Method for predicting arsenic accumulation risk of rice

Abstract

The invention discloses a rice arsenic accumulation risk prediction method, which comprises the following steps: collecting paddy field plough layer soil, carrying out a potting experiment on the collected soil, collecting potting soil and rice grains after the potting experiment enters a rice mature period, measuring the total arsenic content in the soil, the effective state arsenic content and the arsenic content in the rice grains, and predicting the arsenic accumulation risk of the rice. And performing linear regression on the ratio of the soil available arsenic content to the soil total arsenic content and the ratio (BCF value) of the rice arsenic content to the soil total arsenic content, and accurately predicting the rice arsenic. The method is simple and convenient to operate and low in cost, the measured ratio of the plant available arsenic to the total arsenic in the rice field soil has a better linear correlation relationship with the BCF value of the rice arsenic, and accurate and rapid risk prediction can be carried out on rice arsenic accumulation.

Description

Technical Field

[0001] The present invention relates to the technical field of risk assessment of heavy metal pollution in agricultural environment, and more specifically, to a method for predicting the risk of arsenic accumulation in rice. Background Art

[0002] Arsenic is a toxic metalloid. Due to the effective absorption and transportation of arsenic by rice, the arsenic content accumulated in rice grains is often higher than that of other food crops, posing a threat to the health of the population that mainly eats rice. During the rice planting process, water management with flooding is often implemented. Under the flooded state, the mobility and bioavailability of soil arsenic are both significantly increased, and rice is prone to enrich inorganic arsenic compounds in the soil during this process. Due to the differences in composition and properties of different soils, arsenic shows different bioavailabilities and accumulation degrees in different soils. Solving the relationship between soil available arsenic and crop accumulation is a key step in evaluating the impact of arsenic pollution in soil on crops. The extraction method is a common method for determining available arsenic in paddy soil, but the results obtained by these conventional methods have a low correlation with the accumulation of arsenic in rice. In recent years, the DGT technology has developed rapidly and shown good application prospects in in-situ characterization of the availability of heavy (metalloid) metals such as As. However, its operation steps are complex, the determination cost is high, and its applicability in different types of soils remains to be explored. Moreover, there are obvious differences in the laws of the forms and availabilities of arsenic in different property soils with the change of soil moisture conditions. Therefore, these cannot well predict the risk of crop absorption and accumulation of arsenic. Summary of the Invention

[0003] In view of this, the present invention proposes a standardization method based on the biological enrichment coefficient (BCF) and soil available arsenic to predict the risk of arsenic accumulation in rice, and conducts field verification, which can more accurately characterize the risk of rice absorbing and accumulating arsenic, and has simple operation and low cost, and is an ideal extraction method.

[0004] To achieve the above object, the present invention adopts the following technical solutions: A method for predicting the risk of arsenic accumulation in rice, comprising the following steps: Step 1: Pot experiment Collect paddy soil samples from the plough layer, conduct pot experiments, adopt conventional water management, and take soil samples and rice grain samples in the pots at the rice maturity stage; Step 2: Sample treatment Determine the content of available arsenic and total arsenic in the potted soil collected in Step 1, and determine the content of arsenic in the rice grains collected in Step 1; Step 3: Calculation and analysis Perform linear regression analysis between the ratio of available arsenic content to total arsenic content in the soil and the ratio of arsenic content in rice grains to total arsenic content in the soil to predict the risk of arsenic accumulation in rice.

[0005] Preferably, the pot experiment in step one includes the following steps: Load the soil passed through a 1 cm sieve into the rice pot container. Based on the soil weight, apply 0.392 g / kg of urea, 0.164 g / kg of ammonium dihydrogen phosphate, and 0.333 g / kg of potassium chloride and mix them evenly with the soil before transplanting the rice. Add tap water to maintain a water layer of 2 - 3 cm. After balancing for 7 days, transplant the seedlings with basically the same growth status. When the rice enters the mature stage, synchronously collect soil samples and rice grains. Place the soil samples in a cool and ventilated place to air dry naturally, remove impurities, grind them, and then pass them through 20 - mesh and 100 - mesh sieves for storage for later use; dry the rice grain samples to remove moisture, shell them, and then pass them through a ball mill to become white powder for later use.

[0006] Preferably, collect the soil in the depth layer of 0 - 20 cm in step one. Adopt the five - point sampling method. Mix the five collected soil samples thoroughly and use it as the final sample for the soil sampling point of the paddy field plough layer. Air - dry the mixed soil naturally at room temperature and then conduct the pot experiment.

