Method and related equipment for screening suitability of planting crops on contaminated farmland in a region

Abstract

The application provides a contaminated farmland crop planting suitability screening method and related equipment, belonging to the safe utilization of contaminated farmland and crop screening technical field. The method comprises the following steps: collecting soil environment and agricultural product monitoring basic data of a screening area, pre-processing the monitoring basic data to obtain an effective basic data set; carrying out soil-agricultural product collaborative encryption investigation on the contaminated farmland; calculating index values of various crop varieties; screening the crop varieties according to preset preliminary selection conditions to obtain a preliminary test variety list meeting the conditions; carrying out field concentrated verification test on the preliminary test varieties in different cadmium pollution gradient farmlands; calculating a weighted evaluation value by using a preset non-equal weight weighted evaluation model, and comprehensively judging in combination with yield data and agronomic trait stability; and determining the crop varieties with comprehensive evaluation results meeting preset suitability judgment conditions as suitability varieties. The application can be used for guiding planting structure adjustment.

Description

Technical Field

[0001] This application relates to the field of safe utilization of contaminated arable land and crop screening technology, and in particular to methods and related equipment for screening the suitability of crops for planting on contaminated arable land in a region. Background Technology

[0002] In related technologies, the screening criteria are mostly empirical or qualitative descriptions. The standards are not uniform when different personnel and different regions implement them, resulting in highly subjective screening results with poor repeatability, making it difficult to compare and promote their application in different regions.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] The main purpose of this application is to propose a method and related equipment for screening the suitability of crops for planting on polluted arable land in a region, which can be used to guide the adjustment of planting structure.

[0005] To achieve the above objectives, one aspect of this application proposes a method for screening the suitability of crops for planting on contaminated arable land within a region, the method comprising the following steps: Collect basic monitoring data on soil environment and agricultural products in the screening area, and preprocess the basic monitoring data to obtain an effective basic dataset; Based on the aforementioned effective basic dataset, a collaborative intensive survey of soil and agricultural products was conducted on contaminated farmland to obtain collaborative detection datasets of soil and agricultural products for each crop variety. Based on the collaborative detection dataset, the index values ​​of each crop variety are calculated to obtain the core index dataset of each variety; the index values ​​include cadmium pollution index, cadmium exceedance rate and cadmium enrichment coefficient; Based on the core indicator dataset, the crop varieties are screened according to preset preliminary selection conditions to obtain a preliminary list of qualified test varieties. Based on the preliminary list of test varieties, the preliminary test varieties were subjected to concentrated field verification trials on farmland with different cadmium pollution gradients to obtain field verification index datasets and yield data. Based on the field verification index dataset, a pre-set non-equal weighted evaluation model is used to calculate the weighted evaluation value, and the yield data and agronomic trait stability are combined for comprehensive judgment to obtain the comprehensive evaluation results of each tested variety. The crop varieties whose comprehensive evaluation results meet the preset suitability criteria are identified as suitable varieties.

[0006] In some embodiments, the collection and screening of basic monitoring data on soil environment and agricultural products in the screening area, and the preprocessing of the basic monitoring data to obtain an effective basic dataset, includes: Collect basic monitoring data on soil environment and agricultural products in the screening area; the basic monitoring data includes the administrative division of polluted farmland in the screening area, soil type vector map, soil physicochemical properties, climate and meteorological data, and historical survey data on cadmium pollution in farmland soil; The monitoring data is preprocessed to retain valid data that meets preset data integrity requirements, preset data accuracy requirements, and preset timeliness requirements, thus obtaining a valid basic dataset. The preprocessing includes consistency and reasonableness checks, and the removal of records that are judged to be outliers and invalid data; The consistency and rationality review includes: checking the reliability of the data source, the standardization of the data recording format, the temporal logical consistency of multiple monitoring data at the same sampling point, the rationality of the correlation between soil cadmium content and agricultural product cadmium content, and whether the monitoring data is within a reasonable range of instrument detection range and geographical space. The records of outliers and invalid data include: records where the detection value exceeds the linear range of the instrument, records where the coordinates of the sampling point exceed the administrative boundaries of the screening area, records where key fields are missing and therefore cannot be included in the calculation, and records that are determined to be outliers by statistical testing and for which there is no reasonable explanation. The effective basic dataset includes sampling point information, soil cadmium content, agricultural product cadmium content, and corresponding crop variety information.

[0007] In some embodiments, the step of conducting a soil-agricultural product collaborative intensive survey of contaminated farmland based on the effective basic dataset to obtain a soil-agricultural product collaborative detection dataset for each crop variety includes: Based on the effective basic dataset and combined with local planting habits information in the screening area, the types of crop varieties to be investigated are determined, and the total number of collaborative sampling points for a single crop variety is set to be no less than the preset minimum sampling number. Supplementary sampling is carried out for varieties that do not meet the data volume requirements or have no collaborative soil data. During the crop harvest season, soil and crop samples were collected from the same locations at the same time. For paddy fields, sampling points were densely distributed according to the first preset grid size, and for dry land, sampling points were densely distributed according to the second preset grid size. Sampling was performed according to preset sampling specifications. Soil sampling was conducted using a multi-point mixing method to collect topsoil, removing the contact surface with bamboo strips or wooden shovels and retaining a preset soil sample volume. Agricultural product sampling was conducted by collecting edible parts of agricultural products; for vegetables, a preset fresh weight sample volume was collected, and for grains, a preset dry weight sample volume was collected. The latitude and longitude coordinates of each sampling point were recorded. Heavy metal content was tested on collected soil and agricultural product samples. The test indicators included at least cadmium content. Cadmium data below the detection limit were replaced with a preset detection limit value for statistical analysis, resulting in a collaborative detection dataset of soil cadmium content and agricultural product cadmium content corresponding to each crop variety.

[0008] In some embodiments, the step of calculating the index values ​​for each crop variety based on the collaborative detection dataset to obtain the core index dataset for each variety includes: Based on the collaborative detection dataset, according to the crop variety classification, the cadmium content of the edible parts of agricultural products and the soil cadmium content of the corresponding sampling points of each crop variety are obtained one by one. Based on the cadmium content in the edible parts of the agricultural products and the cadmium content in the soil, the index values ​​for each crop variety are calculated; the index values ​​include the cadmium pollution index, the cadmium exceedance rate, and the cadmium enrichment coefficient. The calculation of the cadmium pollution index includes: dividing the cadmium content of the edible part of the agricultural product at each sampling point by the preset food contaminant limit standard value corresponding to the crop variety category to obtain the cadmium pollution index of each sampling point, and taking the arithmetic mean of the cadmium pollution index of all sampling points of the crop variety as the cadmium pollution index of the crop variety. The calculation of the cadmium exceedance rate includes: determining whether the cadmium content of the edible part of the agricultural product at each sampling point exceeds the food contaminant limit standard value, counting the number of samples exceeding the standard, dividing the number of samples exceeding the standard by the total number of samples of the crop variety, and then multiplying by 100% to obtain the cadmium exceedance rate of the crop variety. The calculation of the cadmium enrichment coefficient includes: dividing the cadmium content of the edible part of the agricultural product at each sampling point by the cadmium content of the soil at the corresponding sampling point to obtain the cadmium enrichment coefficient of each sampling point, and taking the arithmetic mean of the cadmium enrichment coefficients of all sampling points of the crop variety as the cadmium enrichment coefficient of the crop variety. The cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient of each crop variety are summarized to form a core indicator dataset containing crop variety names and corresponding indicator values.

