A method for predicting arsenic accumulation risk of rice

Abstract

The application discloses a prediction method of rice arsenic accumulation risk, which comprises the following steps: collecting paddy field plough layer soil, and then performing a pot experiment by using the collected soil; collecting the soil and rice grains in the pot after the pot experiment enters the mature period of rice; determining the total arsenic content and available arsenic content in the soil and the arsenic content in the rice grains; performing linear regression on the ratio of the available arsenic content in the soil to the total arsenic content in the soil and the ratio of the arsenic content in the rice to the total arsenic content in the soil (BCF value) to accurately predict the arsenic in the rice. The method is simple in operation and low in cost, and has a better linear correlation relationship between the determined ratio of the available arsenic in the paddy field soil to the total arsenic in the soil and the BCF value of the arsenic in the rice, so that the arsenic accumulation in the rice can be accurately and quickly predicted.

Description

Technical Field

[0001] This invention relates to the field of agricultural environmental heavy metal pollution risk assessment technology, and more specifically to a method for predicting the risk of arsenic accumulation in rice. Background Technology

[0002] Arsenic is a toxic metalloid. Due to the efficient absorption and translocation of arsenic by rice, the arsenic content accumulated in rice grains is often higher than in other food crops, posing a threat to the health of populations whose staple food is rice. Flooding is commonly implemented during rice cultivation, significantly increasing the mobility and bioavailability of arsenic in the soil. Rice readily accumulates inorganic arsenic compounds in the soil during this process. Due to differences in composition and properties, arsenic exhibits varying bioavailability and accumulation levels in different soils. Understanding the relationship between available arsenic in soil and crop accumulation is a crucial step in assessing the impact of arsenic pollution in soil on crops. Extraction methods are common for determining available arsenic in paddy soils, but the results obtained from these conventional methods have low correlation with arsenic accumulation in rice. In recent years, deep gas chromatography-mass spectrometry (DGT) technology has developed rapidly, showing promising applications in in-situ characterization of the availability of heavy metals such as arsenic (As). However, its operation is complex and costly, and its applicability to different soil types needs further investigation. Furthermore, the speciation and availability of arsenic in soils with different properties vary significantly with soil moisture conditions, thus these factors cannot accurately predict the risk of crop arsenic uptake and accumulation. Summary of the Invention

[0003] In view of this, the present invention proposes a standardized method based on bioaccumulation factor (BCF) and available arsenic in soil to predict the risk of arsenic accumulation in rice and has conducted field validation. This method can more accurately characterize the risk of arsenic absorption and accumulation in rice, and is simple to operate and low in cost, making it a relatively ideal extraction method.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A method for predicting the risk of arsenic accumulation in rice includes the following steps:

[0006] Step 1: Potted Plant Experiment

[0007] Soil samples from the topsoil layer of paddy fields were collected for pot experiments. Conventional water management was adopted, and soil and rice grain samples were taken from the pots at the rice maturity stage.

[0008] Step 2: Sample Processing

[0009] The contents of available arsenic and total arsenic in the potted soil collected in step one were determined, and the contents of arsenic in the rice grains collected in step one were determined.

[0010] Step 3: Calculation and Analysis

[0011] Linear regression analysis was performed between the ratio of available arsenic in soil to total arsenic and the ratio of arsenic content in rice grains to total arsenic content in soil to predict the risk of arsenic accumulation in rice.

[0012] Preferably, the pot experiment in step one includes the following steps:

[0013] Soil passing through a 1 cm sieve was placed into rice pots. Before transplanting, 0.392 g / kg of urea, 0.164 g / kg of ammonium dihydrogen phosphate, and 0.333 g / kg of potassium chloride were added by weight of soil and mixed thoroughly. Tap water was added to maintain a 2-3 cm water layer. After equilibration for 7 days, seedlings with similar growth conditions were transplanted. After the rice entered the ripening stage, soil samples and rice grains were collected simultaneously. The soil samples were placed in a cool and ventilated place to air dry naturally, and impurities were removed. After grinding, the samples were passed through 20-mesh and 100-mesh sieves and stored for later use. The rice grain samples were dried in the sun to remove moisture, dehulled, and then passed through a ball mill to become white powder for later use.

[0014] Preferably, in step one, soil samples are collected from a depth of 0-20 cm. A five-point sampling method is used, and the five soil samples are thoroughly mixed to serve as the final samples from the topsoil sampling points in the paddy field. The mixed soil is then air-dried at room temperature before being used for pot experiments.

[0015] Preferably, the determination of available arsenic content in the soil in step two includes the following steps:

[0016] (2.1) After crushing and grinding the soil sample, pass it through a 20-mesh sieve. Then weigh the soil sample and place it in a centrifuge tube. Add 0.43 mol / L HNO3 extraction solution. The mass ratio of soil sample to HNO3 extraction solution is 1:10 g / mL. Extract for 2 h at 200 r / min in a 5℃ constant temperature horizontal shaker. After extraction, filter to obtain the extract solution for testing.

