CN113344409A - Evaluation method and system for facility continuous cropping soil quality - Google Patents

Evaluation method and system for facility continuous cropping soil quality Download PDF

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CN113344409A
CN113344409A CN202110690198.0A CN202110690198A CN113344409A CN 113344409 A CN113344409 A CN 113344409A CN 202110690198 A CN202110690198 A CN 202110690198A CN 113344409 A CN113344409 A CN 113344409A
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陈晓璐
魏珉
张大龙
李仪曼
李潇雅
刘霜
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Abstract

The application discloses a method and a system for evaluating the quality of facility continuous cropping soil, wherein physical, chemical and biological indexes of the soil are selected as evaluation items, and the evaluation indexes are screened by adopting a minimum data set method; selecting a corresponding membership function according to the positive and negative effects of each index in the minimum data set on the soil and determining the membership of each evaluation index; calculating the weight value of each evaluation index, wherein the index weight value is equal to the ratio of the common factor variance of each index to the sum of the common factor variances of all index minimum data sets; and after determining the weight value of each evaluation index, evaluating by adopting a comprehensive index method. The evaluation method is established by screening indexes for evaluating the quality of the facility continuous cropping soil, the evaluation results are quickly obtained by utilizing the evaluation indexes of soil physics, chemistry, microorganisms and the like, the method is simple, the results are accurate, and a basis is provided for effectively taking measures to improve the facility soil and keeping the sustainable utilization of the facility soil.

Description

Evaluation method and system for facility continuous cropping soil quality
Technical Field
The application relates to the technical field of agricultural soil quality evaluation, in particular to a method and a system for evaluating the quality of facility continuous cropping soil.
Background
The facility soil is a material foundation which depends on the development of facility agriculture, and the texture, the fertility condition, the moisture content, the soil biological activity and other physical and chemical properties of the facility soil can directly influence the growth, development and quality of facility crops.
In the prior art, corresponding research methods exist for the problems of quality degradation and continuous cropping obstacles of facility soil, but no complete evaluation system exists in the evaluation method of the facility continuous cropping soil quality, so that the control and repair of the facility continuous cropping soil are lack of pertinence and effectiveness.
Therefore, how to evaluate the quality of the facility continuous cropping soil is a technical problem to be solved urgently in the field.
Disclosure of Invention
In order to solve the technical problems, the following technical scheme is provided:
in a first aspect, an embodiment of the present application provides a method for evaluating facility continuous cropping soil quality, where the method includes: selecting physical, chemical and biological indexes of soil as evaluation items, and screening the evaluation indexes by adopting a minimum data set method; selecting a corresponding membership function according to the positive and negative effects of each index in the minimum data set on the soil and determining the membership of each evaluation index; calculating the weight value of each evaluation index, wherein the index weight value is equal to the ratio of the common factor variance of each index to the sum of the common factor variances of all index minimum data sets; and after determining the weight value of each evaluation index, evaluating by adopting a comprehensive index method.
By adopting the implementation mode, the evaluation method is established by screening the indexes for evaluating the quality of the facility continuous cropping soil, the evaluation result is quickly obtained by utilizing the evaluation indexes of soil physics, chemistry, microorganisms and the like, the method is simple, the result is accurate, and a basis is provided for effectively taking measures to improve the facility soil and keeping the sustainable utilization of the facility soil.
With reference to the first aspect, in a first possible implementation manner of the first aspect, the selecting physical, chemical, and biological indicators of soil as evaluation items, and screening the evaluation indicators by using a minimum data set method includes: performing principal component analysis on the measured indexes, and selecting indexes with the maximum factor load index and the factor load absolute value reaching 90 percent of the maximum factor load from each principal component to be divided into a group; after grouping, comparing the correlation of indexes in each group with the vector constant modulus value; if the correlation coefficient is larger than the preset value, selecting an index with a large vector constant value to enter a minimum data set; or if the correlation coefficient is less than or equal to the preset value, all entering the minimum data set.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, when there is only one principal component high-factor load indicator, the indicator directly enters the minimum data set.
With reference to the first or second possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, the vector norm calculation formula is:
Figure BDA0003125893910000021
wherein: n is a radical ofikThe comprehensive load of the ith variable on the first k principal components with the characteristic value greater than or equal to 1; u. ofikThe load of the ith variable on the kth principal component; lambda [ alpha ]kIs the characteristic value of the kth principal component.
