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

Abstract

The invention belongs to the technical field of forage grass quality evaluation, and particularly relates to a method for evaluating forage grass quality conditions based on multi-element comprehensive indexes, which comprises the following steps: selecting a plurality of quadrats on a grassland, and applying interference of different concentrations of the same mineral element to plant communities of different quadrats; determining the yield of different plants in each quadrat plant community in the highest grassland biomass period; measuring the content of each mineral element of different plants in each quadrat, and calculating the weighted average content of the community level of each mineral element according to the content of each mineral element of different plants in the quadrat; the standard nutrient concentration of each quadrat is determined; determining the expected nutrient stability of each quadrat; the forage quality condition is evaluated according to the change of standardized nutrient concentration and expected nutrient stability caused by the interference of applying different concentrations of the same mineral element in different ways, how to apply mineral elements to the forage subsequently is determined according to the forage quality condition, and the method has guiding significance for improving the forage quality.

Description

Technical Field

[0001] The present invention belongs to the technical field of forage quality assessment, and in particular relates to a method for assessing forage quality based on a multi-element comprehensive index. Background Art

[0002] Grassland ecosystems are a crucial component of terrestrial ecosystems, occupying 40% of the world's land area and 69% of global agricultural land. Grasslands are crucial because they provide a wide variety of ecosystem functions and services. Among these, aboveground biomass production is a fundamental ecological function, closely linked to the ecosystem service of providing food such as meat and milk. Previous studies evaluating the ecological service value of grasslands (or grassland value) have 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 are posing significant challenges to the material cycle and biodiversity of grassland ecosystems. Global forage quality has also declined to varying degrees, constraining the sustainability of grassland economic benefits. However, the lack of a specific indicator system for measuring forage quality has limited our understanding of how forage production responds to external disturbances.

[0003] In addition to common indicators of forage quality, such as digestibility, net energy, and crude protein content, mineral elements, including a variety of macro- and micronutrients, are also crucial components of forage quality. These elements are increasingly receiving attention due to their close relationship to the health of livestock, such as cattle and sheep. Research in the animal husbandry sector has found that mineral element levels in livestock should be within an appropriate range; exceeding this range can lead to disease. For example, phosphorus deficiency can lead to abnormal bone development, resulting in symptoms such as rickets and loss of appetite; potassium deficiency can cause growth retardation, muscle weakness, and neurological disorders; and calcium deficiency can lead to growth retardation, digestive problems, and decreased reproductive performance. The diversity of forage mineral nutrients complicates quality evaluation. Previous studies have attempted to comprehensively evaluate variations in multiple mineral nutrients, such as the "average mineral element content" metric, which is derived by standardizing the concentrations of various elements and calculating the average. This metric exhibits significant variation with grassland utilization intensity. However, such metrics have not been integrated with livestock nutrient thresholds and have overlooked the relationship between forage nutrient supply and livestock requirements. Therefore, it is urgent to improve the comprehensive evaluation index system of forage mineral elements, including nutrient concentration and supply. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a method for evaluating forage quality based on a multi-element comprehensive index.

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

[0006] S1: Select several sample plots on the grassland and impose different concentrations of the same mineral element on the plant communities in different sample plots, including zero concentration interference;

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

[0008] S3: Determine the content of each mineral element in different plants in each sample 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 sample plant community;

[0009] S4: Determine the standardized nutrient concentrations of each quadrat plant community;

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

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

[0012] Preferably, in step S2, the grassland biomass peaks in early August.

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

[0014] All plants in each sample plant community were harvested, and aboveground biomass was collected. After drying and weighing by species, the yield of different plant species in each sample plant community was obtained.

[0015] Further preferably, in step S3, the method for determining the mineral element content of different plants in each sample plant community is: grinding the various plant samples dried and weighed in S2, and separately determining the mineral element content of different species, and the mineral elements in S3 include phosphorus, potassium, calcium, magnesium, iron, manganese, copper, and zinc.

[0016] Preferably, in step S4, the method for determining the standardized nutrient concentration of each quadrat plant community is as follows:

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

[0018] S4.2: Incorporate the selected threshold values of each mineral element into the weighted average content of each mineral element community level determined in step S3, and standardize each value using the maximum and minimum normalization method;

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

[0020] S4.4: Take the average value of all mineral elements converted by 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 mineral element content of different plant species in each plot determined in step S3. Randomly remove species one by one and calculate the change in effective connectivity between the community and the mineral element after each species is removed.

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

[0024] Further preferably, in S5.1, the criterion for judging whether there is an effective connection 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 that can be provided by the community without species removal and with a mineral element interference concentration of 0 is higher than a limit value, and the limit value is between 0 and 1. The choice of the limit value needs to maximize the difference in expected nutrient stability between the disturbed community and the undisturbed community.

[0025] Further preferably, the total amount of the element provided by the community after random species removal is mineral element concentration × biomass.

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

[0027] 1. This invention is groundbreaking in its comprehensive comparison of the relationship between multiple mineral nutrients in forage and the minimum requirement thresholds for livestock. By normalizing data to minimum and maximum values, it resolves the incomparability caused by differences in the magnitudes of different mineral elements and greatly reduces the complexity of quality evaluation caused by nutrient diversity. The introduction of minimum requirement thresholds for multiple nutrients better reflects the feeding value of forage, helping to further clarify the "grass-livestock" relationship.

