1
|
Sauvant D. Modeling efficiency and robustness in ruminants: the nutritional point of view. Anim Front 2019; 9:60-67. [PMID: 32002252 PMCID: PMC6951951 DOI: 10.1093/af/vfz012] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Daniel Sauvant
- UMR Modélisation Systémique Appliquée aux Ruminants, AgroParisTech, INRA, Université Paris-Saclay, Paris, France
| |
Collapse
|
2
|
Muñoz-Tamayo R, Giger-Reverdin S, Sauvant D. Mechanistic modelling of in vitro fermentation and methane production by rumen microbiota. Anim Feed Sci Technol 2016. [DOI: 10.1016/j.anifeedsci.2016.07.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
|
3
|
Sarhan MA, Beauchemin KA. Ruminal pH predictions for beef cattle: Comparative evaluation of current models. J Anim Sci 2016; 93:1741-59. [PMID: 26020196 DOI: 10.2527/jas.2014-8428] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
This study evaluated 8 empirical models for their ability to accurately predict mean ruminal pH in beef cattle fed a wide range of diets. Models tested that use physically effective fiber (peNDF) as a dependent variable were Pitt et al. (1996, PIT), Mertens (1997, MER), Fox et al. (2004, FOX), Zebeli et al. (2006, ZB6), and Zebeli et al. (2008, ZB8), and those that use rumen VFA were Tamminga and Van Vuuren (1988, TAM), Lescoat and Sauvant (1995, LES), and Allen (1997, ALL). A data set of 65 published papers (231 treatment means) for beef cattle was assembled that included information on animal characteristics, diet composition, and ruminal fermentation and mean pH. Model evaluations were based on mean square prediction error (MSPE), concordance correlation coefficient (CCC), and regression analysis. The prediction potential of the models varied with low root MSPE (RMSPE) values of 4.94% and 5.37% for PIT and FOX, RMSPE values of 9.66% and 12.55% for ZB6 and MER, and intermediate RMSPE values of 5.66% to 6.26% for the other models. For PIT and FOX, with the lowest RMSPE, approximately 96% of MSPE was due to random error, whereas for ZB6 and MER, with the highest RMSPE, 15.85% and 23.42% of MSPE, respectively, was due to linear bias, and 37.19% and 60.12% of the error, respectively, was due to deviation of the regression slope from unity. The CCC was greatest for PIT (0.67) and FOX (0.62), followed by 0.60 for LES and TAM, 0.52 for ZB8, 0.39 for MER, 0.34 for ALL, and 0.22 for ZB6. Residuals plotted against model-predicted values showed linear bias (P < 0.001) for all models except PIT (P = 0.976) and FOX (P = 0.054) and mean bias (P < 0.001) except for FOX (P = 0.293), LES (P = 0.215), and TAM (P = 0.119). The study showed that the empirical models PIT and FOX, based on peNDF, and LES and TAM, based on VFA, are preferred over the others for prediction of mean ruminal pH in beef cattle fed a wide range of diets. Several animal (BW and intake), diet (forage and OM contents), and ruminal (ammonia and acetate concentrations) factors were (P < 0.001) related to the residuals for each model. We conclude that the accuracy of prediction of mean ruminal pH was relatively low for all extant models. Consideration of factors in addition to peNDF and total VFA, as well as the use of data from studies with continuous measurement of ruminal pH over 24 h or more, would be useful in the development of improved models for predicting ruminal pH in beef cattle.
