Disclosure of Invention
In order to solve at least one of the above technical problems, the present invention provides a method, a system and a computer-readable storage medium for pasture management optimization.
In order to achieve the above object, a first aspect of the present invention provides a method for optimizing pasture management, the method including:
acquiring historical data related to pasture production and ecological factors;
inputting the historical data into an evaluation model for evaluation and analysis, and generating an evaluation result;
and generating a pasture management optimization scheme based on the evaluation result and displaying the scheme.
In this scheme, gather and acquire historical data about pasture production and ecological factor, specifically include:
calculating the grass yield of a pasture by a measuring method of the grass biomass, and calculating a CP value and an ME value which can be supplied according to the relation with standard hay; and/or
Acquiring the quantity of livestock of different functional groups, production performance indexes of related livestock, and CP values and ME values of the livestock of different functional groups; and/or
The economic effect of the pasture after a production process or a certain operation period is obtained.
In the scheme, the inputting the historical data into an evaluation model for evaluation analysis and generating an evaluation result specifically comprises:
evaluating and analyzing the grass and livestock balance from the levels of crude protein and metabolic energy, and generating a grass and livestock balance evaluation result; and/or
And establishing an evaluation system from both production and ecology, carrying out evaluation analysis on the grassland health according to the evaluation system, and generating a grassland health evaluation result.
In this embodiment, the method further includes:
according to profit formula
When the profit is the highest, the livestock capacity of the ecological economic pasture is calculated to be
Wherein p: price per animal product (Yuan)/kg); b: weight change (kg) per head of livestock as herding rate increases; m: meadow area (hm)
2) (ii) a x: pasture livestock capacity (SU); a: production potential (kg) of livestock; c: variable expenditure per head of livestock (yuan/head); EC: fixed expenditure per unit area (yuan/hm)
2)。
In this embodiment, the method further includes:
the method comprises the following steps of calculating the total livestock capacity in cold and warm seasons of a pasture by obtaining corresponding parameters, and calculating the number of various optimal herds in cold seasons according to the existing optimal proportion of breeding female livestock, optimal proportion of breeding male livestock, optimal proportion of breeding female livestock, the annual average herd lambing (calf) survival rate and equivalent animal conversion proportion of lambs and calves, wherein the specific formula is as follows:
the number of best breeding ewes in cold seasons is a1 × b1/(1+ c1 × d1 × b 1);
the number of the best breeding cows in cold seasons is a2 × b2/(1+ c2 × d2 × b 2);
the number of ram best bred in cold season is a1 × e1-c1 × e1 × d1 × f 1;
the number of the best bred bulls in cold seasons is a2 × e2-c2 × e2 × d2 × f 2;
the number of the ewes best bred in cold seasons is a1 Xg 1-d1 Xc 1 Xh 1 Xf 1;
the number of the cows which are best bred in cold seasons is a2 Xg 2-d2 Xc 2 Xh 2 Xf 2;
wherein a 1: optimal number of Sheep (SU) in the cold season field; b 1: the optimal proportion (%) of the breeding ewes; c1 lamb complete animal conversion coefficient; d 1: reproductive survival rate (%) of lambs; e 1: the optimal proportion (%) of the bred ram; g 1: the optimal proportion (%) of the bred ewes; h 1: the optimal proportion (%) of the bred ewes; f 1: optimally breeding ewe number (SU) in cold seasons;
a 2: optimal number of cattle (SU) in cold season; b2 optimal ratio (%) for breeding cows; c 2: calculating the conversion coefficient of the calves into livestock; d 2: calving reproductive activity (%); e 2: the optimal proportion (%) of the bred bulls; g 2: the optimal proportion (%) of the bred cows; h 2: the optimal proportion (%) of the bred cows; f 2: the best number of cows (SU) is bred in cold seasons.
In this scheme, the pasture management optimization scheme includes: herd capacity optimization schemes, artificial turf optimization schemes, and simultaneous artificial turf and herd capacity optimization schemes.