[0017] (2.2) 25 mL of 0.43 mol / L HNO3 extract was placed in a capped centrifuge tube and extracted for 2 h at 200 r / min in a 25℃ constant temperature horizontal shaker. After standing, the supernatant was passed through quantitative filter paper to prepare a blank sample for testing.

[0018] (2.3) A standard curve for determining different concentrations of available arsenic was established using inductively coupled plasma mass spectrometry (ICP-MS).

[0019] (2.4) The concentration of available arsenic in the extract was measured using an inductively coupled plasma mass spectrometer via a standard curve;

[0020] (2.5) Based on the measured mass of the soil sample and the measured concentration of available arsenic in the extract, the content of available arsenic in the soil sample is calculated using the following formula:

[0021]

[0022] In the formula: W The content of plant-available arsenic in the soil sample is measured, in mg / kg; c The concentration of available arsenic in the measured extract is expressed in mg / L. V 1 The volume of deionized water added is in mL. V 2 The volume of HNO3 extract added is in mL. m The mass of the measured soil sample is expressed in grams.

[0023] Furthermore, the process of establishing standard curves for different concentrations in step (2.3) is as follows:

[0024] (2.3.1) Measure 1000 mg / L of arsenic standard working solution into a volumetric flask, and dilute to volume with 1% HNO3 solution to obtain arsenic standard working solution with arsenic concentration of 100 mg / L.

[0025] (2.3.2) Take 0 mL, 0.05 mL, 0.125 mL, 0.25 mL, 0.5 mL and 1 mL of arsenic standard working solution with an arsenic concentration of 100 mg / L and place them in a 50 mL volumetric flask. Dilute to the mark with 1% HNO3 solution to obtain arsenic standard working solutions with arsenic concentrations of 0 mg / L, 0.1 mg / L, 0.25 mg / L, 0.5 mg / L, 1 mg / L and 2 mg / L.

[0026] (2.3.3) Arsenic standard working solutions with arsenic concentrations of 0 mg / L, 0.1 mg / L, 0.25 mg / L, 0.5 mg / L, 1 mg / L and 2 mg / L were injected into the inductively coupled plasma mass spectrometer in sequence. The concentration of the arsenic standard working solution was plotted on the x-axis and the intensity of available arsenic was plotted on the y-axis. The inductively coupled plasma mass spectrometer automatically plotted standard curves for different arsenic concentrations. The regression equation of the arsenic concentration relationship was obtained by linear regression of the standard curves.

[0027] Furthermore, the specific steps of step (2.4) are as follows:

[0028] (2.4.1) The blank sample was injected into the inductively coupled plasma mass spectrometer, the intensity value of the available arsenic was measured, and the concentration of available arsenic in the blank sample was calculated by substituting it into the standard curve regression equation.

[0029] (2.4.2) The extract was injected into an inductively coupled plasma mass spectrometer, and the intensity value of the available arsenic was measured. The value was then substituted into the standard curve regression equation in step (2.3) to calculate the concentration of available arsenic in the extract.

[0030] (2.4.3) The concentration of available arsenic in the extract is determined by the formula c = c1 - c0, where c0 is the concentration of available arsenic in the blank sample in mg / L; and c1 is the calculated concentration of available arsenic in the extract in mg / L.

[0031] Preferably, the determination of total arsenic content in the soil in step two includes the following steps:

[0032] After crushing and grinding the soil sample, pass it through a 100-mesh sieve. Weigh 0.5g into a 50ml Erlenmeyer flask, moisten it with water, add 7-10mL of aqua regia for pre-digestion, let it stand overnight, and then heat it at 180-220℃ until the brown color disappears. Then add 2mL of HClO4 for oxidation treatment and continue digestion until grayish-white. Continue heating to remove all HClO4, and then dilute the remaining material to a 25ml colorimetric tube with 1% HNO3. Shake well, filter, and obtain the test solution. The total arsenic content in the soil is determined by hydride generation-atomic fluorescence spectrometry.

[0033] Preferably, the arsenic content in rice grains in step two includes the following steps:

[0034] Microwave-assisted acid digestion was employed. 0.2 g of rice sample (passed through an 80-mesh sieve) was accurately weighed into a digestion tube. 5 mL of 16 mol / L concentrated nitric acid and 2 mL of hydrogen peroxide were added, shaken well, and capped. The tube was then placed in a pressure digestion outer container for microwave digestion. The stainless steel outer casing was tightened, and the tube was placed in a 120-150℃ (not exceeding 180℃) electric heating drying oven for 240-300 min. After natural cooling to room temperature, the stainless steel outer casing was slowly loosened, and the inner digestion vessel was removed. The cap was rinsed with a small amount of ultrapure water, and the tube was placed on a hot plate at 120℃ to remove the brown gas. Once white fumes appeared and 1 mL of liquid remained, 1 mL of HClO4 was added to continue digestion until 1 mL of liquid remained. The digest was then removed, and the digest was transferred to a 25 mL volumetric flask or colorimetric tube. The inner vessel was washed three times with ultrapure water, and the washings were combined. 2.5 mL of HClO4 was added to the inner container. A mixed solution of thiourea and ascorbic acid, with a concentration of 0.05 g / mL for both thiourea and ascorbic acid, was diluted to volume with ultrapure water, shaken well, and allowed to stand for 30 min before being measured using an atomic fluorescence spectrophotometer.

