WO2021159619A1 - 硒镉伴生作物重金属安全诊断系统及方法 - Google Patents

硒镉伴生作物重金属安全诊断系统及方法 Download PDF

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WO2021159619A1
WO2021159619A1 PCT/CN2020/089915 CN2020089915W WO2021159619A1 WO 2021159619 A1 WO2021159619 A1 WO 2021159619A1 CN 2020089915 W CN2020089915 W CN 2020089915W WO 2021159619 A1 WO2021159619 A1 WO 2021159619A1
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content
heavy metal
soil
cadmium
crop
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周杰
杨晨
殷汉琴
邵淑君
李孟奇
龚冬琴
喻景权
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Zhejiang Institute Of Geological Survey
Zhejiang University
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Zhejiang Institute Of Geological Survey
Zhejiang University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/24—Earth materials
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
    • G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
    • G01N27/041—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body

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  • the invention relates to a detection technology for the content of heavy metals in crops, in particular to a safety diagnosis system and method for heavy metals in selenium and cadmium-associated crops.
  • the heavy metals that cause environmental pollution mainly include cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), mercury (Hg), arsenic (As), nickel (Ni) and zinc (Zn). Pollution caused by heavy metals has the characteristics of concealment, irreversibility and long-term nature. Once they enter the soil, water and other living environments, it is difficult to eliminate them by physical, engineering and chemical methods.
  • plants can absorb some essential metal elements (Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, Se, V, Zn) from the soil Plants need different concentrations of heavy metal ions during growth and development. When plants absorb essential heavy metal elements, they also absorb and accumulate some non-essential heavy metal elements. These non-essential heavy metal elements not only affect the yield and quality of crops, but also directly or indirectly endanger human health through the food chain, causing some irreversible damage to the human body.
  • essential metal elements Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, Se, V, Zn
  • the Chinese patent document with the publication number CN104458605A discloses a method for detecting the content of heavy metals in plant samples.
  • the method includes weighing the vegetable samples and cutting them into pieces, adding dilute hydrochloric acid, heating and boiling, cooling, and constant volume; using flame atoms Absorption spectrophotometer for element determination. This method directly detects the content of heavy metals in vegetables, and the operation is complicated, the workload is large, and the work efficiency is low.
  • the Chinese patent document with the publication number CN105651949B discloses a method for evaluating the content of heavy metals in vegetables based on the soil conditions of the production area.
  • the total amount of heavy metals in the soil cannot effectively explain their bioavailability, because the physical and chemical properties of the soil can affect the bioavailability of heavy metals.
  • Selenium is one of the essential trace elements for the human body. It has anti-cancer and anti-cancer effects, protects the heart and liver, strengthens immunity, and delays aging. Selenium is resistant to heavy metals such as cadmium, and to a certain extent, it can alleviate the toxicity of heavy metals to plants, but as the dosage increases, the effect of reducing cadmium decreases.
  • the invention provides a heavy metal safety diagnosis system for selenium and cadmium-associated crops.
  • the system uses soil heavy metal cadmium content, effective selenium content and various physical and chemical properties as conditions to calculate the heavy metal content in selenium-cadmium-associated crops and perform safety evaluation. It is of great significance to the safe production of crops.
  • a selenium-cadmium-associated crop heavy metal safety diagnosis system including:
  • UI module used for input of related parameter data and display of calculation results
  • the processing module includes the relationship model between the relevant parameters and the heavy metal cadmium content in the crop, and calculates the heavy metal cadmium content in the crop according to the relevant parameter data, and evaluates the safety of the heavy metal content of the crop;
  • the relevant parameters include the soil available selenium content and the soil pH , Soil electrical conductivity, soil organic matter content, soil heavy metal cadmium content, soil heavy metal cadmium extractable content;
  • the management module after receiving the relevant parameter data, inputs the relevant parameter data into the relational model for calculation and evaluation of the safety of the heavy metal content of the crop, and transmits the evaluation result to the UI module for display.
  • Selenium is resistant to heavy metals such as cadmium, and to a certain extent, it can alleviate the toxicity of heavy metals to plants, but as the dosage increases, the effect of reducing cadmium decreases.
