Claim · model-written summary
ADL and ADF gave the greatest correlation with uNDF of any single variable in the whole data set.
- Taxon
- forage typest0
- Compound
- ADL and ADFe1
- Outcome
- greatest correlation with a single variablee1
- Value
- 0.63e1
- Qualifier
- whole data sete1
Not reportedMaterialGeneOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirection
Verbatim
t0“Estimation of the indigestible fiber in different forage types”
e1“The greatest correlation with a single variable was obtained by ADL and ADF when applied to the whole data set ( = 0.63)”
Title
Estimation of the indigestible fiber in different forage types
A. Palmonari; A. Gallo; M. Fustini; et al. Journal of Animal Science 2015. doi:10.2527/jas.2015-9649
Other claims from this paper (12)
- Observation Grass hay had an uNDF value of 22.7% ± 4.48% DM.
- Observation Alfalfa hay had an uNDF value of 20.1% ± 4.23% DM.
- Observation Corn silage had an uNDF value of 11.8% ± 3.5% DM.
- Observation The observed uNDF:ADL ratio was 3.22 for grass hay.
- Observation The observed uNDF:ADL ratio was 3.11 for corn silage.
- Association The relationship between uNDF and ADL was not constant and differed for grass hay and corn silage from the 2.4 × lignin value of the Chandler equation.
- Association The multiple regression equation gave a coefficient of determination of 0.80 for the whole data set.
- Association Within grass hay, the multiple regression equation gave a coefficient of determination of 0.65.
- Association Within alfalfa hay, the multiple regression equation gave a coefficient of determination of 0.77.
- Association Within corn silage, the multiple regression equation gave a coefficient of determination of 0.54.
- Recommendation A regression approach for forage uNDF requires specific equations and different regression coefficients for each forage type.
- Method / resource Direct measurement of uNDF was the best approach for an accurate prediction of iNDF, compared with a regression approach.