Differences in burden of gastrointestinal nematode infestations in indigenous does foraging in grassland and forestland vegetation types.

Trop Anim Health Prod

Department of Veterinary Tropical Diseases, University of Pretoria, Private Bag X04, Onderstepoort, 0110, South Africa.

Published: September 2021

Gastrointestinal nematode (GIN) infestations remain a major challenge to the health, productivity and reproductive performance of small ruminants. A longitudinal study was conducted to assess the effect of vegetation type, season and parity on the burden of GIN in indigenous does that were foraging in grassland and forestland vegetation types. Body condition scores (BCS), packed cell volume (PCV), FAMACHA score and faecal egg counts (FEC) were determined in Xhosa lob-eared does (n = 165) during the cool-dry, hot-wet and post-rainy seasons in both vegetation types. Faecal samples were collected from the rectum and analysed using the modified McMaster technique. There was a significant association between vegetation type and season on the recorded BCS, body weight (BW), FEC, PCV and FAMACHA scores. Xhosa lob-eared does in the forestland had higher (P < 0.05) BCS as compared to those in grassland. Higher FEC (P < 0.05) were observed in Xhosa lob-eared does in the grassland vegetation compared to those in forestland. Body condition scores, FEC and FAMACHA scores were significantly higher in the hot-wet season than cool-dry and post-rainy seasons, while PCV was significantly higher during the cool-dry compared to hot-wet season in forestland. Strongyles and Strongyloides eggs were higher in does grazing in the grassland than those in the forestland during the hot-wet season. Strategies for the effective control of GIN in goats should consider that infestation levels differ with vegetation type, season and parity. Controlling of GIN in goats, therefore, requires an integrated control strategy that should consider the vegetation type that the goats are reared on.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11250-021-02929-3DOI Listing

Publication Analysis

Top Keywords

vegetation types
12
gastrointestinal nematode
8
indigenous foraging
8
foraging grassland
8
grassland forestland
8
forestland vegetation
8
vegetation type
8
type season
8
pcv famacha
8
xhosa lob-eared
8

Similar Publications

Biophysical effects of croplands on land surface temperature.

Nat Commun

December 2024

Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT, USA.

Converting natural vegetation to croplands alters the local land surface energy budget. Here, we use two decades of satellite data and a physics-based framework to analyse the biophysical mechanisms by which croplands influence daily mean land surface temperature (LST). Globally, 60% of croplands exhibit an annual warming effect, while 40% have a cooling effect compared to their surrounding natural ecosystems.

View Article and Find Full Text PDF

Pine needle, pine bark, and soil samples were collected from various regions in South Korea, considering the suitability of vegetation samples as passive samplers. A total of 27 organochlorine pesticides (OCPs) were analyzed using gas chromatography/high-resolution mass spectrometry (GC/HRMS). The total concentrations of OCPs ranged between 650 and 3,652 pg/g dw in soil, 215 and 1384 pg/g ww in pine needles, and 456 and 1,723 pg/g ww in pine bark.

View Article and Find Full Text PDF

Vegetation restoration can be effective in containing gully head advance. However, the effect of vegetation restoration type on soil aggregate stability and erosion resistance at the head of the gully is unclear. In this study, five types of vegetation restoration-Pinus tabulaeformis (PT), Prunus sibirica (PS), Caragana korshinskii (CKS), Hippophae rhamnoides (HR), and natural grassland (NG, the dominant species is Leymus chinensis)-in the gully head were studied.

View Article and Find Full Text PDF

This study delves into the multi-scale temporal and spatial variations of soil heat flux (G) within riparian zones and its correlation with net radiation (Rn) across six riparian woodlands in Shanghai, each characterized by distinct vegetation types. The objective is to assess the complex interrelations between G and Rn, and how these relationships are influenced by varying vegetation and seasons. Over the course of a year, data on G and Rn is collected to investigate their dynamics.

View Article and Find Full Text PDF

This paper presents a deep learning model based on an active learning strategy. The model achieves accurate identification of vegetation types in the study area by utilizing multispectral data obtained from preprocessing of unmanned aerial vehicle (UAV) remote sensing equipment. This approach offers advantages such as high data accuracy, mobility, and easy data collection.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!