Evaluation method and system for lactation behavior of dairy cows

Abstract

The embodiment of the present invention provides a method and system for evaluating the lactation behavior of dairy cows, which belongs to the field of agricultural breeding technology. The method comprises: obtaining the feeding status information of dairy cows in a cowshed; preprocessing the status information to obtain evaluation information; performing regression analysis on the evaluation information to obtain the influence information of the evaluation information on the lactation behavior; and evaluating the lactation behavior of dairy cows in the corresponding cowshed according to the influence information. The scheme of the present invention establishes a monitoring system for the lactation behavior of dairy cows in a pasture with the milk production and milk quality of dairy cows in the pasture as evaluation indicators, so as to ensure the normal lactation of dairy cows in the pasture and improve the efficiency of the pasture.

Description

Technical Field

[0001] The invention relates to the technical field of agricultural breeding, and in particular to a method for evaluating the lactation behavior of a dairy cow and a system for evaluating the lactation behavior of a dairy cow. Background Art

[0002] Lactation behavior is an important part of dairy cow production. Milk production affects the economic benefits of the ranch, and milk composition determines the quality and flavor of milk. Lactation behavior is affected by internal and external factors, including environmental factors, behavioral factors, feeding programs, etc. In view of the necessity of monitoring lactation behavior, the existing lactation behavior monitoring methods are mainly based on the animal feeding environment THI (thermal index) for evaluation, and the changes in dairy cow lactation behavior are described by a simple correlation coefficient, and it is assumed that the two are in a broken line relationship, that is, it is assumed that there is a breakpoint. When the THI index is less than the breakpoint, the lactation behavior is not affected by the high temperature environment. When the THI is greater than the breakpoint (threshold), the lactation behavior of dairy cows gradually becomes abnormal with the increase of THI. This method only uses the THI breakpoint as the threshold for abnormal lactation behavior. It is set on the assumption that the lactation behavior of all lactation periods and breeds of dairy cows has the same response to THI. However, studies have shown that the THI threshold for a decrease in milk production in multiparous dairy cows is lower than that in primiparous dairy cows. It can be seen that the method of setting the THI threshold is not applicable to all dairy cows. In addition, changes in lactation behavior are not only related to environmental factors, but also affected by changes in feeding quality and maintenance behavior. Studies have shown that the total milk production of dairy cows is significantly positively correlated with the dry matter intake of feeding behavior, and is significantly positively correlated with the drinking time and frequency of drinking behavior. Therefore, there are certain limitations in describing lactation behavior based only on environmental factors, and the relationship between the two is not a simple correlation coefficient.

[0003] As for the method of measuring lactation behavior by milk production, this method is only a single basis for measuring the lactation behavior of dairy cows, without considering the correlation between milk quality and milk production. It only ensures the monitoring method of stable milk production, ignoring the possibility of reduced milk quality. It is not practical and reliable and cannot meet the needs of pastures. It can be seen that there is currently no objective and comprehensive lactation behavior evaluation method. Based on this, it is necessary to create a new lactation behavior evaluation method for dairy cows. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a method and system for evaluating the lactation behavior of dairy cows, so as to at least solve the problems of poor objectivity and single evaluation consideration of the existing lactation behavior evaluation methods.

[0005] In order to achieve the above-mentioned purpose, the first aspect of the present invention provides a method for evaluating the lactation behavior of dairy cows, the method comprising: obtaining the feeding status information of dairy cows in a cowshed; preprocessing the status information to obtain evaluation information; performing regression analysis on the evaluation information to obtain the influence information of the evaluation information on the lactation behavior; and evaluating the lactation behavior of dairy cows in the corresponding cowshed according to the influence information.

[0006] Optionally, the cow feeding status information of the cowshed includes: cowshed environment information, cow behavior characteristic information and cow feeding plan information.

[0007] Optionally, the cowshed environmental information includes at least: the temperature, humidity, light intensity and carbon dioxide concentration of the cowshed; the cow behavior characteristic information includes at least: the proportion of cows eating, lying and drinking in the herd; the cow feeding plan information includes at least: the ratio of concentrate to roughage, the nutritional content of the feed and the energy of the feed.

