Method for predicting cryptocaryoniosis in Larimichthys crocea

A technology that stimulates cryptonium disease and prediction methods, which is applied in fish farming, application, climate change adaptation and other directions, and can solve the problem that there is no research report on the prediction technology of water environment factors, and there is no large yellow croaker to stimulate the mature method of predicting cryptonium disease, etc. problems, to achieve the effect of facilitating disease prevention and control, prevention and mitigation of disasters, and convenient use

Inactive Publication Date: 2012-07-11
XIAMEN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is no research report on the prediction technology of water environment factors related to cryptocytoniasis in my country, and there is no mature method for predicting cryptocytoniasis in large yellow croaker

Method used

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  • Method for predicting cryptocaryoniosis in Larimichthys crocea
  • Method for predicting cryptocaryoniosis in Larimichthys crocea
  • Method for predicting cryptocaryoniosis in Larimichthys crocea

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] Example 1: Establishment of water environment factor prediction technology.

[0033] The present invention first collects the monthly monitoring data of water temperature, dissolved oxygen and ammonia nitrogen value of 5 different stations in the large yellow croaker breeding sea area of ​​Sandu Bay, Ningde, Fujian (the water quality data comes from the East China Sea Sub-bureau Fujian Ocean Environment Monitoring Center Station of the State Oceanic Administration, and the disease data From the Department of Disease Prevention and Control of Fujian Marine Aquaculture Technology Extension General Station, data collection and analysis are in accordance with national standards), and a regression equation reflecting its changing trend and historical law was established. Among them, the months are recorded as 1-65 according to January 2005 to May 2010; the water temperature, dissolved oxygen, and ammonia nitrogen values ​​​​at different stations are respectively averaged, and...

Embodiment 2

[0050] Example 2 Accuracy Analysis of Water Environment Factor Prediction Technology

[0051] According to the fitting equation established in Example 1, the water temperature, dissolved oxygen and ammonia nitrogen values ​​in July of a certain year were predicted. Table 1 compares the predicted value with the actual value. It can be seen from Table 1 that the average relative error between the predicted value and the actual value of each factor is within 10%, indicating that the water quality prediction effect is good.

[0052] Table 1 Comparison of predicted and actual values ​​of water quality factors in July of a certain year

[0053] factor

[0054] Note: relative error = (predicted value - actual value) / actual value * 100%

Embodiment 3

[0055] Example 3 stimulates the advance prediction of Cryptocaryon morbidity

[0056] Collect the historical month, water temperature, dissolved oxygen and ammonia nitrogen 4 factors and the corresponding severity level data of cryptocystosis, use the random forest program package loaded in the R software environment to analyze the above data, and establish the month, water temperature, dissolved oxygen and A mathematical model for distinguishing disease grades with 4 factors of ammonia nitrogen.

[0057] The predicted value of water temperature in July of a certain year is 28.6°C, the predicted value of dissolved oxygen is 6.04 mg / l, and the predicted value of ammonia nitrogen is 0.034 mg / l. Substituting it into the established disease discrimination model can predict the stimulus in July of a certain year. The incidence of cryptocystosis.

[0058] After calculation, the degree of stimulating cryptocystosis in July of a certain year is level 2, that is to say, it is in a sta...

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Abstract

A method for predicting cryptocaryoniosis in Larimichthys crocea relates to Larimichthys crocea, and belongs to a method of accurately predicting a water environmental factor at a certain future point-in-time to achieve advanced prediction on cryptocaryoniosis in Larimichthys crocea. The method includes: plugging a predicted value of the obtained water environmental factor in a mathematical discriminatory model for cryptocaryoniosis based on the water environmental factor; calculating a predicted value of the cryptocaryoniosis to generate the advanced prediction on the cryptocaryoniosis in Larimichthys crocea; and obtaining advanced prediction on the cryptocaryoniosis in Larimichthys crocea. The method is simple and convenient and capable of reflecting anural variation, parameters of the water environmental factor can be obtained according to a series of fitting equations only by providing month, the parameters can be calculated with a disease discriminatory model to finally obtain the predicted value of the cryptocaryoniosis, and accordingly, the method is quite convenient in use. For the specific cryptocaryoniosis, the method is convenient for farmers to timely take measures to control the disease and prevent and alleviate disasters.

Description

technical field [0001] The invention relates to a large yellow croaker, in particular to a method for predicting cryptocytoniasis stimulated by large yellow croakers. Background technique [0002] Large yellow croaker (Pseudosciaena crocea) is the fish with the largest output of a single species in marine cage culture in my country, with an annual output of about 70,000 tons. However, in recent years, it has stimulated the outbreak and spread of Cryptocaryon irritans disease, which seriously threatens the sustainable development of large yellow croaker farming industry. According to statistics, since 2005, large yellow croakers in the Sanduao breeding area of ​​Ningde City, Fujian Province have caused direct economic losses of more than 300 million yuan each year due to secondary infections caused by parasites and bacteria. In 2008, the Ministry of Agriculture has listed Cryptocaryoniasis as a second-class animal disease in the new version of "List of Types I, II, and III A...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A01K61/00
CPCY02A40/81
Inventor 毛勇蔡晓鹏吕伟航王洪杰苏永全王军丁少雄
Owner XIAMEN UNIV
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