[0028] 2. The present invention introduces the nutrient supply of forage into the evaluation of forage quality, which can reflect the ability of grassland to stably and adequately provide multiple mineral elements; and establishes a connection between nutrient supply capacity and community composition. The nutrient supply capacity characterized by expected nutrient stability can reflect the specific community composition, which provides assistance for targeted restoration or addition of some species to improve grassland forage quality. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0031] Figure 3 Trend graphs showing the effect of nitrogen addition on normalized nutrient concentration (a) and expected nutrient stability (b). DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0033] Example:

[0034] Trial Year: 2015-2023

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

[0036] 1. Sample site selection and interference application

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

[0038] 2. Sample collection and determination

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

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

[0041] The thresholds selected for each element were incorporated into the weighted average content of each mineral element community level and the data were normalized using the maximum and minimum values (see Table 1 for the nutrient requirement thresholds for livestock). The mineral elements that increased significantly after nitrogen enrichment were removed, and the absolute value of the normalized value of the lowest threshold of each remaining mineral element was added or subtracted from all normalized values of each mineral element, so that the normalized value corresponding to the lowest threshold became 0. Finally, the average value of the converted values of all mineral elements in each sample plot was calculated to obtain the standardized nutrient concentration of the corresponding sample plot (see Table 1). Figure 2 a).

[0042] Table 1 Minimum requirement thresholds for mineral nutrients

[0043]

[0044] A bipartite network was constructed using the community species composition of each sample plot and the content of each mineral element of different plants. Species were randomly removed one by one, and the change in effective connectivity between the community and the mineral elements after each species was removed was calculated. Multiple simulations were performed to obtain paired data on the number of species lost and the number of mineral elements retained in the sample plot. Regression analysis of this data yielded a nonlinear regression line, and the area enclosed by the regression line and the coordinate axis was calculated as the expected nutrient stability (see Figure 2 b).

[0045] The criterion for determining whether a community has an effective connection to any mineral element is that 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 subjected to a zero concentration of the mineral element is above a threshold value, which lies between 0 and 1 and is 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 the mineral element concentration multiplied by 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) were significantly reduced, and the expected nutrient stability response to nitrogen enrichment was even more pronounced. The dots in the figure show the data for each nitrogen addition concentration, tested from 2015 to 2023. Analysis of the changes in the above two factors along the nitrogen addition gradient reveals that to ensure forage quality in Erguna mowed grassland, nitrogen addition should be kept within a reasonable range. Excessive nitrogen addition can cause the mineral content in the forage to approach the minimum mineral nutrient requirement threshold for livestock and reduce the forage's ability to consistently provide sufficient nutrients.

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

Claims

1. A method for evaluating forage quality based on a multi-element comprehensive index, characterized in that: The following steps are involved: S1: Select several sample plots on the grassland and impose different concentrations of the same mineral element on the plant communities in different sample plots, including zero concentration interference; S2: Determine the yield of different plant species in each quadrat plant community during the period of maximum grassland biomass; S3: Determine the content of each mineral element in different plants in each sample 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 sample plant community; S4: Determine the standardized nutrient concentrations of each quadrat plant community; S5: Determine the expected nutrient stability of each quadrat plant community; S6: Assess forage quality based on changes in standardized nutrient concentration and expected nutrient stability caused by applying different concentrations of the same mineral element in different samples, and decide how to apply mineral elements to the forage based on the forage quality.

2. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 1, wherein: In step S2, the grassland biomass peaks in early August.

3. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 1, wherein: In step S2, the method for determining the yield of different plants in each quadrat plant community is: All plants in each sample plant community were harvested, and aboveground biomass was collected. After drying and weighing by species, the yield of different plant species in each sample plant community was obtained.

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 sample plant community is: grinding the various plant samples dried and weighed in S2, and measuring the mineral element content of different species respectively. 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, wherein: In step S4, the method for determining the standardized nutrient concentration of each quadrat plant community is as follows: S4.1: First, determine the minimum requirement thresholds for different mineral elements for livestock during their growth and development stages. Select the highest minimum requirement threshold for the same mineral element among different livestock for the next calculation; S4.2: Incorporate the selected threshold values of each mineral element into the weighted average content of each mineral element community level determined in step S3, and standardize each value using the maximum and minimum normalization method; S4.3: Remove the mineral elements that are significantly increased after the interference, and add or subtract the absolute value of the normalized value of the lowest threshold value of each mineral element from all normalized values of the remaining mineral elements, so that the normalized value corresponding to the lowest threshold value of each remaining mineral element becomes 0; S4.4: Take the average value of all mineral elements converted by S4.3 to obtain the standardized nutrient concentration.

6. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 1, wherein: In step S5, the method for determining the expected nutrient stability is as follows: S5.1: Construct a bipartite network using the community species composition and the mineral element content of different plant species in each plot determined in step S3. Randomly remove species one by one and calculate the change in effective connectivity between the community and the mineral element after each species is removed. S5.2: Through multiple simulations, obtain paired data on the number of species lost in the community and the number of mineral element species retained. Perform regression analysis on the paired data to obtain a nonlinear regression line. The area enclosed by the regression line and the coordinate axis is solved as the expected nutrient stability.

7. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 6, characterized in that: In S5.1, the criterion for judging whether there is an effective connection between a community and any mineral element is that the ratio of the total amount of the element provided by the community after random species removal to the total amount of the element that can be 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 needs to be chosen to maximize the difference in expected nutrient stability between the disturbed community and the undisturbed community.

8. The method for evaluating forage quality based on a multi-element comprehensive index according to claim 7, 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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