Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

The evolution and evaluation of dairy cattle models for predicting milk production: an agricultural model intercomparison and improvement project (AgMIP) for livestock

Luis O. Tedeschi A E , Luigi F. L. Cavalcanti B , Mozart A. Fonseca A , Mario Herrero C and Phillip K. Thornton D
+ Author Affiliations
- Author Affiliations

A Department of Animal Science, Texas A&M University, College Station, TX 77843-2471, USA.

B Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270, Brazil.

C Commonwealth Scientific and Industrial Research Organisation, St Lucia, Qld 4067, Australia.

D CGIAR Research Program on Climate Change, Agriculture and Food Security, International Livestock Research Institute, 00100 Nairobi, Kenya.

E Corresponding author. Email: luis.tedeschi@tamu.edu

Animal Production Science 54(12) 2052-2067 https://doi.org/10.1071/AN14620
Submitted: 3 June 2014  Accepted: 25 July 2014   Published: 15 October 2014

Abstract

The contemporary concern about anthropogenic release of greenhouse gas (GHG) into the environment and the contribution of livestock to this phenomenon have sparked animal scientists’ interest in predicting methane (CH4) emissions by ruminants. We contend that improving the adequacy of mathematical nutrition model estimates of production of meat and milk is a sine qua non condition to reliably determine ruminants’ worldwide contribution to GHG. Focusing on milk production, we address six basic nutrition models or feeding standards (mostly empirical systems) and five complex nutrition models (mostly mechanistic systems), describe their key characteristics, and highlight their similarities and differences. We also present derivative systems. We compiled a database of milk production information from 37 published studies from six regions of the world, totalling 173 data points: 19 for Africa, 45 for Asia, 16 for Europe, 12 for Latin America, 44 for North America and 37 for Oceania. Four models were used to predict milk production in lactating dairy cows, and the adequacy of their predictions was measured against the observed milk production from our database. Even though these mathematical nutrition models shared similar assumptions and calculations, they have different conceptual and structural foundations inherent to their intended purposes. A direct comparison among these models was further complicated by the different models requiring unique inputs that are very often not available, and the low reliability of the inputs prevents an unbiased assessment of the model predictions. Very few studies have collected the necessary information to run more mechanistic systems, and users have to rely on standard information to populate many model inputs. Study effect was a critical source of variation that limited our ability to conclusively evaluate the models’ applicability under different scenarios of production around the world. Only after study variation was removed from the database did the adequacy of the model predictions of milk production improved, but deficiencies still existed. On the basis of these analyses, we conclude that not all models were suitable for predicting milk production and that simpler systems might be more resilient to variations in studies and production conditions around the world. Improving the predictability of milk production by mathematical nutrition models is a prerequisite to further development of systems that can effectively and correctly estimate the contribution of ruminants to GHG emissions and their true share of the global warming event.

Additional keywords: adequacy, comparison, modelling, nutrition, simulation, testing.


References

Abdullah M, Young JW, Tyler HD, Mohiuddin G (2000) Effects of feeding high forage diets and supplemental fat on feed intake and lactation performance in dairy cow. Asian-Australasian Journal of Animal Sciences 13, 457–463.

Agnew RE, Yan T (2000) Impact of recent research on energy feeding systems for dairy cattle. Livestock Production Science 66, 197–215.
Impact of recent research on energy feeding systems for dairy cattle.CrossRef |

Agricultural and Food Research Council (1993) ‘Energy and protein requirements of ruminants.’ Agricultural and Food Research Council. (CAB International: Wallingford, UK)

Agricultural Research Council (1965) ‘The nutrient requirements of farm livestock. No. 2, ruminants.’ (H.M. Stationery Office: London)

Agricultural Research Council (1980) ‘The nutrient requirements of ruminant livestock.’ Agricultural Research Council. (The Gresham Press: London)

Alderman G (2001) A critique of the Cornell net carbohydrate and protein system with emphasis on dairy cattle. 1. The rumen model. Journal of Animal and Feed Sciences 10, 1–24.

Alderman G, France J, Kebreab E (2001a) A critique of the Cornell net carbohydrate and protein system with emphasis on dairy cattle. 2. The post-rumen digestion model. Journal of Animal and Feed Sciences 10, 203–221.

Alderman G, France J, Kebreab E (2001b) A critique of the Cornell net carbohydrate and protein system with emphasis on dairy cattle. 3. The requirements model. Journal of Animal and Feed Sciences 10, 361–383.

Allen MS, Mertens DR (1988) Evaluating constraints on fiber digestion by rumen microbes. The Journal of Nutrition 118, 261–270.

Alvarez HJ, Santini FJ, Rearte DH, Elizalde JC (2001) Milk production and ruminal digestion in lactating dairy cows grazing temperate pastures and supplemented with dry cracked corn or high moisture corn. Animal Feed Science and Technology 91, 183–195.
Milk production and ruminal digestion in lactating dairy cows grazing temperate pastures and supplemented with dry cracked corn or high moisture corn.CrossRef |

Arnold RN, Bennett GL (1991a) Evaluation of four simulation models of cattle growth and body composition: Part I – Comparison and characterization of the models. Agricultural Systems 35, 401–432.
Evaluation of four simulation models of cattle growth and body composition: Part I – Comparison and characterization of the models.CrossRef |

Arnold RN, Bennett GL (1991b) Evaluation of four simulation models of cattle growth and body composition: Part II – simulation and comparison with experimental growth data. Agricultural Systems 36, 17–41.
Evaluation of four simulation models of cattle growth and body composition: Part II – simulation and comparison with experimental growth data.CrossRef |

Assis AJ, Campos JMS, Filho SCV, Queiroz AC, Lana RP, Euclydes RF, Neto JM, Magalhaes ALR, Mendonca SS (2004) Polpa citrica em dietas de vacas em lactação. 1. Consumo de nutrientes, produção e composição do leite. Revista Brasileira de Zootecnia 33, 242–250.
Polpa citrica em dietas de vacas em lactação. 1. Consumo de nutrientes, produção e composição do leite.CrossRef |

Auldist DE, Atkinson KL, Dellow DW, Silvapulle MJ, McDowell GH (1999) Utilisation of white clover silage fed alone or with maize silage by lactating dairy cows. Australian Journal of Experimental Agriculture 39, 237–246.
Utilisation of white clover silage fed alone or with maize silage by lactating dairy cows.CrossRef |

Axelsson J (1949) The amount of produced methane energy in the European metabolic experiments with adult cattle. The Annals of the Royal Agricultural College of Sweden 16, 404–419.

Baldwin RL (1995) ‘Modeling ruminant digestion and metabolism.’ (Chapman & Hall: New York)

Baldwin RL, Koong LJ, Ulyatt MJ (1977) A dynamic model of ruminant digestion for evaluation of factors affecting nutritive value. Agricultural Systems 2, 255–288.
A dynamic model of ruminant digestion for evaluation of factors affecting nutritive value.CrossRef |

Baldwin RL, Smith NE, Taylor J, Sharp M (1980) Manipulating metabolic parameters to improve growth rate and milk secretion. Journal of Animal Science 51, 1416–1428.

