Dynamic evaluation method and system for nutritional requirements of dairy cows

Abstract

The invention relates to the technical field of intelligent breeding, in particular to a dairy cow nutritional requirement dynamic evaluation method and system, and the method comprises the following steps: S1, calculating a circadian rhythm phase parameter; s2, establishing fiber-decomposing bacteria activity coefficients under different rhythm phases; s3, correcting the theoretical digestibility of the NDF in the roughage according to the activity coefficient of the cellulose-decomposing bacteria obtained in the S2; s4, calculating dynamic basic metabolism energy consumption for maintaining the body temperature and behavior activities in combination with data of an environment temperature and humidity sensor; s5, outputting the day and night distribution proportion of protein and energy substances; and S6, controlling a feed feeding time sequence according to the rumen pH fluctuation threshold value. By monitoring the day and night rhythm and rumen environment state of the dairy cow in real time and dynamically regulating and controlling the precise proportion and feeding time sequence of the fine and coarse feed, the feed utilization efficiency is effectively improved, high cooperation of nutrition supply and physiological needs of the dairy cow is guaranteed, and the production performance and breeding economic benefits of the dairy cow are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent breeding, and particularly relates to a method and system for dynamically evaluating the nutritional requirements of dairy cows. Background Art

[0002] In the process of modern dairy cow breeding, the evaluation of the nutritional requirements of dairy cows has an important impact on their health status, lactation performance and feed utilization rate; the physiological metabolism of dairy cows has obvious circadian rhythm characteristics, and its core body temperature, rumination behavior, rumen microbial activity and feed digestibility are all dynamically regulated by the circadian rhythm; at the same time, the nutritional requirements of dairy cows change with different lactation stages, and reasonably allocating the supply ratio of protein and energy substances is the key to improving the production efficiency of dairy cows; in addition, the stability of the rumen environment directly affects the digestion and absorption efficiency of dairy cows, and too large a fluctuation in rumen pH will lead to rumen acidosis or indigestion; therefore, in the process of dairy cow feeding, it is necessary to accurately regulate the ratio and feeding time sequence of feed according to the physiological rhythm, energy metabolism requirements and rumen environmental status of dairy cows, so as to optimize the nutritional supply structure of dairy cows.

[0003] However, most of the existing methods for evaluating the nutritional requirements of dairy cows adopt a static formula calculation mode, and only roughly estimate based on basic indicators such as feed composition and the body weight and milk yield of dairy cows, without fully considering the physiological rhythm and dynamic metabolic changes of dairy cows, resulting in a lack of pertinence in feed supply; in addition, the existing technologies usually cannot monitor the core body temperature, rumination behavior and rumen microbial activity of dairy cows in real time, and it is difficult to accurately evaluate the dynamic impact of the rumen internal environment on nutrient digestion, resulting in a decrease in feed utilization rate; at the same time, the traditional feeding method is not optimized and regulated in combination with the dynamic changes of rumen pH in dairy cows, which may cause abnormal fluctuations in rumen pH and affect the health of dairy cows. Therefore, there is an urgent need for a method and system for dynamically evaluating the nutritional requirements of dairy cows to solve the above problems. Summary of the Invention

[0004] Based on the above purpose, the present invention provides a method and system for dynamically evaluating the nutritional requirements of dairy cows.

[0005] A method for dynamically evaluating the nutritional requirements of dairy cows includes the following steps:

[0006] S1: Continuously collect the core body temperature fluctuation curve and rumination interval cycle data of dairy cows within 48 hours through a rumen capsule sensor, and calculate the circadian rhythm phase parameter in combination with the data of the light intensity sensor;

[0007] S2: Based on the circadian rhythm phase parameter obtained in S1, synchronously detect the peak period of the concentration of volatile fatty acids in the rumen fluid, and establish the activity coefficient of cellulolytic bacteria under different rhythm phases;

[0008] S3: According to the fiber decomposing bacteria activity coefficient obtained in S2, the theoretical digestibility of NDF in roughage is corrected to generate a real-time effective NDF supply;

[0009] S4: The ratio of standing time to lying time is obtained through the three-dimensional accelerometer worn by the cow, and combined with the data from the ambient temperature and humidity sensors, the dynamic basal metabolic energy consumption for maintaining body temperature and behavioral activities is calculated;

[0010] S5: Input the effective NDF supply of S3 and the dynamic basal metabolic energy consumption of S4 into the nutrient spatiotemporal matrix, match the calcium-phosphorus ion channel opening time window according to the current lactation stage, and output the diurnal distribution ratio of protein and energy substances;

[0011] S6: Based on the day and night distribution ratio of S5, the daily diet is divided into high-metabolizable energy feed in the light period and high-fiber slow-release feed in the dark period, and the feeding sequence is controlled according to the rumen pH fluctuation threshold.

[0012] Optionally, the S1 specifically includes:

[0013] S11: The rumen capsule sensor is implanted into the rumen of the dairy cow. The rumen capsule sensor has a built-in temperature sensing module and a pressure sensing module. It continuously monitors the rumen environment temperature and rumen pressure values ​​once per minute, and transmits the data to the data receiving terminal in real time through wireless communication. The continuous monitoring time is 48 hours.

[0014] S12: The continuously collected rumen environment temperature values ​​are processed by data smoothing and filtering to form a core body temperature fluctuation curve of the dairy cow within 48 hours;

[0015] S13: inputting the rumen pressure value into the pressure change rate calculation formula, recording the time point when the pressure value reaches the pressure change threshold, the time difference between two adjacent pressure threshold time points is defined as a rumination interval cycle, and sequentially obtaining the rumination interval cycle data of the dairy cow within 48 hours;

[0016] S14: installing a light intensity sensor in the environment where the cow is located, measuring the ambient light intensity value in real time at a frequency of once per minute, and obtaining 48 hours of continuous light intensity data;

[0017] S15: Perform Fourier transform on the core body temperature fluctuation curve and rumination interval period data to obtain the circadian rhythm characteristic frequency and phase of the cow's body temperature and rumination behavior;

[0018] S16: The light intensity data is processed by Fourier transform to obtain the characteristic frequency and phase of the circadian rhythm of the ambient light, and the frequency and phase are matched in time domain with the characteristic phase of the circadian rhythm of the cow's body temperature and rumination behavior obtained in S15 to calculate the circadian rhythm phase parameters.

