/MS; AGC: Full MS, 1e6; MS/MS, 1e5; IT: Full MS, 200ms; MS/MS, 60ms; Loop count: 1; MSX count: 1; Isolation width: 2.0m/z; NCE (Stepped NCE): 40 (50%); Under fill ratio: 1%; Apex trigger: 2-6s; Dynamic Exclusion: 5s.
  • the mass spectrometry results were collected and processed by TraceFinder software to obtain a chromatogram of the apple sample under the specified chromatographic mass spectrometry conditions.
  • Example 1 The sample pretreatment step, the LC-Q-Orbitrap operating conditions, and the pesticide residue screening process in the sample are all referred to in Example 1.
  • LC-Q-Orbitrap screening and confirmation techniques for more than 500 pesticides (such as the pesticides described above) in commercially available cabbage.
  • Example 1 The sample pretreatment step, the LC-Q-Orbitrap operating conditions, and the pesticide residue screening process in the sample are all referred to in Example 1.

Landscapes

  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Other Investigation Or Analysis Of Materials By Electrical Means (AREA)

Abstract

一种基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法。电子身份数据库包含多种农药化合物电子身份证信息的集合、智能匹配值和碰撞能量,并按照电子身份证中的按保留时间进行排序,其中电子身份证包括农药化合物信息、保留时间、加合离子信息、碎片离子信息、碰撞能量和最优全扫描质谱图;检测方法包括样品前处理步骤、LC-Q-Orbitrap操作条件设置和样品中农药残留筛查过程;其中LC-Q-Orbitrap操作条件包括设置合适的色谱条件和质谱条件,农药筛查过程中首先利用保留时间查找农药化合物电子身份数据库,若匹配则提取对应电子身份证信息,比较智能匹配值,若相同则记录和显示结果,筛查完成。