Baldwin RL, Thornley JHM, Beever DE (1987) Metabolism of the lactating cow. II. Digestive elements of a mechanistic model. The Journal of Dairy Research 54, 107–131.
Metabolism of the lactating cow. II. Digestive elements of a mechanistic model.CrossRef | 1:CAS:528:DyaL2sXkvFWhsg%3D%3D&md5=8442cb40efc705f11b46c7f5dcf45b46CAS | 3819150PubMed |

Baldwin RL, France J, Beever DE, Gill M, Thornley JHM (1987a) Metabolism of the lactating cow. III. Properties of mechanistic models suitable for evaluation of energetic relationships and factors involved in the partition of nutrients. The Journal of Dairy Research 54, 133–145.
Metabolism of the lactating cow. III. Properties of mechanistic models suitable for evaluation of energetic relationships and factors involved in the partition of nutrients.CrossRef | 1:CAS:528:DyaL2sXkvFWhsw%3D%3D&md5=53889228d65f8fab5fc050ac3e0b5f6fCAS | 3819152PubMed |

Baldwin RL, France J, Gill M (1987b) Metabolism of the lactating cow. I. Animal elements of a mechanistic model. The Journal of Dairy Research 54, 77–105.
Metabolism of the lactating cow. I. Animal elements of a mechanistic model.CrossRef | 1:CAS:528:DyaL2sXkslKitA%3D%3D&md5=43d67267723bd391d3469df7c55f71aaCAS | 3819156PubMed |

Bannink A, Visser H, Van Vuuren AM (1997) Comparison and evaluation of mechanistic rumen models. The British Journal of Nutrition 78, 563–581.
Comparison and evaluation of mechanistic rumen models.CrossRef | 1:CAS:528:DyaK2sXmslens7s%3D&md5=ca6d102746e166d4e37cfe9387fa58a4CAS | 9389884PubMed |

Bannink A, Kogut J, Dijkstra J, France J, Kebreab E, Van Vuuren AM, Tamminga S (2006) Estimation of the stoichiometry of volatile fatty acid production in the rumen of lactating cows. Journal of Theoretical Biology 238, 36–51.
Estimation of the stoichiometry of volatile fatty acid production in the rumen of lactating cows.CrossRef | 1:CAS:528:DC%2BD2MXht1Oms7jN&md5=45dade30c3d863e7c6b284f978bb5874CAS | 16111711PubMed |

Bannink A, France J, Lopez S, Gerrits WJJ, Kebreab E, Tamminga S, Dijkstra J (2008) Modelling the implications of feeding strategy on rumen fermentation and functioning of the rumen wall. Animal Feed Science and Technology 143, 3–26.
Modelling the implications of feeding strategy on rumen fermentation and functioning of the rumen wall.CrossRef |

Bannink A, van Schijndel MW, Dijkstra J (2011) A model of enteric fermentation in dairy cows to estimate methane emission for the Dutch national inventory report using the IPCC Tier 3 approach. Animal Feed Science and Technology 166–167, 603–618.
A model of enteric fermentation in dairy cows to estimate methane emission for the Dutch national inventory report using the IPCC Tier 3 approach.CrossRef |

Bargo F, Rearte DH, Santini FJ, Muller LD (2001) Ruminal digestion by dairy cows grazing winter oats pasture supplemented with different levels and sources of protein. Journal of Dairy Science 84, 2260–2272.
Ruminal digestion by dairy cows grazing winter oats pasture supplemented with different levels and sources of protein.CrossRef | 1:CAS:528:DC%2BD3MXnvV2ksLg%3D&md5=30fa7e2e9d8e3baef07848b6714f390bCAS | 11699458PubMed |

Beever DE, Black JL, Faichney GJ (1981) Simulation of the effects of rumen function of the flow of nutrients from the stomach of sheep: Part 2. Assessment of computer predictions. Agricultural Systems 6, 221–241.
Simulation of the effects of rumen function of the flow of nutrients from the stomach of sheep: Part 2. Assessment of computer predictions.CrossRef |

Benchaar C, Rivest J, Pomar C, Chiquette J (1998) Prediction of methane production from dairy cows using existing mechanistic models and regression equations. Journal of Animal Science 76, 617–627.

Beyer M, Chudy A, Hoffman HL, Jentsch W, Laube W, Nehring K, Schiermann R (2003) ‘Rostock feed evaluation system; reference numbers of feed value and requirement of the base of net energy.’ (Gottlob Volkhardtsche Druckerei: Amorbach, Germany)

Bickel H, Landis J (1978) Feed evaluation for ruminants. III. Proposed application of the new system of energy evaluation in Switzerland. Livestock Production Science 5, 367–372.
Feed evaluation for ruminants. III. Proposed application of the new system of energy evaluation in Switzerland.CrossRef |

Black JL, Beever DE, Faichney GJ, Howarth BR, Graham NM (1981) Simulation of the effects of rumen function on the flow of nutrients from the stomach of sheep: Part 1. Description of a computer program. Agricultural Systems 6, 195–219.
Simulation of the effects of rumen function on the flow of nutrients from the stomach of sheep: Part 1. Description of a computer program.CrossRef |

Blaxter KL (1962) ‘The energy metabolism of ruminants.’ (Hutchinson: London)

Blaxter KL, Clapperton JL (1965) Prediction of the amount of methane produced by ruminants. The British Journal of Nutrition 19, 511–522.
Prediction of the amount of methane produced by ruminants.CrossRef | 1:CAS:528:DyaF28XitFKktg%3D%3D&md5=cce47ad397fedf3bced4f69441c525dfCAS | 5852118PubMed |

Boer HMT, Stötzel C, Röblitz S, Deuflhard P, Veerkamp RF, Woelders H (2011) A simple mathematical model of the bovine estrous cycle: follicle development and endocrine interactions. Journal of Theoretical Biology 278, 20–31.
A simple mathematical model of the bovine estrous cycle: follicle development and endocrine interactions.CrossRef | 1:STN:280:DC%2BC3Mvjs1amuw%3D%3D&md5=57c3cf5d6d3ef481cb6036df09b03a15CAS |

Boston RC, Fox DG, Sniffen CJ, Janczewski R, Munsen R, Chalupa W (2000) The conversion of a scientific model describing dairy cow nutrition and production to an industry tool: the CPM Dairy project. In ‘Modelling nutrient utilization in farm animals’. (Eds JP McNamara, J France, D Beever) pp. 361–377. (CABI Publishing: Oxford, UK)

Cannas A, Tedeschi LO, Fox DG, Pell AN, Van Soest PJ (2004) A mechanistic model for predicting the nutrient requirements and feed biological values for sheep. Journal of Animal Science 82, 149–169.

