CN113435640A - Method for predicting in-situ EC (soil EC) of soil in different plough layers of main growth period of rice in soda saline-alkali soil - Google Patents
Method for predicting in-situ EC (soil EC) of soil in different plough layers of main growth period of rice in soda saline-alkali soil Download PDFInfo
- Publication number
- CN113435640A CN113435640A CN202110701940.3A CN202110701940A CN113435640A CN 113435640 A CN113435640 A CN 113435640A CN 202110701940 A CN202110701940 A CN 202110701940A CN 113435640 A CN113435640 A CN 113435640A
- Authority
- CN
- China
- Prior art keywords
- soil
- situ
- stage
- plough layer
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000002689 soil Substances 0.000 title claims abstract description 276
- 238000011065 in-situ storage Methods 0.000 title claims abstract description 194
- 235000007164 Oryza sativa Nutrition 0.000 title claims abstract description 43
- 235000009566 rice Nutrition 0.000 title claims abstract description 43
- CDBYLPFSWZWCQE-UHFFFAOYSA-L Sodium Carbonate Chemical compound [Na+].[Na+].[O-]C([O-])=O CDBYLPFSWZWCQE-UHFFFAOYSA-L 0.000 title claims abstract description 39
- 239000003513 alkali Substances 0.000 title claims abstract description 39
- 238000000034 method Methods 0.000 title claims abstract description 21
- 240000007594 Oryza sativa Species 0.000 title 1
- 241000209094 Oryza Species 0.000 claims abstract description 42
- 239000008267 milk Substances 0.000 claims abstract description 27
- 210000004080 milk Anatomy 0.000 claims abstract description 27
- 235000013336 milk Nutrition 0.000 claims abstract description 27
- 230000017260 vegetative to reproductive phase transition of meristem Effects 0.000 claims abstract description 27
- 239000000523 sample Substances 0.000 claims description 33
- 239000002184 metal Substances 0.000 claims description 17
- 238000004140 cleaning Methods 0.000 claims description 6
- 239000004744 fabric Substances 0.000 claims description 6
- 239000007788 liquid Substances 0.000 claims description 5
- 238000002474 experimental method Methods 0.000 description 9
- 238000005259 measurement Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000001356 surgical procedure Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000007605 air drying Methods 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 239000012153 distilled water Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 238000002386 leaching Methods 0.000 description 1
- 239000011707 mineral Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 230000021962 pH elevation Effects 0.000 description 1
- -1 salt ions Chemical class 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- UIIMBOGNXHQVGW-UHFFFAOYSA-M sodium bicarbonate Substances [Na+].OC([O-])=O UIIMBOGNXHQVGW-UHFFFAOYSA-M 0.000 description 1
- 229910000030 sodium bicarbonate Inorganic materials 0.000 description 1
- 229910000029 sodium carbonate Inorganic materials 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Operations Research (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- General Engineering & Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Software Systems (AREA)
- Quality & Reliability (AREA)
- Databases & Information Systems (AREA)
- Algebra (AREA)
- Life Sciences & Earth Sciences (AREA)
- Agronomy & Crop Science (AREA)
- Animal Husbandry (AREA)
- Marine Sciences & Fisheries (AREA)
- Mining & Mineral Resources (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Consolidation Of Soil By Introduction Of Solidifying Substances Into Soil (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
A method for predicting in-situ EC of soil in different plough layers of main growth periods of rice in soda saline-alkali soil relates to a method for predicting indexes of soda saline-alkali soil. The method aims to solve the technical problem that the rapid and accurate acquisition of the plough layer in-situ EC in the main growth period of the rice in the soda saline-alkali soil is time-consuming and labor-consuming. The method comprises the following steps: measuring to obtain plough layer soil in-situ EC of 5cm in a seedling turning stage, a tillering stage, an elongation stage, a booting stage, a heading stage, a flowering stage and a milk stage; and secondly, substituting the numerical value obtained in the step one into an EC regression prediction equation to obtain the in-situ EC of the plough layer soil of 10cm, 15cm and 20 cm. According to the method, the in-situ EC of the plough layer soil of 10cm, 15cm and 20cm in the corresponding main growth period of the soda saline-alkali soil rice field is predicted based on the in-situ EC of the plough layer soil of 5cm in the main growth period of the rice through a regression equation. The determination method is time-saving and labor-saving, and can simply, quickly, scientifically and accurately obtain the in-situ EC of the soil in different plough layers in the main growth period of the rice. Belonging to the field of prediction of soil in-situ EC of different plough layers in the rice growth period.
Description
Technical Field
The invention relates to a method for predicting indexes of soda saline-alkali soil.
