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System for early prediction of postpartum subclinical ketosis of dairy cow based on intestinal microorganisms

A technology of intestinal microbes and microbes, applied in prediction, bioinformatics, genomics, etc., to improve health and production levels, relieve metabolic burden, and improve stress status

Active Publication Date: 2022-04-19
ZHEJIANG UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The potential value of gut microbes in regulation and prediction of dairy cow health remains to be discovered

Method used

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  • System for early prediction of postpartum subclinical ketosis of dairy cow based on intestinal microorganisms
  • System for early prediction of postpartum subclinical ketosis of dairy cow based on intestinal microorganisms
  • System for early prediction of postpartum subclinical ketosis of dairy cow based on intestinal microorganisms

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Embodiment example

[0047] In an intensive pasture in Hangzhou, the intestinal contents of dairy cows within three weeks before delivery were randomly collected through the microbial collection module, and 16S rRNA sequencing was performed to obtain the abundance of six microorganisms. The discriminant model was used to evaluate the prediction accuracy of 0.818, such as As shown in Table 2, Table 2 is based on the implementation effect of 6 marker microorganisms

[0048] cow number 1 2 3 4 5 6 7 8 9 10 11 g__Cellulosilyticum 0.67 0.21 0.19 0.07 0.64 0.17 0.16 0.21 0.1 0.16 0.25 g__Parabacteroides 0.18 0.44 0.28 0.64 0.45 0.6 0.64 0.43 0.58 0.51 0.44 g__Roseburia 0.09 0.26 0.27 0.11 0.24 0.23 0.24 0.16 0.31 0.3 0.2 g__Shigella 0.01 0.07 0.15 0.02 0.01 0.02 0.02 0 0.04 0.03 0.01 g__Acetanaerobacterium 0.01 0.07 0.04 0.05 0.04 0.08 0.09 0.02 0.01 0.01 0.04 g__Sporobacter 0.06 0.07 0.04 0.06 0...

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Abstract

The invention discloses a system for early prediction of postpartum subclinical ketosis of dairy cows based on intestinal microorganisms, the postpartum subclinical ketosis of dairy cows is predicted by using the abundance of intestinal prognostic marker microorganisms of dairy cows at the early perinatal stage, and the prognostic marker microorganisms comprise the genus level Parabacterides, Shigiella, Cellulosilylium, Roseburia, Sporobacter and Actinaerobacterium. Prognostic marker microorganisms of the six subclinical ketodiseases are screened, and a prognostic discrimination model is established based on discriminant analysis. The method has accurate and stable prediction capability on the postpartum subclinical ketosis of the dairy cows, can perform early warning screening on the perinatal dairy cows through a non-invasive rectum sampling method, and provides an effective means for preventing and treating the postpartum ketosis and the subclinical ketosis of the dairy cows as soon as possible in a dairy farm.

Description

technical field [0001] The invention relates to the field of dairy cow health in the peripartum period, in particular to a system for predicting postpartum subclinical ketosis based on prepartum intestinal microorganisms for predicting blood β-hydroxybutyric acid level of dairy cows one week after parturition. Background technique [0002] my country's dairy farming industry has developed rapidly in the 21st century, and the annual yield per unit of dairy cows has risen from less than 4,000 kg to more than 8,000 kg. However, with the continuous increase in dairy cow production, health problems have become increasingly prominent. Postpartum, because the energy supplied by consuming feed cannot meet the needs of milk production, dairy cows usually have varying degrees of negative energy balance, so they need to mobilize their own body tissues for energy supply. During this process, a large amount of long-chain fatty acids in body fat are decomposed into non-esterified fatty ac...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B20/00G16H50/30G06Q10/04G06K9/62
CPCG16B20/00G06Q10/04G16H50/30G06F18/24323
Inventor 孙会增朱森林顾凤飞刘建新
Owner ZHEJIANG UNIV
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