Description

基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法 技术领域
本发明设计基于LC‐Q‐Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法,该发明能实现针对多种食用农产品中500多种农药残留的非靶标、多指标、快速筛查。
背景技术
早在1976年世界卫生组织(WHO)、粮农组织(FAO)和联合国环境规划署(UNEP)共同建立了全球环境检测系统/食品项目(GlobalEnvironmentMonitoringSystem,GEMS/Food),旨在掌握会员国食品污染状况,了解食品污染物摄入量,保护人体健康,促进贸易发展。现在,世界各国都把食品安全提升到国家安全的战略地位。农药残留限量是食品安全标准之一,也是国际贸易准入门槛。同时,对农药残留的要求呈现出品种越来越多,限量越来越严格的发展趋势,也就是国际贸易设立的农药残留限量门槛越来越高。例如,欧盟、日本和美国分别制定了169068项(481种农药),44340项(765种农药),13055项(395种农药)农药残留限量标准,我国2016年发布了433种农药的4140项MRL标准。目前,国际上普遍采用的一律标准限量为10μg/kg。因此,食品安全和国际贸易都呼唤高通量快速农药残留检测技术,这无疑也给广大农药残留分析工作者提供了机遇和挑战。在目前的众多农药残留分析技术中,色谱质谱联用技术是实现高通量多残留快速检测的最佳分析手段。
目前农药残留分析多以气相色谱、液相色谱、气相色谱-质谱和液相色谱-质谱联用技术为主。这些检测技术都首先需要农药标准品对照进行定性。例如,对100种农药的检测就需要准备相应的100种农药标准品对照,而这100种之外的农药都会被漏检。在农药残留实验室的实际工作中,绝大多数实验室都不会储备数百种农药标准品,其原因是农药标准品不仅价格昂贵,而且有效期只有2、3年,需要重复投资。一般实验室常备农药标准品只有几十种,其日常监测的农药品种也就只限于这几十种,由此造成食品安全监测漏洞。
本发明人团队经过多年潜心研究,基于LC-Q-Orbitrap,研发了500多种农药的精确质量质谱数据库以及农药残留筛查技术方法,实现了不需标准品对照、 即可同时对农产品中500多种农药残留快速筛查,满足了当前农产品中农药残留高通量快速检测的急需。
发明内容
本发明针对目前农药残留筛查技术方法中无法实现对多种农药同时快速检测的问题,开发了一种基于高通量高分辨率液相色谱-四极杆-静电场轨道阱质谱(LC-Q-Orbitrap)新技术的食用农产品农药化合物电子身份数据库及检测方法,实现了不需标准品对照、即可同时对农产品中500多种农药残留快速筛查检测,满足了当前农产品中农药残留高通量快速检测的急需。
本发明的技术方案如下:
一种基于LC-Q-Orbitrap的农药化合物的电子身份数据库,包括多个农药化合物电子身份证,所述电子身份证包括农药化合物信息、保留时间、加合离子信息、碎片离子信息、碰撞能量和最优全扫描质谱图;
所述农药化合物信息包括化合物名称、化合物分子式;
通过LC-Q-Orbitrap仪器在Full MS/ddMS 2模式下测量所述农药化合物指定色谱质谱条件下的保留时间,确定所述农药化合物ESI源下的离子化形式(+H、+NH 4、+Na)及化合物分子式,得到农药化合物加合离子的精确质量数;
在多次不同碰撞能量下,采集碎片离子的全扫描质谱图,选择离子信息丰富的最优全扫描质谱图,所述最优全扫描质谱图是指加合离子丰度比是10%-20%,在所述最优全扫描质谱图中选择离子丰度比最大的3-5个碎片离子,记录该碰撞能量值;
所述碎片离子信息是在所述最优全扫描质谱图下的碎片离子理论精确质量数和丰度比;
所述丰度比是指质谱图中该离子与信号最强碎片离子的信号强度比。
所述数据库按照电子身份证中的按保留时间进行排序。
进一步,所述电子身份数据库还包括智能匹配模型,匹配模型在所述电子身份证中增加智能匹配值P m,其计算模型为:
Figure PCTCN2018121001-appb-000001
Figure PCTCN2018121001-appb-000002
W b+W q=1;
其中M b为加和离子的理论精确质量数,M i为第i个碎片离子的精确质量数, W i为第i个碎片离子的权重,I i为第i个碎片离子的离子丰度比,碎片离子的排列顺序为离子丰度比的从大到小;W b为加和离子的权重,W q为碎片离子的综合权重,n为碎片离子的个数。
