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Effects of correcting in situ ruminal microbial colonization of feed particles on the relationship between ruminally undegraded and intestinally digested crude protein in concentrate feeds.
Journal of the Science of Food and Agriculture 2018 Februrary
BACKGROUND: In situ estimates of ruminally undegraded protein (RUP) and intestinally digested protein (IDP) of ten concentrates, uncorrected or corrected for the ruminal microbial colonization, were used to examine the effects of this correction on the relationship between IDP and RUP values. Both variables were established for three rumen and duodenum cannulated wethers using 15 N labeling-techniques and considering measured rates of ruminal particle comminution (kc ) and outflow (kp ).
RESULTS: A covariance analysis showed that the close relationship found between both variables (IDP = -0.0132 ± 0.00679 + 0.776 ± 0.0002 RUP; n = 60; P < 0.001; r = 0.960) is not affected by correcting for microbial colonization (P = 0.682).
CONCLUSION: The IDP content in concentrates and industrial by-products can be predicted from RUP values, thus avoiding the laborious and complex procedure of determining intestinal digestibility; however, a larger sample of feeds is necessary to achieve more accurate predictions. The lack of influence of the correction for microbial contamination on the prediction observed in the present study increases the data available for this prediction. However, only the use of corrected values may provide an accurate evaluation. © 2017 Society of Chemical Industry.
RESULTS: A covariance analysis showed that the close relationship found between both variables (IDP = -0.0132 ± 0.00679 + 0.776 ± 0.0002 RUP; n = 60; P < 0.001; r = 0.960) is not affected by correcting for microbial colonization (P = 0.682).
CONCLUSION: The IDP content in concentrates and industrial by-products can be predicted from RUP values, thus avoiding the laborious and complex procedure of determining intestinal digestibility; however, a larger sample of feeds is necessary to achieve more accurate predictions. The lack of influence of the correction for microbial contamination on the prediction observed in the present study increases the data available for this prediction. However, only the use of corrected values may provide an accurate evaluation. © 2017 Society of Chemical Industry.
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