The second aspect of the present invention further provides a pasture management optimizing system, including: a memory and a processor, wherein the memory includes a pasture management optimization method program, and the pasture management optimization method program when executed by the processor implements the following steps:
acquiring historical data related to pasture production and ecological factors;
inputting the historical data into an evaluation model for evaluation and analysis, and generating an evaluation result;
and generating a pasture management optimization scheme based on the evaluation result and displaying the scheme.
In this scheme, gather and acquire historical data about pasture production and ecological factor, specifically include:
calculating the grass yield of a pasture by a measuring method of the grass biomass, and calculating a CP value and an ME value which can be supplied according to the relation with standard hay; and/or
Acquiring the quantity of livestock of different functional groups, production performance indexes of related livestock, and CP values and ME values of the livestock of different functional groups; and/or
The economic effect of the pasture after a production process or a certain operation period is obtained.
In the scheme, the inputting the historical data into an evaluation model for evaluation analysis and generating an evaluation result specifically comprises:
evaluating and analyzing the grass and livestock balance from the levels of crude protein and metabolic energy, and generating a grass and livestock balance evaluation result; and/or
And establishing an evaluation system from both production and ecology, carrying out evaluation analysis on the grassland health according to the evaluation system, and generating a grassland health evaluation result.
The third aspect of the present invention also provides a computer-readable storage medium, which includes a pasture management optimization method program, and when the program is executed by a processor, the method realizes the steps of the pasture management optimization method.
The method and the system perform objective evaluation around the aspects of the structure of the grasses and the livestock, the environmental capacity, the economic income and the like, provide an optimization scheme which gives consideration to the pasture income and the grassland ecological health for the pasture users according to the evaluation result, and facilitate the subsequent pasture management and operation of the pasture users according to the optimization scheme.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a flow chart of a pasture management optimization method of the invention.
As shown in fig. 1, a first aspect of the present invention provides a method for optimizing pasture management, where the method includes:
s102, acquiring historical data related to pasture production and ecological factors;
s104, inputting the historical data into an evaluation model for evaluation and analysis, and generating an evaluation result;
and S106, generating a pasture management optimization scheme based on the evaluation result and displaying the pasture management optimization scheme.
It should be noted that the technical solution of the present invention can be operated in a terminal device such as a PC, a mobile phone, a PAD, and the like.
It should be noted that the historical data may include any one or more of, but is not limited to, ranch environmental change data, market economic cycle fluctuation data, and ranch annual benefit data.
According to the embodiment of the invention, acquiring historical data related to pasture production and ecological elements specifically comprises the following steps:
calculating the grass yield of a pasture by a measuring method of the grass biomass, and calculating a CP value and an ME value which can be supplied according to the relation with standard hay; and/or
Acquiring the quantity of livestock of different functional groups, production performance indexes of related livestock, and CP values and ME values of the livestock of different functional groups; and/or
The economic effect of the pasture after a production process or a certain operation period is obtained.
It should be noted that the CP value is the nutrient value (yield protein) of livestock, the ME value is the energy value (metabolic energy) of livestock, and the natural pasture is one of the most important sources for obtaining forage from livestock. Pasture grass yield is calculated by adopting different methods, and available CP and ME are calculated according to the relation with standard hay. Specifically, the available CP and ME values can be calculated and generated by selecting grass type, selecting grass biomass measuring method (remote sensing measurement, field measurement, mathematical measurement) and combining the grass yield per unit area (g/m2) and the available grass area. The principle of mathematical measurement is to regard the grass layer as a rectangular entity with continuously changing height and density, apply the principle of calculus, regard the average height of grass group as independent variable, and calculate the biomass per unit area. The specific calculation formula is as follows:
in the above formula, W: yield per unit area (kg/hm 2); x: grass group average height; y: adjusting the coefficient; 1m is S2。
The formula for calculating the grassland pasture CP and ME is as follows:
warm season grassland cp (kg) ═ a × b × c × d × e × f;
warm season grassland me (mj) ═ a × b × c × d × i × f;
cold season grassland cp (kg) ═ a × g × h × d × e × f;
cold season grassland me (mj) ═ a × g × h × d × i × f;
in the above formula, a: grassy, edible grass yield (kg); b: utilization ratio (%) of warm-season forage grass; c: conversion rate of water content of pasture (warm season); d: the conversion coefficient of the standard hay in the warm season; e: protein content (%) in standard hay dry matter; f: standard hay dry matter percentage (%); g: utilization ratio (%) of cold-season pasture; h: conversion rate (%) of water content of pasture (cold season); i: metabolic energy content (MJ/kg) in standard hay dry matter.