进一步,所述W b,W q可根据智能匹配模型的变化进行调整,一般取值为W b=W q=0.5。
进一步,所述碎片离子的理论精确质量数的确定方法为:
1)根据化合物分子式,明确碎片离子元素组成;
2)根据质谱图中碎片离子的质量数M,通过计算获得可能的碎片离子元素组成列表;
Figure PCTCN2018121001-appb-000003
其中:X i为第i个碎片离子元素质量数,n为碎片离子的元素数,y i为第i个碎片离子对应元素的个数。
3)通过分子结构的裂解机理从碎片离子元素组成列表中选择合理的碎片离子元素组成,并计算其理论精确质量M′。
M′=X 1y′ 1+X 2y′ 2+…+X ny′ n
其中:X 1、X 2……X n为所述碎片离子元素质量数,y′ 1、y′ 2、……y′ n为优选碎片离子元素组成的对应元素的个数。
进一步,所述色谱质谱条件为:
色谱条件:通过液相色谱系统进行分离,配有反相色谱柱(Accucore aQ 150×2.1mm,2.6μm);流动相A为5mM的乙酸铵-0.1%甲酸-水;流动相B为0.1%甲酸-甲醇;梯度洗脱程序,0min:1%B,3min:30%B,6min:40%B,9min:40%B,15min:60%B,19min:90%B,23min:90%B,23.01min:1%B,后运行4min;流速为0.4mL/min;柱温:40℃;进样量:5μL;
质谱条件:扫描模式:Full MS-ddMS 2;Full MS scan range:70-1050m/z;Resolution:70,000,Full MS;17,500,MS/MS;AGC:Full MS,1e6;MS/MS,1e5;Max IT:Full MS,200ms;MS/MS,60ms;Loop count:1;MSX count:1;Isolation width:2.0m/z;NCE(Stepped NCE):40(50%);Under fill ratio:1%;Apex trigger:2-6s;Dynamic Exclusion:5s;通过TraceFinder软件对质谱检测结果采集与处理。
一种基于LC-Q-Orbitrap的食用农产品中农药化合物检测方法,包括:
1)将待检测样品酸化乙腈匀浆提取,经脱水和离心、浓缩后,再经固相萃取柱(SPE)净化,乙腈+甲苯溶液洗脱残留农药,经浓缩、过滤后制成样品溶液;
2)通过LC-Q-Orbitrap仪器在Full MS/ddMS 2模式下获得样品溶液指定色谱质谱条件下的色谱图;
3)通过LC-Q-Orbitrap仪器在Full MS/ddMS 2模式下获得样品溶液指定色谱质谱条件下的色谱图和质谱图,从而获得色谱图中的保留时间和加合离子的精确质量数信息,以及对应最佳碰撞能量下得到的碎片离子和质谱图,并记录该保留时间对应的未知物的电子身份证;
4)依次将未知物电子身份证与权利要求2中的电子身份数据库中每个农药化合物的电子身份证比较,如果ΔT≤0.3并且ΔP≤10%,则记录该农药化合物,如果ΔT≤0.3并且10%<ΔP≤30%,则通过质谱图中质谱峰的高度和重合度确定度判断是否包括该农药化合物,否则进入下一个未知物电子身份证的比较;
5)检测完成,显示样品溶液中所含农药化合物的信息;
其中ΔT为未知物保留时间与数据库中任一农药化合物保留时间的差值的绝对值,
Figure PCTCN2018121001-appb-000004
其中P c为未知物智能匹配值,P i数据库中任一农药化合物智能匹配值。
进一步,所述样品还包括如下前处理:
称取10.0g样品(精确到0.01g)于100mL离心管中,加入30~40mL酸化乙腈提取液,10000~11000rpm均质1~2min;加入无水硫酸镁和氯化钠(质量比,4:1),振荡8~10min;4200rpm离心5~7min后,取15~20mL上清液于150mL鸡心瓶中,40℃水浴加热旋转蒸发至1~2mL,待净化;
使用CarbonNH2柱,在CarbonNH2柱内加入约1~2cm高的无水硫酸钠,用5~6mL乙腈-甲苯溶液预洗SPE净化柱,同时轻敲净化柱排出柱内气泡,净化柱下方流出液弃置。待液面略高于硫酸钠顶部时,将浓缩液转移入净化柱,下接50mL鸡心瓶。用2~3mL乙腈-甲苯溶液冲洗沾有样品的鸡心瓶,将洗涤液转移至净化柱内,重复2~3次;柱上接25mL储液器,以25~30mL乙腈-甲苯溶液洗脱。收集完毕后旋转蒸发至约0.5mL,氮吹至近干,加入1mL乙腈-水溶液, 超声溶解后经0.22μm尼龙膜过滤。