Chalupa W, Boston R (2003) Development of the CNCPS and CPM models: the Sniffen affect. In ‘Proceedings of Cornell nutrition conference for feed manufacturers’. Syracuse, NY. pp. 15–24. (New York State College of Agriculture & Life Sciences, Cornell University: Ithaca, NY)

Chudy A (2006) Rostock feed evaluation system – an example of the transformation of energy and nutrient utilization models to practical application. In ‘Nutrient digestion and utilization in farm animals: modelling approaches’. (Eds E Kebreab, J Dijkstra, A Bannink, WJJ Gerrits, J France) pp. 366–382. (CABI Publishing: Cambridge, MA)

Colmenero JJO, Broderick GA (2006) Effect of dietary crude protein concentration on milk production and nitrogen utilization in lactating dairy cows. Journal of Dairy Science 89, 1704–1712.
Effect of dietary crude protein concentration on milk production and nitrogen utilization in lactating dairy cows.CrossRef | 1:CAS:528:DC%2BD28XktVOhtrs%3D&md5=49e2c66de630f640c9239b4cad03a541CAS |

Commonwealth Scientific and Industrial Research Organization (1990) ‘Feeding standards for Australian livestock. Ruminants.’ (CSIRO Publishing: Melbourne)

Commonwealth Scientific and Industrial Research Organization (2007) ‘Nutrient requirements of domesticated ruminants.’ (CSIRO Publishing: Melbourne)

Conrad HR, Weiss WP, Odwongo WO, Shockey WL (1984) Estimating net energy lactation from components of cell solubles and cell walls. Journal of Dairy Science 67, 427–436.
Estimating net energy lactation from components of cell solubles and cell walls.CrossRef |

Crout NMJ, Tarsitano D, Wood AT (2009) Is my model too complex? Evaluating model formulation using model reduction. Environmental Modelling & Software 24, 1–7.
Is my model too complex? Evaluating model formulation using model reduction.CrossRef |

Danes MA, Chagas LJ, Pedroso AM, Santos FA (2013) Effect of protein supplementation on milk production and metabolism of dairy cows grazing tropical grass. Journal of Dairy Science 96, 407–419.
Effect of protein supplementation on milk production and metabolism of dairy cows grazing tropical grass.CrossRef | 1:CAS:528:DC%2BC38XhvV2rsbzF&md5=a9ed534b4f2a9eff3c8d790bb3815464CAS | 23127909PubMed |

Danfær A (1990) A dynamic model of nutrient digestion and metabolism in lactating dairy cows. PhD Dissertation Thesis, National Institute of Animal Science, Foulum, Denmark.

Danfær A, Huhtanen P, Udén P, Sveinbjörnsson J, Volden H (2006a) The Nordic Dairy Cow Model, Karoline – description. In ‘Nutrient digestion and utilization in farm animals: modelling approaches’. (Eds E Kebreab, J Dijkstra, A Bannink, WJJ Gerrits, J France) pp. 383–406. (CABI Publishing: Cambridge, MA)

Danfær A, Huhtanen P, Udén P, Sveinbjörnsson J, Volden H (2006b) The Nordic Dairy Cow Model, Karoline – evaluation. In ‘Nutrient digestion and utilization in farm animals: modelling approaches’. (Eds E Kebreab, J Dijkstra, A Bannink, WJJ Gerrits, J France) pp. 407–415. (CABI Publishing: Cambridge, MA)

Dey A, De PS (2014) Influence of condensed tannins from Ficus bengalensis leaves on feed utilization, milk production and antioxidant status of crossbred cows. Asian–Australasian Journal of Animal Sciences 27, 342–348.
Influence of condensed tannins from Ficus bengalensis leaves on feed utilization, milk production and antioxidant status of crossbred cows.CrossRef | 1:CAS:528:DC%2BC2cXns1Wit74%3D&md5=5b7344322b5b95a1160e5c1323e7e538CAS | 25049960PubMed |

Dijkstra J (1993) Mathematical modelling and integration of rumen fermentation processes. Dissertation Thesis, University of Wageningen, The Netherlands.

Dijkstra J (1994) Simulation of the dynamics of protozoa in the rumen. The British Journal of Nutrition 72, 679–699.
Simulation of the dynamics of protozoa in the rumen.CrossRef | 1:CAS:528:DyaK2MXis1enurc%3D&md5=a72e1162fde5aba1d018430393448d14CAS | 7826992PubMed |

Dijkstra J, Tamminga S (1995) Simulation of the effects of diet on the contribution of rumen protozoa to degradation of fibre in the rumen. The British Journal of Nutrition 74, 617–634.
Simulation of the effects of diet on the contribution of rumen protozoa to degradation of fibre in the rumen.CrossRef | 1:CAS:528:DyaK28Xht1equg%3D%3D&md5=2f23e73b8cdecb9178c4ed06c4e4d031CAS | 8541269PubMed |

Dijkstra J, Neal HSSC, Beever DE, France J (1992) Simulation of nutrient digestion, absorption and outflow in the rumen: model description. The Journal of Nutrition 122, 2239–2256.

Dijkstra J, Kebreab E, Bannink A, Crompton LA, López S, Abrahamse PA, Chilibroste P, Mills JAN, France J (2008) Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets. Animal Feed Science and Technology 143, 203–219.
Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets.CrossRef |

Donnelly JR, Moore AD, Freer M (1997) GRAZPLAN: decision support systems for Australian grazing enterprises-I. Overview of the GRAZPLAN project, and a description of the MetAccess and LambAlive DSS. Agricultural Systems 54, 57–76.
GRAZPLAN: decision support systems for Australian grazing enterprises-I. Overview of the GRAZPLAN project, and a description of the MetAccess and LambAlive DSS.CrossRef |

Donnelly JR, Freer M, Salmon L, Moore AD, Simpson RJ, Bolger TP (2002) Evolution of the GRAZPLAN decision support tools and adoption by the grazing industry in temperate Australia. Agricultural Systems 74, 115–139.
Evolution of the GRAZPLAN decision support tools and adoption by the grazing industry in temperate Australia.CrossRef |

Ellis JL, Kebreab E, Odongo NE, McBride BW, Okine EK, France J (2007) Prediction of methane production from dairy and beef cattle. Journal of Dairy Science 90, 3456–3466.
Prediction of methane production from dairy and beef cattle.CrossRef | 1:CAS:528:DC%2BD2sXntlCksLY%3D&md5=33ae06dfa51110ac12c0cbaac2378c1eCAS | 17582129PubMed |

Ellis JL, Kebreab E, Odongo NE, Beauchemin K, McGinn S, Nkrumah JD, Moore SS, Christopherson R, Murdoch GK, McBride BW, Okine EK, France J (2009) Modeling methane production from beef cattle using linear and nonlinear approaches. Journal of Animal Science 87, 1334–1345.
Modeling methane production from beef cattle using linear and nonlinear approaches.CrossRef | 1:CAS:528:DC%2BD1MXjsFKis7o%3D&md5=8fdce6baf99a273fea52496c0af60d68CAS | 19098240PubMed |

Erasmus LJ, Botha PM, Kistner A (1992) Effect of yeast culture supplement on production, rumen fermentation, and duodenal nitrogen flow in dairy cows. Journal of Dairy Science 75, 3056–3065.
Effect of yeast culture supplement on production, rumen fermentation, and duodenal nitrogen flow in dairy cows.CrossRef | 1:CAS:528:DyaK3sXnvF2kug%3D%3D&md5=60d0483b423c889cb88f40386c34a868CAS | 1460136PubMed |

Erasmus LJ, Botha PM, Meissner HH (1994) Effect of protein source on ruminal fermentation and passage of amino acids to the small intestine of lactating cows. Journal of Dairy Science 77, 3655–3665.
Effect of protein source on ruminal fermentation and passage of amino acids to the small intestine of lactating cows.CrossRef | 1:CAS:528:DyaK2MXivVyhsb4%3D&md5=fe2395a6c499d6775cf32f0e45996708CAS | 7699144PubMed |

Erasmus LJ, Smith I, Muller A, O’Hagan D (1999) Effects of lasalocid on performance of lactating dairy cows. Journal of Dairy Science 82, 1817–1823.
Effects of lasalocid on performance of lactating dairy cows.CrossRef | 1:CAS:528:DyaK1MXlsVyku74%3D&md5=4e6f2c5d48b534b15112ba475066e428CAS | 10480108PubMed |

Erasmus LJ, Venter R, Coertze RJ (2004) The effect of a liquid rumen protected lysine on the productivity of Holstein cows. South African Journal of Animal Science 34, 89–91.