[0035] Preferably, the rice varieties tested in the pot experiment in step one are Xiangzaoxian 24 and Zhuliangyou 189.

[0036] Preferred options also include:

[0037] Step 4: Field Verification

[0038] (4.1) Test soil: Soil samples were collected around the soil sites of the pot experiment as test soil for field verification;

[0039] (4.2) Experimental procedure: Soil and rice samples were collected during the rice ripening period. The total arsenic and available arsenic in the soil were determined, and the arsenic content in the rice grains was determined.

[0040] (4.3) Linear regression analysis was performed on the ratio of available arsenic in soil to total arsenic determined by the above method and the ratio of arsenic in rice grains to total arsenic in soil to verify the accuracy of the method in characterizing the risk of arsenic accumulation in rice.

[0041] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a method for predicting the risk of arsenic accumulation in rice, which has the following beneficial effects:

[0042] This method is simple to operate and low in cost. The ratio of plant-available arsenic to total soil arsenic in paddy soil has a better linear correlation with the BCF value of rice arsenic, which can accurately and quickly predict the risk of arsenic accumulation in rice. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0044] Figure 1 Linear regression analysis of plant-available arsenic in soil and rice arsenic in pot experiments, and linear regression analysis of predicted and measured BCF values ​​of rice arsenic.

[0045] Figure 2 Linear regression analysis of plant available arsenic in soil / total soil arsenic and rice arsenic BCF value in pot experiment and linear regression analysis of predicted and measured rice arsenic BCF values;

[0046] Figure 3 Linear regression analysis of plant-available arsenic / total soil arsenic and rice arsenic BCF values ​​determined by DGT technology in the comparative example;

[0047] Figure 4 Linear regression analysis of plant-available arsenic in soil / total arsenic in soil and BCF value of rice arsenic in regional validation experiments, and linear regression analysis of predicted and measured BCF values ​​of rice arsenic;

[0048] Figure 5 Linear regression analysis was performed on the ratio of plant-available arsenic to total soil arsenic and straw arsenic BCF values ​​determined by different extraction methods in the regional validation experiment, and linear regression analysis was performed on the predicted and measured values ​​of straw arsenic BCF. Detailed Implementation

[0049] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0050] A risk prediction method for available arsenic in paddy soil is proposed. Based on the content of available arsenic extracted from different soils, the ratio of available arsenic to total soil arsenic is used to establish a linear regression equation with the BCF value of arsenic in rice grains.

[0051] Includes the following steps:

[0052] S100) Determination and Collection of Potted Soil

[0053] A pot experiment was conducted on collected paddy soil samples. Conventional water management was adopted. The arsenic content in rice grains was measured at the rice maturity stage. Linear regression analysis was performed on the plant-available arsenic in the soil samples and the arsenic content in rice grains to verify the accuracy of this method in characterizing plant-available arsenic in paddy soil.

[0054] S110) Soil Sample Collection and Pretreatment

[0055] Soil samples were collected from 10 different counties and cities in the upper, middle, and lower reaches of the Xiangjiang River, considering the complex soil types and significant differences in soil physicochemical properties due to the vast span of the watershed. Collecting soil samples from a single region for risk prediction might lack regional universality. These samples were taken from the upstream areas of Guiyang County (Chenzhou City), Qiyang City (Yongzhou City), Leiyang City (Hengyang City), and Changning City (Hengyang City); the midstream areas of Youxian County (Zhuzhou City), Liling City (Zhuzhou City), and Xiangxiang City (Xiangtan City); and the downstream areas of Liuyang City (Changsha City), Wangcheng District (Changsha City), and Heishan District (Yiyang City). A five-point sampling method was used, collecting topsoil from paddy fields (0–20 cm). Five soil samples were thoroughly mixed and used as the final sample for each point. The remaining soil profile and surrounding environment were observed on-site to determine the soil type and its parent rock.

[0056] S111) Pot Experiment Setup

[0057] Plastic containers with a diameter of 20 cm and a height of 25 cm were used as rice pots. Each pot contained 5 kg of soil sample that had passed through a 1 cm sieve. Before transplanting, nitrogen, phosphorus, and potassium fertilizers were mixed into the soil. The amounts of urea, ammonium dihydrogen phosphate, and potassium chloride added were 0.392 g / kg, 0.164 g / kg, and 0.333 g / kg, respectively. Tap water was added to the pots, maintaining a water layer of 2-3 cm. After equilibration for 7 days, rice seedlings (Xiangzaoxian 24 and Zhuliangyou 189) were transplanted. Seedlings with similar growth characteristics were selected before transplanting. Two rice plants were planted per pot. The same water depth was maintained throughout the growth period. The field was sun-dried for 10 days during the late tillering stage and for 15 days during the late grain-filling stage. Soil samples and rice grains were collected simultaneously after the rice entered the ripening stage. Soil samples should be placed in a cool, ventilated place to air dry naturally, and mixed plant residues and large-sized impurities should be removed. After grinding, they should be passed through 20-mesh and 100-mesh sieves and stored for later use. Rice grain samples should be dried in the sun to remove moisture, dehulled, and then passed through a ball mill to become white powder for later use.