[0007] Preferably, the determination of the available arsenic content in the soil described in step two includes the following steps: (2.1) Crush and grind the soil sample and then pass it through a 20 - mesh sieve. Then weigh the soil sample and place it in a centrifuge tube. Add 0.43 mol / L of HNO3 extraction solution. The mass ratio of the soil sample to the volume of the HNO3 extraction solution is 1:10 g / mL. Extract it in a 5℃ constant - temperature horizontal shaker at 200 r / min for 2 h. After extraction, filter it to obtain the extraction solution for measurement; (2.2) Take 25 mL of 0.43 mol / L HNO3 extraction solution in a centrifuge tube with a lid. Extract it in a 25℃ constant - temperature horizontal shaker at 200 r / min for 2 h. After standing, take the supernatant and filter it through a quantitative filter paper to obtain a blank sample for measurement; (2.3) Use an inductively coupled plasma mass spectrometer to establish a standard curve of different concentrations for the determination of available arsenic by inductively coupled plasma mass spectrometry; (2.4) Use an inductively coupled plasma mass spectrometer to measure the concentration of available arsenic in the extraction solution through the standard curve; (2.5) Calculate the content of plant - available arsenic in the measured soil sample according to the measured mass of the soil sample and the concentration of available arsenic in the measured extraction solution. The calculation formula is as follows: In the formula: W is the content of plant - available arsenic in the measured soil sample, with the unit of mg / kg; c is the concentration of available arsenic in the measured extraction solution, with the unit of mg / L; V1 is the volume of deionized water added, with the unit of mL; V 2 is the volume of HNO3 extraction solution added, with the unit of mL; m is the mass of the measured soil sample, with the unit of g.

[0008] Further, the specific process for establishing the standard curves with different concentrations in step (2.3) is as follows: (2.3.1) Measure 1000 mg / L arsenic standard working solution and place it in a volumetric flask, dilute it to the mark with HNO3 solution with a volume concentration of 1% to prepare an arsenic standard working solution with an arsenic concentration of 100 mg / L; (2.3.2) Respectively measure 0 mL, 0.05 mL, 0.125 mL, 0.25 mL, 0.5 mL and 1 mL of the arsenic standard working solution with an arsenic concentration of 100 mg / L and place them in 50 mL volumetric flasks, dilute them to the mark with HNO3 solution with a volume concentration of 1% to prepare 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) Sequentially inject the 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 into the inductively coupled plasma mass spectrometer. Taking the concentration value of the arsenic standard working solution as the abscissa and the intensity value of the available arsenic as the ordinate, the inductively coupled plasma mass spectrometer automatically plots the standard curves of different concentrations of arsenic, performs linear regression on the standard curves, and obtains the regression equation of the arsenic concentration relationship.

[0009] Further, the specific steps of step (2.4) are as follows: (2.4.1) Inject the blank sample into the inductively coupled plasma mass spectrometer, measure the intensity value of the available arsenic, substitute it into the standard curve regression equation, and calculate the concentration of the available arsenic in the blank sample; (2.4.2) Inject the extraction solution into the inductively coupled plasma mass spectrometer, measure the intensity value of the available arsenic, substitute it into the standard curve regression equation in step (2.3), and calculate the concentration of the available arsenic in the extraction solution; (2.4.3) Determine the concentration of the available arsenic in the extraction solution through the formula c = c1 - c0, where c0 is the concentration of the available arsenic in the blank sample, with the unit of mg / L; c1 is the calculated concentration of the available arsenic in the extraction solution, with the unit of mg / L.

[0010] Preferably, the determination of the total arsenic content in the soil in step two includes the following steps: The soil sample was crushed and ground, then passed through a 100-mesh sieve. 0.5 g was weighed and placed in a 50-ml Erlenmeyer flask. After moistening with water, 7 - 10 mL of aqua regia was added for pre-digestion and left to stand overnight. Then it was heated and digested at 180 - 220 °C until the brown color faded completely. Subsequently, 2 mL of HClO4 was added for oxidation treatment and digestion continued until it became grayish-white. After heating to drive off HClO4 completely, the residue was fixed to a 25-ml colorimetric tube with 1% HNO3 by volume, shaken well, filtered, and the test solution was obtained. The total arsenic content in the soil was determined by hydride generation-atomic fluorescence spectrometry.

