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Martineau R, Ouellet DR, Pellerin D, Firkins JL, Hanigan MD, White RR, LaPierre PA, Van Amburgh ME, Lapierre H. Ability of three dairy feed evaluation systems to predict postruminal outflows of amino acids in dairy cows: A meta-analysis. J Dairy Sci 2024; 107:3573-3600. [PMID: 38216041 DOI: 10.3168/jds.2023-24300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/05/2023] [Indexed: 01/14/2024]
Abstract
Adequate prediction of postruminal outflows of essential AA (EAA) is the starting point of balancing rations for EAA in dairy cows. The objective of this meta-analysis was to compare the performance of 3 dairy feed evaluation systems (National Research Council [NRC], Cornell Net Protein and Carbohydrate System version 6.5.5 [CNCPS], and National Academies of Sciences, Engineering and Medicine [NASEM]) to predict EAA outflows (Trp was not tested). The data set included a total of 354 treatment means from 70 duodenal and 24 omasal studies. To avoid Type I error, mean and linear biases were considered of concern if statistically significant and representing >5.0% of the observed mean. Analyses were conducted on raw observed values and on observations adjusted for the random effect of study. The analysis on raw data indicates the ability of the feed evaluation system to predict absolute values whereas the analysis on adjusted values indicates its ability to predict responses of EAA outflows to dietary changes. For the prediction of absolute values (based on raw data), NRC underpredicted outflows of all EAA, from 5.3% to 8.6% of the observed mean (%obs.mean) except for Leu, Lys, and Val; NASEM overpredicted Lys (10.8%obs.mean); and CNCPS overpredicted Arg, His, Lys, Met, and Val (5.2 to 26.0%obs.mean). No EAA had a linear bias of concern with NASEM, followed by NRC for His (6.8%obs.mean), and CNCPS for all EAA (5.6 to 12.2%obs.mean) except Leu, Phe, and Thr. In contrast, for the prediction of responses to dietary changes (based on adjusted data), NRC had 2 EAA presenting a linear bias of concern, followed by NASEM and CNCPS with 4 and 6 EAA, respectively. Predictions of His showed a linear bias of concern (5.3 to 9.6%obs.mean) with the 3 feed evaluation systems. Measured chemistry of crude protein and EAA were reported for 1 or more feed ingredients of the ration in 36% of the studies, and resulted in decreased linear biases in the 3 feed evaluation systems. The difference in mean biases of Met outflows was systematically positive when comparing omasal versus duodenal studies. Predictions of Met outflows with NRC had a higher concordance correlation coefficient in duodenal (used to develop NRC equations) versus omasal studies, whereas the opposite was observed with CNCPS, the latter showing the lowest mean bias for Met in omasal sampling studies. The 30% difference in Met mean biases between sampling sites appeared related to a similar difference found for observed Met versus nonammonia nitrogen outflows between duodenal and omasal studies, which is independent of predictions. In conclusion, NRC and NASEM yielded accurate predictions of EAA outflows, with a small superiority of NASEM to predict absolute values, and slight superiority of NRC to predict the responses to dietary changes. In comparison, CNCPS may present mean and linear biases of concern for many EAA. Moreover, it remains to determine which sampling site is more representative of the true supply of EAA to the cows.
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Affiliation(s)
- R Martineau
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8.
| | - D R Ouellet
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8
| | - D Pellerin
- Department of Animal Science, Laval University, Québec, QC, Canada, G1V 0A6
| | - J L Firkins
- Department of Animal Sciences, The Ohio State University, Columbus, OH 43210
| | - M D Hanigan
- Department of Dairy Science, Virginia Tech, Blacksburg, VA 24060
| | - R R White
- Department of Dairy Science, Virginia Tech, Blacksburg, VA 24060
| | - P A LaPierre
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - M E Van Amburgh
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - H Lapierre
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8
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Martineau R, Ouellet DR, Pellerin D, Firkins JL, Hanigan MD, White RR, LaPierre PA, Van Amburgh ME, Lapierre H. Ability of three dairy feed evaluation systems to predict postruminal outflows of nitrogenous compounds in dairy cows: A meta-analysis. J Dairy Sci 2023; 106:8583-8610. [PMID: 37683889 DOI: 10.3168/jds.2022-23215] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 05/15/2023] [Indexed: 09/10/2023]
Abstract
Adequate prediction of postruminal outflow of protein fractions is the starting point for the determination of metabolizable protein supply in dairy cows. The objective of this meta-analysis was to compare the performance of 3 dairy feed evaluation systems (National Research Council [NRC], Cornell Net Protein and Carbohydrate System [CNCPS], and National Academies of Sciences, Engineering and Medicine [NASEM]) to predict outflows (g/d) of nonammonia nitrogren (NAN), microbial N (MiN), and nonammonia nonmicrobial N (NANMN). Predictions of rumen degradabilities (% of nutrient) of protein (RDP), NDF, and starch were also evaluated. The data set included 1,294 treatment means from 312 digesta flow studies. The 3 feed evaluation systems were compared using the concordance correlation coefficient (CCC), the ratio of root mean square prediction error (RMSPE) on standard deviation of observed values (RSR), and the slope between observed and predicted values. Mean and linear biases were deemed biologically relevant and are discussed if higher than a threshold of 5% of the mean of observed values. The comparisons were done on observed values adjusted or not for the study effect; the adjustment had a small effect on the mean bias but the linear bias reflected a response to a dietary change rather than absolute predictions. For the absolute predictions of NAN and MiN, CNCPS had the best-fit statistics (8% greater CCC; 6% lower RMSPE) without any bias; NRC and NASEM underpredicted NAN and MiN, and NASEM had an additional linear bias indicating that the underprediction of MiN increased at increased predictions. For