Evidence map›Paper›PMID 41078982›Full record

ArticleVeterinary and animal science2025

Infrared thermographic imaging as a promising on-farm method to estimate parasite load in dairy goats.

M Bernau, T Schilling, H Eßlinger, L E Hoelzle, S A Goth

Abstract read
In one paragraph

Article in Veterinary and animal science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

M BernauHochschule für Wirtschaft und Umwelt Nürtingen-Geislingen, Fakultät Agrarwirtschaft, Neckarsteige 6-10, 72622 Nürtingen, Germany.
T SchillingUniversität Hohenheim, Institut für Nutztierwissenschaften, Fachgebiet Infektions- und Umwelthygiene bei Nutztieren, Garbenstr. 30, 70599 Stuttgart, Germany.
H EßlingerHochschule für Wirtschaft und Umwelt Nürtingen-Geislingen, Fakultät Agrarwirtschaft, Neckarsteige 6-10, 72622 Nürtingen, Germany.
L E HoelzleUniversität Hohenheim, Institut für Nutztierwissenschaften, Fachgebiet Infektions- und Umwelthygiene bei Nutztieren, Garbenstr. 30, 70599 Stuttgart, Germany.
S A GothHochschule für Wirtschaft und Umwelt Nürtingen-Geislingen, Fakultät Agrarwirtschaft, Neckarsteige 6-10, 72622 Nürtingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Faecal egg count (FEC) evaluation is the method of choice to detect parasite load in individuals, but it cannot be used directly on farm. Clinical parameters like body condition scores (BCS), body weight (BW) and milk yield (MY) have been described in this context, but all fail due to a low correlation with FEC. The present study evaluated the utility of clinical parameters, linear body measurements, and infrared thermographic imaging (IRT) in eight dairy goat herds in Germany as potential methods for estimating FEC categories. A total of 893 dairy goats comprising German Fawn Goats (GFG) and German White Goats (GWG) were examined up to six times during three consecutive lactation periods. FEC was determined using individual faecal samples, analysed via the McMaster method. Based on eggs per gram of faeces (EPG), mean FEC across all examinations was categorized into three groups: low (Category 1: ≤500 EPG), medium (Category 2: >500 to ≤1500 EPG), and high (Category 3: >1500 EPG). Statistical analyses were conducted using SAS Studio to identify factors influencing FEC. Significant differences were observed between the two breeds. In GFG, animals in Category 3 exhibited significantly lower BCS, BW, chest circumference, and MY compared to those in Category 1. IRT measurements also showed significant differences across FEC categories, with higher IRT values observed in goats with higher FEC. These findings suggest that IRT has potential as a non-invasive, on-farm method for assessing parasitic load. However, further studies are necessary to validate its practical application as a direct health monitoring method.

Indexed as

Dairy goatsFaecal egg countHealth indicatorsParasite loadThermographic imaging

Identifiers

PMID41078982
PMCPMC12508859

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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.