Background
The Songnen plain is one of three concentrated regions of soda saline-alkali soil in the world, and the soda saline-alkali soil is composed of NaHCO3With Na2CO3Mainly has pH more than 8.5, is strong alkaline, has alkalinization degree more than 70 percent, has poor physicochemical property, large treatment difficulty, long time and slow effect. Practice proves that the development of the rice seeds is an effective way for improving and utilizing the soda saline-alkali land. The soil conductivity (EC) is an index for measuring water-soluble salt in soil and is an important reference for judging the light and heavy degree of soda saline-alkali soil. Meanwhile, the soil EC of different plough layers of the rice is an important factor for judging whether the salt ions in the soda saline-alkali soil limit the growth of the rice and influence the absorption and utilization of mineral nutrition. Therefore, monitoring of soil salinity of different plough layers of the main growth period of the rice in soda saline-alkali soil is an essential measure. For a long time, most of saline-alkali soil plough layer EC measurement is carried out by taking a soil sample and air-drying the soil, and then preparing a soil leaching solution for indoor measurement, and along with the development of the technology, the soil in-situ EC is taken as a portable soil salinity measuring instrument for wide application. Before the in-situ EC meter is used for testing, the surface of a metal probe of the in-situ EC meter is firstly cleaned by an abrasive cloth so as to prevent the measurement precision of the in-situ EC meter from being influenced. When the method is used for measuring the soil EC of different plough layers, after the in-situ EC of soil of one plough layer depth is measured, the soil on the surface of a metal probe of the EC meter needs to be cleaned in time, and the in-situ EC of the soil of other depths is measured after the EC meter is washed by distilled water. However, the physical and chemical properties of the soda saline-alkali soil are poor, the heavy soil is adhered to the surface of the probe, the cleaning process is troublesome and labor-consuming, and the rapid and accurate acquisition of the in-situ EC of the soil in different plough layers of the main growth period of the rice in the soda saline-alkali soil has certain difficulty.
Disclosure of Invention
The invention aims to solve the technical problem that the rapid and accurate acquisition of the in-situ EC of the soil in different plough layers of the main growth period of the rice in the soda saline-alkali soil is time-consuming and labor-consuming, and provides a method for predicting the in-situ EC of the soil in different plough layers of the main growth period of the rice in the soda saline-alkali soil.
The method for predicting different plough layers EC of the main growth period of the rice in the soda saline-alkali soil is carried out according to the following steps:
cleaning the surface of a metal probe of a soil in-situ EC meter by using grinding cloth, and correcting the precision of the probe by using standard liquid of the soil in-situ EC meter;
secondly, in the rice green turning stage, tillering stage, jointing stage, booting stage, heading stage, flowering stage and milk stage of soda saline-alkali soil, vertically and clockwise inserting a metal probe of a soil in-situ EC meter into soil of a plough layer of a rice field, stopping inserting the probe into the soil with the depth of 5cm, and enabling the soil to be completely and uniformly contacted with the metal surface of the probe, wherein the response time is 10-20 seconds, and the number displayed by an instrument is the measured value of the EC of the soil of the plough layer of 5cm in the green turning stage, tillering stage, jointing stage, heading stage, flowering stage and milk stage;
and thirdly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning period obtained in the step two as an x value into an EC regression prediction equation (1):
Y＝-0.001x3+0.04x2+0.62x+0.681，R2obtaining the in-situ EC of the soil of 10cm plough layer in the green turning period as 0.965 (1);
substituting the EC measured value of the soil in the 5cm plough layer of the green turning period obtained in the step two as an x value into an EC regression prediction equation (2):
Y＝-0.001x3+0.033x2+0.700x+0.748，R2obtaining the in-situ EC of the soil of the 15cm plough layer in the green turning period as 0.927 (2);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the green turning period obtained in the step two as an x value into an EC regression prediction equation (3):
Y＝-0.001x3+0.005x2+1.052x+0.324，R2obtaining the in-situ EC of the soil of the 20cm plough layer in the green turning period as 0.914 (3);
and fourthly, substituting the measured value of the in-situ EC of the soil in the plough layer of 5cm at the tillering stage obtained in the second step into an EC regression prediction equation (4) as an x value:
Y＝3.953E-05x3-0.014x2+1.272x-0.910，R2obtaining the in-situ EC of the soil of 10cm plough layer at the tillering stage as 0.992 (4);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the tillering stage obtained in the step two as an x value into an EC regression prediction equation (5):
Y＝0.980x0 . 993，R2obtaining the in-situ EC of the soil of a plough layer of 15cm at the tillering stage as 0.916 (5);
substituting the EC in-situ measured value of the soil EC of the 5cm plough layer at the tillering stage obtained in the step two as an x value into an EC regression prediction equation (6):
Y＝3.755E-05x3-0.013x2+1.191x-0.159，R20.979(6), namely obtaining the in-situ EC of the soil of a 20cm plough layer at the tillering stage;
and fifthly, substituting the measured value of the soil in-situ EC of the soil of the 5cm plough layer in the jointing stage obtained in the step two as an x value into an EC regression prediction equation (7):
