Method for evaluating forage quality condition based on multi-element comprehensive index

Abstract

The present application belongs to the technical field of pasture quality evaluation, and particularly relates to a method for evaluating pasture quality condition based on a multi-element comprehensive index, which comprises selecting a plurality of sample plots on a grassland, applying the same mineral element with different concentrations to plant communities of different sample plots; determining the yield of different plants in the plant community of each sample plot at the highest biomass period of the grassland; measuring the content of each mineral element of different plants in each sample plot, and calculating the weighted average content of each mineral element at the community level according to the content of each mineral element of different plants in the sample plot; determining the standardized nutrient concentration of each sample plot; determining the expected nutrient stability of each sample plot; evaluating the pasture quality condition according to the changes of the standardized nutrient concentration and the expected nutrient stability caused by the same mineral element with different concentrations applied to different sample plots, and determining how to apply the mineral element to the pasture in the subsequent process according to the pasture quality condition, which has guiding significance for improving the quality of the pasture.

Description

Technical Field

[0001] This invention belongs to the field of forage quality assessment technology, specifically relating to a method for assessing forage quality based on a multi-element comprehensive index. Background Technology

[0002] Grassland ecosystems are a crucial component of terrestrial ecosystems, covering 40% of the global land area and 69% of global agricultural land. Grasslands are vital due to the diverse range of ecosystem functions and services they provide. Among these, grassland biomass production is a fundamental ecological function, closely related to the ecosystem service of providing food such as meat and dairy. Previous studies evaluating the value of grassland ecosystem services (or grassland value) typically focused solely on forage yield. In recent years, forage quality has gained increasing attention as another important aspect of grassland value assessment. Intensifying global change and high-intensity human activities pose significant challenges to material cycling and biodiversity in grassland ecosystems, leading to varying degrees of decline in global grassland forage quality, which constrains the sustainability of grassland economic benefits. However, the lack of specific indicators for measuring forage quality limits our understanding of how forage production responds to external disturbances.

[0003] Besides common indicators of forage quality such as digestibility, net energy, and crude protein content, mineral elements are also crucial components of forage quality, including various macro- and micro-elements. These elements are increasingly valued due to their close relationship with the health of livestock such as cattle and sheep. Research in animal husbandry has found that the mineral element content in livestock should be within a suitable range; exceeding this range can lead to disease. For example, phosphorus (P) deficiency causes abnormal skeletal development, resulting in rickets and loss of appetite; potassium (K) deficiency leads to stunted growth, muscle weakness, and neurological disorders; and calcium (Ca) deficiency leads to stunted growth, digestive problems, and decreased reproductive performance. The diversity of mineral nutrients in forage contributes to the complexity of quality evaluation. Previous studies have attempted to comprehensively evaluate changes in various mineral nutrients, such as the proposed "average mineral element content" indicator, which is obtained by standardizing the content of various elements and averaging them, showing significant changes with grassland utilization intensity. However, such indicators have not been linked to livestock nutrient requirement thresholds and have neglected the relationship between forage nutrient supply and livestock demand. Therefore, it is urgent to improve the comprehensive evaluation index system for forage mineral elements, including both nutrient concentration and supply. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method for evaluating forage quality based on a multi-element comprehensive index.

[0005] This invention is implemented by providing a method for evaluating forage quality based on a multi-element comprehensive index, comprising the following steps:

[0006] S1: Select several quadrats on the grassland and apply different concentrations of the same mineral element to the plant communities in different quadrats, including interference with a concentration of zero.

[0007] S2: Determine the yield of different plant species in each quadrat plant community during the period of highest grassland biomass;

[0008] S3: Determine the content of each mineral element in different plants in each quadrat plant community, and calculate the weighted average content of each mineral element at the community level based on the content of each mineral element in different plants in the quadrat plant community.

[0009] S4: Determine the standardized nutrient concentration for the plant community in each quadrat;

[0010] S5: Determine the expected nutrient stability of the plant community in each quadrat;

[0011] S6: Assess the quality of forage by evaluating the changes in standardized nutrient concentration and expected nutrient stability caused by different concentrations of the same mineral element applied in different formulations, and determine how to apply mineral elements to the forage subsequently based on the quality of the forage.

[0012] Preferably, in step S2, the period with the highest grassland biomass is early August.

[0013] Preferably, in step S2, the method for determining the yield of different plants in each quadrat plant community is as follows:

[0014] By harvesting all plants in each quadrat plant community, aboveground biomass was collected, dried by species, and weighed to obtain the yield of different plants in each quadrat plant community.

[0015] Further preferred, in step S3, the method for determining the mineral element content of different plants in each quadrat plant community is as follows: the various plant samples dried and weighed in S2 are ground, and the mineral element content of different species is determined respectively. The mineral elements in S3 include phosphorus, potassium, calcium, magnesium, iron, manganese, copper and zinc.

[0016] Preferably, in step S4, the standardized nutrient concentration of each quadrat plant community is determined using the following method:

[0017] S4.1: First, determine the minimum requirement threshold of different types of mineral elements for livestock during their growth and development stages, and select the highest value among the minimum requirement thresholds of different livestock for the same mineral element for the next step of calculation.

[0018] S4.2: The threshold values ​​of each selected mineral element are incorporated into the weighted average content of each mineral element community level determined in step S3, and the maximum-minimum normalization method is used to standardize each value.

[0019] S4.3: Remove the mineral elements that have increased significantly after the interference is applied, and add or subtract the absolute value of the normalized value of the lowest threshold of each mineral element to all the normalized values ​​of the remaining mineral elements, so that the normalized value corresponding to the lowest threshold of each remaining mineral element becomes 0.

[0020] S4.4: Calculate the average value of all mineral elements after transformation in S4.3 to obtain the standardized nutrient concentration.

[0021] Preferably, in step S5, the method for determining the expected nutrient stability is as follows:

[0022] S5.1: Construct a bipartite network using the community species composition and the content of each mineral element in different plant species in each quadrat plant community determined in step S3. Randomly remove species one by one and calculate the change in the effective connection between the community and mineral elements after each species is removed.

[0023] S5.2: Through multiple simulations, paired data of the number of community species lost and the number of mineral element species retained are obtained. Regression analysis is performed on the paired data to obtain a nonlinear regression line. The area enclosed by the regression line and the coordinate axis is calculated as the expected nutrient stability.

[0024] Further optimization, in S5.1, the criterion for determining whether an effective connection exists between a community and any mineral element is: the ratio of the total amount of the element provided by the community after random species removal to the total amount of the element provided by the community without species removal and with a mineral element disturbance concentration of 0 is higher than a threshold value, the threshold value being between 0 and 1, and the selection of the threshold value is to maximize the difference in expected nutrient stability between the disturbed community and the undisturbed community.

[0025] Further optimization showed that the total amount of this element provided by the community after random species removal was the mineral element concentration × biomass.

[0026] Compared with the prior art, the advantages of the present invention are as follows:

[0027] 1. This invention is groundbreaking in comprehensively comparing the relationship between various mineral nutrients in forage and the minimum requirement thresholds for livestock. By normalizing data through minimum and maximum values, it resolves the incomparability caused by differences in the magnitude of different mineral elements, greatly reducing the complexity of quality evaluation due to nutrient diversity; the introduction of minimum requirement thresholds for multiple nutrients better reflects the feeding value of forage and helps to further clarify the "forage-livestock" relationship;

[0028] 2. This invention incorporates the nutrient supply of forage into the evaluation of forage quality, which can reflect the grassland's ability to stably and adequately provide various mineral elements; and establishes a link between nutrient supply capacity and community composition. The nutrient supply capacity characterized by expected nutrient stability can reflect a specific community composition, which helps to specifically restore or add certain species to improve grassland forage quality. Attached Figure Description

[0029] Figure 1 Add photos of the experimental platform for nitrogen compounds at Ergun Station;

[0030] Figure 2 Conceptual diagram of reducing standardized nutrient concentrations (a) and expected nutrient stability (b) for nitrogen enrichment;

[0031] Figure 3 Trend graph showing the effect of nitrogen addition on standardized nutrient concentration (a) and expected nutrient stability (b). Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0033] Example:

[0034] Trial period: 2015-2023

[0035] Experimental location: Ergun Forest-Grassland Transitional Zone Ecosystem Research Station, Heishantou Town, Ergun City, Inner Mongolia Autonomous Region.

[0036] 1. Selection of sample plots and application of disturbance

[0037] Based on the nitrogen compound addition experimental platform at the Ergun Station, 48 plots of land that had been treated with slow-release urea and mowed were selected as the research subjects. The platform employed a randomized block design, comprising 8 blocks with 6 nitrogen addition levels: 0, 2, 5, 10, 20, and 50 g Nm³. -2 yr -1 The quadrat size was set at 10m × 10m, with a quadrat spacing of 1m and a plot spacing of 2m. Nitrogen fertilizer was applied at the end of May each year, mixed with fine sand. The grassland was mowed at the end of August each year, leaving a stubble height of 10cm to simulate local herders' use of the grassland.

[0038] 2. Sample collection and determination

[0039] During the peak grassland biomass period (early August), 1m × 1m quadrats were selected from all quadrats. All aboveground plants within each quadrat were harvested at ground level, sorted by species, placed in envelopes, and brought back to the laboratory. After drying at 60°C for 48 hours, the aboveground biomass was measured. The dried plant samples were then pulverized using a ball mill, digested with nitric acid and perchloric acid, and the contents of eight elements (phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), copper (Cu), and zinc (Zn)) in the forage were determined using inductively coupled plasma optical emission spectrometry (ICP-OES).

[0040] 3. Calculation of standardized nutrient concentration and expected nutrient stability

[0041] The selected thresholds for each element were incorporated into the weighted average content of each mineral element community level, and the data were standardized using maximum-minimum normalization (see Table 1 for livestock nutrient requirement thresholds). Mineral elements that showed a significant increase after nitrogen enrichment were removed, and the absolute value of the normalized value of the remaining mineral elements was added to or subtracted from the minimum threshold normalized value of each mineral element, making the normalized value corresponding to the minimum threshold zero. Finally, the average value of all transformed mineral element values ​​for each sample plot was calculated to obtain the standardized nutrient concentration of the corresponding sample plot (see Table 1 for livestock nutrient requirement thresholds). Figure 2 a).

[0042] Table 1 Minimum Requirement Thresholds for Mineral Nutrients

[0043]

[0044] A bipartite network was constructed using the community species composition and the content of each mineral element in different plant species for each quadrat. Species were randomly removed one by one, and the changes in the effective connections between the community and mineral elements after each species removal were calculated. Through multiple simulations, paired data on the number of community species lost and the number of mineral elements retained in each quadrat were obtained. Regression analysis of this data yielded a nonlinear regression line. The area enclosed by this regression line and the coordinate axes was calculated as the expected nutrient stability (see...). Figure 2 b).

[0045] The criterion for determining whether a valid connection exists between a community and any mineral element is: the ratio of the total amount of that element provided by the community after random species removal to the total amount of that element provided by the community without species removal and with a mineral element disturbance concentration of 0 is higher than a threshold value, which is between 0 and 1. The threshold value should be chosen to maximize the difference in expected nutrient stability between the disturbed and undisturbed communities. The total amount of that element provided by the community after random species removal is mineral element concentration × biomass.

[0046] The results showed that with the increase of nitrogen addition, the standardized nutrient concentration ( Figure 3 a) and expected nutrient stability ( Figure 3 (b) Both decreased significantly, and the response to nitrogen enrichment was more pronounced for those with stable nutrient levels. The dots in the figure represent the detection results from 2015 to 2023 for each nitrogen addition concentration. Analysis of the changes in nitrogen addition gradients for both groups reveals that, to ensure the quality of forage in the Ergun cut grassland, nitrogen addition should not be too high. Excessive nitrogen addition will cause the mineral element content in the forage to approach the minimum threshold required by livestock for mineral nutrients, and will also reduce the forage's ability to stably provide sufficient nutrients.

[0047] The above description is merely a preferred embodiment of the present invention and is illustrative rather than restrictive. Those skilled in the art will understand that many changes, modifications, and even equivalents can be made within the spirit and scope defined by the claims of the present invention, all of which will fall within the protection scope of the present invention.

Claims

1. A method for assessing forage quality based on a multi-element comprehensive index, characterized in that, Includes the following steps: S1: Select several quadrats on the grassland and apply different concentrations of the same mineral element to the plant communities in different quadrats, including interference with a concentration of zero. S2: Determine the yield of different plant species in each quadrat plant community during the period of highest grassland biomass; S3: Determine the content of each mineral element in different plants in each quadrat plant community, and calculate the weighted average content of each mineral element at the community level based on the content of each mineral element in different plants in the quadrat plant community. S4: Determine the standardized nutrient concentrations for the plant community in each quadrat, using the following method: S4.1: First, determine the minimum requirement threshold of different types of mineral elements for livestock during their growth and development stages, and select the highest value among the minimum requirement thresholds of different livestock for the same mineral element for the next step of calculation. S4.2: The threshold values ​​of each selected mineral element are incorporated into the weighted average content of each mineral element community level determined in step S3, and the maximum-minimum normalization method is used to standardize each value. S4.3: Remove the mineral elements that have increased significantly after the interference is applied, and add or subtract the absolute value of the normalized value of the lowest threshold of each mineral element to all the normalized values ​​of the remaining mineral elements, so that the normalized value corresponding to the lowest threshold of each remaining mineral element becomes 0. S4.4: Calculate the average value of all mineral elements after transformation in S4.3 to obtain the standardized nutrient concentration; S5: Determine the expected nutrient stability of the plant community in each quadrat, using the following method: S5.1: Construct a bipartite network using the community species composition and the content of each mineral element in different plants in each quadrat plant community determined in step S3. Randomly remove species one by one and calculate the change in the effective connection between the community and the mineral element after each species removal. The criterion for determining whether an effective connection exists between the community and any mineral element is: the ratio of the total amount of the element provided by the community after random species removal to the total amount of the element provided by the community without species removal and with a mineral element interference concentration of 0 is higher than the threshold value, which is between 0 and 1. The threshold value should be selected to maximize the difference in expected nutrient stability between the disturbed community and the undisturbed community. S5.2: Through multiple simulations, paired data of the number of community species lost and the number of mineral element species retained are obtained. Regression analysis is performed on the paired data to obtain a nonlinear regression line. The area enclosed by the regression line and the coordinate axis is calculated as the expected nutrient stability. S6: Assess the quality of forage by evaluating the changes in standardized nutrient concentration and expected nutrient stability caused by different concentrations of the same mineral element applied in different formulations, and determine how to apply mineral elements to the forage subsequently based on the quality of the forage.

2. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 1, characterized in that, In step S2, the period with the highest grassland biomass is in early August.

3. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 1, characterized in that, In step S2, the method for determining the yield of different plants in each quadrat plant community is as follows: By harvesting all plants in each quadrat plant community, aboveground biomass was collected, dried by species, and weighed to obtain the yield of different plants in each quadrat plant community.

4. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 3, characterized in that, In step S3, the method for determining the mineral element content of different plants in each quadrat plant community is as follows: the various plant samples dried and weighed in S2 are ground, and the mineral element content of different species is determined separately. The mineral elements in S3 include phosphorus, potassium, calcium, magnesium, iron, manganese, copper, and zinc.

5. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 1, characterized in that, The total amount of this element provided by the community after random species removal is the mineral element concentration × biomass.

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