本发明的有益效果:
1、利用LC-Q-Orbitrap技术获得农药化合物的电子身份证信息、以及利用电子身份证信息组件农药化合物电子身份数据库,创新性地建立了500多种农药精确质量可达到0.00001m/z的数据库,以电子标准取代农药实物标准,实现高精度、高效率、节约资源的非靶标农药残留检测。以农药电子身份证为电子标准的筛查方法取代农药实物标准做参比的传统鉴定方法,实现了非靶标农药残留检测技术的跨跃发展。
2、创新性地建立了以高分辨精确质量数、离子丰度比等化合物质谱信息为识别标准的,依据农药化合物电子身份数据库对500多种农药进行筛查和确证的LC-Q-Orbitrap技术方法;这一技术彻底改变了原有以化合物标准物为参比的定性模式,是一种不需要标准物对照,快速、高通量、准确可靠的农药残留检测新技术。取消了标准品做参比,而凭电子标准定性鉴定,实现了以电子身份证代替实物标准的传统方法,同时也实现了从靶向检测向非靶向筛查的跨跃式发展。节省了资源,减少了污染,提高了分析速度,完全达到了绿色发展、环境友好和清洁高效的要求。
3、本发明建立的LC-Q-Orbitrap残留筛查技术方法能够依据目标化合物的保留时间、精确质量数、离子丰度比、碰撞能量等信息,通过与农药化合物电子身份数据库中化合物的对应信息检索比对,给出目标化合物的匹配度。依据目标化合物的匹配情况,实现对农药的定性筛查。在数据库中创新性的增加了碰撞能量,通过碰撞能量的调整实现对最优全扫描质谱图的采集和数据提取,提高了数据的准确性,在最佳碰撞能量选择时,选择加合离子丰度比是10%-20%的质谱图为最优质谱图,这样既确保加和离子经碰撞后生产相关碎片离子,也保证加和离子的存在。
4、本发明建立的LC-Q-Orbitrap残留筛查技术方法,采用Full MS/dd MS2模式进样分析,通过一次进样分析即可获得500多种农药的指定色谱质谱条件下的色谱图和质谱图,缩短了样品分析时间,提高了样品检测效率。
5、本发明建立的LC-Q-Orbitrap残留筛查技术方法,同时筛查的500多种农药中,超过80%的农药筛查灵敏度低于一律标准10微克/千克,较好地满足各国 农药残留MRL水平筛查的要求,这种筛查技术质量精度均在5ppm以内,极大地降低了假阳性检出结果,较好的满足多残留、高精度的农药残留筛查要求。
6、本发明为每种化合物计算出快速自动比较的智能匹配值,智能匹配值兼顾了精确质量数和离子丰度比的信息,并根据加和离子和不同碎片离子间差异化的离子丰度比突出差距较大的离子碎片的影响,通过智能匹配值的引入改变了原有的根据人为判断的不足,能够实现精确的制动匹配,真正实现检测的自动化。
附图说明
图1 LC-Q-Orbitrap农药化学污染物质电子身份证模型
图2 Benalaxyl的[M+H]+一级质谱图
图3 Benalaxyl[M+H]+归一化法能量NCE为20时典型的二级质谱图
图4 Benalaxyl[M+H]+归一化法能量NCE为40时典型的二级质谱图
图5 Benalaxyl[M+H]+归一化法能量NCE为60时典型的二级质谱图
图6 Benalaxyl[M+H]+阶梯归一化法能量Step NCE为20,40,60时典型的二级质谱图
图7 LC-Q-Orbitrap农药残留筛查流程
具体实施方式
下面结合附图和具体实施例对本发明作进一步说明。
图1表示LC-Q-Orbitrap农药化学污染物质谱数据库建立流程,发明内容部分已详细说明,下面以Benalaxyl为例,对农药化合物电子身份证的建立过程进行详细介绍:
色谱条件:通过液相色谱系统进行分离,配有反相色谱柱(Accucore aQ 150×2.1mm,2.6μm);流动相A为5mM的乙酸铵-0.1%甲酸-水;流动相B为0.1%甲酸-甲醇;梯度洗脱程序,0min:1%B,3min:30%B,6min:40%B,9min:40%B,15min:60%B,19min:90%B,23min:90%B,23.01min:1%B,后运行4min;流速为0.4mL/min;柱温:40℃;进样量:5μL;