Y＝0.065x3+0.508x2–0.521x+1.882，R2obtaining the soil in-situ EC of 10cm plough layer in the jointing stage when the yield is 0.488 (7);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the jointing stage obtained in the step two into an EC regression prediction equation (8) as an x value:
Y＝-0.027x3+0.161x2+0.190x+1.916，R2obtaining the soil in-situ EC of 15cm plough layer soil in the jointing stage when the soil is 0.131 (8);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the jointing stage obtained in the step two into an EC regression prediction equation (9) as an x value:
Y＝0.057x3-0.546x2+2.495x-0.817，R20.031(9), namely getting the soil in-situ EC of 20cm plough layer in jointing stage;
and sixthly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two as an x value into an EC regression prediction equation (10):
Y＝0.005x3-0.135x2+0.853x+2.021，R2obtaining the in-situ EC of the soil of 10cm plough layer in the booting stage as 0.590 (10);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two into an EC regression prediction equation (11) as an x value:
Y＝2.105x0 . 434，R2obtaining the in-situ EC of the soil in the plough layer of 15cm in the booting stage, namely 0.158 (11);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two into an EC regression prediction equation (12) as an x value:
Y＝0.314x3–3.076x2+9.856x-6.375，R2obtaining the soil in-situ EC of 20cm plough layer soil in the booting stage as 0.069 (12);
and seventhly, substituting the in-situ EC measured value of the soil in the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (13):
Y＝-0.196x3+1.500x2-2.897x+3.786，R2obtaining the in-situ EC of the soil of 10cm plough layer in the heading stage when the yield is 0.450 (13);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (14):
Y＝-0.353x3+2.287x2-3.978x+4.321，R2obtaining the in-situ EC of the soil in the plough layer of 15cm in the heading stage when the yield is 0.188 (14);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (15):
Y＝-0.173x3+0.996x2-0.956x+2.611，R2obtaining the in-situ EC of the soil of a 20cm plough layer in the heading stage as 0.082 (15);
and eighthly, substituting the in-situ EC measured value of the soil of the 5cm plough layer at the flowering stage obtained in the step two into an EC regression prediction equation (16) as an x value:
Y＝1.350x0 . 768，R20.598(16), namely obtaining the in-situ EC of the 10cm plough layer soil in the flowering period;
substituting the in-situ EC measured value of the soil of 5cm plough layer of flowering phase obtained in the step two into an EC regression prediction equation (17) as an x value:
Y＝1.444x0 . 765，R20.433(17), namely obtaining the in-situ EC of the soil of a 15cm plough layer in the flowering period;
substituting the in-situ EC measured value of the soil of 5cm plough layer of the flowering phase obtained in the step two into an EC regression prediction equation (18) as an x value:
Y＝0.156x3-1.511x2+5.330x-2.902，R20.336(18), namely obtaining the in-situ EC of 20cm plough layer soil in the flowering period;
and ninthly, substituting the measured value of the soil in-situ EC of the plough layer of 5cm in the milk stage obtained in the step two as the x value into an EC regression prediction equation (19):
Y＝-0.095x3+0.893x2-1.759x+3.150，R20.635(19), namely obtaining the in-situ EC of the soil of a 10cm plough layer in the milk stage;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the milk stage obtained in the step two as an x value into an EC regression prediction equation (20):
Y＝-0.068x3+0.636x2-1.263x+3.383，R20.384(20), namely the in-situ EC of the soil of the plough layer of 15cm in the milk stage is obtained;
substituting the in-situ EC measured value of soil of 5cm plough layer in the milk stage obtained in the step two as an x value into an EC regression prediction equation (21):
Y＝-0.117x3+1.028x2-2.344x+4.725，R2and (3) obtaining the in-situ EC of the soil of the 20cm plough layer in the milk stage when the yield is 0.170 (21).
According to the method, the in-situ EC of the plough layer soil of 10cm, 15cm and 20cm in the corresponding main growth period of the soda saline-alkali soil rice field can be predicted based on the in-situ EC of the plough layer soil of 5cm in the main growth period of the rice through a regression equation.
The determination method is time-saving and labor-saving, and can simply, quickly, scientifically and accurately obtain the in-situ EC of the soil in different plough layers in the main growth period of the rice.
Drawings
FIG. 1 is a correlation graph of the predicted value and the measured value of the in-situ EC of the soil of a plough layer of 10cm in the rice green turning period in the soda saline-alkali soil in the first experiment;
FIG. 2 is a correlation graph of the predicted value and the measured value of the in-situ EC of the soil in the plough layer of 15cm at the rice green turning stage in the soda saline-alkali soil in the first experiment;
FIG. 3 is a correlation graph of the predicted value and the measured value of the in-situ EC of the soil in the 20cm plough layer of the rice at the seedling turning stage in the soda saline-alkali soil in the first experiment;
FIG. 4 is a correlation graph of the predicted value and the measured value of the in-situ EC of the plough layer soil of 10cm at the tillering stage of the rice in the soda saline-alkali soil in the second experiment;
FIG. 5 is a correlation graph of the predicted value and the measured value of the in-situ EC of the plough layer soil of 10cm at the tillering stage of the rice in the soda saline-alkali soil in the second experiment;
FIG. 6 is a correlation graph of the predicted value and the measured value of the in-situ EC of the plough layer soil of 10cm at the tillering stage of the rice in the soda saline-alkali soil in the second experiment.
Detailed Description
The technical solution of the present invention is not limited to the following specific embodiments, but includes any combination of the specific embodiments.
