不同品类蔬菜中噻虫嗪残留量检测分析数据

农药残留是农产品的主要安全问题之一，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，主要用于防治蚜虫、飞虱、蓟马等刺吸式害虫。如果长期食用噻虫嗪超标的食品对人体呼吸系统及神经系统等造成损害。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 2763-2021 《食品安全国家标准 食品中农药最大残留限量》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≥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 food safety concerns for agricultural products. Thiamethoxam residues in fruits and vegetables are frequently detected. Thiamethoxam is a second-generation neonicotinoid efficient and low-toxicity insecticide with a novel structural design, mainly used for controlling sucking pests such as aphids, planthoppers and thrips. Long-term consumption of foods with excessive thiamethoxam residues may cause damage to the human respiratory system, nervous system and other bodily systems. Therefore, through the detection and analysis of thiamethoxam residues in fruits and vegetables, we can further understand the residue status and risk profile of thiamethoxam across different fruit and vegetable categories. We can identify risk-prone varieties that easily exceed the standard residue limits via the qualified rate, and determine the key annual supervision categories based on the non-conforming proportion, so as to strengthen the oversight of thiamethoxam and other pesticide residues in fruits and vegetables. This provides guiding significance for the rational application of pesticides in the planting industry, and also offers data support for regulatory authorities to conduct special supervision on pesticide residues.

1、Data Collection: Collect fruit and vegetable samples according to requirements, perform sample preparation, conduct quantitative analysis in accordance with the specified detection method, and obtain the final detection result values.

2、Data Processing: Obtain the result values through quantitative analysis, and set the standard residue limit in accordance with GB 2763-2021 National Food Safety Standard: Maximum Residue Limits of Pesticides in Foods. A sample is judged as qualified if the detection result value ≤ the standard limit; otherwise, it is judged as unqualified. The annual qualified rate of this subcategory = (number of qualified detected batches A of this subcategory in the current year / total number of detected batches N of this subcategory in the current year) * 100%, rounded to two decimal places. The total number of non-conforming items M is the sum of all thiamethoxam non-conforming samples from fruits and vegetables in the current year. The non-conforming proportion of this subcategory = (number of non-conforming items X of this subcategory / total non-conforming number M) * 100%, rounded to two decimal places. The non-conforming proportion of this specific variety = (number of non-conforming items Y of this variety / total non-conforming number M) * 100%, rounded to two decimal places. The risk assessment is defined as follows: LR when the annual qualified rate of this subcategory ≥ 98%; MR when 98% > annual qualified rate of this subcategory ≥ 95%; HR when the annual qualified rate of this subcategory < 95%.

3、Data Application: Detect and analyze the thiamethoxam residues in various fruits and vegetables to understand the residue distribution of thiamethoxam across different fruit and vegetable categories. Identify risk-prone varieties that easily exceed the standard limits via risk assessment, and grasp the overall non-conforming situation of annual supervision categories through the non-conforming proportion, so as to strengthen the oversight of thiamethoxam and other pesticide residues in fruits and vegetables. This provides reference significance for the rational use of pesticides by production units, and also offers data support for regulatory authorities to carry out special supervision on pesticide residues.