Erasmus LJ, Bester Z, Coertze RJ (2013) Milk composition as technique to evaluate the relative bioavailability of a liquid rumen protected methionine source. South African Journal of Animal Science 43, S86–S92.

Fatahnia F, Nikkhah A, Zamiri MJ, Kahrizi D (2008) Effect of dietary fish oil and soybean oil on milk production and composition of holstein cows in early lactation. Asian-Australasian Journal of Animal Sciences 21, 386–391.
Effect of dietary fish oil and soybean oil on milk production and composition of holstein cows in early lactation.CrossRef | 1:CAS:528:DC%2BD1cXmtFSmsbs%3D&md5=d75018d4b96812022ea4ae5ac9b259e6CAS |

Fox DG, Black JR (1984) A system for predicting body composition and performance of growing cattle. Journal of Animal Science 58, 725–739.

Fox DG, Sniffen CJ, O’Connor JD, Russell JB, Van Soest PJ (1992) A net carbohydrate and protein system for evaluating cattle diets: III. Cattle requirements and diet adequacy. Journal of Animal Science 70, 3578–3596.

Fox DG, Tylutki TP, Tedeschi LO, Van Amburgh ME, Chase LE, Pell AN, Overton TR, Russell JB (2003) ‘The net carbohydrate and protein system for evaluating herd nutrition and nutrient excretion: model documentation.’ Bulletin 213. (Animal Science Department, Cornell University: Ithaca, NY)

Fox DG, Tedeschi LO, Tylutki TP, Russell JB, Van Amburgh ME, Chase LE, Pell AN, Overton TR (2004) The Cornell net carbohydrate and protein system model for evaluating herd nutrition and nutrient excretion. Animal Feed Science and Technology 112, 29–78.
The Cornell net carbohydrate and protein system model for evaluating herd nutrition and nutrient excretion.CrossRef | 1:CAS:528:DC%2BD2cXmvFymsQ%3D%3D&md5=25935ea755db8cd57530a9e85de2633aCAS |

France J (2013) Application of mathematical modelling in animal nutrition, physiology and energy balance. In ‘Proceedings of the 4th international symposium on energy and protein metabolism and nutrition, Sacramento, CA’. (Eds JW Oltjen, E Kebreab, H Lapierre) pp. 517–519. (Wageningen Academic Publishers)

France J, Thornley JHM, Beever DE (1982) A mathematical model of the rumen. The Journal of Agricultural Science 99, 343–353.
A mathematical model of the rumen.CrossRef | 1:CAS:528:DyaL3sXos1Omtg%3D%3D&md5=8f1027dd1c0f4d3fb016bd54dd8b54ecCAS |

France J, Thornley JHM, Baldwin RL, Crist KA (1992) On solving stiff equations with reference to simulating ruminant metabolism. Journal of Theoretical Biology 156, 525–539.
On solving stiff equations with reference to simulating ruminant metabolism.CrossRef |

France J, Theodorou MK, Lowman RS, Beever DE (2000) Feed evaluation for animal production. In ‘Feeding systems and feed evaluation models’. (Eds MK Theodorou, J France) pp. 1–9. (CABI Publishing: New York)

Freer M, Moore AD, Donnelly JR (1997) GRAZPLAN: decision support systems for Australian grazing enterprises-II. The animal biology model for feed intake, production and reproduction and the GrazFeed DSS. Agricultural Systems 54, 77–126.
GRAZPLAN: decision support systems for Australian grazing enterprises-II. The animal biology model for feed intake, production and reproduction and the GrazFeed DSS.CrossRef |

Garrett WN, Meyer JH, Lofgreen GP (1959) The comparative energy requirements of sheep and cattle for maintenance and gain. Journal of Animal Science 18, 528–547.

Gerber PJ, Hristov AN, Henderson B, Makkar H, Oh J, Lee C, Meinen R, Montes F, Ott T, Firkins J, Rotz A, Dell C, Adesogan AT, Yang WZ, Tricarico JM, Kebreab E, Waghorn G, Dijkstra J, Oosting S (2013) Technical options for the mitigation of direct methane and nitrous oxide emissions from livestock: a review. Animal 7, 220–234.
Technical options for the mitigation of direct methane and nitrous oxide emissions from livestock: a review.CrossRef | 23739465PubMed |

Gill M, Thornley JHM, Black JL, Oldham JD, Beever DE (1984) Simulation of the metabolism of absorbed energy-yielding nutrients in young sheep. The British Journal of Nutrition 52, 621–649.
Simulation of the metabolism of absorbed energy-yielding nutrients in young sheep.CrossRef | 1:CAS:528:DyaL2cXmtV2kt7w%3D&md5=319d3b4cd1efde6878995ebf5d462a79CAS | 6498153PubMed |

Gill M, Beever DE, France J (1989) Biochemical bases needed for the mathematical representation of whole animal metabolism. Nutrition Abstracts and Reviews 2, 181–200.

Grainger C, Williams R, Clarke T, Wright ADG, Eckard RJ (2010) Supplementation with whole cottonseed causes long-term reduction of methane emissions from lactating dairy cows offered a forage and cereal grain diet. Journal of Dairy Science 93, 2612–2619.
Supplementation with whole cottonseed causes long-term reduction of methane emissions from lactating dairy cows offered a forage and cereal grain diet.CrossRef | 1:CAS:528:DC%2BC3cXhtVahs7nP&md5=aed2b4982ed90d711eecfcc46eb466bbCAS | 20494170PubMed |

Greenwood JS, Auldist MJ, Marett LC, Hannah MC, Jacobs JL, Wales WJ (2013) Ruminal pH and whole-tract digestibility in dairy cows consuming fresh cut herbage plus concentrates and conserved forage fed either separately or as a partial mixed ration. Animal Production Science 54, in press.

Gregorini P, Beukes PC, Hanigan MD, Waghorn G, Muetzel S, McNamara JP (2013) Comparison of updates to the Molly cow model to predict methane production from dairy cows fed pasture. Journal of Dairy Science 96, 5046–5052.
Comparison of updates to the Molly cow model to predict methane production from dairy cows fed pasture.CrossRef | 1:CAS:528:DC%2BC3sXptV2ltbw%3D&md5=f433d9405dbdd8f95811d30665636164CAS | 23746585PubMed |

Hanigan MD, Bateman HG, Fadel JG, McNamara JP, Smith NE (2006) An ingredient-based input scheme for Molly. In ‘Nutrient digestion and utilization in farm animals: modelling approaches’. (Eds E Kebreab, J Dijkstra, A Bannink, WJJ Gerrits, J France) pp. 328–348. (CABI Publishing: Cambridge, MA)

Hanigan MD, Palliser CC, Gregorini P (2009) Altering the representation of hormones and adding consideration of gestational metabolism in a metabolic cow model reduced prediction errors. Journal of Dairy Science 92, 5043–5056.
Altering the representation of hormones and adding consideration of gestational metabolism in a metabolic cow model reduced prediction errors.CrossRef | 1:CAS:528:DC%2BD1MXhtF2qtrbO&md5=ab2d2bcaac40cfc611927b502a17afd3CAS | 19762823PubMed |

Hanigan MD, Appuhamy JADRN, Gregorini P (2013) Revised digestive parameter estimates for the Molly cow model. Journal of Dairy Science 96, 3867–3885.
Revised digestive parameter estimates for the Molly cow model.CrossRef | 1:CAS:528:DC%2BC3sXmtValsbY%3D&md5=0e68d4db759089e1dfaef4ebf67184c5CAS | 23587389PubMed |

Heard JW, Walker GP, Royle PJ, McIntosh GH, Doyle PT (2004) Effects of short-term supplementation with selenised yeast on milk production and composition of lactating cows. Australian Journal of Dairy Technology 59, 199–203.