The first embodiment is as follows: the method for predicting the in-situ EC of the soil in different plough layers of the main growth period of the rice in the soda saline-alkali soil is carried out according to the following steps:
cleaning the surface of a metal probe of a soil in-situ EC meter by using grinding cloth, and correcting the precision of the probe by using standard liquid of the soil in-situ EC meter;
secondly, in the rice green turning stage, tillering stage, jointing stage, booting stage, heading stage, flowering stage and milk stage of soda saline-alkali soil, vertically and clockwise inserting a metal probe of a soil in-situ EC meter into soil of a plough layer of a rice field, stopping inserting the probe into the soil with the depth of 5cm, and enabling the soil to be completely and uniformly contacted with the metal surface of the probe, wherein the response time is 10-20 seconds, and the number displayed by an instrument is the measured value of the in-situ EC of the soil of the plough layer of 5cm in the green turning stage, tillering stage, jointing stage, heading stage, flowering stage and milk stage;
performing correlation analysis on the in-situ EC of 5cm plough layer soil in a rice green turning stage, a tillering stage, an elongation stage, a booting stage, a heading stage, a flowering stage and a milk stage and the in-situ EC of 10cm, 15cm and 20cm plough layer soil in corresponding growth stages by adopting SPSS software;
respectively constructing regression equations for the in-situ EC of 5cm plough layer soil in the rice green turning stage, the tillering stage, the jointing stage, the booting stage, the heading stage, the flowering stage and the milk stage and the in-situ EC of 10cm plough layer soil, 15cm plough layer soil and 20cm plough layer soil in the corresponding growth stages by adopting SPSS software;
and thirdly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning period obtained in the second step into an EC regression prediction equation (1) as an x value (obtained according to 834 sample measured values):
Y＝-0.001x3+0.04x2+0.62x+0.681，R2obtaining the in-situ EC of the soil of 10cm plough layer in the green turning period as 0.965 (1);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the green turning period obtained in the step two into an EC regression prediction equation (2) as an x value (obtained according to 834 sample measured values):
Y＝-0.001x3+0.033x2+0.700x+0.748，R2obtaining the in-situ EC of the soil of the 15cm plough layer in the green turning period as 0.927 (2);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the green turning period obtained in the step two as an x value into an EC regression prediction equation (3) (obtained according to 834 sample measured values):
Y＝-0.001x3+0.005x2+1.052x+0.324，R2obtaining the in-situ EC of the soil of the 20cm plough layer in the green turning period as 0.914 (3);
and fourthly, substituting the in-situ EC measured value of the soil in the plough layer of 5cm at the tillering stage obtained in the second step into an EC regression prediction equation (4) as an x value (obtained according to actual measured values of 1080 samples):
Y＝3.953E-05x3-0.014x2+1.272x-0.910，R2obtaining the in-situ EC of the soil of 10cm plough layer at the tillering stage as 0.992 (4);
substituting the in-situ EC measured value of the soil in the plough layer of 5cm at the tillering stage obtained in the step two as an x value into an EC regression prediction equation (5) (obtained according to actual measured values of 1080 samples):
Y＝0.980x0 . 993，R2obtaining the in-situ EC of the soil of a plough layer of 15cm at the tillering stage as 0.916 (5);
substituting the in-situ EC measured value of the soil in the plough layer of 5cm at the tillering stage obtained in the step two as an x value into an EC regression prediction equation (6) (obtained according to actual measured values of 1080 samples):
Y＝3.755E-05x3-0.013x2+1.191x-0.159，R20.979(6), namely obtaining the in-situ EC of the soil of a 20cm plough layer at the tillering stage;
and fifthly, substituting the in-situ EC measured value of the soil of the 5cm plough layer in the jointing stage obtained in the step two as an x value into an EC regression prediction equation (7) (obtained according to 460 sample measured values):
Y＝0.065x3+0.508x2–0.521x+1.882，R2obtaining the soil in-situ EC of 10cm plough layer in the jointing stage when the yield is 0.488 (7);
substituting the EC measured value of the soil in situ of the 5cm plough layer soil in the jointing stage obtained in the step two into an EC regression prediction equation (8) as an x value (obtained according to the actual measured values of 460 samples):
Y＝-0.027x3+0.161x2+0.190x+1.916，R2obtaining the soil in-situ EC of 15cm plough layer soil in the jointing stage when the soil is 0.131 (8);
substituting the EC measured value of the soil in situ of the 5cm plough layer soil in the jointing stage obtained in the step two into an EC regression prediction equation (9) as an x value (obtained according to the actual measured values of 460 samples):
Y＝0.057x3-0.546x2+2.495x-0.817，R20.031(9), namely getting the soil in-situ EC of 20cm plough layer in jointing stage;
and sixthly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two as an x value into an EC regression prediction equation (10) (obtained according to actual measured values of 320 samples):
Y＝0.005x3-0.135x2+0.853x+2.021，R2obtaining the in-situ EC of the soil of 10cm plough layer in the booting stage as 0.590 (10);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two as an x value into an EC regression prediction equation (11) (obtained according to actual measured values of 320 samples):
Y＝2.105x0 . 434，R2obtaining the in-situ EC of the soil in the plough layer of 15cm in the booting stage, namely 0.158 (11);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two as an x value into an EC regression prediction equation (12) (obtained according to actual measured values of 320 samples):
Y＝0.314x3–3.076x2+9.856x-6.375，R2obtaining the soil in-situ EC of 20cm plough layer soil in the booting stage as 0.069 (12);
and seventhly, substituting the in-situ EC value of the soil of the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (13) (obtained according to measured values of 320 samples):
Y＝-0.196x3+1.500x2-2.897x+3.786，R2obtaining the in-situ EC of the soil of 10cm plough layer in the heading stage when the yield is 0.450 (13);
substituting the in-situ EC measured value of the soil in the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (14) (obtained according to actual measured values of 320 samples):
Y＝-0.353x3+2.287x2-3.978x+4.321，R2obtaining the in-situ EC of the soil in the plough layer of 15cm in the heading stage when the yield is 0.188 (14);
substituting the in-situ EC measured value of the soil in the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (15) (obtained according to actual measured values of 320 samples):
Y＝-0.173x3+0.996x2-0.956x+2.611，R2obtaining the in-situ EC of the soil of a 20cm plough layer in the heading stage as 0.082 (15);