[0058] The determination of total soil arsenic and plant-available arsenic in the above-mentioned potted soil samples included the following steps:

[0059] S200) Soil Total As Determination: Weigh 0.5g of 100-mesh soil sample into a 50ml Erlenmeyer flask, moisten with a small amount of water, add 7-10mL of aqua regia for pre-digestion, let stand overnight, heat at 180-220℃ to digest until the brown color disappears, then add 2mL of HClO4 for oxidation treatment and continue digestion until grayish-white, continue heating to remove HClO4, and then dilute the remaining material to a 25mL colorimetric tube with 1% dilute nitric acid. Shake well, filter to obtain the test solution, and determine by hydride generation-atomic fluorescence spectrometry (HG-AFS, AFS-2202E).

[0060] S210) Determination of the concentration of available arsenic in soil

[0061] S211) Preparation of extract

[0062] Weigh 2.5 g of soil sample into a capped centrifuge tube, add 2.5 mL of 0.43 mol / L HNO3 extraction solution, extract at 200 r / min for 2 h in a 25℃ constant temperature horizontal shaker, and after standing, take the supernatant and pass it through quantitative filter paper to obtain the extract. Each treatment is repeated 3 times.

[0063] S212) Preparation of blank samples

[0064] Add 25 mL of 0.43 mol / L HNO3 extraction solution to a capped centrifuge tube, extract at 200 r / min for 2 h in a 25℃ constant temperature horizontal shaker, and after standing, take the supernatant and pass it through quantitative filter paper to prepare a blank sample.

[0065] S220) Establishing Standard Curves

[0066] A standard curve for determining different concentrations of available arsenic was established using inductively coupled plasma mass spectrometry (ICP-MS).

[0067] S221) Take an appropriate amount of 1000 mg / L arsenic standard working solution and dilute it with 1% HNO3 solution to prepare an arsenic standard working solution with an arsenic concentration of 100 mg / L.

[0068] S222) Measure 0 mL, 0.05 mL, 0.125 mL, 0.25 mL, 0.5 mL and 1 mL of arsenic standard working solution with an arsenic concentration of 100 mg / L into 50 mL volumetric flasks, and dilute to volume with 1% HNO3 solution to obtain arsenic standard working solutions with arsenic concentrations of 0 mg / L, 0.1 mg / L, 0.25 mg / L, 0.5 mg / L, 1 mg / L and 2 mg / L.

[0069] (S223) Arsenic standard solutions with concentrations of 0 mg / L, 0.1 mg / L, 0.25 mg / L, 0.5 mg / L, 1 mg / L and 2 mg / L were injected into the inductively coupled plasma mass spectrometer in sequence. The concentration of the arsenic standard solution was plotted on the x-axis and the intensity of available arsenic was plotted on the y-axis. The inductively coupled plasma mass spectrometer automatically plotted standard curves for different arsenic concentrations. The regression equation of the arsenic concentration relationship was obtained by linear regression of the standard curves.

[0070] S230) Measure the concentration of available arsenic in the extract.

[0071] The concentration of available arsenic in the extract was measured using inductively coupled plasma mass spectrometry via a standard curve.

[0072] S231) The blank sample is injected into an inductively coupled plasma mass spectrometer, the intensity value of available arsenic is measured, and the concentration of available arsenic in the blank sample is calculated by substituting it into the regression equation.

[0073] S232) The extract was injected into an inductively coupled plasma mass spectrometer, the intensity value of available arsenic was measured, and the value was substituted into the regression equation to calculate the concentration of available arsenic in the extract.

[0074] S233) The concentration of available arsenic in the extract is determined by the formula c = c1 - c0, where c0 is the concentration of available arsenic in the blank sample in mg / L; and c1 is the concentration of available arsenic in the extract in mg / L.

[0075] S300) Results Analysis

[0076] S310) Determine the content of plant-available arsenic in potted soil samples.

[0077] Based on the measured mass of the soil sample and the concentration of the measured extract, the content of plant-available arsenic in the measured soil sample was calculated using the following formula:

[0078]

[0079] In the formula: W The content of plant-available arsenic in the soil sample is measured, in mg / kg; c The concentration of available arsenic in the measured extract is expressed in mg / L. V 1 The volume of deionized water added is in mL. V 2 The volume of HNO3 extract added is in mL. m The mass of the measured soil sample is expressed in grams.