Collapse
|
4
|
Quantification of the main digestive processes in ruminants: the equations involved in the renewed energy and protein feed evaluation systems. Animal 2016; 10:755-70. [DOI: 10.1017/s1751731115002670] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
|
5
|
Higgs R, Chase L, Ross D, Van Amburgh M. Updating the Cornell Net Carbohydrate and Protein System feed library and analyzing model sensitivity to feed inputs. J Dairy Sci 2015; 98:6340-60. [DOI: 10.3168/jds.2015-9379] [Citation(s) in RCA: 97] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2015] [Accepted: 05/25/2015] [Indexed: 11/19/2022]
|
6
|
Ramin M, Huhtanen P. Nordic dairy cow model Karoline in predicting methane emissions: 2. Model evaluation. Livest Sci 2015. [DOI: 10.1016/j.livsci.2015.05.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|
7
|
Van Amburgh ME, Collao-Saenz EA, Higgs RJ, Ross DA, Recktenwald EB, Raffrenato E, Chase LE, Overton TR, Mills JK, Foskolos A. The Cornell Net Carbohydrate and Protein System: Updates to the model and evaluation of version 6.5. J Dairy Sci 2015; 98:6361-80. [PMID: 26142847 DOI: 10.3168/jds.2015-9378] [Citation(s) in RCA: 172] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2015] [Accepted: 05/15/2015] [Indexed: 11/19/2022]
Abstract
New laboratory and animal sampling methods and data have been generated over the last 10 yr that had the potential to improve the predictions for energy, protein, and AA supply and requirements in the Cornell Net Carbohydrate and Protein System (CNCPS). The objectives of this study were to describe updates to the CNCPS and evaluate model performance against both literature and on-farm data. The changes to the feed library were significant and are reported in a separate manuscript. Degradation rates of protein and carbohydrate fractions were adjusted according to new fractionation schemes, and corresponding changes to equations used to calculate rumen outflows and postrumen digestion were presented. In response to the feed-library changes and an increased supply of essential AA because of updated contents of AA, a combined efficiency of use was adopted in place of separate calculations for maintenance and lactation to better represent the biology of the cow. Four different data sets were developed to evaluate Lys and Met requirements, rumen N balance, and milk yield predictions. In total 99 peer-reviewed studies with 389 treatments and 15 regional farms with 50 different diets were included. The broken-line model with plateau was used to identify the concentration of Lys and Met that maximizes milk protein yield and content. Results suggested concentrations of 7.00 and 2.60% of metabolizable protein (MP) for Lys and Met, respectively, for maximal protein yield and 6.77 and 2.85% of MP for Lys and Met, respectively, for maximal protein content. Updated AA concentrations were numerically higher for Lys and 11 to 18% higher for Met compared with CNCPS v6.0, and this is attributed to the increased content of Met and Lys in feeds that were previously incorrectly analyzed and described. The prediction of postruminal flows of N and milk yield were evaluated using the correlation coefficient from the BLUP (R(2)BLUP) procedure or model predictions (R(2)MDP) and the concordance correlation coefficient. The accuracy and precision of rumen-degradable N and undegradable N and bacterial N flows were improved with reduced bias. The CNCPS v6.5 predicted accurate and precise milk yield according to the first-limiting nutrient (MP or metabolizable energy) with a R(2)BLUP=0.97, R(2)MDP=0.78, and concordance correlation coefficient=0.83. Furthermore, MP-allowable milk was predicted with greater precision than metabolizable energy-allowable milk (R(2)MDP=0.82 and 0.76, respectively, for MP and metabolizable energy). Results suggest a significant improvement of the model, especially under conditions of MP limitation.
Collapse
Affiliation(s)
- M E Van Amburgh
- Department of Animal Science, Cornell University, Ithaca, NY 14850.
