Digital ecological agriculture integrated production and supply coordination system

Abstract

The invention, which relates to the technical field of agricultural management, discloses a digital ecological agriculture integrated production and supply coordination system comprising a model establishment unit, a crop growth monitoring unit, a fertilizer reserve prediction unit, a reserve control unit and a supply management unit. According to the invention, plant growth data over the years is obtained through the model establishment unit to draw a historical average seedling height growth cycle curve graph, a reference is provided for subsequent crop growth monitoring, and the crop growth progress is monitored in real time through the crop growth monitoring unit. A fertilizer reserve prediction unit predicts a fertilization node of a current crop according to a historical fertilization node and an environmental influence factor, and then a reserve control unit monitors the fluctuation of a fertilizer price according to the predicted fertilization node and selects a proper price to purchase a required fertilizer in a purchase monitoring period. Therefore, the efficiency and sustainability of agricultural production are improved, and reasonable distribution of funds is realized.

Description

Technical Field

[0001] This invention relates to the field of agricultural management technology, and in particular to a digital ecological agricultural integrated production and supply coordination system. Background Technology

[0002] The Digital Ecological Agriculture Integrated Production and Supply Coordination System is a management platform based on modern information technology and ecological agriculture concepts, aiming to achieve intelligent, precise, and efficient management of the entire agricultural production process. This system links all aspects of agricultural planting, management, and sales through digital technology, forming a coordinated and unified ecological agricultural production system. First, the system uses big data technology to monitor and analyze information such as climate, soil, crop growth status, and market demand in real time, providing farmers with scientific decision-making support. Through IoT technology, sensors can collect field data in real time, such as soil moisture, temperature, and nutrient content, helping farmers understand crop needs and make timely adjustments to water and fertilizer management and pest and disease control. Furthermore, the use of blockchain technology can improve the transparency and traceability of the supply chain, ensuring that every step of agricultural products from production to sales can be verified, increasing consumer trust. The system can also achieve intelligent scheduling; through predictive analysis, it can optimize resource allocation, such as optimizing planting and harvesting times, rationally allocating transportation and storage, and reducing production waste.

[0003] Existing digital ecological agriculture integrated production and supply coordination systems generally monitor crop growth status and formulate harvesting, processing, and storage plans based on this status. By rationally allocating resources and human resources, they can improve planting efficiency. However, because these systems cannot monitor fertilizer price fluctuations based on the fertilization cycle of the crops, they can only purchase the required fertilizers directly based on fertilization needs. This results in the inability to choose the appropriate time to purchase fertilizers based on crop growth status and market fertilizer prices, leading to high fertilizer purchase prices and low efficiency in the use of idle funds.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to: draw historical average seedling height growth cycle curves by acquiring plant growth data from previous years, providing a benchmark for subsequent crop growth monitoring; monitor crop growth progress in real time through a crop growth monitoring unit; predict current crop fertilization points based on historical fertilization points and environmental impact factors through a fertilizer reserve prediction unit; and monitor fertilizer price fluctuations based on predicted fertilization points, and purchase the required fertilizer at an appropriate price during the monitoring period, thereby improving the efficiency and sustainability of agricultural production and achieving rational resource allocation.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a digital ecological agriculture integrated production and supply coordination system, comprising a model building unit, a crop growth monitoring unit, a fertilizer reserve prediction unit, a reserve control unit, and a supply management unit;

[0007] The model building unit is used to acquire several sets of plant growth data of target plants in ecological agriculture over the years. The plant growth data includes total planting cycle, crop height data, collection nodes and historical fertilization nodes. Based on the plant growth data, a historical average seedling height growth cycle curve is drawn.

[0008] The crop growth monitoring unit is used to acquire real-time crop height data of the target plant in ecological agriculture, and calculate the difference in crop height data based on the historical average seedling height growth cycle curve. Then, it acquires comprehensive data of the environment in which the target plant is located, and calculates environmental impact factors based on the difference in plant height and sends them to the fertilizer reserve prediction unit.

