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Estimation of dairy goat body composition: A direct calibration and comparison of eight methods
- Source :
- Methods, Methods, Elsevier, In press, ⟨10.1016/j.ymeth.2020.06.014⟩, Methods, Elsevier, 2020, ⟨10.1016/j.ymeth.2020.06.014⟩, Methods, Elsevier, 2021, 186, pp.68-78. ⟨10.1016/j.ymeth.2020.06.014⟩
- Publication Year :
- 2020
- Publisher :
- HAL CCSD, 2020.
-
Abstract
- International audience; The objective was to compare eight methods for estimation of dairy goat body composition, by calibrating against chemical composition (water, lipid, protein, mineral and energy) measured post-mortem. The methods tested on 20 Alpine goats were body condition score (BCS), 3-dimension imaging (3D) automatic assessment of BCS or whole body scan, ultrasound, computer tomography (CT), adipose cell diameter, deuterium oxide dilution space (D 2 OS) and bioelectrical impedance spectroscopy (BIS). Regressions were tested between predictive variates derived from the methods and empty body (EB) composition. The best equations for estimation of EB lipid mass included BW combined with i) perirenal adipose tissue mass and cell diameter (R 2 = 0.95, residual standard deviation, rSD = 0.57 kg), ii) volume of fatty tissues measured by CT (R 2 = 0.92, rSD = 0.76 kg), iii) D 2 OS (R 2 = 0.91, rSD = 0.85 kg), and iv) resistance at infinite frequency from BIS (R 2 = 0.87, rSD = 1.09 kg). The D 2 OS combined with BW provided the best equation for EB protein mass (R 2 = 0.97, rSD = 0.17 kg), whereas BW alone provided a fair estimate (R 2 = 0.92, rSD = 0.25 kg). Sternal BCS combined with BW provided good estimation of EB lipid and protein mass (R 2 = 0.80 and 0.95, rSD = 1.27 and 0.22 kg, respectively). Compared to manual BCS, BCS by 3D slightly decreased the precision of the predictive equation for EB lipid (R 2 = 0.74, rSD = 1.46 kg), and did not improve the estimation of EB protein compared with BW alone. Ultrasound measurements and whole body 3D imaging methods were not satisfactory estimators of body composition (R 2 ≤ 0.40). Further developments in body composition techniques may contribute for high-throughput phenotyping of robustness.
- Subjects :
- Cell diameter
Computer tomography
residual standard deviation
[SDV]Life Sciences [q-bio]
Adipose cell size
isotope ratio mass spectrometry
Xc
DM
computer-tomography
Ultrasonography
0303 health sciences
residual coefficient of variation
ultrasound
Chemistry
Goats
030302 biochemistry & molecular biology
Ultrasound
D 2 O
BCS
Dilution
Dairying
Milk
Adipose Tissue
Deuterium oxide
Body Composition
Female
CV
Composition (visual arts)
standard deviation
Bioelectrical impedance spectroscopy
3D
CT
rSD
Residual standard deviation
empty body
Ruminant
three-dimension
D 2 OS
General Biochemistry, Genetics and Molecular Biology
resistance
body weight
03 medical and health sciences
Imaging, Three-Dimensional
Animal science
Body condition score
3D imaging
bioelectrical impedance spectroscopy
Calibration
Animals
Lactation
Body Weights and Measures
adipose cell diameter
rCV
BW
Molecular Biology
SD
030304 developmental biology
US
EB
body condition score
business.industry
reactance
BIS
deuterium oxide dilution space
Body chemical composition
IRMS
coefficient of variation
Ruminant Body chemical composition 3D imaging Computer tomography Adipose cell size Deuterium oxide Abbreviations: ACD
dry matter
Tomography, X-Ray Computed
business
Subjects
Details
- Language :
- English
- ISSN :
- 10462023 and 10959130
- Database :
- OpenAIRE
- Journal :
- Methods, Methods, Elsevier, In press, ⟨10.1016/j.ymeth.2020.06.014⟩, Methods, Elsevier, 2020, ⟨10.1016/j.ymeth.2020.06.014⟩, Methods, Elsevier, 2021, 186, pp.68-78. ⟨10.1016/j.ymeth.2020.06.014⟩
- Accession number :
- edsair.doi.dedup.....5df6915fdd04d6549b19646bc1cb5604
- Full Text :
- https://doi.org/10.1016/j.ymeth.2020.06.014⟩