| | - E A Collao-Saenz
- Department of Animal Science, Federal University of Goiás, Jataí, Brazil 75800-970
| | - R J Higgs
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - D A Ross
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - E B Recktenwald
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - E Raffrenato
- Department of Animal Sciences, Stellenbosch University, Stellenbosch, South Africa 7600
| | - L E Chase
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - T R Overton
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| | - J K Mills
- Elanco Animal Health, Canastota, NY 13032
| | - A Foskolos
- Department of Animal Science, Cornell University, Ithaca, NY 14850
| |
Collapse
|
8
|
van der Leek ML. Beyond traditional dairy veterinary services: 'It's not just about the cows!'. J S Afr Vet Assoc 2015; 86:e1-e10. [PMID: 26244586 PMCID: PMC6138145 DOI: 10.4102/jsava.v86i1.1221] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Accepted: 02/16/2015] [Indexed: 11/04/2022] Open
Abstract
It remains a challenge for the role of the dairy veterinarian to move beyond that traditionally held. In larger herds with a high reproductive workload, we are at great risk of becoming specialist technicians. Instead we seek greater involvement, to deliver comprehensive services and to be recognised for them, personally and financially. Given the frequency of our visits, knowledge and analytical skills we are in a unique position to provide inputs that complement advice given by other consultants. Failure to do so has economic consequences for both veterinarian and dairyman. The opportunity for and value of inputs will differ for every client, and we need to remain cognizant of their motivation. This review article shares perspectives, opportunities and tools that might enable moving beyond the traditional role. It starts with a review of available research describing the dynamic between dairyman and veterinarian and how this might impact an animal health production management programme. A description of the experiences of others follows, interspersed by the personal experiences of the author, working with large total mixed ration-fed herds in the United States of America. The following attributes and roles can be associated with a significant economic impact: gatekeeper; conduit; executor; verifier; monitor; facilitator and mediator; trainer, motivator and coach; applied nutritionist; technologist; champion of animal welfare, food safety and judicious antibiotic use; and confidant. Each is elucidated and described in context, revealing a need for continuing education. The nature of the relationship between veterinarian and client will determine the opportunity for and value of each. The veterinarian is in a unique position to become an integral part of the management team and to be fairly compensated as such. The onus rests on the veterinarian to broaden his/her knowledge and skills and to demonstrate their value.
Collapse
|
9
|
Dong R, Zhao G. Relationship between the Methane Production and the CNCPS Carbohydrate Fractions of Rations with Various Concentrate/roughage Ratios Evaluated Using In vitro Incubation Technique. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2014; 26:1708-16. [PMID: 25049761 PMCID: PMC4092889 DOI: 10.5713/ajas.2013.13245] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2013] [Revised: 08/06/2013] [Accepted: 07/02/2013] [Indexed: 11/30/2022]
Abstract
The objective of the trial was to study the relationship between the methane (CH4) production and the Cornell Net Carbohydrate and Protein System (CNCPS) carbohydrate fractions of feeds for cattle and the suitability of CNCPS carbohydrate fractions as the dietary variables in modeling the CH4 production in rumen fermentation. Forty-five rations for cattle with the concentrate/roughage ratios of 10:90, 20:80, 30:70, 40:60, and 50:50 were formulated as feed samples. The Menke and Steingass’s gas test was used for the measurement of CH4 production. The feed samples were incubated for 48 h and the CH4 production was analyzed using gas chromatography. Statistical analysis indicated that the CH4 production (mL) was closely correlated with the CNCPS carbohydrate fractions (g), i.e. CA (sugars); CB1 (starch and pectin); CB2 (available cell wall) in a multiple linear pattern: CH4 = (89.16±14.93) CA+ (124.10±13.90) CB1+(30.58±11.72) CB2+(3.28±7.19), R2 = 0.81, p<0.0001, n = 45. Validation of the model using 10 rations indicated that the CH4 production of the rations for cattle could accurately be predicted based on the CNCPS carbohydrate fractions. The trial indicated that the CNCPS carbohydrate fractions CA, CB1 and CB2 were suitable dietary variables for predicting the CH4 production in rumen fermentation in vitro.
