Intelligent feeding condition management method and system for laying hens

Abstract

The invention discloses a laying hen intelligent feeding condition management method and system, and relates to the technical field of breeding management. The method comprises the following steps: extracting an initial parameter value of a feeding condition of each item of a corresponding week age of each laying hen group of the current batch in a range of execution parameter values of a feeding condition of each item of each week age of each laying hen group of a previous batch in a fence; continuously acquiring the average egg yield of each laying hen group in each week age during the breeding period of the laying hens in the same batch; adjusting the initial parameter value of the feeding condition of each item of each laying hen group of the current week age according to the difference value between the average egg production of the current batch of laying hens and the average egg production of the last batch of laying hens at the previous multiple week ages, and obtaining the execution parameter value of the feeding condition of each item of each laying hen group of the current week age. The feed effectively improves the egg yield of laying hens.

Description

Technical Field

[0001] The invention belongs to the technical field of breeding management, and in particular relates to an intelligent breeding condition management method and system for laying hens. Background Art

[0002] With the development of modern agriculture, laying hen farming is gradually moving towards scale, intensiveness and intelligence. In the laying hen farming process, feeding after entering the pen is one of the key links that determine the health and production performance of the flock. Traditional laying hen farming management mainly relies on manual operation and experience judgment. Although this method can achieve an increase in egg production rate to a certain extent, it still has many shortcomings, such as manual monitoring cannot effectively increase the egg production of laying hens. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent feeding condition management method and system for laying hens, which continuously optimizes the feeding conditions of laying hens at different ages through egg production and improves the egg production of laying hens.

[0004] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0005] The present invention provides an intelligent feeding condition management method for laying hens, comprising:

[0006] For each batch of laying hens entering the pen, multiple laying hens that are raised and counted together are divided into the same laying hen group;

[0007] Obtain the execution parameter values ​​of the feeding conditions of each item of each laying hen group at each week of age and the average egg production of the last batch of laying hens, wherein the feeding conditions include daily light hours, ambient temperature, protein intake and / or several trace element intakes, wherein the execution parameter values ​​of the feeding conditions of each item of the first batch of laying hens at each week of age are set by the staff, and these most economical meat-feed ratios formulated by breeding experts are used as reference benchmarks for subsequent calculations and adjustments;

[0008] Extract the initial parameter value of the feeding condition of each item of the corresponding week age for each group of laying hens in the current batch within the range of the execution parameter value of the feeding condition of each item of each week age for each group of laying hens in the previous batch;

[0009] During the breeding period of this batch of laying hens, the average egg production of each laying hen group in each week of age is continuously obtained;

[0010] According to the difference between the average egg production of the current batch and the previous batch of laying hens in the previous weeks, the initial parameter value of the feeding conditions of each item of each laying hen group at the current week age is adjusted to obtain the execution parameter value of the feeding conditions of each item of each laying hen group at the current week age;

[0011] The execution parameter values ​​of the feeding conditions of each item of each laying hen group at each week of age during the breeding period of each batch of laying hens entering the pen are continuously updated.

[0012] The present invention also discloses a method for intelligent feeding condition management of laying hens, comprising:

[0013] Receive execution parameter values ​​of feeding conditions of each item of each laying hen group at the current age;

[0014] The execution parameter value of each feeding condition of each item corresponding to each laying hen group of the current week age is executed.

[0015] The present invention also discloses a method for intelligent feeding condition management of laying hens, comprising:

[0016] Obtain the measured parameter value of the feeding condition of each item of each laying hen group at the current week age;

[0017] Receive execution parameter values ​​of feeding conditions of each item of each laying hen group at the current age;

[0018] According to the difference between the measured parameter value and the corresponding execution parameter value, the feeding conditions of each item of each laying hen group at the current age are corrected and adjusted.

[0019] The present invention also discloses an intelligent laying hen feeding condition management system, comprising:

[0020] A control unit is used to divide a plurality of laying hens that are raised and counted together into the same laying hen group for each batch of laying hens entering the pen;

[0021] Obtain the execution parameter values ​​of the feeding conditions of each item and the average egg production of each laying hen group at each week of age in the last batch;

[0022] Extract the initial parameter value of the feeding condition of each item of the corresponding week age for each group of laying hens in the current batch within the range of the execution parameter value of the feeding condition of each item of each week age for each group of laying hens in the previous batch;

[0023] During the breeding period of this batch of laying hens, the average egg production of each laying hen group in each week of age is continuously obtained;

[0024] According to the difference between the average egg production of the current batch and the previous batch of laying hens in the previous weeks, the initial parameter value of the feeding conditions of each item of each laying hen group at the current week age is adjusted to obtain the execution parameter value of the feeding conditions of each item of each laying hen group at the current week age;

[0025] Continuously update the execution parameter values ​​of the feeding conditions of each item of each laying hen group at each week of age during the breeding period of each batch of laying hens;

[0026] An execution unit, configured to receive an execution parameter value of a feeding condition for each item of each laying hen group of a current age;

[0027] Execute the execution parameter value of each feeding condition of each corresponding item for each laying hen group of the current week age;

[0028] The inspection unit is used to obtain the measured parameter value of the feeding conditions of each item of each laying hen group at the current age;

[0029] Receive execution parameter values ​​of feeding conditions of each item of each laying hen group at the current age;

[0030] According to the difference between the measured parameter value and the corresponding execution parameter value, the feeding conditions of each item of each laying hen group at the current age are corrected and adjusted.

