Genetic Variants and Allele Frequencies of Kappa Casein in Egyptian Cattle and Buffalo Using PCR-RFLP


  •  Eman M. Gouda    
  •  Mona Kh. Galal    
  •  Samy A. Abdelaziz    

Abstract

Kappa casein (K-Ca) genetic variations affected quality and composition of the milk. Several variants of Kappa casein (K-Ca) gene locus IV have been reported with special interest for the ‘B’ allele for its relation to the milk protein and fat yields. Genotyping and allelic frequencies of K-Ca among Native Egyptian breeds of cattle and buffalo were the aim of the present study. PCR amplification of DNA isolated from 300 blood samples collected from Holstein and Baladi cattle and buffalo were performed followed by restriction fragment length polymorphism using Hind-III restriction endonuclease (PCR-RFLP). Detection of ‘AA’ and ‘AB’ genotypes in cattle breeds, ‘BB’ and ‘AB’ in buffalo and two alleles ‘A’ and ‘B’ in the studied breeds. Molecular selection for animals carrying the ‘B’ allele could impact breeding programs for dairy production in native cattle and buffalo breeds in Egypt. ast-language:AR-SA'>Simulated daily cycle of temperature was compared with data registered at six meteorological stations located in the cultivated floor of the semiarid Limari Valley (Chile, 31°S). Although in some cases the simulated temperature differs in about 2°C with the observed one, a good fit between model results and experimental data was observed. Using the simulated seasonal minimum and maximum mean temperature fields, maps of temperature differences with respect to a reference station were drawn. In order to observe the influence of the orography on the lapse rate around a station, the methodology was applied for two reference stations located in places with different orographic characteristics. Results for winter and summer seasons are shown.

 

These generated maps can be used by farmers and agricultural planners to obtain information of seasonal minimum and maximum mean temperature from a station in any site of the cultivated area. This technique is a good alternative to obtain meteorological information at low costs, contributing to territorial planning for climate resilient agriculture sustainability.

 



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