[0080] S311) Determine the arsenic content of potted rice grains

[0081] Samples were collected during the rice ripening period. The arsenic content of rice grains was determined according to national standard methods using microwave-assisted acid digestion. 0.2 g of rice sample (passed through an 80-mesh sieve) was accurately weighed into a digestion tube, and 5 mL of 16 mol / L concentrated nitric acid and 2 mL of hydrogen peroxide were added. The tube was shaken well, capped, and then placed in a pressure digestion outer container for microwave digestion. The stainless steel outer casing was tightened, and the tube was placed in an electric heating drying oven at 120-150℃ (not exceeding 180℃) for 240-300 min. After natural cooling to room temperature, the stainless steel outer casing was slowly loosened, and the inner digestion container was removed. The cap was rinsed with a small amount of ultrapure water, and the container was placed on a hot plate at 120℃ to remove the brown gas. After white smoke appeared and approximately 1 mL of liquid remained, an appropriate amount (1 mL) of HClO4 was added to continue digestion until approximately 1 mL of liquid remained. The container was then removed, and the digest was transferred to a 25°C container. In a volumetric flask or colorimetric tube, wash the inner container three times with a small amount of ultrapure water, combine the washing solutions, add 2.5 mL of a mixed solution of thiourea and ascorbic acid (the concentrations of thiourea and ascorbic acid in the mixed solution are both 0.05 g / mL), dilute to volume with ultrapure water, shake well, let stand for 30 min, and then measure with an atomic fluorescence spectrophotometer (AFS-2202E).

[0082] S312 performed linear regression analysis between the soil available arsenic / total arsenic ratio (HNO3-As / T-As) extracted from pot experiments and the arsenic BCF value in rice grains (Rice-As / T-As) to verify the accuracy of this method in characterizing the risk of arsenic accumulation in rice. The bioconcentration factor (BCF) is the ratio of heavy metal content in rice plants to heavy metal content in the soil; this index can effectively characterize the absorption and accumulation characteristics of heavy metals in plants.

[0083] S400) Field Verification

[0084] S410) Test soil: In order to maintain consistency with the test soil sites of the pot experiment as much as possible, 298 new soil-rice sample sites were added in the small watersheds of the tributaries of the Xiangjiang River around the soil sites of the pot experiment. The collected soil samples were used as test soil for field verification.

[0085] S411) Experimental procedure: Soil and rice samples were collected at the rice maturity stage to determine the total amount of arsenic in the soil, and the arsenic content in rice grains and straw; available arsenic in the soil was extracted from the air-dried soil samples using the HNO3 extraction method; the total arsenic and available arsenic in the soil and the arsenic in the rice grains were determined in the test soil.

[0086] S412) A linear regression analysis was performed between the soil available arsenic / total arsenic ratio (HNO3-As / T-As) determined by the above method and the arsenic BCF value in rice grains (Rice-As / T-As) to verify the accuracy of this method in characterizing the risk of arsenic accumulation in rice.

[0087] Results analysis:

[0088] The linear regression relationship between available arsenic in soil and arsenic content in rice grains extracted from two types of rice (Xiangzaoxian 24 and Zhuliangyou 189) in a pot experiment is as follows: Figure 1 As shown, where Figure 1 a is a linear regression analysis graph showing the relationship between the content of available arsenic determined by the method of this invention and the arsenic content in rice grains. Figure 1 b is a linear regression analysis graph showing the relationship between the measured available arsenic content in rice and the actual arsenic content in rice grains.

[0089] Depend on Figure 1 As can be seen from a, the linear correlation formula between the content of available arsenic determined by the method of the present invention and the arsenic content of the two types of rice grains is:

[0090] Xiangzaoxian No. 24: y1=0.0771x1+0.3700(R1) 2 =0.2314, P <0.01, n=30);

[0091] Zhu Liangyou 189: y2 = 0.0409x2 + 0.3543 (R2) 2 =0.1008, n=30);

[0092] Depend on Figure 1 As shown in b, the linear correlation formula between rice arsenic content calculated from the measured available arsenic content and actual rice grain arsenic content is:

[0093] Xiangzaoxian No. 24: y1=0.9999x1 (R1) 2 =0.2314, P <0.01, n=30);

[0094] Zhu Liangyou 189: y2=0.9998x2+0.0001(R2) 2 =0.1008, n=30).

[0095] The above results indicate that the correlation between direct prediction of arsenic accumulation in rice is low, and a more accurate prediction method is needed.

[0096] The linear regression relationship between the ratio of available arsenic to total arsenic extracted from soil and the BCF value of arsenic in rice grains in pot experiments of two rice varieties (Xiangzaoxian 24 and Zhuliangyou 189) is shown in the figure below. Figure 2 As shown, where Figure 2 a is a linear regression analysis graph showing the relationship between the measured available arsenic / total soil arsenic and the BCF values ​​of arsenic in the grains of the two rice varieties. Figure 2 b is a linear regression analysis graph showing the relationship between the BCF value of rice arsenic calculated based on the measured content of available arsenic and the actual BCF value of rice grains.

