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Record W2123672755 · doi:10.5539/jas.v5n2p197

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

2013· article· en· W2123672755 on OpenAlexvenueno aff
Eman M. Gouda, Mona K. Galal, Samy A. Abdelaziz

Bibliographic record

VenueJournal of Agricultural Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
Fundersnot available
KeywordsGenotypingAlleleBiologyLocus (genetics)GenotypeRestriction fragment length polymorphismRestriction enzymeVeterinary medicineDairy cattleAnimal scienceGeneticsGene

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.234
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2013
Admission routes1
Has abstractyes

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