Evidence map›Paper›PMID 28687941›Full record

ArticleTropical animal health and production2017

Genetic parameters for tick counts across months for different tick species and anatomical locations in South African Nguni cattle.

N O Mapholi, A Maiwashe, O Matika, V Riggio, C Banga, M D MacNeil, V Muchenje, K Nephawe, K Dzama

Abstract read
In one paragraph

Article in Tropical animal health and production, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Populational Model ofVeterinary sciences · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

N O MapholiDepartment of Life and Consumer Sciences, University of South Africa, Private Bag X6, Florida, 1710, South Africa. maphon@unisa.ac.za.
A MaiwasheAgricultural Research Council, Private Bag X2, Irene, 0062, South Africa.
O MatikaThe Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, UK.
V RiggioThe Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, UK.
C BangaAgricultural Research Council, Private Bag X2, Irene, 0062, South Africa.
M D MacNeilAgricultural Research Council, Private Bag X2, Irene, 0062, South Africa.
V MuchenjeUniversity of Fort Hare, Private Bag X 1314, Alice, South Africa.
K NephaweDepartment of Animal Sciences, Faculty of Science, Tshwane University of Technology (TUT), P/Bag X680, Pretoria, 0001, South Africa.
K DzamaDepartment of Animal Science, University of Stellenbosch, P Bag X1, Matieland, 7602, South Africa.

Funding

Biotechnology and Biological Sciences Research Council BBS/E/D/20211553
6 · The paper itself

Abstract

The objective of the study was to characterise genetic parameters across months for different tick species and anatomical locations in South African Nguni cattle. Tick counts were conducted monthly, over a 2-year period, on 586 Nguni cattle under natural infestation, from four herds located in different provinces of South Africa. The counts were recorded for six species of ticks (Amblyomma hebraeum, Rhipicephalus evertsi evertsi, Rhipicephalus decoleratus and microplus (Boofilids), Rhipicephalus appendiculatus, Rhipicephalus simus and Hyalomma marginatum) attached on eight anatomical locations on the animals and were summed by species and anatomical location. Heritability estimates, phenotypic and genetic correlations were estimated on a monthly basis using mixed linear models, fitting univariate and bivariate sire models. Fixed effects considered were location, sex, year and age as a covariate. Tick counts were higher in the hot months, and A. hebraeum was the most dominant tick species. Heritability estimates for tick count varied by month and trait and ranged from 0 to 0.89. Genetic correlations were mostly positive, and low to high, with some negative correlations with high standard error. Phenotypic correlations were low to moderate. In general, high genetic correlations were observed between whole body count and the anatomical location counts, suggesting that it may not be necessary to conduct whole body counts. Counts from the belly and perineum appeared to be the most suitable surrogate traits for whole body count. These findings provide useful information for developing strategies for the practical implementation of genetic selection, as a supplement to the traditional tick control measures.

Indexed as

PhenotypeAnimalsCattleCattle DiseasesFemaleIxodidaeMalePrevalenceSouth AfricaSpecies SpecificityTick InfestationsCorrelationHeritabilityTick countTick resistance

Identifiers

PMID28687941
PMCPMC5519660

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.