[0008] Optionally, before performing regression analysis on the evaluation information, the method also includes: judging current climate conditions, including: comparing the temperature and humidity of the current cowshed with the temperature range and humidity range of each preset climate stage, respectively, to determine which preset climate stage the current cowshed climate belongs to; wherein the preset climate stages include: cold climate, hot climate and suitable climate.

[0009] Optionally, the method of obtaining the feeding status information of the cows in the cowshed includes: performing frame processing on the collected video information to obtain multiple cowshed image information; preprocessing the cowshed image information and using a multi-target detection algorithm to identify the cows in the preprocessed cowshed image information; extracting shape features of the identified cows and performing cluster analysis on the extracted features to obtain cow behavior feature information.

[0010] Optionally, different climate stages correspond to different evaluation information; wherein the evaluation information under cold climate includes: temperature, humidity, light intensity and carbon dioxide concentration in the cowshed; the evaluation information under hot climate includes: temperature, humidity, proportion of cows eating, proportion of cows lying, and proportion of cows drinking water in the dairy herd; the evaluation information under suitable climate includes: concentrate-to-roughage ratio of feed, nutritional content of feed and energy of feed.

[0011] Optionally, the lactation behavior includes: milk production and milk quality; the regression analysis of the evaluation information to obtain the impact information of the evaluation information on the lactation behavior includes: taking the evaluation information under each climate stage as input, importing it into a preset milk production evaluation model and a preset milk production quality model respectively, and outputting the corresponding milk production influence index and milk production quality influence index; the evaluation of the lactation behavior of the dairy cows in the corresponding cowshed according to the impact information includes: predicting the milk production and milk quality of the dairy cows in the current scenario based on the milk production influence index and the milk quality influence index; using the milk production prediction results and the milk quality prediction results as the evaluation results of the lactation behavior of the dairy cows.

[0012] Optionally, the method also includes: obtaining the preset milk production evaluation model and the preset milk production quality evaluation model; collecting historical monitoring data of the cowshed and the lactation behavior influencing information in the dairy cow animal husbandry knowledge base; wherein the historical monitoring data of the cowshed and the lactation behavior influencing information both include recorded scene information and lactation behavior information under the corresponding scene information; using the historical monitoring data of the cowshed and the lactation behavior influencing information as training samples, obtaining the milk production evaluation model based on the LightGBM regression algorithm training, and obtaining the milk production quality evaluation model based on the random forest regression algorithm training.

[0013] A second aspect of the present invention provides a system for evaluating the lactation behavior of dairy cows, the system comprising: a collection unit for acquiring the feeding status information of dairy cows in a cowshed; a processing unit for preprocessing the status information to obtain evaluation information; performing regression analysis on the evaluation information to obtain information on the impact of the evaluation information on lactation behavior; and an evaluation unit for evaluating the lactation behavior of dairy cows in the corresponding cowshed according to the impact information.

[0014] On the other hand, the present invention provides a computer-readable storage medium, on which instructions are stored, which, when executed on a computer, enable the computer to execute the above-mentioned method for evaluating the lactation behavior of dairy cows.

[0015] Through the above technical scheme, with multiple factors such as environmental factors (temperature, humidity, light intensity, carbon dioxide concentration), behavioral characteristics (feeding ratio, lying ratio, drinking water ratio) and feeding plan (feed concentrate-to-roughage ratio, feed nutritional content, feed energy) as influencing factors, and the milk production and milk quality of pasture cows as evaluation indicators, a monitoring system for the lactation behavior of pasture cows is established to ensure the normal lactation of pasture cows and improve the efficiency of the pasture.

[0016] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0018] Figure 1 It is a flowchart of the steps of a method for evaluating the lactation behavior of dairy cows provided by one embodiment of the present invention;

[0019] Figure 2 It is a system structure diagram of a dairy cow lactation behavior evaluation system provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0020] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0021] Lactation behavior is an important part of dairy cow production. Milk production affects the economic benefits of the ranch, and milk composition determines the quality and flavor of milk. Lactation behavior is affected by internal and external factors, including environmental factors, behavioral factors, feeding programs, etc.

