CN115148304A - 一种农产品污染诊断及措施选取方法 - Google Patents
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Abstract
本发明提供一种农产品污染诊断方法,综合利用土壤及农产品各器官监测数据,通过污染相似度确定重金属传递突变环节,进而选取针对性措施,为农产品质量安全保障工作提供技术支撑;计算过程还得到了得分系数,得分系数越大,则该指标对传递过程的影响越大,在治理过程中需要重点关注,提高治理过程的准确性,预先明确农产品修复治理效果最佳环节/对象,结合研究区域实际生产情况,为农产品污染防治资金规划提供技术支撑,减少盲目实施措施的人力物力投入。
Description
技术领域
本发明属于农业环境技术领域,具体涉及一种农产品污染诊断及措施选取方法。
背景技术
研究显示农产品安全与土壤环境息息相关,且农产品各器官对重金属的吸收转化能力差异明显;目前针对土壤重金属与农产品各器官之间的传递关系研究较少,且多为盆栽实验,对农产品重金属污染防治支撑力较差,此外,农产品各器官重金属之间的关系多采用相关性分析,方法单一且缺乏验证。
上述技术方法存在的主要问题有:(1)土壤重金属及农产品各器官间的吸收转化机制不明确;(2)农产品各器官间重金属传递及吸收关系不明晰;(3) 现有研究方法不成熟且数据限制性较大;(4)农产品污染防治措施缺乏针对性及实用性。
发明内容
本发明提供了一种农产品污染诊断及措施选取方法,包括产地环境数据库建立、数据前处理、污染相似度计算及污染诊断四个部分。本发明实现过程中综合利用土壤监测数据及农产品各器官的重金属监测数据,将数据统一前处理,消除数据特征差异性;随后通过土壤及农产品各器官监测数据之间的矩阵转换,分别获得多对象间重金属含量的相似性,明确重金属传递突变环节,并结合因子分析结果确定关键影响因素,进而选取针对性防治措施;本发明兼顾科学算法及实际情况,有利于保障农产品质量安全及人体健康。
为了解决上述技术问题,本发明公开了一种农产品污染诊断及措施选取方法,所述方法包括:
(1)产地环境数据库建立
(1.1)土壤重金属影响指标信息
明确对土壤研究指标有影响的土壤影响指标,同时获取研究区域土壤影响指标监测信息并上传至所述产地环境数据库;
(1.2)获取研究区域内的环境信息、土壤研究指标监测信息和农产品研究指标监测信息,上传产地环境数据库;
(2)数据前处理
对所有土壤影响指标、土壤研究指标及农产品研究指标的监测数据进行前处理,包括对数处理及归一化处理两步:
(2.1)对数处理,计算公式具体如下:
其中xs’为标准化数据,xs为土壤影响指标/土壤研究指标/农产品研究指标的监测数据;
(2.2)标准化数据再采用z-score方法进行归一化处理,获得归一化监测值 ys,计算公式具体如下:
(3)污染相似度计算
(3.1)矩阵转换
将所有土壤影响指标及土壤研究指标组合成矩阵进行矩阵运算,获取得分系数矩阵,所述得分系数矩阵的行为土壤监测指标及土壤研究指标的得分系数,列为主成份类别;
根据得分系数矩阵得到任意主成份类别E对应的土壤研究指标j与土壤影响指标i的矩阵关系式如下:
E=m1I1+m2I2+…+miIi+mjIj
其中:mi为得分系数矩阵中土壤影响指标i对应的得分系数,mj为得分系数矩阵中土壤研究指标j对应的得分系数,Ii对应单项土壤影响指标,仅示意无取值,Ij对应土壤研究指标j,仅示意无取值;
(3.2)污染相似度计算
分别计算土壤研究指标与农产品各器官的农产品研究指标、农产品各器官之间的农产品研究指标污染相似度,所述污染相似度的计算需要包括对象1和对象2两部分的权重求解及污染相似度计算:
所述对象1与对象2分别对应于土壤研究指标或农产品各单一器官的研究指标,且对象1和对象2不相同;
(3.2.1)通过最小二乘法求解得出各主成份类别对应的对象1的权重,单项主成份类别E与对象1权重、土壤影响指标及土壤研究指标对应得分系数的关系式具体如下:
E=∑yimi+yjmj