[0009] In some embodiments, the step of screening crop varieties according to preset preliminary selection criteria based on the core indicator dataset to obtain a preliminary list of qualified test varieties includes: Based on the core indicator dataset, the cadmium exceedance rate, cadmium pollution index and cadmium enrichment coefficient of each crop variety are determined in sequence. The preset preliminary selection conditions include: the cadmium exceedance rate is less than or equal to the preset exceedance rate threshold, the cadmium pollution index is less than or equal to the preset pollution index threshold, and the cadmium enrichment coefficient is less than or equal to the preset enrichment coefficient threshold. The crop varieties that meet one of the preset preliminary selection conditions are selected, and the variety name and the corresponding index value of the crop variety are recorded to form a preliminary list of test varieties.

[0010] In some embodiments, the step of conducting concentrated field validation trials on farmland with different cadmium pollution gradients based on the preliminary list of test varieties, and obtaining field validation index datasets and yield data, includes: At least two test plots with different cadmium pollution gradients were selected within the screening area. The soil cadmium content of the first test plot was between the screening value and the control value of the preset soil pollution risk screening standard, and the soil cadmium content of the second test plot was higher than the control value of the preset soil pollution risk screening standard. The irrigation water quality of each test plot met the preset farmland irrigation water quality standard. Each crop variety in the preliminary list of test varieties will be planted in test plots with different cadmium pollution gradients. The test period will be no less than the preset minimum number of independent growth cycles. The planting plot area of ​​each crop variety will be no less than the preset minimum plot area. The preset number of replicates will be adopted. The random block arrangement or a combination of random block and comparison method will be used. The cultivation and management will be uniform. During the crop maturity period, soil and agricultural products of each plot of each crop variety were collected simultaneously. A preset number of mixed samples were collected from each experimental plot. The cadmium content of the soil and agricultural product samples was tested. At the same time, the yield of each plot of each crop variety was measured and the yield data of each crop variety was recorded. The data on cadmium content of agricultural products, corresponding soil cadmium content, and yield of each crop variety under different cadmium pollution gradients and different growth cycles were compiled to form a field validation index dataset and yield data.

[0011] In some embodiments, the step of calculating weighted evaluation values ​​using a preset non-equal weighted evaluation model based on the field validation index dataset, and combining the yield data with the stability of agronomic traits for comprehensive judgment, to obtain the comprehensive evaluation results of each tested variety, includes: Based on the field validation index dataset, cadmium content detection data of agricultural products of each tested variety under different cadmium pollution gradient plots and different growth cycles were extracted, and the index values ​​of each variety were recalculated; the index values ​​include the cadmium pollution index, the cadmium exceedance rate, and the cadmium enrichment coefficient. A pre-defined non-equal weighted evaluation model is used to calculate the weighted values ​​of the indicators. In the non-equal weighted evaluation model, the cadmium pollution index is assigned a first pre-defined weight, the cadmium exceedance rate is substituted in decimal form and assigned a second pre-defined weight, and the cadmium enrichment coefficient is assigned a third pre-defined weight. The weighted evaluation value is calculated by multiplying the cadmium pollution index by the first pre-defined weight, the cadmium exceedance rate by the second pre-defined weight, and the cadmium enrichment coefficient by the third pre-defined weight. Simultaneously, the yield data and agronomic trait stability are combined for auxiliary judgment to obtain yield comparison results and agronomic trait stability performance information; the auxiliary judgment combining the yield data and agronomic trait stability includes: comparing the yield data of each tested variety with the yield data of the same variety in the screening area, determining whether there are differences between the two that meet the preset conditions, and observing whether the agronomic trait performance of each tested variety is stable and consistent under different growth cycles and different pollution gradients. A comprehensive evaluation result was obtained based on the weighted evaluation value of each tested variety, the yield comparison results, and the information on the stability of agronomic traits.

[0012] To achieve the above objectives, another aspect of this application provides a device for screening the suitability of crops for planting on contaminated arable land within a region. The device includes: The first module is used to collect basic monitoring data on soil environment and agricultural products in the screening area, and to preprocess the basic monitoring data to obtain an effective basic dataset. The second module is used to conduct a soil-agricultural product collaborative intensive survey of contaminated farmland based on the effective basic dataset, and obtain a soil-agricultural product collaborative detection dataset for each crop variety. The third module is used to calculate the index values ​​of each crop variety based on the collaborative detection dataset, and obtain the core index dataset of each variety; the index values ​​include cadmium pollution index, cadmium exceedance rate and cadmium enrichment coefficient; The fourth module is used to screen the crop varieties according to the core indicator dataset and preset preliminary selection conditions to obtain a list of preliminary test varieties that meet the conditions. The fifth module is used to conduct centralized field verification trials on farmland with different cadmium pollution gradients based on the preliminary list of test varieties, and to obtain a dataset of field verification indicators and yield data. The sixth module is used to calculate the weighted evaluation value based on the field verification index dataset using a preset non-equal weighted evaluation model, and to make a comprehensive judgment by combining the yield data and the stability of agronomic traits to obtain the comprehensive evaluation result of each tested variety. The seventh module is used to determine the crop varieties whose comprehensive evaluation results meet the preset suitability judgment conditions as suitable varieties.

[0013] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a method, apparatus, electronic device, storage medium, and program product for screening the suitability of crops for planting in polluted arable land within a region. The scheme includes: collecting basic monitoring data on soil environment and agricultural products in the screening area; preprocessing the basic monitoring data to obtain an effective basic dataset; conducting a soil-agricultural product synergistic intensive survey of polluted arable land; calculating the index values ​​of each crop variety; screening crop varieties according to preset preliminary selection conditions to obtain a list of preliminary selected test varieties that meet the conditions; conducting concentrated field verification tests on the preliminary selected test varieties on arable land with different cadmium pollution gradients; calculating weighted evaluation values ​​using a preset non-equal weighted evaluation model, and making a comprehensive judgment based on yield data and agronomic trait stability; and determining crop varieties whose comprehensive evaluation results meet the preset suitability judgment conditions as suitable varieties. This application can be used to guide the adjustment of planting structure. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for screening crop suitability for contaminated farmland within a region, provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0021] 1) GB2762, National Food Safety Standard, Limits of Contaminants in Food, specifies the limits for contaminants such as lead, cadmium, mercury, arsenic, and chromium in various foods such as grains, vegetables, fruits, beans, and potatoes.

[0022] 2) GB15618, "Soil Environmental Quality Standard for Risk Control of Soil Pollution in Agricultural Land (Trial)". This standard specifies the screening and control values ​​for soil pollution risk in agricultural land. The screening value indicates that when the soil pollutant content is below this value, the risk of agricultural products exceeding the standard is low; the control value indicates that when the content exceeds this value, the risk of agricultural products exceeding the standard is high, and in principle, strict control measures should be taken.

[0023] 3) GB5084, "Standards for Irrigation Water Quality in Farmland". This standard specifies the water quality requirements for irrigation water in farmland, including limits for indicators such as heavy metals and organic pollutants.

[0024] 4) NY / T 395, Technical Specification for Monitoring of Farmland Soil Environmental Quality. This standard specifies the technical requirements for the site selection, sample collection, sample preparation, sample preservation, testing and analysis, and quality control of farmland soil environmental quality monitoring.