and eighthly, substituting the in-situ EC measured value of the soil of the 5cm plough layer at the flowering stage obtained in the step two into an EC regression prediction equation (16) as an x value (obtained according to the actual measured values of 320 samples):
Y＝1.350x0 . 768，R20.598(16), namely obtaining the in-situ EC of the 10cm plough layer soil in the flowering period;
substituting the in-situ EC measured value of the soil of 5cm plough layer at the flowering stage obtained in the step two into an EC regression prediction equation (17) as an x value (obtained according to the actual measured values of 320 samples):
Y＝1.444x0 . 765，R20.433(17), namely obtaining the in-situ EC of the soil of a 15cm plough layer in the flowering period;
substituting the in-situ EC measured value of the soil of 5cm plough layer at the flowering stage obtained in the step two into an EC regression prediction equation (18) as an x value (obtained according to the actual measured values of 320 samples):
Y＝0.156x3-1.511x2+5.330x-2.902，R20.336(18), namely obtaining the in-situ EC of 20cm plough layer soil in the flowering period;
and ninthly, substituting the in-situ EC measured value of the soil in the plough layer of 5cm in the milk stage obtained in the step two as the x value into an EC regression prediction equation (19) (obtained according to the measured values of 250 samples):
Y＝-0.095x3+0.893x2-1.759x+3.150，R20.635(19), namely obtaining the in-situ EC of the soil of a 10cm plough layer in the milk stage;
substituting the in-situ EC measured value of soil in the plough layer of 5cm in the milk stage obtained in the step two as an x value into an EC regression prediction equation (20) (obtained according to the measured values of 250 samples):
Y＝-0.068x3+0.636x2-1.263x+3.383，R20.384(20), namely the in-situ EC of the soil of the plough layer of 15cm in the milk stage is obtained;
substituting the in-situ EC measured value of soil in the plough layer of 5cm in the milk stage obtained in the step two as an x value into an EC regression prediction equation (21) (obtained according to the measured values of 250 samples):
Y＝-0.117x3+1.028x2-2.344x+4.725，R2and (3) obtaining the in-situ EC of the soil of the 20cm plough layer in the milk stage when the yield is 0.170 (21).
The following experiments are adopted to verify the effect of the invention:
experiment one:
in 2019, the plough layer soil of the rice green turning period in the soda saline-alkali soil of the national field surgery observation research station of the Jilin Daan farmland ecosystem is predicted.
The method for predicting different plough layers EC of the main growth period of the rice in the soda saline-alkali soil is carried out according to the following steps:
cleaning the surface of a metal probe of a soil in-situ EC meter by using grinding cloth, and correcting the precision of the probe by using standard liquid of the soil in-situ EC meter;
secondly, in the rice green turning period of the soda saline-alkali soil, vertically and clockwise inserting a metal probe of a soil in-situ EC meter into soil of a plough layer of a rice field, stopping inserting the probe into the soil at a depth of 5cm, and enabling the soil to be completely and uniformly contacted with the metal surface of the probe, wherein the response time is 10-20 seconds, the number displayed by an instrument is the measured value of the in-situ EC of the soil of the plough layer of 5cm in the green turning period, and the in-situ EC is 9.10, 8.94 and 9.59 mS/cm;
and thirdly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning period obtained in the step two as an x value into an EC regression prediction equation (1):
Y＝-0.001x3+0.04x2+0.62x+0.681，R2the in-situ EC of the soil of the 10cm plough layer in the green turning period is 8.88, 8.71 and 9.42mS/cm respectively as 0.965 (1);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the green turning period obtained in the step two as an x value into an EC regression prediction equation (2):
Y＝-0.001x3+0.033x2+0.700x+0.748，R2the in-situ EC of the soil of the 15cm plough layer in the green turning period is respectively 9.10, 8.93 and 9.61mS/cm, namely 0.927 (2);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the green turning period obtained in the step two as an x value into an EC regression prediction equation (3):
Y＝-0.001x3+0.005x2+1.052x+0.324，R2and (3), namely the in-situ EC of the soil of the 20cm plough layer in the green turning period is 9.56, 9.41 and 9.99mS/cm respectively.
Further applying regression equation to fit measured values and predicted values of soil in situ EC of plough layer of 10cm, 15cm and 20cm in the green turning period (figure 1-figure 3), wherein the goodness of fit is R respectively2＝0.981，R2＝0.962，R2The equation is 0.952(P is less than 0.0001), which shows that the equation has statistical significance, and the method realizes the prediction of the soil in-situ EC of the plough layer soil of 10cm, 15cm and 20cm in the field green-turning period of the soda saline-alkali soil.
Experiment two:
in 2019, the tilth soil of the rice tillering stage of soda saline-alkali soil of the national field surgery observation and research station of Jilin Daan farmland ecosystem is predicted.
The method for predicting different plough layers EC of the main growth period of the rice in the soda saline-alkali soil is carried out according to the following steps:
cleaning the surface of a metal probe of a soil in-situ EC meter by using grinding cloth, and correcting the precision of the probe by using standard liquid of the soil in-situ EC meter;
secondly, in the tillering stage of the rice in the soda saline-alkali soil, vertically and clockwise inserting a metal probe of a soil in-situ EC meter into the soil of a plough layer of the rice field, stopping inserting the probe into the soil at a depth of 5cm, and enabling the soil to be completely and uniformly contacted with the metal surface of the probe, wherein the response time is 10-20 seconds, the number displayed by an instrument is the measured value of the in-situ EC of the soil of the plough layer of 5cm in the green turning stage, and the in-situ EC is respectively 4.43, 3.53 and 2.66 mS/cm;
and thirdly, substituting the measured value of the soil in-situ EC of the plough layer of 5cm at the tillering stage obtained in the second step into an EC regression prediction equation (4) as an x value:
Y＝3.953E-05x3-0.014x2+1.272x-0.910，R2the in-situ EC of the soil of 10cm plough layer at the tillering stage is 4.45, 3.41 and 2.38mS/cm respectively as 0.992 (4);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the tillering stage obtained in the step two as an x value into an EC regression prediction equation (5):
Y＝0.980x0 . 993，R2the in-situ EC of the soil in the plough layer with the tillering period of 15cm is 4.30, 3.43 and 2.59mS/cm respectively as 0.916 (5);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the tillering stage obtained in the step two as an x value into an EC regression prediction equation (6):
Y＝3.755E-05x3-0.013x2+1.191x-0.159，R2and (6), namely the in-situ EC of the soil in the plough layer with the tillering period of 20cm is 4.87 mS/cm, 3.38 mS/cm and 2.92mS/cm respectively.