[0009] The fertilizer reserve prediction unit is used to obtain historical fertilization points, calculate the fertilization points for the current year based on environmental impact factors, preset the purchase monitoring period based on the fertilization points for the current year, and send the data to the reserve control unit.

[0010] The reserve control unit is used to obtain fertilizer market price information in real time during the purchase monitoring period Dm through an integrated data interface, and to obtain the historical price data set of fertilizer in the previous year. It analyzes the fluctuations of historical price data to set purchase thresholds, compares the real-time market price with the purchase threshold, and generates a purchase signal when the market price is lower than the purchase threshold and sends it to the supply management unit.

[0011] After obtaining the purchase signal, the supply management unit obtains the purchase time based on the purchase signal and completes the fertilizer purchase operation based on the purchase time.

[0012] The specific process for plotting the historical average seedling height growth cycle curve is as follows:

[0013] S101. Obtain several sets of historical plant growth data of target plants in ecological agriculture from the website of the agricultural and rural affairs department.

[0014] S102. Establish a standard two-dimensional coordinate system with the total planting cycle T as the horizontal axis and the crop plant height data Ht as the vertical axis. After averaging several sets of crop plant height data Htn, the average crop plant height data Htp is obtained.

[0015] S103. Based on the data collected at node t, mark the corresponding average plant height data Htp on the standard two-dimensional coordinate system to obtain several corresponding plant height marking points. Connect the plant height marking points one by one to obtain the historical average seedling height growth cycle curve P1.

[0016] The specific monitoring process of the crop growth monitoring unit is as follows:

[0017] S201. Based on the collection node t in the plant growth data of previous years, set the collection node t′ for the current year. Similarly, build a real-time two-dimensional coordinate system with the total planting cycle T′ of the current year as the horizontal axis and the crop height data Ht as the vertical axis. The total planting cycle T′ of the current year is the same as the total planting cycle T.

[0018] S202. Based on the acquisition node t′, obtain the real-time crop height data Ht of the target plant in ecological agriculture in the current year through the scale method, and mark the corresponding real-time crop height data Ht on the real-time two-dimensional coordinate system according to the acquisition node t′.

[0019] S203. Calculate the difference in plant height ΔH = |Ht - Htp| based on the real-time crop plant height data Ht and the corresponding average crop plant height data Htp.

[0020] S204. At the time corresponding to the acquisition node t′, acquire comprehensive data of the environment in which the target plant is located. The comprehensive data includes soil moisture data Rh, soil temperature data Tt, and soil nutrient coefficient Ht.

[0021] S205. Calculate the environmental impact factor Ep according to the following formula: Where e1, e2, and e3 are preset scaling factors;

[0022] S205. Obtain historical fertilization nodes Kh, and calculate the current year's fertilization node Khe based on the environmental impact factor Ep: Kh′ is the reference fertilization node for the historical fertilization node Kh, i = 1, 2, 3, ..., n, where n is the number of historical fertilization nodes Kh.

[0023] The specific process for calculating the soil nutrient index Ht is as follows:

[0024] Soil samples were collected from the planting environment of the target plants in ecological agriculture. The collected soil samples were placed in a well-ventilated place to dry naturally. The soil samples were crushed using a grinding tool and sieved through a sieve. The processed soil samples were then sent to the laboratory and the element content data in the soil were determined by chromatography. The element content data included the nitrogen content (N), phosphorus content (P), and potassium content (K) in the soil.

[0025] Calculate the soil nutrient coefficient Ht using the following formula:

[0026]

[0027] The specific forecasting process of the fertilizer reserve forecasting unit is as follows:

[0028] S301. Obtain the fertilization node Khe for the current year, and calculate the transportation and storage period Dmb(Khe-T1, Khe-T2) based on the preset transportation and storage period Y1(T1, T2).

[0029] S302. Obtain the preset preparation period Y2(T3,T4) and calculate the purchase monitoring period Dm(Khe-T1-T3, Khe-T2-T4).

[0030] The specific monitoring process of the reserve control unit is as follows:

[0031] S401. Obtain the historical price data set N of the fertilizer required for the target plant species in the current year through the agricultural trading website, obtain the purchase monitoring period Dm, set the price reference period of the previous year based on the purchase monitoring period Dm, and find the reference price data set M within the price reference period of the previous year based on the historical price data set N.

