CN105701575A - An agricultural product heavy metal risk assessment method based on a soil-crop system - Google Patents
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- 229910001385 heavy metal Inorganic materials 0.000 title claims abstract description 93
- 238000012502 risk assessment Methods 0.000 title claims abstract description 43
- 238000000034 method Methods 0.000 title claims abstract description 32
- 239000002689 soil Substances 0.000 claims description 89
- 229910052751 metal Inorganic materials 0.000 claims description 36
- 239000002184 metal Substances 0.000 claims description 36
- 238000005341 cation exchange Methods 0.000 claims description 14
- 241000894007 species Species 0.000 claims description 14
- 239000013256 coordination polymer Substances 0.000 claims description 13
- 238000009825 accumulation Methods 0.000 abstract description 3
- 238000013508 migration Methods 0.000 abstract description 3
- 230000005012 migration Effects 0.000 abstract description 3
- 238000009472 formulation Methods 0.000 abstract description 2
- 239000000203 mixture Substances 0.000 abstract description 2
- 230000002265 prevention Effects 0.000 abstract description 2
- 229910052793 cadmium Inorganic materials 0.000 description 10
- BDOSMKKIYDKNTQ-UHFFFAOYSA-N cadmium atom Chemical group [Cd] BDOSMKKIYDKNTQ-UHFFFAOYSA-N 0.000 description 10
- 230000008569 process Effects 0.000 description 6
- 235000007164 Oryza sativa Nutrition 0.000 description 4
- QTBSBXVTEAMEQO-UHFFFAOYSA-N Acetic acid Chemical compound CC(O)=O QTBSBXVTEAMEQO-UHFFFAOYSA-N 0.000 description 3
- 241000196324 Embryophyta Species 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
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- KMUONIBRACKNSN-UHFFFAOYSA-N potassium dichromate Chemical compound [K+].[K+].[O-][Cr](=O)(=O)O[Cr]([O-])(=O)=O KMUONIBRACKNSN-UHFFFAOYSA-N 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 241000209094 Oryza Species 0.000 description 2
- 240000007594 Oryza sativa Species 0.000 description 2
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- 238000000673 graphite furnace atomic absorption spectrometry Methods 0.000 description 2
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Abstract
The invention relates to an agricultural product heavy metal risk assessment method based on a soil-crop system. The method comprises the following steps: agricultural product heavy metal risk assessment indexes are established according to soil-crop characteristics; the content of heavy metal in an agricultural product is obtained through weighting of the risk assessment indexes; and the content of the heavy metal in the agricultural product is compared with a standard to obtain the risk probability of exceeding standard of the heavy metal of the agricultural product and regard the risk probability as assessment results. On the basis of migration and accumulation rules of heavy metal in a soil-crop system, with a latent/direct risk source, a risk acceptor and primary/secondary influence factors taken into consideration, and with quantified factors being used an index system, an agricultural product heavy metal risk assessment method based on the soil-crop system is established and can be applied to prediction of risk probability of heavy metal standard exceeding risks of agricultural products of agricultural areas and formulation of prevention strategies and measures.
