一种用于设施蔬菜及其产品中农药残留和品质劣变因子的筛查方法

By constructing a GC-MS/MS screening database, the problems of pesticide residues and quality deterioration in the whole chain of greenhouse vegetables have been solved, achieving efficient and accurate detection and ensuring the quality and safety of greenhouse vegetables from the field to the table.

CN122409897APending Publication Date: 2026-07-17INST OF QUALITY STANDARD & TESTING TECH FOR AGRO PROD OF CAAS

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
INST OF QUALITY STANDARD & TESTING TECH FOR AGRO PROD OF CAAS
Filing Date
2026-04-30
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies lack a systematic monitoring scheme covering the entire chain from field raw materials to processed finished products, making it impossible to effectively screen for pesticide residues and quality deterioration factors in greenhouse vegetables, resulting in excessive pesticide residues and changes in fatty acids that affect quality and safety.

Method used

A GC-MS/MS screening database was constructed, including sub-databases for pesticide residues and quality deterioration factors. By using GC-MS/MS to test vegetables and their products, and combining the qualitative principles of retention time and ion abundance ratio, rapid and high-throughput detection can be achieved.

Benefits of technology

It enables high-throughput and high-sensitivity detection of pesticide residues and fatty acid changes in greenhouse vegetables, ensuring the accuracy of screening results and providing full-chain quality and safety control.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122409897A_ABST
    Figure CN122409897A_ABST
Patent Text Reader

Abstract

本发明涉及农产品质量安全检测技术领域,具体为一种用于设施蔬菜及其产品中农药残留和品质劣变因子的筛查方法,包括:构建农药残留和品质劣变因子的GC‑MS / MS筛查数据库;针对设施蔬菜鲜样中多种农药残留,以及其加工产品中由脂肪酸变化表征的品质劣变因子,分别进行样品前处理;采用GC‑MS / MS对处理后的样品进行检测;基于构建的数据库和确定的定性原则,对检测结果进行快速筛查与定性分析。本发明首次将设施蔬菜生产过程中的农药残留风险与加工储藏过程中的品质劣变风险进行关联筛查,通过一套核心技术平台,实现了对农药残留和脂肪酸类品质标记物的高通量、高灵敏、快速检测,为设施蔬菜从“田间到餐桌”的全链条质量安全控制提供了有力的技术支撑。
Need to check novelty before this filing date? Find Prior Art