不同品类果蔬中噻虫胺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，近年来果蔬中噻虫胺农药残留也常有检出，噻虫胺是一种新烟碱类杀虫剂，具有内吸性、触杀和胃毒作用。少量的噻虫胺残留不会引起人体急性中毒，但如果长期食用噻虫胺超标的食品，可能会出现恶心、呕吐、头痛、乏力、躁动、抽搐等症状。因此通过对果蔬中噻虫胺残留量的检测分析，能够进一步了解各品类果蔬中噻虫胺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胺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为当年果蔬中噻虫胺不合格数之和，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≥98%时，风险评价=LR，当98%＞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：对各果蔬中噻虫胺残留量进行检测分析，可以了解不同品类果蔬中噻虫胺残留情况，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胺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, clothianidin residues in fruits and vegetables have been frequently detected. Clothianidin is a neonicotinoid insecticide with systemic activity, contact toxicity and stomach toxicity. Low levels of clothianidin residues do not cause acute poisoning in humans, but long-term consumption of foods exceeding clothianidin residue limits may lead to symptoms such as nausea, vomiting, headache, fatigue, restlessness and convulsions. Therefore, detection and analysis of clothianidin residues in fruits and vegetables can further clarify the residue status and risk levels of clothianidin in different fruit and vegetable varieties. The risk-prone varieties that easily exceed the residue limits can be identified via the pass rate, while the key regulated categories for the current year can be determined through the proportion of non-conforming samples. This will enhance attention to clothianidin and other pesticide residues 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 specialized supervision of pesticide residues.
1. Data Collection: Collect fruit and vegetable samples as required, perform sample preparation, and conduct quantitative analysis in accordance with the specified detection methods to obtain detected result values.
2. Data Processing: Obtain the detected result values via quantitative analysis, and set the standard limit in accordance with GB 2763. A sample is judged as conforming if the detected result value ≤ the standard limit; otherwise, it is judged as non-conforming. The pass rate of the subcategory in the current year is calculated as: (number of conforming batches A of the subcategory in the current year / total number of tested batches N of the subcategory in the current year) × 100%, rounded to two decimal places. The total number of non-conforming samples M is the sum of non-conforming clothianidin samples from all fruits and vegetables in the current year. The proportion of non-conforming samples of the subcategory is: (number of non-conforming samples X of the subcategory / total number of non-conforming samples M) × 100%, rounded to two decimal places. The proportion of non-conforming samples of the variety is: (number of non-conforming samples Y of the variety / total number of non-conforming samples M) × 100%, rounded to two decimal places. The risk assessment is defined as follows: LR when the pass rate of the subcategory in the current year ≥ 98%; MR when 98% > the pass rate of the subcategory in the current year ≥ 95%; HR when the pass rate of the subcategory in the current year < 95%.
3. Data Application: Detection and analysis of clothianidin residues in various fruits and vegetables can help understand the clothianidin residue status of different fruit and vegetable varieties, identify risk-prone varieties that easily exceed residue limits via risk assessment, and grasp the overall non-conforming situation of the annual regulated categories through the proportion of non-conforming samples. This will enhance attention to clothianidin and other pesticide residues in fruits and vegetables, provide reference for the rational use of pesticides by production enterprises, and offer data support for regulatory authorities to carry out specialized supervision of pesticide residues.

搜集汇总

数据集介绍

特点

该数据集包含1183条不同品类果蔬中噻虫胺残留量的检测数据，每年更新，用于分析农药残留情况和风险评价，为农药使用和监管提供支持。