[0019] Optionally, S16 specifically includes:

[0020] S161: Process the ambient light intensity data, cow body temperature fluctuation curve data, and rumination interval period data through Fourier transform to obtain the ambient light circadian rhythm characteristic frequency f L and the characteristic phase φ L , the cow core body temperature circadian rhythm characteristic frequency f T and the characteristic phase φ T as well as the cow rumination behavior circadian rhythm characteristic frequency f R and the characteristic phase φ R ;

[0021] S162: Based on the ambient light circadian rhythm characteristic frequency f L respectively perform frequency consistency matching with the cow core body temperature and rumination behavior circadian rhythm characteristic frequencies f T , f R to obtain the frequency matching degree parameter C f ;

[0022] S163: Based on the ambient light circadian rhythm characteristic phase φ L respectively perform phase difference calculation with the cow core body temperature and rumination behavior circadian rhythm characteristic phases φ T , φ R to obtain the circadian rhythm phase difference parameter P φ ;

[0023] S164: Substitute the frequency matching degree parameter C f and the circadian rhythm phase difference parameter P φ into the circadian rhythm phase parameter calculation formula to obtain the circadian rhythm phase parameter D p , and its calculation formula is: In the formula; C f is the frequency matching degree parameter; P φ is the circadian rhythm phase difference parameter; π is the pi, and its value is 3.1416.

[0024] Optionally, S2 specifically includes:

[0025] S21: Through the volatile fatty acid concentration detection probe built in the rumen capsule sensor, detect the concentrations of acetic acid, propionic acid, and butyric acid in the rumen fluid in real time at a sampling frequency of once every 15 minutes, and transmit the concentration data to the data receiving terminal to obtain a 48-hour continuous volatile fatty acid concentration change curve;

[0026] S22: Perform first derivative calculation on the volatile fatty acid concentration change curve, extract the time period when the derivative is zero and the second derivative is less than zero as the volatile fatty acid concentration peak time period, and record the time point corresponding to each peak;

[0027] S23: According to the circadian rhythm phase parameter calculated in claim S1, divide the peak period of volatile fatty acid concentration into a peak period during the light phase and a peak period during the dark phase according to the circadian rhythm phase parameter;

[0028] S24: During the peak periods of the light phase and the dark phase respectively, input the peak concentration of volatile fatty acids detected in the corresponding periods into the fiber decomposing bacteria activity calculation formula to obtain the fiber decomposing bacteria activity coefficient F c ;

[0029] S25: According to the fiber decomposing bacteria activity coefficient obtained in S24, establish a fiber decomposing bacteria activity coefficient database corresponding to the light phase and the dark phase respectively, and form the fiber decomposing bacteria activity coefficient under different rhythm phases.

[0030] Optionally, the specific steps of S3 include:

[0031] S31: Collect the roughage sample currently eaten by the dairy cow, and use a near-infrared spectroscopy analyzer to detect and obtain the theoretical digestibility of NDF in the roughage, denoted as parameter N d ;

[0032] S32: Substitute the theoretical digestibility parameter N d and the fiber decomposing bacteria activity coefficient F c into the NDF theoretical digestibility correction formula to obtain the corrected effective NDF digestibility N r ;

[0033] S33: Substitute the corrected effective NDF digestibility parameter N r into the effective NDF supply amount calculation formula to generate the real-time effective NDF supply amount. The specific calculation formula is: N s = Q × C N × N r , where N s is the real-time effective NDF supply amount; Q is the current actual roughage intake; C N is the NDF content in the roughage.

[0034] Optionally, the specific steps of S4 include:

[0035] S41: Fix the wearable three-dimensional accelerometer with a built-in three-axis accelerometer on the neck of the dairy cow, continuously collect the acceleration data of the dairy cow in the X-axis, Y-axis, and Z-axis directions at a frequency of once per second, and calculate the acceleration synthesis vector parameter A in real time v ;

[0036] S42: Set the dairy cow behavior posture determination threshold A th . When A v ≥ A th , it is determined as a standing posture. When Av <A th When it is determined to be in the lying posture, the continuous standing and lying time data of the dairy cow within 48 hours can be obtained;

[0037] S43: According to the standing and lying time data obtained in S42, calculate the standing and lying time ratio parameter R of the dairy cow sl ;

[0038] S44: Install temperature and humidity sensors in the living environment of the dairy cow, and collect environmental temperature parameters and environmental humidity parameters in real time at a frequency of once per minute, and calculate the environmental temperature-humidity index parameter THI;

[0039] S45: Input the standing and lying time ratio parameter R sl and the environmental temperature-humidity index parameter THI into the dynamic basal metabolic energy consumption calculation formula of the dairy cow, and calculate the dynamic basal metabolic energy consumption parameter for maintaining body temperature and behavioral activities. The formula is: E b = E m × (1 + k1 × R sl + k2 × THI), where E b is the dynamic basal metabolic energy consumption parameter; E m is the basal metabolic energy consumption benchmark value of the dairy cow; k1 is the behavioral activity coefficient; k2 is the heat stress coefficient.

[0040] Optionally, the specific steps of S5 include:

[0041] S51: Construct a nutritional spatio-temporal matrix of dairy cows, specifically with the effective NDF supply parameter N s as the row and the dynamic basal metabolic energy consumption parameter E b as the column;

[0042] S52: Determine the current lactation stage L of the dairy cow according to the number of days after calving p ;

[0043] S53: According to the lactation stage parameter L p call the preset calcium and phosphorus ion channel opening time window database to determine the opening time window T of the calcium and phosphorus ion channels w ;

[0044] S54: Based on the tantalum and phosphorus ion channel opening time window parameter T determined in S53 w , match the matrix elements corresponding to the time window in the nutritional spatio-temporal matrix to obtain the energy substance diurnal distribution ratio R e and the protein diurnal distribution ratio R p .

[0045] Optionally, the specific steps of S6 include:

[0046] S61: Determine the total amount of nutrients required by dairy cows during the light period and the dark period based on the daily and nightly distribution ratios of proteins and energy substances obtained in S5; at the same time, select high-starch and high-sugar feeds as high-metabolic-energy feeds during the light period, and select high-fiber roughage as high-fiber slow-release feeds during the dark period;

[0047] S62: According to the circadian rhythm phase in which the dairy cow is currently located, preset the high-metabolic-energy feed during the light period and the high-fiber slow-release feed during the dark period in the automatic feeding device for the corresponding time periods;

[0048] S63: Real-time monitor the pH value of the rumen environment in the dairy cow through a rumen capsule sensor, and transmit it to the data receiving terminal by wireless communication to obtain the real-time fluctuation of the rumen pH value;

[0049] S64: Set a rumen pH fluctuation threshold according to the real-time fluctuation of the rumen pH value, and compare the real-time monitored rumen pH value with this threshold; and dynamically control the feed feeding timing according to the comparison result between the rumen pH value and the rumen pH fluctuation threshold.

