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Use of real-time PCR to predict dry matter disappearance of individual feeds in a total mixed ration

Alexander, T.W., Wang, Y., Reuter, T., Okine, E.K., Dixon, W.T., McAllister, T.A. (2009). Use of real-time PCR to predict dry matter disappearance of individual feeds in a total mixed ration, 149(3-4), 240-249. http://dx.doi.org/10.1016/j.anifeedsci.2008.06.011

Abstract

In ruminant nutrition, the accuracy of predicting available energy from a total mixed ration (TMR) is limited because digestibilities of individual feedstuffs vary from predicted values in response to associative effects. To overcome this limitation, it was proposed that plant-specific real-time PCR assays could be used to predict the digestion of individual feeds within a TMR. To test this hypothesis, alfalfa and corn substrates (0.5 g dry matter) were incubated in buffered rumen fluid at pH 6.8 or 5.5 for up to 48 h. Regression analysis between DNA disappearance and dry matter disappearance (DMD) for only alfalfa or corn was used to predict DMD in mixed rations containing 75:25, 50:50, and 25:75 ratios of alfalfa to corn, after plant-specific DNA quantification. The actual DM remaining was compared against the total predicted DM remaining by summing the individual values predicted for alfalfa and corn in the mixed rations. The method was accurate and precise in predicting DM remaining (Concordance and Pearson correlations were 0.89 and 0.91, respectively). Differences between coefficients of the actual and total predicted DM remaining ranged between -0.081 and 0.087 or -0.08 and 0.09 when the pH was 6.8 or 5.5, respectively. Furthermore, by analyzing substrate incubated at pH 5.5, the method was tested in the presence of an associative effect (reduced pH) known to inhibit fibre digestion but have limited consequence on starch utilization. The method predicted DMD in agreement with the expected results. The DMD of alfalfa was significantly affected (P<0.05) by interactions between time and pH or between diet and pH, whereas DMD for corn was affected by time or diet (P<0.05). The presented method may lead to redefined models to more effectively predict the available energy of individual feedstuffs within a TMR. Crown Copyright © 2008.

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