With reference to the first aspect, in a fourth possible implementation manner of the first aspect, the membership function is divided into an ascending type and a descending type according to a positive-negative effect of each index on soil, where:
the ascending membership function calculation formula:
Figure BDA0003125893910000022
a formula for calculating the reduced membership function:
Figure BDA0003125893910000031
minimum value x of each index1And maximum value x2As the turning point of the function.
With reference to the first aspect, in a fifth possible implementation manner of the first aspect, the calculation formula of the synthetic exponential method is:
Figure BDA0003125893910000032
wherein: SQI is soil comprehensive quality index; wiIs the weight of the ith soil index; n is a radical ofiThe membership degree of the ith soil index; n is the minimum data set indicator.
In a second aspect, an embodiment of the present application provides a system for evaluating facility continuous cropping soil quality, where the system includes: the screening module is used for selecting physical, chemical and biological indexes of soil as evaluation items and screening the evaluation indexes by adopting a minimum data set method; the determining module is used for selecting a corresponding membership function according to the positive and negative effects of each index in the minimum data set on the soil and determining the membership of each evaluation index; the calculation module is used for calculating the weight value of each evaluation index, and the weight value of each index is equal to the ratio of the common factor variance of each index to the sum of the common factor variances of all minimum index data sets; and the evaluation module is used for evaluating by adopting a comprehensive index method after determining the weight value of each evaluation index.
With reference to the second aspect, in a first possible implementation manner of the second aspect, the screening module includes: the grouping unit is used for performing principal component analysis on the measured indexes, and in each principal component, the indexes including the maximum factor load index and the factor load absolute value of which reaches 90 percent of the maximum factor load are selected and divided into a group; the comparison unit is used for comparing the correlation of the indexes in each group with the vector constant modulus value after grouping; the screening unit is used for selecting the index with the large vector constant modulus value to enter the minimum data set if the correlation coefficient is larger than the preset value; or if the correlation coefficient is less than or equal to the preset value, all entering the minimum data set.
With reference to the first possible implementation manner of the second aspect, in a second possible implementation manner of the second aspect, the vector norm calculation formula is:
Figure BDA0003125893910000041
wherein: n is a radical ofikThe comprehensive load of the ith variable on the first k principal components with the characteristic value greater than or equal to 1; u. ofikThe load of the ith variable on the kth principal component; lambda [ alpha ]kIs the characteristic value of the kth principal component.
With reference to the second aspect, in a third possible implementation manner of the second aspect, the membership function is divided into an ascending type and a descending type according to positive and negative effects of each index on soil, where:
the ascending membership function calculation formula:
Figure BDA0003125893910000042
a formula for calculating the reduced membership function:
Figure BDA0003125893910000043
minimum value x of each index1And maximum value x2As the turning point of the function.
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Fig. 1 is a schematic flow chart of a method for evaluating the quality of facility continuous cropping soil provided in an embodiment of the present application;
FIG. 2 is a schematic diagram of soil quality indexes of different regions according to an embodiment of the present application;
FIG. 3 is a graph of soil SQI values for full and minimum data set indices provided in an example of the present application;
fig. 4 is a schematic diagram of an evaluation system for facility continuous cropping soil quality provided in an embodiment of the present application.
Detailed Description
The present invention will be described with reference to the accompanying drawings and embodiments.
Fig. 1 is a schematic flow chart of an evaluation method for facility continuous cropping soil quality provided in an embodiment of the present application, and referring to fig. 1, the evaluation method for facility continuous cropping soil quality in the embodiment includes:
s101, selecting physical, chemical and biological indexes of soil as evaluation items, and screening the evaluation indexes by adopting a minimum data set method.
In this embodiment, the measurement indexes are subjected to principal component analysis, and in each principal component, indexes including a maximum factor load index and a factor load absolute value of 90% of the maximum factor load are selected and divided into a group. After grouping, the correlation of the indexes in each group is compared with the vector constant modulus value. If the correlation coefficient is larger than the preset value, selecting an index with a large vector constant value to enter a minimum data set; or if the correlation coefficient is less than or equal to the preset value, all entering the minimum data set. If there is only one principal component high factor load indicator, the indicator goes directly into the minimum data set.
The vector norm has the calculation formula as follows:
Figure BDA0003125893910000051
wherein: n is a radical ofikThe comprehensive load of the ith variable on the first k principal components with the characteristic value greater than or equal to 1; u. ofikThe load of the ith variable on the kth principal component; lambda [ alpha ]kIs the characteristic value of the kth principal component.
And S102, selecting a corresponding membership function according to the positive and negative effects of each index in the minimum data set on the soil, and determining the membership of each evaluation index.
According to the positive and negative effects of each index on soil, the membership function is divided into an ascending type and a descending type, wherein:
the ascending membership function calculation formula:
Figure BDA0003125893910000052
a formula for calculating the reduced membership function:
Figure BDA0003125893910000061
minimum value x of each index1And maximum value x2As the turning point of the function.
And S103, calculating the weight value of each evaluation index, wherein the weight value of each index is equal to the ratio of the common factor variance of each index to the common factor variance sum of all index minimum data sets.
And S104, determining the weight value of each evaluation index, and evaluating by adopting a comprehensive index method.
The comprehensive index method has the calculation formula as follows:
Figure BDA0003125893910000062
wherein: SQI is soil comprehensive quality index; wiIs the weight of the ith soil index; n is a radical ofiThe membership degree of the ith soil index; n is the minimum data set indicator.
In this example, a method for evaluating the quality of continuous cropping soil of Shandong facility cucumber is used.
In Shandong area, 40 cucumber sunlight greenhouses with different successive cropping years (0 year, 3 years, 6 years, 9 years, 12 years, 15 years and 18 years) of 4 facility cucumber dominant production areas (Lanling, Yinan, shouguang and Shenzhou) are selected. Distributing 7 points in each greenhouse according to the shape of N, respectively taking 0-20cm root zone soil at each point by using a soil drill, and finally mixing the soil samples at the 7 points in equal volume to form a soil sample.
The soil property determination adopts a conventional analysis method: measuring the volume weight of the soil by adopting a cutting ring method; the conductivity (EC value) of the soil is measured by an electrode method; measuring the pH value by adopting a potential method; the content of organic matters is measured by adopting a potassium dichromate-external heating method; measuring the contents of ammonium nitrogen and nitrate nitrogen by using a flow analyzer; the content of the quick-acting potassium is measured by adopting an ammonium acetate leaching-flame photometry method; the content of the hydrolyzable nitrogen is measured by an alkaline hydrolysis diffusion method; the effective phosphorus content is measured by sodium bicarbonate leaching-molybdenum antimony scandium colorimetric method; the total nitrogen content is measured by adopting a semi-micro Kjeldahl method; the contents of total phosphorus and total potassium are measured by adopting an inductively coupled plasma atomic emission spectrometry; the Cation Exchange Capacity (CEC) is measured by an ammonium acetate method; the total salt content is measured by a gravimetric method; the content of slow-release potassium is measured by a nitric acid leaching-flame photometry method. The catalase activity is measured by a potassium permanganate titration method; the phosphatase activity is measured by a disodium phenyl phosphate colorimetric method; the activity of the sucrase is measured by a 3, 5-dinitrosalicylic acid colorimetric method; urease activity was measured by sodium phenolate-sodium hypochlorite colorimetry. The soil microorganism-related indexes were measured by Shanghai Megi biomedical science and technology Limited.
Firstly, performing principal component analysis on 25 measured indexes, selecting indexes including a maximum factor load index and a factor load absolute value of which reaches 90% of a maximum factor load in each principal component, dividing the indexes into a group, and comparing the correlation and the Norm value of the indexes in each group after grouping, wherein if the correlation coefficient r is greater than 0.4, the index with a large Norm value is selected to enter a minimum data set; if the correlation coefficient r is less than 0.4, the minimum data set is entered. When the number of 1 principal component high factor load indexes is only 1, the indexes directly enter a minimum data set.
TABLE 1 soil indexes main component factor load and Norm value
Figure BDA0003125893910000071
Figure BDA0003125893910000081
TABLE 2 analysis of the correlation between high factor load indicators in the soil constituents
Figure BDA0003125893910000082
According to the correlation analysis and Norm calculation of each high-factor load index, the main component of the group 1 is selected into a minimum data set because the sucrase has the highest factor load, and the total nitrogen, the nitrate nitrogen and the slow-release potassium are removed because the total nitrogen, the nitrate nitrogen and the slow-release potassium have a significant correlation with the sucrase although the maximum factor load is within 90 percent, and the correlation between the hydrolytic nitrogen and the sucrase is less than 0.4, so that the main component enters the minimum data set; the same applies to determine that group 2 principal component available phosphorus and bacterial diversity were selected into the minimal data set. Only one high factor load indicator was satisfactory for groups 3, 4 and 5, respectively, and therefore, full potassium, fungal diversity and cation exchange capacity were selected into the minimum data set. In summary, sucrase, hydrolyzable nitrogen, available phosphorus, bacterial diversity, total potassium, fungal diversity and cation exchange capacity eventually entered the minimal dataset.
Calculating the weight value of the index and determining a membership function: the minimum data set index has positive effects of sucrase, hydrolyzable nitrogen, available phosphorus, bacterial diversity, total potassium, fungal diversity and cation exchange capacity, and thus belongs to a liter type membership function.
TABLE 3 minimum data set indicator weight values
Figure BDA0003125893910000091
See fig. 2, which is a schematic diagram of quality index of continuous cropping soil quality evaluation in major producing area of facility cucumber in Shandong.
Minimum data set accuracy verification: referring to fig. 3, soil SQI values of all initially selected 25 indexes, namely, Total Data Set (TDS) and Minimum Data Set (MDS) indexes, are respectively calculated, and regression analysis is performed on soil quality indexes of the minimum data set and the total data set, so that the reliability of the minimum data set evaluation result is verified. The calculation shows that the relation between SQI-MDS and SQI-TDS is that MDS is 1.1084 TDS-0.058, and R2 is 0.73 > 0.5.
According to the analysis result, the soil quality index of the minimum data set index and the soil quality index of the full data set are in a positive correlation, and the minimum data set selected in the research area can better reflect soil quality evaluation information.
Corresponding to the method for evaluating the facility continuous cropping soil quality provided by the embodiment, the application also provides an embodiment of a system for evaluating the facility continuous cropping soil quality. Referring to fig. 4, the system 20 for evaluating the quality of facility continuous cropping soil includes: a screening module 201, a determination module 202, a calculation module 203 and an evaluation module 204.
The screening module 201 is configured to select physical, chemical, and biological indexes of soil as evaluation items, and screen the evaluation indexes by using a minimum data set method.
In an exemplary embodiment, the screening module 201 includes: grouping unit, comparing unit and screening unit. And the grouping unit is used for performing principal component analysis on the measured indexes, and in each principal component, the indexes including the maximum factor load index and the factor load absolute value of which reaches 90 percent of the maximum factor load are selected and grouped. And the comparison unit is used for comparing the correlation of the indexes in each group with the vector constant modulus value after grouping. The screening unit is used for selecting the index with the large vector constant modulus value to enter the minimum data set if the correlation coefficient is larger than the preset value; or if the correlation coefficient is less than or equal to the preset value, all entering the minimum data set. When only one principal component high factor load indicator is present, the indicator is entered directly into the minimum data set.
In this embodiment, the vector norm has a calculation formula as follows:
Figure BDA0003125893910000101
wherein: n is a radical ofikThe comprehensive load of the ith variable on the first k principal components with the characteristic value greater than or equal to 1; u. ofikThe load of the ith variable on the kth principal component; lambda [ alpha ]kIs the k-th principal componentThe characteristic value of the score.
The determining module 202 is configured to select a corresponding membership function according to the positive and negative effects of each index in the minimum data set on the soil and determine the membership of each evaluation index.
According to the positive and negative effects of each index on soil, the membership function is divided into an ascending type and a descending type, wherein:
the ascending membership function calculation formula:
Figure BDA0003125893910000102
a formula for calculating the reduced membership function:
Figure BDA0003125893910000103
minimum value x of each index1And maximum value x2As the turning point of the function.
The calculating module 203 is configured to calculate a weight value of each evaluation indicator, where the weight value of each indicator is equal to a ratio between a common factor variance of each indicator and a common factor variance sum of all minimum indicator data sets. The evaluation module 204 is configured to determine a weight value of each evaluation index, and evaluate the evaluation index by using a comprehensive index method.
In this embodiment, the formula of the comprehensive exponential method is:
Figure BDA0003125893910000111
wherein: SQI is soil comprehensive quality index; wiIs the weight of the ith soil index; n is a radical ofiThe membership degree of the ith soil index; n is the minimum data set indicator.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Of course, the above description is not limited to the above examples, and technical features that are not described in this application may be implemented by or using the prior art, and are not described herein again; the above embodiments and drawings are only for illustrating the technical solutions of the present application and not for limiting the present application, and the present application is only described in detail with reference to the preferred embodiments instead, it should be understood by those skilled in the art that changes, modifications, additions or substitutions within the spirit and scope of the present application may be made by those skilled in the art without departing from the spirit of the present application, and the scope of the claims of the present application should also be covered.

Claims (10)

1. A method for evaluating the quality of facility continuous cropping soil, which is characterized by comprising the following steps:
selecting physical, chemical and biological indexes of soil as evaluation items, and screening the evaluation indexes by adopting a minimum data set method;
selecting a corresponding membership function according to the positive and negative effects of each index in the minimum data set on the soil and determining the membership of each evaluation index;
calculating the weight value of each evaluation index, wherein the index weight value is equal to the ratio of the common factor variance of each index to the sum of the common factor variances of all index minimum data sets;
and after determining the weight value of each evaluation index, evaluating by adopting a comprehensive index method.
2. The method according to claim 1, wherein the physical, chemical and biological indexes of the soil are selected as evaluation items, and the evaluation indexes are screened by a minimum data set method, and the method comprises the following steps:
performing principal component analysis on the measured indexes, and selecting indexes with the maximum factor load index and the factor load absolute value reaching 90 percent of the maximum factor load from each principal component to be divided into a group;
after grouping, comparing the correlation of indexes in each group with the vector constant modulus value;
if the correlation coefficient is larger than the preset value, selecting an index with a large vector constant value to enter a minimum data set; or if the correlation coefficient is less than or equal to the preset value, all entering the minimum data set.
3. The method of claim 2, wherein a principal component high factor load indicator is entered directly into the minimum data set when there is only one of the indicators.
4. A method according to claim 2 or 3, wherein the vector norm is calculated by the formula:
Figure FDA0003125893900000011
wherein: n is a radical ofikThe comprehensive load of the ith variable on the first k principal components with the characteristic value greater than or equal to 1; u. ofikThe load of the ith variable on the kth principal component; lambda [ alpha ]kIs the characteristic value of the kth principal component.
5. The method of claim 1, wherein the membership functions are classified into ascending and descending types according to the positive and negative effects of each index on the soil, wherein:
the ascending membership function calculation formula:
Figure FDA0003125893900000021
a formula for calculating the reduced membership function:
Figure FDA0003125893900000022
minimum value x of each index1And maximum value x2As the turning point of the function.
6. The method of claim 1, wherein the synthetic exponential method is calculated by the formula:
Figure FDA0003125893900000023
wherein: SQI is soil comprehensive quality index; wiIs the weight of the ith soil index; n is a radical ofiThe membership degree of the ith soil index; n is the minimum data set indicator.
7. A system for evaluating the quality of facility continuous cropping soil, the system comprising:
the screening module is used for selecting physical, chemical and biological indexes of soil as evaluation items and screening the evaluation indexes by adopting a minimum data set method;
the determining module is used for selecting a corresponding membership function according to the positive and negative effects of each index in the minimum data set on the soil and determining the membership of each evaluation index;
the calculation module is used for calculating the weight value of each evaluation index, and the weight value of each index is equal to the ratio of the common factor variance of each index to the sum of the common factor variances of all minimum index data sets;
and the evaluation module is used for evaluating by adopting a comprehensive index method after determining the weight value of each evaluation index.
8. The system of claim 7, wherein the screening module comprises:
the grouping unit is used for performing principal component analysis on the measured indexes, and in each principal component, the indexes including the maximum factor load index and the factor load absolute value of which reaches 90 percent of the maximum factor load are selected and divided into a group;
the comparison unit is used for comparing the correlation of the indexes in each group with the vector constant modulus value after grouping;
the screening unit is used for selecting the index with the large vector constant modulus value to enter the minimum data set if the correlation coefficient is larger than the preset value; or if the correlation coefficient is less than or equal to the preset value, all entering the minimum data set.
9. The system of claim 8, wherein the vector norm is calculated by the formula:
Figure FDA0003125893900000031
wherein: n is a radical ofikThe comprehensive load of the ith variable on the first k principal components with the characteristic value greater than or equal to 1; u. ofikThe load of the ith variable on the kth principal component; lambda [ alpha ]kIs the characteristic value of the kth principal component.
10. The system of claim 7, wherein the membership functions are classified into ascending and descending types according to the positive and negative effects of each index on the soil, wherein:
the ascending membership function calculation formula:
Figure FDA0003125893900000032
a formula for calculating the reduced membership function:
Figure FDA0003125893900000033
minimum value x of each index1And maximum value x2As the turning point of the function.
CN202110690198.0A 2021-06-22 2021-06-22 Evaluation method and system for facility continuous cropping soil quality Pending CN113344409A (en)

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