质谱条件:扫描模式:Full MS-ddMS 2;Full MS scan range:70-1050m/z;Resolution:70,000,Full MS;17,500,MS/MS;AGC:Full MS,1e6;MS/MS,1e5;Max IT:Full MS,200ms;MS/MS,60ms;Loop count:1;MSX count:1;Isolation width:2.0m/z;NCE(Stepped NCE):40(50%);Under fill ratio:1%;Apex trigger: 2-6s;Dynamic Exclusion:5s;通过TraceFinder软件对质谱检测结果采集与处理。
在Full MS/dd MS 2模式下对其溶剂标准进行测定,其分子式为C20H23NO3,提取其一级信息发现其加合离子为[M+H] +峰,其精确质量数为326.17507见图2。为了了解Benalaxyl的二级碎片信息,分别在NCE=20(见图3),NCE=40(见图4),NCE=60(见图5)和stepNCE=20,40,60(见图6)时运行采集方法,根据Benalaxyl的化学性质,结合其在不同NCE下的二级谱图,可以推断其5个实际测定的二级碎片分别为148.11212,91.05415,121.08865,208.13303和294.14871从而结合结构式信息和分子式可以对其5个二级碎片的理论值进行确定,分别为148.11208(C 10H 14N,丰度比100.00%),91.05423(C 7H 7,丰度比85.34%),121.0886(C 8H 11N,丰度比47.17%),208.13364(C 12H 18O 2N,丰度比13.40%)和294.14886(C 19H 20O 2N,丰度比5.65%)。计算Benalaxyl的智能匹配值P m为:
Figure PCTCN2018121001-appb-000005
按照图1建立其电子身份证并存入电子身份数据库。
图7表示本发明提出的农药检测电子化方法中,一次制备样品,可同时筛查500多种农药;取消了标准品做参比,而凭电子标准定性鉴定,实现了以电子身份证替实物标准,同时也实现了从靶向检测向非靶向筛查的跨跃式发展。节省了资源,减少了污染,提高了分析速度,完全达到了绿色发展、环境友好和清洁高效的要求。
表1给出了LC-Q-Orbitrap电子身份数据库中5种代表农药化合物电子身份证示例(不含分子式),表2给出了LC-Q-Orbitrap电子身份数据库中500多种农药清单。
表1 LC-Q-Orbitrap5种代表农药化合物电子身份证示例(不含分子式)
Figure PCTCN2018121001-appb-000006
Figure PCTCN2018121001-appb-000007
表2 500多种农药清单
Figure PCTCN2018121001-appb-000008
Figure PCTCN2018121001-appb-000009
Figure PCTCN2018121001-appb-000010
Figure PCTCN2018121001-appb-000011
Figure PCTCN2018121001-appb-000012
Figure PCTCN2018121001-appb-000013
Figure PCTCN2018121001-appb-000014
Figure PCTCN2018121001-appb-000015
Figure PCTCN2018121001-appb-000016
Figure PCTCN2018121001-appb-000017
Figure PCTCN2018121001-appb-000018
Figure PCTCN2018121001-appb-000019
Figure PCTCN2018121001-appb-000020
Figure PCTCN2018121001-appb-000021
Figure PCTCN2018121001-appb-000022
实施例
实施例1
市售苹果中500多种农药(如前述说明的农药)LC-Q-Orbitrap筛查和确证技术实施实例。
1、样品前处理技术的具体步骤:
1.1苹果样品取可食部分切碎,混匀,密封,标明标记;
1.2称取10g苹果样品(精确至0.01g),于100mL离心管中,加入40mL1%醋酸乙腈提取液,10000rpm均质1min。加入无水硫酸镁和氯化钠(质量比,4:1),振荡10min。4200rpm离心5min后,取20mL上清液于150mL鸡心瓶中,40℃水浴加热旋转蒸发至1mL,待净化;
