Breeding method of tilapia hybrid line based on big data

Abstract

The invention belongs to the technical field of tilapia hybridization breeding, and discloses a method for breeding tilapia hybridization matching lines based on big data. The temperature of the refrigeration device is adjusted through the temperature adjustment knob, and the temperature in the low temperature box is lowered; the electromagnetic valve is closed. Finally, measure the flow of water in the low-temperature box and the normal temperature box through the first flow meter and the second flow meter, indirectly measure the number of internal fry, and calculate the ratio of the first flow meter and the second flow meter through the data processing chip. The ratio is displayed on the display screen, and the measured value is transmitted to the device terminal through the wifi connector to analyze the breed of mating offspring. The invention separates the offspring produced by the crossbreeding of male Nile tilapia and female Olia tilapia, avoiding the phenomenon of tilapia cannibalism; separates different offspring species through normal temperature and low temperature, and is equipped with big data measurement , improve breeding success rate and reduce workload.

Description

technical field [0001] The invention belongs to the technical field of tilapia hybrid breeding, in particular to a method for breeding tilapia hybrid mating lines based on big data. Background technique [0002] At present, Nile tilapia is the offspring produced by the mating of female Nile tilapia and male Olia tilapia. It has the characteristics of high male rate, cold resistance, and disease resistance. The yield is low, so people manually select the male parent and the female parent for hybridization, and the workload is huge; tilapia fry have the habit of cannibalism, which is mainly manifested in the phenomenon that large fry eat small fry during the period of 8-9 dynasties. It was particularly serious. We dissected and found that there were more than 20 young tilapia in the intestines and stomachs of some 5-dynasty tilapia fry, which seriously affected the number of offspring of tilapia oni. [0003] In summary, the problems in the prior art are: [0004] (1) People...

AI Technical Summary

Problems solved by technology

[0004] (1) People use manual selection of male and female parents for hybridization, which is a huge workload; tilapia fry have the habit of cannibalizing each other, and the phenomenon of large seedlings swallowing small seedlings is more serious, which seriously affects the number of offspring of Oni hybrid tilapia

[0005] (2) The existing sound denoising algorithm has certain limitations. It is not ideal for suppressing noise pollution and maintaining signal details. It cannot effectively eliminate background noise, cannot improve the separability of signal features, and does not have high practicality. value

Affects the clarity of images for analyzing mated progeny breeds

[0006] (3) In practical engineering applications, due to the configuration limitations of the hardware platform, the control algorithm requires a large number of iterative operations on the hardware platform, which will increase the calculation time of the algorithm and affect the real-time performance of the control system

[0007] (4) The existing definition algorithm has a large amount of calculation, low execution efficiency, and is not easy to realize by hardware

[0008] In the prior art, the flow control effect of the first flow meter and the second flow meter is poor

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