Description
Technical field
The present invention relates to the technical field of agricultural product heavy metal pollution risk assessment, specifically a kind of agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System。
Background technology
The risk assessment of heavy metal pollution agricultural land soil is the focus that research is paid close attention at present。Long-term result of study shows, agricultural product heavy metal problem is limited mainly by the dual function of heavy metal content in soil and crops absorptance to be affected。Wherein, soil environment quality is the important exopathogenic factor that agricultural product exceed standard, " whole nation Investigation of Soil Pollution publication " display, and China's arable soil is based on heavy metal pollution, and concentrating on contour background value Central-South, southwestern area and nonferrous metals ore Tibetan area, the district that takes place frequently of exceeding standard with agricultural product is identical。And the absorption characteristic of heavy metal-polluted soil is the important endogenous cause of ill that agricultural product exceed standard by crops, a large amount of agricultural product quality follow-up investigation results also indicate that, the crops of variety classes and kind, and the regulation and control of the nutrient in plant growing process, all can cause the difference that agricultural product heavy metal accumulates。
Conventional research pays close attention to the response relation relation of content of beary metal between soil and agricultural product, but due between the two by various factors such as soil environment and crops characteristics, it is difficult to obtain method credible, propagable and conclusion。Therefore, should on original scattered single-factor Research foundation, soil-crop is considered as the system of a heavy metal transformation, heavy metal-polluted soil total amount is as potential risk resource, heavy metal-polluted soil available state is as direct risk source, agricultural product as risk receptor, then can contain the influence factors such as soil physico-chemical property and agricultural product characteristic。
As can be seen here, how based on heavy metal migration in Removed In Soil-crop System and Accumulation, from the angle of system, set up agricultural product heavy metals exceeding standard methods of risk assessment, specify main affecting factors, take specific aim measure, to ensureing that agricultural production security has important technical meaning。
Summary of the invention
Present invention aim at providing a kind of agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System。
The technical solution used in the present invention is for achieving the above object: a kind of agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System, comprises the following steps:
Feature according to soil-crop, sets up agricultural product heavy metal risk assessment index；
Content of beary metal in agricultural product is obtained by the weighting of risk assessment index；
Content of beary metal in agricultural product and established standards are compared, obtains the risk probability of agricultural product heavy metals exceeding standard and as assessment result。
Described agricultural product heavy metal risk indicator includes multiple first class index: heavy metal-polluted soil total content CS, heavy metal available state COEFFICIENT KA, heavy metal in soil bio-available Zn concentration CA, crop Metal uptake COEFFICIENT KP, agricultural product content of beary metal CP。
Described heavy metal available state COEFFICIENT KAIncluding multiple two-level index: soil acidity or alkalinity KpH, soil organism KOM, soil cation exchange capacity KCEC, soil redox potential KEh。
Described agricultural product content of beary metal CPIncluding multiple two-level index: crop specie KV, nutriture KTWith transhipment regulation and control KR。
The described weighting by risk assessment index obtains content of beary metal in agricultural product and comprises the following steps:
First class index is obtained by two-level index weighting；
First class index is multiplied and obtains content of beary metal in agricultural product。
Described obtain first class index by two-level index weighting particularly as follows:
KA=KpH+KOM+KCEC+KEh=WpH×MpH+WOM×MOM+WCEC×MCEC+WEh×MEh
Wherein, KAIt is heavy metal available state coefficient, KpHIt is soil acidity or alkalinity, KOMIt is the soil organism, KCECIt is soil cation exchange capacity, KEhIt it is soil redox potential；WpHIt is the weight of soil acidity or alkalinity, WOMIt is the weight of the soil organism, WCECIt is the weight of soil cation exchange capacity, WEhIt is the weight of soil redox potential, MpHIt is soil acidity or alkalinity rank value, MOMIt is soil organism rank value, MCECIt is soil cation exchange capacity rank value, MEhIt it is soil redox potential rank value；
KP=KV+KT+KR=WV×MV+WT×MT+WR×MR
Wherein, KPIt is crop Metal uptake coefficient, KVIt is crop specie, KTIt is nutriture, KRIt is transhipment regulation and control；WVIt is the weight of crop specie, WTIt is the weight of nutriture, WRIt it is the weight of transhipment regulation and control；MVIt is crop specie classification value, MTIt is nutriture rank value, MRIt it is transhipment regulation and control rank value。
