CN110956404A - Pasture management optimization method, system and computer-readable storage medium - Google Patents
Pasture management optimization method, system and computer-readable storage medium Download PDFInfo
- Publication number
- CN110956404A CN110956404A CN201911236250.4A CN201911236250A CN110956404A CN 110956404 A CN110956404 A CN 110956404A CN 201911236250 A CN201911236250 A CN 201911236250A CN 110956404 A CN110956404 A CN 110956404A
- Authority
- CN
- China
- Prior art keywords
- pasture
- livestock
- evaluation
- bred
- cold
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000005457 optimization Methods 0.000 title claims abstract description 78
- 238000000034 method Methods 0.000 title claims abstract description 53
- 238000003860 storage Methods 0.000 title claims abstract description 16
- 244000144972 livestock Species 0.000 claims abstract description 111
- 238000011156 evaluation Methods 0.000 claims abstract description 71
- 238000007726 management method Methods 0.000 claims abstract description 55
- 238000004519 manufacturing process Methods 0.000 claims abstract description 44
- 238000004458 analytical method Methods 0.000 claims abstract description 19
- 230000036541 health Effects 0.000 claims abstract description 16
- 238000013210 evaluation model Methods 0.000 claims abstract description 14
- 239000013256 coordination polymer Substances 0.000 claims description 57
- 244000025254 Cannabis sativa Species 0.000 claims description 52
- 244000144980 herd Species 0.000 claims description 38
- 238000009395 breeding Methods 0.000 claims description 35
- 230000001488 breeding effect Effects 0.000 claims description 35
- 241000283690 Bos taurus Species 0.000 claims description 33
- 241001465754 Metazoa Species 0.000 claims description 25
- 238000006243 chemical reaction Methods 0.000 claims description 19
- 241001494479 Pecora Species 0.000 claims description 18
- 125000000524 functional group Chemical group 0.000 claims description 15
- 244000309466 calf Species 0.000 claims description 12
- 230000002503 metabolic effect Effects 0.000 claims description 10
- 239000002028 Biomass Substances 0.000 claims description 8
- 241000283903 Ovis aries Species 0.000 claims description 8
- 244000309464 bull Species 0.000 claims description 8
- 230000008859 change Effects 0.000 claims description 8
- 230000001850 reproductive effect Effects 0.000 claims description 8
- 230000004083 survival effect Effects 0.000 claims description 8
- 235000019750 Crude protein Nutrition 0.000 claims description 6
- 230000000694 effects Effects 0.000 claims description 6
- 235000019687 Lamb Nutrition 0.000 claims description 5
- 241000209504 Poaceae Species 0.000 abstract description 7
- 230000007613 environmental effect Effects 0.000 abstract description 5
- 239000004459 forage Substances 0.000 description 12
- 230000008901 benefit Effects 0.000 description 7
- 239000000047 product Substances 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 5
- 238000009304 pastoral farming Methods 0.000 description 5
- 230000008878 coupling Effects 0.000 description 4
- 238000010168 coupling process Methods 0.000 description 4
- 238000005859 coupling reaction Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 4
- 102000004169 proteins and genes Human genes 0.000 description 3
- 108090000623 proteins and genes Proteins 0.000 description 3
- 238000011867 re-evaluation Methods 0.000 description 3
- 244000241257 Cucumis melo Species 0.000 description 2
- 235000015510 Cucumis melo subsp melo Nutrition 0.000 description 2
- 235000010627 Phaseolus vulgaris Nutrition 0.000 description 2
- 244000046052 Phaseolus vulgaris Species 0.000 description 2
- FJJCIZWZNKZHII-UHFFFAOYSA-N [4,6-bis(cyanoamino)-1,3,5-triazin-2-yl]cyanamide Chemical compound N#CNC1=NC(NC#N)=NC(NC#N)=N1 FJJCIZWZNKZHII-UHFFFAOYSA-N 0.000 description 2
- 239000006227 byproduct Substances 0.000 description 2
- 235000013339 cereals Nutrition 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 235000013399 edible fruits Nutrition 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006651 lactation Effects 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 235000012054 meals Nutrition 0.000 description 2
- 238000010899 nucleation Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 244000144977 poultry Species 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000004460 silage Substances 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 241000196324 Embryophyta Species 0.000 description 1
- 235000015278 beef Nutrition 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 230000037396 body weight Effects 0.000 description 1
- 235000012970 cakes Nutrition 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000001079 digestive effect Effects 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 235000013336 milk Nutrition 0.000 description 1
- 239000008267 milk Substances 0.000 description 1
- 210000004080 milk Anatomy 0.000 description 1
- 235000015097 nutrients Nutrition 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 238000012946 outsourcing Methods 0.000 description 1
- 230000035935 pregnancy Effects 0.000 description 1
- 238000013077 scoring method Methods 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- 230000004584 weight gain Effects 0.000 description 1
- 235000019786 weight gain Nutrition 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/70—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in livestock or poultry
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/90—Financial instruments for climate change mitigation, e.g. environmental taxes, subsidies or financing
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Animal Husbandry (AREA)
- Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Marine Sciences & Fisheries (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Mining & Mineral Resources (AREA)
- Agronomy & Crop Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a pasture management optimization method, a system and a computer readable storage medium, wherein the method comprises 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. 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.
