M. Bernau , T. Schilling , H. Eßlinger , L.E. Hoelzle , S.A. Goth
{"title":"Infrared thermographic imaging as a promising on-farm method to estimate parasite load in dairy goats","authors":"M. Bernau , T. Schilling , H. Eßlinger , L.E. Hoelzle , S.A. Goth","doi":"10.1016/j.vas.2025.100506","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div><div>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.</div></div>","PeriodicalId":37152,"journal":{"name":"Veterinary and Animal Science","volume":"30 ","pages":"Article 100506"},"PeriodicalIF":1.9000,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Veterinary and Animal Science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451943X2500078X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
引用次数: 0
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.