[0025] 5) NY / T 398, Technical Specifications for Pollution Monitoring of Agricultural, Livestock and Aquatic Products. This standard specifies the technical requirements for sample collection, preparation, preservation, testing and quality control for pollution monitoring of agricultural products.

[0026] 6) GB 5009.11, National Food Safety Standard - Determination of Total Arsenic and Inorganic Arsenic in Food. This standard specifies the methods for determining total arsenic and inorganic arsenic in food.

[0027] 7) GB 5009.12, National Food Safety Standard - Determination of Lead in Food. This standard specifies the methods for determining the lead content in food, including graphite furnace atomic absorption spectrometry and inductively coupled plasma mass spectrometry.

[0028] 8) GB 5009.15, National Food Safety Standard - Determination of Cadmium in Food. This standard specifies the method for determining the cadmium content in food.

[0029] 9) GB 5009.17, National Food Safety Standard - Determination of Total Mercury and Organic Mercury in Food. This standard specifies the methods for determining total mercury and organic mercury in food.

[0030] 10) GB 5009.123, National Food Safety Standard - Determination of Chromium in Food. This standard specifies the method for determining the chromium content in food.

[0031] 11) GB 5009.268, National Food Safety Standard - Determination of Multiple Elements in Food. This standard specifies methods for the simultaneous determination of multiple elements in food using inductively coupled plasma mass spectrometry and inductively coupled plasma atomic emission spectrometry.

[0032] This application takes into account that, with the increasing prominence of heavy metal pollution in arable land, the safe production of agricultural products from arable land with cadmium as the main pollutant has become a core issue in agricultural ecological environmental protection. Cadmium is easily absorbed and accumulated by crops into the food chain, posing a potential risk to human health. Screening and large-scale cultivation of crops with low heavy metal accumulation is a key technological approach to achieving the safe utilization of contaminated arable land, controlling food chain risks, and ensuring the sustainability of agricultural production.

[0033] In related technologies, the screening of crops with low heavy metal accumulation in contaminated farmland lacks a systematic process: (1) the screening indicators are singular, mostly based on enrichment coefficients, without comprehensively considering pollution levels and the risk of exceeding standards; (2) there is a lack of a unified and quantitative weighted evaluation system, and the judgment criteria are vague; (3) there is a lack of multi-cycle and multi-gradient field verification, resulting in insufficient stability of the results. The above defects lead to poor applicability and scalability of existing screening methods, and cannot provide scientific and effective variety support for alternative planting and planting structure adjustment in contaminated farmland.

[0034] In view of this, this application provides a method and related equipment for screening the suitability of crops for planting on contaminated arable land within a region, belonging to the technical field of safe utilization of contaminated arable land and crop screening. The method includes steps such as data collection, sampling and monitoring, initial selection of test varieties, regional field verification, comprehensive evaluation, and variety list construction. Using cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient as core indicators, a non-equal weighted evaluation system of 0.5:0.3:0.2 is constructed. Field verification is conducted for arable land with different levels of pollution for no less than two growth cycles to ensure the stability and reliability of the screening results. Finally, the weighted evaluation value is used as the standard for determining planting suitability. This application addresses the problems of existing screening methods having single indicators, vague judgment standards, and a lack of large-scale field verification. The screening results can be directly used for adjusting the planting structure of contaminated arable land and managing agricultural product safety risks.

[0035] Figure 1 This is an optional flowchart of the method for screening crop suitability for contaminated arable land within a region, provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S107.

[0036] Step S101: Collect basic monitoring data on soil environment and agricultural products in the screening area, preprocess the basic monitoring data to obtain an effective basic dataset; Step S102: Based on the effective basic dataset, conduct a soil-agricultural product collaborative intensive survey on the contaminated farmland to obtain a soil-agricultural product collaborative detection dataset for each crop variety. Step S103: Based on the collaborative detection dataset, calculate the index values ​​for each crop variety to obtain the core index dataset for each variety; the index values ​​include cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient. Step S104: Based on the core indicator dataset, crop varieties are screened according to preset preliminary selection conditions to obtain a list of preliminary test varieties that meet the conditions. Step S105: Based on the preliminary list of test varieties, conduct field verification trials on farmland with different cadmium pollution gradients to obtain field verification index datasets and yield data. Step S106: Based on the field verification index dataset, calculate the weighted evaluation value using a preset non-equal weighted evaluation model, and make a comprehensive judgment by combining yield data and agronomic trait stability to obtain the comprehensive evaluation results of each tested variety. Step S107: Crop varieties whose comprehensive evaluation results meet the preset suitability criteria are identified as suitable varieties.

[0037] Steps S101 to S107 as shown in the embodiments of this application involve sequentially executing these screening steps to transform the historical monitoring data of contaminated farmland into a valid basic dataset after quality review. Based on this, a soil-agricultural product collaborative intensive survey is conducted to obtain a one-to-one collaborative detection dataset. Then, the cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient of each crop variety are calculated to form a core indicator dataset. The three core indicators are then used to initially select varieties to obtain a list of test varieties. Subsequently, the initially selected varieties are placed on farmland with different cadmium pollution gradients to conduct multi-cycle field centralized verification experiments to obtain field verification indicators and yield data. Finally, a non-equal weighted evaluation model is used to comprehensively score each test variety and make a final judgment based on yield and agronomic trait stability. In this way, suitable planting varieties with low cadmium accumulation, low risk of exceedance, and stable yield are selected from the contaminated farmland.

[0038] In some embodiments, step S101 may include, but is not limited to, steps S111 to S112: Step S111: Collect basic monitoring data on soil environment and agricultural products in the screening area; the basic monitoring data includes the administrative division of polluted farmland in the screening area, soil type vector map, soil physicochemical properties, climate and meteorological data, and historical survey data on cadmium pollution in farmland soil. Step S112: Preprocess the monitoring basic data, retain the valid data that meets the preset data integrity requirements, preset data accuracy requirements and preset timeliness requirements, and obtain the valid basic dataset; Preprocessing includes consistency and reasonableness checks, and the removal of records that are judged to be outliers or invalid data; Consistency and reasonableness review includes: checking the reliability of data sources, the standardization of data recording formats, the temporal logical consistency of multiple monitoring data from the same sampling point, the reasonableness of the correlation between soil cadmium content and agricultural product cadmium content, and whether the monitoring data is within a reasonable range of instrument detection range and geographical space. Outlier and invalid data records include: records where the detection value exceeds the linear range of the instrument, records where the sampling point coordinates exceed the administrative boundaries of the screening area, records where key fields are missing and therefore cannot be included in the calculation, and records that are determined to be outliers by statistical testing without a reasonable explanation. The effective basic dataset includes sampling point information, soil cadmium content, agricultural product cadmium content, and corresponding crop variety information.

[0039] In steps S111 to S112 of some embodiments, standardized data review and preprocessing are used to eliminate noise and errors in historical data, ensuring that subsequent encrypted sampling and analysis are based on reliable data, thus avoiding deviations in screening results due to issues with the quality of the basic data. For example, in the screening of 29 crops, if outliers exist in the basic data and are not removed, the cadmium pollution index of some varieties may be incorrectly calculated, thereby affecting the accuracy of the initial selection results.

