农业工程学报
農業工程學報
농업공정학보
2015年
4期
306-311
,共6页
钱建平%张保岩%邢斌%杨信廷%李茏%王鸿彬
錢建平%張保巖%邢斌%楊信廷%李蘢%王鴻彬
전건평%장보암%형빈%양신정%리롱%왕홍빈
农产品%检测%系统%追溯%蔬菜
農產品%檢測%繫統%追溯%蔬菜
농산품%검측%계통%추소%소채
agricultural products%measurements%systems%traceability%vegetable
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。
農產品檢測信息是直觀、可信的追溯內容，但批次不對應及信息篡改的風險使其在追溯繫統中的作用不能很好髮揮。該研究在分析現有繫統中檢測信息不能有效集成的基礎上，提齣瞭集成快速檢測信息的蔬菜追溯繫統改進框架，構建瞭以檢測儀與繫統連接測試、產品檢測、數據鑑聽與解析、數據入庫等為覈心的檢測信息自動讀取與解析流程，設計瞭蔬菜種植批次、包裝追溯碼和檢測編號的關聯規則；基于.Net 框架，在已有蔬菜安全生產管理繫統的基礎上，通過開髮檢測數據穫取接口，升級檢測信息穫取與管理功能。將改進後的繫統應用于天津市153傢基地，應用結果錶明使用改進繫統後檢測數據的穫取成功率為100%；企業自檢值與政府抽檢值的偏差小于使用繫統前，其偏差絕對值為4.37；使用改進繫統後雖有檢測值的偏差存在，但不存在不同性質的檢測結果。因此，改進後的繫統在提高檢測數據穫取效率、降低檢測數據篡改風險等方麵具有一定優勢。研究結果為檢測信息與追溯信息深入融閤、滿足深入追溯需求等提供瞭參攷。
농산품검측신식시직관、가신적추소내용，단비차불대응급신식찬개적풍험사기재추소계통중적작용불능흔호발휘。해연구재분석현유계통중검측신식불능유효집성적기출상，제출료집성쾌속검측신식적소채추소계통개진광가，구건료이검측의여계통련접측시、산품검측、수거감은여해석、수거입고등위핵심적검측신식자동독취여해석류정，설계료소채충식비차、포장추소마화검측편호적관련규칙；기우.Net 광가，재이유소채안전생산관리계통적기출상，통과개발검측수거획취접구，승급검측신식획취여관리공능。장개진후적계통응용우천진시153가기지，응용결과표명사용개진계통후검측수거적획취성공솔위100%；기업자검치여정부추검치적편차소우사용계통전，기편차절대치위4.37；사용개진계통후수유검측치적편차존재，단불존재불동성질적검측결과。인차，개진후적계통재제고검측수거획취효솔、강저검측수거찬개풍험등방면구유일정우세。연구결과위검측신식여추소신식심입융합、만족심입추소수구등제공료삼고。
Thedetection 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 1stto 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.