[0032] S402. Input the reference price data set M into the Prophet time series model to obtain the estimated highest price fluctuation value Da and the lowest price fluctuation value Db of the fertilizer required for the target plant species in the current year during the purchase monitoring period Dm.

[0033] S403. Preset the safety percentage Dc, and obtain the highest price fluctuation value Da and the lowest price fluctuation value Db. Calculate the purchase threshold Dma according to the following formula:

[0034] S404. During the purchase monitoring period Dm, monitor the real-time price data of fertilizer required for the target plant species in the current year according to the purchase threshold Dma. When the real-time price data is lower than the purchase threshold Dma, generate a purchase signal and send it to the supply management unit.

[0035] From S405 to Khe-T2-T4, if the real-time price data is never lower than the purchase threshold Dma, a purchase signal will be generated and sent to the supply management unit.

[0036] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0037] This digital ecological agriculture integrated production and supply coordination system uses a model building unit to draw historical average seedling height growth cycle curves based on plant growth data from previous years, providing a benchmark for subsequent crop growth monitoring. A crop growth monitoring unit then monitors crop growth progress in real time. A fertilizer reserve prediction unit predicts current fertilization points based on historical fertilization dates and environmental impact factors. Finally, a reserve control unit monitors fertilizer price fluctuations based on the predicted fertilization dates and purchases the necessary fertilizer at an appropriate price during the monitoring period, thereby improving agricultural production efficiency and sustainability and achieving rational allocation of funds. Attached Figure Description

[0038] Figure 1 A schematic diagram of the system modules of the present invention is shown. Detailed Implementation

[0039] 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0040] like Figure 1 As shown, a digital ecological agriculture integrated production and supply coordination system includes a model building unit, a crop growth monitoring unit, a fertilizer reserve prediction unit, a reserve control unit, and a supply management unit.

[0041] The model building unit is used to acquire several sets of plant growth data of target plants in ecological agriculture over the years. The plant growth data includes total planting cycle, crop height data, collection nodes and historical fertilization nodes. Based on the plant growth data, a historical average seedling height growth cycle curve is drawn.

[0042] The specific process for plotting the historical average seedling height growth cycle curve is as follows:

[0043] S101. Obtain several sets of historical plant growth data of target plants in ecological agriculture from the website of the agricultural and rural affairs department.

[0044] Taking corn as the target crop for the year as an example, the plant growth data of corn in ecological agriculture can be obtained through the website of the agricultural and rural affairs department. If multiple different types of crops are planted at the same time, multiple plant growth data for each crop can be obtained.

[0045] S102. Establish a standard two-dimensional coordinate system with the total planting cycle T as the horizontal axis and the crop plant height data Ht as the vertical axis. After averaging several sets of crop plant height data Htn, the average crop plant height data Htp is obtained.

[0046] S103. According to the data collection node t, mark the corresponding average plant height data Htp on the standard two-dimensional coordinate system one by one to obtain several corresponding plant height marking points. Connect the plant height marking points one by one to obtain the historical average seedling height growth cycle curve P1.

[0047] The crop growth monitoring unit is used to acquire real-time crop height data of the target plant in ecological agriculture, and calculate the difference in crop height data based on the historical average seedling height growth cycle curve. Then, it acquires comprehensive data of the environment in which the target plant is located, and calculates environmental impact factors based on the difference in plant height and sends them to the fertilizer reserve prediction unit.

[0048] Based on the collection node t in the plant growth data of previous years, the collection node t′ of the current year is set. Similarly, a real-time two-dimensional coordinate system is built with the total planting cycle T′ of the current year as the horizontal axis and the crop height data Ht as the vertical axis. The total planting cycle T′ of the current year is the same as the total planting cycle T.

[0049] The specific monitoring process of the crop growth monitoring unit is as follows:

[0050] Based on the data collection node t′, the real-time crop height data Ht of the target plant in ecological agriculture for the current year is obtained by the scale method. Based on the data collection node t′, the corresponding real-time crop height data Ht is marked on the real-time two-dimensional coordinate system one by one.