The formula for calculating the cold shrubs CP and ME is as follows:
warm season shrub cp (kg) a × b × c × d × e × f;
warm season shrub me (mj) ═ a × b × c × d × g × f;
cold season shrub cp (kg) a × h × I × d × e × f;
cold season shrub me (mj) ═ a × h × I × d × g × f;
in the above formula, a: grassy edible shrub yield (kg); b: the utilization rate (%) of the warm season shrubs; c: conversion rate of water content of shrubs (warm season); d: the conversion coefficient of the standard hay in the warm season; e: protein content (%) in standard hay dry matter; f: standard hay dry matter percentage (%); g: metabolic energy content (MJ/kg) in standard hay dry matter; h: cold season shrub utilization (%); i: conversion rate of water content of shrub (cold season).
It should be noted that the artificial grassland is also one of the main sources of winter forage grass for livestock, and beef cattle feed can be divided into grass, green feed, silage feed, root tuber, tuber melon and fruit, agricultural by-products, cereals, beans, meals, bran and dregs. The sheep feed is divided into grass, green feed, silage, root tuber, tuber melon and fruit, tree leaf, root tuber, tuber stem, agricultural by-product, grain, bean, cake meal, sugar bran, and dregs. In addition, outsourcing forage and concentrate are also one of the main sources of winter feed for livestock.
It should be noted that the number of livestock with different functional groups and the production performance index of the related livestock are obtained as the data source for the later optimization. Therefore, indexes such as the monthly body weight (calculating the daily gain), the gestation period, the daily lactation yield (DLN), the lambing rate and the like of the livestock of related functional groups need to be recorded. Obtains the nutrition (CP) and energy (ME) demand of livestock with different functional groups.
According to the embodiment of the invention, the inputting of the historical data into an evaluation model for evaluation analysis and generating of an evaluation result specifically comprises:
evaluating and analyzing the grass and livestock balance from the levels of crude protein and metabolic energy, and generating a grass and livestock balance evaluation result; and/or
And establishing an evaluation system from both production and ecology, carrying out evaluation analysis on the grassland health according to the evaluation system, and generating a grassland health evaluation result.
It should be noted that the contents of the model evaluation may include the breeding stock production configuration, the farm stock capacity, the forage balance, the lawn health, and the farm returns. But is not limited thereto.
It is to be noted that the core of the grassland animal husbandry is to apply all physical and chemical and active labor and natural energy to livestock, and to produce more livestock and obtain income without damaging the environment. This requires the livestock species and herd structure of the livestock to be rational, and therefore internal and external factors such as livestock breeding characteristics, forage resources, labor, capital, technology, market direction, policy, etc. must be considered, ultimately reflecting the virtuous circle and economic benefits of the ecological economic system of the grassland animal husbandry.
It should be noted that a certain herd livestock capacity is the basis for forming a home pasture, while a suitable herd livestock capacity is the basis for obtaining the maximum economic benefit on the premise of realizing the virtuous cycle of pasture ecology. Appropriate pasture stock capacity must take into account factors such as meadow resources, stock quantity, market price, disposable resources, and the like. Based on the factors, the invention also provides an ecological and economic optimal pasture livestock capacity model.
According to an embodiment of the invention, the method further comprises:
profit formula based on ecological economy optimal pasture livestock capacity model
When the profit is the highest, the livestock capacity of the ecological economic pasture is calculated to be
Wherein p: price per animal product (yuan/kg); b: weight change (kg) per head of livestock as herding rate increases; m: meadow area (hm)
2) (ii) a x: pasture livestock capacity (SU); a: production potential (kg) of livestock; c: variable expenditure per head of livestock (yuan/head); EC: fixed expenditure per unit area (yuan/hm)
2)。
It is to be noted that the ecological livestock capacity
Can be compared to know
The eco-economical livestock capacity is thus much smaller than the eco-economical livestock capacity, which is the livestock capacity with the highest economic benefit in the pasture and with ecological stability of the grassland not being affected by excessive pasturing.