[0031] The present invention analyzes the egg production and feeding conditions of each laying hen group in the current batch and the past batches through a control unit, thereby continuously optimizing the feeding conditions of each item of the laying hen in this batch at each week of age, thereby achieving the technical effect of increasing the egg production of laying hens. At the same time, the system also executes the execution parameter value of the feeding conditions of each item of each laying hen group at the current week of age through an execution unit, and conducts actual measurement and inspection of different egg groups in the chicken house through an inspection unit, thereby avoiding errors in the actual execution link.

[0032] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0034] Figure 1 A schematic diagram of functional units and information flows of an intelligent laying hen feeding condition management system according to an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of a flow chart of steps of a control unit according to an embodiment of the present invention;

[0036] Figure 3 A schematic diagram of a step flow chart of an execution unit according to an embodiment of the present invention;

[0037] Figure 4 A schematic diagram of a process flow of an inspection unit according to an embodiment of the present invention;

[0038] Figure 5 This is a schematic diagram of the step flow of step S3 in one embodiment of the present invention;

[0039] Figure 6 This is a schematic diagram of the step flow of step S33 in one embodiment of the present invention;

[0040] Figure 7 A schematic diagram of a step flow chart of step S34 in an embodiment of the present invention;

[0041] Figure 8 This is a schematic diagram of the step flow of step S5 in one embodiment of the present invention;

[0042] Fig. 9 A schematic diagram of a step flow chart of step S53 in an embodiment of the present invention;

[0043] Fig.10 A schematic diagram of a step flow chart of step S54 in an embodiment of the present invention;

[0044] In the accompanying drawings, the components represented by the reference numerals are listed as follows:

[0045] 1-control unit, 2-execution unit, 3-inspection unit, sensor 4. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0047] It should be noted that the terms "first", "second", etc. in this application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0048] See also Figures 1 to 4As shown, the present invention provides an intelligent feeding condition management system for laying hens, which is divided from the functional unit, including three independent units: control unit 1, execution unit 2 and inspection unit 3. Each part can continue to work independently, but all need control unit 1 as the main operation unit. In the actual operation process, the control unit 1 needs to be provided with data by sensor 4, and then the control unit 1 distributes the calculated execution parameter values ​​of the feeding conditions of each item of each laying hen group at the current age to the execution unit 2 and the inspection unit 3. The execution unit 2 can be a feeding condition controller of the chicken house, and the inspection unit 3 can be various virtual functional units or electrical equipment, as long as they can complete the inspection task.

[0049] During the operation of this system, the control unit 1 can first execute step S1 to divide the multiple laying hens that are raised and counted together into the same laying hen group. The laying hen grouping here can be random grouping, or it can be grouping laying hens with the same or similar weight, coat color, etc. into one laying hen group, which can facilitate subsequent calculation and analysis. Next, step S2 can be executed to obtain the execution parameter values ​​of the feeding conditions and the average egg production of each item of each week of each laying hen group in the last batch. In the actual operation of this system, the feeding conditions include daily light time, ambient temperature, protein intake and several trace element intakes. The execution parameter values ​​of the feeding conditions of the first batch of laying hens at each week of age are set by the staff, and these most economical meat-feed ratios formulated by breeding experts are used as reference benchmarks for later calculations and adjustments.

[0050] During the process of analyzing and managing the current batch of laying hens, the control unit 1 can execute step S3 to extract the initial parameter values ​​of the feeding conditions of each item of the corresponding age for each group of laying hens in the current batch within the range of the execution parameter values ​​of the feeding conditions of each item of each week of age for each group of laying hens in the previous batch. Of course, the extraction mentioned here refers to computational analysis, which can be selected or obtained by comprehensive calculation.

[0051] During the breeding period of this batch of laying hens, first, step S4 can be executed to continuously obtain the average egg production of each laying hen group at each week of age. Next, step S5 can be executed to adjust the initial parameter value of the feeding conditions of each item of each laying hen group at the current week of age according to the difference between the average egg production of this batch and the previous batch of laying hens at the previous weeks of age, and obtain the execution parameter value of the feeding conditions of each item of each laying hen group at the current week of age. During the continuous breeding and egg laying of laying hens, the execution parameter value of the feeding conditions of each item of each laying hen group at each week of age for each batch of laying hens is continuously updated.

[0052] The execution unit 2 in the present system can firstly execute step S021 to receive the execution parameter value of the feeding conditions of each item of each egg-laying hen group of the current age during operation. Afterwards, step S022 can be executed to execute the execution parameter value of the feeding conditions of each item corresponding to each egg-laying hen group of the current age. Since the execution unit 2 is only an execution mechanism, it cannot ensure that the control instruction of the control unit 1 is executed in place, so the present system also requires the inspection unit 3 to execute step S031 to obtain the measured parameter value of the feeding conditions of each item of each egg-laying hen group of the current age. Afterwards, step S032 can be executed to receive the execution parameter value of the feeding conditions of each item of each egg-laying hen group of the current age. Finally, step S033 can be executed to correct and adjust the feeding conditions of each item of each egg-laying hen group of the current age according to the difference between the measured parameter value and the corresponding execution parameter value. The adjustment here can be to notify the staff to make adjustments according to local conditions, or to make automatic adjustments according to a preset program.