Described being multiplied by first class index is obtained content of beary metal in agricultural product and can be obtained by following formula:
CP=KA×KP×CS
Wherein, CSIt is heavy metal in soil total content, KAIt is heavy metal available state coefficient, KPIt is crop Metal uptake coefficient, CPIt is agricultural product content of beary metal。
Based on the agricultural product heavy metal methods of risk assessment of Removed In Soil-crop System, after obtaining assessment result, it is determined that the dominant factor of agricultural product heavy metal risk, and Corresponding Countermeasures is proposed。
The present invention has the following advantages and beneficial effect:
The present invention is based on heavy metal migration in Removed In Soil-crop System and Accumulation, consider potential/direct risk source, risk receptor and primary/secondary influence factor, using the factor that quantifies as index system, establish the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System, can be used for the prediction of agricultural product heavy metals exceeding standard risk probability and the formulation of prevention countermeasure。
Accompanying drawing explanation
Fig. 1 is the agricultural product heavy metal risk evaluating system schematic diagram based on Removed In Soil-crop System provided by the invention。
Fig. 2 is the agricultural product heavy metal Risk Assessment Index System schematic diagram based on Removed In Soil-crop System provided by the invention。
Detailed description of the invention
Below in conjunction with embodiment, the present invention is described in further detail。
A kind of agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System, comprises the following steps:
1) agricultural product heavy metal Risk Assessment Index System is set up；
2) based on the classification of risk assessment index or classification assignment, the risk probability of agricultural product heavy metals exceeding standard is calculated；
3) determine the dominant factor of agricultural product heavy metal risk, and propose countermeasure。
Agricultural product heavy metal risk indicator system, including potential risk resource, direct risk source, risk receptor and primary and secondary influences factor:
1) potential risk resource, refers to the indirect source being likely to result in agricultural product heavy metals exceeding standard, including the various forms of heavy metal-polluted soil, refers specifically to crops and can absorb and nonabsorable part；
2) direct risk source, refers to the direct source being likely to result in agricultural product heavy metals exceeding standard, and referring specifically to crops in heavy metal-polluted soil can absorption portion；
3) risk receptor, refers to the recipient of risk, i.e. agricultural product itself；
4) primary effect factor, refers to that risk source is transferred to direct acting influence factor by latent effect, specifically refers specifically to the available state coefficient of heavy metal in soil, mainly includes the factors such as the acid-base value of soil, organic matter, cation exchange capacity, oxidation-reduction potential；
5) secondary influences factor, refers to the influence factor of relation between direct risk source and receptor, refers specifically to crop heavy metal absorptance, mainly includes the influence factors such as crop specie, nutriture and transhipment regulation and control。
The calculating of agricultural product heavy metal risk index, specifically includes:
1) adopt analytic hierarchy process (AHP), give weight (W) to the primary risk assessment index with secondary influences factor；
2) the primary risk assessment index with secondary influences factor is carried out classification or classification assignment (M), and normalization converts the decimal between 0～1 to；
3) follow the relation that is multiplied of first class index and the weighted connections of two-level index, calculate agricultural product content of beary metal, and according to agricultural product quality standard, calculate the risk probability of agricultural product heavy metals exceeding standard。
The determination of risk dominant factor and reply, specifically include:
1) according to leading factor method, it is determined that risk dominant factor；
2) take corresponding measure, regulate and control risk dominant factor, ensure agricultural product quality and safety。
The present invention comprises the concrete steps that: 1) the Removed In Soil-crop System feature according to region to be assessed, sets up agricultural product heavy metal Risk Assessment Index System；2) index is carried out compose weight, and classification or classification assignment, thus calculating the risk probability of agricultural product heavy metals exceeding standard；3) determine the dominant factor of agricultural product heavy metal risk, and propose countermeasure。
Step 1: the Removed In Soil-crop System feature according to region to be assessed, sets up agricultural product heavy metal Risk Assessment Index System。