1.3在SPE柱内加入约2cm高的无水硫酸钠,用5mL乙腈-甲苯溶液预洗SPE净化柱,同时轻敲净化柱排出柱内气泡,净化柱下方流出液弃置。待液面略高于硫酸钠顶部时,将浓缩液转移入净化柱,下接50mL鸡心瓶。用2mL乙腈-甲苯溶液冲洗沾有样品的鸡心瓶,将洗涤液转移至净化柱内,重复2次;柱上接25mL储液器,以25mL乙腈-甲苯溶液洗脱。收集完毕后旋转蒸发至约0.5mL。
1.4氮吹至近干,加入1mL乙腈-水溶液,超声溶解后经0.22μm尼龙膜过滤,供LC-Q-Orbitrap检测。。
2、LC-Q-Orbitrap操作条件
化合物通过液相色谱系统进行分离,配有反相色谱柱(Accucore aQ 150×2.1mm,2.6μm);流动相A为5mM的乙酸铵-0.1%甲酸-水;流动相B为0.1%甲酸-甲醇;梯度洗脱程序,0min:1%B,3min:30%B,6min:40%B,9min:40%B,15min:60%B,19min:90%B,23min:90%B,23.01min:1%B,后运行4min;流速为0.4mL/min;柱温:40℃;进样量:5μL。
质谱条件:扫描模式:Full MS-ddMS 2;Full MS scan range:70-1050m/z;Resolution:70,000,Full MS;17,500,MS/MS;AGC:Full MS,1e6;MS/MS,1e5;Max IT:Full MS,200ms;MS/MS,60ms;Loop count:1;MSX count:1;Isolation width:2.0m/z;NCE(Stepped NCE):40(50%);Under fill ratio:1%;Apex trigger:2-6s;Dynamic Exclusion:5s。通过TraceFinder软件对质谱检测结果采集与处理,获得苹果样品指定色谱质谱条件下的色谱图。
3、按顺序提取色谱图中的保留时间和对应加和离子的精确质量数,检索电子身份数据库中,记录与所述保留时间和对应加和离子精确质量数的电子身份证信息,则用数据库中对应的碰撞能量轰击得到质谱图,建立所有保留时间对应的苹果样品疑似农药的电子身份证;
4)依次将苹果样品疑似农药的电子身份证与电子身份数据库中每个农药化合物的电子身份证比较,如果ΔT≤0.3并且ΔP≤10%,则记录该农药化合物,否则进入下一个疑似农药的电子身份证的比较;
5)检测完成,显示样品溶液中所含农药化合物的信息;
某省会城市苹果样品中LC-Q-Orbitrap筛查结果:.
采集某省会城市市售苹果样品18个,应用LC-Q-Orbitrap技术对500多种农药残留进行筛查,检出15种农药残留,共计62频次,涉及样品14个,具体结果见表3。
表3 某地区苹果样品中农药残留LC-Q-Orbitrap筛查结果
Figure PCTCN2018121001-appb-000023
实施例2
市售柠檬中500多种农药(如前述说明的农药)LC-Q-Orbitrap筛查和确证技术实施实例。
样品前处理步骤、LC-Q-Orbitrap操作条件和样品中农药残留筛查过程均参照实施例1。
某省会城市柠檬样品中LC-Q-Orbitrap筛查结果:.
采集某省会城市市售柠檬样品13个,应用LC-Q-Orbitrap技术对500多种农药残留进行筛查,检出9种农药残留,共计53频次,涉及样品10个,具体结果见表4。
表4 某地区柠檬样品中农药残留LC-Q-Orbitrap筛查结果
Figure PCTCN2018121001-appb-000024
Figure PCTCN2018121001-appb-000025
实施例3
市售结球甘蓝中500多种农药(如前述说明的农药)LC-Q-Orbitrap筛查和确证技术实施实例。
样品前处理步骤、LC-Q-Orbitrap操作条件和样品中农药残留筛查过程均参照实施例1。
某省会城市结球甘蓝样品中LC-Q-Orbitrap筛查结果:
采集某省会城市市售结球甘蓝样品25个,应用LC-Q-Orbitrap技术对500多种农药残留进行筛查,检出18种农药残留,共计121频次,涉及样品21个,具体结果见表5。
表5 某地区结球甘蓝样品中农药残留LC-Q-Orbitrap筛查结果
Figure PCTCN2018121001-appb-000026
Figure PCTCN2018121001-appb-000027
上文所列出的一系列的详细说明仅仅是针对本发明的可行性实施方式的具体说明,它们并非用以限制本发明的保护范围,凡未脱离本发明技艺精神所作的等效实施方式或变更均应包含在本发明的保护范围之内。