[0040] In some embodiments, step S102 may include, but is not limited to, steps S201 to S203: Step S201: Based on the effective basic dataset and combined with local planting habit information in the screening area, determine the types of crop varieties to be investigated, set the total number of collaborative sampling points for a single crop variety to be no less than the preset minimum sampling number, and conduct supplementary sampling for varieties that do not meet the data volume requirements or have no collaborative soil data. Step S202: During the crop harvest season, soil and crop samples are collected at the same locations and at the same time. For paddy fields, sampling points are densely distributed according to the first preset grid size, and for dry land, sampling points are densely distributed according to the second preset grid size. Sampling is performed according to preset sampling specifications. Soil sampling is set as follows: a multi-point mixing method is used to collect topsoil, and a preset soil sample volume is retained after removing the contact surface using bamboo strips or wooden shovels. Agricultural product sampling is set as follows: edible parts of agricultural products are collected, with a preset fresh weight sample volume for vegetables and a preset dry weight sample volume for grains. The latitude and longitude coordinates of each sampling point are recorded. Step S203: The collected soil and agricultural product samples are tested for heavy metal content. The test indicators include at least cadmium content. Cadmium data below the detection limit are replaced by a preset detection limit value for statistical analysis to obtain a collaborative detection dataset of soil cadmium content and agricultural product cadmium content corresponding to each crop variety.

[0041] In steps S201 to S203 of some embodiments, the survey varieties can be determined based on the effective basic dataset and local planting habits. The total number of sampling points for a single variety should not be less than 15. Supplementary sampling is conducted for varieties with insufficient data. During the harvest season, soil and agricultural product samples are collected simultaneously at the same locations. For paddy fields, sampling points are arranged in a 500m×500m grid, and for dry land, in a 1000m×1000m grid. Approximately 1.0kg of soil sample from the 0-20cm topsoil layer is collected, along with 1000g of fresh weight for vegetables and 500g of dry weight for grains. Cadmium data below the detection limit are included in the statistical analysis at half the detection limit. Finally, a one-to-one corresponding dataset of soil and agricultural product cadmium content is obtained. Simultaneous sampling at the same locations eliminates spatial and temporal mismatches between soil and agricultural product data. The dense grid layout ensures that sampling covers the spatial variation of the entire screening area. The sample size of at least 15 points guarantees statistical representativeness, and the half-detection-limit substitution avoids data loss. For example, hundreds of co-existing samples were collected from 29 crops, obtaining reliable data covering different soil types. This enabled the subsequent calculations of cadmium pollution index values ​​such as 0.408 for Chinese cabbage and 0.046 for green beans to accurately reflect the actual performance of each variety in the region.

[0042] In some embodiments, step S103 may include, but is not limited to, steps S301 to S303: Step S301: Based on the collaborative detection dataset, classify by crop variety, and obtain the cadmium content of the edible parts of agricultural products and the soil cadmium content of the corresponding sampling points for each crop variety. Step S302: Calculate the index values ​​for each crop variety based on the cadmium content in the edible parts of agricultural products and the cadmium content in the soil; the index values ​​include the cadmium pollution index, the cadmium exceedance rate, and the cadmium enrichment coefficient. The calculation of the cadmium pollution index includes: dividing the cadmium content of the edible part of the agricultural product at each sampling point by the preset food contaminant limit standard value corresponding to the crop variety category to obtain the cadmium pollution index of each sampling point, and taking the arithmetic mean of the cadmium pollution index of all sampling points of the crop variety as the cadmium pollution index of the crop variety. The calculation of cadmium exceedance rate includes: determining whether the cadmium content of the edible parts of agricultural products at each sampling point exceeds the food contaminant limit standard value, counting the number of samples exceeding the standard, dividing the number of samples exceeding the standard by the total number of samples of crop variety, and then multiplying by 100% to obtain the cadmium exceedance rate of crop variety. The calculation of the cadmium enrichment coefficient includes: dividing the cadmium content of the edible part of the agricultural product at each sampling point by the cadmium content of the soil at the corresponding sampling point to obtain the cadmium enrichment coefficient of each sampling point, and taking the arithmetic mean of the cadmium enrichment coefficients of all sampling points of the crop variety as the cadmium enrichment coefficient of the crop variety. Step S303: Summarize the cadmium pollution index, cadmium exceedance rate and cadmium enrichment coefficient of each crop variety to form a core indicator dataset containing crop variety names and corresponding indicator values.

[0043] In steps S301 to S303 of some embodiments, based on the collaborative detection dataset, three core indicators are calculated for each variety: the cadmium pollution index is the arithmetic mean of the cadmium content of agricultural products at each sampling point divided by the GB2762 limit standard value, reflecting the degree of exceedance; the cadmium exceedance rate is the number of exceedance samples divided by the total number of samples multiplied by 100%, reflecting the probability of exceedance; and the cadmium enrichment coefficient is the arithmetic mean of the cadmium content of agricultural products at each sampling point divided by the corresponding soil cadmium content, reflecting the absorption and enrichment capacity. These are then compiled into a core indicator dataset containing the variety name and the values ​​of the three indicators. These three indicators complement each other, providing a comprehensive evaluation from three dimensions: the degree of exceedance, the probability of exceedance, and the enrichment capacity, overcoming the one-sidedness of single-indicator screening. For example, spinach had a cadmium pollution index of 1.412 (exceeding the standard), an exceedance rate of 46.0%, and an enrichment coefficient of 0.441. All three indicators were poor, and it was accurately identified as a high-risk variety. Lettuce, on the other hand, had a cadmium pollution index of 0.307 (not exceeding the standard), but an exceedance rate of 6.7% and an enrichment coefficient of 0.148. These three indicators comprehensively reflected its risk level.

[0044] In some embodiments, step S104 may include, but is not limited to, steps S401 to S402: Step S401: Based on the core indicator dataset, determine the cadmium exceedance rate, cadmium pollution index and cadmium enrichment coefficient of each crop variety in sequence, and set preset preliminary selection conditions including: cadmium exceedance rate is less than or equal to preset exceedance rate threshold, cadmium pollution index is less than or equal to preset pollution index threshold, and cadmium enrichment coefficient is less than or equal to preset enrichment coefficient threshold. Step S402: Select crop varieties that meet one of the preset preliminary selection conditions, record the variety name and the corresponding index value of the crop variety, and form a preliminary list of test varieties.

[0045] In steps S401 to S402 of some embodiments, based on the core indicator dataset, preliminary selection conditions can be set as follows: cadmium exceedance rate ≤10%, cadmium pollution index ≤1, or cadmium enrichment coefficient ≤1. Meeting any one of these conditions allows a variety to be included in the preliminary list of test varieties. This flexible parallel screening strategy, requiring only one of the three conditions to be met, avoids overlooking potentially suitable varieties due to stringent single indicators, while quickly eliminating high-risk varieties with poor performance across all three indicators, narrowing the scope of subsequent field validation and improving screening efficiency. For example, in Table 1 of this application's embodiments, spinach was excluded because it did not meet all three indicators; varieties such as green beans (cadmium pollution index 0.046), snow peas (cadmium pollution index 0.046), and broccoli (cadmium pollution index 0.133), although exhibiting excellent performance in one indicator, were retained for field validation through the parallel selection criteria.