[0011] Preferably, the content of arsenic in rice grains in step two includes the following steps: Using microwave-assisted acid digestion method, accurately weigh 0.2 g of rice sample passed through an 80-mesh sieve and place it in a digestion tube. Add 5 mL of 16 mol / L concentrated nitric acid and 2 mL of hydrogen peroxide, shake well, cover the cap, then place it in the outer pressure digestion tank for microwave digestion. Tighten the stainless steel outer cover, put it into an electric blast drying oven at 120 - 150 °C (not exceeding 180 °C) and heat for 240 - 300 min. Let it cool naturally to room temperature, then slowly loosen the stainless steel outer cover, take out the inner digestion tank, rinse the bottle cap with a small amount of ultrapure water, place it on a hot plate, drive off the brown gas at 120 °C. When white smoke appears and there is 1 mL of liquid left, add 1 mL of HClO4 and continue digestion until 1 mL of liquid is left and then take it out. Transfer the digestion solution to a 25-mL volumetric flask or colorimetric tube, wash the inner tank 3 times with 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 of thiourea and ascorbic acid are both 0.05 g / mL. Fix the volume with ultrapure water, shake well, let it stand for 30 min, and then determine it with an atomic fluorescence spectrophotometer.

[0012] Preferably, in step one, the tested rice varieties for the pot experiment are Xiangzaoxian 24 and Zhuliangyou 189.

[0013] Preferably, it further includes: Step four: Field verification (4.1) Tested soil: Collect soil samples around the soil sites of the pot experiment as the tested soil for field verification; (4.2) Test process: Collect soil and rice samples during the rice maturity period, determine the total arsenic and available arsenic in the tested soil, and determine the arsenic content in rice grains; (4.3) Conduct a linear regression analysis between the ratio of available arsenic / total arsenic in the soil measured by the above method and the ratio of arsenic in rice grains / soil total arsenic to verify the accuracy of this method in characterizing the arsenic accumulation risk in rice.

[0014] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses a method for predicting the arsenic accumulation risk in rice, which has the following beneficial effects: This method is easy to operate and has low cost. There is a better linear correlation between the ratio of plant-available arsenic to total arsenic in paddy soil measured by this method and the BCF value of arsenic in rice, which can accurately and rapidly predict the risk of arsenic accumulation in rice. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on the provided drawings.

[0016] Figure 1 For the linear regression analysis of plant-available arsenic in soil and arsenic in rice and the linear regression analysis of the predicted value and the measured value of the BCF of arsenic in rice in the pot experiment; Figure 2 For the linear regression analysis of the ratio of plant-available arsenic to total arsenic in soil and the BCF value of arsenic in rice and the linear regression analysis of the predicted value and the measured value of the BCF of arsenic in rice in the pot experiment; Figure 3 For the linear regression analysis of the ratio of plant-available arsenic to total arsenic in soil measured by the DGT technique and the BCF value of arsenic in rice in the comparative example; Figure 4 For the linear regression analysis of the ratio of plant-available arsenic to total arsenic in soil and the BCF value of arsenic in rice and the linear regression analysis of the predicted value and the measured value of the BCF of arsenic in rice in the regional verification experiment; Figure 5 For the linear regression analysis of the ratio of plant-available arsenic to total arsenic in soil measured by different extraction methods and the BCF value of arsenic in straw and the linear regression analysis of the predicted value and the measured value of the BCF of arsenic in straw in the regional verification experiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The following will clearly and completely describe the technical solutions of the present invention in combination with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0018] A risk prediction method for plant-available arsenic in paddy soil, based on the content of available arsenic in soil extracted by different methods, establishes a linear regression equation between the ratio of it to total arsenic in soil and the BCF value of arsenic in rice grains.