Collapse
Affiliation(s)
- Ruilan Dong
- College of Animal Science and Technology, China Agricultural University, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Guangyong Zhao
- College of Animal Science and Technology, China Agricultural University, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| |
Collapse
|
10
|
Jardim JG, Vieira RAM, Fernandes AM, Pavesi Araujo R, Siqueira Glória L, Moreno Rohem Júnior N, Silva Rocha N, Lima Correa Abreu M. Application of a nonlinear optimization tool to balance diets with constant metabolizability. Livest Sci 2013. [DOI: 10.1016/j.livsci.2013.09.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
11
|
Létourneau-Montminy MP, Narcy A, Lescoat P, Magnin M, Bernier JF, Sauvant D, Jondreville C, Pomar C. Modeling the fate of dietary phosphorus in the digestive tract of growing pigs1. J Anim Sci 2011; 89:3596-611. [DOI: 10.2527/jas.2010-3397] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
12
|
Alemu AW, Dijkstra J, Bannink A, France J, Kebreab E. Rumen stoichiometric models and their contribution and challenges in predicting enteric methane production. Anim Feed Sci Technol 2011. [DOI: 10.1016/j.anifeedsci.2011.04.054] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
13
|
In vivo production and molar percentages of volatile fatty acids in the rumen: a quantitative review by an empirical approach. Animal 2011; 5:403-14. [DOI: 10.1017/s1751731110002016] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
|
14
|
Lettat A, Nozière P, Silberberg M, Morgavi DP, Berger C, Martin C. Experimental feed induction of ruminal lactic, propionic, or butyric acidosis in sheep1. J Anim Sci 2010; 88:3041-6. [DOI: 10.2527/jas.2010-2926] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
15
|
Place S, Mitloehner F. Invited review: Contemporary environmental issues: A review of the dairy industry's role in climate change and air quality and the potential of mitigation through improved production efficiency. J Dairy Sci 2010; 93:3407-16. [DOI: 10.3168/jds.2009-2719] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2009] [Accepted: 04/01/2010] [Indexed: 11/19/2022]
|
16
|
Meta-analysis of phosphorus utilisation by broilers receiving corn-soyabean meal diets: influence of dietary calcium and microbial phytase. Animal 2010; 4:1844-53. [DOI: 10.1017/s1751731110001060] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
|
17
|
Carbohydrate quantitative digestion and absorption in ruminants: from feed starch and fibre to nutrients available for tissues. Animal 2010; 4:1057-74. [DOI: 10.1017/s1751731110000844] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
|
18
|
Growth heterogeneity in rearing sea bass (Dicentrarchus labrax): test of hypothesis with an iterative energetic model. Animal 2009; 3:1299-307. [DOI: 10.1017/s1751731109004595] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
|
19
|
Chilibroste P, Dijkstra J, Robinson P, Tamminga S. A simulation model “CTR Dairy” to predict the supply of nutrients in dairy cows managed under discontinuous feeding patterns. Anim Feed Sci Technol 2008. [DOI: 10.1016/j.anifeedsci.2007.05.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
|
20
|
|
21
|
Bannink A, France J, Lopez S, Gerrits W, Kebreab E, Tamminga S, Dijkstra J. Modelling the implications of feeding strategy on rumen fermentation and functioning of the rumen wall. Anim Feed Sci Technol 2008. [DOI: 10.1016/j.anifeedsci.2007.05.002] [Citation(s) in RCA: 101] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
22
|
Johnson HA, Maas JA, Calvert CC, Baldwin RL. Use of computer simulation to teach a systems approach to metabolism. J Anim Sci 2008; 86:483-99. [PMID: 17940156 DOI: 10.2527/jas.2007-0393] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- H A Johnson
- Animal Science Department, University of California, Davis, CA 95616, USA.