  • the present invention uses the soil available selenium content as a parameter for evaluating the heavy metal cadmium content in crops, so that the evaluation method is more accurate.
  • the crop is rice.
  • the relationship model is:
  • M (Cd rice ) is the heavy metal cadmium content in the crop, the unit is mg/kg; pH is the soil pH; EC is the soil electrical conductivity, the unit is ms; OM is the soil organic matter content, the unit is g/kg; M(Cd total ) is the soil heavy metal cadmium content in mg/kg; M (Cd ex ) is the soil heavy metal cadmium extract content in mg/kg; M (Se ex ) is the soil available selenium content in mg/kg ; A ⁇ g are constants.
  • the crop heavy metal content in the crop to be tested calculated by the relationship model is less than 0.16mg/kg
  • the crop heavy metal content is defined as safe
  • the calculated heavy metal cadmium content is within the range of 0.16 ⁇ 0.26mg/kg
  • the crop heavy metal is defined
  • the content has a risk of exceeding the standard
  • the calculated heavy metal cadmium content is greater than 0.26mg/kg, it is defined that the heavy metal content of the crop exceeds the standard.
  • the present invention also provides a safety diagnosis method for heavy metals in selenium-cadmium-associated crops, which includes the following steps:
  • the target crops in high-cadmium-selenium-rich soil and determine the relevant parameters of the soil; the relevant parameters include soil available selenium content, soil pH, soil electrical conductivity, soil organic matter content, soil heavy metal cadmium content, soil heavy metals Cadmium extractable content;
  • M (Cd rice ) is the heavy metal cadmium content in the crop; pH is the soil pH; EC is the soil electrical conductivity; OM is the soil organic matter content; M (Cdt otal ) is the soil heavy metal cadmium content; M (Cd ex ) is the soil heavy metal Cadmium extractable content; M (Se ex ) is the soil available selenium content; a ⁇ g are constants;
  • the soil available selenium content refers to the weak acid extraction of selenium in the soil, that is, the selenium form content that can be extracted with acetic acid;
  • the soil heavy metal cadmium content refers to the total amount of cadmium in the soil, and the cadmium content is measured by Agilent 7500a inductively coupled plasma mass spectrometry ICP-MS measurement;
  • soil heavy metal cadmium extractable content refers to the weak acid extractable content of cadmium in the soil, that is, the cadmium form content that can be extracted with acetic acid.
  • the crop is rice.
  • step (3) a multivariate attribution analysis is performed using the Lasso function of the software Matlab to calculate the value of a to g to obtain the relationship model.
  • the relationship model is:
  • M (Cd rice ) is the heavy metal cadmium content in the crop, the unit is mg/kg; pH is the soil pH; EC is the soil electrical conductivity, the unit is ms; OM is the soil organic matter content, the unit is g/kg; M(Cd total ) is the soil heavy metal cadmium content in mg/kg; M (Cd ex ) is the soil heavy metal cadmium extract content in mg/kg; M (Se ex ) is the soil available selenium content in mg/kg .
  • step (4) when the heavy metal cadmium content in the crop to be tested calculated by the relationship model is less than 0.16mg/kg, the heavy metal content of the crop is defined as safe; when the calculated heavy metal cadmium content is in the range of 0.16 ⁇ 0.26mg/kg When the content of heavy metal in the crop is defined as the risk of exceeding the standard; when the calculated heavy metal cadmium content is greater than 0.26mg/kg, the content of the heavy metal in the defined crop is beyond the standard.
  • the diagnostic system of the present invention can determine the heavy metal content of selenium-cadmium-associated rice soil planted rice according to the soil heavy metal cadmium content, effective selenium content and its physical and chemical properties, and perform prediction and safety evaluation, which can reduce and guide agricultural practitioners to a certain extent.
  • the workload and burden are of great guiding significance for actual agricultural production.
  • the heavy metal safety diagnosis system for selenium-cadmium associated crops of the present invention is particularly suitable for heavy metal safety detection of rice in high-cadmium and selenium-rich soil.