[0019] It includes the following steps: S100) Determination and collection of potting soil The collected paddy soil was used for a pot experiment with conventional water management. Samples were taken at the rice maturity stage, and the arsenic content in rice grains was measured. A linear regression analysis was conducted between the plant-available arsenic in the soil samples and the arsenic content in rice to verify the accuracy of this method for characterizing plant-available arsenic in paddy soil. S110) Soil sample collection and pretreatment Test soil: Considering the complex soil types caused by the large watershed span and the significant differences in soil physical and chemical properties, collecting soil samples from a single region for risk prediction may lack regional universality. Therefore, the test soil was taken from 10 different county-level cities in the upper, middle, and lower reaches of the Xiangjiang River Basin, including: Guiyang County, Chenzhou City; Qiyang City, Yongzhou City; Leiyang City, Hengyang City; Changning City, Hengyang City in the upper reaches; Youxian County, Zhuzhou City; Liling City, Zhuzhou City; Xiangxiang City, Xiangtan City in the middle reaches; Liuyang City, Changsha City; Wangcheng District, Changsha City; Heshan District, Yiyang City in the lower reaches. The five-point sampling method was used to collect the surface paddy soil (0 - 20 cm). The five collected soil samples were thoroughly mixed as the final sample at this point, and the soil type and its parent rock and parent material were determined by observing the remaining soil profile and the surrounding environment on-site. S111) Pot experiment setup Plastic containers with a diameter of 20 cm and a height of 25 cm were used as rice pots. Each pot was filled with 5 kg of soil samples passed through a 1 cm sieve. Before transplantation, nitrogen, phosphorus, and potassium fertilizers were added and mixed with the soil. The addition amounts of urea, ammonium dihydrogen phosphate, and potassium chloride were 0.392 g / kg, 0.164 g / kg, and 0.333 g / kg, respectively. Tap water was added to the pots to maintain a water layer of 2 - 3 cm. After 7 days of equilibration, rice seedlings (Xiangzaoxian 24, Zhuliangyou 189) were transplanted. Before transplantation, seedlings with basically the same growth status were selected, and 2 rice plants were planted in each pot. The same water depth was maintained throughout the growth period, and the fields were drained for 10 days in the late tillering stage and 15 days in the late filling stage. When the rice entered the maturity stage, soil samples and rice grains were collected synchronously. The soil samples were placed in a cool and ventilated place to air dry naturally, and the mixed plant residues and larger-sized impurities were removed. After grinding, they were passed through 20-mesh and 100-mesh sieves and stored for later use; the rice grain samples were dried to remove moisture, shelled, and ground into white powder by a ball mill for later use; The total arsenic and plant-available arsenic in the above pot soil samples were determined, including the following steps: S200) Determination of total As in soil: Weigh 0.5 g of 100-mesh soil sample into a 50-ml Erlenmeyer flask. After moistening with a small amount of water, add 7 - 10 mL of aqua regia for pre-digestion and let it stand overnight. Then, heat and digest at 180 - 220 °C until the brown color fades completely. Subsequently, add 2 mL of HClO4 for oxidation treatment and continue digestion until it turns grayish white. Continue heating to drive off HClO4 completely, and then dilute the residue to 25 mL in a volumetric flask with 1% dilute nitric acid by volume. After shaking well and filtering, obtain the test solution, and determine it by hydride generation-atomic fluorescence spectrometry (HG-AFS, AFS-2202E); S210) Determine the concentration of available arsenic in soil S211) Prepare the extraction solution [[ID=⑥]]Weigh 2.5 g of soil sample into a capped centrifuge tube, add 25 mL of 0.43 mol / L HNO3 extraction solution, extract at 200 r / min for 2 h in a constant temperature horizontal shaker at 25 °C. After standing, take the supernatant and filter it through a quantitative filter paper to obtain the extraction solution. Repeat each treatment 3 times; S212) Prepare the blank sample Add 25 mL of 0.43 mol / L HNO3 extraction solution into a capped centrifuge tube, extract at 200 r / min for 2 h in a constant temperature horizontal shaker at 25 °C. After standing, take the supernatant and filter it through a quantitative filter paper to obtain the blank sample; S220) Establish the standard curve Use an inductively coupled plasma mass spectrometer to establish a standard curve for different concentrations of available arsenic by inductively coupled plasma mass spectrometry; S221) Take an appropriate amount of 1000 mg / L arsenic standard working solution, dilute it with 1% HNO3 solution by volume to obtain an arsenic standard working solution with an arsenic concentration of 100 mg / L. S222) Respectively take 0 mL, 0.05 mL, 0.125 mL, 0.25 mL, 0.5 mL and 1 mL of the 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 by volume 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; S223) Inject the 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 into the inductively coupled plasma mass spectrometer in sequence. Take the concentration value of the arsenic standard working solution as the abscissa and the intensity value of available arsenic as the ordinate. The inductively coupled plasma mass spectrometer automatically plots the standard curve for different concentrations of arsenic, performs linear regression on the standard curve, and obtains the regression equation for the arsenic concentration relationship; S230) Measure the concentration of available arsenic in the extract Use an inductively coupled plasma mass spectrometer to measure the concentration of available arsenic in the extract through a standard curve; S231) Inject the blank sample into the inductively coupled plasma mass spectrometer, measure the intensity value of available arsenic, substitute it into the regression equation, and calculate the concentration of available arsenic in the blank sample; S232) Inject the extract into the inductively coupled plasma mass spectrometer, measure the intensity value of available arsenic, substitute it into the regression equation, and calculate the concentration of available arsenic in the extract; S233) Determine the concentration of available arsenic in the extract through the formula c = c1 - c0, where c0 is the concentration of available arsenic in the blank sample, in mg / L; c1 is the concentration of available arsenic in the extract, in mg / L.

