Selective Breeding under a Hierarchical Mating Using Osborne Index Web App

M. P. Raj *

Department of Agricultural Statistics, BACA, AAU, Anand, India.

F. P. Savaliya

Poultry Research Station, Kamdhenu University, Anand, India.

A. B. Patel

Poultry Research Station, Kamdhenu University, Anand, India.

*Author to whom correspondence should be addressed.


Abstract

The poultry industry has targets to meet consumption trends and thus to produce genetically superior birds with high productivity of egg. Better egg production techniques are recommended, to satisfy in-house and export demand. The correlation of egg production with various parameters is considered by various breeders. With the efforts of breeders to satisfy demand, poultry breeding has introduced individual feed conversion testing, Osborne index, pedigreeing, hybridization, selection index, artificial insemination, and mass selection etc. The most reliable and proven Osborne index states that the maximum efficiency of egg production can be obtained by selection on the basis of a combination of family average and individual record. Technological advances have fostered the poultry sector in the last few decades. ICT led transmutation of processes and practices is apparent in almost all aspects of human activities. Knowledge about a particular breeding technique is required for its prefect implementation. These techniques require a kind of data mining and statistical analysis for matting sires and dams. In the era of 5G, Web Apps can provide better options for providing timely, precise analyzed information to poultry owners or breeders. This paper proposes a device responsive web app for Osborne Index for hierarchical mating using selective breeding.

Keywords: Selective breeding, hierarchical mating, osborne index, web app, poultry


How to Cite

Raj , M. P., F. P. Savaliya, and A. B. Patel. 2023. “Selective Breeding under a Hierarchical Mating Using Osborne Index Web App”. Asian Journal of Research in Computer Science 16 (4):1-7. https://doi.org/10.9734/ajrcos/2023/v16i4365.

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