yj=w1E1+w2E2+…+wtEt
其中,yj为对象1研究指标j的归一化监测值,yi为土壤影响指标i的归一化监测值,wt为第t个主成份类别下对应的对象1权重,Et为第t个主成份类别对应数值;
(3.2.2)将上述对象1研究指标j的归一化监测值替换为对象2研究指标j 的归一化监测值,相同方法求得对象2的权重vj;
所述对象1权重与对象2权重的数据量一致,且与主成份类别数量相同;
(3.2.3)基于对象1权重和对象2权重分别构建矩阵,进而求出污染相似度cosθj,具体公式如下:
其中w为对象1权重矩阵,v为对象2权重矩阵;
(4)污染诊断
(4.1)比较计算出的污染相似度绝对值的大小差异,污染相似度绝对值最小的环节则为研究指标的传递突变环节,并依据重金属传递顺序将所述传递突变环节中涉及到的两个对象分为首环节和尾环节;
(4.2)比较传递突变环节首环节和尾环节两个对象的各主成份类别下对应下的权重大小,权重差值最大的主成份类别即为差异主成份类别;
(4.3)将差异主成份类别中所有土壤影响指标及土壤研究指标的得分系数进行大小比较,选取得分系数前2%-40%的土壤影响指标作为防控措施的治理对象。
进一步地,所述研究区域实际情况包括但不限于耕种时间、农产品类型、农产品生长情况、地方资金、措施实施难度等;
进一步地,所述传递突变环节涉及到土壤、根部的主要选取针对土壤调理的措施,传递突变环节仅涉及到地面部分的主要选取针对农产品植株阻控的措施;
进一步地,所述防治措施优先选取对传递过程影响较大的指标有作用的措施。
进一步地,所述土壤影响指标包括但不限于:锌、钙、硫、铁、锰、磷、钾、钠、镁、硒、氮、硅、铜、氯、铝、镧、钼、硼、重金属有效态、pH、CEC、 SOM等,
进一步地,所述土壤影响指标监测信息包括但不限于:监测指标、监测数据、监测日期、称样量、检测方法等;
进一步地,所述土壤研究指标为Cd、Hg、As、Pb、Cr五项中的一项或多项,且土壤研究指标与农产品研究指标一致;
进一步地,所述环境信息包括但不限于:区域面积、历史点位数量、历史点位地理信息、周边环境、污染源信息、投入品信息等;土壤研究指标监测信息包括但不限于:研究指标、监测数据、监测日期、称样量、检测方法等;农产品研究指标监测信息包括但不限于:数据采集器官、研究指标、监测数据、监测日期、称样量、检测方法、种植制度、农产品类型、年产量等;
进一步地,所述农产品类型包括水稻、玉米、大豆、红薯、甘蔗等;
进一步地,计算过程采用计算机软件进行,所述计算机软件包括SPSS、 python、Excel等;
进一步地,所述主成份类别与土壤影响指标及土壤研究指标的指标数量一致;
本发明的一种农产品污染诊断及措施选取方法,具有以下优点:
1.本发明综合利用土壤及农产品各器官监测数据,通过污染相似度确定重金属传递突变环节,进而选取针对性措施,为农产品质量安全保障工作提供技术支撑;计算过程还得到了得分系数,得分系数越大,则该指标对传递过程的影响越大,在治理过程中需要重点关注,提高治理过程的准确性。
2.本发明计算获得农产品各器官之间的污染相似度,通过污染相似度绝对值比较进一步明晰重金属在农产品体内的传输吸收能力;此外通过影响主因的筛选明确各土壤影响指标对重金属传输的阻碍能力;
3.本发明预先明确农产品修复治理效果最佳环节/对象,结合研究区域实际生产情况,为农产品污染防治资金规划提供技术支撑,减少盲目实施措施的人力物力投入,与正常农产品污染防治工作相比,节约近15%的时间及近20%资金投入。
附图说明
图1为一种农产品污染诊断及措施选取方法技术流程图;
图2为T县历史点位分布图;
图3为各器官农产品权重分布图;
图4为土壤权重分布图;
图5为相似度绝对值分布图;
图6为传递突变环节权重差异分布图;
图7为变异主成份得分系数分布图;
具体实施方式
下面通过实施例对本发明做进一步的详细说明,以令本领域技术人员参照说明书文字能够据以实施。
应当理解,本文所使用的诸如“具有”,“包含”以及“包括”术语并不排除一个或多个其它元件或其组合的存在或添加。
实施例1
1.产地环境数据库建立
(1)通过查阅论文、会议资料、询问专家等方式,确认Cd、Hg、As、Pb、 Cr五项土壤主要重金属的影响指标信息,包括锌、汞、钙、硫、铁、锰、磷、钾、钠、镁、硒、氮、硅、铜、氯、铝、镧、钼、硼等;此次研究选取Cd为研究指标,收集T县已有的影响土壤Cd的土壤影响指标监测数据,确认包括汞、砷、铅、铬、锌、钙、铁、锰、磷、钾、钠、镁、硒、氮、硅、铜、铝、镧、钼共计19项;
(2)收集T县环境信息、土壤Cd及农产品(均为水稻)根部、茎部、叶部和糙米四个器官中Cd的监测信息,确定历史点位共计148个,点位分布情况见图2;
2.数据前处理
选取excel分析工具,将148个点位的土壤影响指标、土壤Cd及水稻四个器官(根部、茎部、叶部和糙米)的Cd均进行对数处理及归一化处理,获得各指标的归一化监测值;
3.污染相似度计算
(1)选取SPSS分析工具,将土壤影响指标及土壤Cd的归一化监测值进行主成份分析,获得得分系数矩阵,矩阵共包括20个主成份类别,每类别主成份对应20个得分系数;
(2)依据计算公式,分别带入水稻四个器官(根部、茎部、叶部和糙米) Cd的归一化监测值,计算出各器官对应的农产品权重,结果见图3;将土壤Cd 归一化监测值代替水稻根部的Cd归一化监测值,计算出对应的土壤权重,结果见图4;
(3)基于根部、茎部、叶部和糙米四个器官的农产品权重及土壤权重分别构建矩阵,通过污染相似度公式分别计算出土壤与水稻各器官的相似度及水稻各器官之间的污染相似度;
4.污染诊断
(1)比较分析土壤与水稻根部、茎部,水稻相连器官之间的污染相似度绝对值大小,确定传递突变环节为茎-米环节,结果见图5;茎-叶环节虽然相似度绝对值也较小,但叶部未与籽粒部分直接相连,故不分析此环节;
(2)比较水稻茎部的权重和糙米部分的权重大小,确定权重差值最大的为第20个主成份类别,即为差异主成份,结果见图6;
(3)比较差异主成份中土壤影响指标及土壤Cd指标对应的得分系数,确定影响最较大的指标包含Mn、Na、Si、Se、Al等,结果见图7;T县水稻目前正处于接穗时期,结合相关实验,选取喷施降Cd类叶面阻控剂中可阻碍Mn、 Na、Si、Se、Al等指标传递的药物进行稻米污染防控。
尽管本发明的实施方案已公开如上,但其并不仅仅限于说明书和实施方式中所列运用,它完全可以被适用于各种适合本发明的领域,对于熟悉本领域的人员而言,可容易地实现另外的修改,因此在不背离权利要求及等同范围所限定的一般概念下,本发明并不限于特定的细节和这里示出与描述的实施例。
Claims (10)
1.一种农产品污染诊断及措施选取方法,其特征在于,所述方法包括:
(1)产地环境数据库建立
(1.1)土壤重金属影响指标信息
明确对土壤研究指标有影响的土壤影响指标,同时获取研究区域土壤影响指标监测信息并上传至所述产地环境数据库;
(1.2)获取研究区域内的环境信息、土壤研究指标监测信息和农产品研究指标监测信息,上传产地环境数据库;
(2)数据前处理
对所有土壤影响指标、土壤研究指标及农产品研究指标的监测数据进行前处理,包括对数处理及归一化处理两步:
(2.1)对数处理,计算公式具体如下:
其中xs’为标准化数据,xs为土壤影响指标/土壤研究指标/农产品研究指标的监测数据;
(2.2)标准化数据再采用z-score方法进行归一化处理,获得归一化监测值ys,计算公式具体如下:
(3)污染相似度计算
(3.1)矩阵转换
将所有土壤影响指标及土壤研究指标组合成矩阵进行矩阵运算,获取得分系数矩阵,所述得分系数矩阵的行为土壤监测指标及土壤研究指标的得分系数,列为主成份类别;
根据得分系数矩阵得到任意主成份类别E对应的土壤研究指标j与土壤影响指标i的矩阵关系式如下:
E=m1I1+m2I2+…+miIi+mjIj
其中:mi为得分系数矩阵中土壤影响指标i对应的得分系数,mj为得分系数矩阵中土壤研究指标j对应的得分系数,Ii对应单项土壤影响指标,仅示意无取值,Ij对应土壤研究指标j,仅示意无取值;
(3.2)污染相似度计算