[0022] In view of the necessity of monitoring lactation behavior, the existing lactation behavior monitoring methods are mainly evaluated based on the animal breeding environment THI (thermal index), and the changes in the lactation behavior of dairy cows are described by a simple correlation coefficient, and the two are assumed to be in a broken line relationship, that is, it is assumed that there is a breakpoint. When the THI index is less than the breakpoint, the lactation behavior is not affected by the high temperature environment. When the THI is greater than the breakpoint (threshold), the lactation behavior of dairy cows gradually becomes abnormal with the increase of THI. It is pointed out that when THI is between 65-71, the milk protein rate begins to decline, and the THI value at which milk production begins to decline is 73-76. When THI reaches 65.2 and 50.2, the milk protein rate and milk fat rate begin to decline respectively. First of all, this method only uses the THI breakpoint as the threshold for abnormal lactation behavior, which is set on the assumption that the lactation behavior of all lactation periods and breeds of dairy cows has the same response to THI. However, studies have shown that the THI threshold for a decrease in milk production in multiparous dairy cows is lower than that in first-time dairy cows. It can be seen that the method of setting the THI threshold is not applicable to all dairy cows. In addition, changes in lactation behavior are not only related to environmental factors, but also affected by changes in feeding quality and maintenance behavior. Studies have shown that the total milk production of dairy cows is significantly positively correlated with the dry matter intake of feeding behavior, and is significantly positively correlated with the drinking time and frequency of drinking behavior. Therefore, there are certain limitations in describing lactation behavior based only on environmental factors, and the relationship between the two is not a simple correlation coefficient.

[0023] In addition, there are methods to measure lactation behavior by milk production, which mainly analyzes the daily rumination time, rumination behavior, lying time, drinking frequency and other behavioral data of dairy cows, and finds that the total milk production of dairy cows is significantly positively correlated with the dry matter intake of feeding behavior, significantly positively correlated with the drinking time and drinking frequency of drinking behavior, and significantly negatively correlated with the number of walking steps of walking behavior. However, the method of measuring the lactation behavior of dairy cows based on a single basis does not consider the correlation between milk quality and milk production. It only ensures the monitoring method of stable milk production, ignores the possibility of reduced milk quality, is not practical and reliable, and cannot meet the needs of pastures.

[0024] High temperatures in summer can directly lead to abnormal lactation behavior in dairy cows. Studies have found that under the influence of high temperatures, the concentration of protein in dairy cow milk decreases significantly. To maintain a balance between heat production and heat dissipation, dairy cows reduce metabolic heat production by reducing feed intake. When the daily dry matter intake (DMI) of dairy cows decreases by 1.4 kg, milk production will decrease by 1.7 kg compared to normal. The standing time is increased to improve heat dissipation efficiency (the contact area between the fur surface and the air in a standing posture is larger than that in a lying posture, and the heat dissipation efficiency is higher). As the standing time changes, the mammary blood flow also changes accordingly, which in turn affects lactation behavior. In cold seasons, light intensity and carbon dioxide concentration are the main factors affecting the lactation behavior of dairy cows. Studies have shown that when the light intensity is 800 lx and the carbon dioxide concentration is 6×10 -4 When the temperature is suitable, a reasonable feed management plan can ensure the digestibility of feed nutrients and good lactation behavior. Feeding high-energy diets to dairy cows in the middle and late lactation period can significantly increase feed intake, milk production, and milk protein rate, but reduce milk fat rate and feed efficiency.