Heard JW, Stockdale CR, Walker GP, Leddin CM, Dunshea FR, McIntosh GH, Shields PM, McKenna A, Young GP, Doyle PT (2007) Increasing selenium concentration in milk: effects of amount of selenium from yeast and cereal grain supplements. Journal of Dairy Science 90, 4117–4127.
Increasing selenium concentration in milk: effects of amount of selenium from yeast and cereal grain supplements.CrossRef | 1:CAS:528:DC%2BD2sXpslequro%3D&md5=4c331611dfaa923f7fd3ba92d14a8ba8CAS | 17699029PubMed |

Herrero M (1997) Modelling dairy grazing systems: an integrated approach. Dissertation, University of Edinburgh, Edinburgh, UK.

Herrero M, Havlík P, Valin H, Notenbaert A, Rufino MC, Thornton PK, Blümmel M, Weiss F, Grace D, Obersteiner M (2013) Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences 110, 20 888–20 893.

Hoffmann L, Schiemann R, Jentsch W, Henseler G (1974) Die verwertung der futterenergie für die milchproduktion. Archiv fur Tierernahrung 24, 245–261.
Die verwertung der futterenergie für die milchproduktion.CrossRef | 1:STN:280:DyaE2M%2Fltlyjtg%3D%3D&md5=d804b06874f9e9559b52d0d514c5129eCAS | 4433239PubMed |

Hristov AN, Oh J, Lee C, Meinen R, Montes F, Ott T, Firkins J, Rotz A, Dell C, Adesogan A, Yang W, Tricarico J, Kebreab E, Waghorn G, Dijkstra J, Oosting S (2013) ‘Mitigation of greenhouse gas emissions in livestock production: a review of technical options for non-CO2 emissions.’ Report no. 177. (Food and Agriculture Organization: Rome, Italy)

Huhtanen P, Nousiainen J, Rinne M (2006) Recent developments in forage evaluation with special reference to practical applications. Agricultural and Food Science 15, 293–323.
Recent developments in forage evaluation with special reference to practical applications.CrossRef | 1:CAS:528:DC%2BD2sXkslKisA%3D%3D&md5=10f51fab9529dfe11010bd823b0c1407CAS |

Illius AW, Gordon IJ (1991) Prediction of intake and digestion in ruminants by a model of rumen kinetics integrating animal size and plant characteristics. The Journal of Agricultural Science 116, 145–157.
Prediction of intake and digestion in ruminants by a model of rumen kinetics integrating animal size and plant characteristics.CrossRef |

Institut National de la Recherche Agronomique (1988) ‘Alimentation des bovins, ovins & caprins.’ (INRA-Quae: Paris, France)

Institut National de la Recherche Agronomique (1989) ‘Ruminant nutrition. Recommended allowances and feed tables.’ (Institut National de la Recherche Agronomique, John Libbey Eurotext: Montrouge, France)

Institut National de la Recherche Agronomique (2007) ‘Alimentation des bovins, ovins et caprins. Besoins des animaux. Valeurs des aliments.’ (Editions Quae: Versailles, France)

Intergovernmental Panel on Climate Change (2007) ‘Climate change 2007: synthesis report. Contribution of Working Groups I, II, and III to the fourth assessment report of the Intergovernmental Panel on Climate Change.’ (Cambridge University Press: Geneva, Switzerland)

Irvine LD, Freeman MJ, Donaghy DJ, Yoon I, Lee G, Roche JR (2011) Short communication: responses to supplemental Saccharomyces cerevisiae fermentation product and triticale grain in dairy cows grazing high-quality pasture in early lactation. Journal of Dairy Science 94, 3119–3123.
Short communication: responses to supplemental Saccharomyces cerevisiae fermentation product and triticale grain in dairy cows grazing high-quality pasture in early lactation.CrossRef | 1:CAS:528:DC%2BC3MXnvFCnsr0%3D&md5=08aee57d847d1af9726df029629ab8e5CAS | 21605780PubMed |

Janssen PH (2010) Influence of hydrogen on rumen methane formation and fermentation balances through microbial growth kinetics and fermentation thermodynamics. Animal Feed Science and Technology 160, 1–22.
Influence of hydrogen on rumen methane formation and fermentation balances through microbial growth kinetics and fermentation thermodynamics.CrossRef | 1:CAS:528:DC%2BC3cXhtV2itLvF&md5=f711073648fa8a61705a2f9dffb04381CAS |

Jentsch W, Chudy A, Beyer M (2003) ‘Rostock Feed Evaluation System: reference numbers of feed value and requirement on the base of net energy.’ (Plexus Verlag: Miltenberg-Frankfurt, Germany)

Jentsch W, Schweigel M, Weissbach F, Scholze H, Pitroff W, Derno M (2007) Methane production in cattle calculated by the nutrient composition of the diet. Archives of Animal Nutrition 61, 10–19.
Methane production in cattle calculated by the nutrient composition of the diet.CrossRef | 1:CAS:528:DC%2BD2sXjtlymsbs%3D&md5=3e75473fd60edfed01460bc4a503e191CAS | 17361944PubMed |

Kalscheur KF, Vandersall JH, Erdman RA, Kohn RA, Russek-Cohen E (1999) Effects of dietary crude protein concentration and degradability on milk production responses of early, mid, and late lactation dairy cows. Journal of Dairy Science 82, 545–554.
Effects of dietary crude protein concentration and degradability on milk production responses of early, mid, and late lactation dairy cows.CrossRef | 1:CAS:528:DyaK1MXitVWjtL8%3D&md5=55dc48eb7b3712b29050af0590cd2fdcCAS | 10194673PubMed |

Kaustell K, Tuori M, Huhtanen P (1997) Comparison of energy evaluation systems for dairy cow feeds. Livestock Production Science 51, 255–266.
Comparison of energy evaluation systems for dairy cow feeds.CrossRef |

Kohn RA, Boston RC (2000) The role of thermodynamics in controlling rumen metabolism. In ‘Modelling nutrient utilization in farm animals’. (Eds JP McNamara, J France, DE Beever) pp. 11–24. (CABI Publishing: New York)

Kohn RA, Boston R, Ferguson JD, Chalupa W (1994) The integration and comparison of dairy cow models. In ‘Proceedings of the 4th international workshop on modeling nutrient utilization in farm animals, Foulum, Denmark’. pp. 117–128.

Kokkonen T, Tuori M, Leivonen V, Syrjälä-Qvist L (2000) Effect of silage dry matter content and rapeseed meal supplementation on dairy cows. 1. Milk production and feed utilisation. Animal Feed Science and Technology 84, 213–228.
Effect of silage dry matter content and rapeseed meal supplementation on dairy cows. 1. Milk production and feed utilisation.CrossRef |

Kriss M (1930) Quantitative relations of the dry matter of the food consumed, the heat production, the gaseous outgo, and the insensible loss in body weight of cattle. Journal of Agricultural Research 40, 283–295.

