CN113435640B - 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 - Google Patents
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 Download PDFInfo
- Publication number
- CN113435640B CN113435640B CN202110701940.3A CN202110701940A CN113435640B CN 113435640 B CN113435640 B CN 113435640B CN 202110701940 A CN202110701940 A CN 202110701940A CN 113435640 B CN113435640 B CN 113435640B
- 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.)
- Active
Links
- 239000002689 soil Substances 0.000 title claims abstract description 281
- 238000011065 in-situ storage Methods 0.000 title claims abstract description 191
- 235000007164 Oryza sativa Nutrition 0.000 title claims abstract description 43
- 235000009566 rice Nutrition 0.000 title claims abstract description 43
- 239000003513 alkali Substances 0.000 title claims abstract description 39
- CDBYLPFSWZWCQE-UHFFFAOYSA-L Sodium Carbonate Chemical compound [Na+].[Na+].[O-]C([O-])=O CDBYLPFSWZWCQE-UHFFFAOYSA-L 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 title claims abstract description 21
- 240000007594 Oryza sativa Species 0.000 title 1
- 230000007613 environmental effect Effects 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 31
- 239000002184 metal Substances 0.000 claims description 17
- 238000004140 cleaning Methods 0.000 claims description 6
- 239000004744 fabric Substances 0.000 claims description 6
- 239000012086 standard solution Substances 0.000 claims description 4
- 238000002474 experimental method Methods 0.000 description 9
- 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
- 238000010586 diagram Methods 0.000 description 1
- 239000012153 distilled water Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012625 in-situ measurement Methods 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 238000002386 leaching Methods 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000005259 measurement 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
- -1 salt ions Chemical class 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- 238000005527 soil sampling Methods 0.000 description 1
- 239000000243 solution 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 land 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 of 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 contains NaHCO 3 With Na 2 CO 3 Mainly has pH more than 8.5, is strong in alkalinity, has the alkalization degree of more than 70 percent, has poor physicochemical properties, large treatment difficulty, long time and slow effect. Practice proves that the development of the rice seed is an effective way for improving and utilizing the soda saline-alkali soil. The soil conductivity (EC) is an index for measuring water-soluble salt of 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, saline-alkali soil plough layer EC determination is mainly carried out by preparing soil leaching liquor after soil sampling and air drying, and with the development of technology, soil in-situ EC is counted as a portable soil salinity determination instrument and is widely applied. Before the in-situ EC meter is used for testing, the surface of a metal probe of the soil in-situ EC meter needs to be cleaned by an abrasive cloth to prevent the measurement precision 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. But due toThe physicochemical property of the soil of the soda saline-alkali soil is poor, the heavily-adhered 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 of different plough layers in 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 the EC of different plough layers in 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 a grinding cloth, and then correcting the precision of the probe by using a standard solution 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 stage obtained in the second step as an x value into an EC regression prediction equation (1):
Y=-0.001x 3 +0.04x 2 +0.62x+0.681,R 2 obtaining 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=-0.001x 3 +0.033x 2 +0.700x+0.748,R 2 obtaining 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 plough layer of 5cm in the green turning stage obtained in the step two as the x value into an EC regression prediction equation (3):
Y=-0.001x 3 +0.005x 2 +1.052x+0.324,R 2 obtaining 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 plough layer soil with the thickness of 5cm at the tillering stage obtained in the second step as an x value into an EC regression prediction equation (4):
Y=3.953E-05x 3 -0.014x 2 +1.272x-0.910,R 2 0.992(4), namely obtaining the in-situ EC of the 10cm plough layer soil in the tillering stage;
substituting the in-situ EC measured value of the plough layer soil with the thickness of 5cm obtained in the tillering stage as an x value into an EC regression prediction equation (5):
Y=0.980x 0 . 993 ,R 2 obtaining 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 measurement value of the plough layer soil EC of 5cm in the tillering stage obtained in the step two as the x value into an EC regression prediction equation (6):