Description
Technical Field
The present invention relates to the field of animal husbandry, and in particular, to a method, system, and computer-readable storage medium for optimizing pasture management.
Background
Grass is one of the major ecosystems of the world, and many grass fields are now being recognized as playing a multi-functional role in the production of food and in the protection of farmlands, in environmental management and cultural inheritance. However, as the global population grows, turf area decreases with increasing numbers of livestock, animal product trade decreases and production efficiency varies, and the complexity of turf utilization can be addressed by developing better management.
At present, the research on the production mode optimization of the grassland animal husbandry mainly comprises the aspects of animal carrying rate, grazing mode, seasonal supplementary feeding, grazing grassland and grass cutting field utilization and the like. The grassland grazing system emphasizes 2 key links of grassland vegetation production and grazing production, realizes multi-path coupling through artificial optimization regulation and control, and releases the production potential of the grazing system in a multi-path way so as to obtain the net energy of the system or the maximum output of animal products. Within the complex ecosystem of the pasture, if it is very difficult to optimize each subsystem, the result of the optimal optimization is that there is no significant loss in production and ecosystem function, such as livestock weight gain management per unit area of grass is acceptable to the herdsmen. Forage resources in pastures vary constantly in time and space, which means that it is impractical to maintain optimum yield of the system for long periods of time, a real-world situation should be as close as possible to the point where the benefits of the system are maximized.
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.
Drawings
FIG. 1 is a flow chart of a pasture management optimization method of the present invention;
fig. 2 shows a block diagram of a pasture management optimization system of the present 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.
Claims (10)
1. A method for pasture management optimization, the method comprising:
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.
2. The pasture management optimization method according to claim 1, wherein the collecting and obtaining historical data about pasture production and ecological factors specifically comprises:
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.
3. The pasture management optimization method according to claim 1, wherein the historical data is input to an evaluation model for evaluation analysis, and an evaluation result is generated, and the method specifically comprises the following steps:
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.
4. The pasture management optimization method of claim 1, further comprising:
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)。
5. The pasture management optimization method of claim 4, wherein the method further comprises:
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.
6. The pasture management optimization method according to claim 1, wherein the pasture management optimization scheme comprises: herd capacity optimization schemes, artificial turf optimization schemes, and simultaneous artificial turf and herd capacity optimization schemes.
7. A pasture management optimization system, comprising: 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.
8. The pasture management optimization system according to claim 7, wherein the collecting and obtaining historical data about pasture production and ecological factors specifically comprises:
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.
9. The pasture management optimization system according to claim 7, wherein the historical data is input to an evaluation model for evaluation analysis and evaluation result generation, and the evaluation result generation specifically includes:
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.