NANMN, fit statistics were similar among the 3 feed evaluation systems with no mean bias; however, the linear bias with NRC and CNCPS indicated underprediction at low predictions and overprediction at elevated predictions. On average, the CCC were smaller and RSR ratios were greater for MiN versus NAN indicating increased prediction errors for MiN. For NAN responses to a dietary change, CNCPS also had the best predictions, although the mean bias with NASEM was not biologically relevant and the 3 feed evaluation systems did not present a linear bias. However, CNCPS, but not the 2 other feed evaluation systems, presented a linear bias for MiN, with responses being overpredicted at increased predictions. For NANMN, responses were overpredicted at increased predictions for the 3 feed evaluation systems, but to a lesser extent with NASEM. The site of sampling had an effect on the mean bias of MiN and NANMN in the 3 feed evaluation systems. The mean bias of MiN was higher in omasal than duodenal studies in the 3 feed evaluation systems (from 55 to 61 g/d) and this mean bias was twice as large when 15N labeling was used as a microbial marker compared with purines. Such a difference was not observed for duodenal studies. The reasons underlying these systematic differences are not clear as the type of measurements used in the current meta-analysis does not allow to delineate if one site or one microbial marker is yielding the "true" postruminal N outflows. Rumen degradabilities of protein was underpredicted with CNCPS, and RDP responses to a dietary change was underpredicted by the 3 feed evaluation systems with increased RDP predictions. Rumen degradability of NDF was underpredicted and had poor fit statistics for NASEM compared with CNCPS. Fit statistics were similar between CNCPS and NASEM for rumen degradability of starch, but with an underprediction of the response with NASEM and absolute values being overpredicted with CNCPS. Multivariate regression analyses showed that diet characteristics were correlated with prediction errors of N outflows in each feed evaluation system. Globally, compared with NAN and NANMN, residuals of MiN were correlated with several moderators in the 3 feed evaluation systems reflecting the complexity to measure and model this outflow. In addition, residuals of NANMN were correlated positively with RDP suggesting an overestimation of this parameter. In conclusion, although progress is still to be made to improve equations predicting postruminal N outflows, the current feed evaluation systems provide sufficient precision and accuracy to predict postruminal outflows of N fractions.
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Affiliation(s)
- R Martineau
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8.
| | - D R Ouellet
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8
| | - D Pellerin
- Department of Animal Science, Laval University, Québec, QC, Canada, G1V 0A6
| | - J L Firkins
- Department of Animal Sciences, The Ohio State University, Columbus, OH 43210
| | - M D Hanigan
- Department of Dairy Science, Virginia Tech, Blacksburg, VA 24060
| | - R R White
- Department of Dairy Science, Virginia Tech, Blacksburg, VA 24060
| | - P A LaPierre
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - M E Van Amburgh
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - H Lapierre
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8
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Daniel JB, Sanz-Fernandez MV, Nichols K, Doelman J, Martín-Tereso J. Digestive and metabolic efficiency of energy and nitrogen during lactation and the dry period in dairy cows. J Dairy Sci 2022; 105:9564-9580. [DOI: 10.3168/jds.2022-22142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 07/22/2022] [Indexed: 11/06/2022]
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Laboratory Analyses Used to Define the Nutritional Parameters and Quality Indexes of Some Unusual Forages. Animals (Basel) 2022; 12:ani12182320. [PMID: 36139179 PMCID: PMC9494946 DOI: 10.3390/ani12182320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 09/02/2022] [Accepted: 09/03/2022] [Indexed: 11/20/2022] Open
Abstract
Simple Summary In the present study, laboratory analyses conducted on unusual forages have been used to calculate various parameters and define some quality indexes using different equations. It was found that the quality of unusual forages decreased during the growth but maintained a high level. Different indexes were used to evaluate the forage quality. The Relative Feed Value and the Relative Forage Quality indexes, when calculated with the formula for legumes, correctly summarized the trend of the nutritional characteristics of the unusual forages at different maturity stages. Abstract The quality of a forage influences the production of animals, and it can be defined in many ways. Laboratory analyses are important tools because they can be used to indicate the quality of the forages, and they represent a relatively quick way of defining their nutritive values. However, specific quality indexes are necessary to evaluate and rank forages. The quality of conventional forages is predicted by different indexes, according to whether they are legumes or grasses. However, no indications are given about what formulae should be used for unusual forages. In the present study, laboratory analyses have been conducted on three unusual crops belonging to three different botanical families (amaranth, borage, and camelina) at four growth stages, and conventional quality indexes have been calculated and applied to establish their quality. The obtained results have shown that the nutritive value of the unusual forages modified during the growth, although they always maintained a high quality. Hence, the Relative Feed Value of unusual forages can be measured using the ADF content or digestibility value. The Relative Forage Quality, calculated with the legume formula, seems more appropriate for the considered unusual forages as it was able to reveal any changes that took place during maturity.
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Harmon DL. Grand Challenge in Animal Nutrition. FRONTIERS IN ANIMAL SCIENCE 2020. [DOI: 10.3389/fanim.2020.621638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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