Y=3.755E-05x 3 -0.013x 2 +1.191x-0.159,R 2 0.979(6), namely obtaining the in-situ EC of 20cm plough layer soil in 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=0.065x 3 +0.508x 2 –0.521x+1.882,R 2 0.488(7), namely obtaining the soil in-situ EC of 10cm plough layer soil in the jointing stage;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the jointing stage obtained in the step two as an x value into an EC regression prediction equation (8):
Y=-0.027x 3 +0.161x 2 +0.190x+1.916,R 2 obtaining 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=0.057x 3 -0.546x 2 +2.495x-0.817,R 2 0.031(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=0.005x 3 -0.135x 2 +0.853x+2.021,R 2 obtaining 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):
Y=2.105x 0 . 434 ,R 2 obtaining 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):
Y=0.314x 3 –3.076x 2 +9.856x-6.375,R 2 0.069(12), namely obtaining the soil in-situ EC of 20cm plough layer soil in the booting stage;
and seventhly, 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 (13):
Y=-0.196x 3 +1.500x 2 -2.897x+3.786,R 2 0.450(13), namely obtaining the in-situ EC of the plough layer soil with 10cm in the heading period;
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=-0.353x 3 +2.287x 2 -3.978x+4.321,R 2 obtaining 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=-0.173x 3 +0.996x 2 -0.956x+2.611,R 2 obtaining the in-situ EC of the soil of 20cm plough layer in heading period, namely 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 the x value:
Y=1.350x 0 . 768 ,R 2 0.598(16), namely obtaining the 10cm plough layer soil in-situ EC 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=1.444x 0 . 765 ,R 2 0.433(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 flowering phase obtained in the step two into an EC regression prediction equation (18) as an x value:
Y=0.156x 3 -1.511x 2 +5.330x-2.902,R 2 0.336(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=-0.095x 3 +0.893x 2 -1.759x+3.150,R 2 0.635(19), namely obtaining the in-situ EC of the plough layer soil with 10cm 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=-0.068x 3 +0.636x 2 -1.263x+3.383,R 2 0.384(20), namely obtaining the soil in-situ EC of 15cm plough layer soil in the milk stage;
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=-0.117x 3 +1.028x 2 -2.344x+4.725,R 2 and (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 of 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 diagram of the predicted value and the measured value of the in-situ EC of the plough layer soil of 15cm in the rice green turning period 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 in the plough layer soil of 10cm at the tillering stage of rice in 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 in the plough layer soil of 10cm at the tillering stage of rice in soda saline-alkali soil in experiment II;
FIG. 6 is a graph showing correlation between predicted values and measured values of in-situ EC in plough layer soil at 10cm tillering stage of rice in soda saline-alkali soil in experiment II.
Detailed Description
The technical solution of the present invention is not limited to the embodiments listed below, and includes any combination of the 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 a grinding cloth, and then correcting the precision of the probe by using a standard solution of the soil in-situ EC meter;
secondly, in the rice green turning period, tillering period, heading period, booting period, heading period, flowering period and milk stage of soda saline-alkali soil, vertically and clockwise inserting a metal probe of a soil in-situ EC meter into soil on a plough layer of the rice field, stopping inserting the probe into the soil by 5cm depth to ensure that the soil is 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 on the plough layer of 5cm of the green turning period, tillering period, heading period, flowering period and milk stage;
performing correlation analysis on 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;
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=-0.001x 3 +0.04x 2 +0.62x+0.681,R 2 0.965(1), namely obtaining the in-situ EC of the 10cm plough layer soil in the green turning period;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning stage obtained in the step two as an x value into an EC regression prediction equation (2) (obtained according to measured values of 834 samples):
Y=-0.001x 3 +0.033x 2 +0.700x+0.748,R 2 obtaining 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 plough layer of 5cm in the green turning stage obtained in the step two as the x value into an EC regression prediction equation (3) (obtained according to measured values of 834 samples):
Y=-0.001x 3 +0.005x 2 +1.052x+0.324,R 2 obtaining 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-05x 3 -0.014x 2 +1.272x-0.910,R 2 obtaining 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 plough layer soil of 5cm in the tillering stage obtained in the step two as an x value into an EC regression prediction equation (5) (obtained according to measured values of 1080 samples):
Y=0.980x 0 . 993 ,R 2 0.916(5), i.e. get scoreIn-situ EC of 15cm plough layer soil in a tillering stage;
substituting the 5cm plough layer soil in-situ EC measured value of the tillering stage obtained in the step two into an EC regression prediction equation (6) as an x value (obtained according to 1080 sample measured values):
