不同品类果蔬中噻虫嗪残留量检测分析数据

农药残留是植物源性食品的主要安全问题之一，近年来果蔬中噻虫嗪农药残留也常有检出，噻虫嗪是一种全新结构的第二代烟碱类高效低毒杀虫剂，对害虫具有胃毒、触杀及内吸活性，用于叶面喷雾及土壤灌根处理。少量的噻虫嗪残留不会引起人体急性中毒，但如果长期接触或大量接触，会对人体造成伤害，引起中毒症状，如头痛、恶心、呕吐、眩晕等。因此通过对果蔬中噻虫嗪残留量的检测分析，能够进一步了解各品类果蔬中噻虫嗪残留情况和风险情况。通过合格率了解易超标的风险品种，通过不合格占比了解年度重点监管品类，从而加强对果蔬中噻虫嗪等农药残留情况的关注，为种植业合理使用农残具有指导意义，也为监管单位进行农药残留专项监管提供数据支持。1、数据采集：根据要求采集果蔬样品并进行样品制备，依据检测方法进行定量分析，获得检测结果值。2、数据处理：通过定量分析获得结果值，依据GB 2763设定标准值，当结果值≤标准值时，判定合格；否则判定不合格；该细类当年合格率=该细类当年检测合格批次数A/该细类当年检测批次N*100%，保留两位小数；总不合格数M为当年果蔬中噻虫嗪不合格数之和，该细类不合格占比=该细类不合格数X/总不合格数M*100%，保留两位小数；该品种不合格占比=该品种不合格数Y/总不合格数M*100%，保留两位小数。当该细类当年合格率≥99.0%时，风险评价=LR，当99%＞该细类当年合格率≥95%时，风险评价=MR，当该细类当年合格率＜95%时，风险评价=HR。3、数据应用：对各果蔬中噻虫嗪残留量进行检测分析，可以了解不同品类果蔬中噻虫嗪残留情况，通过风险评价了解易超标的风险品种，通过不合格占比了解年度监管品类不合格总体情况，从而加强对果蔬中噻虫嗪等农药残留情况的关注，为生产单位合理使用农残具有参考意义，也为监管单位进行农药残留专项监管提供数据支持。

Pesticide residues are one of the major safety concerns for plant-derived foods. In recent years, thiamethoxam residues in fruits and vegetables have been frequently detected. Thiamethoxam is a second-generation neonicotinoid insecticide with a novel structure, featuring high efficiency and low toxicity, and exhibits stomach poison, contact toxicity and systemic activity against pests. It is applied via foliar spraying and soil drenching. Trace amounts of thiamethoxam residues do not cause acute poisoning in humans, but long-term or high-dose exposure may harm human health and induce symptoms such as headache, nausea, vomiting and dizziness. Therefore, detecting and analyzing thiamethoxam residues in fruits and vegetables can further clarify the residue status and risk profile of thiamethoxam across various fruit and vegetable categories. By identifying risk-prone varieties through qualified rates and key annual supervision categories through unqualified proportions, this work can enhance attention to pesticide residues including thiamethoxam in fruits and vegetables, provide guidance for the rational use of pesticides in the planting industry, and offer data support for regulatory authorities to carry out special supervision on pesticide residues.
1. Data Collection: Collect fruit and vegetable samples and prepare them in accordance with requirements, then conduct quantitative analysis per the detection method to obtain test result values.
2. Data Processing: Obtain quantitative analysis results, and set standard values based on "GB 2763". A sample is judged as qualified if the result value ≤ the standard value; otherwise, it is deemed unqualified. The annual qualified rate of a subgroup = (number of qualified batches A of the subgroup in the current year / total number of tested batches N of the subgroup in the current year) × 100%, rounded to two decimal places. The total number of unqualified cases M is the sum of all thiamethoxam-related unqualified cases in fruits and vegetables during the current year. The unqualified proportion of a subgroup = (number of unqualified cases X of the subgroup / total unqualified cases M) × 100%, rounded to two decimal places. The unqualified proportion of a single variety = (number of unqualified cases Y of the variety / total unqualified cases M) × 100%, rounded to two decimal places. Risk assessment is graded as follows: LR when the annual qualified rate of the subgroup ≥ 99.0%, MR when 99% > annual qualified rate of the subgroup ≥ 95%, and HR when the annual qualified rate of the subgroup < 95%.
3. Data Application: Detecting and analyzing thiamethoxam residues in various fruits and vegetables can help understand the residue status of thiamethoxam across different fruit and vegetable categories. By grasping risk-prone varieties through risk assessment and the overall unqualified situation of annual supervision categories through unqualified proportions, this work can enhance attention to pesticide residues including thiamethoxam in fruits and vegetables, provide reference for producers to use pesticides rationally, and offer data support for regulatory authorities to conduct special supervision on pesticide residues.

搜集汇总

背景与挑战

背景概述

该数据集包含2688条记录，每年更新，通过Excel格式存储不同品类果蔬中噻虫嗪农药残留的检测数据，包括样品信息、检测结果、合格率和风险评价。其特点是用于监控农药残留安全，指导种植和监管决策，确保食品健康。