Lanzas C, Sniffen CJ, Seo S, Tedeschi LO, Fox DG (2007a) A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants. Animal Feed Science and Technology 136, 167–190.
A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants.CrossRef | 1:CAS:528:DC%2BD2sXnslGht7c%3D&md5=d4fb4fb4fd07f0bea12ce892f219886aCAS |

Lanzas C, Tedeschi LO, Seo S, Fox DG (2007b) Evaluation of protein fractionation systems used in formulating rations for dairy cattle. Journal of Dairy Science 90, 507–521.
Evaluation of protein fractionation systems used in formulating rations for dairy cattle.CrossRef | 1:CAS:528:DC%2BD2sXmsFSkuw%3D%3D&md5=5a943522112739e14fafe54e417440baCAS | 17183120PubMed |

Lanzas C, Broderick GA, Fox DG (2008) Improved feed protein fractionation schemes for formulating rations with the Cornell net carbohydrate and protein system. Journal of Dairy Science 91, 4881–4891.
Improved feed protein fractionation schemes for formulating rations with the Cornell net carbohydrate and protein system.CrossRef | 1:CAS:528:DC%2BD1cXhsVKgtrnK&md5=3cddf4ee63996d0cbca1bb7f7bee8b5aCAS | 19038964PubMed |

Leroy AM (1954) Utilization de l’energie des aliments par les animaux. Annales de Zootechnie 3, 337–372.
Utilization de l’energie des aliments par les animaux.CrossRef |

Lofgreen GP (1965) A comparative slaughter technique for determining net energy values with beef cattle. In ‘Proceedings of the 3rd symposium of energy metabolism, Troon, Scotland’. (Ed. KL Blaxter) pp. 309–317. (Academic Press)

Lofgreen GP, Garrett WN (1968) A system for expressing net energy requirements and feed values for growing and finishing beef cattle. Journal of Animal Science 27, 793–806.

Lofgreen GP, Hull JL, Otagaki KK (1962) Estimation of the empty body weight of beef cattle. Journal of Animal Science 21, 20–24.

Lunsin R, Wanapat M, Rowlinson P (2012) Effect of cassava hay and rice bran oil supplementation on rumen fermentation, milk yield and milk composition in lactating dairy cows. Asian-Australasian Journal of Animal Sciences 25, 1364–1373.
Effect of cassava hay and rice bran oil supplementation on rumen fermentation, milk yield and milk composition in lactating dairy cows.CrossRef | 1:CAS:528:DC%2BC38XhvVClt7%2FI&md5=40751d6e1c597af75a29b8a3b517e63eCAS | 25049491PubMed |

Mambrini M (1997) Retention time of feed particles and liquids in the stomachs and intestines of dairy cows. Direct measurement and calculations based on faecal collection. Reproduction, Nutrition, Development 37, 427–442.
Retention time of feed particles and liquids in the stomachs and intestines of dairy cows. Direct measurement and calculations based on faecal collection.CrossRef | 1:STN:280:DyaK1c%2Fgt1aisw%3D%3D&md5=d58ded4a187bbda613851145d60ae73cCAS | 9342792PubMed |

McCormick ME, Redfearn DD, Ward JD, Blouin DC (2001a) Effect of protein source and soluble carbohydrate addition on rumen fermentation and lactation performance of Holstein cows. Journal of Dairy Science 84, 1686–1697.
Effect of protein source and soluble carbohydrate addition on rumen fermentation and lactation performance of Holstein cows.CrossRef | 1:CAS:528:DC%2BD3MXlvFamu7k%3D&md5=6cdcf01c9c018a296a0311bff104e986CAS | 11467819PubMed |

McCormick ME, Ward JD, Redfearn DD, French DD, Blouin DC, Chapa AM, Fernandez JM (2001b) Supplemental dietary protein for grazing dairy cows: effect on pasture intake and lactation performance. Journal of Dairy Science 84, 896–907.
Supplemental dietary protein for grazing dairy cows: effect on pasture intake and lactation performance.CrossRef | 1:CAS:528:DC%2BD3MXjtFyksLY%3D&md5=e3f461259d97cd3d3294ba760e427ecfCAS | 11352166PubMed |

McGinn SM, Beauchemin KA (2012) Dairy farm methane emissions using a dispersion model. Journal of Environmental Quality 41, 73–79.
Dairy farm methane emissions using a dispersion model.CrossRef | 1:CAS:528:DC%2BC38XovFSitA%3D%3D&md5=7b4a17d7b8001371f0ab9876c1c12d3fCAS | 22218175PubMed |

McGinn SM, Beauchemin KA, Iwaasa AD, McAllister TA (2006a) Assessment of the sulfur hexafluoride (SF6) tracer technique for measuring enteric methane emissions from cattle. Journal of Environmental Quality 35, 1686–1691.
Assessment of the sulfur hexafluoride (SF6) tracer technique for measuring enteric methane emissions from cattle.CrossRef | 1:CAS:528:DC%2BD28XhtVCktr7I&md5=819b195b9ccdb8f148f78c694682e750CAS | 16899740PubMed |

McGinn SM, Flesch TK, Harper LA, Beauchemin KA (2006b) An approach for measuring methane emissions from whole farms. Journal of Environmental Quality 35, 14–20.
An approach for measuring methane emissions from whole farms.CrossRef | 1:CAS:528:DC%2BD28XhtFGisL8%3D&md5=006979cedcec342b71b5cc9592d58a68CAS | 16391273PubMed |

McGinn SM, Turner D, Tomkins N, Charmley E, Bishop-Hurley G, Chen D (2011) Methane emissions from grazing cattle using point-source dispersion. Journal of Environmental Quality 40, 22–27.
Methane emissions from grazing cattle using point-source dispersion.CrossRef | 1:CAS:528:DC%2BC3MXps12kug%3D%3D&md5=21c05e7d5071d77cd7671c21e6ecf58dCAS | 21488489PubMed |

McNamara JP, Shields SL (2013) Reproduction during lactation of dairy cattle: integrating nutritional aspects of reproductive control in a systems research approach. Animal Frontiers 3, 76–83.
Reproduction during lactation of dairy cattle: integrating nutritional aspects of reproductive control in a systems research approach.CrossRef |

Meeske R, Botha PR, Merwe GDvd, Greyling JF, Hopkins C, Marais JP (2009) Milk production potential of two ryegrass cultivars with different total non-structural carbohydrate contents. South African Journal of Animal Science 39, 15–21.
Milk production potential of two ryegrass cultivars with different total non-structural carbohydrate contents.CrossRef | 1:CAS:528:DC%2BD1MXotV2jsr8%3D&md5=7d4af9f468950d3272281bb593503cb5CAS |

Mertens DR (1989) Evaluating alternative models of passage and digestion kinetics. In ‘Proceedings of the 3rd international modelling ruminant digestion and metabolism’, Lincoln College, Canterbury, New Zealand’. (Eds AB Robson, DP Poppi) pp. 79–97. (Lincoln University: Canterbury, New Zealand)

Mertens DR (1993) Kinetics of cell wall digestion and passage in ruminants. In ‘Forage cell wall structure and digestibility’. (Eds HG Jung, DR Buxton, RD Hatfield, J Ralph) pp. 535–570. (American Society of Agronomy: Madison, WI)

Mertens DR (2005) Rate and extent of digestion. In ‘Quantitative aspects of ruminant digestion and metabolism’. (Eds J Dijkstra, JM Forbes, J France) pp. 13–47. (CAB International: Wallingford, UK)

Mills JAN, Dijkstra J, Bannink A, Cammell SB, Kebreab E, France J (2001) A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation, and application. Journal of Animal Science 79, 1584–1597.