Y=3.755E-05x 3 -0.013x 2 +1.191x-0.159,R 2 0.979(6), namely obtaining the in-situ EC of 20cm plough layer soil in the tillering stage;
and fifthly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the jointing stage obtained in the step two into an EC regression prediction equation (7) as an x value (obtained according to 460 sample measured values):
Y=0.065x 3 +0.508x 2 –0.521x+1.882,R 2 obtaining 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=-0.027x 3 +0.161x 2 +0.190x+1.916,R 2 0.131(8), namely obtaining the soil in-situ EC of the plough layer of 15cm in the jointing stage;
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=0.057x 3 -0.546x 2 +2.495x-0.817,R 2 0.031(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=0.005x 3 -0.135x 2 +0.853x+2.021,R 2 0.590(10), namely obtaining the soil in-situ EC of 10cm plough layer soil in the booting stage;
and (3) 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 the measured values of 320 samples):
Y=2.105x 0 . 434 ,R 2 =0.158(11),obtaining the soil in-situ EC of 15cm plough layer soil in the booting stage;
and (3) 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 the measured values of 320 samples):
Y=0.314x 3 –3.076x 2 +9.856x-6.375,R 2 obtaining 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=-0.196x 3 +1.500x 2 -2.897x+3.786,R 2 0.450(13), namely obtaining the in-situ EC of the plough layer soil with 10cm in the heading period;
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=-0.353x 3 +2.287x 2 -3.978x+4.321,R 2 obtaining 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=-0.173x 3 +0.996x 2 -0.956x+2.611,R 2 obtaining the in-situ EC of the soil of 20cm plough layer in heading period, namely 0.082 (15);
and eighthly, substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the flowering period obtained in the step two into an EC regression prediction equation (16) as an x value (obtained according to the measured values of 320 samples):
Y=1.350x 0 . 768 ,R 2 0.598(16), namely obtaining the 10cm plough layer soil in-situ EC 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 (17) as an x value (obtained according to the measured values of 320 samples):
Y=1.444x 0 . 765 ,R 2 =0.433(17)obtaining the 15cm plough layer soil in-situ EC 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=0.156x 3 -1.511x 2 +5.330x-2.902,R 2 0.336(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 of the plough layer of 5cm in the milk stage obtained in the step two into an EC regression prediction equation (19) as an x value (obtained according to the measured values of 250 samples):
Y=-0.095x 3 +0.893x 2 -1.759x+3.150,R 2 0.635(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=-0.068x 3 +0.636x 2 -1.263x+3.383,R 2 0.384(20), namely obtaining the soil in-situ EC of 15cm plough layer soil in the milk stage;
and (3) 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 into an EC regression prediction equation (21) (obtained according to the measured values of 250 samples) as an x value:
Y=-0.117x 3 +1.028x 2 -2.344x+4.725,R 2 and (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 a grinding cloth, and then correcting the precision of the probe by using a standard solution 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 stage obtained in the second step as an x value into an EC regression prediction equation (1):
Y=-0.001x 3 +0.04x 2 +0.62x+0.681,R 2 0.965(1), namely the EC of the in-situ soil of 10cm plough layer in the green turning period is 8.88 mS/cm, 8.71 mS/cm and 9.42mS/cm respectively;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning stage obtained in the step two as the x value into an EC regression prediction equation (2):
Y=-0.001x 3 +0.033x 2 +0.700x+0.748,R 2 0.927(2), namely the EC of the soil in situ of the 15cm plough layer at the green turning stage is respectively 9.10, 8.93 and 9.61 mS/cm;
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=-0.001x 3 +0.005x 2 +1.052x+0.324,R 2 and (3) obtaining the in-situ EC of the 20cm plough layer soil in the green turning stage to be 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 respectively 2 =0.981,R 2 =0.962,R 2 The 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 tillered layer soil of the soda saline-alkali soil rice tillering stage of the national field surgery observation and research station of Daan farmland ecosystem of Jilin 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 plough layer soil of the rice field, stopping inserting the probe into the soil for 5cm in depth, and enabling the soil to be in complete and uniform contact 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 in 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 in-situ EC measured value of the plough layer soil with the thickness of 5cm at the tillering stage obtained in the second step as an x value into an EC regression prediction equation (4):
Y=3.953E-05x 3 -0.014x 2 +1.272x-0.910,R 2 the 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 plough layer soil with the thickness of 5cm obtained in the tillering stage as an x value into an EC regression prediction equation (5):
Y=0.980x 0 . 993 ,R 2 0.916(5), namely the in-situ EC of the plough layer soil with 15cm of tillering stage is respectively 4.30, 3.43 and 2.59 mS/cm;