[0020] S300) Result analysis S310) Determine the content of plant-available arsenic in the potted soil sample According to the mass of the measured soil sample and the concentration of the measured extract, calculate the content of plant-available arsenic in the measured soil sample. The calculation formula is as follows: In the formula: W is the content of plant-available arsenic in the measured soil sample, in mg / kg; c is the concentration of available arsenic in the measured extract, in mg / L; V 1 is the volume of deionized water added, in mL; V 2 is the volume of HNO3 extract added, in mL; m is the mass of the measured soil sample, in g; S311) Determine the arsenic content in the potted rice grains Samples were collected during the mature stage of rice. The arsenic content in rice grains was determined according to the national standard method. The microwave-assisted acid digestion method was used. Exactly 0.2 g of rice samples passed through an 80-mesh sieve was weighed and placed in a digestion tube. 5 mL of 16 mol / L concentrated nitric acid and 2 mL of hydrogen peroxide were added. After shaking well and covering the cap, it was placed in an external pressure digestion tank for microwave digestion. The stainless steel outer jacket was tightened and placed in an electrothermal blast drying oven at 120 - 150 °C (not exceeding 180 °C) for heating for 240 - 300 min. It was naturally cooled to room temperature, and then the stainless steel outer jacket was slowly loosened. The inner digestion tank was taken out, the bottle cap was rinsed with a small amount of ultrapure water, placed on a hot plate, and the brown gas was removed at 120 °C. When white smoke appeared and about 1 mL of liquid remained, an appropriate amount (1 mL) of HClO4 was added to continue digestion. After about 1 mL of liquid remained, it was taken out. The digestion solution was transferred to a 25 mL volumetric flask or colorimetric tube. The inner tank was washed 3 times with a small amount of ultrapure water, and the washing solutions were combined. 2.5 mL of a mixed solution of thiourea and ascorbic acid was added. The concentrations of thiourea and ascorbic acid in the mixed solution of thiourea and ascorbic acid were both 0.05 g / mL. It was made up to the mark with ultrapure water, shaken well and left standing for 30 min, and then determined with an atomic fluorescence spectrophotometer (AFS-2202E); A linear regression analysis was performed between the ratio of available arsenic to total arsenic in soil (HNO3-As / T-As) extracted from the pot experiment and the BCF value of arsenic in rice grains (Rice-As / T-As) by S312 to verify the accuracy of this method for characterizing the arsenic accumulation risk in rice. The bioconcentration factor (BCF) is the ratio of the heavy metal content in rice plants to the heavy metal content in soil. This index can effectively characterize the absorption and accumulation characteristics of plants for heavy metals; S400) Field verification S410) Tested soil: To keep the tested soil sites in the pot experiment as consistent as possible, 298 new soil-rice sample sites were added in the small watersheds of the tributaries of the Xiangjiang River Basin around the pot experiment soil sites. The collected soil samples were used as the tested soil for field verification; S411) Test process: Soil and rice samples were collected during the mature stage of rice. The total amount of arsenic in the soil was determined, as well as the arsenic content in rice grains and straws. The available arsenic in the air-dried soil samples was extracted by the HNO3 extraction method. The total arsenic and available arsenic in the tested soil and the arsenic in rice grains were determined; S412) A linear regression analysis was performed between the ratio of available arsenic to total arsenic in soil (HNO3-As / T-As) and the BCF value of arsenic in rice grains (Rice-As / T-As) determined by the above method to verify the accuracy of this method for characterizing the arsenic accumulation risk in rice.

[0021] Result analysis: The linear regression relationships between the available arsenic in soil extracted from pot experiments of two rice varieties (Xiangzaoxian 24 and Zhuliangyou 189) and the arsenic content in rice grains are as follows Figure 1 shown, where Figure 1 a is the linear regression analysis chart of the content of available arsenic determined by the method of the present invention and the arsenic content in rice grains, Figure 1 b is the linear regression analysis chart between the arsenic in rice calculated from the content of available arsenic determined and the actual arsenic in rice grains.

[0022] From Figure 1 a, it can be seen that the linear correlation formula between the content of available arsenic determined by the method of the present invention and the arsenic content in the grains of the two rice varieties is as follows: For Xiangzaoxian 24: y1 = 0.0771x1 + 0.3700 (R1 2 = 0.2314, P <0.01, n = 30); For Zhuliangyou 189: y2 = 0.0409x2 + 0.3543 (R2 2 = 0.1008, n = 30); From Figure 1 b, it can be seen that the linear correlation formula between the arsenic in rice calculated from the content of available arsenic determined and the actual arsenic in rice grains is as follows: For Xiangzaoxian 24: y1 = 0.9999x1 (R1 2 = 0.2314, P <0.01, n = 30); For Zhuliangyou 189: y2 = 0.9998x2 + 0.0001 (R2 2 = 0.1008, n = 30).

[0023] The above results show that the correlation for directly predicting the arsenic accumulation in rice is relatively low, and a more accurate prediction method is needed.