[0053] See also Figure 5 As shown, since the physique of laying hens is different when they are just put into the pen, but the feeding conditions of laying hens with similar physiques are common, the feeding conditions of this batch can be preset with reference to the execution parameter values ​​of the feeding conditions of each item of the group of laying hens that entered the pen in the previous batch. Specifically, step S31 can be first executed to obtain the weight of each laying hen in each group of laying hens that entered the pen in the previous batch at the first week of age after entering the pen. Next, step S32 can be executed to obtain the weight of each laying hen in each group of laying hens that entered the pen in this batch at the first week of age after entering the pen. Next, step S33 can be executed to match each group of laying hens that entered the pen in this batch with each group of laying hens that entered the pen in the previous batch according to the weight of each laying hen in each group of laying hens that entered the pen in this batch and the previous batch at the first week of age after entering the pen, so as to obtain each group of laying hens that entered the pen in this batch corresponding to several groups of laying hens that entered the pen in the previous batch. Finally, step S34 can be executed to refer to the execution parameter values ​​of the feeding conditions of each item of each laying hen group in the previous batch at each week of age and each laying hen group in this batch corresponds to several laying hen groups in the previous batch to obtain the initial parameter values ​​of the feeding conditions of each item of each laying hen group in this batch at the corresponding week of age. In actual operation, the mean or a random value within a range can be used.

[0054] See also Figure 6As shown, in order to perform similarity matching between each group of laying hens in this batch and the previous batch, the weight of the laying hens in the laying hens group can be analyzed. Of course, other items, such as body shape, feather color and other information can be used. In this solution, the most relevant weight in practice is used as the basis for analysis. Specifically, step S331 can be first performed to obtain the weight mean and weight dispersion of each laying hen in each group of laying hens in the previous batch according to the weight of each laying hen in the first week after entering the pen.

[0055] In the process of analyzing each group of laying hens entering the pen in this batch, first, step S332 can be executed to calculate the mean of the difference between the mean weight and the mean weight of each group of laying hens entering the pen in the previous batch as the mean weight difference. Next, step S333 can be executed to use the group of laying hens entering the pen in the previous batch whose difference is less than the mean weight difference as the weight candidate egg group. Next, step S334 can be executed to calculate the mean of the difference between the weight dispersion value and the weight dispersion value of each group of laying hens entering the pen in the previous batch as the discrete mean difference. Next, step S335 can be executed to use the group of laying hens entering the pen in the previous batch whose difference is less than the discrete mean difference as the discrete candidate egg group. Next, step S336 can be executed to use the overlapping part of the weight candidate egg group and the discrete candidate egg group as the group of laying hens entering the pen in this batch corresponding to the group of laying hens entering the pen in the previous batch. Finally, step S337 can be executed to summarize and obtain the group of laying hens entering the pen in this batch corresponding to the group of laying hens entering the pen in the previous batch.

[0056] In order to supplement the implementation process of the above steps S331 to S337, the source code of some functional modules is provided, and the explanation is compared in the comment section. In order to avoid the leakage of data involving commercial secrets, some data that does not affect the implementation of the solution are desensitized, the same below.

[0057] #include <iostream>

[0058] #include <vector>

[0059] #include <cmath>

[0060] #include <algorithm>

[0061] / / Define the laying hen structure, including weight

[0062] struct Chicken{

[0063] double weight; / / weight at the first week of age

[0064] };

[0065] / / Define the laying hen grouping structure, including several laying hens and weight statistics

[0066] struct ChickenGroup{

[0067] std::vector <chicken>chickens; / / Laying chickens in the group

[0068] double average_weight; / / average weight

[0069] double weight_std_dev; / / weight dispersion (standard deviation)

[0070] };

[0071] / / Calculate the mean weight and dispersion (standard deviation) of the group

[0072] void calculateStatistics(ChickenGroup&group){

[0073] double sum = 0;

[0074] double sq_sum = 0;

[0075] size_t n=group.chickens.size();

[0076] for(const auto&chicken:group.chickens){

[0077] sum += chicken.weight;

[0078] sq_sum+=chicken.weight*chicken.weight;

[0079] }

[0080] group.average_weight=sum / n;

[0081] double mean_sq=group.average_weight*group.average_weight;

[0082] group.weight_std_dev=std::sqrt((sq_sum / n)-mean_sq);

[0083] }

[0084] / / Get the previous batch of grouped data

[0085] std::vector <chickengroup>getPreviousBatchGroups(){

[0086] std::vector <chickengroup>previousGroups;

[0087] / / Example: Get data for 10 groups, each with 5 laying hens

[0088] for(int i=0;i<10;++i){

[0089] ChickenGroup group;