  • the system uses the open source development tool myeclipse company jdk1.6 and above as the compiling and running environment, and the desktop UI is based on Java Swing, which is used to receive user input data and display output results.
  • the software architecture includes 2 types of files (program source files, persistent data files) and 6 modules: management module, UI (user interface) module, configuration module, preprocessing module, processing module, and calculation module.
  • the program source file sets up three classes in total, namely VegeFrame (panel building class), FormularTool (calculation tool class) and Vegesys (panel initialization layout class).
  • the persistent data file sets up a total of two persistent types of files, namely, formal.properties (formula properties, as shown in Table 2, used to store the corresponding values of each coefficient of the formula), standard.properties (standard properties, as shown in Table 3, using To store the corresponding value of the safety standard).
  • the diagnosis system does not adopt the design mode of relational database, but adopts the method of reading properties file. Access permanent data, thereby improving the efficiency of the interaction between source code and persistent data.
  • the heavy metal safety diagnosis system for selenium and cadmium associated crops includes 6 modules:
  • UI module initialization of the user interface, user data input and calculation result display;
  • Configuration module configure through code.
  • Hardware environment CPU 2GHZ or above; memory: 256M or above; hard disk: 80G or above.
  • Software environment operating system Chinese version of winXP and other models configured above;
  • Preprocessing module to verify the rationality of the data entered by the user
  • Processing module preprocess and calculate the data input by the user according to the configuration module parameters
  • Calculation module According to the data input by the user, combined with the system background formula to perform calculations;
  • Management module After the user input data is received, the processing module performs preprocessing and calculation according to the configuration module parameters, and finally outputs the result to the interface.
  • the calculation module includes a cadmium accumulation model:
  • M (Cd rice ) is the heavy metal cadmium content in rice, the unit is mg/kg; pH is the soil pH; EC is the soil electrical conductivity, the unit is ms; OM is the soil organic matter content, the unit is g/kg; M(Cd total ) is the soil heavy metal cadmium content in mg/kg; M (Cd ex ) is the soil heavy metal cadmium weak acid extraction content, in mg/kg; M (Se ex ) is the soil available selenium content in mg/kg kg.
  • the cadmium accumulation model is obtained through the following steps:
  • Plant rice in high-cadmium-selenium-rich soil determine the following parameters: 1Soil available selenium content (mg/kg), 2Soil pH, 3Soil conductivity EC (ms), 4Soil organic matter content OM (g/kg) , 6 Soil heavy metal cadmium content (mg/kg), 6 soil heavy metal cadmium extractable content (mg/kg), etc.
  • 1Soil available selenium content mg/kg
  • 4Soil organic matter content OM g/kg
  • 6 Soil heavy metal cadmium content mg/kg
  • 6 soil heavy metal cadmium extractable content mg/kg
  • Step 1 Enter the effective selenium Se content in the soil in the input box, and the effective Se content entered in this box, and the data unit is mg/kg.
  • Step 2 Enter the pH value of the soil.
  • the box after the pH value of the soil is used to enter the value of the pH value, which is usually 2 decimal places.
  • Step 3 Enter the soil conductivity, the box after the soil conductivity is used to enter the value of the conductivity, the unit is ms.
  • Step 4 Enter the soil organic matter content.
  • the box after the soil organic matter is used to enter the value of the soil organic matter content in g/kg.
  • Step 5 Enter the soil heavy metal Cd content.
  • the box after the soil heavy metal is used to enter the value of the soil heavy metal Cd content in mg/kg.
  • Step 6 Enter the content of soil heavy metals in the weak acid extraction state.
  • the box after the soil heavy metals extraction is used to enter the value of the soil Cd weak acid extraction state in mg/kg.
  • Step 7 Click Calculate, synthesize the above input data, calculate and output the result. Click the reset button to clear the user's choice of type information and input information, and re-enter it for calculation.
  • the relevant data of the soil part is brought into the model, and the cadmium absorption value in rice is calculated and compared with the actual measured value to verify the reliability of the model.
  • the deviation range is -20% ⁇ +30% is defined as the safety risk value.