[0024] The linear regression relationships between the ratio of available arsenic / total arsenic in soil extracted from pot experiments of two rice varieties (Xiangzaoxian 24 and Zhuliangyou 189) and the arsenic BCF values in rice grains are as follows Figure 2 shown, where Figure 2 a is the linear regression analysis chart between the available arsenic / total arsenic in soil determined and the arsenic BCF values in the grains of the two rice varieties, Figure 2 b is the linear regression analysis chart between the arsenic BCF value in rice calculated from the content of available arsenic determined and the actual arsenic BCF in rice grains.

[0025] From Figure 2 a, it can be seen that the linear correlation formula between the available arsenic / total arsenic in soil determined and the arsenic BCF values in the grains of the two rice varieties is as follows: Xiangzaoxian 24: y1 = 0.2558x1 + 0.0019 (R1 2 = 0.7206, P <0.01, n = 30); Zhuliangyou 189: y2 = 0.2336x2 + 0.0005 (R2 2 = 0.6727, n = 30); From Figure 2 b, it can be seen that the linear correlation formula between the rice arsenic BCF value calculated according to the measured content of available arsenic and the actual rice grain arsenic BCF is:<--Removed redundant tag as it seems to be an error or not needed.-->Xiangzaoxian 24: y1 = 1.0001x1 (R1 2 = 0.7206, P <0.01, n = 30); Zhuliangyou 189: y2 = 1.0001x2 + 0.0005 (R2 2 = 0.6727, P <0.01, n = 30); From the above results, the linear correlation between the measured available arsenic / total soil arsenic and the BCF values of arsenic in the grains of two types of rice (Xiangzaoxian 24 and) is: For Xiangzaoxian 24, R1 2 = 0.7206, for Zhuliangyou 189, R2 2 = 0.6727. The linear correlation between the rice arsenic BCF value calculated according to the measured content of available arsenic and the actual rice grain arsenic BCF is: For Xiangzaoxian 24, R1 2 = 0.7206, for Zhuliangyou 189, R2 2 = 0.6727. This indicates that this method can be used to accurately predict the rice arsenic BCF value.

[0026] The linear regression relationship between the available arsenic / total arsenic in soil verified in the field at nearly 300 points and the BCF value of arsenic in rice grains is as Figure 4 shown, where Figure 4 a is the linear regression analysis graph between the measured available arsenic / total soil arsenic and the BCF of arsenic in rice grains, Figure 4 b is the linear regression analysis graph between the rice arsenic BCF value calculated according to the measured content of available arsenic and the actual rice grain arsenic BCF.

[0027] From Figure 4 a, the linear correlation formula between the measured available arsenic / total soil arsenic and the BCF of arsenic in rice grains is: y = 0.1214x + 0.0094 (R1 2 = 0.2612, P <0.01, n = 293); From Figure 4As can be seen from b, the linear correlation formula between the rice arsenic BCF value calculated based on the measured content of available arsenic and the actual rice grain arsenic BCF is: y = 0.9986x + 0.0008 (R1 2 = 0.2612, P <0.01, n = 293); From the above results, the linear correlation between the measured available arsenic / total soil arsenic and the rice grain arsenic BCF is R1 2 = 0.2612; the linear correlation between the rice arsenic BCF value calculated based on the measured content of available arsenic and the actual rice grain arsenic BCF is R1 2 = 0.2612. This method is easy to operate and has a certain correlation even in the field verification of nearly 300 points with multiple soil properties and multiple rice varieties.

[0028] The linear regression relationship between the available arsenic in soil and the arsenic BCF value in rice straw verified through nearly 300 points in the field is as Figure 5 shown, where Figure 5 a is the linear regression analysis diagram between the measured available arsenic / total soil arsenic and the arsenic BCF in rice straw, Figure 5 b is the linear regression analysis diagram between the rice arsenic BCF value calculated based on the measured content of available arsenic and the actual rice grain arsenic BCF.

[0029] From Figure 5 a, the linear correlation formula between the measured available arsenic / total soil arsenic and the arsenic BCF in rice straw is: y = 2.1087x + 0.0765 (R1 2 = 0.2739, P <0.01, n = 293); From Figure 5 b, the linear correlation formula between the rice arsenic BCF value calculated based on the measured content of available arsenic and the actual rice grain arsenic BCF is: y = 1.0000x + 0.0004 (R1 2 = 0.2739, P <0.01, n = 293); From the above results, 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 content of available arsenic and the actual rice grain arsenic BCF is R1 2 = 0.2739, slightly higher than the rice arsenic BCF. This method is easy to operate and has a certain correlation even in the field verification of nearly 300 points with multiple soil properties and multiple rice varieties.