[0090] for(int j=0;j<5;++j){

[0091] Chicken chicken;

[0092] chicken.weight = 100 + i*5 + (rand()% 10-5); / / Example of weight fluctuation

[0093] group.chickens.push_back(chicken);

[0094] }

[0095] calculateStatistics(group); / / Calculate the mean and dispersion of weight

[0096] previousGroups.push_back(group);

[0097] }

[0098] return previousGroups;

[0099] }

[0100] / / Get the grouped data of the current batch

[0101] std::vector <chickengroup>getCurrentBatchGroups(){

[0102] std::vector <chickengroup>currentGroups;

[0103] / / Example: Get data for 10 groups, each with 5 laying hens

[0104] for(int i=0;i<10;++i){

[0105] ChickenGroup group;

[0106] for(int j=0;j<5;++j){

[0107] Chicken chicken;

[0108] chicken.weight = 105 + i * 5 + (rand()% 10-5); / / Example weight fluctuation

[0109] group.chickens.push_back(chicken);

[0110] }

[0111] calculateStatistics(group); / / Calculate the mean and dispersion of weight

[0112] currentGroups.push_back(group);

[0113] }

[0114] return currentGroups;

[0115] }

[0116] / / Calculate the difference between the mean weights of the two groups

[0117] double meanWeightDifference(const ChickenGroup&group1,constChickenGroup&group2){

[0118] return std::fabs(group1.average_weight-group2.average_weight);

[0119] }

[0120] / / Calculate the difference between the two grouping discrete degrees (standard deviation)

[0121] double stdDevDifference(const ChickenGroup&group1,const ChickenGroup&group2){

[0122] return std::fabs(group1.weight_std_dev-group2.weight_std_dev);

[0123] }

[0124] / / Get weight alternative groups

[0125] std::vector <int>getWeightCandidateGroups(const ChickenGroup¤tGroup,const std::vector <chickengroup>&previousGroups){

[0126] std::vector <int>weightCandidates;

[0127] double total_diff = 0;

[0128] / / Calculate the sum of the weight mean difference between the current group and each previous batch of groups

[0129] for(const auto&prevGroup:previousGroups){

[0130] total_diff+=meanWeightDifference(currentGroup,prevGroup);

[0131] }

[0132] / / Calculate the mean weight difference

[0133] double mean_diff=total_diff / previousGroups.size();

[0134] / / Take the group whose difference is less than the average difference as the weight alternative group

[0135] for(size_t i=0;i <previousGroups.size();++i){

[0136] if(meanWeightDifference(currentGroup,previousGroups[i]) <mean_diff){

[0137] weightCandidates.push_back(i);

[0138] }

[0139] }

[0140] return weightCandidates;

[0141] }

[0142] / / Get discrete candidate groups

[0143] std::vector <int>getStdDevCandidateGroups(const ChickenGroup¤tGroup,const std::vector <chickengroup>&previousGroups){

[0144] std::vector <int>stdDevCandidates;

[0145] double total_diff = 0;

[0146] / / Calculate the sum of the discrete degree differences between the current group and each previous batch of groups

[0147] for(const auto&prevGroup:previousGroups){

[0148] total_diff+=stdDevDifference(currentGroup,prevGroup);

[0149] }

[0150] / / Calculate the discrete mean difference

[0151]

[0152]

[0153] In the above code, there are four sections: data initialization, weight and discreteness matching, intersection matching, and final summary. The data initialization getPreviousBatchGroups() and getCurrentBatchGroups() functions generate the grouping data of the previous batch and the current batch of laying hens respectively, and calculate the weight mean and discreteness (standard deviation) of each group. Weight and discreteness matching uses getWeightCandidateGroups() and getStdDevCandidateGroups() to select qualified groups according to the weight mean difference and discreteness difference respectively. The intersection matching matchGroups() function obtains the final matching of the previous batch grouping through the intersection of the weight candidate grouping and the discrete candidate grouping. The final summary matchAllGroups() function summarizes the matching results of all current batch groups and outputs the matching correspondence.

[0154] See also Figure 7 As shown, as shown above, the step of obtaining the initial parameter value of the feeding conditions of each item of the corresponding week age for each egg-laying chicken grouping in this batch of pens in step S34 can be the use of the mean value, or it can be a random value within a range. This scheme exemplifies the operation process using the mean value. Specifically, first, step S341 can be executed to substitute the execution parameter values ​​of the feeding conditions of each item of each egg-laying chicken grouping in the previous batch of pens for each egg-laying chicken grouping in the previous batch of pens at each week age for each egg-laying chicken grouping in the previous batch of pens, and obtain the several execution parameter values ​​corresponding to the feeding conditions of each item of each week age for each egg-laying chicken grouping in this batch of pens. Afterwards, step S342 can be executed to average the several execution parameter values ​​corresponding to the feeding conditions of each item of each week age for each egg-laying chicken grouping in this batch of pens, and obtain the initial parameter value of the feeding conditions of each item of each week age for each egg-laying chicken grouping in this batch of pens.