[0051] The difference in plant height ΔH = |Ht-Htp| is calculated based on the real-time crop plant height data Ht and the corresponding average crop plant height data Htp.

[0052] At the time corresponding to the acquisition node t′, comprehensive data of the environment in which the target plant is located is acquired. The comprehensive data includes soil moisture data Rh, soil temperature data Tt, and soil nutrient coefficient Ht.

[0053] Soil moisture data Rh can be detected using resistive soil moisture sensors EC-5 and SM300. By inserting the resistive soil moisture sensor into the soil, it directly contacts the soil and measures the soil moisture data Rh of the target plant species in that year.

[0054] Soil temperature data Tt can be detected using the DS18B20 soil temperature sensor. The sensor is buried in the soil at a depth that is consistent with the depth of the rootstock of the target plant in the soil that year, thereby measuring the soil temperature data Tt of the target plant in that year.

[0055] Calculate the environmental impact factor Ep using the following formula: Where e1, e2, and e3 are preset scaling factors;

[0056] Obtain historical fertilization nodes Kh, and calculate the current year's fertilization node Khe based on the environmental impact factor Ep: Kh′ is the reference fertilization node for the historical fertilization node Kh, i = 1, 2, 3, ..., n, where n is the number of historical fertilization nodes Kh;

[0057] Soil samples were collected in containers within the target plant growing environment of ecological agriculture. The collected soil samples were placed in a well-ventilated place to allow them to dry naturally. The soil samples were then crushed using a grinding tool and sieved using a sieve to remove larger particles and impurities, retaining fine soil particles smaller than 2 mm. The processed soil samples were then sent to a laboratory to determine the elemental content data of the soil using chromatography. The elemental content data included the nitrogen content (N), phosphorus content (P), and potassium content (K) in the soil.

[0058] Calculate the soil nutrient coefficient Ht using the following formula:

[0059]

[0060] The fertilizer reserve prediction unit is used to obtain historical fertilization points, calculate the fertilization points for the current year based on environmental impact factors, preset the purchase monitoring period based on the fertilization points for the current year, and send the data to the reserve control unit.

[0061] The specific forecasting process for the fertilizer reserve forecasting unit is as follows:

[0062] S301. Obtain the fertilization node Khe for the current year, and calculate the transportation and storage period Dmb(Khe-T1, Khe-T2) based on the preset transportation and storage period Y1(T1, T2).

[0063] The transportation and storage cycle Y1 can be preset by referring to the number of workers, the amount of fertilizer purchased, and the transportation time.

[0064] S302. Obtain the preset preparation period Y2(T3,T4) and calculate the purchase monitoring period Dm(Khe-T1-T3, Khe-T2-T4).

[0065] The reserve control unit is used to obtain fertilizer market price information in real time during the purchase monitoring period Dm through an integrated data interface, and to obtain the historical price data set of fertilizer in the previous year. It analyzes the fluctuations of historical price data to set purchase thresholds, compares the real-time market price with the purchase threshold, and generates a purchase signal when the market price is lower than the purchase threshold and sends it to the supply management unit.

[0066] The specific monitoring process of the reserve control unit is as follows:

[0067] S401. Obtain the historical price data set N of the fertilizer required for the target plant species in the current year through the agricultural trading website, obtain the purchase monitoring period Dm, set the price reference period of the previous year based on the purchase monitoring period Dm, and find the reference price data set M within the price reference period of the previous year based on the historical price data set N.

[0068] S402. Input the reference price data set M into the Prophet time series model to obtain the estimated highest price fluctuation value Da and the lowest price fluctuation value Db of the fertilizer required for the target plant species in the current year during the purchase monitoring period Dm.