substituting the in-situ EC measured value of the plough layer soil 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-05x 3 -0.013x 2 +1.191x-0.159,R 2 and (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 respectively 2 =0.992,R 2 =0.457,R 2 The 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 a grinding cloth, and then correcting the precision of the probe by using a standard solution 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 stage obtained in the second step as an x value into an EC regression prediction equation (1):
Y=-0.001 x 3 +0.04x 2 + 0.62x +0.681,R 2 =0.965 (1), namely 10cm plough layer soil EC in the green turning period is obtained;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning stage obtained in the step two as the x value into an EC regression prediction equation (2):
Y=-0.001 x 3 +0.033x 2 + 0.700x +0.748,R 2 =0.927 (2), namely obtaining the in-situ EC of the soil of a 15cm plough layer in the green turning period;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the green turning stage obtained in the step two as the x value into an EC regression prediction equation (3):
Y=-0.001 x 3 +0.005x 2 +1.052x +0.324,R 2 =0.914 (3), namely the in-situ EC of the soil of the 20cm plough layer in the green turning period is obtained;
and fourthly, substituting the in-situ EC measured value of the plough layer soil with the thickness of 5cm at the tillering stage obtained in the second step as an x value into an EC regression prediction equation (4):
Y= 3.953E-05 x 3 - 0.014x 2 + 1.272x - 0.910,R 2 =0.992 (4), namely obtaining the in-situ EC of 10cm plough layer soil in a tillering stage;
substituting the in-situ EC measured value of the plough layer soil with the thickness of 5cm obtained in the tillering stage as an x value into an EC regression prediction equation (5):
Y=0.980x 0.993 ,R 2 =0.916 (5), namely the in-situ EC of the soil of a plough layer of 15cm at the tillering stage is obtained;
substituting the EC measured value of the plough layer soil 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-05 x 3 - 0.013x 2 + 1.191x - 0.159,R 2 =0.979 (6), namely the in-situ EC of the soil of 20cm plough layer at the tillering stage is obtained;
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= 0.065 x 3 +0.508x 2 –0.521x +1.882,R 2 =0.488 (7), namely the soil in-situ EC of 10cm plough layer in the jointing stage is obtained;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the jointing stage obtained in the step two as an x value into an EC regression prediction equation (8):
Y= -0.027 x 3 + 0.161x 2 + 0.190x + 1.916,R 2 =0.131 (8), namely the soil in-situ EC of the plough layer of 15cm in the jointing stage is obtained;
substituting the in-situ EC measured value of the soil of the plough layer of 5cm in the jointing stage obtained in the step two as an x value into an EC regression prediction equation (9):
Y= 0.057x 3 -0.546x 2 +2.495x-0.817,R 2 =0.031 (9), namely 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= 0.005 x 3 - 0.135x 2 + 0.853x +2.021,R 2 =0.590 (10), namely the soil in-situ EC of 10cm plough layer soil in the booting stage;
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=2.105x 0.434 ,R 2 =0.158 (11), namely the soil in-situ EC of the plough layer of 15cm at the booting stage;
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= 0.314 x 3 – 3.076x 2 + 9.856x -6.375,R 2 =0.069 (12), namely the soil in-situ EC of 20cm plough layer soil in the booting stage is obtained;
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= -0.196 x 3 +1.500x 2 - 2.897x +3.786,R 2 =0.450 (13), namely the 10cm plough layer soil in-situ EC in heading period is obtained;
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= -0.353x 3 +2.287x 2 - 3.978x +4.321,R 2 =0.188 (14), namely the soil in-situ EC of a plough layer of 15cm in the heading stage;
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= -0.173x 3 +0.996x 2 - 0.956x +2.611,R 2 =0.082 (15), namely obtaining 20cm plough layer in-situ soil EC in heading period;
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=1.350x 0.768 ,R 2 =0.598 (16), namely the 10cm plough layer soil in-situ EC of the flowering period is obtained;
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=1.444x 0.765 ,R 2 =0.433 (17), namely the in-situ EC of the soil in the 15cm plough layer at the flowering period is obtained;
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= 0.156x 3 -1.511x 2 +5.330x -2.902,R 2 =0.336 (18), namely the 20cm plough layer soil in-situ EC of the flowering period is obtained;
and ninthly, 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 the x value into an EC regression prediction equation (19):
Y= -0.095x 3 +0.893x 2 -1.759x +3.150,R 2 =0.635 (19), namely 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= -0.068x 3 +0.636x 2 -1.263x +3.383,R 2 =0.384 (20), namely the soil in-situ EC of 15cm plough layer soil 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= -0.117x 3 +1.028x 2 -2.344x + 4.725,R 2 =0.170 (21), i.e. the soil in situ EC of 20cm plough layer in the milk stage, R in the above equations (1) to (21) 2 Indicating the goodness of fit.
