集成实时快速检测信息的蔬菜追溯系统改进与应用

农产品检测信息是直观、可信的追溯内容,但批次不对应及信息篡改的风险使其在追溯系统中的作用不能很好发挥。该研究在分析现有系统中检测信息不能有效集成的基础上,提出了集成快速检测信息的蔬菜追溯系统改进框架,构建了以检测仪与系统连接测试、产品检测、数据监听与解析、数据入库等为核心的检测信息自动读取与解析流程,设计了蔬菜种植批次、包装追溯码和检测编号的关联规则;基于.Net框架,在已有蔬菜安全生产管理系统的基础上,通过开发检测数据获取接口,升级检测信息获取与管理功能。将改进后的系统应用于天津市153家基地,应用结果表明使用改进系统后检测数据的获取成功率为100%;企业自检值与政府抽检值的偏差小于使用系统前,其偏差绝对值为4.37;使用改进系统后虽有检测值的偏差存在,但不存在不同性质的检测结果。因此,改进后的系统在提高检测数据获取效率、降低检测数据篡改风险等方面具有一定优势。研究结果为检测信息与追溯信息深入融合、满足深入追溯需求等提供了参考。

Improvement and application of vegetable traceability system with integrated real-time rapid detection of information

Abstract: The detection information of farm products increases rapidly, and plays an important role in traceability. The existed detection processing method used the mode of testing sample with detection instruments and manual recording data. This mode leads to the hazard of unassociated batches and distorted information, so the direct and credible effects of detection information in the traceability content are needed. In this paper, the reasons why detection information is not able to be integrated in the existed traceability system were analyzed. Modified system framework with detection information extracting and identification was proposed, which combined the rapid real-time detection instrument for vegetable pesticide residues mainly using enzyme inhibition method. In the detection process, information including detection ID, farm product batch and inhibition rate was recorded. In order to implement the automation reading and extracting of detection information, the access flowchart of detection data included the steps of instrument connection, vegetable detection, data extraction and data storing. The correlation between vegetable plant batch, detection identification number and product traceability code was the other important step for detection information tracing. Because one vegetable plant batch may be divided into many package units, the relationship between the batch code of vegetable plants and product traceability code was the type of 'one to many'. Because of the similar characteristics in one plant batch, the same batch of vegetable was detected once and the relationship between vegetable plant batch code and detection identification code was the type of 'one to one'. The batch correlation between product traceability code and detection identification code was established with the link of vegetable plant batch code. Based on .Net platform and the existed vegetable safety production management system, the vegetable production management and traceability system was updated for three functions. The detection instrument linked the vegetable production management and traceability system with serial port, and linking self-checking was implemented in the instrument link function. Then detection data was obtained through special data format. The detection data could be displayed but not modified in the data management function. The updated system was applied in 153 vegetable production bases in Tianjin city. During March 1st to May 30th in 2014, 28038 vegetable samples were detected and data obtain success rate with the updated system was 100%, and the data acquirement efficiency was improved. Furthermore, the detection results of 20 samples were compared between rapid real-time detection by enterprise self-check and casual inspection by supervision departments. The 20 samples were divided into two groups with No.1-8 samples using the manual recording mode of detection data without the updated the system and No.9-20 obtaining the detection data by automatic reading with the updated the system. The application results showed that the data acquisition success rate was 100% and the difference between the enterprise self-check value and the supervision casual inspection value was low with the absolute value of 4.37 after using the updated the system. The detection value with manual recording of No.3 sample was obviously lower than the one by supervision departments, which has the possible of distort data. Furthermore, the traceability results for using and not using the updated system were compared. Through using the system, the traceability results could indicate the precision detection information through the batches' correlation. The study in this paper presents an important step for satisfying the deeper requirement in traceability system.