  • the model calculates that the Cd content in rice is less than 0.16mg/kg, it is considered safe; in the range of 0.16-0.26mg/kg, it is considered that there is a risk of exceeding the standard; when it is greater than 0.26mg/kg, the heavy metal in rice is considered to be excessive.
  • the accuracy rate of the heavy metal safety diagnosis system for selenium-cadmium-associated rice is more than 75%.
  • This model has the function of predicting the accumulation and safety of heavy metal cadmium in rice under the condition of selenium-cadmium associated.

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Abstract

一种硒镉伴生作物重金属安全诊断系统及方法，包括：UI模块，用于相关参数数据的输入以及计算结果的显示；处理模块，根据相关参数数据计算作物中重金属镉含量，评估作物重金属含量的安全性；相关参数包括土壤有效态硒含量、土壤pH、土壤电导率、土壤有机质含量、土壤重金属镉含量、土壤重金属镉提取态含量；管理模块，接收相关参数数据后，将相关参数数据输入到关系模型中进行计算并评估作物重金属含量的安全性，并将评估结果传输给UI模块进行显示。以土壤重金属镉含量、有效态硒含量及多种理化性质为条件，计算出作物的重金属含量并进行安全评价，对于作物的安全生产具有重要意义。

Description

硒镉伴生作物重金属安全诊断系统及方法 技术领域
本发明涉及作物重金属含量的检测技术，尤其涉及一种硒镉伴生作物重金属安全诊断系统及方法。
背景技术
在我国，农田生态环境污染虽然得到一定的遏制，但仍有日益加重的趋势。造成环境污染的重金属主要包括镉(Cd)、铬(Cr)、铜(Cu)、铅(Pb)、汞(Hg)、砷(As)、镍(Ni)及锌(Zn)等。重金属造成的污染具有隐蔽性、不可逆性和长期性等特点，它们一旦进入土壤、水体等生活环境中，采用物理的、工程的和化学的方法很难消除。
植物作为一种固着在土壤中不能移动的有机体，能够从土壤中吸收一些必需的金属元素(Ca、Co、Cu、Fe、K、Mg、Mn、Mo、Na、Ni、Se、V、Zn)植物在生长和发育过程中需要不同浓度的重金属离子。植物在吸收必需的重金属元素的同时，也会吸收、积累一些非必需重金属元素。这些非必需的重金属元素不仅影响作物的产量和品质，还可直接或间接地通过食物链危害人类健康，对人体造成一些不可逆的损伤。
如何检测作物重金属含量已引起人们的广泛关注。
公开号为CN104458605A的中国专利文献公开了一种检测植物样品中重金属含量的方法，该方法包括将蔬菜样品称重后剪碎，加入稀盐酸，加热煮沸后冷却，并进行定容；使用火焰原子吸收分光度计进行元素测定。该方法直接检测蔬菜中重金属含量，操作复杂，工作量大，工作效率较低。
目前，还有技术通过产地土壤中重金属含量的检测来间接检测作物中重金属含量。
公开号为CN105651949B的中国专利文献公开了一种基于产地土壤情况评价蔬菜中重金属含量的方法。然而，土壤重金属的总量不能有效的说明其生物有效性，原因在于土壤的理化性质能够影响重金属的生物有效性。
硒是人体必需的微量元素之一，具有防癌抗癌，保护心脏肝脏，增强 免疫力，延缓衰老等功效。硒对镉等重金属具有拈抗作用，在一定程度上能够缓解重金属对植物的毒害，但随着用量的加大，降镉效果反而下降。