[0025] From this information, we can know that the lactation behavior of dairy cows is affected by multiple factors such as environmental factors, behavioral factors, and feeding programs. Therefore, in view of the problem that the existing lactation behavior detection method cannot comprehensively and accurately evaluate the lactation behavior of dairy cows, the present invention proposes a new method for evaluating the lactation behavior of dairy cows. The present invention takes multiple factors such as environmental factors (temperature, humidity, light intensity, carbon dioxide concentration), behavioral characteristics (feeding ratio, lying ratio, drinking water ratio) and feeding programs (feed concentrate to roughage ratio, feed nutritional content, feed energy) as influencing factors, and uses the milk production and milk quality of dairy cows on the ranch as evaluation indicators to establish a monitoring system for the lactation behavior of dairy cows on the ranch, so as to ensure the normal lactation of dairy cows on the ranch and improve the efficiency of the ranch.

[0026] Figure 2 1 is a system structure diagram of a dairy cow lactation behavior evaluation system provided by one embodiment of the present invention. Figure 2As shown, an embodiment of the present invention provides a system for evaluating the lactation behavior of dairy cows, the system comprising: a collection unit for acquiring the feeding status information of dairy cows in a cowshed; a processing unit for preprocessing the status information to obtain evaluation information; performing regression analysis on the evaluation information to obtain the influence information of the evaluation information on the lactation behavior; and an evaluation unit for evaluating the lactation behavior of dairy cows in the corresponding cowshed according to the influence information.

[0027] Figure 1 1 is a flow chart of a method for evaluating the lactation behavior of dairy cows provided by one embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a method for evaluating the lactation behavior of a dairy cow, the method comprising:

[0028] Step S10: Acquire the feeding status information of the dairy cows in the cowshed.

[0029] Specifically, it is known that the lactation behavior of cows is affected by environmental factors, behavioral factors, feeding programs and other factors. The scheme of the present invention needs to comprehensively consider these factors that affect the lactation behavior to ensure that the final evaluation results are in line with the actual situation and avoid missing key influencing factors and causing inaccurate results. In the prior art, the research on lactation behavior is relatively mature, but these research directions are generally based on the study of lactation behavior under corresponding climatic conditions. For example, the influence information on the lactation behavior of dairy cows under hot conditions and the influence information on the behavior of dairy cows under cold conditions are studied. These research contents are all relatively targeted, and because there are indeed great differences in the lactation behavior of dairy cows under different climatic conditions. The scheme of the present invention wants to evaluate the lactation behavior of dairy cows in all aspects, and it has to evaluate different environmental conditions. Therefore, the basic concept of the scheme of the present invention is to first distinguish the climatic conditions of the cowshed according to the actual environmental parameters of the cowshed, and then execute different evaluation models based on the distinguished climate scenes to ensure that the final evaluation results are accurate.

[0030] Based on the factors that actually affect the lactation behavior of dairy cows, preferably, the present invention scheme includes the following information on the feeding status of dairy cows in the cowshed: cowshed environment information, dairy cow behavior characteristic information, and dairy cow feeding sub-scheme information. Further subdivided, the cowshed environment information at least includes: the temperature, humidity, light intensity, and carbon dioxide concentration of the cowshed; the cow behavior characteristic information at least includes: the proportion of cows eating, cows lying, and cows drinking water in the herd; the cow feeding scheme information at least includes: the ratio of feed to roughage, feed nutritional content, and feed energy. Of course, there may be other factors that affect the lactation behavior of dairy cows, but other factors may change with the geographical location of the cowshed. Therefore, in order to ensure the applicability of the scheme, the feeding status information at least includes the above information, and other environmental information for the scene is added on this basis. The lactation behavior of dairy cows can also be evaluated based on the method proposed in the scheme of the present invention.

[0031] Different collection methods are required for different collection parameters. When collecting temperature and humidity information, the temperature sensors and humidity sensors set at various locations in the cowshed are used for direct reading. Then, the light intensity is collected through the illuminance meter set in the cowshed, and finally the carbon dioxide concentration in the cowshed is collected based on the carbon dioxide concentration sensor.