Ministry of Agriculture, Fisheries and Food (1975) ‘Energy allowances and feeding systems for ruminants.’ Her Majesty’s Stationery Office, 33, London.

Moe PW, Tyrrell HF (1974) Prediction of the net energy value of feeds for lactation. In ‘Proceedings of the 6th energy metabolism of farm animals, Stuttgart’. (Eds KH Menke, HJ Lantzsch, JR Reichl) pp. 201–204. (European Association of Animal Production)

Moe PW, Tyrrell HF (1975) Efficiency of conversion of digested energy to milk. Journal of Dairy Science 58, 602–610.
Efficiency of conversion of digested energy to milk.CrossRef | 1:STN:280:DyaE2M7lt1Smtw%3D%3D&md5=3cb7b553be7eb59446d1b00513b31963CAS | 1092740PubMed |

Moe PW, Tyrrell HF (1979) Methane production in dairy cows. Journal of Dairy Science 62, 1583–1586.
Methane production in dairy cows.CrossRef | 1:CAS:528:DyaL3cXlt1Og&md5=83e2a753e2e757a8337673236d8a23b3CAS |

Moe PW, Tyrrell HF, Flatt WP (1970) Partial efficiency of energy use for maintenance, lactation, body gain and gestation in the dairy cow. In ‘Proceedings of the 5th energy metabolism of farm animals, Vitznau, Switzerland’. (Eds A Schürch, C Wenk) pp. 65–68. (European Association of Animal Production)

Moe PW, Tyrrell HF, Flatt WP (1971) Energetics of body tissue mobilization. Journal of Dairy Science 54, 548–553.
Energetics of body tissue mobilization.CrossRef | 1:STN:280:DyaE3M3oslCrsw%3D%3D&md5=fa17914855205035bd870de8ddfe0399CAS | 5106186PubMed |

Moe PW, Flatt WP, Tyrrell HF (1972) Net energy value of feeds for lactation. Journal of Dairy Science 55, 945–958.
Net energy value of feeds for lactation.CrossRef |

Moharrery A (2010) Effect of particle size of forage in the dairy ration on feed intake, production parameters and quantification of manure index. Asian-Australasian Journal of Animal Sciences 23, 483–490.
Effect of particle size of forage in the dairy ration on feed intake, production parameters and quantification of manure index.CrossRef | 1:CAS:528:DC%2BC3cXmvFKlsb4%3D&md5=b8a81fcb8e41f149244e6f895cf7ad3eCAS |

Mosavi GHR, Fatahnia F, Mirzaei Alamouti HR, Mehrabi AA, Darmani Kohi H (2012) Effect of dietary starch source on milk production and composition of lactating Holstein cows. South African Journal of Animal Science 42, 201–209.

Moss AR, Jouany J-P, Newbold J (2000) Methane production by ruminants: its contribution to global warming. Annales de Zootechnie 49, 231–253.
Methane production by ruminants: its contribution to global warming.CrossRef | 1:CAS:528:DC%2BD3MXnt12msrk%3D&md5=5c16f7d8f4d5fcbaada5a760b2da87f6CAS |

Murphy JJ (1999) The effects of increasing the proportion of molasses in the diet of milking dairy cows on milk production and composition. Animal Feed Science and Technology 78, 189–198.
The effects of increasing the proportion of molasses in the diet of milking dairy cows on milk production and composition.CrossRef |

Nagorcka BN, Gordon GLR, Dynes RA (2000) Towards a more accurate representation of fermentation in mathematical models of the rumen. In ‘Modelling nutrient utilization in farm animals’. (Eds JP McNamara, J France, DE Beever) pp. 37–48. (CABI Publishing: New York)

National Research Council (1945a) ‘Recommended nutrient allowances for beef cattle.’ (National Academy Press: Washington, DC)

National Research Council (1945b) ‘Recommended nutrient allowances for dairy cattle.’ (National Academy Press: Washington, DC)

National Research Council (1982) ‘United States–Canadian tables of feed composition.’ (National Academy Press: Washington, DC)

National Research Council (1996) ‘Nutrient requirements of beef cattle.’ (National Academy Press: Washington, DC)

National Research Council (2000) ‘Nutrient requirements of beef cattle.’ (National Academy Press: Washington, DC)

National Research Council (2001) ‘Nutrient requirements of dairy cattle.’ (National Academy Press: Washington, DC)

Neal HSSC, Dijkstra J, Margaret G (1992) Simulation of nutrient digestion, absorption and outflow in the rumen: model evaluation. The Journal of Nutrition 122, 2257–2272.

Nehring K, Schiemann R, Hoffmann L (1966) Vorschlag eines neuen systems der energetischen bewertung des futters auf der grundlage der nettoenergie-fett. In ‘Sitzungsberichte Deutschen Akademie der Landwirtschaftswissenschaften, Berlin, Germany’. pp. 19–30.

O’Connor JD, Sniffen CJ, Fox DG, Chalupa W (1993) A net carbohydrate and protein system for evaluating cattle diets: IV. Predicting amino acid adequacy. Journal of Animal Science 71, 1298–1311.

O’Mara FP, Murphy JJ, Rath M (2000) The effect of concentrate supplements differing in ruminal protein degradability on milk production and blood metabolite concentrations of dairy cows grazing perennial ryegrass pasture. Livestock Production Science 64, 183–191.
The effect of concentrate supplements differing in ruminal protein degradability on milk production and blood metabolite concentrations of dairy cows grazing perennial ryegrass pasture.CrossRef |

Oguz FK, Oguz MN, Buyukoglu T, Sahinduran S (2006) Effects of varying levels of whole cottonseed on blood, milk and rumen parameters of dairy cows. Asian-Australasian Journal of Animal Sciences 19, 852–856.
Effects of varying levels of whole cottonseed on blood, milk and rumen parameters of dairy cows.CrossRef | 1:CAS:528:DC%2BD28Xlt1Gqsrc%3D&md5=f0e44d785c3a0887f513796985631f17CAS |

Palliser CC, Bright KP, Macdonald KA, Penno JW, Wastney ME (2001) Adapting the MOLLY cow model to fit production data from New Zealand animals. Proceedings of the New Zealand Society of Animal Production 61, 234–236.

Petit HV, Gagnon N (2011) Production performance and milk composition of dairy cows fed different concentrations of flax hulls. Animal Feed Science and Technology 169, 46–52.
Production performance and milk composition of dairy cows fed different concentrations of flax hulls.CrossRef | 1:CAS:528:DC%2BC3MXhtFeku7%2FE&md5=ef718c03b5d18d80285372e111c8a537CAS |

Piamphon N, Wachirapakorn C, Wanapat M, Navanukraw C (2009) Effects of protected conjugated linoleic acid supplementation on milk fatty acid in dairy cows. Asian–Australasian Journal of Animal Sciences 22, 49–56.
Effects of protected conjugated linoleic acid supplementation on milk fatty acid in dairy cows.CrossRef | 1:CAS:528:DC%2BD1MXjsF2hsLo%3D&md5=650fe299e23ebb07dbe519669477ca77CAS |

Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2014) ‘nlme: linear and nonlinear mixed effects models.’ (R Foundation for Statistical Computing: Vienna)

Pitt RE, Van Kessel JS, Fox DG, Pell AN, Barry MC, Van Soest PJ (1996) Prediction of ruminal volatile fatty acids and pH within the net carbohydrate and protein system. Journal of Animal Science 74, 226–244.