目前，缺乏一种快速、有效的硒镉伴生作物中重金属含量的检测方法。
发明内容
本发明提供了一种硒镉伴生作物重金属安全诊断系统，该系统以土壤重金属镉含量、有效态硒含量及多种理化性质为条件，计算出在硒镉伴生作物的重金属含量并进行安全评价，对于作物的安全生产具有重要意义。
具体技术方案如下：
一种硒镉伴生作物重金属安全诊断系统，包括：
UI模块，用于相关参数数据的输入以及计算结果的显示；
处理模块，包含相关参数与作物中重金属镉含量之间的关系模型，根据相关参数数据计算作物中重金属镉含量，评估作物重金属含量的安全性；所述相关参数包括土壤有效态硒含量、土壤pH、土壤电导率、土壤有机质含量、土壤重金属镉含量、土壤重金属镉提取态含量；
管理模块，接收相关参数数据后，将相关参数数据输入到所述关系模型中进行计算并评估作物重金属含量的安全性，并将评估结果传输给UI模块进行显示。
硒对镉等重金属具有拈抗作用，在一定程度上能够缓解重金属对植物的毒害，但随着用量的加大，降镉效果反而下降。本发明将土壤有效态硒含量作为评估作物中重金属镉含量的一个参数，使得评估方法更加准确。
优选的，所述的作物为水稻。
进一步优选的，所述关系模型为：
LogM(Cd rice)＝a+b·pH+c·EC+d·OM+e·logM(Cd total)+f·logM(Cd ex)+g·logM(Se ex)；
其中，M(Cd rice)为作物中重金属镉含量，单位为mg/kg；pH为土壤pH；EC为土壤电导率，单位为ms；OM为土壤有机质含量，单位为g/kg；M(Cd total)为土壤重金属镉含量，单位为mg/kg；M(Cd ex)为土壤重金属镉提取态含量，单位为mg/kg；M(Se ex)为土壤有效态硒含量，单位为mg/kg；a～g为常数。
进一步优选的，配置模块为所述的关系模型配置的具体参数为：a＝-4.1378，b＝0.3862，c＝0.2718，d＝0.0043，e＝0.6275，f＝0.2625，g＝-0.1111。
优选的，当关系模型计算的待测作物中的重金属镉含量低于0.16mg/kg时，定义作物重金属含量安全；当计算的重金属镉含量在0.16～0.26mg/kg范围内时，定义作物重金属含量存在超标风险；当计算的重金属镉含量大于0.26mg/kg时，定义作物重金属含量超标。
通过实际样品检测，硒镉伴生作物重金属安全诊断系统准确率在75％以上，该模型具有预测硒镉伴生情况下作物中重金属镉的积累和安全性的作用。
基于同样的发明构思，本发明还提供了一种硒镉伴生作物重金属安全诊断方法，包括以下步骤：
(1)将目标作物种植于高镉富硒土壤中，测定土壤的相关参数；所述相关参数包括土壤有效态硒含量、土壤pH、土壤电导率、土壤有机质含量、土壤重金属镉含量、土壤重金属镉提取态含量；
(2)作物成熟收获后，测定作物中重金属镉含量；
(3)建立所述相关参数与作物中重金属镉含量之间的关系模型，所述关系模型为：
LogM(Cd rice)＝a+b·pH+c·EC+d·OM+e·logM(Cd total)+f·logM(Cd ex)+g·logM(Se ex)；
其中，M(Cd rice)为作物中重金属镉含量；pH为土壤pH；EC为土壤电导率；OM为土壤有机质含量；M(Cdt otal)为土壤重金属镉含量；M(Cd ex)为土壤重金属镉提取态含量；M(Se ex)为土壤有效态硒含量；a～g为常数；
(4)测定待测作物的产地土壤的相关参数，根据所述关系模型计算待测作物中的重金属镉含量，评估待测作物的重金属安全性。
土壤有效态硒含量是指土壤中硒的弱酸提取态含量，即能够用醋酸提取的硒形态含量；土壤重金属镉含量是指土壤中含镉的总量，镉含量用Agilent 7500a电感耦合等离子体质谱仪(ICP-MS)测定；土壤重金属镉提取态含量是指土壤中镉的弱酸提取态含量，即能够用醋酸提取的镉形态含量。
优选的，所述的作物为水稻。
优选的，步骤(3)中，利用软件Matlab的Lasso函数进行多元归因分析，推算出a～g的值，得到所述的关系模型。
进一步优选的，所述关系模型为：