According to an embodiment of the invention, the method further comprises:
the method comprises the steps of calculating the total livestock capacity in cold and warm seasons of a pasture by obtaining corresponding parameters, and meanwhile calculating the number of various optimal herds in cold seasons according to the existing optimal proportion of breeding female livestock, optimal proportion of breeding male livestock, optimal proportion of breeding female livestock, the annual average herd lamb (calf) survival rate and the equivalent animal conversion proportion of lambs and calves in cold seasons, so that reasonable planning is made for herds when the herds go out of the pastures. The concrete formula is as follows:
the number of best breeding ewes in cold seasons is a1 × b1/(1+ c1 × d1 × b 1);
the number of the best breeding cows in cold seasons is a2 × b2/(1+ c2 × d2 × b 2);
the number of ram best bred in cold season is a1 × e1-c1 × e1 × d1 × f 1;
the number of the best bred bulls in cold seasons is a2 × e2-c2 × e2 × d2 × f 2;
the number of the ewes best bred in cold seasons is a1 Xg 1-d1 Xc 1 Xh 1 Xf 1;
the number of cows best bred in cold season is a2 Xg 2-d2 Xc 2 Xh 2 Xf 2.
Wherein a 1: optimal number of Sheep (SU) in the cold season field; b 1: the optimal proportion (%) of the breeding ewes; c1 lamb complete animal conversion coefficient; d 1: reproductive survival rate (%) of lambs; e 1: the optimal proportion (%) of the bred ram; g 1: the optimal proportion (%) of the bred ewes; h 1: the optimal proportion (%) of the bred ewes; f 1: optimally breeding ewe number (SU) in cold seasons;
a 2: optimal number of cattle (SU) in cold season; b2 optimal ratio (%) for breeding cows; c 2: calculating the conversion coefficient of the calves into livestock; d 2: calving reproductive activity (%); e 2: the optimal proportion (%) of the bred bulls; g 2: the optimal proportion (%) of the bred cows; h 2: the optimal proportion (%) of the bred cows; f 2: the best number of cows (SU) is bred in cold seasons.
According to an embodiment of the present invention, the pasture management optimization scheme includes: herd capacity optimization schemes, artificial turf optimization schemes, and simultaneous artificial turf and herd capacity optimization schemes.
It should be noted that the herd capacity optimization scheme is an optimization of the livestock structure and the major economic herd of the pasture. According to the income conditions of all the livestock and poultry, the method helps a pasture owner to eliminate the livestock and poultry with negative income, and ensures the effective allocation of forage grass resources. The herd number of the primary economic herd may be increased, decreased or unchanged. The number of animals to be increased is increased by default to the sheep unit increase criteria. The reduced number is needed to optimize dam population conditions and productivity (reasonable numbers of sires in most farms). The invention adopts a scoring method, the maximum value standardization is carried out on 4 indexes of daily gain, lambing rate, age and daily lactation amount of all breeding female animals (pregnant female animals and lactating female animals), then the weights are respectively given, the obtained values are sorted from large to small, and the calculation formula of an evaluation model is as follows:
G=a1×L+a2×M+a3×A+a4×W;
in the above formula, L: the annual average lambing rate standardization value; m: the standard value of milk yield of the yearly average day; a: an age normalized value; w: average daily gain normalized value.
a1, a2, a3 and a4 are weight values which are sequentially assigned as 0.4, 0.3, 0.2 and 0.1, and the aims of accurate management are fulfilled by eliminating female animals with lower scores, so that the herd is helped to optimize the overall quality of the herd.
Since changes in the number of herds affect the CP and ME values supplied by natural turf grass, the CP and ME supply of natural and artificial turf grass must be modified for re-evaluation of the grass balance.