[0030] Comparative example In recent years, the DGT technology has developed rapidly, which can accurately evaluate the bioavailability of heavy (metalloid) metals such as arsenic in various soils and simulate the dynamic reaction process of soils. It has the advantages of being in-situ, passive, and biomimetic, etc. Its disadvantage is the high determination cost. Figure 3 It is a linear regression analysis diagram of DGT-As / T-As and rice grain As-BCF for two rice varieties (Xiangzaoxian 24 and Zhuliangyou 189), where Figure 3 a is the linear regression analysis diagram for acidic soils, Figure 3 b is the linear regression analysis diagram for alkaline soils, Figure 3 c is the linear regression analysis diagram for all soil conditions.

[0031] Figure 3 As can be seen from c, the linear correlation formula between the available arsenic determined by the DGT technology / total soil arsenic and the arsenic BCF values of the two rice grains is: For Xiangzaoxian 24: y1 = 0.1257x1 + 0.0231 (R1 2 = 0.0357, n = 30); For Zhuliangyou 189: y2 = 0.0750x2 + 0.0212 (R2 2 = 0.0137, n = 30); That is, according to the linear regression results, the linear correlation between the available arsenic determined by the DGT technology / total soil arsenic and the arsenic BCF values of the two rice grains: for Xiangzaoxian 24, R1 2 = 0.0357, for Zhuliangyou 189, R2 2 = 0.0137 is much lower than that of Xiangzaoxian 24, R1 2 = 0.7206, and Zhuliangyou 189, R2 2 = 0.6727 in the method of the present invention, as well as R1 2 = 0.2612 in the field verification example using the method of the present invention. Therefore, the present invention can predict the arsenic accumulation risk in rice more cheaply and accurately.

[0032] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the various embodiments can be referred to each other. The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will conform to 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: The following steps are involved: Step 1: Potted experiment Soil samples from the topsoil layer of rice fields were collected for pot experiments. Conventional water management was adopted, and soil samples and rice grain samples were taken from the pots during the rice maturity period. Step 2: Sample processing Determine the available arsenic content and the total arsenic content in the potted soil collected in step 1, and determine the arsenic content in the rice grains collected in step 1; Step 3: Computational Analysis Linear regression analysis was performed between the ratio of available arsenic content in soil to total arsenic content and the ratio of arsenic content in rice grains to total arsenic content in soil to predict the arsenic accumulation risk of rice.

2. The method for predicting arsenic accumulation risk in rice according to claim 1, wherein: The pot experiment in step 1 includes the following steps: Rice pots were filled with soil that had passed through a 1 cm sieve. Before transplanting rice, 0.392 g / kg of urea, 0.164 g / kg of ammonium dihydrogen phosphate, and 0.333 g / kg of potassium chloride were applied to the soil and mixed evenly. Tap water was added to maintain a 2-3 cm water layer. After 7 days of equilibrium, seedlings with basically the same growth conditions were transplanted. After the rice entered the maturity period, soil samples and rice grains were collected simultaneously. The soil samples were placed in a cool and ventilated place to dry naturally, and impurities were removed. After grinding, the soil samples were sieved through 20 mesh and 100 mesh sieves and stored for later use. The rice grain samples were dried in the sun to remove moisture, shelled, and passed through a ball mill to become white powder for later use.

3. The method for predicting arsenic accumulation risk in rice according to claim 1, wherein: In step 1, soil from the 0-20 cm depth layer was collected. The five-point sampling method was used. The five collected soil samples were fully mixed and used as the final samples of the paddy field topsoil sampling points. The mixed soil was naturally air-dried at room temperature before potting experiments.

4. The method for predicting arsenic accumulation risk in rice according to claim 1, wherein: The determination of the available arsenic content in the soil described in step 2 includes the following steps: (2.1) Grind the soil sample and pass it through a 20-mesh sieve. Weigh the soil sample and place it in a centrifuge tube. Add 0.43 mol / L HNO3 extractant at a volume ratio of 1:10 g / mL. Incubate the sample in a 5°C horizontal oscillator at 200 rpm for 2 h. After extraction, filter the sample to obtain the extract for testing. (2.2) Place 25 mL of 0.43 mol / L HNO3 extract in a capped centrifuge tube and incubate at 25°C in a horizontal shaker at 200 rpm for 2 h. After stabilization, remove the supernatant and pass it through a quantitative filter paper to prepare a blank sample for testing. (2.3) Establish a standard curve for determining different concentrations of available arsenic using inductively coupled plasma mass spectrometry (ICP-MS). (2.4) Measure the concentration of available arsenic in the extract using an inductively coupled plasma mass spectrometer (ICP-MS) using a standard curve. (2.5) Based on the measured mass of the soil sample and the measured concentration of available arsenic in the extract, calculate the plant-available arsenic content in the soil sample using the following formula: Where: W is the plant available arsenic content in the measured soil sample, in mg / kg; c is the concentration of available arsenic in the measured extract, in mg / L; V 1 is the volume of deionized water added, in mL; V 2 is the volume of HNO3 extract added, in mL; m is the mass of the soil sample measured in g.

