Literature DB >> 35857152

Accuracy of image analysis for linear zoometric measurements in dromedary camels.

Djalel Eddine Gherissi1, Ramzi Lamraoui2,3, Faycel Chacha2,4, Semir Bechir Suheil Gaouar5.   

Abstract

The present study was designed to verify the effectiveness of the image analysis method for body measurement in dromedary camel compared to manual measurements as a reference method. To achieve this aim, twenty-one linear body measurements were estimated on 59 adult Sahraoui dromedary camels (22 males and 37 females) with a normal clinical condition by using a measuring stick or vernier caliper (standard method). On the other hand, image analysis on profile, front, or behind photographs was processed using Axiovision Software. Overall mean comparison, relative error, variance, Pearson's correlation coefficient, and coefficient of variance showed that the image analysis method was accurate in relation to the manual measurement. Furthermore, image analysis results indicated relevant accuracy (bias correction factor, Cb ≈1) and precision (Pearson ρ ≈1) which were significantly correlated with the results of the reference method (Lin's concordance correlation coefficients rccc ≈ 1). According to Bland-Altman upper and lower limits of agreement, the concordance was estimated between 93.22 and 98.3%. Passing-Bablok regression showed a good relationship between the results of the two methods displaying no significant systematic and proportional bias. The image analysis method for linear body measurements in dromedary camel showed results that are in agreement with the manual measuring method. Therefore, the image analysis could be considered a valid tool for camel conformation trait studies.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Body measurements; Distance-based measurements; Dromedary camel; Image analysis

Mesh:

Year:  2022        PMID: 35857152     DOI: 10.1007/s11250-022-03242-3

Source DB:  PubMed          Journal:  Trop Anim Health Prod        ISSN: 0049-4747            Impact factor:   1.893


  23 in total

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Authors:  J M Bland; D G Altman
Journal:  Stat Methods Med Res       Date:  1999-06       Impact factor: 3.021

2.  Comparison of methods: Passing and Bablok regression.

Authors:  Lidija Bilić-Zulle
Journal:  Biochem Med (Zagreb)       Date:  2011       Impact factor: 2.313

3.  Comparison of concordance correlation coefficient and coefficient of individual agreement in assessing agreement.

Authors:  Huiman X Barnhart; Yuliya Lokhnygina; Andrzej S Kosinski; Michael Haber
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4.  The differentiation of camel breeds based on meat measurements using discriminant analysis.

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Journal:  Trop Anim Health Prod       Date:  2016-02-27       Impact factor: 1.559

5.  Automatic recording of daily walkover liveweight of dairy cattle at pasture in the first 100 days in milk.

Authors:  J I Alawneh; M A Stevenson; N B Williamson; N Lopez-Villalobos; T Otley
Journal:  J Dairy Sci       Date:  2011-09       Impact factor: 4.034

6.  Determination of some body measurements of camels with three-dimensional modeling method (3D).

Authors:  A Çağlı; M Yılmaz
Journal:  Trop Anim Health Prod       Date:  2021-12-01       Impact factor: 1.559

7.  Potential for estimation of body condition scores in dairy cattle from digital images.

Authors:  J M Bewley; A M Peacock; O Lewis; R E Boyce; D J Roberts; M P Coffey; S J Kenyon; M M Schutz
Journal:  J Dairy Sci       Date:  2008-09       Impact factor: 4.034

8.  A proposal of linear assessment scheme for the udder of dairy camels (Camelus dromedarius L.).

Authors:  Moez Ayadi; Riyadh Saleh Aljumaah; Emad Mohammed Samara; Bernard Faye; Gerardo Caja
Journal:  Trop Anim Health Prod       Date:  2016-04-02       Impact factor: 1.559

9.  Rear shape in 3 dimensions summarized by principal component analysis is a good predictor of body condition score in Holstein dairy cows.

Authors:  A Fischer; T Luginbühl; L Delattre; J M Delouard; P Faverdin
Journal:  J Dairy Sci       Date:  2015-05-07       Impact factor: 4.034

10.  A method for measuring human body composition using digital images.

Authors:  Olivia Affuso; Ligaj Pradhan; Chengcui Zhang; Song Gao; Howard W Wiener; Barbara Gower; Steven B Heymsfield; David B Allison
Journal:  PLoS One       Date:  2018-11-05       Impact factor: 3.240

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