分别计算土壤研究指标与农产品各器官的农产品研究指标、农产品各器官之间的农产品研究指标污染相似度,所述污染相似度的计算需要包括对象1和对象2两部分的权重求解及污染相似度计算:
所述对象1与对象2分别对应于土壤研究指标或农产品各单一器官的研究指标,且对象1和对象2不相同;
(3.2.1)通过最小二乘法求解得出各主成份类别对应的对象1的权重,单项主成份类别E与对象1权重、土壤影响指标及土壤研究指标对应得分系数的关系式具体如下:
E=∑yimi+yjmj
yj=w1E1+w2E2+…+wtEt
其中,yj为对象1研究指标j的归一化监测值,yi为土壤影响指标i的归一化监测值,wt为第t个主成份类别下对应的对象1权重,Et为第t个主成份类别对应数值;
(3.2.2)将上述对象1研究指标j的归一化监测值替换为对象2研究指标j的归一化监测值,相同方法求得对象2的权重vj;
所述对象1权重与对象2权重的数据量一致,且与主成份类别数量相同;
(3.2.3)基于对象1权重和对象2权重分别构建矩阵,进而求出污染相似度cosθj,具体公式如下:
其中w为对象1权重矩阵,v为对象2权重矩阵;
(4)污染诊断
(4.1)比较计算出的污染相似度绝对值的大小差异,污染相似度绝对值最小的环节则为研究指标的传递突变环节,并依据重金属传递顺序将所述传递突变环节中涉及到的两个对象分为首环节和尾环节;
(4.2)比较传递突变环节首环节和尾环节两个对象的各主成份类别下对应下的权重大小,权重差值最大的主成份类别即为差异主成份类别;
(4.3)将差异主成份类别中所有土壤影响指标及土壤研究指标的得分系数进行大小比较,选取得分系数前2%-40%的土壤影响指标作为防控措施的治理对象。
2.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述研究区域实际情况包括:耕种时间、农产品类型、农产品生长情况、地方资金、措施实施难度。
3.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述传递突变环节涉及到土壤、根部的主要选取针对土壤调理的措施,传递突变环节仅涉及到地面部分的主要选取针对农产品植株阻控的措施。
4.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述防治措施优先选取对传递过程影响较大的指标有作用的措施。
5.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述土壤影响指标包括:锌、钙、硫、铁、锰、磷、钾、钠、镁、硒、氮、硅、铜、氯、铝、镧、钼、硼、重金属有效态、pH、CEC、SOM。
6.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述土壤影响指标监测信息包括:监测指标、监测数据、监测日期、称样量、检测方法。
7.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述土壤研究指标为Cd、Hg、As、Pb、Cr五项中的一项或多项,且土壤研究指标与农产品研究指标一致。
8.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述环境信息包括:区域面积、历史点位数量、历史点位地理信息、周边环境、污染源信息、投入品信息等;土壤研究指标监测信息包括:研究指标、监测数据、监测日期、称样量、检测方法等;农产品研究指标监测信息包括:数据采集器官、研究指标、监测数据、监测日期、称样量、检测方法、种植制度、农产品类型、年产量。
9.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述农产品类型包括水稻、玉米、大豆、红薯、甘蔗。
10.如权利要求1所述的一种农产品污染诊断及措施选取方法,其特征在于,所述主成份类别与土壤影响指标及土壤研究指标的指标数量一致。
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