[0046] In some embodiments, step S105 may include, but is not limited to, steps S501 to S504: Step S501: Select at least two test plots with different cadmium pollution gradients within the screening area. The soil cadmium content of the first test plot is between the screening value and the control value of the preset soil pollution risk screening standard, and the soil cadmium content of the second test plot is higher than the control value of the preset soil pollution risk screening standard. The irrigation water quality of each test plot meets the preset farmland irrigation water quality standard. Step S502: Plant each crop variety in the preliminary list of test varieties on test plots with different cadmium pollution gradients. The test period shall not be less than the preset minimum number of independent growth cycles. The planting plot area of ​​each crop variety shall not be less than the preset minimum plot area. The preset number of replicates shall be adopted. The random block arrangement or a combination of random block and comparison method shall be used. The cultivation and management shall be uniform. Step S503: During the crop maturity period, soil and agricultural products of each crop variety in each plot are collected simultaneously. A preset number of mixed samples are collected from each experimental plot. The cadmium content of the soil and agricultural product samples is tested. At the same time, the yield of each crop variety in each plot is measured and the yield data of each crop variety is recorded. Step S504: Summarize the cadmium content detection data of agricultural products, corresponding soil cadmium content data, and yield data of each crop variety under different cadmium pollution gradients and different growth cycles to form a field validation index dataset and yield data.

[0047] In steps S501 to S504 of some embodiments, two types of pollution gradient test plots are selected—soil cadmium content between the GB15618 screening value and the control value, and above the control value; irrigation water meets the requirements of GB5084. Tests are conducted on the initially selected varieties for no less than two independent growth cycles, with each variety having a plot area ≥30m². 2Three replicates were performed, arranged using a randomized block or comparable method, with uniform cultivation management. Soil and agricultural product samples were collected simultaneously at maturity, and yields were measured. Different pollution gradients were set up to cover safe-use and strictly controlled arable land. At least two growth cycles were used to eliminate the interference of interannual climate differences on variety performance. Three replicates and plot areas ≥30m² were used. 2 This ensured the statistical validity of the experiment. For example, soil cadmium levels of 0.64 mg / kg in plot 1 and 1.67 mg / kg in plot 2 represented two different control categories. The spring and autumn experiments accumulated data from 12 samples for each variety, ensuring that the seven varieties selected, including broccoli, corn, and green beans, performed stably on both types of farmland and could be directly used for practical promotion.

[0048] In some embodiments, step S106 may include, but is not limited to, steps S601 to S604: Step S601: Based on the field verification index dataset, extract the cadmium content detection data of agricultural products of each tested variety under different cadmium pollution gradient plots and different growth cycles, and recalculate the index values ​​of each variety; the index values ​​include cadmium pollution index, cadmium exceedance rate and cadmium enrichment coefficient. Step S602: Using a pre-set non-equal weighted evaluation model, the index values ​​are weighted and calculated. In the non-equal weighted evaluation model, the cadmium pollution index is assigned a first pre-set weight, the cadmium exceedance rate is substituted in decimal form and assigned a second pre-set weight, and the cadmium enrichment coefficient is assigned a third pre-set weight. The weighted evaluation value is calculated by multiplying the cadmium pollution index by the first pre-set weight, the cadmium exceedance rate by the second pre-set weight, and the cadmium enrichment coefficient by the third pre-set weight. Step S603: Simultaneously, combine yield data with agronomic trait stability for auxiliary judgment to obtain yield comparison results and agronomic trait stability performance information; the auxiliary judgment combining yield data with agronomic trait stability includes: comparing the yield data of each tested variety with the yield data of similar varieties in the screening area, determining whether there are differences between the two that meet the preset conditions, and observing whether the agronomic trait performance of each tested variety is stable and consistent under different growth cycles and different pollution gradients. Step S604: Based on the weighted evaluation values ​​of each tested variety, yield comparison results, and agronomic trait stability information, a comprehensive evaluation result is obtained.

[0049] In steps S601 to S604 of some embodiments, this step recalculates the cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient for each variety based on field validation data. A non-equal-weighted evaluation model is used, with a weighted evaluation value calculated using a weight of 0.5 for the cadmium pollution index, 0.3 for the cadmium exceedance rate, and 0.2 for the cadmium enrichment coefficient (formula: weighted evaluation value = P × 0.5 + ER × 0.3 + BCF × 0.2). Simultaneously, the yield of each variety is compared with that of similar varieties in the local area to determine if there are significant differences, and the stability of agronomic traits under different cycles and gradients is observed. The evaluation results are then comprehensively derived. The weights are determined through the analytic hierarchy process and expert scoring. The cadmium pollution index, directly related to food safety limits, is assigned the highest weight of 0.5, ensuring that food safety is the primary focus of the evaluation. The weighted evaluation value combines the three indicators into a single numerical value, making the judgment intuitive and unified. Combining yield and agronomic trait stability avoids selecting varieties that are safe for consumption but have low yields, poor production returns, and are undesirable for farmers, thus ensuring the acceptability of the screening results in agricultural production.

[0050] As an optional implementation, the method for screening crop suitability for contaminated arable land within a region according to this application includes the following steps: S1 collects and screens basic data on soil environment and agricultural products in the screening area, and conducts data quality review and removes invalid data; S2 conducted soil testing on contaminated farmland. Collaborative and encrypted surveys of agricultural products; S3 calculates the cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient of different crops within the region; S4 preliminarily screens test varieties based on indicator values; S5 conducted a concentrated field verification experiment on farmland with different cadmium pollution gradients; S6 uses non-equal weighting to calculate the core indicators and conducts a comprehensive evaluation by combining yield and trait stability. S7 recommends suitable varieties for planting based on the weighted evaluation value range.

[0051] In step S2: soil for each crop The total number of sampling points for agricultural products shall not be less than 15; the sampling points shall be densely distributed at 500m×500m for paddy fields and 1000m×1000m for dry land; the sampling shall be carried out in accordance with NY / T 395 and NY / T 398; cadmium data below the detection limit shall be included in the statistics at half the detection limit.

[0052] In step S3: Cadmium exceedance rate ER = number of samples exceeding the standard / total number of samples × 100%; Cadmium pollution index P = cadmium content in edible parts of crops / food contaminant limit standard value; Cadmium enrichment coefficient BCF = cadmium content in edible parts of crops / soil cadmium content.

[0053] In step S4, the initial test varieties must meet one of the following conditions: cadmium exceedance rate ≤10%, cadmium pollution index ≤1, cadmium enrichment coefficient ≤1.

[0054] In step S5: centralized verification tests were conducted at different gradient pollution levels of soil heavy metal content, covering the range between the screening and control values ​​of GB 15618 and the levels above the control values; the plot area for each variety was no less than 30㎡, with 3 replicates; soil and agricultural product samples were collected simultaneously during the crop maturity period.

[0055] In step S6: Weighted evaluation value = P × 0.5 + ER (decimal) × 0.3 + BCF × 0.2; The comprehensive evaluation should take into account both yield and the stability of agronomic traits.

[0056] In step S7: Crops with a weighted evaluation value of <0.1 are considered suitable varieties for planting.

[0057] This application belongs to the field of farmland pollution control and crop selection technology, specifically involving a method for screening the suitability of crops for planting in polluted farmland within a region. It is applicable to crop screening, alternative planting, and planting structure adjustment for farmland with cadmium pollution as the main pollutant, which is classified as safe utilization land or strictly controlled land.