R Core Team (2014) ‘R: a language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna)

Ramin M, Huhtanen P (2012) Development of non-linear models for predicting enteric methane production. Acta Agriculturae Scandinavica, Section A. Animal Science 62, 254–258.

Ramin M, Huhtanen P (2013) Development of equations for predicting methane emissions from ruminants. Journal of Dairy Science 96, 2476–2493.
Development of equations for predicting methane emissions from ruminants.CrossRef | 1:CAS:528:DC%2BC3sXitlemt7s%3D&md5=51d8461c686291971aaa9c2701a5f54eCAS | 23403199PubMed |

Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Boote KJ, Throburn P, Antle JM, Nelson GC, Porter C, Janssen S, Asseng S, Basso B, Ewert F, Wallach D, Baigorria G, Winter JM (2013) The Agricultural Model Intercomparison and Improvement Project (AgMIP): protocols and pilot studies. Agricultural and Forest Meteorology 170, 166–182.
The Agricultural Model Intercomparison and Improvement Project (AgMIP): protocols and pilot studies.CrossRef |

Russell JB, O’Connor JD, Fox DG, Van Soest PJ, Sniffen CJ (1992) A net carbohydrate and protein system for evaluating cattle diets: I. Ruminal fermentation. Journal of Animal Science 70, 3551–3561.

Salmon L, Donnelly JR, Moore AD, Freer M, Simpson RJ (2004) Evaluation of options for production of large lean lambs in south-eastern Australia. Animal Feed Science and Technology 112, 195–209.
Evaluation of options for production of large lean lambs in south-eastern Australia.CrossRef |

Sauvant D (1996) A comparative evaluation of models of lactating ruminant. Annales de Zootechnie 45, 215–235.
A comparative evaluation of models of lactating ruminant.CrossRef |

Schiemann R, Nehring K, Hoffmann L, Jentsch W, Chudy A (1971) ‘Energetische Futterbewertung und Energienormen: Dokumentation der wissenschaftlichen Grundlagen eines neuen energetischen Futterbewertungssystems.’ (Deutscher Landwirtschaftsverlag: Berlin)

Seo S, Tedeschi LO, Schwab CG, Fox DG (2006) Development and evaluation of empirical equations to predict feed passage rate in cattle. Animal Feed Science and Technology 128, 67–83.
Development and evaluation of empirical equations to predict feed passage rate in cattle.CrossRef |

Sniffen CJ, O’Connor JD, Van Soest PJ, Fox DG, Russell JB (1992) A net carbohydrate and protein system for evaluating cattle diets: II. Carbohydrate and protein availability. Journal of Animal Science 70, 3562–3577.

Sun T, Yu X, Li SL, Dong YX, Zhang HT (2009) Responses of dairy cows to supplemental highly digestible rumen undegradable protein and rumen-protected forms of methionine. Asian-Australasian Journal of Animal Sciences 22, 659–666.
Responses of dairy cows to supplemental highly digestible rumen undegradable protein and rumen-protected forms of methionine.CrossRef | 1:CAS:528:DC%2BD1MXot12rtLo%3D&md5=5383149be64b7b500c2dd31bc5ba9f25CAS |

Sundstøl F (1993) Energy systems for ruminants. Iceland Agriculture Science 7, 11–19.

Sveinbjörnsson J, Huhtanen P, Udén P (2006) The Nordic Dairy Cow Model, Karoline – development of volatile fatty acid sub-model. In ‘Nutrient digestion and utilization in farm animals: modelling approaches’. (Eds E Kebreab, J Dijkstra, A Bannink, WJJ Gerrits, J France) pp. 1–14. (CABI Publishing: Cambridge, MA)

Tamminga S, Van Straalen WM, Subnel APJ, Meijer RGM, Steg A, Wever CJG, Blok MC (1994) The Dutch protein evaluation system: the DVE/OEB-system. Livestock Production Science 40, 139–155.
The Dutch protein evaluation system: the DVE/OEB-system.CrossRef |

Teague R, Provenza F, Kreuter U, Steffens T, Barnes M (2013) Multi-paddock grazing on rangelands: why the perceptual dichotomy between research results and rancher experience? Journal of Environmental Management 128, 699–717.
Multi-paddock grazing on rangelands: why the perceptual dichotomy between research results and rancher experience?CrossRef | 23850765PubMed |

Tedeschi LO (2006) Assessment of the adequacy of mathematical models. Agricultural Systems 89, 225–247.
Assessment of the adequacy of mathematical models.CrossRef |

Tedeschi LO, Fox DG, Chase LE, Wang SJ (2000a) Whole-herd optimization with the Cornell net carbohydrate and protein system. I. Predicting feed biological values for diet optimization with linear programming. Journal of Dairy Science 83, 2139–2148.
Whole-herd optimization with the Cornell net carbohydrate and protein system. I. Predicting feed biological values for diet optimization with linear programming.CrossRef | 1:CAS:528:DC%2BD3cXmvFKitLg%3D&md5=5d81571508763ecf54ec0921ef824f90CAS | 11003249PubMed |

Tedeschi LO, Fox DG, Russell JB (2000b) Accounting for the effects of a ruminal nitrogen deficiency within the structure of the Cornell net carbohydrate and protein system. Journal of Animal Science 78, 1648–1658.

Tedeschi LO, Pell AN, Fox DG, Llames CR (2001) The amino acid profiles of the whole plant and of four residues from temperate and tropical forages. Journal of Animal Science 79, 525–532.

Tedeschi LO, Boin C, Fox DG, Leme PR, Alleoni GF, Lanna DPD (2002a) Energy requirement for maintenance and growth of Nellore bulls and steers fed high-forage diets. Journal of Animal Science 80, 1671–1682.

Tedeschi LO, Fox DG, Pell AN, Lanna DPD, Boin C (2002b) Development and evaluation of a tropical feed library for the Cornell net carbohydrate and protein system model. Scientia Agricola 59, 1–18.
Development and evaluation of a tropical feed library for the Cornell net carbohydrate and protein system model.CrossRef | 1:CAS:528:DC%2BD38XitVCnurw%3D&md5=56c9af9c53304838e8c318cb301a0313CAS |

Tedeschi LO, Fox DG, Tylutki TP (2003) Potential environmental benefits of ionophores in ruminant diets. Journal of Environmental Quality 32, 1591–1602.
Potential environmental benefits of ionophores in ruminant diets.CrossRef | 1:CAS:528:DC%2BD3sXnsFKmtLs%3D&md5=567041f38149460adad7aa53b909e9c3CAS | 14535299PubMed |

Tedeschi LO, Fox DG, Doane PH (2005a) Evaluation of the tabular feed energy and protein undegradability values of the National Research Council nutrient requirements of beef cattle. The Professional Animal Scientist 21, 403–415.

Tedeschi LO, Fox DG, Sainz RD, Barioni LG, Medeiros SR, Boin C (2005b) Using mathematical models in ruminant nutrition. Scientia Agricola 62, 76–91.
Using mathematical models in ruminant nutrition.CrossRef |

Tedeschi LO, Seo S, Fox DG, Ruiz R (2006) Accounting for energy and protein reserve changes in predicting diet-allowable milk production in cattle. