Development of equations to estimate microbial nitrogen contamination in rumen incubation residues using 15N data and chemical composition of feedstuffs
In situ rumen incubation of feedstuffs is used to obtain estimates for the rate of rumen microbial degradation of nutrients in feedstuffs such as organic matter and protein. These estimated values are used in feed evaluation systems for predicting amounts of nutrients fermented in the rumen. However, with respect to rumen degradation of protein, these rumen degradation estimates may not be accurate due to microbial contamination of in situ nitrogen residues. The objective of this study was to develop equations for predicting microbial contamination of rumen incubation residues. A literature review was carried out in order to build a dataset containing the results of studies in which microbial nitrogen (N) contamination of in situ rumen incubation residues of feedstuffs was measured based on 15N labeled feedstuffs or microbes. These prediction equations may be used in feed evaluation systems to correct in situ incubation results for microbial N contamination and, thereby, in predicting more accurate estimates of rumen protein degradation rate of feedstuffs. The data set contained results of 11 published papers in scientific journals using a 15N labeling method for estimating microbial contamination that had at least an incubation period equal to or larger than 24 h. The dataset contained 22 feedstuffs, of which 10 forages (R; 122 data points) and 12 concentrates (C; 175 data points). From the concentrate dataset, a subset of data was selected containing only low CP concentrate feedstuffs (CP < 300 g/kg DM) to estimate microbial contamination in low protein concentrates (LPC: 9 concentrates; 106 data points). Microbial N-contamination was estimated by the exponential equation of Krawielitzki et al. (2006). This model was further extended by including the effects of feed characteristics such as CP, NDF, and the combination of CP and NDF (CP and NDF expressed in g/kg DM). Coefficient of determination (R2), root mean squared prediction error (RMSPE), concordance correlation coefficient (CCC), AIC, and BIC were used to assess goodness of fit. The in situ microbial N-contamination (NCONT) of R was best predicted as follows: NCONT_R (%) = (89.0 ± 3.16−0.209 ± 0.0194 × CP) × [1 - e^(-0.117 ± 0.0121 × incubation time (h))] (R2 = 0.89; CCC = 0.94). For C and LPC the microbial nitrogen contaminationNCONT was best estimated as follows: NCONT_C (%) = (43.8 ± 4.26−0.070 ± 0.0081 × CP + 0.015 ± 0.0063 × NDF) × [1 - e^(-0.068 ± 0.0121 × incubation time (h))] (R2 = 0.75; CCC = 0.86); NCONT_LPC (%) = (53.0 ± 4.99−0.188 ± 0.0311 × CP + 0.031 ± 0.0084 × NDF) × [1 - e^(-0.072 ± 0.0134 × incubation time (h))] (R2 = 0.82; CCC = 0.90). These models can be used to correct for microbial N-contamination and thereby improve the accuracy in predicting rumen N degradation characteristics of feedstuffs for ruminants.
| Main Authors: | , |
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| Format: | Article/Letter to editor biblioteca |
| Language: | English |
| Subjects: | In situ incubation, Microbial contamination, N, Protein degradability, Rumen, |
| Online Access: | https://research.wur.nl/en/publications/development-of-equations-to-estimate-microbial-nitrogen-contamina |
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| Summary: | In situ rumen incubation of feedstuffs is used to obtain estimates for the rate of rumen microbial degradation of nutrients in feedstuffs such as organic matter and protein. These estimated values are used in feed evaluation systems for predicting amounts of nutrients fermented in the rumen. However, with respect to rumen degradation of protein, these rumen degradation estimates may not be accurate due to microbial contamination of in situ nitrogen residues. The objective of this study was to develop equations for predicting microbial contamination of rumen incubation residues. A literature review was carried out in order to build a dataset containing the results of studies in which microbial nitrogen (N) contamination of in situ rumen incubation residues of feedstuffs was measured based on 15N labeled feedstuffs or microbes. These prediction equations may be used in feed evaluation systems to correct in situ incubation results for microbial N contamination and, thereby, in predicting more accurate estimates of rumen protein degradation rate of feedstuffs. The data set contained results of 11 published papers in scientific journals using a 15N labeling method for estimating microbial contamination that had at least an incubation period equal to or larger than 24 h. The dataset contained 22 feedstuffs, of which 10 forages (R; 122 data points) and 12 concentrates (C; 175 data points). From the concentrate dataset, a subset of data was selected containing only low CP concentrate feedstuffs (CP < 300 g/kg DM) to estimate microbial contamination in low protein concentrates (LPC: 9 concentrates; 106 data points). Microbial N-contamination was estimated by the exponential equation of Krawielitzki et al. (2006). This model was further extended by including the effects of feed characteristics such as CP, NDF, and the combination of CP and NDF (CP and NDF expressed in g/kg DM). Coefficient of determination (R2), root mean squared prediction error (RMSPE), concordance correlation coefficient (CCC), AIC, and BIC were used to assess goodness of fit. The in situ microbial N-contamination (NCONT) of R was best predicted as follows: NCONT_R (%) = (89.0 ± 3.16−0.209 ± 0.0194 × CP) × [1 - e^(-0.117 ± 0.0121 × incubation time (h))] (R2 = 0.89; CCC = 0.94). For C and LPC the microbial nitrogen contaminationNCONT was best estimated as follows: NCONT_C (%) = (43.8 ± 4.26−0.070 ± 0.0081 × CP + 0.015 ± 0.0063 × NDF) × [1 - e^(-0.068 ± 0.0121 × incubation time (h))] (R2 = 0.75; CCC = 0.86); NCONT_LPC (%) = (53.0 ± 4.99−0.188 ± 0.0311 × CP + 0.031 ± 0.0084 × NDF) × [1 - e^(-0.072 ± 0.0134 × incubation time (h))] (R2 = 0.82; CCC = 0.90). These models can be used to correct for microbial N-contamination and thereby improve the accuracy in predicting rumen N degradation characteristics of feedstuffs for ruminants. |
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