Claims (8)

  1. 一种基于LC-Q-Orbitrap的食用农产品中农药化合物的电子身份数据库,其特征在于,包括多个农药化合物电子身份证,所述电子身份证包括农药化合物信息、保留时间、加合离子信息、碎片离子信息、碰撞能量和最优全扫描质谱图;
    所述农药化合物信息包括化合物名称、化合物分子式;
    通过LC-Q-Orbitrap仪器在Full MS/ddMS 2模式下测量所述农药化合物指定色谱质谱条件下的保留时间,确定所述农药化合物ESI源下的离子化形式(+H、+NH 4、+Na)及化合物分子式,得到农药化合物加合离子的精确质量数;
    在多次不同碰撞能量下,采集碎片离子的全扫描质谱图,选择离子信息丰富的最优全扫描质谱图,所述最优全扫描质谱图是指加合离子丰度比是10%-20%,在所述最优全扫描质谱图中选择离子丰度比最大的3-5个碎片离子,记录该碰撞能量值;
    所述碎片离子信息是在所述最优全扫描质谱图下的碎片离子理论精确质量数和丰度比;
    所述丰度比是指质谱图中该离子与信号最强碎片离子的信号强度比。
    所述数据库按照电子身份证中的按保留时间进行排序。
  2. 根据权利要求1所述的一种基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库,其特征在于,所述电子身份数据库还包括智能匹配模型,匹配模型在所述电子身份证中增加智能匹配值P m,其计算模型为:
    Figure PCTCN2018121001-appb-100001
    Figure PCTCN2018121001-appb-100002
    W b+W q=1;
    其中M b为加合离子的理论精确质量数,M i为第i个碎片离子的精确质量数,W i为第i个碎片离子的权重,I i为第i个碎片离子的离子丰度比,碎片离子的排列顺序为离子丰度比的从大到小;W b为加合离子的权重,W q为碎片离子的综合权重,n为碎片离子的个数。
  3. 根据权利要求1所述的一种基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库,其特征在于,所述W b,W q可根据智能匹配模型的变化进行调整,一般取值为W b=W q=0.5。
  4. 根据权利要求1所述的一种基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库,其特征在于,所述碎片离子的理论精确质量数的确定方法为:
    1)根据化合物分子式,明确碎片离子元素组成;
    2)根据质谱图中碎片离子的质量数M,通过计算获得可能的碎片离子元素组成列表;
    Figure PCTCN2018121001-appb-100003
    其中:X i为第i个碎片离子元素质量数,n为碎片离子的元素数,y i为第i个碎片离子对应元素的个数。
    3)通过分子结构的裂解机理从碎片离子元素组成列表中选择合理的碎片离子元素组成,并计算其理论精确质量M′。
    M′=X 1y′ 1+X 2y′ 2+…+X ny′ n
    其中:X 1、X 2……X n为所述碎片离子元素质量数,y′ 1、y′ 2、……y′ n为优选碎片离子元素组成的对应元素的个数。
  5. 根据权利要求1所述的一种基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库,其特征在于,所述色谱质谱条件为:
    色谱条件:通过液相色谱系统进行分离,配有反相色谱柱(AccucoreaQ 150×2.1mm,2.6μm);流动相A为5mM的乙酸铵-0.1%甲酸-水;流动相B为0.1%甲酸-甲醇;梯度洗脱程序,0min:1%B,3min:30%B,6min:40%B,9min:40%B,15min:60%B,19min:90%B,23min:90%B,23.01min:1%B,后运行4min;流速为0.4mL/min;柱温:40℃;进样量:5μL;
    质谱条件:扫描模式:Full MS-ddMS 2;Full MS scan range:70-1050m/z;Resolution:70,000,Full MS;17,500,MS/MS;AGC:Full MS,1e6;MS/MS,1e5;Max IT:Full MS,200ms;MS/MS,60ms;Loop count:1;MSX count:1;Isolation width:2.0m/z;NCE(Stepped NCE):40(50%);Under fill ratio:1%;Apex trigger:2-6s;Dynamic Exclusion:5s;通过TraceFinder软件对质谱检测结果采集与处理。
  6. 一种基于LC-Q-Orbitrap的食用农产品中农药化合物检测方法,包括:
    1)将待检测样品酸化乙腈匀浆提取,经脱水和离心、浓缩后,再经固相萃 取柱(SPE)净化,乙腈+甲苯溶液洗脱残留农药,经浓缩、过滤后制成样品溶液;
    2)通过LC-Q-Orbitrap仪器在Full MS/ddMS 2模式下获得样品溶液指定色谱质谱条件下的色谱图和质谱图,从而获得色谱图中的保留时间和加合离子的精确质量数信息,以及对应最佳碰撞能量下得到的碎片离子和质谱图,并记录该保留时间对应的未知物的电子身份证;
    3)依次将未知物电子身份证与权利要求2中的电子身份数据库中每个农药化合物的电子身份证比较,如果ΔT≤0.3并且ΔP≤10%,则记录该农药化合物,否则进入下一个未知物电子身份证的比较;
    4)检测完成,显示样品溶液中所含农药化合物的信息;
    其中ΔT为未知物保留时间与数据库中任一农药化合物保留时间的差值的绝对值,
    Figure PCTCN2018121001-appb-100004
    其中P c为未知物智能匹配值,P i数据库中任一农药化合物智能匹配值。
  7. 如权利要求6所述的一种基于LC-Q-Orbitrap的食用农产品中农药化合物检测方法,其特征在于,步骤4)中如果ΔT≤0.3并且10%<ΔP≤30%,则通过质谱图中质谱峰的高度和重合度确定度判断是否包括该农药化合物。
  8. 如权利要求6所述的一种基于LC-Q-Orbitrap的食用农产品中农药化合物检测方法,其特征在于,
    所述样品还包括如下前处理:
    称取10.0g样品(精确到0.01g)于100mL离心管中,加入30~40mL酸化乙腈提取液,10000~11000rpm均质1~2min;加入无水硫酸镁和氯化钠(质量比,4:1),振荡8~10min;4200rpm离心5~7min后,取15~20mL上清液于150mL鸡心瓶中,40℃水浴加热旋转蒸发至1~2mL,待净化;
    使用CarbonNH2柱,在CarbonNH2柱内加入约1~2cm高的无水硫酸钠,用5~6mL乙腈-甲苯溶液预洗SPE净化柱,同时轻敲净化柱排出柱内气泡,净化柱下方流出液弃置。待液面略高于硫酸钠顶部时,将浓缩液转移入净化柱,下接50mL鸡心瓶。用2~3mL乙腈-甲苯溶液冲洗沾有样品的鸡心瓶,将洗涤液转移至净化柱内,重复2~3次;柱上接25mL储液器,以25~30mL乙腈-甲苯溶液 洗脱。收集完毕后旋转蒸发至约0.5mL,氮吹至近干,加入1mL乙腈-水溶液,超声溶解后经0.22μm尼龙膜过滤。
PCT/CN2018/121001 2018-04-16 2018-12-14 基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法 WO2019200947A1 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US16/314,599 US11169128B2 (en) 2018-04-16 2018-12-14 Electronic ID database and detection method for pesticide compound in edible agro-products based on LC-Q-Orbitrap