Further applying regression equation to fit measured values and predicted values of soil in situ EC of plough layers of 10cm, 15cm and 20cm at tillering stage (figure 4-figure 6), wherein goodness of fit is R respectively2＝0.992，R2＝0.457，R2The equation is 0.989(P is less than 0.0001), which shows that the equation has statistical significance, and the method realizes the prediction of the in-situ EC of the plough layer soil of 10cm, 15cm and 20cm in the tillering stage of the paddy field of the soda saline-alkali soil.
Claims (1)
1. The method for predicting the in-situ EC of the soil in different plough layers in the main growth period of the rice in the soda saline-alkali soil is characterized by comprising the following steps of:
cleaning the surface of a metal probe of a soil in-situ EC meter by using grinding cloth, and correcting the precision of the probe by using standard liquid of the soil in-situ EC meter;
secondly, in the rice green turning stage, tillering stage, jointing stage, booting stage, heading stage, flowering stage and milk stage of soda saline-alkali soil, vertically and clockwise inserting a metal probe of a soil in-situ EC meter into soil of a plough layer of a rice field, stopping inserting the probe into the soil with the depth of 5cm, and enabling the soil to be completely and uniformly contacted with the metal surface of the probe, wherein the response time is 10-20 seconds, and the number displayed by an instrument is the measured value of the in-situ EC of the soil of the plough layer of 5cm in the green turning stage, tillering stage, jointing stage, heading stage, flowering stage and milk stage;
and thirdly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning period obtained in the step two as an x value into an EC regression prediction equation (1):
Y＝-0.001x3+0.04x2+0.62x+0.681，R20.965(1), namely obtaining the soil EC of 10cm plough layer in the green turning period;
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the green turning period obtained in the step two as an x value into an EC regression prediction equation (2):
Y＝-0.001x3+0.033x2+0.700x+0.748，R2obtaining the in-situ EC of the soil of the 15cm plough layer in the green turning period as 0.927 (2);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the green turning period obtained in the step two as an x value into an EC regression prediction equation (3):
Y＝-0.001x3+0.005x2+1.052x+0.324，R2obtaining the in-situ EC of the soil of the 20cm plough layer in the green turning period as 0.914 (3);
and fourthly, substituting the measured value of the in-situ EC of the soil in the plough layer of 5cm at the tillering stage obtained in the second step into an EC regression prediction equation (4) as an x value:
Y＝3.953E-05x3-0.014x2+1.272x-0.910，R2obtaining the in-situ EC of the soil of 10cm plough layer at the tillering stage as 0.992 (4);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the tillering stage obtained in the step two as an x value into an EC regression prediction equation (5):
Y＝0.980x0.993，R2obtaining the in-situ EC of the soil of a plough layer of 15cm at the tillering stage as 0.916 (5);
substituting the EC measured value of the soil in the plough layer of 5cm at the tillering stage obtained in the step two as an x value into an EC regression prediction equation (6):
Y＝3.755E-05x3-0.013x2+1.191x-0.159，R20.979(6), namely obtaining the in-situ EC of the soil of a 20cm plough layer at the tillering stage;
and fifthly, substituting the measured value of the soil in-situ EC of the soil of the 5cm plough layer in the jointing stage obtained in the step two as an x value into an EC regression prediction equation (7):
Y＝0.065x3+0.508x2–0.521x+1.882，R2obtaining the soil in-situ EC of 10cm plough layer in the jointing stage when the yield is 0.488 (7);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the jointing stage obtained in the step two into an EC regression prediction equation (8) as an x value:
Y＝-0.027x3+0.161x2+0.190x+1.916，R2obtaining the soil in-situ EC of 15cm plough layer soil in the jointing stage when the soil is 0.131 (8);
substituting the in-situ EC measured value of the soil of the 5cm plough layer in the jointing stage obtained in the step two into an EC regression prediction equation (9) as an x value:
Y＝0.057x3-0.546x2+2.495x-0.817，R20.031(9), namely getting the soil in-situ EC of 20cm plough layer in jointing stage;
and sixthly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two as an x value into an EC regression prediction equation (10):
Y＝0.005x3-0.135x2+0.853x+2.021，R2obtaining the in-situ EC of the soil of 10cm plough layer in the booting stage as 0.590 (10);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two into an EC regression prediction equation (11) as an x value:
Y＝2.105x0.434，R2obtaining the in-situ EC of the soil in the plough layer of 15cm in the booting stage, namely 0.158 (11);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the booting stage obtained in the step two into an EC regression prediction equation (12) as an x value:
Y＝0.314x3–3.076x2+9.856x-6.375，R20.069(12), namely the in-situ EC of the soil of the 20cm plough layer in the booting stage；