[0155] See also Figures 8 to 10 As shown, since the growth of laying hens is continuous, when laying hens enter the egg-laying cycle, the adjustment of the feeding conditions of laying hens needs to refer to the previous parameter values, otherwise the adjustment changes are too drastic and may cause stress reactions in laying hens, which will reduce egg production. Taking the above factors into consideration, when laying hens enter the egg-laying cycle, in the process of adjusting the feeding conditions of each laying hen group of the current week age in this batch of laying hens, first, step S51 can be executed to obtain the ratio of the average egg production of several laying hen groups corresponding to the previous batch of laying hens in the previous week age to the laying hen group of this batch of laying hens in the previous week age as the egg production correction coefficient. Next, step S52 can be executed to multiply the initial parameter value of the feeding conditions of each item of the laying hen group of the current week age by the egg production correction coefficient to obtain the preliminary correction parameter value of the feeding conditions of each item of the laying hen group of the current week age.

[0156] The above process is based on the difference in egg production. However, the initial correction parameter values ​​of the feeding conditions for each item may change dramatically. In order to make adaptive adjustments, please refer to Fig. 9 As shown, step S53 can be performed next to obtain the historical reference correction amount according to the execution parameter value of the feeding condition of each item of the laying hen group in the previous week age and the execution parameter value of the feeding condition of each item of the corresponding week age of the corresponding laying hen group in the previous batch during the laying cycle. Specifically, step S531 can be performed first to arrange the execution parameter value of the feeding condition of each item of the laying hen group in the previous week age in the laying cycle according to the set project order, and obtain the executed parameter matrix of the laying hen group in each week age in the previous period. Next, step S532 can be performed to arrange the average execution parameter value of the feeding condition of each item of the corresponding week age of the corresponding laying hen group in the previous batch according to the set project order, and obtain the reference execution parameter matrix of the laying hen group in the previous batch of each week age. Next, step S533 can be performed to respectively calculate the difference matrix of the executed parameter matrix of the laying hen group in each week age in the previous period and the reference execution parameter matrix of the laying hen group in the previous batch of each week age in the previous period. Finally, step S534 may be executed to calculate and obtain the mean matrix of each difference matrix as the historical reference correction amount.

[0157] See also Fig.10 As shown, since the mean matrix is ​​used as the historical reference correction amount in step S3, in order to adapt to the matrix operation, in the process of executing step S54 to use the historical reference correction amount to correct the preliminary correction parameter value of the feeding conditions of each item of the egg grouping at the current age to obtain the execution parameter value of the feeding conditions of each item of the egg grouping at the current age, firstly, step S541 can be executed to arrange the preliminary correction parameter value of the feeding conditions of each item of the egg grouping at the current age according to the set project order to obtain the preliminary correction execution parameter matrix of the egg grouping at the current age. Next, step S542 can be executed to add the preliminary correction execution parameter matrix to the mean matrix to obtain the actual execution parameter matrix. Finally, step S543 can be executed to expand each element in the actual execution parameter matrix according to the set project order to obtain the execution parameter value of the feeding conditions of each item of the egg grouping at the current age.

[0158] Since the above process obtains the execution parameter value of the feeding condition of each item of a certain laying hen group of the current week age in this batch of pens, it is necessary to execute step S55 to summarize and obtain the execution parameter value of the feeding condition of each item of each laying hen group of the current week age. When the age of the laying hen increases, the feeding condition control of the laying hen throughout the egg-laying cycle is realized, and the egg production of the laying hen is effectively guaranteed.

[0159] In order to provide supplementary explanation for the implementation process of the above-mentioned steps S51 to S55, source codes of some functional modules are provided, and comparative explanations are provided in the comments.

[0160] #include <iostream>

[0161] #include <vector>

[0162] #include <numeric> / / For summing

[0163] #include <map> / / Used to store feeding conditions and parameter matrix

[0164] / / Define the feeding condition structure, which contains the feeding condition values ​​of different items

[0165] struct FeedingCondition{

[0166] double lightHours; / / Daily light hours

[0167] double temperature; / / ambient temperature

[0168] double proteinIntake; / / Protein intake

[0169] double traceElements; / / Trace element intake

[0170] };

[0171] / / Define the laying hen group structure

[0172] struct ChickenGroup{

[0173] int groupID; / / Group ID

[0174] std::map<int,FeedingCondition> weeklyConditions; / / Feeding conditions for each week of age

[0175] std::map<int,double> weeklyEggProduction; / / Egg production per week

[0176] }

[0177] / / Get the egg production correction factor

[0178] double getEggProductionCorrectionFactor(doublecurrentBatchProduction,double previousBatchProduction){

[0179] return currentBatchProduction / previousBatchProduction;

[0180] }

[0181] / / Calculate the initial correction parameters for feeding conditions

[0182] FeedingCondition calculatePreliminaryAdjustment(const FeedingCondition& initialCondition, double correctionFactor) {

[0183] FeedingCondition adjustedCondition;

[0184] adjustedCondition.lightHours = initialCondition.lightHours * correctionFactor;

[0185] adjustedCondition.temperature = initialCondition.temperature * correctionFactor;

[0186] adjustedCondition.proteinIntake = initialCondition.proteinIntake * correctionFactor;

