A method for evaluating the replacement effect of natural grassland forage supply based on artificial forage grass and straw

Abstract

The application discloses a kind of natural grassland forage supply substitution efficiency evaluation method based on artificial forage grass and straw, and is applied to grassland ecological management technical field.It includes the following steps: constructing the evaluation index system including multiple measures, collecting multi-source basic data, taking natural grassland standard theoretical supply as benchmark, calculating the actual forage nutrition provided by each measure, obtaining the substitution efficiency index corresponding to the measure;Build a total substitution efficiency index calculation model containing the interaction effect between measures;Calculate the total substitution efficiency index and the theoretical grass-livestock balance degree of each time period;Generate an evaluation report containing the substitution efficiency index of each measure, the total substitution efficiency index, the theoretical grass-livestock balance degree and optimization suggestions.The present application overcomes the one-sidedness of single measure evaluation, considers the interactive synergistic effect of different measures, and can accurately quantify the forage substitution contribution under the synergistic effect of multiple measures, providing scientific and dynamic decision support for regional grass-livestock resource allocation and ecological management.

Description

Technical Field

[0001] This invention relates to the field of grassland ecological management technology, and more specifically to a method for evaluating the substitution effect of artificial forage and straw in natural grassland forage supply. Background Technology

[0002] Natural grasslands are a fundamental resource for livestock development. However, with the degradation of natural grasslands, existing solutions mostly involve planting artificial forage crops (such as alfalfa, oats, and corn) and utilizing crop straw as feed to partially replace the forage supply from natural grasslands in order to alleviate pressure on these areas. Simultaneously, optimizing livestock population structure and feeding patterns can also reduce the direct demand for natural pasture. Scientifically measuring the substitution effect of these artificial measures on natural grasslands is fundamental to setting carrying capacity limits, ecological compensation standards, and agricultural and livestock structure optimization plans.

[0003] However, there is currently no effective assessment method for the aforementioned alternative measures (such as different forage planting, forage processing, and optimization of livestock structure). Existing assessment schemes mostly focus on the effects of single measures and fail to establish an integrated assessment model that includes multiple measures and indicators from the perspective of the coupling between the ecosystem and the livestock production system. Existing assessments generally assume that each measure works independently and fail to consider the synergistic efficiency of different measures. In addition, the yield of natural grasslands has strong interannual fluctuations and seasonal dynamics, and the growth of artificial forage is also significantly affected by meteorological conditions. Existing assessment schemes do not consider dynamic changes at different time scales. Pasture managers find it difficult to accurately determine the substitution effectiveness of various measures and cannot dynamically optimize the allocation of forage and livestock resources. Therefore, how to provide a method for assessing the substitution effectiveness of natural grassland forage supply based on artificial forage and straw is an urgent problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention provides a method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw, constructs an evaluation index system that includes multiple measures, uniformly quantifies the nutritional contribution of each measure, and realizes dynamic integrated evaluation of the substitution effect of multiple measures.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for evaluating the substitution effect of artificial forage and natural grassland forage supply, comprising the following steps: S1. Based on the livestock production structure and resource utilization patterns within the target area, construct an evaluation index system, including: natural grassland nutrient regulation efficiency index, alfalfa planting substitution efficiency index, oat planting substitution efficiency index, corn planting substitution efficiency index, forage processing efficiency index, sheep breeding population structure optimization efficiency index, and feeding pattern optimization efficiency index. S2. Collect and preprocess multi-source basic data within the assessment area; S3. Based on the standard theoretical supply of natural grassland, calculate the actual amount of forage nutrients provided by each measure to obtain the substitution efficiency index of the corresponding measure. S4. Use the analytic hierarchy process (AHP) to determine the weights of each measure indicator and construct a total substitution effectiveness index calculation model that includes the interaction effects between measures. S5. Establish a dynamic evaluation mechanism to calculate the total substitution efficiency index and theoretical grass-livestock balance for each time period; S6. Generate an evaluation report that includes the substitution efficiency index of each measure, the total substitution efficiency index, the theoretical grass-livestock balance, and optimization suggestions.

[0006] Optionally, the multi-source basic data collected in S2 includes: the area of ​​natural grasslands, the sequence of grass yield and the proportion of edible forage, the nutritional parameters of natural forage and various artificial forages and straw, the planting area, yield per unit area and dry matter content of various artificial forages, the processing amount of straw and the effective utilization rate before and after processing, and the livestock inventory, population structure and feeding pattern parameters.