5. The method for predicting arsenic accumulation risk in rice according to claim 4, characterized in that: The specific process of establishing the standard curve of different concentrations in step (2.3) is as follows: (2.3.1) Measure 1000 mg / L of standard working arsenic solution into a volumetric flask and dilute to volume with 1% HNO3 solution to obtain a standard working arsenic solution with an arsenic concentration of 100 mg / L. (2.3.2) Measure 0 mL, 0.05 mL, 0.125 mL, 0.25 mL, 0.5 mL, and 1 mL of the 100 mg / L arsenic standard working solution into a 50 mL volumetric flask. Dose to volume with 1% HNO3 solution to prepare 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) Inject standard arsenic 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 into the inductively coupled plasma mass spectrometer, sequentially. The inductively coupled plasma mass spectrometer automatically plots standard curves for different arsenic concentrations, with the concentration of the standard arsenic solution as the horizontal axis and the intensity of the effective arsenic as the vertical axis. Perform a linear regression on the standard curves to determine the regression equation for the arsenic concentration relationship.

6. The method for predicting arsenic accumulation risk in rice according to claim 4, characterized in that: The specific steps of step (2.4) are: (2.4.1) Inject the blank sample into the inductively coupled plasma mass spectrometer and measure the intensity of the available arsenic. Substitute the intensity into the standard curve regression equation to calculate the concentration of the available arsenic in the blank sample. (2.4.2) Inject the extract into an inductively coupled plasma mass spectrometer to measure the intensity of available arsenic. Substitute the intensity into the standard curve regression equation from step (2.3) to calculate the concentration of available arsenic in the extract. (2.4.3) Determine the concentration of available arsenic in the extract using the formula c = c1 - c0, where c0 is the concentration of available arsenic in the blank sample, expressed in mg / L; c1 is the calculated concentration of available arsenic in the extract, expressed in mg / L.

7. The method for predicting arsenic accumulation risk in rice according to claim 1, wherein: The determination of total arsenic content in soil in step 2 includes the following steps: The soil sample was crushed and ground, passed through a 100-mesh sieve, 0.5 g was weighed and placed in a 50 ml conical flask, moistened with water, and pre-digested with 7-10 ml aqua regia. After standing overnight, it was heated at 180-220 ° C and digested until the brown color faded. Subsequently, 2 ml HClO4 was added for oxidation treatment and continued to digest until it turned off-white. After continuing to heat to drive out the HClO4, the residue was diluted to a 25 ml colorimetric tube with 1% HNO3 by volume. After shaking and filtering, the test solution was obtained, and the total arsenic content in the soil was determined by hydride generation-atomic fluorescence spectrometry.

8. The method for predicting arsenic accumulation risk in rice according to claim 1, wherein: The arsenic content in rice grains in step 2 comprises the following steps: Microwave-assisted acid digestion was used. 0.2 g of rice sample that had passed through an 80-mesh sieve was accurately weighed and placed in a digestion tube. 5 mL of 16 mol / L concentrated nitric acid and 2 mL of hydrogen peroxide were added. The mixture was shaken and covered. The mixture was then placed in a pressure digestion outer tank for microwave digestion. The stainless steel jacket was tightened and the sample was placed in an electric blast drying oven at 120-150 °C and heated for 240-300 min. The sample was naturally cooled to room temperature. The stainless steel jacket was then slowly loosened. The digestion inner tank was taken out. The bottle cap was rinsed with a small amount of ultrapure water and placed on a hot plate. The brown gas was driven away at 120 °C. When white smoke appeared and 1 mL of liquid remained, 1 mL of HClO4 was added to continue digestion. The remaining 1 mL of liquid was taken out and the digestion solution was transferred to a 25 mL volumetric flask or colorimetric tube. The inner tank was washed 3 times with ultrapure water. The washing solution was combined and 2.5 mL of HClO4 was added. mL of thiourea and ascorbic acid mixed solution, the concentration of thiourea and ascorbic acid in the mixed solution was 0.05 g / mL, the volume was made up with ultrapure water, the mixture was shaken and allowed to stand for 30 min before determination by atomic fluorescence spectrophotometer.

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

10. The method for predicting arsenic accumulation risk in rice according to claim 1, wherein: Also includes: Step 4: Field Verification (4.1) Test soil: Soil samples were collected around the pot test soil site as field validation test soil; (4.2) Experimental Procedure: Soil and rice samples were collected during the rice maturity period. The total arsenic and available arsenic content in the soil were determined, and the arsenic content in the rice grains was determined. (4.3) Linear regression analysis was performed between 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 this method in characterizing the arsenic accumulation risk of rice.

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