LogM(Cd rice)＝-4.1378+0.3862pH+0.2718EC+0.0043OM+0.6275logM(Cd total)+0.2625logM(Cd ex)-0.1111logM(Se ex)；
其中，M(Cd rice)为作物中重金属镉含量，单位为mg/kg；pH为土壤pH；EC为土壤电导率，单位为ms；OM为土壤有机质含量，单位为g/kg；M(Cd total)为土壤重金属镉含量，单位为mg/kg；M(Cd ex)为土壤重金属镉提取态含量，单位为mg/kg；M(Se ex)为土壤有效态硒含量，单位为mg/kg。
优选的，步骤(4)中，当关系模型计算的待测作物中的重金属镉含量低于0.16mg/kg时，定义作物重金属含量安全；当计算的重金属镉含量在0.16～0.26mg/kg范围内时，定义作物重金属含量存在超标风险；当计算的重金属镉含量大于0.26mg/kg时，定义作物重金属含量超标。
与现有技术相比，本发明的有益效果为：
本发明的诊断系统可根据土壤的重金属镉含量、有效态硒含量及其理化性质，确定硒镉伴生水稻土壤种植稻米的重金属含量并进行预测和安全评价，能够在一定程度上减轻指导农业从业人员的工作量和负担，对实际农业生产具有重要指导意义。
具体实施方式
本发明的硒镉伴生作物重金属安全诊断系统特别适用于高镉富硒土壤水稻的重金属安全性检测。该系统采用开源开发工具myeclipse公司的jdk1.6及以上版本为编译运行环境，桌面UI基于Java Swing，用于接收用户输入数据和展示输出结果。
软件平台参数见表1。
表1软件平台参数
Figure PCTCN2020089915-appb-000001
Figure PCTCN2020089915-appb-000002
软件体系结构包括2类文件(程序源文件、持久化数据文件)和6个模块：管理模块、UI(用户界面)模块、配置模块、预处理模块、处理模块和计算模块。
程序源文件一共设置了三个类，分别是VegeFrame(面板组建类)、FormularTool(计算工具类)和Vegesys(面板初始化布局类)。
持久化数据文件一共设置了两个持久化类型的文件分别是formular.properties(公式属性，如表2，用来存放公式的各个系数对应值)、standard.properties(标准属性，如表3，用来存放安全标准对应值)。
表2 formular.properties文件
Figure PCTCN2020089915-appb-000003
表3 standard.properties文件
Figure PCTCN2020089915-appb-000004
硒镉伴生作物重金属安全诊断系统中，由于持久化数据量非常小，考虑到软件的便携性与性能的提升，诊断系统没有采取关系型数据库的设计模式，而是采用properties文件读取的方式来存取永久性数据，进而提高源码与持久化数据之间交互的效率。
硒镉伴生作物重金属安全诊断系统包括6个模块：
UI模块：用户界面的初始化、用户数据输入以及计算结果显示；
配置模块：通过代码进行配置。硬件环境CPU：2GHZ或者以上；内存：256M或者以上；硬盘：80G或者以上。软件环境操作系统：中文版winXP及以上配置的其他机型；
预处理模块：对用户输入的数据进行合理性验证；
处理模块：根据配置模块参数，对用户输入的数据进行预处理和计算；
计算模块：根据用户输入的数据，结合系统后台公式，进行计算；
管理模块：实现用户输入数据接收后，由处理模块根据配置模块参数，进行预处理和计算，最后将结果输出到界面。
计算模块中包含镉积累模型：
LogM(Cd rice)＝-4.1378+0.3862pH+0.2718EC+0.0043OM+0.6275logM(Cd total)+0.2625logM(Cd ex)-0.1111logM(Se ex)；
其中，M(Cd rice)为稻米中重金属镉含量，单位为mg/kg；pH为土壤pH；EC为土壤电导率，单位为ms；OM为土壤有机质含量，单位为g/kg；M(Cd total)为土壤重金属镉含量，单位为mg/kg；M(Cd ex)为土壤重金属镉弱酸提取态含量，单位为mg/kg；M(Se ex)为土壤有效态硒含量，单位为mg/kg。