10. A computer-readable storage medium, characterized in that it comprises a pasture management optimization method program which, when executed by a processor, carries out the steps of a method of pasture management optimization according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911236250.4A CN110956404A (en) | 2019-12-05 | 2019-12-05 | Pasture management optimization method, system and computer-readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911236250.4A CN110956404A (en) | 2019-12-05 | 2019-12-05 | Pasture management optimization method, system and computer-readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110956404A true CN110956404A (en) | 2020-04-03 |
Family
ID=69980099
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911236250.4A Pending CN110956404A (en) | 2019-12-05 | 2019-12-05 | Pasture management optimization method, system and computer-readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110956404A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113796327A (en) * | 2021-08-26 | 2021-12-17 | 北京市农林科学院智能装备技术研究中心 | Control method and device for stock farm pushing robot |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101014973A (en) * | 2004-07-29 | 2007-08-08 | Can科技公司 | System and method for optimizing animal production |
| WO2010023056A1 (en) * | 2008-08-29 | 2010-03-04 | Delaval Holding Ab | Method and arrangement for animal management |
| CN106780082A (en) * | 2016-12-07 | 2017-05-31 | 兰州大学 | Stocking rate measuring method and device |
| WO2018018062A1 (en) * | 2016-07-29 | 2018-02-01 | Commonwealth Scientific And Industrial Research Organisation | Growth performance improvements in pasture and feedlot systems |
| CN108537680A (en) * | 2018-04-17 | 2018-09-14 | 内蒙古蒙草生态环境（集团）股份有限公司 | The management method in grassland ecology pasture |
| CN109329201A (en) * | 2018-09-18 | 2019-02-15 | 甘肃农业大学 | Family domestic animal-meadow configuration technology is herded by a kind of family |
-
2019
- 2019-12-05 CN CN201911236250.4A patent/CN110956404A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101014973A (en) * | 2004-07-29 | 2007-08-08 | Can科技公司 | System and method for optimizing animal production |
| WO2010023056A1 (en) * | 2008-08-29 | 2010-03-04 | Delaval Holding Ab | Method and arrangement for animal management |
| WO2018018062A1 (en) * | 2016-07-29 | 2018-02-01 | Commonwealth Scientific And Industrial Research Organisation | Growth performance improvements in pasture and feedlot systems |
| CN106780082A (en) * | 2016-12-07 | 2017-05-31 | 兰州大学 | Stocking rate measuring method and device |
| CN108537680A (en) * | 2018-04-17 | 2018-09-14 | 内蒙古蒙草生态环境（集团）股份有限公司 | The management method in grassland ecology pasture |
| CN109329201A (en) * | 2018-09-18 | 2019-02-15 | 甘肃农业大学 | Family domestic animal-meadow configuration technology is herded by a kind of family |
Non-Patent Citations (3)
| Title |
|---|
| 安玉锋等: "高山草原放牧系统控制的研究", 《草业学报》 * |
| 王海霞: "青海省兴海县畜草平衡优化方案分析", 《青海科技》 * |
| 董瑞兰等: "草地产草量和动物承载力预测模型研究进展", 《草地学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113796327A (en) * | 2021-08-26 | 2021-12-17 | 北京市农林科学院智能装备技术研究中心 | Control method and device for stock farm pushing robot |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Waithaka et al. | Bio-economic evaluation of farmers’ perceptions of viable farms in western Kenya | |
| Lisson et al. | A participatory, farming systems approach to improving Bali cattle production in the smallholder crop–livestock systems of Eastern Indonesia | |
| Groot et al. | Multi-objective optimization and design of farming systems | |
| Altahat et al. | Factors affecting profitability of layer hens enterprises | |
| Burgess et al. | Agricultural technology and land use futures: the UK case | |
| Kamanzi et al. | Feed inventory and smallholder farmers’ perceived causes of feed shortage for dairy cattle in Gisagara District, Rwanda | |
| Olawumi et al. | Economic analysis of homestead fish production in Ogun state Nigeria | |
| Shapiro et al. | Rwanda livestock master plan | |
| Chakeredza et al. | Managing fodder trees as a solution to human–livestock food conflicts and their contribution to income generation for smallholder farmers in southern Africa | |
| Abebe | Smallholder farms livestock management practices and their implications on livestock water productivity in mixed crop-livestock systems in the highlands of Blue Nile basin: A case study from fogera, diga and jeldu districts (Ethiopia) | |
| Flaten et al. | The profitability of harvesting grass silages at early maturity stages: An analysis of dairy farming systems in Norway | |
| Basson | A financial analysis of different livestock management approaches within different crop rotation systems in the Middle Swartland | |
| Staal et al. | Targeting strategic investment in livestock development as a vehicle for rural livelihoods | |
| Banson et al. | Economic and market analysis of swine rearing and pork production in Ghana | |
| CN110956404A (en) | Pasture management optimization method, system and computer-readable storage medium | |
| Reyes et al. | Measuring sustainability on cattle ranches | |
| Yisa et al. | Profitability analysis of catfish farming in Suleja local government area of Niger state, Nigeria | |
| BABATUNDE | Assessment of feed resources utilization for livestock production by agro-pastoralists in Tafa Local Government Area of Nigeria | |
| Azarov et al. | Characteristics and Profitability of Livestock-based Farming Systems in At-Bashy, Naryn Oblast | |
| Efendi et al. | Assessing the Potential of Livestock and Plantation Businesses in Several Lampung Regions | |
| Mangesho et al. | Assessing the environmental impacts of intervention packages in dairy systems in Tanzania. CLEANED baseline and scenario assessment report | |
| Landman | Economic analysis of intensive sheep production systems in central South Africa | |
| Rana | Recent advances in integrated farming systems | |
| Misra | Integration of livestock in land use diversification | |
| Singh et al. | The importance of dairy farming for landless households in Punjab |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20200403 |