[0050] Optionally, S64 specifically includes:

[0051] S641: Real-time monitor the rumen pH value through a rumen capsule sensor, denoted as pH r ;

[0052] S642: Set the rumen pH fluctuation threshold pH t ;

[0053] S643: Compare the real-time monitored rumen pH value pH r with the rumen pH fluctuation threshold pH t and execute different feed feeding control strategies according to the comparison result. The specific control rules include:

[0054] Control rule 1, if pH r ≥pH t , it is determined that the rumen pH is in a relatively stable state, and the high-metabolic-energy feed during the light period is allowed to be fed;

[0055] Control rule 2, if pH r <pH t , it is determined that the rumen pH has entered the low pH risk zone, immediately stop feeding the high-metabolic-energy feed during the light period, and delay starting to feed the high-fiber slow-release feed during the dark period.

[0056] A dynamic evaluation system for dairy cow nutritional requirements, used to implement the above-mentioned dynamic evaluation method for dairy cow nutritional requirements, includes the following modules:

[0057] Data acquisition module: It is used to continuously collect the core body temperature fluctuation curve, rumination interval cycle data, and the change data of volatile fatty acid concentration in rumen fluid of dairy cows within 48 hours through rumen capsule sensors, and to obtain the behavior posture data of dairy cows in real time through a three-dimensional accelerometer, and simultaneously collect environmental parameters in real time by using a light intensity sensor and an environmental temperature and humidity sensor;

[0058] Rhythm analysis module: It is connected to the data acquisition module and is used to calculate the circadian rhythm phase parameters of dairy cows according to the core body temperature fluctuation curve, rumination interval cycle data, and light intensity data, and to determine the peak period of volatile fatty acid concentration in combination with the change data of volatile fatty acid concentration, and establish the activity coefficient of fiber-decomposing bacteria under different rhythm phases;

[0059] Digestibility correction module: It is connected to the rhythm analysis module and is used to correct the theoretical digestibility of NDF in roughage in real time according to the activity coefficient of fiber-decomposing bacteria to generate a real-time effective NDF supply;

[0060] Energy consumption calculation module: It is connected to the data acquisition module and is used to calculate the ratio of standing time to lying time of dairy cows according to the behavior posture data of dairy cows, and to calculate the dynamic basal metabolic energy consumption for dairy cows to maintain body temperature and behavioral activities in combination with environmental parameters;

[0061] Nutrition distribution module: It is connected to the digestibility correction module and the energy consumption calculation module. After receiving the effective NDF supply and dynamic basal metabolic energy consumption data, it inputs the nutrition spatio-temporal matrix, matches the opening time window of calcium and phosphorus ion channels according to the current lactation stage, and outputs the daily and nightly distribution ratios of protein and energy substances;

[0062] Feeding control module: It is connected to the nutrition distribution module and the data acquisition module, and is used to divide the diet into high-metabolic-energy feed during the light period and high-fiber slow-release feed during the dark period according to the daily and nightly distribution ratios of protein and energy substances, and to dynamically control the specific feeding time sequence of concentrate and roughage according to the rumen pH fluctuation threshold.

[0063] Advantages of the present invention:

[0064] In the present invention, by collecting the core body temperature fluctuation curve, rumination interval cycle, volatile fatty acid concentration in rumen fluid, behavior posture data, and environmental parameters of dairy cows in real time, combining the Fourier transform analysis method to calculate the circadian rhythm phase parameters of dairy cows, and based on the peak period of volatile fatty acid concentration under different rhythm phases, constructing an activity coefficient model of fiber-decomposing bacteria, the dynamic evaluation of the rumen microbial digestion ability of dairy cows is realized. Through this method, the theoretical digestibility of NDF in roughage can be accurately corrected to generate a real-time effective NDF supply, and the dynamic basal metabolic energy consumption is calculated in combination with the ratio of standing time to lying time of dairy cows and the environmental temperature and humidity index, making the nutritional requirement assessment more accurate and capable of adapting to the nutritional requirement changes of dairy cows in different lactation stages.

[0065] In the present invention, by dividing the high-metabolic-energy feed during the light period and the high-fiber slow-release feed during the dark period according to the diurnal distribution ratio of proteins and energy substances, and by dynamically adjusting the feed feeding sequence in real time by monitoring the rumen pH value and combining the rumen pH fluctuation threshold, precise regulation of the supply of concentrate and roughage is achieved. Through this technology, abnormal fluctuations in rumen pH can be effectively reduced, feed digestion efficiency can be improved, the energy metabolism balance of dairy cows can be optimized, thereby enhancing the production performance of dairy cows, while reducing feed waste and improving the economic benefits of breeding. Brief Description of the Drawings

[0066] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only those of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0067] Figure 1 Schematic diagram of the dynamic assessment method for the nutritional requirements of dairy cows according to the embodiments of the present invention;

[0068] Figure 2 Schematic diagram of the dynamic assessment system for the nutritional requirements of dairy cows according to the embodiments of the present invention. Detailed Embodiments

[0069] The present invention will be described in detail below in conjunction with the drawings and specific embodiments. At the same time, it should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; moreover, the drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0070] It should be pointed out that in the specification, when referring to "an embodiment", "embodiment", "exemplary embodiment", "some embodiments", etc., it indicates that the described embodiment may include specific features, structures or characteristics, but not necessarily every embodiment includes such specific features, structures or characteristics. Additionally, when combining an embodiment to describe a specific feature, structure or characteristic, implementing such a feature, structure or characteristic in combination with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the relevant art.

[0071] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0072] like Figure 1 As shown, a method for dynamically assessing the nutritional requirements of dairy cows comprises the following steps:

[0073] S1: The core body temperature fluctuation curve and rumination interval cycle data of dairy cows within 48 hours are continuously collected through the rumen capsule sensor, and the circadian rhythm phase parameters are calculated in combination with the light intensity sensor data;

[0074] S2: Based on the circadian rhythm phase parameters obtained in S1, the peak period of volatile fatty acid concentration in rumen fluid was synchronously detected to establish the activity coefficient of fiber decomposing bacteria under different rhythm phases;

[0075] S3: According to the activity coefficient of fiber decomposing bacteria obtained in S2, the theoretical digestibility of NDF (neutral detergent fiber) in roughage is corrected to generate real-time effective NDF supply;

[0076] S4: The ratio of standing time to lying time is obtained through the three-dimensional accelerometer worn by the cow, and combined with the data from the ambient temperature and humidity sensors, the dynamic basal metabolic energy consumption for maintaining body temperature and behavioral activities is calculated;

[0077] S5: Input the effective NDF supply of S3 and the dynamic basal metabolic energy consumption of S4 into the nutrient spatiotemporal matrix, match the calcium-phosphorus ion channel opening time window according to the current lactation stage, and output the diurnal distribution ratio of protein and energy substances;

[0078] S6: Based on the day and night distribution ratio of S5, the daily diet is divided into high-metabolizable energy feed in the light period and high-fiber slow-release feed in the dark period, and the feeding sequence is controlled according to the rumen pH fluctuation threshold.

[0079] S1 specifically includes:

[0080] S11: The rumen capsule sensor is implanted into the rumen of the dairy cow. The rumen capsule sensor has a built-in temperature sensing module and a pressure sensing module. It continuously monitors the rumen environment temperature and rumen pressure values ​​once per minute, and transmits the data to the data receiving terminal in real time through wireless communication. The continuous monitoring time is 48 hours.

[0081] S12: After processing the continuously collected rumen internal environment temperature values through data smoothing filtering, a core body temperature fluctuation curve of the dairy cow within 48 hours is formed;

[0082] S13: Input the rumen pressure values into the pressure change rate calculation formula, record the time points when the pressure values reach the pressure change thresholds, and define the time difference between adjacent two pressure threshold time points as a rumination interval period, and sequentially obtain the rumination interval period data of the dairy cow within 48 hours;

[0083] S14: Install a light intensity sensor in the environment where the dairy cow is located, and measure the environmental light intensity values in real time at a frequency of once per minute to obtain continuous light intensity data for 48 hours;

[0084] S15: Perform Fourier transform processing on the core body temperature fluctuation curve and the rumination interval period data to obtain the circadian rhythm characteristic frequencies and phases of the dairy cow's body temperature and rumination behavior;

[0085] S16: Perform Fourier transform processing on the light intensity data to obtain the circadian rhythm characteristic frequencies and phases of the environmental light, and perform time domain matching on them with the circadian rhythm characteristic phases of the dairy cow's body temperature and rumination behavior obtained in S15, and calculate to obtain the circadian rhythm phase parameters; Through the above specific steps, it is possible to achieve precise real-time monitoring and quantitative analysis of the core body temperature fluctuation and rumination behavior in the rumen of the dairy cow, and accurately combine the environmental light rhythm data to calculate the circadian rhythm phase parameters, effectively improving the data basis accuracy and reliability of the subsequent dynamic assessment method for the nutritional requirements of dairy cows.

[0086] The specific calculation of the circadian rhythm phase parameters in S16 includes:

[0087] S161: Through Fourier transform processing of the environmental light intensity data, the dairy cow body temperature fluctuation curve data, and the rumination interval period data, obtain the circadian rhythm characteristic frequency f L of the environmental light and the characteristic phase φ L , the circadian rhythm characteristic frequency f T of the dairy cow's core body temperature and the characteristic phase φ T , and the circadian rhythm characteristic frequency f R of the dairy cow's rumination behavior and the characteristic phase φ R ;

[0088] S162: Based on the circadian rhythm characteristic frequency f L of the environmental light, respectively perform frequency consistency matching with the circadian rhythm characteristic frequencies f T , f R of the dairy cow's core body temperature and rumination behavior to obtain the frequency matching degree parameter C f , and its calculation formula is: In the formula, f L is the circadian rhythm characteristic frequency of the environmental light, fi Representing the characteristic frequency f of the circadian rhythm of the core body temperature of dairy cows T or the characteristic frequency f of the circadian rhythm of the rumination behavior of dairy cows R , with the unit of Hz;

[0089] S163: Based on the phase φ of the circadian rhythm characteristics of environmental light L calculate the phase difference with the phase φ of the circadian rhythm characteristics of the core body temperature and rumination behavior of dairy cows respectively T 、φ R to obtain the circadian rhythm phase difference parameter P φ , and its calculation formula is: P φ =|φ L -φ i |, where φ L is the phase of the circadian rhythm characteristics of environmental light, with the unit of radian (rad); φ i respectively represent the phase φ of the circadian rhythm characteristics of the core body temperature of dairy cows T or the phase φ of the circadian rhythm characteristics of the rumination behavior of dairy cows R , with the unit of radian (rad);

[0090] S164: Substitute the frequency matching degree parameter C f and the circadian rhythm phase difference parameter P φ into the calculation formula of the circadian rhythm phase parameter to obtain the circadian rhythm phase parameter D p , and its calculation formula is: In the formula; C f is the frequency matching degree parameter; P φ is the circadian rhythm phase difference parameter; π is the pi, with a value of 3.1416; Through the above steps, the time-domain matching relationship between the core body temperature, rumination behavior of dairy cows and the circadian rhythm of environmental light intensity can be accurately quantified, and accurate circadian rhythm phase parameters can be obtained, providing a reliable basis for the subsequent dynamic assessment of the nutritional requirements of dairy cows.

[0091] S2 specifically includes:

[0092] S21: Through the volatile fatty acid concentration detection probe built in the rumen capsule sensor, detect the concentrations of acetic acid, propionic acid and butyric acid in the rumen fluid in real time at a sampling frequency of once every 15 minutes, and transmit the concentration data to the data receiving terminal to obtain a 48-hour continuous volatile fatty acid concentration change curve;

[0093] S22: Perform the first derivative calculation on the volatile fatty acid concentration change curve, extract the time period when the derivative is zero and the second derivative is less than zero as the peak time period of the volatile fatty acid concentration, and record the time point corresponding to each peak;

[0094] S23: According to the circadian rhythm phase parameter calculated in claim S1, divide the peak period of volatile fatty acid concentration into a peak period during the light phase and a peak period during the dark phase according to the circadian rhythm phase parameter; the specific division formula is: T L ={T p |D p ≥0.5} and T D ={T p |D p <0.5}, where T L is the set of peak periods of volatile fatty acid concentration during the light phase, representing all peak periods of volatile fatty acid concentration corresponding to the circadian rhythm phase parameter value greater than or equal to 0.5; T D is the set of peak periods of volatile fatty acid concentration during the dark phase, representing all peak periods of volatile fatty acid concentration corresponding to the circadian rhythm phase parameter value less than 0.5; T p is the specific time point corresponding to the peak period of volatile fatty acid concentration, representing the occurrence time of each peak of volatile fatty acid concentration obtained in step S22; D p is the circadian rhythm phase parameter, the matching degree of the dairy cow's physiological rhythm and the environmental light rhythm obtained in step S16, with a value range of 0 to 1;

[0095] S24: Respectively within the peak periods during the light phase and the dark phase, input the peak concentration of volatile fatty acids detected in the corresponding periods into the fiber-decomposing bacteria activity calculation formula to obtain the fiber-decomposing bacteria activity coefficient F c , and the formula is where F c is the fiber-decomposing bacteria activity coefficient; V fa is the average concentration of the peak concentration of volatile fatty acids in the rumen fluid during the peak period, in mmol / L; V b is the average baseline concentration of volatile fatty acids in the rumen fluid during the non-peak period, in mmol / L;

[0096] S25: According to the fiber-decomposing bacteria activity coefficient obtained in S24, respectively establish fiber-decomposing bacteria activity coefficient databases corresponding to the light phase and the dark phase to form fiber-decomposing bacteria activity coefficients under different rhythm phases; through the above steps, the peak periods of volatile fatty acid concentration in the dairy cow's rumen fluid can be accurately identified, and accurate fiber-decomposing bacteria activity coefficients can be established based on the circadian rhythm phase parameter, providing accurate data support for the subsequent correction of the NDF theoretical digestibility.

[0097] S3 specifically includes:

[0098] S31: Collect the current roughage sample eaten by the dairy cow, and use a near-infrared spectroscopy analyzer to detect and obtain the theoretical digestibility of NDF in the roughage, denoted as parameter N d ;

[0099] S32: Substitute the theoretical digestibility parameter N d and the cellulolytic bacteria activity coefficient F c into the NDF theoretical digestibility correction formula to obtain the corrected effective NDF digestibility N r , and the formula is: N r = N d ×(1 + F c ), where N r is the corrected effective NDF digestibility, representing the actual NDF digestibility after correction by the cellulolytic bacteria activity, expressed as a percentage;

[0100] S33: Substitute the corrected effective NDF digestibility parameter N r into the effective NDF supply amount calculation formula to generate the real-time effective NDF supply amount. The specific calculation formula is: N s = Q × C N × N r , where N s is the real-time effective NDF supply amount, representing the amount of effective NDF that the roughage currently ingested by the dairy cow can provide, in grams; Q is the current actual roughage intake, representing the dry matter amount of roughage actually ingested by the dairy cow at the current time, in grams; C N is the NDF content in the roughage, representing the proportion of neutral detergent fiber in the roughage dry matter, expressed as a percentage; Through the above steps, the real-time correction of the NDF theoretical digestibility in the roughage according to the cellulolytic bacteria activity coefficient is realized, so as to obtain accurate effective NDF supply amount parameters and ensure the real-time and accuracy of the data in the dairy cow nutritional requirement assessment method.

[0101] S4 specifically includes:

[0102] S41: Fix the wearable three-dimensional accelerometer with an internal triaxial accelerometer on the neck of the dairy cow, continuously collect the acceleration data of the dairy cow in the X-axis, Y-axis and Z-axis directions at a frequency of 1 time per second, and calculate the acceleration synthesis vector parameter A v , and the specific formula is: where A v is the acceleration synthesis vector parameter, representing the comprehensive motion acceleration of the dairy cow at the current moment, in meters per second squared; A x , A y , A z are the real-time acceleration values of the dairy cow in the X-axis, Y-axis and Z-axis directions respectively, and the units are all meters per second squared;

[0103] S42: Set the dairy cow behavior posture determination threshold A th , when A v ≥ Ath is determined as the standing posture when, and when A v <A th is determined as the lying posture, so as to obtain the continuous standing and lying time data of the dairy cow within 48 hours;

[0104] S43: According to the standing and lying time data obtained in S42, calculate the standing and lying time ratio parameter R of the dairy cow sl , and the formula is: In the formula; T s is the cumulative standing time of the dairy cow within 48 hours; T l is the cumulative lying time of the dairy cow within 48 hours;

[0105] S44: Install temperature and humidity sensors in the living environment of the dairy cow, and collect environmental temperature parameters and environmental humidity parameters in real time at a frequency of once per minute, and calculate the environmental temperature-humidity index parameter THI. The specific calculation formula is: THI = (1.8×E T +32)-[(0.55 - 0.0055×E H )×(1.8×E T -26)], in the formula, THI is the environmental temperature-humidity index parameter, indicating the degree of heat stress in the environment where the dairy cow is located; E T is the environmental temperature parameter, indicating the real-time temperature of the environment where the dairy cow is located, in degrees Celsius; E H is the environmental humidity parameter, indicating the real-time relative humidity of the environment where the dairy cow is located, in percentage;

[0106] S45: Input the standing and lying time ratio parameter R sl and the environmental temperature-humidity index parameter THI into the dynamic basic metabolic energy consumption calculation formula of the dairy cow, and calculate the dynamic basic metabolic energy consumption parameter for maintaining body temperature and behavioral activities. The formula is: E b = E m ×(1 + k1×R sl + k2×THI), in the formula, E b is the dynamic basic metabolic energy consumption parameter, indicating the real-time basic metabolic energy consumed by the dairy cow for maintaining body temperature and behavioral activities, in megajoules; E m is the basic metabolic energy consumption benchmark value of the dairy cow, indicating the basic metabolic energy consumption of the dairy cow in the standard resting state, in megajoules; k1 is the behavioral activity coefficient, indicating the influence coefficient of the standing and lying behaviors of the dairy cow on the basic metabolic energy consumption; k2 is the heat stress coefficient, indicating the influence coefficient of the environmental temperature-humidity index on the basic metabolic energy consumption; through the steps, accurately quantify the real-time influence of the behavioral posture of the dairy cow and environmental factors on the basic metabolic energy consumption, obtain the dynamic basic metabolic energy consumption parameter, and ensure the accuracy and dynamic adaptability of the nutritional requirement assessment of the dairy cow.

[0107] S5 specifically includes:

[0108] S51: Construct a spatio-temporal matrix of dairy cow nutrition, specifically using the parameter N of the effective NDF supply s as rows, and the parameter E of the dynamic basal metabolic energy consumption b as columns. Each matrix element is the ratio of energy substances and proteins required by dairy cows under the corresponding effective NDF supply and basal metabolic energy consumption;

[0109] S52: Determine the current lactation stage L of the dairy cow according to the number of days postpartum p ; The specific determination rule is:

[0110]

[0111] In the formula, L p is the lactation stage; D p is the number of days postpartum; where L p = 1 is the early lactation period, L p = 2 is the mid-lactation period, L p = 3 is the late lactation period;

[0112] S53: According to the lactation stage parameter L p call the preset calcium and phosphorus ion channel opening time window database to determine the calcium and phosphorus ion channel opening time window T w ; The time window database is mapped and represented as:

[0113]

[0114] In the formula, T w is the calcium and phosphorus ion channel opening time window parameter, representing the specific period with high absorption and utilization efficiency of calcium and phosphorus ions in the body cells of dairy cows in the current lactation stage; L p is the lactation stage, determined by step S52;

[0115] S54: Based on the tantalum and phosphorus ion channel opening time window parameter T determined in S53 w , match the matrix elements corresponding to the time window in the spatio-temporal matrix of nutrition to obtain the daily allocation ratio R of energy substances e and the daily allocation ratio R of proteins p , and the matching expression is as follows: In the formula, R e is the daily allocation ratio of energy substances, representing the ratio of energy substance supply between day and night of dairy cows in the current lactation stage; R p is the daily allocation ratio of proteins, representing the ratio of protein supply between day and night of dairy cows in the current lactation stage; M t (N s , E b) is the supply demand of energy substances and proteins corresponding to the effective NDF supply in the t-th hour of the nutritional spatio-temporal matrix and the dynamic basal metabolic energy consumption; through the above steps, the precise matching method of the lactation stage division of dairy cows, the opening time window of calcium and phosphorus ion channels and the day-night distribution ratio is clarified, providing reliable data support for accurately outputting the day-night distribution ratio of proteins and energy substances of dairy cows.