[0069] The Prophet time series model, when applied to fertilizer price forecasting, can be expressed by the following formula:

[0070] y(t) = g(t) + s(t) + c(t) + ∈(t), where y(t) represents the predicted fertilizer price at time t, s(t) represents the seasonality term, which captures the periodic fluctuations in fertilizer prices, such as the seasonal changes in fertilizer demand caused by agricultural seasonal variations, c(t) represents the market supply and demand term, which reflects the impact of market supply and demand balance on fertilizer prices, including factors such as inventory levels, import volume, and export volume, and ∈(t) is the error term, which represents the random fluctuations that the model failed to capture. It is assumed to follow a Gaussian distribution and is used to measure the prediction accuracy of the model.

[0071] S403. Preset the safety percentage Dc, and obtain the highest price fluctuation value Da and the lowest price fluctuation value Db. Calculate the purchase threshold Dma according to the following formula:

[0072] When formulating procurement decisions, the safety percentage serves as an important reference indicator. By setting an acceptable range for price fluctuations, it helps growers control risk when facing market price volatility. The safety percentage (Dc) can be calculated using the following formula: Where Sf represents the grower's available funds, Sp represents the expected price fluctuation range, and Si represents the current remaining inventory;

[0073] S404. During the purchase monitoring period Dm, monitor the real-time price data of fertilizer required for the target plant species in the current year according to the purchase threshold Dma. When the real-time price data is lower than the purchase threshold Dma, generate a purchase signal and send it to the supply management unit.

[0074] From S405 to Khe-T2-T4, if the real-time price data is never lower than the purchase threshold Dma, a purchase signal will be generated and sent to the supply management unit.

[0075] After receiving the purchase signal, the supply management unit obtains the purchase time based on the purchase signal and completes the fertilizer purchase operation based on the purchase time.

[0076] This invention uses a model building unit to draw historical average seedling height growth cycle curves based on plant growth data from previous years, providing a benchmark for subsequent crop growth monitoring. A crop growth monitoring unit then monitors crop growth progress in real time. A fertilizer reserve prediction unit predicts current fertilization points based on historical fertilization dates and environmental impact factors. Finally, a reserve control unit monitors fertilizer price fluctuations based on the predicted fertilization dates and purchases the necessary fertilizer at an appropriate price during the monitoring period. This improves agricultural production efficiency and sustainability, and achieves rational allocation of funds.

[0077] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0078] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0079] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A digital ecological agricultural integrated production and supply coordination system, characterized in that: It includes a model building unit, a crop growth monitoring unit, a fertilizer reserve prediction unit, a reserve control unit and a supply management unit; The model building unit is used to obtain several groups of historical plant growth data of target plants in ecological agriculture, wherein the plant growth data includes the total planting cycle, crop plant height data, collection nodes and historical fertilization nodes, and a historical average seedling height growth cycle curve is drawn according to the plant growth data; The crop growth monitoring unit is used to obtain the real-time crop height data of the target plant in the current year in ecological agriculture, and calculate the plant height difference of the real-time crop height data according to the historical average seedling height growth cycle curve, and then obtain the comprehensive data of the environment in which the target plant is located, and calculate the environmental impact factor based on the plant height difference and send it to the fertilizer reserve prediction unit; The fertilizer reserve prediction unit is used to obtain historical fertilization nodes, calculate the fertilization nodes of the current year according to environmental impact factors, preset the purchase monitoring period according to the fertilization nodes of the current year and send it to the reserve control unit; The reserve control unit is used to obtain the price information of the fertilizer market in real time during the purchase monitoring period Dm through the integrated data interface, and obtain the historical price data set of the fertilizer in the previous year, analyze the fluctuation of the historical price data to set the purchase threshold, compare the real-time market price with the purchase threshold, and generate a purchase signal when the market price is lower than the purchase threshold and send it to the supply management unit; After obtaining the purchase signal, the supply management unit obtains the purchase time according to the purchase signal and completes the fertilizer purchase operation according to the purchase time.

2. The digital ecological agriculture integrated production and supply coordination system according to claim 1 is characterized in that: The specific process of drawing the historical average seedling height growth cycle curve is as follows: S101. Obtain several groups of historical plant growth data of target plants in ecological agriculture from the website of the agricultural and rural department; S102, establishing a standard two-dimensional coordinate system with the total planting cycle T as the horizontal coordinate and the crop plant height data Ht as the vertical coordinate, and performing average calculation on several groups of crop plant height data Htn to obtain average plant height data Htp; S103, marking the corresponding average plant height data Htp on the standard two-dimensional coordinate system one by one according to the collection node t, obtaining a number of corresponding plant height marking points, and connecting the plant height marking points one by one to obtain the historical average seedling height growth cycle curve graph P1.