And seventhly, substituting the in-situ EC measured value of the soil in the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (13):
Y＝-0.196x3+1.500x2-2.897x+3.786，R2obtaining the in-situ EC of the soil of 10cm plough layer in the heading stage when the yield is 0.450 (13);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (14):
Y＝-0.353x3+2.287x2-3.978x+4.321，R2obtaining the in-situ EC of the soil in the plough layer of 15cm in the heading stage when the yield is 0.188 (14);
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the heading stage obtained in the step two as an x value into an EC regression prediction equation (15):
Y＝-0.173x3+0.996x2-0.956x+2.611，R2obtaining 20cm plough layer in-situ soil EC in heading period as 0.082 (15);
and eighthly, substituting the in-situ EC measured value of the soil of the 5cm plough layer at the flowering stage obtained in the step two into an EC regression prediction equation (16) as an x value:
Y＝1.350x0.768，R20.598(16), namely obtaining the in-situ EC of the 10cm plough layer soil in the flowering period;
substituting the in-situ EC measured value of the soil of 5cm plough layer of flowering phase obtained in the step two into an EC regression prediction equation (17) as an x value:
Y＝1.444x0.765，R20.433(17), namely obtaining the in-situ EC of the soil of a 15cm plough layer in the flowering period;
substituting the in-situ EC measured value of the soil of 5cm plough layer of the flowering phase obtained in the step two into an EC regression prediction equation (18) as an x value:
Y＝0.156x3-1.511x2+5.330x-2.902，R20.336(18), namely obtaining the in-situ EC of 20cm plough layer soil in the flowering period;
and ninthly, substituting the measured value of the soil in-situ EC of the plough layer of 5cm in the milk stage obtained in the step two as the x value into an EC regression prediction equation (19):
Y＝-0.095x3+0.893x2-1.759x+3.150，R20.635(19), i.e.Obtaining the soil in-situ EC of 10cm plough layer soil in the milk stage;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the milk stage obtained in the step two as an x value into an EC regression prediction equation (20):
Y＝-0.068x3+0.636x2-1.263x+3.383，R20.384(20), namely the in-situ EC of the soil of the plough layer of 15cm in the milk stage is obtained;
substituting the in-situ EC measured value of soil of 5cm plough layer in the milk stage obtained in the step two as an x value into an EC regression prediction equation (21):
Y＝-0.117x3+1.028x2-2.344x+4.725，R2and (3) obtaining the in-situ EC of the soil of the 20cm plough layer in the milk stage when the yield is 0.170 (21).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110701940.3A CN113435640B (en) | 2021-06-24 | 2021-06-24 | Method for predicting in-situ EC (environmental impact) of soils with different plough layers in main growth period of rice in soda saline-alkali soil |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110701940.3A CN113435640B (en) | 2021-06-24 | 2021-06-24 | Method for predicting in-situ EC (environmental impact) of soils with different plough layers in main growth period of rice in soda saline-alkali soil |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113435640A true CN113435640A (en) | 2021-09-24 |
| CN113435640B CN113435640B (en) | 2022-07-26 |
Family
ID=77753769
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110701940.3A Active CN113435640B (en) | 2021-06-24 | 2021-06-24 | Method for predicting in-situ EC (environmental impact) of soils with different plough layers in main growth period of rice in soda saline-alkali soil |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113435640B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201724984U (en) * | 2010-06-13 | 2011-01-26 | 浙江大学 | Device of measuring electrical conductivity of cross section of soil |
| CN106376407A (en) * | 2016-08-31 | 2017-02-08 | 山东胜伟园林科技有限公司 | Energy-saving planting method of paddy rice in saline and alkaline land |
| US20190017984A1 (en) * | 2017-07-14 | 2019-01-17 | SafeNet International LLC | Method of efficient acquisition of soil data using image mapping |
| US20200011845A1 (en) * | 2018-06-18 | 2020-01-09 | Fernando SARRÍA PUEYO | Device for estimating the moisture content and the availability of water in soils |
| CN111011146A (en) * | 2019-11-06 | 2020-04-17 | 青岛农业大学 | Equal-amplitude intercropping alternate crop rotation planting method for peanuts/cotton in saline-alkali soil |
| AU2020102098A4 (en) * | 2020-09-02 | 2020-10-08 | Gautam, Deepesh Kumar MR | Soil salinity degradation estimation by regression algorithm using agricultural internet of things |
| CN111783288A (en) * | 2020-06-19 | 2020-10-16 | 青岛农业大学 | Inversion method for soil salinity of yellow river delta based on Landsat8 |
| CN113299350A (en) * | 2021-05-20 | 2021-08-24 | 中国科学院东北地理与农业生态研究所 | Method for predicting chemical index of soda salt and alkali by using soil pH |
| CN113484384A (en) * | 2021-07-07 | 2021-10-08 | 中国科学院东北地理与农业生态研究所 | Method for predicting in-situ pH values of soils in different plough layers in rice growth period in soda saline-alkali soil |
-
2021
- 2021-06-24 CN CN202110701940.3A patent/CN113435640B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201724984U (en) * | 2010-06-13 | 2011-01-26 | 浙江大学 | Device of measuring electrical conductivity of cross section of soil |