[0116] S6 specifically includes:

[0117] S61: According to the day-night distribution ratio of proteins and energy substances obtained in S5, determine the total amount of nutrients required by dairy cows during the light period and the dark period, and divide it into the total feeding amount of high metabolic energy feed during the light period and high fiber slow-release feed during the dark period; at the same time, select high-starch and high-sugar feeds as high metabolic energy feeds during the light period, and select high-fiber roughage as high fiber slow-release feeds during the dark period;

[0118] S62: According to the day-night rhythm phase of the dairy cows currently in, preset the high metabolic energy feed during the light period and the high fiber slow-release feed during the dark period in the automatic feeding device corresponding to the corresponding time period;

[0119] S63: Real-time monitor the pH value of the rumen environment of dairy cows through a rumen capsule sensor, and transmit it to the data receiving terminal by wireless communication to obtain the real-time fluctuation of the rumen pH value;

[0120] S64: According to the real-time fluctuation of the rumen pH value, set the rumen pH fluctuation threshold, and compare the real-time monitored rumen pH value with this threshold; and dynamically control the feed feeding timing according to the comparison result of the rumen pH value and the rumen pH fluctuation threshold; through the above steps, the day-night precise division of the dairy cow diet and the real-time monitoring of the rumen environment state can be realized, so as to effectively control the feeding timing of concentrate and roughage, and achieve the precise matching of feed feeding and the digestive physiological rhythm of dairy cows.

[0121] S64 specifically includes:

[0122] S641: Real-time monitor the rumen pH value through a rumen capsule sensor, denoted as pH r , and record the pH change curve continuously for 24 hours at a frequency of once per minute;

[0123] S642: Calculate the daily average value pH m of the rumen pH value and the standard deviation σ pH , and set the rumen pH fluctuation threshold pH t according to the rumen health status. The calculation formula is as follows: pH t = pH m - k×σ pH , where pH tis the rumen pH fluctuation threshold, representing the pH control boundary value for feed feeding; pH m is the daily average value of the rumen pH; σ pH is the standard deviation of the rumen pH; k is the adjustment coefficient, representing the control weight of the rumen pH fluctuation range;

[0124] S643: Compare the real-time monitored rumen pH value pH r with the rumen pH fluctuation threshold pH t and execute different feed feeding control strategies according to the comparison results. The specific control rules are as follows:

[0125] Control rule 1: If pH r ≥pH t , it is determined that the rumen pH is in a relatively stable state, and it is allowed to feed high metabolic energy feed during the light period, and calculate the feeding rate: In the formula, R f is the current feed feeding rate, in grams per minute; R max is the maximum feeding rate, in grams per minute; pH r is the current rumen pH value, dimensionless; pH t is the rumen pH fluctuation threshold, obtained by S642 calculation; pH m is the daily average value of the rumen pH, obtained by S642 calculation;

[0126] Control rule 2: If pH r <pH t , it is determined that the rumen pH enters the low pH risk area, immediately stop feeding high metabolic energy feed during the light period, and delay the start of feeding high fiber slow release feed during the dark period. The specific formula for calculating the delay time is: T d =T base +α×(pH t -pH r ), in the formula, T d is the feed feeding switching delay time, in minutes; T base is the basic delay time, in minutes; α is the pH drop correction coefficient; Through the above steps, the dynamic monitoring of the rumen pH and the adjustment of the intelligent feeding strategy are realized, ensuring the stability of the rumen environment, optimizing the nutrient absorption efficiency of dairy cows, and improving the feed utilization rate.

[0127] As Figure 2 shown, a dynamic evaluation system for the nutritional requirements of dairy cows is used to implement the above-mentioned dynamic evaluation method for the nutritional requirements of dairy cows, including the following modules:

[0128] Data acquisition module: It is used to continuously collect the core body temperature fluctuation curve, rumination interval cycle data, and the change data of volatile fatty acid concentration in rumen fluid of dairy cows within 48 hours through a rumen capsule sensor, and to obtain the behavioral posture data of dairy cows in real time through a three-dimensional accelerometer. Meanwhile, environmental parameters are collected in real time by using a light intensity sensor and an environmental temperature and humidity sensor in synchronization;

[0129] Rhythm analysis module: Connected to the data acquisition module, it is used to calculate the circadian rhythm phase parameters of dairy cows according to the core body temperature fluctuation curve, rumination interval cycle data, and light intensity data, and to determine the peak period of volatile fatty acid concentration in combination with the change data of volatile fatty acid concentration, and establish the activity coefficient of fiber-decomposing bacteria under different rhythm phases;

[0130] Digestibility correction module: Connected to the rhythm analysis module, it is used to correct the theoretical digestibility of NDF in roughage in real time according to the activity coefficient of fiber-decomposing bacteria, and generate the real-time effective NDF supply;

[0131] Energy consumption calculation module: Connected to the data acquisition module, it is used to calculate the ratio of standing time to lying time of dairy cows according to the behavioral posture data of dairy cows, and to calculate the dynamic basal metabolic energy consumption for dairy cows to maintain body temperature and behavioral activities in combination with environmental parameters;

[0132] Nutrition distribution module: Connected to the digestibility correction module and the energy consumption calculation module, it is used to input the effective NDF supply and dynamic basal metabolic energy consumption data into the nutrition spatio-temporal matrix after receiving them, and to match the opening time window of calcium and phosphorus ion channels according to the current lactation stage, and output the diurnal distribution ratio of protein and energy substances;

[0133] Feeding control module: Connected to the nutrition distribution module and the data acquisition module, it is used to divide the diet into high metabolic energy feed during the light period and high fiber slow-release feed during the dark period according to the diurnal distribution ratio of protein and energy substances, and to dynamically control the specific feeding timing of concentrate and roughage according to the rumen pH fluctuation threshold.

[0134] The present invention covers any substitutions, modifications, equivalent methods, and solutions made within the essence and scope of the present invention. For the public to have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention. However, those skilled in the art can fully understand the present invention without these detailed descriptions. Additionally, well-known methods, processes, procedures, components, and circuits are not described in detail to avoid unnecessary confusion to the essence of the present invention.

[0135] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A dynamic assessment method for the nutritional requirements of dairy cows, characterized in that, It includes the following steps: S1: Continuously collect the core body temperature fluctuation curve and rumination interval cycle data of dairy cows within 48 hours through a rumen capsule sensor, and combine the data of the light intensity sensor to calculate the circadian rhythm phase parameter; S2: Based on the circadian rhythm phase parameter obtained in S1, synchronously detect the peak period of the volatile fatty acid concentration in the rumen fluid, and establish the activity coefficient of fibrolytic bacteria under different rhythm phases; S3: According to the activity coefficient of fibrolytic bacteria obtained in S2, correct the theoretical digestibility of NDF in roughage to generate the real-time effective NDF supply; S4: Obtain the ratio of standing time to lying time through a three-dimensional accelerometer worn by dairy cows, and combine the data of the environmental temperature and humidity sensor to calculate the dynamic basal metabolic energy consumption for maintaining body temperature and behavioral activities; S5: Input the effective NDF supply in S3 and the dynamic basal metabolic energy consumption in S4 into the nutritional spatio-temporal matrix, match the calcium and phosphorus ion channel opening time window according to the current lactation stage, and output the daily and nightly distribution ratio of protein and energy substances; S6: According to the daily and nightly distribution ratio in S5, divide the diet into high metabolic energy feed during the light period and high fiber slow-release feed during the dark period, and control the feed feeding sequence according to the rumen pH fluctuation threshold.

2. The dynamic assessment method for dairy cow nutritional requirements according to claim 1, wherein The specific content of S1 includes: S11: Implant the rumen capsule sensor into the rumen of dairy cows. The rumen capsule sensor is internally equipped with a temperature sensing module and a pressure sensing module, continuously monitor the rumen internal environment temperature value and rumen pressure value at a frequency of once per minute, and transmit them to the data receiving terminal in real time through wireless communication. The continuous monitoring duration is 48 hours; S12: After the continuously collected rumen internal environment temperature values are processed by data smoothing filtering, form the core body temperature fluctuation curve of dairy cows within 48 hours; S13: Input the rumen pressure value into the pressure change rate calculation formula, record the time point when the pressure value reaches the pressure change threshold, and define the time difference between two adjacent pressure threshold time points as a rumination interval cycle, and sequentially obtain the rumination interval cycle data of dairy cows within 48 hours; S14: Install a light intensity sensor in the environment where dairy cows are located, and measure the environmental light intensity value in real time at a frequency of once per minute to obtain 48 hours of continuous light intensity data; S15: Perform Fourier transform processing on the core body temperature fluctuation curve and rumination interval cycle data to obtain the circadian rhythm characteristic frequencies and phases of the body temperature and rumination behavior of dairy cows; S16: Perform Fourier transform processing on the light intensity data to obtain the circadian rhythm characteristic frequencies and phases of the environmental light, and perform time domain matching with the circadian rhythm characteristic phases of the body temperature and rumination behavior of dairy cows obtained in S15, and calculate and obtain the circadian rhythm phase parameter.

3. The dynamic evaluation method for the nutritional requirements of dairy cows according to claim 2, characterized in that, The specific content of S16 includes: S161: Process the ambient light intensity data, cow body temperature fluctuation curve data, and rumination interval cycle data through Fourier transform to obtain the characteristic frequency f of the ambient light circadian rhythm L and the characteristic phase φ L , the characteristic frequency f of the cow core body temperature circadian rhythm T and the characteristic phase φ T as well as the characteristic frequency f of the cow rumination behavior circadian rhythm R and the characteristic phase φ R ; S162: Based on the circadian rhythm characteristic frequency f of the ambient light L respectively perform frequency consistency matching with the circadian rhythm characteristic frequencies f T , f R of the core body temperature and rumination behavior of dairy cows to obtain the frequency matching degree parameter C f ; S163: Based on the phase φ of the circadian rhythm characteristics of environmental light L respectively calculate the phase differences with the phase φ of the circadian rhythm characteristics of the core body temperature and rumination behavior of dairy cows T and φ R to obtain the circadian rhythm phase difference parameter P φ ; S164: Substitute the frequency matching degree parameter C f and the circadian rhythm phase difference parameter P φ into the circadian rhythm phase parameter calculation formula to obtain the circadian rhythm phase parameter D p , and its calculation formula is: In the formula; C f is the frequency matching degree parameter; P φ is the circadian rhythm phase difference parameter; π is the pi, and its value is 3.1416.

4. The dynamic evaluation method for dairy cow nutritional requirements according to claim 1, characterized in that The specific content of S2 includes: S21: Through the volatile fatty acid concentration detection probe built in the rumen capsule sensor, sample the concentrations of acetic acid, propionic acid and butyric acid in the rumen fluid at a sampling frequency of once every 15 minutes, and transmit the concentration data to the data receiving terminal to obtain a 48-hour continuous volatile fatty acid concentration change curve; S22: Calculate the first derivative of the volatile fatty acid concentration change curve, extract the time period when the derivative is zero and the second derivative is less than zero as the peak period of the volatile fatty acid concentration, and record the time point corresponding to each peak; S23: According to the circadian rhythm phase parameters calculated in claim S1, divide the peak period of the volatile fatty acid concentration into the peak period in the light period and the peak period in the dark period according to the circadian rhythm phase parameters; S24: During the peak periods of the light period and the dark period respectively, input the peak concentrations of volatile fatty acids detected in the corresponding periods into the calculation formula of the cellulolytic bacteria activity to obtain the cellulolytic bacteria activity coefficient F c ; S25: According to the cellulolytic bacteria activity coefficients obtained in S24, establish the cellulolytic bacteria activity coefficient databases corresponding to the light period and the dark period respectively, and form the cellulolytic bacteria activity coefficients under different rhythm phases.

5. The dynamic evaluation method for dairy cow nutritional requirements according to claim 4, characterized in that The specific content of S3 includes: S31: Collect the sample of the roughage currently consumed by the dairy cow, and use a near-infrared spectroscopy analyzer to detect and obtain the theoretical digestibility of NDF in the roughage, denoted as parameter N d ; S32: Substitute the theoretical digestibility parameter N d and the cellulolytic bacteria activity coefficient F c into the NDF theoretical digestibility correction formula to obtain the corrected effective NDF digestibility N r ; S33: Substitute the corrected effective NDF digestibility parameter N r into the formula for calculating the supply amount of effective NDF to generate the real-time supply amount of effective NDF. The specific calculation formula is: N s = Q × C N × N r , where N s is the real-time supply amount of effective NDF; Q is the current actual intake of roughage; C N is the NDF content in the roughage.