镉积累模型通过以下步骤获得：
将水稻种植于高镉富硒土壤中，测定以下参数：①土壤有效态硒含量(mg/kg)、②土壤pH、③土壤电导率EC(ms)、④土壤有机质含量OM(g/kg)、⑥土壤重金属镉含量(mg/kg)、⑥土壤重金属镉提取态含量(mg/kg)等。水稻收获后，测定稻米中镉含量。
将测得的7项数据作为一组数据，将若干组数据输入一个矩阵，代入函数LogM(Cd rice)＝a+b·pH+c·EC+d·OM+e·logM(Cd total)+f·logM(Cd ex)+g·logM(Se ex)，利用专业数学软件Matlab的Lasso函数进行多元归因分析，推算出a～g各参数，分别为：a＝-4.1378，b＝0.3862，c＝0.2718，d＝0.0043，e＝0.6275，f＝0.2625，g＝-0.1111。
本系统具体操作如下：
第一步：输入框中输入土壤中有效态硒Se含量，此方框输入的为有效态含量Se，数据单位是mg/kg。
第二步：输入土壤pH值，土壤pH值后的方框用来输入pH值的数值，常为2位小数。
第三步：输入土壤电导率，土壤电导率后的方框用来输入电导率的数值，单位是ms。
第四步：输入土壤有机质含量，土壤有机质后的方框用来输入土壤有机质含量的数值，单位是g/kg。
第五步：输入土壤重金属Cd含量，土壤重金属后的方框用来输入土壤重金属Cd含量数值，单位是mg/kg。
第六步：输入土壤重金属弱酸提取态含量，土壤重金属提取态后的方框用来输入土壤Cd弱酸提取态含量的数值，单位是mg/kg。
第七步：点击计算，综合上述的输入数据，计算并输出结果。点击重置按钮可将用户选择种类信息，和输入信息清空，重新输入进行计算。
基于上述的硒镉伴生稻米中镉积累模型，将土壤部分的相关数据带入模型中，计算稻米中镉吸收值，并与实际测定值进行对比，从而验证模型的可靠性。
根据相关标准《GBT 27404-2008实验室质量控制规范食品理化检测》中，重复分析标准物质(实物标样)或水平测试样品，测定含量平均值与真值的偏差指导范围，样品Cd的含量在0.01～10mg/kg时，其对应的偏差范围是-20％～+10％。所以模拟计算数值与测量值误差在上述范围内的即为准确可靠的。考虑到实际情况，样品的取样点均为高镉富硒区，镉吸收规律受到一定程度干扰，同时还有其他7组数据在测定时也存在一定的误差，所以将偏差范围在-20％～+30％定义为安全风险值。当模型计算出稻米中Cd含量低于0.16mg/kg认为是稻米安全；在0.16～0.26mg/kg范围内，认为稻米存在超标风险；当大于0.26mg/kg时认为稻米重金属超标。
通过实际样品检测，硒镉伴生水稻重金属安全诊断系统准确率在75％以上，该模型具有预测硒镉伴生情况下稻米中重金属镉的积累和安全性的作用。
以上所述的实施例对本发明的技术方案和有益效果进行了详细说明，应理解的是以上所述仅为本发明的具体实施例，并不用于限制本发明，凡在本发明的原则范围内所做的任何修改、补充和等同替换等，均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种硒镉伴生作物重金属安全诊断系统，其特征在于，包括：
    UI模块，用于相关参数数据的输入以及计算结果的显示；
    处理模块，包含相关参数与作物中重金属镉含量之间的关系模型，根据相关参数数据计算作物中重金属镉含量，评估作物重金属含量的安全性；所述相关参数包括土壤有效态硒含量、土壤pH、土壤电导率、土壤有机质含量、土壤重金属镉含量、土壤重金属镉提取态含量；
    管理模块，接收相关参数数据后，将相关参数数据输入到所述关系模型中进行计算并评估作物重金属含量的安全性，并将评估结果传输给UI模块进行显示。
  2. 根据权利要求1所述的硒镉伴生作物重金属安全诊断系统，其特征在于，所述的作物为水稻。
  3. 根据权利要求1所述的硒镉伴生作物重金属安全诊断系统，其特征在于，所述关系模型为：