1) based on the agricultural product risk evaluating system of soil-crop relation, mainly consider from risk source, receptor and influence factor, including potential risk resource, direct risk source, risk receptor, primary and secondary influences factor (Fig. 1)。
2) key component according to the heavy metal risk evaluating system of agricultural product, sets up one-level and light breeze danger evaluation index (Fig. 2), specific targets and illustrated in table 1。
Table 1 agricultural product heavy metal risk assessment index and explanation
Step 2: index is carried out compose weight, and classification or classification assignment, thus calculating the risk probability of agricultural product heavy metals exceeding standard。
1) adopt analytic hierarchy process (AHP), give weight (W) and W to the primary risk assessment index with secondary influences factorpH+WOM+WCEC+WEh=1, WV+WT+WR=1。
Wherein, WpHIt is the weight of soil acidity or alkalinity, WOMIt is the weight of the soil organism, WCECIt is the weight of soil cation exchange capacity, WEhIt is the weight of soil redox potential, WVIt is the weight of crop specie, WTIt is the weight of nutriture, WRIt it is the weight of transhipment regulation and control。
2) just give a batch experimental result according in the past potted plant with field, the primary risk assessment index with secondary influences factor is carried out classification or classification assignment (M), and normalization converts the decimal between 0～1 to；
Classification or classification value include MpHIt is soil acidity or alkalinity rank value, MOMIt is soil organism rank value, MCECIt is soil cation exchange capacity rank value, MEhIt is soil redox potential rank value, MVIt is crop specie classification value, MTIt is nutriture rank value, MRIt it is transhipment regulation and control rank value。
3) follow the relation that is multiplied of first class index and the weighted connections of two-level index, calculate agricultural product content of beary metal, wherein,
The relation that is multiplied of first class index:
CA=KA×CS(formula 1)
CP=KP×CA(formula 2)
CP=KA×KP×CS(formula 3)
Wherein, CSIt is heavy metal in soil total content, KAIt is heavy metal available state coefficient, CAIt is heavy metal in soil bio-available Zn concentration, KPIt is crop Metal uptake coefficient, CPIt is agricultural product content of beary metal。
The weighted connections of two-level index:
KA=KpH+KOM+KCEC+KEh
=WpH×MpH+WOM×MOM+WCEC×MCEC+WEh×MEh(formula 4)
Wherein, KAIt is heavy metal available state coefficient, KpHIt is soil acidity or alkalinity, KOMIt is the soil organism, KCECIt is soil cation exchange capacity, KEhIt it is soil redox potential。
KP=KV+KT+KR
=WV×MV+WT×MT+WR×MR(formula 5)
Wherein, KPIt is crop Metal uptake coefficient, KVIt is crop specie, KTIt is nutriture, KRIt is transhipment regulation and control。
4) according to the agricultural product standard that " pollutants in food limitation " (GB2762-2012) is corresponding, to calculate the risk probability of agricultural product heavy metals exceeding standard, particularly as follows:
Wherein, P is agricultural production heavy metals exceeding standard probability, N1It is the agricultural product quantity exceeded standard, N2It is the agricultural product quantity not exceeded standard。
Step 3: determine the dominant factor of agricultural product heavy metal risk, and propose countermeasure。
1) according to leading factor method, by SPSS20.0 software analysis, it is determined that risk dominant factor；
2) take corresponding measure, regulate and control risk dominant factor, ensure agricultural product quality and safety。
Embodiment 1:
The adopted soil of the present embodiment, picks up from irrigating region farmland, somewhere, Shenyang City, Liaoning Province, and the heavy metal that mainly exceeds standard is cadmium, sample district area 50 mu, and long-term cropping is Oryza sativa L., and kind is Shennong-265。Grid is layouted, and gathers soil and corresponding each 100 of Oryza sativa L. sample。
The assay method of each factor is as follows:
Cadmium in Soil total amount concentration measures and adopts graphite furnace atomic absorption spectrometry (GB/T17141-1997)；Cadmium available state method for measurement of concentration is with reference to Tessier continuous extraction, and wherein available state concentration is exchangeable species；In rice grain, cadmium content measures and adopts GFAAS (GB/T5009.15-2003)；The content of beary metal of input adopts potassium bichromate titrimetric method (NY-525-2002)；Soil pH adopts potentiometry (NY/T1377-2007)；The soil organism adopts potassium dichromate method (NY/T85-1988)；Soil cation exchange capacity adopts acetic acid money exchange process (LY/T1243-1999), soil redox potential adopts potentiometry (HJ746-2015), Nutrient Elements in Soil magnesium adopts atomic absorption spectrophotometry (NY/T2272-2012), and in the page siliceous fertilizer sprayed, silicone content is using plasma emission spectrometry (NY/T2272-2012)。
Concrete operations flow process includes:
Step 1: the Removed In Soil-crop System feature according to region to be assessed, sets up agricultural product heavy metal Risk Assessment Index System。
1) based on the agricultural product risk evaluating system of soil-crop relation, mainly consider from risk source, receptor and influence factor, including potential risk resource, direct risk source, risk receptor, primary and secondary influences factor (Fig. 1)。
2) key component according to the heavy metal risk evaluating system of agricultural product, sets up one-level and light breeze danger evaluation index (Fig. 2), specific targets and illustrated in table 1。
Wherein, first class index includes wherein, heavy metal in soil total content (CS), heavy metal available state coefficient (KA), heavy metal in soil bio-available Zn concentration (CA), crop Metal uptake coefficient (KP), agricultural product content of beary metal (CP)。
Two-level index includes heavy metal in soil total content (CS), soil acidity or alkalinity (KpH), the soil organism (KOM), soil cation exchange capacity (KCEC), soil redox potential (KEh), heavy metal in soil bio-available Zn concentration (CA), crop specie (KV), nutriture (KT), transhipment regulation and control (KR), agricultural product content of beary metal (CP)。
Step 2: index is carried out compose weight, and classification or classification assignment, thus calculating the risk probability of agricultural product heavy metals exceeding standard。
1) adopt analytic hierarchy process (AHP), give weight (W) and W to the primary risk assessment index with secondary influences factorpH+WOM+WCEC+WEh=1, WV+WT+WR=1。The present embodiment weight assignment refers to table 2。
Table 2 Index Weighting of Risk Assessment assignment table
2) just giving a batch experimental result according to potted plant with field, the primary risk assessment index with secondary influences factor carries out classification or classification assignment (M), and normalization converts the decimal between 0～1 to, the present embodiment result is in Table 3 and table 4:
Table 3 primary effect factor two-level index hierarchical table
Table 4 secondary influences factor two-level index classification/hierarchical table
3) testing result (table 5) according to two-level index, by classifying or classification conversion, follow the relation that is multiplied (formula 1, formula 2 and formula 3) of first class index, and the weighted connections of two-level index (formula 4 and formula 5), calculate agricultural product content of beary metal (table 6)。
Table 5 two-level index testing result
Table 6 risk indicator result of calculation
3) based on the assignment of each index, according to the agricultural product standard that " pollutants in food limitation " (GB2762-2012) is corresponding, it is 38 that statistics obtains the agricultural product quantity that content of beary metal exceeds standard, and the agricultural product quantity that content of beary metal exceeds standard is 62。
According to formula 6, calculate the risk probability of agricultural product heavy metals exceeding standard, then the risk probability that this region crops cadmium exceeds standard is 38%。
Step 3: determine the dominant factor of agricultural product heavy metal risk, and propose countermeasure。
1) according to leading factor method, by SPSS20.0 software analysis, it is determined that in the present embodiment, soil acidity or alkalinity, variety of crops are risk dominant factors；
2) in order to ensure agricultural product quality and safety, following scheme can be taked:
Scheme one is cadmium content in dilution topsoil soils: by ploughing deeply the agro-farming measure that waits, cadmium content 40% in reduction topsoil soils, can in effective guarantee Rice Seed cadmium content up to standard。
Scheme two is to reduce the activity of Cadmium in Soil: under the premise not changing Rice Cropping, by applying Calx in soil, adjusts soil acidity or alkalinity 6.5～7.5, controls heavy metal available state coefficient between 0.5～0.6, it is ensured that the quality safety of Rice Seed。
Scheme three is to adjust variety of crops: without nursing one's health Cadmium in Soil content and activity, replant Semen Maydis, thus controlling crops absorptance between 0.16～0.3, it is ensured that the quality safety of Semen Maydis seed。
Claims (8)
1. the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System, it is characterised in that comprise the following steps:
Feature according to soil-crop, sets up agricultural product heavy metal risk assessment index；
Content of beary metal in agricultural product is obtained by the weighting of risk assessment index；
Content of beary metal in agricultural product and established standards are compared, obtains the risk probability of agricultural product heavy metals exceeding standard and as assessment result。
2. by the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System described in claim 1, it is characterised in that described agricultural product heavy metal risk indicator includes multiple first class index: heavy metal-polluted soil total content CS, heavy metal available state COEFFICIENT KA, heavy metal in soil bio-available Zn concentration CA, crop Metal uptake COEFFICIENT KP, agricultural product content of beary metal CP。