6. The dynamic assessment method for the nutritional requirements of dairy cows according to claim 1, wherein The specific content of S4 includes: S41: Fix the wearable three-axis accelerometer with a built-in three-axis acceleration sensor on the neck of the cow, continuously collect the acceleration data of the cow in the X-axis, Y-axis, and Z-axis directions at a frequency of once per second, and calculate the acceleration composite vector parameter A in real time v ; S42: Set the threshold A for judging the behavioral posture of cows th , when A v ≥A th , it is judged as the standing posture. When A v <A th , it is judged as the lying posture, so as to obtain the continuous standing and lying time data of cows within 48 hours; S43: Calculate the standing and lying time ratio parameter R of the cow based on the standing and lying time data obtained in S42 sl ; S44: Install temperature and humidity sensors in the living environment of the dairy cows, collect the environmental temperature parameters and environmental humidity parameters in real time at a frequency of once per minute, and calculate the environmental temperature-humidity index parameter THI; S45: Input the ratio parameter R of standing time to lying time sl and the ambient temperature-humidity index parameter THI into the dynamic basal metabolic energy consumption calculation formula for dairy cows, and calculate the dynamic basal metabolic energy consumption parameter for maintaining body temperature and behavioral activities. The formula is: E b = E m ×(1 + k1×R sl + k2×THI), where E b is the dynamic basal metabolic energy consumption parameter; E m is the basal metabolic energy consumption reference value for dairy cows; k1 is the behavioral activity coefficient; k2 is the heat stress coefficient.

7. The dynamic assessment method for dairy cow nutritional requirements according to claim 1, characterized in that The specific content of S5 includes: S51: Construct a spatio-temporal matrix of dairy cow nutrition, specifically with the parameter N of the effective NDF supply s as the row and the parameter E of the dynamic basal metabolic energy consumption b as the column; S52: Determine the current lactation stage L of the dairy cow according to the number of days postpartum of the dairy cow p ; S53: According to the lactation stage parameter L p Call the preset calcium and phosphorus ion channel opening time window database to determine the time window T for the opening of the calcium and phosphorus ion channels w ; S54: Tantalum-phosphorus ion channel opening time window parameter T determined according to S53 w , match the matrix elements of the corresponding time window in the nutrient spatio-temporal matrix, and obtain the energy substance diurnal distribution ratio R corresponding to the current time window e and the protein diurnal distribution ratio R p .

8. The dynamic evaluation method for the nutritional requirements of dairy cows according to claim 1, wherein The specific content of S6 includes: S61: According to the daily and nightly distribution ratios of proteins and energy substances obtained in S5, determine the total amount of nutrients required by the dairy cows in the light period and the dark period; at the same time, select high-starch and high-sugar feeds as the high-metabolic-energy feeds in the light period, and select high-fiber roughage as the high-fiber slow-release feeds in the dark period; S62: According to the circadian rhythm phase in which the dairy cows are currently located, preset the high-metabolic-energy feeds in the light period and the high-fiber slow-release feeds in the dark period into the automatic feeding devices corresponding to the corresponding time periods; S63: Real-time monitor the pH value of the rumen environment in the dairy cows through a rumen capsule sensor, and transmit it to the data receiving terminal by wireless communication to obtain the real-time fluctuation of the rumen pH value; S64: Set a rumen pH fluctuation threshold according to the real-time fluctuation of the rumen pH value, and compare the real-time monitored rumen pH value with this threshold; and dynamically control the feed feeding timing according to the comparison result between the rumen pH value and the rumen pH fluctuation threshold.

9. A method for dynamically evaluating the nutritional requirements of dairy cows according to claim 8, characterized in that, The specific content of S64 includes: S641: Real-time monitoring of the rumen pH value through a rumen capsule sensor, denoted as pH r ; S642: Set the rumen pH fluctuation threshold pH according to the rumen health status t ; S643: Compare the real-time monitored rumen pH value pH r with the rumen pH fluctuation threshold pH t and execute different feed feeding control strategies according to the comparison results. The specific control rules are as follows: Control rule 1, if the pH r ≥ pH t , it is determined that the rumen pH is in a relatively stable state, and it is allowed to feed high metabolic energy feed during the light period; Control rule 2, if the pH r <pH t , it is determined that the rumen pH has entered the low pH risk zone, and the feeding of high metabolic energy feed during the light period is immediately stopped, and the feeding of high fiber slow-release feed during the dark period is delayed from starting.

10. A dynamic evaluation system for dairy cow nutritional requirements, which is used to implement a dynamic evaluation method for dairy cow nutritional requirements as described in any one of claims 1-9, characterized in that, It includes the following modules: Data acquisition module: Used to continuously collect the core body temperature fluctuation curve, rumination interval cycle data, and volatile fatty acid concentration change data in the rumen fluid of the dairy cows within 48 hours through a rumen capsule sensor, and obtain the behavioral posture data of the dairy cows in real time through a three-dimensional accelerometer, and simultaneously collect environmental parameters in real time using a light intensity sensor and an environmental temperature and humidity sensor; Rhythm analysis module: Connected to the data acquisition module, used to calculate the circadian rhythm phase parameters of the dairy cows according to the core body temperature fluctuation curve, rumination interval cycle data, and light intensity data, and determine the peak period of the volatile fatty acid concentration in combination with the volatile fatty acid concentration change data, and establish the cellulolytic bacteria activity coefficients under different rhythm phases; Digestibility correction module: Connected to the rhythm analysis module, used to real-time correct the theoretical digestibility of NDF in the roughage according to the cellulolytic bacteria activity coefficient, and generate the real-time effective NDF supply; Energy consumption calculation module: Connected to the data acquisition module, used to calculate the ratio of the standing and lying time of the dairy cows according to the behavioral posture data of the dairy cows, and calculate the dynamic basal metabolic energy consumption for the dairy cows to maintain body temperature and behavioral activities in combination with environmental parameters. Nutrient distribution module: Connected to the digestibility correction module and the energy consumption calculation module, it is used to receive the effective NDF supply amount and dynamic basal metabolic energy consumption data, input them into the nutrient spatio-temporal matrix, match the calcium and phosphorus ion channel opening time window according to the current lactation stage, and output the day-night distribution ratio of protein and energy substances; Feeding control module: Connected to the nutrient distribution module and the data acquisition module, it is used to divide the daily ration into high metabolic energy feed during the light period and high fiber slow-release feed during the dark period according to the day-night distribution ratio of protein and energy substances, and dynamically control the specific feeding time sequence of concentrate and roughage according to the rumen pH fluctuation threshold.

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