[0187] adjustedCondition.traceElements = initialCondition.traceElements * correctionFactor;

[0188] return adjustedCondition;

[0189] }

[0190] / / Calculate the historical reference correction matrix

[0191] FeedingCondition calculateHistoricalReference(const std::vector <feedingcondition>& executedMatrix, const std::vector <feedingcondition>&referenceMatrix){

[0192] FeedingCondition historicalCorrection;

[0193] int numWeeks = executedMatrix.size();

[0194] / / Initialize the correction amount to zero

[0195] historicalCorrection.lightHours = 0;

[0196] historicalCorrection.temperature = 0;

[0197] historicalCorrection.proteinIntake = 0;

[0198] historicalCorrection.traceElements = 0;

[0199] / / Calculate the difference and take the average

[0200] for(int i = 0; i < numWeeks; ++i){

[0201] historicalCorrection.lightHours += (executedMatrix[i].lightHours - referenceMatrix[i].lightHours);

[0202] historicalCorrection.temperature += (executedMatrix[i].temperature - referenceMatrix[i].temperature);

[0203] historicalCorrection.proteinIntake += (executedMatrix[i].proteinIntake - referenceMatrix[i].proteinIntake);

[0204] historicalCorrection.traceElements += (executedMatrix[i].traceElements - referenceMatrix[i].traceElements);

[0205] }

[0206] / / Calculate the mean

[0207] historicalCorrection.lightHours / = numWeeks;

[0208] historicalCorrection.temperature / = numWeeks;

[0209] historicalCorrection.proteinIntake / = numWeeks;

[0210] historicalCorrection.traceElements / = numWeeks;

[0211] return historicalCorrection;

[0212] }

[0213] / / Calculate the final execution parameter matrix

[0214] FeedingCondition calculateFinalExecutionParameters(const FeedingCondition& preliminaryMatrix, const FeedingCondition& referenceCorrection) {

[0215] FeedingCondition finalCondition;

[0216] finalCondition.lightHours = preliminaryMatrix.lightHours + referenceCorrection.lightHours;

[0217] finalCondition.temperature = preliminaryMatrix.temperature + referenceCorrection.temperature;

[0218] finalCondition.proteinIntake = preliminaryMatrix.proteinIntake + referenceCorrection.proteinIntake;

[0219] finalCondition.traceElements = preliminaryMatrix.traceElements + referenceCorrection.traceElements;

[0220] return finalCondition;

[0221] }

[0222] / / Obtain the feeding condition data of the previous batch

[0223] std::vector <chickengroup>getPreviousBatchConditions(){

[0224] std::vector <chickengroup>previousGroups;

[0225] / / Example 10 groups, each group has 10 weeks of feeding conditions

[0226] for(int i=0;i<10;++i){

[0227] ChickenGroup group;

[0228] group.groupID=i+1;

[0229] for(int week=1;week<=10;++week){

[0230] FeedingCondition condition;

[0231] condition.lightHours = 12 + i * 0.5; / / Example lighting time

[0232] condition.temperature = 25 + i * 0.3; / / Example temperature

[0233] condition.proteinIntake = 20 + i * 0.4; / / Example protein intake

[0234] condition.traceElements = 1 + i * 0.1; / / Example of trace element intake

[0235] group.weeklyConditions[week]=condition;

[0236] group.weeklyEggProduction[week] = 10 + i * 0.2; / / Example of weekly egg production

[0237] }

[0238] previousGroups.push_back(group);

[0239] }

[0240] return previousGroups;

[0241] }

[0242] / / Example of feeding condition data for this batch

[0243] ChickenGroup getCurrentBatchConditions(int groupID){

[0244] ChickenGroup currentGroup;

[0245] currentGroup.groupID = groupID;

[0246] / / Initial conditions for example at 10 weeks of age

[0247] for(int week = 1; week <= 10; ++week){

[0248] FeedingCondition condition;

[0249] condition.lightHours = 11.5; / / Initial light hours

[0250]

[0251]

[0252] std::cout << "Temperature: " << finalCondition.temperature << " degrees Celsius" << std::endl;

[0253] std::cout << "Protein intake: " << finalCondition.proteinIntake << " grams" << std::endl;

[0254] std::cout << "Trace element intake: " << finalCondition.traceElements << " grams" << std::endl;

[0255] }

[0256] return 0;

[0257] }

[0258] The above code includes three submodules: egg production correction, historical reference correction, and solving the final execution parameters. The egg production correction submodule calculates the egg production correction coefficient of the current week of age during operation, obtains the correction coefficient through the ratio of last week's egg production, and adjusts the feeding conditions. After that, the historical reference correction submodule calculates the historical correction based on the previous execution feeding conditions and the execution conditions of the previous batch. Finally, the final execution parameter submodule adds the preliminary corrected feeding parameters and the historical correction to obtain the final feeding conditions for the current week of age and outputs the results. Through this process, the feeding conditions of each laying hen group at different ages can be dynamically adjusted to ensure the stability of egg production.

[0259] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the device, system, method and computer program product according to multiple embodiments of the present application. In this regard, each square frame in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the logical function of the specification. In some alternative implementations, the functions marked in the square frame can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square frames can actually be executed substantially in parallel, and they can also be executed in reverse order sometimes, depending on the functions involved.