[0032] When collecting cow behavior feature information, cow activity video is collected through a video surveillance system installed in a cowshed, and then the collected video screen is framed to obtain multiple image information that is continuous in time, and the image information at the preset monitoring time is extracted, and the image information is preprocessed. Preferably, the preprocessing means at least includes image noise reduction, brightness correction, and grayscale conversion, etc., to ensure that the obtained image information can accurately extract cow behavior features. After completing the image preprocessing, the cow target is identified by a preset target detection algorithm. This target detection algorithm can locate the cow based on the cow contour identified in the image. Then the shape of the identified cow is determined, and the target feature is extracted based on the determined shape to determine which posture the current cow shape corresponds to. There is a big difference between the lying posture of the cow and the standing posture, so the lying cow can be easily identified based on the shape feature. The postures of the cows eating and the cows drinking are similar, so when extracting the target features, it is also necessary to extract the position information, because there is a difference between the feeding area and the drinking area. Based on the extracted position feature information, the cows eating and the cows drinking can be well distinguished. Based on the total number of cows identified in the complete scenario, or the total number of cows pre-recorded, combined with the identified number of lying cows, drinking cows and feeding cows, the proportion of lying cows, drinking cows and feeding cows in the herd can be directly obtained.

[0033] Feeding plan information can be obtained directly through front-end feed procurement information and feed mixing information.

[0034] After the cow feeding status information of the cowshed is obtained, it is necessary to judge the climate stage of the current cowshed to ensure that the subsequent evaluation method is applicable to the current climate conditions. Preferably, the temperature and humidity of the current cowshed are compared with the temperature range and humidity range of each preset climate stage to determine which preset climate stage the climate of the current cowshed is; wherein the preset climate stage includes: cold climate, hot climate and suitable climate. For example, the situation where the temperature is lower than 15°C is positioned as a cold climate, the temperature of 15°C-28°C is positioned as a suitable climate, and the temperature higher than 28°C is positioned as a hot climate. When judging the climate, the current temperature can be directly compared. Humidity is similar to temperature. Different humidity intervals are preset for different climate stages, and the climate stage is judged by the collected humidity values ​​later. Of course, there may be a situation where the humidity and temperature judgment results are different later. In order to avoid this problem, in another possible implementation, the collected temperature and humidity are weighted averaged, and the corresponding climate stage value is preset based on the weighted average. The climate stage of the current scene can be accurately judged by comparing a value later.

[0035] Step S20: pre-process the status information to obtain evaluation information.

[0036] Specifically, in hot climates, the impact on the lactation of dairy cows is comprehensive. As mentioned above, in order to maintain the balance between heat production and heat dissipation, dairy cows reduce metabolic heat production by reducing feed intake. When the daily dry matter intake (DMI) of dairy cows decreases by 1.4kg, milk production will be 1.7kg lower than normal; by increasing standing time to improve heat dissipation efficiency (the contact area between the fur surface and the air in a standing posture is larger than that in a lying posture, and the heat dissipation efficiency is higher), as the standing time changes, the mammary blood flow also changes accordingly, thereby affecting lactation behavior. Therefore, when evaluating lactation behavior under hot conditions, the evaluation is mainly carried out by analyzing the behavioral characteristic information of dairy cows. The reason why all factors are not analyzed in each state is that in a specific scenario, the influence of other factors on lactation behavior is very small. Therefore, in order to reduce the amount of calculated data, this part of the data with little influence can be directly discarded, and only the directly related parameters are analyzed, thereby greatly saving computing power and shortening the evaluation response time of the system while ensuring accurate evaluation.

[0037] Based on this, for different climatic conditions, the applicable evaluation information is set as follows: the evaluation information under cold climate includes: the temperature, humidity, light intensity and carbon dioxide concentration of the cowshed; the evaluation information under hot climate includes: the temperature of the cowshed, the humidity of the cowshed, the proportion of cows eating, the proportion of cows lying, and the proportion of cows drinking water; the evaluation information under suitable conditions includes: the ratio of concentrate to roughage, the nutritional content of feed and the energy of feed. Among them, suitable climate means that the temperature and humidity are suitable for the activities of dairy cows, so the only factor affecting the lactation behavior of dairy cows is the feed situation. Therefore, under suitable conditions, the corresponding feeding situation evaluation can be carried out.