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 CN113435640A (en) | 2021-09-24 |
CN113435640B true 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 (7)
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 |
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 |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10247717B2 (en) * | 2017-07-14 | 2019-04-02 | SafeNet International LLC | Method of efficient acquisition of soil data using image mapping |
ES2735474B2 (en) * | 2018-06-18 | 2020-08-03 | Sarria Pueyo Fernando | Device for estimating moisture content and water availability in soils |
-
2021
- 2021-06-24 CN CN202110701940.3A patent/CN113435640B/en active Active
Patent Citations (7)
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 |
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 |
---|
Using Sentinel-1 Imagery for Soil Salinity Prediction Under the Condition of Coastal Restoration;Ren-Min Yang 等;《IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing》;20190403;第12卷(第5期);1482-1488 * |
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;李诗朦等;《测绘科学》;20180201;第43卷(第08期);14-22+44 * |
干旱区土壤含水率和盐分的空间变异性及其关系研究;胡小东 等;《水资源与水工程学报》;20200815;第31卷(第04期);238-244 * |
松嫩平原西部土壤盐碱化特征研究;张晓光 等;《土壤》;20130415;第45卷(第02期);1332-1338 * |
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;马成霞;《中国优秀博硕士学位论文全文数据库(硕士)农业科技辑》;20160315(第03期);D043-90 * |
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;齐春艳 等;《农业系统科学与综合研究》;20090515;第25卷(第02期);198-203+207 * |
覆沙对松嫩平原盐碱裸地的改良和利用效果研究;胡娟 等;《中国农学通报》;20210325;第37卷(第09期);85-94 * |
Also Published As
Publication number | Publication date |
---|---|
CN113435640A (en) | 2021-09-24 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106501144A (en) | A kind of tight sand calculation of permeability based on the double cutoffs of nuclear magnetic resonance | |
CN102621058A (en) | Simulated accelerated corrosion testing method of ship fastener and protective coating | |
Pathak et al. | Measurable biophysical indicators for impact assessment: changes in soil quality | |
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 | |
CN206223771U (en) | A kind of seawater total alkalinity on-line monitoring system | |
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 | |
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 | |
CN105138761A (en) | Method for estimating surface roughness and soil moisture absorption rate of slope under rainfall conditions | |
CN113299350B (en) | Method for predicting chemical index of soda salt and alkali by using soil pH | |
CN104034652A (en) | Rust-preventive oil/liquid multi-electrode electrochemical anticorrosion performance test method and device | |
CN113484384A (en) | Method for predicting in-situ pH values of soils in different plough layers in rice growth period in soda saline-alkali soil | |
Trudgill et al. | Field and laboratory approaches to limestone weathering | |
Zimmerman et al. | Electrical conductivity of agricultural drainage water in Iowa | |
CN115391739A (en) | Quantitative calculation method and system for crack permeability | |
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 | |
Tanriverdi | Using TDR in the agricultural water management | |
CN109738313A (en) | A kind of method for testing and analyzing of rocky erosion depth and mechanical property degradation | |
KR101242213B1 (en) | Automated test stand for a sensor array consisting of ion-selective electrodes | |
CN105606690A (en) | DGT/LA-ICP-MS based analysis method of sediment void water metal element micro-area distribution | |
Souffaché et al. | Laboratory study of the electrical properties of Lutetian limestones in the 100 Hz to 10 MHz frequency range | |
Ren et al. | Quantitative Research on the Relationship between Salinity and Crack Length of Soda Saline-Alkali Soil. | |
Dafter et al. | Prediction of long-term corrosion in soils using electrochemical tests | |
Santoyo et al. | Capillary electrophoretic analysis of inorganic anions in atmospheric hailstone samples |
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 |