[0260] It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented by hardware that performs the corresponding function or action, such as a circuit or ASIC (Application Specific Integrated Circuit), or can be implemented by a combination of hardware and software, such as firmware.

[0261] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0262] The embodiments of the present application have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those of ordinary skill in the art without departing from the scope of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.< / chickengroup> < / chickengroup> < / feedingcondition> < / feedingcondition> < / map> < / numeric> < / vector> < / iostream> < / int> < / chickengroup> < / int> < / int> < / chickengroup> < / int> < / chickengroup> < / chickengroup> < / chickengroup> < / chickengroup> < / chicken> < / algorithm> < / cmath> < / vector> < / iostream>

Claims

1. A method for intelligent feeding condition management of laying hens, characterized in that: include, For each batch of laying hens entering the pen, multiple laying hens that are raised and counted together are divided into the same laying hen group; Obtain the execution parameter values ​​of the feeding conditions of each item and the average egg production of each laying hen group at each week of age in the last batch; Extract the initial parameter value of the feeding condition of each item of the corresponding week age for each group of laying hens in the current batch within the range of the execution parameter value of the feeding condition of each item of each week age for each group of laying hens in the previous batch; During the breeding period of this batch of laying hens, the average egg production of each laying hen group in each week of age is continuously obtained; According to the difference between the average egg production of the current batch and the previous batch of laying hens in the previous weeks, the initial parameter value of the feeding conditions of each item of each laying hen group at the current week age is adjusted to obtain the execution parameter value of the feeding conditions of each item of each laying hen group at the current week age; The execution parameter values ​​of the feeding conditions of each item of each laying hen group at each week of age during the breeding period of each batch of laying hens entering the pen are continuously updated.

2. The method according to claim 1, characterized in that The step of extracting the initial parameter value of the feeding condition of each item of the corresponding week age for each group of laying hens in the current batch within the range of the execution parameter value of the feeding condition of each item of each week age for each group of laying hens in the previous batch comprises: Obtain the weight of each laying hen in each laying hen group of the last batch after entering the pen in the first week of age; Obtain the weight of each laying hen in each laying hen group in this batch at the first week of age after entering the pen; According to the weight of each laying hen in each laying hen group of the current batch and the previous batch in the first week after entering the pen, each laying hen group of the current batch and the previous batch are matched to obtain each laying hen group of the current batch corresponding to a number of laying hen groups of the previous batch; Referring to the execution parameter values ​​of the feeding conditions of each item of each laying hen group in the previous batch at each week of age and the corresponding several laying hen groups in the previous batch to each laying hen group in this batch, the initial parameter values ​​of the feeding conditions of each item of each laying hen group in this batch at the corresponding week of age are obtained.

3. The method according to claim 2, characterized in that The step of matching each egg-laying chicken group of the current batch with each egg-laying chicken group of the previous batch according to the weight of each egg-laying chicken in each egg-laying chicken group of the current batch and the previous batch to obtain a number of egg-laying chicken groups corresponding to each egg-laying chicken group of the previous batch includes: According to the weight of each laying hen in each laying hen group of the last batch of laying hens in the first week after entering the pen, the mean weight and weight dispersion of each laying hen in each laying hen group of the last batch of laying hens are obtained; For each group of laying hens in this batch, Calculate the average of the difference between the mean weight and the mean weight of each laying hen group in the previous batch as the mean weight difference. Grouping several laying hens from the last batch whose weight difference is less than the average weight difference as the weight candidate egg groups, Calculate the mean of the difference between the weight dispersion value and the weight dispersion value of each laying hen group in the previous batch as the discrete mean difference. The grouping of several laying hens from the last batch whose difference is smaller than the discrete mean difference is used as discrete candidate egg groups. The overlapping part of the weight candidate egg grouping and the discrete candidate egg grouping is used as the egg grouping of this batch of laying hens corresponding to the several egg groups of the previous batch of laying hens; It is summarized that each group of laying hens in this batch corresponds to several groups of laying hens in the previous batch.

4. The method according to claim 2, characterized in that: The step of obtaining the initial parameter value of the feeding condition of each item of each laying hen group in the current batch at the corresponding week age by referring to the execution parameter value of the feeding condition of each item of each laying hen group in the previous batch and the several laying hen groups in the previous batch corresponding to each laying hen group in the current batch comprises: Substituting the execution parameter values ​​of the feeding conditions of each item of each laying hen group in the previous batch at each week of age for each laying hen group in the previous batch corresponding to the several laying hen groups in the previous batch, and obtaining the several execution parameter values ​​corresponding to the feeding conditions of each item of each laying hen group in the current batch at each week of age; The average of several execution parameter values ​​corresponding to the feeding conditions of each item of each week age of each laying hen group in this batch is taken to obtain the initial parameter value of the feeding conditions of each item of each laying hen group in this batch at the corresponding week age.