3. The digital ecological agriculture integrated production and supply coordination system according to claim 1 is characterized in that: The specific monitoring process of the crop growth monitoring unit is as follows: S201, setting the current year's collection node t' according to the collection node t in the plant growth data of previous years, and also building a real-time two-dimensional coordinate system with the total planting cycle T' of the current year as the horizontal coordinate and the crop height data Ht as the vertical coordinate; S202, obtaining the real-time crop height data Ht of the target plant in the current year in ecological agriculture by using the ruler method according to the acquisition node t′, and marking the corresponding real-time crop height data Ht one by one on the real-time two-dimensional coordinate system according to the acquisition node t′; S203, calculating the plant height difference ΔH= according to the real-time crop plant height data Ht and the corresponding average plant height data Htp. | Ht-Htp | ; S204, acquiring comprehensive data of the environment in which the target plant is located at the time corresponding to the acquisition node t′, wherein the comprehensive data includes soil moisture data Rh, soil temperature data Tt and soil nutrient coefficient Ht; S205. Calculate the environmental impact factor Ep according to the following formula: Among them, e1, e2 and e3 are preset proportional coefficients; S205, obtain the historical fertilization node Kh, and calculate the fertilization node Khe of the current year according to the environmental impact factor Ep: Kh′ is the reference fertilization node of the historical fertilization node Kh, i=1, 2, 3, ..., n, and n is the number of historical fertilization nodes Kh.

4. The digital ecological agriculture integrated production and supply coordination system according to claim 1 is characterized in that: The specific process of calculating the soil nutrient coefficient Ht is as follows: Collect soil samples in the target plant planting environment of ecological agriculture, place the collected soil samples in a well-ventilated place to dry naturally, use a grinding tool to crush the soil samples and sieve them, then send the processed soil samples to the laboratory and determine the element content data in the soil by chromatography, the element content data includes the nitrogen content N in the soil, the phosphorus content P in the soil, and the potassium content K in the soil; Calculate the soil nutrient coefficient Ht according to the following formula:

5. The digital ecological agriculture integrated production and supply coordination system according to claim 1 is characterized in that: The specific prediction process of the fertilizer reserve prediction unit is as follows: S301, obtaining the fertilization node Khe of the current year, and calculating the transportation storage period Dmb(Khe-T1, Khe-T2) according to the preset transportation storage period Y1(T1, T2); S302, obtaining the preset pre-preparation period Y2 (T3, T4), and calculating the purchase monitoring period Dm (Khe-T1-T3, Khe-T2-T4).

6. The digital ecological agriculture integrated production and supply coordination system according to claim 1 is characterized in that: The specific monitoring process of the reserve control unit is as follows: S401, obtaining a historical price data set N of the fertilizer required for the target plant species of the current year from the previous year through an agricultural trading website, obtaining a purchase monitoring period Dm, and setting a price reference period for the previous year based on the purchase monitoring period Dm, and searching for a reference price data set M within the price reference period for the previous year based on the historical price data set N; S402, inputting the reference price data set M into the Prophet time series model to obtain the estimated maximum price fluctuation value Da and the minimum price fluctuation value Db of the fertilizer required for the target plant species in the purchase monitoring period Dm of the year; S403, preset the safety percentage Dc, obtain the maximum price fluctuation value Da and the minimum price fluctuation value Db, and calculate the purchase threshold Dma according to the following calculation formula: S404, monitoring the real-time price data of fertilizers required for the target plants of the year according to the purchase threshold Dma during the purchase monitoring period Dm, and when the real-time price data is lower than the purchase threshold Dma, generating a purchase signal and sending it to the supply management unit; S405 Until Khe-T2-T4, if the real-time price data is never lower than the purchase threshold Dma, a purchase signal is also generated and sent to the supply management unit.

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