A system for predicting the time of occurrence of a peak in blood non-esterified fatty acid concentration in a dairy cow postpartum

Abstract

The application discloses a system for predicting the occurrence time of the peak value of the non-esterified fatty acid concentration in the blood of a dairy cow after delivery, and belongs to the technical field of healthy breeding of dairy cows. The system takes the genus level relative abundance of five marker microorganisms in the intestinal contents of a dairy cow one week before delivery as input data, calculates a score through a preset discriminant model, and judges whether the peak value of the blood free fatty acid concentration after delivery occurs on the day of calving according to a set threshold. The overall prediction accuracy of the discriminant model reaches 90%, the prediction accuracy for dairy cows with a peak on the day of calving reaches 75%, the system is simple to operate and stable in performance, can realize pre-delivery early warning of high health risks of peripartum dairy cows, provides technical support for taking preventive measures in advance, improving the postpartum health status and lactation level of dairy cows, and has important practical application value and economic significance.

Description

Technical Field

[0001] This invention relates to the field of dairy cow health technology, and in particular to a system for predicting the peak time of non-esterified fatty acid concentration in the blood of dairy cows after calving. Background Technology

[0002] Perinatal dairy cows refer to dairy cows in the three weeks before and after calving. During this period, cows undergo a series of physiological activities including pregnancy, calving, and lactation, accompanied by changes in hormone levels and energy requirements. This makes them prone to metabolic disorders, high incidence of inflammation, and immunosuppression. Especially in the late perinatal period, cows have lower feed intake and need to utilize their body's energy reserves to meet the energy demands of lactation, leading to a significant mobilization of body fat and a negative energy balance. At this time, glucose and lipid metabolism change, and the concentration of NEFAs in the blood increases sharply.

[0003] Studies have shown that elevated blood non-esterified fatty acid (NEFA) concentrations increase health risks in dairy cows. Furthermore, the timing of NEFA peak concentrations has a significant impact on the health status of dairy cows, specifically, dairy cows whose NEFA peak concentrations occur on the day of calving have a significantly higher health risk than those whose peak concentrations occur one week postpartum.

[0004] Meanwhile, studies on gut microbiota have shown that peripartum gut microbiota in dairy cows has a significant impact on blood NEFA concentrations. While current research exists on the health effects of blood NEFA concentrations and the influence of gut microbiota on blood NEFA concentrations, there is a lack of research on predicting the timing of the postpartum peak in blood NEFA concentrations. This makes it difficult to implement early intervention and special management for dairy cows with high health risks before calving to improve their overall economic value.

[0005] Therefore, developing a simple, efficient, and accurate predictive model is of great significance for alleviating metabolic disorders in periparturient dairy cows, providing early warnings, and improving their health and milk production levels. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a system for predicting the peak time of NEFA concentration in the blood of dairy cows after calving, thereby solving the problem that the prior art cannot predict the peak time of NEFA concentration in the blood of dairy cows after calving and is difficult to achieve precise pre-calving prevention and control.

[0007] To achieve the above objectives, the present invention provides a system for predicting the peak time of non-esterified fatty acid concentration in the blood of dairy cows after calving, including a data input module, a discrimination calculation module and a result output module. The data input module is used to obtain the relative abundance data of five marker microorganisms in the rectal contents of dairy cows one week before calving by 16S rRNA gene sequencing.

[0008] The discrimination calculation module uses a preset discrimination model to calculate the input data. The formula for the discrimination model is:

[0009] ;

[0010] Among them, Abundance i Let g be the genus-level relative abundance of the i-th microorganism. i denoted by the discrimination coefficient corresponding to the i-th microorganism;

[0011] The results output module outputs a prediction of whether the peak concentration of free fatty acids in postpartum blood occurs on the day of calving, based on the comparison between the calculated score value and the preset threshold.

[0012] Preferably, the five marker microorganisms are significantly beneficial microorganisms obtained through logistic regression screening, and the screening conditions are as follows: P The value is less than 0.1 and Beta is less than 0.

[0013] Preferably, the preset threshold is 0.1604; when the score is ≥ 0.1604, the risk of the peak concentration of NEFA in the blood of the exporting dairy cow occurring on the day of calving is relatively high; when the score is < 0.1604, the risk of the peak concentration of NEFA in the blood of the exporting dairy cow occurring on the day of calving is relatively low.

[0014] Preferably, the five marker microorganisms are Clostridia_UCG-014 , GWE2-31-10 , Tuzzerella , Paludicola and [Eubacterium]_oxidoreducens_group .

[0015] Preferably, the steps for obtaining relative abundance data at the genus level of microorganisms include: collecting rectal contents samples from dairy cows one week before calving, obtaining genus-level annotation abundance information of microorganisms through 16S rRNA gene sequencing, removing low-abundance species, and then performing CLR conversion and standardization on the relative abundance of the remaining species.

[0016] Preferably, low abundance species refer to species whose abundance is less than 0.01% in 50% of any group of samples.

[0017] Therefore, the system of the present invention for predicting the peak time of non-esterified fatty acid concentration in the blood of dairy cows after calving has the following beneficial effects:

[0018] (1) High prediction accuracy: The overall prediction accuracy of the system reached 90% in the verification test, and the prediction accuracy was 75% for dairy cows whose postpartum blood NEFA concentration peaked on the day of calving;

[0019] (2) Easy to operate: It uses clear mathematical formulas and thresholds for judgment, without complicated operations, which is convenient for actual application in ranches;

[0020] (3) Highly practical: It can provide accurate early warning of postpartum health risks in dairy cows before calving, providing a basis for taking preventive and control measures in advance, which helps to reduce the incidence of metabolic disorders in dairy cows during the peripartum period, improve their health status and milk production level, and lay the foundation for precise prevention and control of dairy cows during the peripartum period.

[0021] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 Cluster analysis diagram showing the dynamic changes in NEFA concentration in the blood of dairy cows during the peripartum period. Detailed Implementation

[0024] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0025] To make the objectives, technical solutions, and advantages of this application clearer, more thorough, and more complete, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. The following detailed descriptions are all illustrations of embodiments, intended to provide further detailed explanation of the present invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0026] The instruments, equipment, reagents, and materials used in the examples were all obtained commercially.

[0027] Example 1

[0028] Fifty-eight Holstein dairy cows in the peripartum period (three weeks before calving to three weeks after calving) were included in this study. Tail vein samples were collected at five time points: three weeks before calving, one week before calving, on the day of calving, one week after calving, and three weeks after calving. Blood NEFA, protein-like amylase A, and haptoglobin levels were measured. Milk yield and milk composition were recorded weekly after calving, for a total of 1-5 weeks postpartum.

[0029] like Figure 1As shown, cluster analysis of NEFA in 58 dairy cows at 5 time points was performed using the Mfuzz package (V2.62.0) in R (V4.3.3). The elbow method was used to determine the optimal number of clusters as 3. The differences between the two groups of dairy cows, Cluster1 and Cluster2, were as follows: the concentration of free fatty acids in the blood of Cluster1 reached its peak on the day of calving, while the concentration of NEFA in the blood of Cluster2 reached its peak one week after calving.

[0030] There was no difference in production performance between the Cluster 1 and Cluster 2 groups of dairy cows, but there were differences in inflammatory markers, indicating that NEFA peaking on the day of calving increases the health risk of dairy cows. The results of postpartum protein-like amylase A, haptoglobin, and production markers in the Cluster 1 and Cluster 2 groups are shown in Tables 1 and 2 below:

[0031] Table 1. Statistical comparison of the concentrations of peripartum inflammatory biomarkers in dairy cows of different clusters.

[0032]

[0033] 1 C = Cluster

[0034] 2 W = Week

[0035] Table 2. Statistical comparison of peripartum dairy cow production performance indicators of different clusters

[0036]

[0037] Intestinal contents were collected one week before farrowing, and microbial genus-level annotation abundance information obtained after 16S rRNA gene sequencing was used for subsequent analysis. Low-abundance species with an abundance below 0.01% in 50% of samples within any given group were removed, leaving 123 genera. The relative abundance data were CLR-transformed and standardized, and logistic regression was performed with clusters, with Cluster 1 defined as "1" and Cluster 2 as "0". Body weight, milk yield, and parity were included as covariates for further screening. P Five significantly beneficial microorganisms were identified, with a value less than 0.1 and a Beta value less than 0.

[0038] Canonical discriminant analysis was performed using the abundance matrices of five microorganisms to obtain a formula for predicting the peak time of non-esterified fatty acid concentration in postpartum blood of dairy cows, which can be calculated based on the abundance of marker microorganisms. The formula is as follows:

[0039] ;

[0040] Among them, Abundance i The input data for the discrimination model is the genus-level abundance of the i-th microorganism obtained from 16S rRNA gene sequencing of the rectal contents of dairy cows one week before calving, g. i The discriminant coefficients are shown in Table 3 below:

[0041] Table 3. Marker microorganisms and their discrimination coefficients

[0042]

[0043] The threshold is calculated in increments of 0.01 for the Youden's Index. The threshold value corresponding to the maximum Youden's Index is taken as the threshold for the discrimination model, which is 0.1604. The judgment rule is then established based on this threshold: when... At that time, it was considered that dairy cows had a higher risk of experiencing a peak postpartum blood NEFA concentration on the day of calving. A prediction system was used to predict the NEFA concentration in 31 dairy cows from Cluster 1 and Cluster 2, with an accuracy of 80.65%. The confusion matrix is ​​shown in Table 4 below.

[0044] Table 4 Confusion Matrix

[0045]

[0046] Example 2

[0047] System validation was conducted at an intensive dairy farm in Hangzhou. Rectal contents of dairy cows were randomly collected one week before calving and 16S rRNA sequencing was performed to obtain abundance data of five microorganisms. The discriminant model in Example 1 was used for evaluation. The overall prediction accuracy was 90%, and the prediction accuracy for cows whose postpartum blood non-esterified fatty acid concentration reached its peak on the day of calving was 75%. The results are shown in Table 5 below, where "1" indicates that the postpartum blood NEFA concentration reached its peak on the day of calving, and "0" indicates otherwise.

[0048] Table 5 Prediction Results

[0049]

[0050] The confusion matrix is ​​shown in Table 6 below:

[0051] Table 6 Confusion Matrix

[0052]

[0053] In summary, this model can effectively predict the peak time of postpartum NEFA concentration in dairy cows before calving, thus helping to ensure the postpartum health of dairy cows through early warning and prevention.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A system for predicting the peak time of non-esterified fatty acid concentration in the blood of dairy cows after calving, characterized in that, It includes a data input module, a discrimination calculation module, and a result output module. The data input module is used to obtain the genus-level relative abundance data of five marker microorganisms in the rectal contents of dairy cows one week before calving, obtained by 16S rRNA gene sequencing. The discrimination calculation module uses a preset discrimination model to calculate the input data. The formula for the discrimination model is: ； Among them, Abundance i Let g be the genus-level relative abundance of the i-th microorganism. i denoted by the discrimination coefficient corresponding to the i-th microorganism; The results output module outputs a prediction of whether the peak concentration of non-esterified fatty acids in postpartum blood occurs on the day of calving, based on the comparison between the calculated score value and the preset threshold. Five marker microorganisms Clostridia_UCG-014 , GWE2-31-10 , Tuzzerella , Paludicola and [Eubacterium]_oxidoreducens_group; The preset threshold is 0.1604. When the score is ≥ 0.1604, the risk of the peak concentration of non-esterified fatty acids in the postpartum blood of dairy cows occurring on the day of calving is relatively high. When the score is < 0.1604, the risk of the peak concentration of non-esterified fatty acids in the postpartum blood of dairy cows occurring on the day of calving is relatively low.

2. The system for predicting the peak time of non-esterified fatty acid concentration in the blood of dairy cows after calving, as described in claim 1, is characterized in that: The five marker microorganisms were significant beneficial microorganisms identified through logistic regression screening. The screening criteria were as follows: P The value is less than 0.1 and Beta is less than 0.

3. The system for predicting the peak time of non-esterified fatty acid concentration in the blood of dairy cows after calving, as described in claim 1, is characterized in that... The steps for obtaining relative abundance data at the genus level of microorganisms include: collecting rectal contents samples from dairy cows one week before calving, obtaining genus-level annotation abundance information of microorganisms through 16S rRNA gene sequencing, removing low-abundance species, and then performing CLR conversion and standardization on the relative abundance of the remaining species.

4. The system for predicting the peak time of non-esterified fatty acid concentration in the blood of dairy cows after calving, as described in claim 3, is characterized in that: Low abundance species refer to species whose abundance is less than 0.01% in 50% of any group of samples.

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