[0058] To address the shortcomings of related technologies, this invention provides a method for screening the suitability of crops for planting in contaminated arable land within a region, which features standardized processes, comprehensive indicators, quantitative judgment, and large-scale verification, thereby achieving stable, reliable, and directly applicable variety screening.

[0059] The embodiments of this application include: S1 Data and Information Collection: Collect historical survey data on soil pollution status and agricultural products at the provincial, municipal, and county levels, as well as relevant data from departments such as ecology and environment, agriculture and rural affairs, and research institutions; conduct consistency and rationality reviews on the data, remove outliers and invalid data, and retain valid data.

[0060] S2 Soil-Agricultural Product Collaborative Intensive Survey and Monitoring: Based on preliminary data analysis, dense sampling points were set up for contaminated farmland in the target area; the total number of sampling points for a single crop was no less than 15; paddy fields were arranged in a grid of 500m×500m and dry land in a grid of 1000m×1000m; sampling, sample preparation and testing were strictly carried out in accordance with NY / T 395 and NY / T 398; cadmium data below the detection limit were substituted into the statistics at half the detection limit.

[0061] S3 Core Indicator Calculation: Calculate the cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient for each crop: Cadmium exceedance rate ER = number of samples exceeding the standard / total number of samples × 100%; Cadmium pollution index P = cadmium content in edible parts of the crop / food contaminant limit standard value; Cadmium enrichment coefficient BCF = cadmium content in edible parts of the crop / soil cadmium content.

[0062] Preliminary selection of S4 test varieties: Varieties selected for field verification must meet one of the following conditions: cadmium exceedance rate ≤10%, pollution index ≤1 or enrichment coefficient ≤1. Varieties that meet the conditions will proceed to subsequent centralized field verification.

[0063] S5 Centralized Validation Test: Select representative production test sites with soil cadmium pollution gradient coverage: 1) between the GB 15618 screening value and the control value; 2) greater than the GB 15618 control value. Irrigation water quality meets the requirements of GB 5084; the test shall be conducted for no less than two independent growth cycles; the plot area for each variety shall be ≥30m². 2 The experiment was repeated three times, using a combination of randomized block and inter-component methods; uniform cultivation management was implemented, and soil and agricultural product samples were collected simultaneously at maturity.

[0064] S6 Weighted Overall Evaluation: A non-equal weighted model was used to calculate the weighted evaluation value, with a cadmium pollution index of 0.5, a cadmium exceedance rate of 0.3, and a cadmium enrichment coefficient of 0.2. The formula was: Weighted Evaluation Value = P × 0.5 + ER (decimal) × 0.3 + BCF × 0.2. Simultaneously, a comprehensive evaluation was conducted combining yield and trait stability. The selected crop varieties showed no significant difference in yield compared to similar varieties in the region, or significantly higher yields, to ensure the economic benefits of agricultural production.

[0065] S7 constructs a variety list: Based on the results of regional screening and verification and variety weighted evaluation, a weighted evaluation value of <0.1 was used as a unified judgment standard, and varieties that met the criteria were identified as low cadmium accumulation varieties. A list of applicable varieties for the region was constructed according to the categories of cereals, legumes, melons and fruits, root and tuber crops, leafy vegetables, and brassica, for use in adjusting the planting structure.

[0066] The beneficial effects of this application are: 1. Scientific combination of indicators: Taking the cadmium pollution index as the core, while taking into account the exceedance rate and enrichment coefficient, the evaluation is more comprehensive and objective.

[0067] 2. Clear weights and judgment values: The system adopts unequal weights of 0.5:0.3:0.2 and a judgment value of <0.1, with unified and repeatable judgment criteria.

[0068] 3. Standardized process: preliminary selection + centralized field verification + weighted evaluation + list construction, the results are stable and can be directly promoted and applied.

[0069] 4. High adaptability: It covers both safe-use and strictly controlled arable land, and can directly serve the adjustment of planting structure in polluted arable land.

[0070] The following is a detailed description and explanation of the solutions in the embodiments of the present invention, using specific application examples: In this application, cadmium-contaminated farmland in a certain city was used as the screening area. The heavy metal limit standard refers to GB 2762, and the soil pollution risk standard refers to GB 15618.

[0071] Example: Screening of crops with low cadmium accumulation in cadmium-contaminated farmland in a certain city: 1. Data and Information Collection (S1): Collect administrative divisions, soil type vector maps, soil physicochemical properties, climate and meteorological data, and historical survey data on cadmium pollution in arable land within the screening area; review and remove invalid data, and retain valid and latest data.

[0072] 2. Intensive Soil-Agricultural Product Collaborative Survey and Monitoring (S2): Based on the collected data and local planting habits, 29 main crops were identified for investigation, with no fewer than 15 co-sampling points for each variety. For varieties lacking sufficient data or without co-sampling soil data, supplementary sampling was conducted. During the crop harvest season, soil and crop samples were collected at the same locations and at the same time. Paddy fields were sampled using a 500m×500m grid, and dry land using a 1000m×1000m grid. Sampling was performed according to NY / T 395 and NY / T 398 standards. Soil samples were collected from the 0-20cm topsoil layer using a multi-point mixing method. After removing the contact surface with bamboo strips / wooden shovels, approximately 1.0kg of sample was retained. For agricultural products, edible parts were collected: 1000g fresh weight for vegetables and 500g dry weight for grains, with latitude and longitude coordinates recorded. A total of 29 soil-agricultural product co-sampling samples were tested. Cadmium data below the detection limit were replaced with the half detection limit.

[0073] 3. Sample monitoring: The analytical testing indicators include the heavy metal content (cadmium, mercury, arsenic, lead, chromium, etc.) in soil and agricultural product samples. Soil heavy metal analysis should be conducted according to the prescribed methods, referring to GB 5009.11, GB 5009.12, GB 5009.15, GB 5009.17, and GB5009.123, to determine the total arsenic (or inorganic arsenic, according to GB 2762), total lead, total cadmium, total mercury, and total chromium content in agricultural products; or referring to GB 5009.268 to determine multiple heavy metals in agricultural products. Laboratory control samples must meet the recovery rate requirements; laboratory parallel samples must meet the relative error requirements; and laboratory matrix spiked samples and matrix-spikeped parallel samples must meet the laboratory accuracy requirements.

[0074] 4. Calculation of core indicators and preliminary selection of test varieties (S3, S4): The cadmium pollution index (P), cadmium exceedance rate (ER), and cadmium enrichment coefficient (BCF) were calculated for each variety. Varieties meeting the criteria of cadmium exceedance rate ≤10%, pollution index ≤1, or enrichment coefficient ≤1, including Chinese cabbage, green beans, sweet potatoes, and corn, were selected for regional field validation. The calculated indicators and the selected varieties are shown in Table 1.

[0075] 5. Multi-gradient field validation trial (S5): Test sites were established in typical cadmium-contaminated farmland within the region. In test site 1, the soil pH was 4.96 and the total cadmium content was 0.64 mg / kg, falling between the screening and control values ​​in GB 15618, while the irrigation water quality met GB 5084 standards. In test site 2, the soil pH was 5.03 and the total cadmium content was 1.67 mg / kg, exceeding the control value in GB 15618, while the irrigation water quality met GB 5084 standards. The test period consisted of two independent growing seasons, spring and autumn. Eighteen varieties were selected for testing, with each variety having a plot area of ​​no less than 30 m². 2 The experiment was conducted with three replicates, using a combination of randomized block and inter-component methods. Cultivation and management were carried out uniformly according to local practices. After maturity, soil and agricultural product samples were collected simultaneously by variety and plot. Two mixed samples were collected from each experimental plot, for a total of 12 samples per crop variety. Cadmium content was tested and yield was determined.

[0076] 6. Weighted Overall Evaluation (S6): Weights were determined for 18 tested varieties using a combined weighting method, with the following weights: 0.5 for cadmium pollution index, 0.3 for cadmium exceedance rate, and 0.2 for cadmium enrichment coefficient. These weights were determined based on the analytic hierarchy process (AHP) and expert scoring, with the core criterion being the direct impact of the indicators on the safety of agricultural products (the cadmium pollution index is directly related to the GB 2762 limit standard and has the highest priority). A dynamic weight optimization scheme was also provided, incorporating entropy weighting combined with multi-source data (soil pH, organic matter content) to dynamically adjust the weights and improve the model's regional adaptability. The weighted evaluation value formula is: Weighted Evaluation Value = P × 0.5 + ER (decimal) × 0.3 + BCF × 0.2. The evaluation process combined yield and trait stability for comprehensive judgment: Statistical analysis of data from 18 crops showed that a weighted evaluation value < 0.1 indicates stable compliance with the GB 2762 limit requirements, thus identifying them as suitable varieties for planting. In this embodiment, the weighted evaluation values ​​of broccoli, zucchini, bitter melon, sweet potato, green beans, corn, and snow peas were <0.1, and their yields were not significantly different from those of similar local varieties, thus they were determined to be suitable varieties for planting. Refer to the verification test indicators and weighted calculation results in Table 2.

[0077] 7. Construction of a list of low-cadmium-accumulation varieties (S7): Based on the evaluation results, a list of recommended varieties for adjusting the planting structure of cadmium-contaminated arable land was constructed, with low-cadmium accumulation varieties categorized by crop type: Grains: Corn; Legumes: green beans, snow peas; Fruits and vegetables: zucchini, bitter melon; Root and tuber crops: sweet potato; Brass: Broccoli.

[0078] The above-mentioned varieties can be promoted and planted on local cadmium-contaminated farmland, which can stably ensure that the cadmium content of agricultural products meets the standards.

[0079] Table 1. Calculation results of indicators and screening of test varieties

[0080] This application embodiment also provides a crop suitability screening device for contaminated arable land in a region, which can implement the above method. The device includes: The first module is used to collect basic monitoring data on soil environment and agricultural products in the screening area, and to preprocess the basic monitoring data to obtain an effective basic dataset. The second module is used to conduct a joint intensive survey of soil and agricultural products on contaminated farmland based on an effective basic dataset, and to obtain a joint detection dataset of soil and agricultural products for each crop variety. The third module is used to calculate the index values ​​of each crop variety based on the collaborative detection dataset, and obtain the core index dataset of each variety; the index values ​​include cadmium pollution index, cadmium exceedance rate and cadmium enrichment coefficient. The fourth module is used to screen crop varieties according to preset preliminary selection conditions based on the core indicator dataset, and obtain a list of preliminary selected test varieties that meet the conditions. The fifth module is used to conduct centralized field verification trials on farmland with different cadmium pollution gradients based on the preliminary list of test varieties, and to obtain a dataset of field verification indicators and yield data. The sixth module is used to calculate the weighted evaluation value based on the field verification index dataset using a preset non-equal weighted evaluation model, and to make a comprehensive judgment by combining yield data and agronomic trait stability to obtain the comprehensive evaluation results of each tested variety. The seventh module is used to identify crop varieties whose comprehensive evaluation results meet the preset suitability criteria as suitable varieties.

[0081] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0082] Table 2. Verification test indicators and weighted calculation results

[0083] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0084] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0085] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0086] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0087] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0088] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0089] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0090] The method, apparatus, electronic equipment, storage medium, and program products for screening crop suitability in contaminated arable land provided in this application establish a screening process of "data collection—collaborative intensive investigation—calculation of three core indicators—preliminary selection under three conditions—multi-gradient and multi-cycle field centralized verification—non-equal weighted evaluation—threshold determination to construct a list." Using cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient as the core indicators, a non-equal weighted evaluation model is employed. For example, a weighted evaluation value of 0.5 for the cadmium pollution index, 0.3 for the cadmium exceedance rate, and 0.2 for the cadmium enrichment coefficient is used. A weighted evaluation value less than 0.1 is used as a unified judgment standard. This achieves quantitative, repeatable, stable, and reliable screening of crop suitability in contaminated arable land. The screening results can be directly used to guide the adjustment of planting structure and the management of agricultural product safety risks in contaminated arable land.

[0091] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0092] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0093] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0095] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0096] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0098] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0100] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0101] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for screening the suitability of planting a crop on a contaminated farmland in a region, characterized by, The method includes the following steps: Collect basic monitoring data on soil environment and agricultural products in the screening area, and preprocess the basic monitoring data to obtain an effective basic dataset; Based on the aforementioned effective basic dataset, a collaborative intensive survey of soil and agricultural products was conducted on contaminated farmland to obtain collaborative detection datasets of soil and agricultural products for each crop variety. Based on the collaborative detection dataset, the index values ​​of each crop variety are calculated to obtain the core index dataset of each variety; the index values ​​include cadmium pollution index, cadmium exceedance rate and cadmium enrichment coefficient; Based on the core indicator dataset, the crop varieties are screened according to preset preliminary selection conditions to obtain a preliminary list of qualified test varieties. Based on the preliminary list of test varieties, the preliminary test varieties were subjected to concentrated field verification trials on farmland with different cadmium pollution gradients to obtain field verification index datasets and yield data. Based on the field verification index dataset, a pre-set non-equal weighted evaluation model is used to calculate the weighted evaluation value, and the yield data and agronomic trait stability are combined for comprehensive judgment to obtain the comprehensive evaluation results of each tested variety. The crop varieties whose comprehensive evaluation results meet the preset suitability criteria are identified as suitable varieties.

2. The method of claim 1, wherein, The basic monitoring data of soil environment and agricultural products in the collected screening area are preprocessed to obtain a valid basic dataset, including: Collect basic monitoring data on soil environment and agricultural products in the screening area; the basic monitoring data includes the administrative division of polluted farmland in the screening area, soil type vector map, soil physicochemical properties, climate and meteorological data, and historical survey data on cadmium pollution in farmland soil; The monitoring data is preprocessed to retain valid data that meets preset data integrity requirements, preset data accuracy requirements, and preset timeliness requirements, thus obtaining a valid basic dataset. The preprocessing includes consistency and reasonableness checks, and the removal of records that are judged to be outliers and invalid data; The consistency and rationality review includes: checking the reliability of the data source, the standardization of the data recording format, the temporal logical consistency of multiple monitoring data at the same sampling point, the rationality of the correlation between soil cadmium content and agricultural product cadmium content, and whether the monitoring data is within a reasonable range of instrument detection range and geographical space. The records of outliers and invalid data include: records where the detection value exceeds the linear range of the instrument, records where the coordinates of the sampling point exceed the administrative boundaries of the screening area, records where key fields are missing and therefore cannot be included in the calculation, and records that are determined to be outliers by statistical testing and for which there is no reasonable explanation. The effective basic dataset includes sampling point information, soil cadmium content, agricultural product cadmium content, and corresponding crop variety information.