5. The method according to any one of claims 1 to 4, characterized in that: The step of adjusting the initial parameter value of the feeding condition of each item of each laying hen group at the current age according to the difference between the average egg production of the current batch and the previous batch of laying hens at the previous ages to obtain the execution parameter value of the feeding condition of each item of each laying hen group at the current age includes: When the laying hens enter the egg-laying cycle, for each laying hen group of the current week of age, The ratio of the average egg production of several groups of laying hens in the previous batch in the previous week of age to the group of laying hens in the current batch in the previous week of age is obtained as the egg production correction coefficient. The initial parameter value of the feeding condition of each item of the laying hen group at the current age is multiplied by the egg production correction coefficient to obtain the preliminary correction parameter value of the feeding condition of each item of the laying hen group at the current age. The historical reference correction value is obtained based on the execution parameter value of the feeding conditions of each item of the laying hen group at the previous week age during the laying cycle and the execution parameter value of the feeding conditions of each item of the corresponding week age of several laying hen groups in the previous batch. Using the historical reference correction amount, the preliminary correction parameter value of the feeding condition of each item of the egg group of the current age is corrected to obtain the execution parameter value of the feeding condition of each item of the egg group of the current age; The execution parameter values ​​of the feeding conditions of each item of each laying hen group at the current week age are summarized and obtained.

6. The method according to claim 5, characterized in that The step of obtaining a historical reference correction value according to the execution parameter value of the feeding conditions of each item of the laying hen group at the previous week age during the laying cycle and the execution parameter value of the feeding conditions of each item of the corresponding week age of the several laying hen groups in the previous batch, comprises: Arrange the execution parameter values ​​of the feeding conditions of each item of the laying hen group at the previous week age during the laying cycle according to the set item order to obtain the executed parameter matrix of the laying hen group at each previous week age. Arrange the average execution parameter values ​​of the feeding conditions of each item of the corresponding week age for the group of laying hens in the previous batch according to the set order of the items, and obtain the reference execution parameter matrix of each week age of the group of laying hens in the previous batch. Calculate the difference matrix between the executed parameter matrix of the laying hen group at each week of age in the past and the reference execution parameter matrix of the laying hen group at each week of age in the previous batch, The mean matrix of each difference matrix is ​​calculated and used as the historical reference correction value.

7. The method according to claim 6, characterized in that The step of using the historical reference correction amount to correct the preliminary correction parameter value of the feeding condition of each item of the egg group at the current age to obtain the execution parameter value of the feeding condition of each item of the egg group at the current age includes: Arrange the preliminary correction parameter values ​​of the feeding conditions of each item of the laying hen group at the current age according to the set item order to obtain the preliminary correction execution parameter matrix of the laying hen group at the current age. The preliminary modified execution parameter matrix is ​​added to the mean value matrix to obtain an actual execution parameter matrix. Each element in the actual execution parameter matrix is ​​expanded according to the set item sequence to obtain the execution parameter value of the feeding condition of each item of the egg group at the current week age.

8. A method for intelligent feeding condition management of laying hens, characterized in that: include, Receiving the execution parameter value of the feeding condition of each item of each laying hen group of the current week age in the method for intelligent feeding condition management of laying hens according to any one of claims 1 to 7; The execution parameter value of each feeding condition of each item corresponding to each laying hen group of the current week age is executed.

9. A method for intelligent feeding condition management of laying hens, characterized in that: include, Obtain the measured parameter value of the feeding condition of each item of each laying hen group at the current week age; Receiving the execution parameter value of the feeding condition of each item of each laying hen group of the current week age in the method for intelligent feeding condition management of laying hens according to any one of claims 1 to 7; According to the difference between the measured parameter value and the corresponding execution parameter value, the feeding conditions of each item of each laying hen group at the current age are corrected and adjusted.

10. An intelligent feeding condition management system for laying hens, characterized in that: include, A control unit is used to divide a plurality of laying hens that are raised and counted together into the same laying hen group for each batch of laying hens entering the pen; Obtain the execution parameter values ​​of the feeding conditions of each item and the average egg production of each laying hen group at each week of age in the last batch; Extract the initial parameter value of the feeding condition of each item of the corresponding week age for each group of laying hens in the current batch within the range of the execution parameter value of the feeding condition of each item of each week age for each group of laying hens in the previous batch; During the breeding period of this batch of laying hens, the average egg production of each laying hen group in each week of age is continuously obtained; According to the difference between the average egg production of the current batch and the previous batch of laying hens in the previous weeks, the initial parameter value of the feeding conditions of each item of each laying hen group at the current week age is adjusted to obtain the execution parameter value of the feeding conditions of each item of each laying hen group at the current week age; Continuously update the execution parameter values ​​of the feeding conditions of each item of each laying hen group at each week of age during the breeding period of each batch of laying hens; An execution unit, configured to receive an execution parameter value of a feeding condition for each item of each laying hen group of a current age; Execute the execution parameter value of each feeding condition of each corresponding item for each laying hen group of the current week age; The inspection unit is used to obtain the measured parameter value of the feeding conditions of each item of each laying hen group at the current age; Receive execution parameter values ​​of feeding conditions of each item of each laying hen group at the current age; According to the difference between the measured parameter value and the corresponding execution parameter value, the feeding conditions of each item of each laying hen group at the current age are corrected and adjusted.

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