[0097] Depend on Figure 2 From a, we can see that the linear correlation formula between the measured available arsenic / total soil arsenic and the arsenic BCF values ​​of the two types of rice grains is:

[0098] Xiangzaoxian No. 24: y1=0.2558x1+0.0019(R1) 2 =0.7206, P <0.01, n=30);

[0099] Zhu Liangyou 189: y2=0.2336x2+0.0005(R2) 2 =0.6727, n=30);

[0100] Depend on Figure 2 As shown in b, the linear correlation formula between the rice arsenic BCF value calculated based on the measured available arsenic content and the actual rice grain arsenic BCF is:

[0101] Xiangzaoxian No. 24: y1=1.0001x1 (R1 2=0.7206, P <0.01, n=30);

[0102] Zhu Liangyou 189: y2 = 1.0001x2 + 0.0005 (R2) 2 =0.6727, P <0.01, n=30);

[0103] The above results show that the linear correlation between the measured available arsenic / total soil arsenic and the BCF values ​​of the two rice grains (Xiangzaoxian 24 and ) is as follows: Xiangzaoxian 24 R1 2 =0.7206, Zhuliangyou 189 R2 2 =0.6727. The linear correlation between the rice arsenic BCF value calculated based on the measured available arsenic content and the actual rice grain arsenic BCF is: R1 for Xiangzaoxian 24. 2 =0.7206, Zhuliangyou 189 R2 2 =0.6727. This indicates that the method can be used to accurately predict the BCF value of arsenic in rice.

[0104] The linear regression relationship between soil available arsenic / total arsenic and the BCF value of arsenic in rice grains, validated through field data at nearly 300 locations, is as follows: Figure 4 As shown, where, Figure 4 a is a linear regression analysis diagram showing the relationship between the measured available arsenic / total soil arsenic and the BCF of arsenic in rice grains. Figure 4 b is a linear regression analysis graph showing the relationship between the BCF value of rice arsenic calculated based on the measured content of available arsenic and the actual BCF value of rice grains.

[0105] Depend on Figure 4 As can be seen from equation a, the linear correlation formula between the measured available arsenic / total soil arsenic and the BCF of rice grain arsenic is: y = 0.1214x + 0.0094 (R1). 2 =0.2612, P <0.01, n=293);

[0106] Depend on Figure 4 As shown in b, the linear correlation formula between the rice arsenic BCF value calculated based on the measured available arsenic content and the actual rice grain arsenic BCF is: y = 0.9986x + 0.0008 (R1) 2 =0.2612, P <0.01, n=293);

[0107] The above results show that the linear correlation between the measured available arsenic / total soil arsenic and the BCF of rice grain arsenic is R1. 2=0.2612; The linear correlation between the rice arsenic BCF value calculated based on the measured available arsenic content and the actual rice grain arsenic BCF is R1. 2 =0.2612. This method is simple to operate and has a certain correlation even when applied to field validation at nearly 300 points with multiple soil properties and multiple rice varieties.

[0108] The linear regression relationship between available arsenic in soil and the BCF value of arsenic in rice straw, verified through nearly 300 field sites, is as follows: Figure 5 As shown, where, Figure 5 a is a linear regression analysis plot showing the relationship between the measured available arsenic / total soil arsenic and the arsenic BCF in rice straw. Figure 5 b is a linear regression analysis graph showing the relationship between the BCF value of rice arsenic calculated based on the measured content of available arsenic and the actual BCF value of rice grains.

[0109] Depend on Figure 5 As can be seen from a, the linear correlation formula between the measured available arsenic / total soil arsenic and the BCF of rice straw arsenic is: y = 2.1087x + 0.0765 (R1). 2 =0.2739, P <0.01, n=293);

[0110] Depend on Figure 5 As shown in b, the linear correlation formula between the rice arsenic BCF value calculated based on the measured available arsenic content and the actual rice grain arsenic BCF is: y = 1.0000x + 0.0004 (R1) 2 =0.2739, P <0.01, n=293);

[0111] The above results show that the linear correlation between the measured available arsenic / total soil arsenic and the arsenic BCF in rice straw is R1. 2 =0.2739; The linear correlation between the rice arsenic BCF value calculated based on the measured available arsenic content and the actual rice grain arsenic BCF is R1. 2 =0.2739, slightly higher than the BCF of arsenic in rice. The method is simple to operate and has a certain correlation even in field validation at nearly 300 points with multiple soil properties and multiple rice varieties.

[0112] Comparative Example

[0113] In recent years, DGT technology has developed rapidly and can accurately assess the bioavailability of heavy metals such as arsenic in various soils and simulate the dynamic response process of soil. It has the advantages of in-situ, passive and biomimetic methods, but its disadvantage is the high cost of measurement. Figure 3The graph shows the linear regression analysis of DGT-As / T-As and As-BCF of rice in two rice varieties (Xiangzaoxian 24 and Zhuliangyou 189). Figure 3 'a' represents the linear regression analysis graph for acidic soil. Figure 3 b is the linear regression analysis diagram for alkaline soil. Figure 3 c is a linear regression analysis graph for all soil conditions.