| CN106376407A (en) * | 2016-08-31 | 2017-02-08 | 山东胜伟园林科技有限公司 | Energy-saving planting method of paddy rice in saline and alkaline land |
| US20190017984A1 (en) * | 2017-07-14 | 2019-01-17 | SafeNet International LLC | Method of efficient acquisition of soil data using image mapping |
| US20200011845A1 (en) * | 2018-06-18 | 2020-01-09 | Fernando SARRÍA PUEYO | Device for estimating the moisture content and the availability of water in soils |
| CN111011146A (en) * | 2019-11-06 | 2020-04-17 | 青岛农业大学 | Equal-amplitude intercropping alternate crop rotation planting method for peanuts/cotton in saline-alkali soil |
| CN111783288A (en) * | 2020-06-19 | 2020-10-16 | 青岛农业大学 | Inversion method for soil salinity of yellow river delta based on Landsat8 |
| AU2020102098A4 (en) * | 2020-09-02 | 2020-10-08 | Gautam, Deepesh Kumar MR | Soil salinity degradation estimation by regression algorithm using agricultural internet of things |
| CN113299350A (en) * | 2021-05-20 | 2021-08-24 | 中国科学院东北地理与农业生态研究所 | Method for predicting chemical index of soda salt and alkali by using soil pH |
| CN113484384A (en) * | 2021-07-07 | 2021-10-08 | 中国科学院东北地理与农业生态研究所 | Method for predicting in-situ pH values of soils in different plough layers in rice growth period in soda saline-alkali soil |
Non-Patent Citations (7)
| Title |
|---|
| REN-MIN YANG 等: "Using Sentinel-1 Imagery for Soil Salinity Prediction Under the Condition of Coastal Restoration", 《IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING》 * |
| 张晓光 等: "松嫩平原西部土壤盐碱化特征研究", 《土壤》 * |
| 李诗朦等: "土壤电导率和pH值光谱特征及反演模型――以呼伦贝尔草原干旱半干旱土壤为例", 《测绘科学》 * |
| 胡娟 等: "覆沙对松嫩平原盐碱裸地的改良和利用效果研究", 《中国农学通报》 * |
| 胡小东 等: "干旱区土壤含水率和盐分的空间变异性及其关系研究", 《水资源与水工程学报》 * |
| 马成霞: "绿洲区域表层土壤水盐的时空异质性 ————以渭干河—库车河绿洲为例", 《中国优秀博硕士学位论文全文数据库(硕士)农业科技辑》 * |
| 齐春艳 等: "苏打盐碱胁迫下水稻抽穗期的变化规律及其影响因素的研究", 《农业系统科学与综合研究》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113435640B (en) | 2022-07-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ye et al. | EIS analysis on chloride-induced corrosion behavior of reinforcement steel in simulated carbonated concrete pore solutions | |
| Zhou et al. | Spatial variability of the shallow groundwater level and its chemistry characteristics in the low plain around the Bohai Sea, North China | |
| Balamurugan et al. | Impact of climate and anthropogenic activities on groundwater quality for domestic and irrigation purposes in Attur region, Tamilnadu, India | |
| Vaezi et al. | Spatial variability of soil erodibility factor (K) of the USLE in north west of Iran. | |
| CN106501144A (en) | A kind of tight sand calculation of permeability based on the double cutoffs of nuclear magnetic resonance | |
| Pathak et al. | Measurable biophysical indicators for impact assessment: changes in soil quality | |
| Qian et al. | Derivation of salt content in salinized soil from hyperspectral reflectance data: A case study at Minqin Oasis, Northwest China | |
| CN206223771U (en) | A kind of seawater total alkalinity on-line monitoring system | |
| CN113435640B (en) | Method for predicting in-situ EC (environmental impact) of soils with different plough layers in main growth period of rice in soda saline-alkali soil | |
| Jiang et al. | In-situ, real-time monitoring of nutrient uptake on plant chip integrated with nutrient sensor | |
| CN111158066B (en) | Method for comprehensively monitoring invasion of seawater into sandstone aquifer | |
| Menningen et al. | Ultrasonic tomography: non-destructive evaluation of the weathering state on a marble obelisk, considering the effects of structural properties | |
| CN104345131A (en) | Rice field nitrogen and phosphorus runoff loss load field scale estimation and calculation method | |
| CN103308443B (en) | A kind of accelerated corrosion method of testing of simulated soil corrosion process | |
| Šoić et al. | Gel-Electrolyte EIS setup used for probing of IR Dried/Cured industrial coatings | |
| CN111505041B (en) | Shale oil saturation well site rapid evaluation method | |
| Crawford et al. | Reduced perchlorate in West Antarctica snow during stratospheric ozone hole | |
| Moghaddama et al. | A spatial variation study of groundwater quality parameters in the Gonabad Plain using deterministic and geostatistical models | |
| CN106248468A (en) | A kind of detection method of humic acids from different soils content | |
| CN113484384A (en) | Method for predicting in-situ pH values of soils in different plough layers in rice growth period in soda saline-alkali soil | |
| Zimmerman et al. | Electrical conductivity of agricultural drainage water in Iowa | |
| Nazri et al. | Geophysical and hydrochemical characteristics of groundwater at Kerian irrigation scheme | |
| Rivera-Valentín et al. | Resolving the water cycle on a salty Mars: Planetary science and astrobiology exploration strategies for the next decade | |
| Souffaché et al. | Laboratory study of the electrical properties of Lutetian limestones in the 100 Hz to 10 MHz frequency range | |
| Kim et al. | Application of an in situ bismuth-coated glassy carbon electrode for electroanalytical determination of Cd (II) and Pb (II) in Korean polished rices |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |