Predicting forage indigestible NDF from lignin concentration. Traxler, M., J., Fox, D., G., Soest, P., J., V., Pell, A., N., Lascano, C., E., Lanna, D., P., Moore, J., E., Lana, R., P., Vélez, M., & Flores, A. Journal of Animal Science, 76(5):1469-1480, 6, 1998.
abstract   bibtex   
We used chemical composition and in vitro digestibility data from temperate and tropical forages to develop relationships between indices of lignification and forage indigestible NDF. Neutral detergent fiber indigestibility increased nonlinearly as the lignin concentration of the NDF increased. Differences in estimated indigestible NDF using equations developed for a specific forage class (C3 and C4 grasses and legumes) were small and are probably not biologically significant when compared to those estimated from a common equation. Selected equations were compared with the Cornell Net Carbohydrate and Protein System (CNCPS) for the prediction of ADG. The linear equation (2.4 times NDF lignin content) used by the CNCPS and the Beef NRC had some of the largest errors due to mean bias. A log-log model [4.37 x (lignin/NDF)(.84)] provided the best combination of low total prediction error, low mean bias, and minimal error due to regression bias when permanganate lignin was used. A similar equation based on sulfuric acid lignin [6.17 x (lignin/NDF)(.77)] also met the above criteria. These equations then were evaluated with the CNCPS model against animal growth data from diets ranging in forage quality. Regardless of the equation used for predicting unavailable fiber, the CNCPS underpredicted daily gain, with mean biases ranging from -.10 to -.22 kg/d. Regression bias ranged from .13 to .14 kg/d and the coefficients differed from unity (P = .0001). The new equations gave numerically lower energy allowable ADG by steers compared to the linear equation currently used by the CNCPS model. The estimates were lower due to a higher predicted indigestible NDF, which resulted in a lower estimated forage energy value.
@article{
 title = {Predicting forage indigestible NDF from lignin concentration.},
 type = {article},
 year = {1998},
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 pages = {1469-1480},
 volume = {76},
 websites = {http://www.journalofanimalscience.org/content/76/5/1469,http://www.journalofanimalscience.org/content/76/5/1469.full.pdf},
 month = {6},
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 abstract = {We used chemical composition and in vitro digestibility data from temperate and tropical forages to develop relationships between indices of lignification and forage indigestible NDF. Neutral detergent fiber indigestibility increased nonlinearly as the lignin concentration of the NDF increased. Differences in estimated indigestible NDF using equations developed for a specific forage class (C3 and C4 grasses and legumes) were small and are probably not biologically significant when compared to those estimated from a common equation. Selected equations were compared with the Cornell Net Carbohydrate and Protein System (CNCPS) for the prediction of ADG. The linear equation (2.4 times NDF lignin content) used by the CNCPS and the Beef NRC had some of the largest errors due to mean bias. A log-log model [4.37 x (lignin/NDF)(.84)] provided the best combination of low total prediction error, low mean bias, and minimal error due to regression bias when permanganate lignin was used. A similar equation based on sulfuric acid lignin [6.17 x (lignin/NDF)(.77)] also met the above criteria. These equations then were evaluated with the CNCPS model against animal growth data from diets ranging in forage quality. Regardless of the equation used for predicting unavailable fiber, the CNCPS underpredicted daily gain, with mean biases ranging from -.10 to -.22 kg/d. Regression bias ranged from .13 to .14 kg/d and the coefficients differed from unity (P = .0001). The new equations gave numerically lower energy allowable ADG by steers compared to the linear equation currently used by the CNCPS model. The estimates were lower due to a higher predicted indigestible NDF, which resulted in a lower estimated forage energy value.},
 bibtype = {article},
 author = {Traxler, M J and Fox, D G and Soest, P J Van and Pell, A N and Lascano, C E and Lanna, D P and Moore, J E and Lana, R P and Vélez, M and Flores, A},
 journal = {Journal of Animal Science},
 number = {5}
}

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