    LogM(Cd rice)＝a+b·pH+c·EC+d·OM+e·logM(Cd total)+f·logM(Cd ex)+
    g·logM(Se xx)；
    其中，M(Cd rice)为作物中重金属镉含量，单位为mg/kg；pH为土壤pH；EC为土壤电导率，单位为ms；OM为土壤有机质含量，单位为g/kg；M(Cd total)为土壤重金属镉含量，单位为mg/kg；M(Cd ex)为土壤重金属镉提取态含量，单位为mg/kg；M(Se ex)为土壤有效态硒含量，单位为mg/kg；a～g为常数。
  4. 根据权利要求3所述的硒镉伴生作物重金属安全诊断系统，其特征在于，配置模块为所述的关系模型配置的具体参数为：a＝-4.1378，b＝0.3862，c＝0.2718，d＝0.0043，e＝0.6275，f＝0.2625，g＝-0.1111。
  5. 根据权利要求4所述的硒镉伴生作物重金属安全诊断系统，其特征在于，当关系模型计算的待测作物中的重金属镉含量低于0.16mg/kg时，定义作物重金属含量安全；当计算的重金属镉含量在0.16～0.26mg/kg范围内时，定义作物重金属含量存在超标风险；当计算的重金属镉含量大于0.26mg/kg时，定义作物重金属含量超标。
  6. 一种硒镉伴生作物重金属安全诊断方法，其特征在于，包括以下步骤：
    (1)将目标作物种植于高镉富硒土壤中，测定土壤的相关参数；所述相关参数包括土壤有效态硒含量、土壤pH、土壤电导率、土壤有机质含量、土壤重金属镉含量、土壤重金属镉提取态含量；
    (2)作物成熟收获后，测定作物中重金属镉含量；
    (3)建立所述相关参数与作物中重金属镉含量之间的关系模型，所述关系模型为：
    LogM(Cd rice)＝a+b·pH+c·EC+d·OM+e·logM(Cd total)+f·logM(Cd ex)+
    g·logM(Se ex)；
    其中，M(Cd rice)为作物中重金属镉含量；pH为土壤pH；EC为土壤电导率；OM为土壤有机质含量；M(Cd total)为土壤重金属镉含量；M(Cd ex)为土壤重金属镉提取态含量；M(Se ex)为土壤有效态硒含量；a～g为常数；
    (4)测定待测作物的产地土壤的相关参数，根据所述关系模型计算待测作物中的重金属镉含量，评估待测作物的重金属安全性。
  7. 根据权利要求6所述的硒镉伴生作物重金属安全诊断方法，其特征在于，所述的作物为水稻。
  8. 根据权利要求6所述的硒镉伴生作物重金属安全诊断方法，其特征在于，步骤(3)中，利用软件Matlab的Lasso函数进行多元归因分析，推算出a～g的值，得到所述的关系模型。
  9. 根据权利要求7所述的硒镉伴生作物重金属安全诊断方法，其特征在于，所述关系模型为：
    LogM(Cd rice)＝-4.1378+0.3862pH+0.2718EC+0.0043OM+
    0.6275logM(Cd total)+0.2625logM(Cd ex)-0.1111logM(Se ex)；
    其中，M(Cd rice)为作物中重金属镉含量，单位为mg/kg；pH为土壤pH；EC为土壤电导率，单位为ms；OM为土壤有机质含量，单位为g/kg；M(Cd total)为土壤重金属镉含量，单位为mg/kg；M(Cd ex)为土壤重金属镉提取态含量，单位为mg/kg；M(Se ex)为土壤有效态硒含量，单位为mg/kg。
  10. 根据权利要求9所述的硒镉伴生作物重金属安全诊断方法，其特征在于，当关系模型计算的待测作物中的重金属镉含量低于0.16mg/kg时，定义作物重金属含量安全；当计算的重金属镉含量在0.16～0.26mg/kg范围 内时，定义作物重金属含量存在超标风险；当计算的重金属镉含量大于0.26mg/kg时，定义作物重金属含量超标。
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