[0114] Figure 3 From c, we can see that the linear correlation formula between the available arsenic / total soil arsenic determined by DGT technology and the arsenic BCF values ​​of the two types of rice grains is:

[0115] Xiangzaoxian No. 24: y1=0.1257x1+0.0231(R1) 2 =0.0357, n=30);

[0116] Zhu Liangyou 189: y2 = 0.0750x2 + 0.0212 (R2) 2 =0.0137, n=30);

[0117] Based on the linear regression results, the linear correlation between the available arsenic / total soil arsenic determined by DGT technology and the BCF value of arsenic in the grains of the two rice varieties was: R1 for Xiangzaoxian 24. 2 =0.0357, Zhuliangyou 189 R2 2 =0.0137, which is much lower than the value of Xiangzaoxian No. 24 R1 in the method of this invention. 2 =0.7206, Zhuliangyou 189 R2 2 =0.6727, and field verification example R1 using the method of the present invention. 2 =0.2612. Therefore, this invention can predict the risk of arsenic accumulation in rice more cost-effectively and accurately.

[0118] The various embodiments described in this specification are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for predicting the risk of arsenic accumulation in rice, characterized in that, Includes the following steps: Step 1: Potted Plant Experiment Soil samples from the topsoil layer of paddy fields were collected for pot experiments. Conventional water management was adopted, and soil and rice grain samples were taken from the pots at the rice maturity stage. Step 2: Sample Processing The contents of available arsenic and total arsenic in the potted soil collected in step one were determined, and the contents of arsenic in the rice grains collected in step one were determined. Step 3: Calculation and Analysis Linear regression analysis was performed on the ratio of available arsenic in soil to total arsenic to the ratio of arsenic content in rice grains to total arsenic content in soil to predict the risk of arsenic accumulation in rice.

2. The method for predicting the risk of arsenic accumulation in rice according to claim 1, characterized in that, The potted plant experiment in step one includes the following steps: Soil passing through a 1 cm sieve was placed into rice pot containers. Before transplanting, 0.392 g / kg of urea, 0.164 g / kg of ammonium dihydrogen phosphate, and 0.333 g / kg of potassium chloride were added by weight of the soil and mixed thoroughly. Tap water was added to maintain a 2-3 cm water layer. After equilibration for 7 days, seedlings with similar growth conditions were transplanted. After the rice entered the ripening stage, soil samples and rice grains were collected simultaneously. The soil samples were placed in a cool and ventilated place to air dry naturally, and impurities were removed. After grinding, the samples were passed through 20-mesh and 100-mesh sieves and stored for later use. The rice grain samples were dried in the sun to remove moisture, dehulled, and then passed through a ball mill to become white powder for later use.

3. The method for predicting the risk of arsenic accumulation in rice according to claim 1, characterized in that, In step one, soil samples were collected from a depth of 0-20 cm. The five-point sampling method was used. The five soil samples were thoroughly mixed and used as the final samples from the topsoil sampling points of the paddy field. The mixed soil was then air-dried at room temperature before being used for pot experiments.

4. The method for predicting the risk of arsenic accumulation in rice according to claim 1, characterized in that, The determination of available arsenic content in the soil described in step two includes the following steps: (2.1) After crushing and grinding the soil sample, pass it through a 20-mesh sieve. Then weigh the soil sample and place it in a centrifuge tube. Add 0.43 mol / L HNO3 extraction solution. The mass ratio of soil sample to HNO3 extraction solution is 1:10 g / mL. Extract for 2 h at 200 r / min in a 5℃ constant temperature horizontal shaker. After extraction, filter to obtain the extract solution for testing. (2.2) 25 mL of 0.43 mol / L HNO3 extract was placed in a capped centrifuge tube and extracted for 2 h at 200 r / min in a 25℃ constant temperature horizontal shaker. After standing, the supernatant was passed through quantitative filter paper to prepare a blank sample for testing. (2.3) A standard curve for determining different concentrations of available arsenic was established using inductively coupled plasma mass spectrometry (ICP-MS). (2.4) The concentration of available arsenic in the extract was measured using an inductively coupled plasma mass spectrometer via a standard curve; (2.5) Based on the measured mass of the soil sample and the measured concentration of available arsenic in the extract, the content of available arsenic in the soil sample is calculated using the following formula: In the formula: W The content of plant-available arsenic in the soil sample is measured, in mg / kg; c The concentration of available arsenic in the measured extract is expressed in mg / L. V 1 The volume of deionized water added is in mL. V 2 The volume of HNO3 extract added is in mL. m The mass of the measured soil sample is expressed in grams.