The calculation formula is as follows:
the demand (kg) of the warm-season CP is (a1 × 4+ a2) × a3/1000 × a 4;
the requirement (MJ) for the warm season ME is (a1 × 4+ a2) × a5 × a 4;
supply (kg) of warm-season CP as a6 × u 3;
supply (MJ) of warm season ME a7 × u 4;
supply (MJ) of warm season ME a7 × u 4;
in the above formula, a 1: warm season cattle herd capacity (SU); a 2: warm season sheep herd capacity (SU); a 3: daily CP requirement (g) of sheep; a 4: warm season days (d); a 5: daily ME demand (MJ) for sheep; a 6: evaluating the CP supply value (kg) of the natural pasture in the warm season; u 3: warm season forage grass CP parameters; a 7: evaluating the ME supply value (MJ) of the warm-season natural pasture inside; u 4: ME parameters of warm-season pasture;
the cold season CP requirement (kg) ((b 1 × 4+ b2) × b3/1000 × b 4)
Requirement (MJ) of cold season ME ═ b1 × 4+ b2 × b5 × b4
Supply (kg) of cold season CP b6 × u1+ b7 × u5
Supply (MJ) of cold season ME b8 × u2+ b9 × u6
In the above formula, b 1: cold season cattle herd capacity (SU); b 2: cold-season sheep herd capacity (SU); b 3: daily CP requirement (g) of sheep; b 4: cold season days (d); b 5: daily ME demand (MJ) for sheep; b 6: evaluating the CP supply value (kg) of the natural pasture in the cold season; u 1: cold season pasture CP parameters: b 7: the CP supply value (kg) of the artificial pasture in the cold season; u 5: cold season artificial pasture CP parameters; b 8: evaluating the ME supply value (MJ) of the inside cold-season natural pasture; u 2: ME parameters of the cold season pasture; b 9: ME supply value (MJ) of artificial pasture in cold season; u 6: ME parameters of the artificial pasture in cold seasons;
the optimized supplementary feeding is supplementary for achieving the balance of the grasses and the livestock. And carrying out planning solution by adopting a nonlinear GRG planning solution method. The user needs to fill in the parameters of dry matter (%), dry matter protein (%), dry matter sugar (%), dry matter fat (%), price (Yuan/kg) of the available supplementary feed, and the optimal supplementary feed scheme is obtained through the related conversion formulas (1g protein is 4kcal, 1g sugar is 4kcal, 1g fat is 9kcal, and metabolic energy is 0.82 times digestive energy).
And according to the income and expenditure table of the pasture, the user fills the optimized value according to the income and expenditure before optimization and the possible change after optimization, and calculates according to the optimization effectiveness to obtain whether the pasture is optimized and effective. And (3) calculating the optimization effectiveness of the pasture:
if the pure income of the pasture after optimization-the pure income of the pasture before optimization is more than 0, the optimization is effective.
And if the pure income of the pasture after optimization-the pure income of the pasture before optimization is less than 0, the optimization is invalid.
It should be noted that, the artificial grassland optimization scheme is to use the artificial grassland as the entry point, optimizes from the technology (seeding mode, seeding time and fertilizing amount, etc.) that the artificial grassland was planted and 2 aspect of the different processing modes (drying, storage, etc.) of forage grass, not only can plant ripe forage grass, processing scientific research achievement applies to the practice, turns into actual productivity, improves herdsman economic income, and can alleviate the burden on natural grassland, be favorable to the grassland to rest and keep alive and ecological restoration. The supply of artificial grasses CP and ME varied and the balance of grasses and animals should be reevaluated.
The concrete re-evaluation calculation formula of the grass and livestock balance is as follows:
evaluating the CP requirement value of the livestock in the warm season in terms of the CP requirement (kg) of the livestock in the warm season;
evaluating the ME requirement value of the internal warm-season livestock in the warm season (MJ);
evaluating the supply (kg) of the CP of the warm-season natural pasture in the greenhouse;
the supply (MJ) of the ME in the warm season is evaluated as the supply value of the ME of the natural pasture in the warm season;
evaluating the CP requirement value of the internal cold-season livestock in kg;
evaluating the ME demand value of the internal cold-season livestock in cold season (MJ);
evaluating the supply (kg) of the cold season CP, namely evaluating the supply value of the cold season natural pasture CP inside, evaluating the supply value of the cold season artificial pasture CP inside, and optimizing the added value of the artificial pasture CP;
and (3) evaluating the supply value of the internal cold-season natural pasture ME, evaluating the supply value of the internal cold-season artificial pasture ME, and increasing the value of the optimized artificial pasture ME.