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
CN201810337240.9 2018-04-16
CN201810337240.9A CN108760909A (zh) 2017-04-17 2018-04-16 一种食用农产品农药残留非靶标、多指标、快速侦测的电子化方法
CN201811376380.3 2018-11-19
CN201811376380.3A CN109917028B (zh) 2017-04-17 2018-11-19 基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库的建立方法及检测方法

Publications (1)

Publication Number Publication Date
WO2019200947A1 true WO2019200947A1 (zh) 2019-10-24

Family

ID=68240643

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/121001 WO2019200947A1 (zh) 2018-04-16 2018-12-14 基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法

Country Status (1)

Country Link
WO (1) WO2019200947A1 (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113295790A (zh) * 2021-05-20 2021-08-24 中国科学院成都生物研究所 一种畜禽肉及其副产品中兽药化合物残留的检测方法

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2927691A1 (en) * 2014-04-04 2015-10-07 IDCGS clinica de Diagnosticos Medicos Biomarkers for assessing HIV
CN105651917A (zh) * 2015-12-28 2016-06-08 中国检验检疫科学研究院 一种水生类蔬菜中708种农药残留gc-q-tof/ms侦测技术
CN105823832A (zh) * 2015-12-28 2016-08-03 中国检验检疫科学研究院 一种仁果类水果中544种农药残留lc-q-tof/ms侦测技术
CN107077592A (zh) * 2014-03-28 2017-08-18 威斯康星校友研究基金会 高分辨率气相色谱‑质谱数据与单位分辨率参考数据库的改进谱图匹配的高质量精确度滤波
CN107085049A (zh) * 2017-04-17 2017-08-22 中国检验检疫科学研究院 一种食用农产品农药残留非靶标、多指标、快速侦测的电子化方法
CN108760909A (zh) * 2017-04-17 2018-11-06 中国检验检疫科学研究院 一种食用农产品农药残留非靶标、多指标、快速侦测的电子化方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107077592A (zh) * 2014-03-28 2017-08-18 威斯康星校友研究基金会 高分辨率气相色谱‑质谱数据与单位分辨率参考数据库的改进谱图匹配的高质量精确度滤波
EP2927691A1 (en) * 2014-04-04 2015-10-07 IDCGS clinica de Diagnosticos Medicos Biomarkers for assessing HIV
CN105651917A (zh) * 2015-12-28 2016-06-08 中国检验检疫科学研究院 一种水生类蔬菜中708种农药残留gc-q-tof/ms侦测技术
CN105823832A (zh) * 2015-12-28 2016-08-03 中国检验检疫科学研究院 一种仁果类水果中544种农药残留lc-q-tof/ms侦测技术
CN107085049A (zh) * 2017-04-17 2017-08-22 中国检验检疫科学研究院 一种食用农产品农药残留非靶标、多指标、快速侦测的电子化方法
CN108760909A (zh) * 2017-04-17 2018-11-06 中国检验检疫科学研究院 一种食用农产品农药残留非靶标、多指标、快速侦测的电子化方法

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113295790A (zh) * 2021-05-20 2021-08-24 中国科学院成都生物研究所 一种畜禽肉及其副产品中兽药化合物残留的检测方法

Similar Documents

Publication Publication Date Title
CN109917028B (zh) 基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库的建立方法及检测方法
Knolhoff et al. Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry
Causon et al. Fingerprinting of traditionally produced red wines using liquid chromatography combined with drift tube ion mobility-mass spectrometry
CN104797939B (zh) 微生物分析的设备和方法
CN111721857A (zh) 一种运用广泛靶向代谢组学技术鉴别荔枝品种的方法
CN108828051B (zh) 快速蒸发离子化质谱的南极磷虾油的脂质实时检测方法
CN105823832A (zh) 一种仁果类水果中544种农药残留lc-q-tof/ms侦测技术
CN113552247A (zh) 一种样品未知成分的液质联用非靶向分析方法
CN112162054A (zh) 一种沙生槐蜂蜜的真实性评价方法
CN107192770B (zh) 一种鉴别荆条蜜与糖浆掺假荆条蜜的分析方法
CN105486796A (zh) 一种瓜果类水果中544种农药残留lc-q-tof/ms侦测技术
WO2019200947A1 (zh) 基于LC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法
CN111487353B (zh) 高含量泽兰黄酮-4’,7-双葡萄糖苷作为玫瑰蜂花粉特征性标志物的应用
Hawkes et al. High-resolution mass spectrometry strategies for the investigation of dissolved organic matter
CN111337605B (zh) 一种评价荷花蜂花粉真实性的方法
CN105784900A (zh) 一种茄果类蔬菜中544种农药残留lc-q-tof/ms侦测技术
WO2019200946A1 (zh) 基于GC-Q-Orbitrap的食用农产品中农药化合物电子身份数据库及检测方法
Rosnack et al. Screening solution using the software platform UNIFI: an integrated workflow by waters
Deng et al. Quality assessment and origin tracing of Guangdong Liangcha granules using direct mass spectrometry fingerprinting
CN105784898A (zh) 一种柑橘类水果中544种农药残留lc-q-tof/ms侦测技术
CN105675789A (zh) 一种瓜类蔬菜中544种农药残留lc-q-tof/ms侦测技术
CN105486795A (zh) 一种浆果和其它小型水果中708种农药残留gc-q-tof/ms侦测技术
CN105784896A (zh) 一种根茎类和薯芋类蔬菜中544种农药残留lc-q-tof/ms侦测技术
CN105675738A (zh) 一种茎类蔬菜中544种农药残留lc-q-tof/ms侦测技术
CN105675703A (zh) 一种食用菌中544种农药残留lc-q-tof/ms侦测技术

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18915526

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18915526

Country of ref document: EP

Kind code of ref document: A1

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 03/02/2021)

122 Ep: pct application non-entry in european phase

Ref document number: 18915526

Country of ref document: EP

Kind code of ref document: A1