5. The method for predicting the risk of arsenic accumulation in rice according to claim 4, characterized in that, The process of establishing standard curves for different concentrations in step (2.3) is as follows: (2.3.1) Measure 1000 mg / L of arsenic standard working solution into a volumetric flask, and dilute to volume with 1% HNO3 solution to obtain arsenic standard working solution with arsenic concentration of 100 mg / L. (2.3.2) Take 0 mL, 0.05 mL, 0.125 mL, 0.25 mL, 0.5 mL and 1 mL of arsenic standard working solution with an arsenic concentration of 100 mg / L and place them in a 50 mL volumetric flask. Dilute to the mark with 1% HNO3 solution to obtain arsenic standard working solutions with arsenic concentrations of 0 mg / L, 0.1 mg / L, 0.25 mg / L, 0.5 mg / L, 1 mg / L and 2 mg / L. (2.3.3) Arsenic standard working solutions with arsenic concentrations of 0 mg / L, 0.1 mg / L, 0.25 mg / L, 0.5 mg / L, 1 mg / L and 2 mg / L were injected into the inductively coupled plasma mass spectrometer in sequence. The concentration of the arsenic standard working solution was plotted on the x-axis and the intensity of available arsenic was plotted on the y-axis. The inductively coupled plasma mass spectrometer automatically plotted standard curves for different arsenic concentrations. The regression equation of the arsenic concentration relationship was obtained by linear regression of the standard curves.

6. The method for predicting the risk of arsenic accumulation in rice according to claim 4, characterized in that, The specific steps of step (2.4) are as follows: (2.4.1) The blank sample was injected into the inductively coupled plasma mass spectrometer, the intensity value of the available arsenic was measured, and the concentration of available arsenic in the blank sample was calculated by substituting it into the standard curve regression equation. (2.4.2) The extract was injected into an inductively coupled plasma mass spectrometer, and the intensity value of the available arsenic was measured. The value was then substituted into the standard curve regression equation in step (2.3) to calculate the concentration of available arsenic in the extract. (2.4.3) The concentration of available arsenic in the extract is determined by the formula c = c1 - c0, where c0 is the concentration of available arsenic in the blank sample in mg / L; and c1 is the calculated concentration of available arsenic in the extract in mg / L.

7. The method for predicting the risk of arsenic accumulation in rice according to claim 1, characterized in that, Step two, the determination of total arsenic content in the soil, includes the following steps: After crushing and grinding the soil sample, pass it through a 100-mesh sieve. Weigh 0.5g into a 50ml Erlenmeyer flask, moisten it with water, add 7-10mL of aqua regia for pre-digestion, let it stand overnight, and then heat it at 180-220℃ until the brown color disappears. Then add 2mL of HClO4 for oxidation treatment and continue digestion until grayish-white. Continue heating to remove all HClO4, and then dilute the remaining material to a 25ml colorimetric tube with 1% HNO3. Shake well, filter, and obtain the test solution. The total arsenic content in the soil is determined by hydride generation-atomic fluorescence spectrometry.

8. The method for predicting the risk of arsenic accumulation in rice according to claim 1, characterized in that, Step two involves the following steps to determine the arsenic content in rice grains: Microwave-assisted acid digestion was employed. 0.2 g of rice sample (passed through an 80-mesh sieve) was accurately weighed into a digestion tube. 5 mL of 16 mol / L concentrated nitric acid and 2 mL of hydrogen peroxide were added, shaken well, and capped. The tube was then placed in a pressure digestion outer container for microwave digestion. The stainless steel outer casing was tightened, and the tube was placed in a 120-150℃ electric heating drying oven for 240-300 min. After natural cooling to room temperature, the stainless steel outer casing was slowly loosened, and the inner digestion vessel was removed. The cap was rinsed with a small amount of ultrapure water, and the tube was placed on a hot plate at 120℃ to remove the brown gas. Once white fumes appeared and 1 mL of liquid remained, 1 mL of HClO4 was added to continue digestion until 1 mL of liquid remained. The digest was then removed, and the digest was transferred to a 25 mL volumetric flask or colorimetric tube. The inner vessel was washed three times with ultrapure water, and the washings were combined. 2.5 mL of HClO4 was added to the inner container. A 0.05 g / mL mixture of thiourea and ascorbic acid was prepared, diluted to volume with ultrapure water, shaken well, and allowed to stand for 30 min before being measured using an atomic fluorescence spectrophotometer.

9. The method for predicting the risk of arsenic accumulation in rice according to claim 1, characterized in that, The rice varieties tested in the pot experiment in step one were Xiangzaoxian 24 and Zhuliangyou 189.

10. The method for predicting the risk of arsenic accumulation in rice according to claim 1, characterized in that, Also includes: Step 4: Field Verification (4.1) Test soil: Soil samples were collected around the soil sites of the pot experiment as test soil for field verification; (4.2) Experimental procedure: Soil and rice samples were collected during the rice ripening period. The total arsenic and available arsenic in the soil were determined, and the arsenic content in the rice grains was determined. (4.3) Linear regression analysis was performed on the ratio of available arsenic in soil to total arsenic determined by the above method and the ratio of arsenic in rice grains to total arsenic in soil to verify the accuracy of the method in characterizing the risk of arsenic accumulation in rice.

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