It should be noted that the simultaneous optimization of the artificial grassland and the stock herd capacity is based on the optimization of grasses and livestock, and the grass yield of the artificial grassland is improved by adjusting the reasonable herd structure and the livestock capacity on the premise of maintaining and restoring the grassland ecology, so that the income of herdsmen is increased.
The change in the stock seed capacity affects the CP and ME values supplied to the natural grassland and the artificial grassland, and the CP and ME values supplied to the livestock are also increased after the artificial grassland is optimized, so that it is necessary to modify the supply change coefficients of the CP and ME of the natural grassland and the artificial grassland and to re-evaluate the subsequent balance of the grassland and the artificial grassland.
The concrete re-evaluation calculation formula of the grass and livestock balance is as follows:
the demand (kg) of the warm-season CP is (a1 × 4+ a2) × a3/1000 × a 4;
the requirement (MJ) for the warm season ME is (a1 × 4+ a2) × a4 × a 5;
supply (kg) of warm-season CP as a6 × u 3;
supply (MJ) of warm season ME a7 × u 4;
in the above formula, a 1: warm season cattle herd capacity (SU); a 2: warm season sheep herd capacity (SU); a 3: daily CP requirement (g) of sheep; a 4: warm season days (d); a 5: daily ME demand (MJ) for sheep; a 6: evaluating the CP supply value (kg) of the natural pasture in the warm season; u 3: warm season forage grass CP parameters; a 7: evaluating the ME supply value (MJ) of the warm-season natural pasture inside; u 4: ME parameters of warm-season pasture;
the demand (kg) of the cold season CP is (b1 × 4+ b2) × b3/1000 × b 4;
the demand (MJ) for the cold season ME is (b1 × 4+ b2) × b5 × b 4;
supply (kg) of cold season CP b6 × u1+ b7 × u5+ b 8;
supply (MJ) of cold season ME b9 × u2+ b10 × u6+ b 11;
in the above formula, b 1: cold season cattle herd capacity (SU); b 2: cold-season sheep herd capacity (SU); b 3: daily CP requirement (g) of sheep; b 4: cold season days (d); b 5: daily ME demand (MJ) for sheep; b 6: evaluating the CP supply value (kg) of the natural pasture in the cold season; u 1: cold season pasture CP parameters; b 7: evaluating the CP supply (kg) of the artificial pasture in the cold season; u 5: cold season artificial pasture CP parameters; b 8: the CP value (kg) of the optimized pasture is increased; b 9: evaluating the ME supply value (MJ) of the inside cold-season natural pasture; u 2: ME parameters of the cold season pasture; b 10: evaluating the ME supply value (MJ) of the cold-season internal artificial pasture; u 6: ME parameters of the artificial pasture in cold seasons; b 11: and adding value (MJ) to the optimized pasture ME.
Fig. 2 shows a block diagram of a pasture management optimization system of the present invention.
As shown in fig. 2, the second aspect of the present invention further provides a pasture management optimizing system 2, where the pasture management optimizing system 2 includes: a memory 21 and a processor 22, wherein the memory includes a pasture management optimization method program, and when executed by the processor, the method realizes the following steps:
acquiring historical data related to pasture production and ecological factors;
inputting the historical data into an evaluation model for evaluation and analysis, and generating an evaluation result;
and generating a pasture management optimization scheme based on the evaluation result and displaying the scheme.
It should be noted that the system of the present invention can be operated in a terminal device such as a PC, a mobile phone, a PAD, etc.
It should be noted that the Processor may be a Central Processing Unit (CPU), other general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It should be noted that the system may further include a display, and the display may be referred to as a display screen or a display unit. In some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an Organic Light-Emitting Diode (OLED) touch panel, or the like. The display is used to display information processed in the system, the generated pasture management optimization plan, and a work interface for displaying visualizations.
