Disease prediction method for aquaculture based on microflora change

A microbial community and aquaculture technology, which is applied in the field of disease prediction and early warning based on changes in microbial communities in aquaculture water, can solve problems such as the lack of public aquaculture disease prediction methods.

Inactive Publication Date: 2015-04-15
NINGBO UNIV
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  • Claims
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Problems solved by technology

However, at present, there are no relevant research reports on the prediction method of aquaculture disease based on the change of microbial community at home and abroad.

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  • Disease prediction method for aquaculture based on microflora change
  • Disease prediction method for aquaculture based on microflora change
  • Disease prediction method for aquaculture based on microflora change

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specific Embodiment

[0031] In the first half of 2012, at 35d, 45d, 55d, 63d, 69d, and 77d after seedling release, water samples from 34 culture ponds of Penaeus vannamei mariculture farms were collected, one sample from each pond; after filtration and DNA extraction High-throughput sequencing (or other methods such as gene chip, PCR-DGGE, etc.) after pretreatment such as PCR amplification, etc., to obtain the number of reads of each microbial OTU in each sample, and convert it into relative abundance. We used 18 samples of 63d and 69d (including 6 diseased samples and 12 healthy samples) as samples for screening characteristic microorganisms and building prediction models, and other samples as prediction samples. When modeling and predicting data at different classification levels (phylum, class, order, family, genus, species), the process and method are completely consistent except for the data. Implementation process reference figure 1 .

[0032] The following uses the data of the genus as a...

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Abstract

The invention discloses a disease prediction method for aquaculture based on microflora change. The method is characterized in that diseases are predicted and warned according to change of sum of relative abundances of featured microflora in aquatic water. The method specifically comprises the following steps: obtaining microflora information in a healthy water body sample and a diseased water body sample by high-throughput sequencing or other methods; screening healthy featured microflora and disease featured microflora which respectively indicate the healthy and diseased states; and then, respectively establishing a predication model to predict unknown samples by taking the relative abundance of microorganisms in a disease featured microbial combination and that of microorganisms in a healthy featured microbial combination as independent variables as well as taking the healthy states of the samples as dependent variables. The method has the advantages that the probability of diseases of aquaculture organisms can be predicted by fewer indicative microbial types, and the prediction accuracy is high.

Description

technical field [0001] The invention relates to a method for predicting and early warning of aquaculture diseases, in particular to a method for realizing disease prediction and early warning according to changes in microbial communities in aquaculture water. Background technique [0002] The disease problem in aquaculture, especially in factory facility aquaculture production, is one of the major problems faced by the aquaculture industry. All kinds of sudden and explosive diseases often cause huge economic losses to the aquaculture industry. In order to prevent the occurrence of diseases, in addition to taking various corresponding management and technical measures, it is also necessary to carry out effective forecasting or early warning of possible diseases before the occurrence of diseases, and on this basis, take effective measures to carry out artificial Intervene to prevent disease or minimize damage. The causes of diseases in aquaculture systems are complex. The b...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): C12Q1/68C12Q1/04
Inventor 朱建林张德民王一农陈和平赵群芬
Owner NINGBO UNIV
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