3. The method of claim 1, wherein, Based on the aforementioned effective basic dataset, a intensive soil-agricultural product collaborative survey is conducted on contaminated farmland to obtain collaborative detection datasets of soil and agricultural products for each crop variety, including: Based on the effective basic dataset and combined with local planting habits information in the screening area, the types of crop varieties to be investigated are determined, and the total number of collaborative sampling points for a single crop variety is set to be no less than the preset minimum sampling number. Supplementary sampling is carried out for varieties that do not meet the data volume requirements or have no collaborative soil data. During the crop harvest season, soil and crop samples were collected from the same locations at the same time. For paddy fields, sampling points were densely distributed according to the first preset grid size, and for dry land, sampling points were densely distributed according to the second preset grid size. Sampling was performed according to preset sampling specifications. Soil sampling was conducted using a multi-point mixing method to collect topsoil, removing the contact surface with bamboo strips or wooden shovels and retaining a preset soil sample volume. Agricultural product sampling was conducted by collecting edible parts of agricultural products; for vegetables, a preset fresh weight sample volume was collected, and for grains, a preset dry weight sample volume was collected. The latitude and longitude coordinates of each sampling point were recorded. Heavy metal content was tested on collected soil and agricultural product samples. The test indicators included at least cadmium content. Cadmium data below the detection limit were replaced with a preset detection limit value for statistical analysis, resulting in a collaborative detection dataset of soil cadmium content and agricultural product cadmium content corresponding to each crop variety.

4. The method of claim 1, wherein, The step involves calculating the index values ​​for each crop variety based on the collaborative detection dataset to obtain the core index dataset for each variety, including: Based on the collaborative detection dataset, according to the crop variety classification, the cadmium content of the edible parts of agricultural products and the soil cadmium content of the corresponding sampling points of each crop variety are obtained one by one. Based on the cadmium content in the edible parts of the agricultural products and the cadmium content in the soil, the index values ​​for each crop variety are calculated; the index values ​​include the cadmium pollution index, the cadmium exceedance rate, and the cadmium enrichment coefficient. The calculation of the cadmium pollution index includes: dividing the cadmium content of the edible part of the agricultural product at each sampling point by the preset food contaminant limit standard value corresponding to the crop variety category to obtain the cadmium pollution index of each sampling point, and taking the arithmetic mean of the cadmium pollution index of all sampling points of the crop variety as the cadmium pollution index of the crop variety. The calculation of the cadmium exceedance rate includes: determining whether the cadmium content of the edible part of the agricultural product at each sampling point exceeds the food contaminant limit standard value, counting the number of samples exceeding the standard, dividing the number of samples exceeding the standard by the total number of samples of the crop variety, and then multiplying by 100% to obtain the cadmium exceedance rate of the crop variety. The calculation of the cadmium enrichment coefficient includes: dividing the cadmium content of the edible part of the agricultural product at each sampling point by the cadmium content of the soil at the corresponding sampling point to obtain the cadmium enrichment coefficient of each sampling point, and taking the arithmetic mean of the cadmium enrichment coefficients of all sampling points of the crop variety as the cadmium enrichment coefficient of the crop variety. The cadmium pollution index, cadmium exceedance rate, and cadmium enrichment coefficient of each crop variety are summarized to form a core indicator dataset containing crop variety names and corresponding indicator values.

5. The method of claim 1, wherein, The process of screening crop varieties according to the core indicator dataset and preset preliminary selection criteria to obtain a preliminary list of eligible test varieties includes: Based on the core indicator dataset, the cadmium exceedance rate, cadmium pollution index and cadmium enrichment coefficient of each crop variety are determined in sequence. The preset preliminary selection conditions include: the cadmium exceedance rate is less than or equal to the preset exceedance rate threshold, the cadmium pollution index is less than or equal to the preset pollution index threshold, and the cadmium enrichment coefficient is less than or equal to the preset enrichment coefficient threshold. The crop varieties that meet one of the preset preliminary selection conditions are selected, and the variety name and the corresponding index value of the crop variety are recorded to form a preliminary list of test varieties.

6. The method according to claim 1, characterized in that, The preliminary list of test varieties is used to conduct concentrated field verification trials on farmland with different cadmium pollution gradients, obtaining a dataset of field verification indicators and yield data, including: At least two test plots with different cadmium pollution gradients were selected within the screening area. The soil cadmium content of the first test plot was between the screening value and the control value of the preset soil pollution risk screening standard, and the soil cadmium content of the second test plot was higher than the control value of the preset soil pollution risk screening standard. The irrigation water quality of each test plot met the preset farmland irrigation water quality standard. Each crop variety in the preliminary list of test varieties will be planted in test plots with different cadmium pollution gradients. The test period will be no less than the preset minimum number of independent growth cycles. The planting plot area of ​​each crop variety will be no less than the preset minimum plot area. The preset number of replicates will be adopted. The random block arrangement or a combination of random block and comparison method will be used. The cultivation and management will be uniform. During the crop maturity period, soil and agricultural products of each plot of each crop variety were collected simultaneously. A preset number of mixed samples were collected from each experimental plot. The cadmium content of the soil and agricultural product samples was tested. At the same time, the yield of each plot of each crop variety was measured and the yield data of each crop variety was recorded. The data on cadmium content of agricultural products, corresponding soil cadmium content, and yield of each crop variety under different cadmium pollution gradients and different growth cycles were compiled to form a field validation index dataset and yield data.

7. The method according to claim 1, characterized in that, The process involves calculating weighted evaluation values ​​using a pre-defined non-equal weighted evaluation model based on the field validation index dataset, and then combining these values ​​with the yield data and agronomic trait stability for a comprehensive assessment. This yields the overall evaluation results for each tested variety, including: Based on the field validation index dataset, cadmium content detection data of agricultural products of each tested variety under different cadmium pollution gradient plots and different growth cycles were extracted, and the index values ​​of each variety were recalculated; the index values ​​include the cadmium pollution index, the cadmium exceedance rate, and the cadmium enrichment coefficient. A pre-defined non-equal weighted evaluation model is used to calculate the weighted values ​​of the indicators. In the non-equal weighted evaluation model, the cadmium pollution index is assigned a first pre-defined weight, the cadmium exceedance rate is substituted in decimal form and assigned a second pre-defined weight, and the cadmium enrichment coefficient is assigned a third pre-defined weight. The weighted evaluation value is calculated by multiplying the cadmium pollution index by the first pre-defined weight, the cadmium exceedance rate by the second pre-defined weight, and the cadmium enrichment coefficient by the third pre-defined weight. Simultaneously, the yield data and agronomic trait stability are combined for auxiliary judgment to obtain yield comparison results and agronomic trait stability performance information; the auxiliary judgment combining the yield data and agronomic trait stability includes: comparing the yield data of each tested variety with the yield data of the same variety in the screening area, determining whether there are differences between the two that meet the preset conditions, and observing whether the agronomic trait performance of each tested variety is stable and consistent under different growth cycles and different pollution gradients. A comprehensive evaluation result was obtained based on the weighted evaluation value of each tested variety, the yield comparison results, and the information on the stability of agronomic traits.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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