[0038] Step S30: performing regression analysis on the evaluation information to obtain information on the impact of the evaluation information on lactation behavior.

[0039] Specifically, lactation behavior includes: milk production and milk quality. Therefore, when evaluating lactation behavior, it is necessary to evaluate milk production and milk quality respectively. Preferably, the scheme of the present invention formulates corresponding evaluation models for milk production and milk quality respectively. Therefore, the scheme of the present invention also proposes a method for constructing a milk production evaluation model and a milk quality evaluation model. Including: obtaining the preset milk production evaluation model and the preset milk production quality evaluation model; collecting historical monitoring data of the cowshed and the lactation behavior influencing information in the dairy cow animal husbandry knowledge base; wherein the historical monitoring data of the cowshed and the lactation behavior influencing information both include recorded scene information and lactation behavior information under the corresponding scene information; using the historical monitoring data of the cowshed and the lactation behavior influencing information as training samples, obtaining a milk production evaluation model based on the LightGBM regression algorithm, and obtaining a milk quality evaluation model based on the random forest regression algorithm.

[0040] In one possible real-time approach, the training data collected for the construction of a milk production model in cold climates is shown in Table 1:

[0041]

[0042] Table 1 Historical monitoring data of cattle houses in cold climates

[0043] Based on the historical monitoring data, the influence relationship between environmental parameters and milk production can be accurately understood. The milk production evaluation model obtained based on the training data can then make corresponding milk production predictions based on the environmental parameters collected in the real-time cowshed.

[0044] Step S40: evaluating the lactation behavior of the cows in the corresponding cowshed according to the impact information.

[0045] In a possible implementation, cows in different lactation stages have different sensitivities to environmental parameters, so before lactation evaluation, cows in different lactation stages are monitored separately, which is greatly beneficial to the accuracy of the final evaluation.

[0046] In the embodiment of the present invention, milk production and milk quality are used as evaluation basis to comprehensively measure the lactation behavior of dairy cows, and the method of measuring lactation behavior by a single indicator is compared to meet the needs of the ranch to increase milk production and ensure milk quality, so as to improve the efficiency of the ranch.

[0047] The embodiment of the present invention further provides a computer-readable storage medium, on which instructions are stored, which, when executed on a computer, enable the computer to execute the above-mentioned method for evaluating the lactation behavior of dairy cows.

[0048] Those skilled in the art will understand that all or part of the steps in the method for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions for making a single-chip microcomputer, a chip or a processor (processor) perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0049] The optional embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the technical concept of the embodiments of the present invention, the technical scheme of the embodiments of the present invention can be subjected to a variety of simple modifications, and these simple modifications all belong to the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0050] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A method for evaluating the lactation behavior of dairy cows, It is characterized in that The method comprises: Get the feeding status information of dairy cows in the cowshed; The dairy cow feeding status information of the cowshed includes: Cowshed environment information, cow behavior characteristics information and cow feeding plan information; The cowshed environment information at least includes: Temperature, humidity, light intensity and carbon dioxide concentration in the barn; The cow behavior characteristic information at least includes: The percentage of cows eating, lying and drinking in the dairy herd; The feeding plan information of the dairy cows at least includes: Feed concentrate-to-roughage ratio, feed nutrient content and feed energy; The step of obtaining the feeding status information of the dairy cows in the cowshed includes: Perform frame processing on the collected video information to obtain multiple cowshed image information; Preprocessing the cowshed image information, and using a multi-target detection algorithm to identify dairy cows in the preprocessed cowshed image information; Extract shape features of identified cows and perform cluster analysis on the extracted features to obtain cow behavior feature information; Preprocessing the status information to obtain evaluation information; Performing regression analysis on the evaluation information to obtain information on the impact of the evaluation information on lactation behavior; Before performing regression analysis on the evaluation information, the method further includes: Interpret current weather conditions, including: Compare the current temperature and humidity of the cowshed with the temperature range and humidity range of each preset climate stage to determine which preset climate stage the current climate of the cowshed belongs to; The preset climate stages include: cold climate, hot climate and suitable climate; Different climate stages correspond to different evaluation information; among them, The cold climate assessment information includes: Temperature, humidity, light intensity and carbon dioxide concentration in the barn; The hot climate assessment information includes: The temperature of the cowshed, the humidity of the cowshed, the percentage of cows eating, lying, and drinking in the herd; The evaluation information under the suitable climate includes: Feed concentrate-to-roughage ratio, feed nutrient content and feed energy; The lactation behavior of the dairy cows in the corresponding cowshed is evaluated according to the impact information.

2. The method according to claim 1, It is characterized in that The lactation behaviors include: milk production and milk quality; The performing regression analysis on the evaluation information to obtain information on the impact of the evaluation information on lactation behavior includes: The evaluation information under each climate stage is used as input parameters, and is respectively introduced into a preset milk yield evaluation model and a preset milk yield quality model, and the corresponding milk yield impact index and milk yield quality impact index are output; The step of evaluating the lactation behavior of the cows in the corresponding cowshed according to the impact information includes: Based on the milk production impact index and the milk production quality impact index, the milk production amount and milk production quality of the dairy cow in the current scenario are predicted; The milk yield prediction results and milk quality prediction results are used as the evaluation results of the lactation behavior of dairy cows.

3. The method according to claim 2, It is characterized in that The method further comprises: Obtaining the preset milk production evaluation model and the preset milk production quality evaluation model; Collect historical monitoring data of cowshed and information on lactation behavior in dairy cow animal husbandry knowledge base; The historical monitoring data of the cowshed and the lactation behavior impact information both include recorded scene information and lactation behavior information under the corresponding scene information; The historical monitoring data of the cowshed and the information on the impact of lactation behavior were used as training samples, and a milk production evaluation model was obtained based on the LightGBM regression algorithm, and a milk production quality evaluation model was obtained based on the random forest regression algorithm.

4. A dairy cow lactation behavior evaluation system, It is characterized in that The system comprises: The collection unit is used to obtain the feeding status information of dairy cows in the cowshed; wherein, The dairy cow feeding status information of the cowshed includes: Cowshed environment information, cow behavior characteristics information and cow feeding plan information; The cowshed environment information at least includes: Temperature, humidity, light intensity and carbon dioxide concentration in the barn; The cow behavior characteristic information at least includes: The percentage of cows eating, lying and drinking in the dairy herd; The feeding plan information of the dairy cows at least includes: Feed concentrate-to-roughage ratio, feed nutrient content and feed energy; The step of obtaining the feeding status information of the dairy cows in the cowshed includes: Perform frame processing on the collected video information to obtain multiple cowshed image information; Preprocessing the cowshed image information, and using a multi-target detection algorithm to identify dairy cows in the preprocessed cowshed image information; Extract shape features of identified cows and perform cluster analysis on the extracted features to obtain cow behavior feature information; A processing unit, used to pre-process the state information to obtain evaluation information; perform regression analysis on the evaluation information to obtain information on the impact of the evaluation information on lactation behavior; Before performing regression analysis on the evaluation information, the method further includes: Interpret current weather conditions, including: Compare the current temperature and humidity of the cowshed with the temperature range and humidity range of each preset climate stage to determine which preset climate stage the current climate of the cowshed belongs to; The preset climate stages include: cold climate, hot climate and suitable climate; Different climate stages correspond to different evaluation information; among them, The cold climate assessment information includes: Temperature, humidity, light intensity and carbon dioxide concentration in the barn; The hot climate assessment information includes: The temperature of the cowshed, the humidity of the cowshed, the percentage of cows eating, lying, and drinking in the herd; The evaluation information under the suitable climate includes: Feed concentrate-to-roughage ratio, feed nutrient content and feed energy; An evaluation unit is used to evaluate the lactation behavior of the cows in the corresponding cowshed according to the impact information.

5. A computer-readable storage medium having instructions stored thereon, which, when executed on a computer, enables the computer to execute the method for evaluating the lactation behavior of a dairy cow according to any one of claims 1 to 3.

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