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Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle

The objective of this study was to evaluate the predictions of dry matter intake (DM) and average daily gain (ADG) of Vietnamese Yellow (Vang) purebred and crossbred (Vang with Red Sindhi or Brahman) bulls fed under Vietnamese conditions using two levels of solution (1 and 2) of the large ruminant n...

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Autores principales: Parsons, David, Van, Nguyen Huu, Malau-Aduli, Aduli E. O., Ba, Nguyen Xuan, Phung, Le Dinh, Lane, Peter A., Ngoan, Le Duc, Tedeschi, Luis O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4092944/
https://www.ncbi.nlm.nih.gov/pubmed/25049686
http://dx.doi.org/10.5713/ajas.2012.12036
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author Parsons, David
Van, Nguyen Huu
Malau-Aduli, Aduli E. O.
Ba, Nguyen Xuan
Phung, Le Dinh
Lane, Peter A.
Ngoan, Le Duc
Tedeschi, Luis O.
author_facet Parsons, David
Van, Nguyen Huu
Malau-Aduli, Aduli E. O.
Ba, Nguyen Xuan
Phung, Le Dinh
Lane, Peter A.
Ngoan, Le Duc
Tedeschi, Luis O.
author_sort Parsons, David
collection PubMed
description The objective of this study was to evaluate the predictions of dry matter intake (DM) and average daily gain (ADG) of Vietnamese Yellow (Vang) purebred and crossbred (Vang with Red Sindhi or Brahman) bulls fed under Vietnamese conditions using two levels of solution (1 and 2) of the large ruminant nutrition system (LRNS) model. Animal information and feed chemical characterization were obtained from five studies. The initial mean body weight (BW) of the animals was 186, with standard deviation ±33.2 kg. Animals were fed ad libitum commonly available feedstuffs, including cassava powder, corn grain, Napier grass, rice straw and bran, and minerals and vitamins, for 50 to 80 d. Adequacy of the predictions was assessed with the Model Evaluation System using the root of mean square error of prediction (RMSEP), accuracy (Cb), coefficient of determination (r(2)), and mean bias (MB). When all treatment means were used, both levels of solution predicted DMI similarly with low precision (r(2) of 0.389 and 0.45 for level 1 and 2, respectively) and medium accuracy (Cb of 0.827 and 0.859, respectively). The LRNS clearly over-predicted the intake of one study. When this study was removed from the comparison, the precision and accuracy considerably increased for the level 1 solution. Metabolisable protein was limiting ADG for more than 68% of the treatment averages. Both levels differed regarding precision and accuracy. While level 1 solution had the least MB compared with level 2 (0.058 and 0.159 kg/d, respectively), the precision was greater for level 2 than level 1 (0.89 and 0.70, respectively). The accuracy (Cb) was similar between level 1 and level 2 (p = 0.8997; 0.977 and 0.871, respectively). The RMSEP indicated that both levels were on average under- or over-predicted by about 190 g/d, suggesting that even though the accuracy (Cb) was greater for level 1 compared to level 2, both levels are likely to wrongly predict ADG by the same amount. Our analyses indicated that the level 1 solution can predict DMI reasonably well for this type of animal, but it was not entirely clear if animals consumed at their voluntary intake and/or if the roughness of the diet decreased DMI. A deficit of ruminally-undegradable protein and/or a lack of microbial protein may have limited the performance of these animals. Based on these evaluations, the LRNS level 1 solution may be an alternative to predict animal performance when, under specific circumstances, the fractional degradation rates of the carbohydrate and protein fractions are not known.
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spelling pubmed-40929442014-07-21 Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle Parsons, David Van, Nguyen Huu Malau-Aduli, Aduli E. O. Ba, Nguyen Xuan Phung, Le Dinh Lane, Peter A. Ngoan, Le Duc Tedeschi, Luis O. Asian-Australas J Anim Sci Article The objective of this study was to evaluate the predictions of dry matter intake (DM) and average daily gain (ADG) of Vietnamese Yellow (Vang) purebred and crossbred (Vang with Red Sindhi or Brahman) bulls fed under Vietnamese conditions using two levels of solution (1 and 2) of the large ruminant nutrition system (LRNS) model. Animal information and feed chemical characterization were obtained from five studies. The initial mean body weight (BW) of the animals was 186, with standard deviation ±33.2 kg. Animals were fed ad libitum commonly available feedstuffs, including cassava powder, corn grain, Napier grass, rice straw and bran, and minerals and vitamins, for 50 to 80 d. Adequacy of the predictions was assessed with the Model Evaluation System using the root of mean square error of prediction (RMSEP), accuracy (Cb), coefficient of determination (r(2)), and mean bias (MB). When all treatment means were used, both levels of solution predicted DMI similarly with low precision (r(2) of 0.389 and 0.45 for level 1 and 2, respectively) and medium accuracy (Cb of 0.827 and 0.859, respectively). The LRNS clearly over-predicted the intake of one study. When this study was removed from the comparison, the precision and accuracy considerably increased for the level 1 solution. Metabolisable protein was limiting ADG for more than 68% of the treatment averages. Both levels differed regarding precision and accuracy. While level 1 solution had the least MB compared with level 2 (0.058 and 0.159 kg/d, respectively), the precision was greater for level 2 than level 1 (0.89 and 0.70, respectively). The accuracy (Cb) was similar between level 1 and level 2 (p = 0.8997; 0.977 and 0.871, respectively). The RMSEP indicated that both levels were on average under- or over-predicted by about 190 g/d, suggesting that even though the accuracy (Cb) was greater for level 1 compared to level 2, both levels are likely to wrongly predict ADG by the same amount. Our analyses indicated that the level 1 solution can predict DMI reasonably well for this type of animal, but it was not entirely clear if animals consumed at their voluntary intake and/or if the roughness of the diet decreased DMI. A deficit of ruminally-undegradable protein and/or a lack of microbial protein may have limited the performance of these animals. Based on these evaluations, the LRNS level 1 solution may be an alternative to predict animal performance when, under specific circumstances, the fractional degradation rates of the carbohydrate and protein fractions are not known. Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST) 2012-09 /pmc/articles/PMC4092944/ /pubmed/25049686 http://dx.doi.org/10.5713/ajas.2012.12036 Text en Copyright © 2012 by Asian-Australasian Journal of Animal Sciences This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License http://creativecommons.org/licenses/by-nc/3.0/ which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Parsons, David
Van, Nguyen Huu
Malau-Aduli, Aduli E. O.
Ba, Nguyen Xuan
Phung, Le Dinh
Lane, Peter A.
Ngoan, Le Duc
Tedeschi, Luis O.
Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle
title Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle
title_full Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle
title_fullStr Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle
title_full_unstemmed Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle
title_short Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle
title_sort evaluation of a nutrition model in predicting performance of vietnamese cattle
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4092944/
https://www.ncbi.nlm.nih.gov/pubmed/25049686
http://dx.doi.org/10.5713/ajas.2012.12036
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