CN111781163B - Method for eliminating influence of soil granularity on soil parameter detection of discrete near-infrared band - Google Patents
Method for eliminating influence of soil granularity on soil parameter detection of discrete near-infrared band Download PDFInfo
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- 239000002689 soil Substances 0.000 title claims abstract description 470
- 238000001514 detection method Methods 0.000 title claims abstract description 73
- 238000000034 method Methods 0.000 title claims abstract description 43
- 238000002835 absorbance Methods 0.000 claims abstract description 179
- 238000012937 correction Methods 0.000 claims abstract description 62
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 48
- 235000019580 granularity Nutrition 0.000 claims description 123
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims description 92
- 239000002245 particle Substances 0.000 claims description 57
- 229910052757 nitrogen Inorganic materials 0.000 claims description 46
- 238000013145 classification model Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 10
- 238000012512 characterization method Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 13
- 238000001228 spectrum Methods 0.000 description 5
- 238000012706 support-vector machine Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000001035 drying Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 3
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- ZOXJGFHDIHLPTG-UHFFFAOYSA-N Boron Chemical compound [B] ZOXJGFHDIHLPTG-UHFFFAOYSA-N 0.000 description 1
- 238000004497 NIR spectroscopy Methods 0.000 description 1
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 1
- XSQUKJJJFZCRTK-UHFFFAOYSA-N Urea Chemical compound NC(N)=O XSQUKJJJFZCRTK-UHFFFAOYSA-N 0.000 description 1
- 229910021529 ammonia Inorganic materials 0.000 description 1
- 229910052796 boron Inorganic materials 0.000 description 1
- 239000004202 carbamide Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000004720 fertilization Effects 0.000 description 1
- 239000003041 laboratory chemical Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000005416 organic matter Substances 0.000 description 1
- 229910052698 phosphorus Inorganic materials 0.000 description 1
- 239000011574 phosphorus Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000007873 sieving Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N2021/3129—Determining multicomponents by multiwavelength light
Abstract
The embodiment of the invention provides a method for eliminating the influence of soil granularity on the detection of soil parameters in a discrete near-infrared band, wherein the method comprises the following steps: determining the original absorbance of the soil to be detected in a plurality of detection wave bands under near infrared spectrum scanning; determining a granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band; the characteristic wave band is determined based on the original absorbance of samples of a plurality of preset wave bands of soil samples under a plurality of soil granularity under near infrared spectrum scanning; and correcting the original absorbance of each detection wave band of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determining the soil parameters of the soil to be detected based on the correction result. The method provided by the embodiment of the invention reduces the interference of the soil granularity on the discrete near infrared band, and improves the soil parameter detection precision.
Description
Technical Field
The invention relates to the technical field of spectrum detection, in particular to a method for eliminating the influence of soil granularity on the detection of soil parameters in a discrete near-infrared band.
Background
The soil parameters are detected based on the discrete near-infrared band, so that the detection cost can be effectively reduced, and the established soil parameter prediction model obtains a better prediction result. However, soil parameter detection based on discrete near infrared bands faces serious interference caused by soil granularity.
In the prior art, the soil is usually ground and sieved to eliminate the interference of the soil granularity, but the method is time-consuming and labor-consuming and cannot be applied to the elimination of the interference of the soil granularity when the discrete near-infrared band is used for online soil detection. In addition, the differential method and the like commonly used for the continuous near infrared spectrum are not suitable for the discrete near infrared band.
Disclosure of Invention
The embodiment of the invention provides a method for eliminating the influence of soil granularity on the detection of soil parameters by discrete near-infrared bands, which is used for solving the problems of serious interference caused by the soil granularity and poor soil parameter detection precision when the soil parameter detection is carried out based on the discrete near-infrared bands in the prior art.
In a first aspect, an embodiment of the present invention provides a method for eliminating an influence of a soil granularity on a discrete near-infrared band detection soil parameter, including:
determining the original absorbance of the soil to be detected in a plurality of detection wave bands under near infrared spectrum scanning;
determining a granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band; the characteristic wave band is determined based on the original absorbance of samples of a plurality of preset wave bands of soil samples under a plurality of soil granularity under near infrared spectrum scanning;
and correcting the original absorbance of each detection wave band of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determining the soil parameters of the soil to be detected based on the correction result.
Optionally, the determining a particle size correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band includes:
determining an absorbance ratio for representing the soil granularity of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band;
and determining the granularity correction coefficient of the soil to be detected based on the absorbance ratio of the soil to be detected and the absorbance ratio of the granularity of the reference soil.
Optionally, the absorbance ratio of the reference soil particle size is determined based on the original absorbance of the sample in the characteristic band of the soil sample under the near infrared spectrum scan.
Optionally, the characteristic band is obtained based on the following method:
performing near infrared spectrum scanning on the soil samples under the multiple soil granularities, and determining the original absorbance of the samples of multiple preset wave bands of the soil samples;
determining a standard deviation value and a comprehensive standard deviation value of each soil sample under each soil granularity based on the original absorbance of the sample of each soil sample at a plurality of preset wave bands;
and determining the characteristic wave band based on the standard deviation value of the soil sample under each soil granularity and the comprehensive standard deviation value.
Optionally, the determining the characteristic waveband based on the standard deviation value of the soil sample at each soil granularity and the comprehensive standard deviation value further comprises:
determining a sample absorbance ratio of the soil sample based on the original sample absorbance of the characteristic wave band of the soil sample;
and establishing a soil granularity classification model based on the sample absorbance ratio and the soil granularity of the soil sample so as to verify the characterization capability of the sample absorbance ratio on the soil granularity.
Optionally, the characteristic wavelength bands are 1361nm and 1870 nm.
Optionally, the soil sample comprises 4 particle size grades of 0.2mm, 0.45mm, 0.9mm and 2.0mm and 6 total nitrogen concentration gradients of 0g/kg, 0.04g/kg, 0.08g/kg, 0.12g/kg, 0.16g/kg and 0.2 g/kg.
In a second aspect, an embodiment of the present invention provides an apparatus for eliminating an influence of soil granularity on a soil parameter detected in a discrete near-infrared band, including:
the absorbance determining unit is used for determining the original absorbance of the soil to be detected in a plurality of detection wave bands under the near infrared spectrum scanning;
the coefficient determining unit is used for determining the granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band; the characteristic wave band is determined based on the original absorbance of samples of a plurality of preset wave bands of soil samples under a plurality of soil granularity under near infrared spectrum scanning;
and the correction detection unit is used for correcting the original absorbance of each detection waveband of the soil to be detected based on the granularity correction coefficient of the soil to be detected and determining the soil parameters of the soil to be detected based on the correction result.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method for eliminating the influence of the soil granularity on the soil parameter detected by the discrete near infrared band according to the first aspect.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for eliminating the influence of the soil granularity on the soil parameter detected by the discrete near-infrared band according to the first aspect.
According to the method for eliminating the influence of the soil granularity on the discrete near-infrared band detection soil parameters, the granularity correction coefficient of the soil to be detected is determined according to the original absorbance of the soil to be detected in the characteristic band under the near-infrared spectrum scanning, the original absorbance of a plurality of detection bands is corrected, the soil parameters of the soil to be detected are determined based on the correction result, the interference of the soil granularity on the discrete near-infrared band is reduced, and the soil parameter detection precision is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for eliminating the influence of soil granularity on soil parameter detection in a discrete near-infrared band according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for detecting total nitrogen concentration in soil according to an embodiment of the present invention;
FIG. 3 is a graph illustrating standard deviation values versus predetermined bands according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a classification result of a soil particle size classification model according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of the original absorbance of a soil total nitrogen concentration detection sample provided in an embodiment of the present invention;
FIG. 6 is a schematic view of a sample corrected absorbance for detecting total nitrogen concentration in soil according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating a soil total nitrogen concentration prediction result based on original absorbance according to an embodiment of the present invention;
FIG. 8 is a schematic diagram illustrating the prediction result of total nitrogen concentration in soil based on corrected absorbance according to an embodiment of the present invention;
FIG. 9 is a schematic diagram illustrating a prediction result of total nitrogen concentration in soil based on reference absorbance according to an embodiment of the present invention;
FIG. 10 is a schematic structural diagram of an apparatus for eliminating the influence of soil granularity on soil parameter detection in a discrete near-infrared band according to an embodiment of the present invention;
fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In recent years, it is becoming more urgent to accurately provide a farmland soil parameter detection value in real time in accordance with the demand for variable rate fertilization work, intelligent farmland management and sustainable agricultural development. The traditional laboratory chemical method for detecting soil parameters is time-consuming, high in cost and environment-polluting. The rapid and nondestructive detection of soil parameters by adopting a spectrum technology is a better choice in cost performance, however, most of spectrometers used in laboratories and early developed soil parameter detectors based on the spectrum technology adopt spectrometers as elements to detect the soil parameters, and the spectrometers are expensive and are not suitable for the severe environment of farmlands. The soil parameter detector developed based on the discrete near-infrared band detects the soil parameters, which becomes a current research hotspot, however, the method faces serious interference caused by soil granularity.
In order to overcome the defects in the prior art, fig. 1 is a schematic flow chart of a method for eliminating the influence of soil granularity on soil parameter detection in a discrete near-infrared band, which is provided by an embodiment of the present invention, and as shown in fig. 1, the method includes:
specifically, factors influencing the farmland soil environment quality are detected, and the farmland environment quality and the change trend thereof can be determined. Soil detection parameters may include total nitrogen, total phosphorus, organic matter, available boron, and the like. In the embodiments of the present invention, the soil detection parameters are not particularly limited, and the following description will take the soil total nitrogen concentration detection as an example.
When the soil to be detected is scanned, a vehicle-mounted soil total nitrogen detector based on a discrete near infrared wave band can be selected. And scanning the soil to be detected by using the near infrared spectrums of the plurality of detection bands to obtain the original absorbance of the soil to be detected under the near infrared spectrum scanning of each detection band.
The plurality of detection bands of the near infrared spectrum scanning can be selected according to actual measurement requirements.
For example, the detection band of near infrared spectrum for detecting the total nitrogen concentration of the soil to be detected can be selected from 1070nm, 1130nm, 1245nm, 1375nm, 1550nm and 1680 nm.
specifically, when the soil to be detected is scanned by using the near infrared spectrum, the soil granularity interferes the original absorbance obtained by scanning to a certain extent. The particle size correction coefficient is a coefficient for correcting the original absorbance obtained by near infrared spectrum scanning in order to eliminate the measurement deviation caused by soil particle size interference as much as possible.
The characteristic wave band is a wave band capable of reflecting the soil granularity through corresponding original absorbance in a plurality of wave bands. The characteristic wave band is determined based on original absorbance of samples of a plurality of preset wave bands of soil samples under a plurality of soil granularity under near infrared spectrum scanning, and the original absorbance of the samples of the characteristic wave band is the original absorbance obtained when the soil samples under the plurality of soil granularity are scanned through the near infrared spectrum. The number of the characteristic bands is not particularly limited in the embodiments of the present invention, and preferably, two characteristic bands may be selected.
Determining the particle size correction coefficient of the soil to be detected according to the original absorbance of the characteristic waveband, for example, determining the particle size correction coefficient of the soil to be detected according to the average value of the original absorbance of the characteristic waveband 1361nm and 1870nm, or determining the particle size correction coefficient of the soil to be detected according to the difference value between the original absorbance of the characteristic waveband 1361nm and 1870nm and the original absorbance of other wavebands.
And step 130, correcting the original absorbance of each detection wave band of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determining the soil parameters of the soil to be detected based on the correction result.
Specifically, according to the particle size correction coefficient of the soil to be detected, the original absorbance of each detection wave band of the soil to be detected is corrected to obtain a correction result, namely the correction absorbance of each detection wave band of the soil to be detected, and the soil parameters of the soil to be detected are determined based on the correction result.
For example, a particle size correction coefficient P of the soil to be detected is determined according to original absorbances of characteristic bands of 1361nm and 1870nm, the original absorbances of the bands of 1070nm, 1130nm, 1245nm, 1375nm, 1550nm and 1680nm are respectively corrected by using the particle size correction coefficient P to obtain the corrected absorbances of each detection band, a soil total nitrogen prediction model is established by using a BP neural network, and the corrected absorbances of each detection band are used as parameters to be input into the prediction model to predict the soil total nitrogen concentration.
According to the method for eliminating the influence of the soil granularity on the discrete near-infrared band detection soil parameters, the granularity correction coefficient of the soil to be detected is determined according to the original absorbance of the soil to be detected in the characteristic band under the near-infrared spectrum scanning, the original absorbance of a plurality of detection bands is corrected, the soil parameters of the soil to be detected are determined based on the correction result, the interference of the soil granularity on the discrete near-infrared band is reduced, and the soil parameter detection precision is improved.
Based on the above embodiment, step 120 includes:
determining an absorbance ratio for representing the soil granularity of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band;
and determining the particle size correction coefficient of the soil to be detected based on the absorbance ratio of the soil to be detected and the absorbance ratio of the reference soil particle size.
Specifically, the original absorbances of characteristic bands of 1361nm and 1870nm are A1361And A1870Determining an absorbance ratio R representing the soil granularity of the soil to be detected, and expressing the absorbance ratio R as follows by using a formula:
the absorbance ratio of the reference soil particle size is
The particle size correction factor P of the soil to be detected can be determined and is expressed by the formula:
based on any of the above embodiments, the absorbance ratio of the reference soil particle size is determined based on the original absorbance of the sample in the characteristic band of the soil sample under the near infrared spectrum scan of the reference soil particle size.
Specifically, soil having a soil particle size of 0.2mm may be selected as the reference soil. And (3) using a plurality of soil samples with the soil granularity of 0.2mm, and obtaining the original absorbance of the samples under the near infrared spectrum scanning of the characteristic wave band for each soil sample, and further obtaining the absorbance ratio of the soil sample. And taking the average value of the absorbance ratios of the plurality of soil samples as the absorbance ratio of the reference soil granularity.
Based on any of the above embodiments, the characteristic band is obtained based on the following method:
performing near infrared spectrum scanning on soil samples under multiple soil granularities, and determining the original absorbance of the samples of multiple preset wave bands of the soil samples;
determining a standard deviation value of the soil sample under each soil granularity and a comprehensive standard deviation value based on the original absorbance of the sample of each soil sample at a plurality of preset wave bands;
and determining the characteristic wave band based on the standard deviation value of the soil sample under each soil granularity and the comprehensive standard deviation value.
Specifically, near infrared spectrum scanning is carried out on soil samples under multiple soil granularities, and the original absorbance of the samples of multiple preset wave bands of the soil samples is determined. The near infrared spectrum is in the region of 780nm to 2526nm, as defined by the American Society for Testing and Materials (ASTM) for the near infrared spectrum. In the embodiment of the invention, the preset wave band is a wave band within 850nm-2500nm of a near infrared spectrum. Each preset waveband is an equally-spaced waveband, and the starting point and the end point of each waveband are sequentially connected, so that the maximum coverage of the near infrared spectrum range is realized.
And determining a standard deviation value of the soil sample under each soil granularity and a comprehensive standard deviation value according to the original absorbance of the soil sample at a plurality of preset wave bands. The comprehensive standard deviation value is the integral standard deviation value of the soil sample.
Here, the standard deviation value of the soil sample at any soil particle size j
This can be obtained by the following formula:
wherein i is the serial number of a preset waveband, j is the serial number of a soil granularity grade, N is the number of soil samples under any soil granularity, W is the serial number of the soil samples under any soil granularity, W is 1,2,3 … N,
the original absorbance of a soil sample with the soil granularity level j under the near infrared spectrum scanning with the preset wave band i,
the method is the average value of original absorbance of N soil samples with soil granularity level j under near infrared spectrum scanning with a preset wave band i.
And determining the characteristic wave band according to the standard deviation value of the soil sample under each soil granularity and the comprehensive standard deviation value. For example, the characteristic wave band can be determined by plotting the standard deviation value of the soil sample at each soil particle size against the preset wave band and integrating the standard deviation value against the preset wave band.
Based on any one of the above embodiments, determining the characteristic waveband based on the standard deviation value of the soil sample at each soil granularity and the comprehensive standard deviation value, and then further comprising:
determining the sample absorbance ratio of the soil sample based on the original sample absorbance of the characteristic wave band of the soil sample;
and establishing a soil granularity classification model based on the sample absorbance ratio and the soil granularity of the soil sample so as to verify the characterization capability of the sample absorbance ratio on the soil granularity.
Specifically, the sample absorbance ratio of the soil sample is determined according to the original sample absorbance of the characteristic wave band of the soil sample.
In order to verify the characterization capability of the absorbance ratio of the sample on the soil granularity, a soil granularity classification model is established, the absorbance ratio of the sample of the soil sample is used as an input variable, a soil granularity classification result is obtained, and the soil granularity classification result is compared with the soil granularity of the soil sample. The soil particle size classification model can be established based on an SVM (Support Vector Machine) model, and the selection of the soil particle size classification model is not specifically limited in the embodiment of the invention.
Based on any of the above embodiments, the characteristic wavelength bands are 1361nm and 1870 nm.
Specifically, soil samples of different soil particle sizes were scanned using near infrared spectroscopy in the range 850nm to 2500nm and analyzed using the methods described in the above examples to obtain characteristic bands of 1361nm and 1870 nm.
Based on any of the above examples, the soil sample included 4 particle size grades of 0.2mm, 0.45mm, 0.9mm and 2.0mm and 6 total nitrogen concentration gradients of 0g/kg, 0.04g/kg, 0.08g/kg, 0.12g/kg, 0.16g/kg and 0.2 g/kg.
The above method is illustrated by an example of soil total nitrogen concentration detection. Fig. 2 is a schematic flow chart of a method for detecting total nitrogen concentration in soil according to an embodiment of the present invention, and as shown in fig. 2, the detailed execution steps of the process for detecting total nitrogen concentration in soil are as follows:
firstly, drying the sampled standard soil (the total nitrogen concentration is 0g/kg), wherein the drying temperature is 85 ℃, and the drying time is 24 hours. The dried soil samples were divided into 6 groups of 4 each. Soil samples were prepared using an ammoniacal solution made of urea, the ammoniacal solution concentration being graded from 1 to 6. The ammonia content of grade 1 is 0g/kg, the nitrogen content of grade 2 is 0.04g/kg, the nitrogen content of grade 3 is 0.08g/kg, the nitrogen content of grade 4 is 0.12g/kg, the nitrogen content of grade 5 is 0.16g/kg, and the nitrogen content of grade 6 is 0.2 g/kg.
When the soil sample is configured, the average soil moisture content (7%) of the actual farmland plough layer in summer can be simulated, and the soil sample is configured.
And after the soil is prepared, drying, and sieving all soil samples by using a 10-mesh sieve (2.0mm), a 20-mesh sieve (0.9mm), a 40-mesh sieve (0.45mm) and an 80-mesh sieve (0.2mm) respectively. And finally obtaining 4 groups of soil samples with different particle sizes, wherein each group comprises 6 total nitrogen concentration grades, and each total nitrogen concentration grade comprises 4 soil samples. In total 96 soil samples were obtained at different particle sizes and total nitrogen concentrations. Table 1 shows the data obtained after statistical analysis of the soil samples.
TABLE 1 statistical analysis of soil samples
Secondly, carrying out near infrared spectrum scanning on 96 soil samples with 4 soil granularity gradients and 6 total nitrogen concentration grades to obtain the original absorbance value of the sample within the waveband range of 850nm to 2500nm
Wherein i is a preset wave band serial numberAnd the interval of the wave bands is 3nm, i is 850,853,856 … and 2500. And m is the serial number of the soil sample, and m is 1,2,3 … and 96.
Thirdly, independently calculating standard deviation values of soil samples under 4 soil granularities
And calculating the comprehensive standard deviation value of all 96 soil samples
j is a soil size grade number, j 1 is all 24 soil samples at 0.2mm, j 2 is all 24 soil samples at 0.45mm, j 3 is all 24 soil samples at 0.9mm, and j 4 is all 24 soil samples at 2.0 mm.
Fig. 3 is a graph showing a relationship between the standard deviation value and the preset waveband provided in the embodiment of the present invention, and as shown in fig. 3, there are 5 curves, which are a relationship between the standard deviation value of a Soil sample under 4 Soil particle sizes (Soil particle sizes) and the preset waveband, and a relationship between the comprehensive standard deviation value and the preset waveband, and the characteristic wavebands of the Soil particle sizes are 1361nm and 1870 nm.
Fourthly, determining the absorbance ratio R of the samples of the soil samples according to the original absorbance of the samples of the soil samples in the characteristic wave bands of 1361nm and 1870nmmIs formulated as:
in the formula, m is the serial number of the soil sample,
the original absorbance of the soil sample at a characteristic wave band of 1870nm is obtained,
the original absorbance of the soil sample at the characteristic wave band of 1361nm is obtained.
The fifth step, based on SVM (Support Vector Machine,support vector machine) to establish a soil granularity classification model and determine the absorbance ratio R of the samplemVerifying the ratio R as a single input variablemAccuracy of soil size classification.
Fig. 4 is a schematic diagram of classification results of the soil particle size classification model according to the embodiment of the present invention, and as shown in fig. 4, a Predicted soil particle size (Predicted soil particle size) obtained by the soil particle size classification model is compared with an actual soil particle size (Measured soil particle size), and a sample absorbance ratio R is obtainedmThe classification of soil particle size can be well characterized. The soil granularity classification accuracy is counted, as shown in table 2:
TABLE 2 soil size Classification accuracy statistics
| Serial number | Classification of soil size | Accuracy of classification |
| 1 | 0.20mm | 100％ |
| 2 | 0.45mm | 83.3％ |
| 3 | 0.90mm | 91.7％ |
| 4 | 2.00mm | 100％ |
Therefore, the absorbance ratio R of the sample is determined according to the original absorbance of the soil sample in the sample with the characteristic wave band of 1361nm and 1870nmmThe accuracy of the classification of the soil granularity is 93.8 percent, and the requirement of practical application is met.
Sixthly, determining a granularity correction coefficient P of the soil sample based on the original absorbance of the characteristic wave bandmThe formula can be expressed as:
in the formula, m is the serial number of the soil sample,
the original absorbance of the soil sample at a characteristic wave band of 1870nm is obtained,
the original absorbance of the soil sample at 1361nm of the characteristic wave band is obtained,
the average value of the absorbance ratio of soil samples at 1870nm and 1361nm under the soil granularity of 0.2mm is used.
The seventh step, using the granularity correction factor PmOriginal absorbance value of soil sample
Correcting to obtain corrected soil absorbance value
Can be expressed by the formula:
in the formula, i is a serial number of a preset waveband, and m is a serial number of a soil sample.
FIG. 5 is a graph showing the Original absorbance of Soil total nitrogen concentration test samples provided by the embodiment of the present invention, and as shown in FIG. 5, five curves of a single Soil sample at a Soil total nitrogen concentration of 0.068g/kg at 6 discrete near infrared bands (1070nm, 1130nm, 1245nm, 1375nm, 1550nm and 1680nm) are respectively the Original absorbance (Original spectrum) of the Soil sample, and the Original absorbance of the Soil sample at a Soil particle size (Soil particle size) of 2.0mm, 0.9mm, 0.45mm and 0.2 mm.
FIG. 6 is a graph showing corrected absorbance of Soil total nitrogen concentration test samples according to an embodiment of the present invention, and as shown in FIG. 6, five curves of a single Soil sample at a Soil total nitrogen concentration of 0.068g/kg at 6 discrete near infrared bands (1070nm, 1130nm, 1245nm, 1375nm, 1550nm and 1680nm) are respectively the absorbance of the Original Soil sample (Original spectrum), and the absorbance of the Soil sample at a Soil particle size (Soil particle size) of 2.0mm, 0.9mm, 0.45mm and 0.2 mm.
And eighthly, scanning the soil to be detected by using a vehicle-mounted soil total nitrogen detector based on discrete near-infrared wave bands and selecting near-infrared spectrums with wave bands of 1070nm, 1130nm, 1245nm, 1375nm, 1550nm and 1680nm to obtain the original absorbance of the soil to be detected.
According to the method in the first step to the seventh step, the particle size correction coefficient of the soil to be detected is determined by using the original absorbance of characteristic wave bands of 1361nm and 1870nm, and the original absorbance of the soil to be detected is corrected to obtain the corrected absorbance of the soil to be detected.
In addition, for comparison, the absorbance of the soil to be detected at a soil particle size of 0.2mm was taken as the reference absorbance.
Establishing a soil total nitrogen concentration prediction model by using a BP neural network, and respectively inputting the original absorbance, the corrected absorbance and the reference absorbance of the soil to be detected into the soil total nitrogen concentration prediction model to obtain respective total nitrogen concentration prediction results, as shown in Table 3:
TABLE 3 model accuracy statistics based on different soil absorbances
Fig. 7 is a schematic diagram of a prediction result of total nitrogen concentration of soil based on original absorbance according to an embodiment of the present invention, fig. 8 is a schematic diagram of a prediction result of total nitrogen concentration of soil based on corrected absorbance according to an embodiment of the present invention, and fig. 9 is a schematic diagram of a prediction result of total nitrogen concentration of soil based on reference absorbance according to an embodiment of the present invention, as shown in fig. 7, 8 and 9, compared with the prediction result of total nitrogen concentration of soil based on reference absorbance (fig. 9), the prediction result of total nitrogen concentration of soil based on original absorbance (fig. 7) has a larger error, and the prediction result of total nitrogen concentration of soil based on corrected absorbance (fig. 8) is closer to an actual situation, so that interference of soil granularity on a discrete near-infrared band is reduced, and soil parameter detection accuracy is improved.
In fig. 7, 8 and 9, the measured value of total nitrogen in soil is obtained by measuring soil to be detected by using a kjeldahl nitrogen meter.
Based on any of the above embodiments, fig. 10 is a schematic structural diagram of an apparatus for eliminating an influence of soil granularity on soil parameter detection in a discrete near-infrared band according to an embodiment of the present invention, as shown in fig. 10, the apparatus includes:
an absorbance determination unit 1010, configured to determine original absorbance of the soil to be detected in multiple detection bands under near infrared spectrum scanning;
a coefficient determining unit 1020, configured to determine a particle size correction coefficient of the soil to be detected based on an original absorbance of the soil to be detected in the characteristic waveband; the characteristic wave band is determined based on the original absorbance of samples of a plurality of preset wave bands of soil samples under the near infrared spectrum scanning of a plurality of soil granularities;
and the correction detection unit 1030 is configured to correct the original absorbance of each detection waveband of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determine the soil parameter of the soil to be detected based on the correction result.
Specifically, the absorbance determination unit 1010 is configured to determine original absorbance of the soil to be detected in a plurality of detection bands under near infrared spectrum scanning. And a coefficient determining unit 1020, configured to determine a particle size correction coefficient of the soil to be detected based on an original absorbance of the soil to be detected in the characteristic waveband. And the correction detection unit 1030 is configured to correct the original absorbance of each detection waveband of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determine the soil parameter of the soil to be detected based on the correction result.
According to the device for eliminating the influence of the soil granularity on the discrete near-infrared band detection soil parameters, the granularity correction coefficient of the soil to be detected is determined according to the original absorbance of the soil to be detected in the characteristic band under the near-infrared spectrum scanning, the original absorbance of a plurality of detection bands is corrected, the soil parameters of the soil to be detected are determined based on the correction result, the interference of the soil granularity on the discrete near-infrared band is reduced, and the soil parameter detection precision is improved.
Based on any of the above embodiments, the coefficient determination unit 1020 includes:
the ratio determining subunit is used for determining an absorbance ratio for representing the soil granularity of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band;
and the coefficient determining subunit is used for determining the granularity correction coefficient of the soil to be detected based on the absorbance ratio of the soil to be detected and the absorbance ratio of the granularity of the reference soil.
Based on any of the above embodiments, the absorbance ratio of the reference soil particle size is determined based on the original absorbance of the sample in the characteristic band of the soil sample under the near infrared spectrum scan of the reference soil particle size.
Based on any of the above embodiments, the characteristic band is obtained based on the following method:
performing near infrared spectrum scanning on soil samples under multiple soil granularities, and determining the original absorbance of the samples of multiple preset wave bands of the soil samples;
determining a standard deviation value of the soil sample under each soil granularity and a comprehensive standard deviation value based on the original absorbance of the sample of each soil sample at a plurality of preset wave bands;
and determining the characteristic wave band based on the standard deviation value of the soil sample under each soil granularity and the comprehensive standard deviation value.
Based on any one of the above embodiments, determining the characteristic waveband based on the standard deviation value of the soil sample at each soil granularity and the comprehensive standard deviation value, and then further comprising:
determining the sample absorbance ratio of the soil sample based on the original sample absorbance of the characteristic wave band of the soil sample;
and establishing a soil granularity classification model based on the sample absorbance ratio and the soil granularity of the soil sample so as to verify the characterization capability of the sample absorbance ratio on the soil granularity.
Based on any of the above embodiments, the characteristic wavelength bands are 1361nm and 1870 nm.
Based on any of the above examples, the soil sample included 4 particle size grades of 0.2mm, 0.45mm, 0.9mm and 2.0mm and 6 total nitrogen concentration gradients of 0g/kg, 0.04g/kg, 0.08g/kg, 0.12g/kg, 0.16g/kg and 0.2 g/kg.
Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 11, the electronic device may include: a Processor (Processor)1110, a communication Interface 1120, a Memory 1130, and a communication Bus 1140. The processor 1110, the communication interface 1120 and the memory 1130 communicate with each other via a communication bus 1140. Processor 1110 may call logical commands in memory 1130 to perform the following method:
determining the original absorbance of the soil to be detected in a plurality of detection wave bands under near infrared spectrum scanning; determining a granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band; the characteristic wave band is determined based on the original absorbance of samples of a plurality of preset wave bands of soil samples under the near infrared spectrum scanning of a plurality of soil granularities; and correcting the original absorbance of each detection wave band of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determining the soil parameters of the soil to be detected based on the correction result.
In addition, the logic commands in the memory 1130 may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of commands for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Embodiments of the present invention further provide a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the method provided in the foregoing embodiments when executed by a processor, and the method includes:
determining the original absorbance of the soil to be detected in a plurality of detection wave bands under near infrared spectrum scanning; determining a granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band; the characteristic wave band is determined based on the original absorbance of samples of a plurality of preset wave bands of soil samples under the near infrared spectrum scanning of a plurality of soil granularities; and correcting the original absorbance of each detection wave band of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determining the soil parameters of the soil to be detected based on the correction result.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes commands for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A method for eliminating the influence of soil granularity on the detection of soil parameters in a discrete near-infrared band is characterized by comprising the following steps:
determining the original absorbance of the soil to be detected in a plurality of detection wave bands under near infrared spectrum scanning;
determining a granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band;
correcting the original absorbance of each detection wave band of the soil to be detected based on the granularity correction coefficient of the soil to be detected, and determining the soil parameters of the soil to be detected based on the correction result; and determining the granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band, wherein the determining comprises the following steps:
determining an absorbance ratio for representing the soil granularity of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band;
determining a granularity correction coefficient of the soil to be detected based on the absorbance ratio of the soil to be detected and the absorbance ratio of the granularity of the reference soil;
the characteristic wave band is obtained based on the following method:
performing near infrared spectrum scanning on the soil samples under the multiple soil granularities, and determining the original absorbance of the samples of multiple preset wave bands of the soil samples;
determining a standard deviation value and a comprehensive standard deviation value of each soil sample under each soil granularity based on the original absorbance of the sample of each soil sample at a plurality of preset wave bands;
and determining the characteristic wave band based on the standard deviation value of the soil sample under each soil granularity and the comprehensive standard deviation value.
2. The method according to claim 1, wherein the absorbance ratio of the reference soil particle size is determined based on the original absorbance of the soil sample at the reference soil particle size in the characteristic wavelength band under the near infrared spectrum scan.
3. The method for eliminating influence of soil granularity on soil parameter detection of discrete near infrared band according to claim 1, wherein the determining the characteristic band based on the standard deviation value of the soil sample at each soil granularity and the comprehensive standard deviation value further comprises:
determining a sample absorbance ratio of the soil sample based on the original sample absorbance of the characteristic wave band of the soil sample;
and establishing a soil granularity classification model based on the sample absorbance ratio and the soil granularity of the soil sample so as to verify the characterization capability of the sample absorbance ratio on the soil granularity.
4. The method for eliminating influence of soil particle size on soil parameter detection in a discrete near infrared band according to any one of claims 1 to 3, wherein the characteristic bands are 1361nm and 1870 nm.
5. The method of eliminating influence of soil particle size on soil parameter detection in discrete near infrared band according to any one of claims 1 to 3, wherein the soil sample comprises 4 particle size grades and 6 total nitrogen concentration gradients, wherein 4 particle size grades are 0.2mm, 0.45mm, 0.9mm and 2.0mm, and 6 total nitrogen concentration grades are 0g/kg, 0.04g/kg, 0.08g/kg, 0.12g/kg, 0.16g/kg and 0.2 g/kg.
6. The utility model provides a soil particle size is to discrete near-infrared wave band detection soil parameter influence's remove device which characterized in that includes:
the absorbance determining unit is used for determining the original absorbance of the soil to be detected in a plurality of detection wave bands under the near infrared spectrum scanning;
the coefficient determining unit is used for determining the granularity correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band;
the correction detection unit is used for correcting the original absorbance of each detection waveband of the soil to be detected based on the granularity correction coefficient of the soil to be detected and determining the soil parameters of the soil to be detected based on the correction result; and in the coefficient determining unit, determining the particle size correction coefficient of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band comprises:
determining an absorbance ratio for representing the soil granularity of the soil to be detected based on the original absorbance of the soil to be detected in the characteristic wave band;
determining a granularity correction coefficient of the soil to be detected based on the absorbance ratio of the soil to be detected and the absorbance ratio of the granularity of the reference soil;
the characteristic wave band is obtained based on the following method:
performing near infrared spectrum scanning on the soil samples under the multiple soil granularities, and determining the original absorbance of the samples of multiple preset wave bands of the soil samples;
determining a standard deviation value and a comprehensive standard deviation value of each soil sample under each soil granularity based on the original absorbance of the sample of each soil sample at a plurality of preset wave bands;
and determining the characteristic wave band based on the standard deviation value of the soil sample under each soil granularity and the comprehensive standard deviation value.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of the method for eliminating the effect of soil granularity on soil parameter detection in discrete near infrared bands as claimed in any one of claims 1 to 5.
8. A non-transitory computer readable storage medium, having stored thereon a computer program, wherein the computer program, when being executed by a processor, implements the steps of the method for eliminating the effect of soil particle size on discrete near-infrared band detection soil parameters according to any one of claims 1 to 5.
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