According to the embodiment of the invention, acquiring historical data related to pasture production and ecological elements specifically comprises the following steps:
calculating the grass yield of a pasture by a measuring method of the grass biomass, and calculating a CP value and an ME value which can be supplied according to the relation with standard hay; and/or
Acquiring the quantity of livestock of different functional groups, production performance indexes of related livestock, and CP values and ME values of the livestock of different functional groups; and/or
The economic effect of the pasture after a production process or a certain operation period is obtained.
According to the embodiment of the invention, the inputting of the historical data into an evaluation model for evaluation analysis and generating of an evaluation result specifically comprises:
evaluating and analyzing the grass and livestock balance from the levels of crude protein and metabolic energy, and generating a grass and livestock balance evaluation result; and/or
And establishing an evaluation system from both production and ecology, carrying out evaluation analysis on the grassland health according to the evaluation system, and generating a grassland health evaluation result.
According to an embodiment of the present invention, when executed by the processor, the pasture management optimization method further includes:
according to profit formula
When the profit is the highest, the livestock capacity of the ecological economic pasture is calculated to be
Wherein p: price per animal product (yuan/kg); b: weight change (kg) per head of livestock as herding rate increases; m: meadow area (hm)
2) (ii) a x: pasture livestock capacity (SU); a: production potential (kg) of livestock; c: variable expenditure per head of livestock (yuan/head); EC: fixed expenditure per unit area (yuan/hm)
2);
According to an embodiment of the present invention, the pasture management optimization method program further realizes the following steps when executed by the processor.
The method comprises the following steps of calculating the total livestock capacity in cold and warm seasons of a pasture by obtaining corresponding parameters, and calculating the number of various optimal herds in cold seasons according to the existing optimal proportion of breeding female livestock, optimal proportion of breeding male livestock, optimal proportion of breeding female livestock, the annual average herd lambing (calf) survival rate and equivalent animal conversion proportion of lambs and calves, wherein the specific formula is as follows:
the number of best breeding ewes in cold seasons is a1 × b1/(1+ c1 × d1 × b 1);
the number of the best breeding cows in cold seasons is a2 × b2/(1+ c2 × d2 × b 2);
the number of ram best bred in cold season is a1 × e1-c1 × e1 × d1 × f 1;
the number of the best bred bulls in cold seasons is a2 × e2-c2 × e2 × d2 × f 2;
the number of the ewes best bred in cold seasons is a1 Xg 1-d1 Xc 1 Xh 1 Xf 1;
the number of the cows which are best bred in cold seasons is a2 Xg 2-d2 Xc 2 Xh 2 Xf 2;
wherein a 1: optimal number of Sheep (SU) in the cold season field; b 1: the optimal proportion (%) of the breeding ewes; c1 lamb complete animal conversion coefficient; d 1: reproductive survival rate (%) of lambs; e 1: the optimal proportion (%) of the bred ram; g 1: the optimal proportion (%) of the bred ewes; h 1: the optimal proportion (%) of the bred ewes; f 1: optimally breeding ewe number (SU) in cold seasons;
a 2: optimal number of cattle (SU) in cold season; b2 optimal ratio (%) for breeding cows; c 2: calculating the conversion coefficient of the calves into livestock; d 2: calving reproductive activity (%); e 2: the optimal proportion (%) of the bred bulls; g 2: the optimal proportion (%) of the bred cows; h 2: the optimal proportion (%) of the bred cows; f 2: the best number of cows (SU) is bred in cold seasons.
Preferably, the pasture management optimization scheme includes: herd capacity optimization schemes, artificial turf optimization schemes, and simultaneous artificial turf and herd capacity optimization schemes.
The third aspect of the present invention also provides a computer-readable storage medium, which includes a pasture management optimization method program, and when the program is executed by a processor, the method realizes the steps of the pasture management optimization method.
The method and the system perform objective evaluation around the aspects of the structure of the grasses and the livestock, the environmental capacity, the economic income and the like, provide an optimization scheme which gives consideration to the pasture income and the grassland ecological health for the pasture users according to the evaluation result, and facilitate the subsequent pasture management and operation of the pasture users according to the optimization scheme.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.