| | | | | | | |
Collapse
|
23
|
A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants. Anim Feed Sci Technol 2007. [DOI: 10.1016/j.anifeedsci.2006.08.025] [Citation(s) in RCA: 67] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
24
|
Firkins JL, Yu Z, Morrison M. Ruminal Nitrogen Metabolism: Perspectives for Integration of Microbiology and Nutrition for Dairy. J Dairy Sci 2007; 90 Suppl 1:E1-16. [PMID: 17517749 DOI: 10.3168/jds.2006-518] [Citation(s) in RCA: 164] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Our objectives are to integrate current knowledge with a future perspective regarding how metagenomics can be used to integrate rumen microbiology and nutrition. Ruminal NH3-N concentration is a crude predictor of efficiency of dietary N conversion into microbial N, but as this concentration decreases below approximately 5 mg/dL (the value most often suggested to be the requirement for optimal microbial protein synthesis), blood urea N transfer into the rumen provides an increasing buffer against excessively low NH3-N concentrations, and the supply of amino N might become increasingly important to improve microbial function in dairy diets. Defaunation typically decreases NH3-N concentration, which should increase the efficiency of blood urea N and protein-derived NH3-N conversion into microbial protein in the rumen. Thus, we explain why more emphasis should be given toward characterization of protozoal interactions with proteolytic and deaminating bacterial populations. In contrast with research evaluating effects of protozoa on N metabolism, which has primarily been done with sheep and cattle with low dry matter intake, dairy cattle have greater intakes of readily available carbohydrate combined with increased ruminal passage rates. We argue that these conditions decrease protozoal biomass relative to bacterial biomass and increase the efficiency of protozoal growth, thus reducing the negative effects of bacterial predation compared with the beneficial effects that protozoa have on stabilizing the entire microbial ecosystem. A better understanding of mechanistic processes altering the production and uptake of amino N will help us to improve the overall conversion of dietary N into microbial protein and provide key information needed to further improve mechanistic models describing rumen function and evaluating dietary conditions that influence the efficiency of conversion of dietary N into milk protein.
Collapse
Affiliation(s)
- J L Firkins
- The MAPLE Research Initiative, Department of Animal Sciences, The Ohio State University, Columbus 43210, USA.
| | | | | |
Collapse
|
25
|
|
26
|
Lanzas C, Tedeschi LO, Seo S, Fox DG. Evaluation of Protein Fractionation Systems Used in Formulating Rations for Dairy Cattle. J Dairy Sci 2007; 90:507-21. [PMID: 17183120 DOI: 10.3168/jds.s0022-0302(07)72653-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Production efficiency decreases when diets are not properly balanced for protein. Sensitivity analyses of the protein fractionation schemes used by the National Research Council Nutrient Requirement of Dairy Cattle (NRC) and the Cornell Net Carbohydrate and Protein System (CNCPS) were conducted to assess the influence of the uncertainty in feed inputs and the assumptions underlying the CNCPS scheme on metabolizable protein and amino acid predictions. Monte Carlo techniques were used. Two lactating dairy cow diets with low and high protein content were developed for the analysis. A feed database provided by a commercial laboratory and published sources were used to obtain the distributions and correlations of the input variables. Spreadsheet versions of the models were used. Both models behaved similarly when variation in protein fractionation was taken into account. The maximal impact of variation on metabolizable protein from rumen-undegradable protein (RUP) was 2.5 (CNCPS) and 3.0 (NRC) kg/d of allowable milk for the low protein diet, and 3.5 (CNCPS) and 3.9 (NRC) kg/d of allowable milk for the high protein diet. The RUP flows were sensitive to ruminal degradation rates of the B protein fraction in NRC and of the B2 protein fraction in the CNCPS for protein supplements, energy concentrates, and forages. Absorbed Met and Lys flows were also sensitive to intestinal digestibility of RUP, and the CNCPS model was sensitive to acid detergent insoluble crude protein and its assumption of complete unavailability. Neither the intestinal digestibility of the RUP nor the protein degradation rates are routinely measured. Approaches need to be developed to account for their variability. Research is needed to provide better methods for measuring pool sizes and ruminal digestion rates for protein fractionation systems.
Collapse
Affiliation(s)
- C Lanzas
- Department of Animal Science, Cornell University, Ithaca, NY 14853, USA.
| | | | | | | |
Collapse
|
27
|
|