3. by the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System described in claim 2, it is characterised in that described heavy metal available state COEFFICIENT KAIncluding multiple two-level index: soil acidity or alkalinity KpH, soil organism KOM, soil cation exchange capacity KCEC, soil redox potential KEh。
4. by the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System described in claim 2, it is characterised in that described agricultural product content of beary metal CPIncluding multiple two-level index: crop specie KV, nutriture KTWith transhipment regulation and control KR。
5. by the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System described in claim 1, it is characterised in that the described weighting by risk assessment index obtains content of beary metal in agricultural product and comprises the following steps:
First class index is obtained by two-level index weighting；
First class index is multiplied and obtains content of beary metal in agricultural product。
6. by the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System described in claim 1, it is characterised in that described obtain first class index by two-level index weighting particularly as follows:
KA=KpH+KOM+KCEC+KEh=WpH×MpH+WOM×MOM+WCEC×MCEC+WEh×MEh
Wherein, KAIt is heavy metal available state coefficient, KpHIt is soil acidity or alkalinity, KOMIt is the soil organism, KCECIt is soil cation exchange capacity, KEhIt it is soil redox potential；WpHIt is the weight of soil acidity or alkalinity, WOMIt is the weight of the soil organism, WCECIt is the weight of soil cation exchange capacity, WEhIt is the weight of soil redox potential, MpHIt is soil acidity or alkalinity rank value, MOMIt is soil organism rank value, MCECIt is soil cation exchange capacity rank value, MEhIt it is soil redox potential rank value；
KP=KV+KT+KR=WV×MV+WT×MT+WR×MR
Wherein, KPIt is crop Metal uptake coefficient, KVIt is crop specie, KTIt is nutriture, KRIt is transhipment regulation and control；WVIt is the weight of crop specie, WTIt is the weight of nutriture, WRIt it is the weight of transhipment regulation and control；MVIt is crop specie classification value, MTIt is nutriture rank value, MRIt it is transhipment regulation and control rank value。
7. by the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System described in claim 1, it is characterised in that described being multiplied by first class index is obtained content of beary metal in agricultural product and can be obtained by following formula:
CP=KA×KP×CS
Wherein, CSIt is heavy metal in soil total content, KAIt is heavy metal available state coefficient, KPIt is crop Metal uptake coefficient, CPIt is agricultural product content of beary metal。
8. by the agricultural product heavy metal methods of risk assessment based on Removed In Soil-crop System described in claim 1, it is characterised in that after obtaining assessment result, it is determined that the dominant factor of agricultural product heavy metal risk, and propose Corresponding Countermeasures。
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| CN111047223A (en) * | 2019-12-31 | 2020-04-21 | 黑龙江八一农垦大学 | Risk assessment method for predicting arsenic content in rice |
| CN111462834A (en) * | 2019-11-14 | 2020-07-28 | 中国科学院地理科学与资源研究所 | Method and system for predicting probability value of excessive cadmium in plant |
| CN112348691A (en) * | 2020-10-30 | 2021-02-09 | 农业农村部环境保护科研监测所 | Method and device for identifying potential overproof area of heavy metal content of agricultural product in situ |
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| CN114238858A (en) * | 2021-12-15 | 2022-03-25 | 中国科学院生态环境研究中心 | Method and system for reducing accumulation value of heavy metals in crops |
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| CN112348691A (en) * | 2020-10-30 | 2021-02-09 | 农业农村部环境保护科研监测所 | Method and device for identifying potential overproof area of heavy metal content of agricultural product in situ |
| CN112348691B (en) * | 2020-10-30 | 2022-05-13 | 农业农村部环境保护科研监测所 | Method and device for identifying potential overproof area of heavy metal content of agricultural product in situ |
| CN112541678A (en) * | 2020-12-11 | 2021-03-23 | 农业农村部环境保护科研监测所 | Rapid screening and targeted regulation and control method for restrictive factors of polluted farmland |
| CN112541678B (en) * | 2020-12-11 | 2022-03-11 | 农业农村部环境保护科研监测所 | Rapid screening and targeted regulation and control method for restrictive factors of polluted farmland |
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| CN112883137B (en) * | 2021-03-02 | 2022-04-15 | 农业农村部环境保护科研监测所 | Agricultural product producing area safety early warning method |
| CN114238858A (en) * | 2021-12-15 | 2022-03-25 | 中国科学院生态环境研究中心 | Method and system for reducing accumulation value of heavy metals in crops |
| CN114238858B (en) * | 2021-12-15 | 2022-09-30 | 中国科学院生态环境研究中心 | Method and system for reducing accumulation value of heavy metals in crops |
| CN115759420A (en) * | 2022-11-17 | 2023-03-07 | 中国科学院生态环境研究中心 | Crop heavy metal enrichment level mixed variable prediction method based on ion activity theory |
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