[0007] Optionally, in S3, the actual forage nutrient content provided by each measure is calculated as follows: Set the baseline vector for natural grassland forage nutrition as follows: ,in, This is the baseline value for metabolizable energy. This is the crude protein baseline value. This is the baseline value for neutral detergent fibers. As a limiting amino acid baseline, the conversion factor for each nutrient dimension is calculated for both artificial forage and straw: Positive indicators: ; Contrarian indicator: ; In the formula, as raw materials From a nutritional perspective The conversion factor, Nutritional dimensions The baseline value, as raw materials From a nutritional perspective The measured values; the positive indicators are metabolizable energy, crude protein, and limiting amino acids, and the negative indicator is neutral detergent fiber, to determine the weight vector of the nutritional dimensions. and raw materials The conversion factor vector Calculate the actual amount of nutrients provided in the forage. .

[0008] Optionally, the substitution effectiveness index for each measure in S3 is calculated as follows: For measures to increase forage supply, the substitution efficiency index , measures The increased dry matter weight, The theoretical supply of natural grasslands, and the substitution efficiency index for measures to reduce forage demand. , measures The total nutritional requirements of livestock have been reduced.

[0009] Optionally, the total substitution efficiency index calculation model in S4 is as follows: ; In the formula, For time period The total substitution efficiency index within the country, measures The weight, For time period Internal measures The substitution efficiency index For time period Internal measures The substitution efficiency index measures and measures The interaction effect coefficient.

[0010] Optional, interaction effect coefficient Based on the actual substitution effect data under different combinations of measures, the results were obtained by fitting using the response surface methodology.

[0011] Optionally, the theoretical grass-livestock balance for each time period is calculated in S5 as follows: ; In the formula, For time period Theoretical grass-livestock balance within the region For time period The theoretical supply of natural grasslands within the area. For time period The total substitution efficiency index within the country, For time period The baseline nutritional requirements of the natural grasslands within the area.

[0012] Optionally, the theoretical supply of natural grassland is calculated using a multiple regression model based on the normalized vegetation index, precipitation, average temperature in the corresponding time period and the theoretical supply of natural grassland in the previous time period.

[0013] As can be seen from the above technical solution, compared with the prior art, the present invention provides a method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw, which has the following beneficial effects: The present invention constructs an integrated evaluation index system including seven measures, incorporating measures such as artificial grass planting, straw processing, and livestock structure optimization into the evaluation framework, overcoming the one-sidedness of single-measure evaluation; considering the interactive synergistic effect of different measures, it improves the accuracy of comprehensive evaluation of multiple measures, dynamically evaluates substitution effect at different time scales, and provides key information for risk management and long-term planning; it converts different qualitative substitution measures into a unified forage supply equivalent, realizes quantitative comparison and comprehensive calculation, and can intuitively demonstrate the actual contribution of artificial measures to alleviating pressure on natural grasslands, providing accurate data support for livestock carrying capacity regulation, ecological compensation, and subsidy policy formulation. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0015] Figure 1 This is a flowchart of the method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw, according to the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] This invention discloses a method for evaluating the substitution effect of artificial forage and straw in natural grassland forage supply, such as... Figure 1 As shown, it includes the following steps: S1. Based on the livestock production structure and resource utilization patterns within the target area, construct an evaluation index system, including: natural grassland nutrient regulation efficiency index, alfalfa planting substitution efficiency index, oat planting substitution efficiency index, corn planting substitution efficiency index, forage processing efficiency index, sheep breeding population structure optimization efficiency index, and feeding pattern optimization efficiency index. S2. Collect and preprocess multi-source basic data within the assessment area; S3. Based on the standard theoretical supply of natural grassland, calculate the actual amount of forage nutrients provided by each measure to obtain the substitution efficiency index of the corresponding measure. S4. Use the analytic hierarchy process (AHP) to determine the weights of each measure indicator and construct a total substitution effectiveness index calculation model that includes the interaction effects between measures. S5. Establish a dynamic evaluation mechanism to calculate the total substitution efficiency index and theoretical grass-livestock balance for each time period; S6. Generate an evaluation report that includes the substitution efficiency index of each measure, the total substitution efficiency index, the theoretical grass-livestock balance, and optimization suggestions.

[0018] Furthermore, the multi-source basic data collected in S2 includes: the area of ​​natural grasslands, the sequence of grass yield and the proportion of edible forage, the nutritional parameters of natural forage and various artificial forages and straw, the planting area, yield per unit area and dry matter content of various artificial forages, the processing amount of straw and the effective utilization rate before and after processing, and the livestock inventory, population structure and feeding pattern parameters.

[0019] In this embodiment of the invention, multi-source basic data are collected, and after outlier removal, missing value imputation and standardization processing, a unified database is constructed.

[0020] Furthermore, S3 calculates the actual forage nutrient content provided by each measure as follows: Set the baseline vector for natural grassland forage nutrition as follows: ,in, This is the baseline value for metabolizable energy. This is the crude protein baseline value. This is the baseline value for neutral detergent fibers. As a limiting amino acid baseline, the conversion factor for each nutrient dimension is calculated for both artificial forage and straw: Positive indicators: ; Contrarian indicator: ; In the formula, as raw materials From a nutritional perspective The conversion factor, Nutritional dimensions The baseline value, as raw materials From a nutritional perspective The measured values; the positive indicators are metabolizable energy, crude protein, and limiting amino acids, and the negative indicator is neutral detergent fiber, to determine the weight vector of the nutritional dimensions. and raw materials The conversion factor vector Calculate the actual amount of nutrients provided in the forage. .

[0021] In an embodiment of the present invention, the raw materials The nutrient parameter vector is The value of the reference vector is Taking alfalfa as an example, the value of its nutrient parameter vector is An analytic hierarchy process (AHP) was used to construct a judgment matrix for the importance of metabolizable energy, crude protein, neutral detergent fiber, and limiting amino acids to livestock production performance. The conversion factor vector is calculated. Then, the actual nutrient content of the forage provided by alfalfa is calculated as follows: .

[0022] Furthermore, the substitution effectiveness index for each measure in S3 is calculated as follows: For measures to increase forage supply, the substitution efficiency index , measures The increased dry matter weight, The theoretical supply of natural grasslands, and the substitution efficiency index for measures to reduce forage demand. , measures The total nutritional requirements of livestock have been reduced.

[0023] In this embodiment of the invention, the theoretical supply of natural grasslands... The calculation formula is: ; In the formula, Area of ​​natural grassland This represents the average grass yield of natural grasslands. This represents the proportion of edible forage in natural grasslands.

[0024] Furthermore, the specific calculation model for the total substitution efficiency index in S4 is as follows: ; In the formula, For time period The total substitution efficiency index within the country, measures The weight, For time period Internal measures The substitution efficiency index For time period Internal measures The substitution efficiency index measures and measures The interaction effect coefficient.

[0025] In this embodiment of the invention, the weights of each measure are also obtained through the analytic hierarchy process (AHP). The weights of the natural grassland nutrient regulation efficiency index, alfalfa planting substitution efficiency index, oat planting substitution efficiency index, corn planting substitution efficiency index, forage processing efficiency index, sheep breeding population structure optimization efficiency index, and feeding pattern optimization efficiency index are 0.08, 0.25, 0.20, 0.15, 0.08, 0.14, and 0.10, respectively.

[0026] Furthermore, the interaction effect coefficient Based on the actual substitution effect data under different combinations of measures, the results were obtained by fitting using the response surface methodology.

[0027] In this embodiment of the invention, fitting using the response surface method specifically involves: Multiple measures were selected to design interactive experiments between different measures. Evaluations were conducted on each combination, and the actual comprehensive substitution effectiveness was recorded. A regression model was established. ; In the formula, For response value, For encoding variables, The intercept is... , , For coefficients, As a random error, in this embodiment, the response value is the actual comprehensive substitution effectiveness, and the encoded variable is the actual implementation amount of the measure; the interaction coefficient is obtained by solving the coefficient vector. .

[0028] Furthermore, the theoretical grass-livestock balance for each time period is calculated in S5 as follows: ; In the formula, For time period Theoretical grass-livestock balance within the region For time period The theoretical supply of natural grasslands within the area. For time period The total substitution efficiency index within the country, For time period The baseline nutritional requirements of the natural grasslands within the area. In this embodiment, a one-month period is set. When the lowest theoretical grass-livestock balance of the year is below 0.8 or less than 1 for two consecutive months, it is assessed as high risk, and an early warning is issued in the assessment report.

[0029] Furthermore, the theoretical supply of natural grassland is calculated using a multiple regression model based on the normalized vegetation index, precipitation, average temperature in the corresponding time period and the theoretical supply of natural grassland in the previous time period.

[0030] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0031] Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the substitution effect of artificial forage and natural grassland forage supply, characterized in that, Includes the following steps: S1. Based on the livestock production structure and resource utilization patterns within the target area, construct an evaluation index system, including: natural grassland nutrient regulation efficiency index, alfalfa planting substitution efficiency index, oat planting substitution efficiency index, corn planting substitution efficiency index, forage processing efficiency index, sheep breeding population structure optimization efficiency index, and feeding pattern optimization efficiency index. S2. Collect and preprocess multi-source basic data within the assessment area; S3. Based on the standard theoretical supply of natural grassland, calculate the actual amount of forage nutrients provided by each measure to obtain the substitution efficiency index of the corresponding measure. S4. Use the analytic hierarchy process (AHP) to determine the weights of each measure indicator and construct a total substitution effectiveness index calculation model that includes the interaction effects between measures. S5. Establish a dynamic evaluation mechanism to calculate the total substitution efficiency index and theoretical grass-livestock balance for each time period; S6. Generate an evaluation report that includes the substitution efficiency index of each measure, the total substitution efficiency index, the theoretical grass-livestock balance, and optimization suggestions.

2. The method for evaluating the substitution effect of artificial forage and straw in natural grassland forage supply according to claim 1, characterized in that, The multi-source basic data collected in S2 includes: the area of ​​natural grasslands, the sequence of grass yield and the proportion of edible forage, the nutritional parameters of natural forage and various artificial forages and straw, the planting area, yield per unit area and dry matter content of various artificial forages, the processing amount of straw and the effective utilization rate before and after processing, and the livestock inventory, population structure and feeding pattern parameters.

3. The method for evaluating the substitution effect of artificial forage and straw in natural grassland forage supply according to claim 1, characterized in that, S3 calculates the actual forage nutrient content provided by each measure as follows: Set the baseline vector for natural grassland forage nutrition as follows: ,in, This is the baseline value for metabolizable energy. This is the crude protein baseline value. This is the baseline value for neutral detergent fibers. As a limiting amino acid baseline, the conversion factor for each nutrient dimension is calculated for both artificial forage and straw: Positive indicators: ; Contrarian indicator: ; In the formula, as raw materials From a nutritional perspective The conversion factor, Nutritional dimensions The baseline value, as raw materials From a nutritional perspective The measured values; the positive indicators are metabolizable energy, crude protein, and limiting amino acids, and the negative indicator is neutral detergent fiber, to determine the weight vector of the nutritional dimensions. and raw materials The conversion factor vector Calculate the actual amount of nutrients provided in the forage. .

4. The method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw according to claim 3, characterized in that, The substitution effectiveness index for each measure in S3 is calculated as follows: For measures to increase forage supply, the substitution efficiency index , measures The increased dry matter weight, The theoretical supply of natural grasslands, and the substitution efficiency index for measures to reduce forage demand. , measures The total nutritional requirements of livestock have been reduced.

5. The method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw according to claim 1, characterized in that, The specific model for calculating the total substitution efficiency index in S4 is as follows: ； In the formula, For time period The total substitution efficiency index within the country, measures The weight, For time period Internal measures The substitution efficiency index For time period Internal measures The substitution efficiency index measures and measures The interaction effect coefficient.

6. The method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw, as described in claim 5, is characterized in that... Interaction effect coefficient Based on the actual substitution effect data under different combinations of measures, the results were obtained by fitting using the response surface methodology.

7. The method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw according to claim 1, characterized in that, The theoretical grass-livestock balance for each time period is calculated in S5 as follows: ； In the formula, For time period Theoretical grass-livestock balance within the region For time period The theoretical supply of natural grasslands within the area. For time period The total substitution efficiency index within the country, For time period The baseline nutritional requirements of the natural grasslands within the area.

8. The method for evaluating the substitution effect of natural grassland forage supply based on artificial forage and straw according to claim 7, characterized in that, The theoretical supply of natural grassland is calculated using a multiple regression model based on the normalized vegetation index, precipitation, average temperature for the corresponding time period and the theoretical supply of natural grassland for the previous time period.

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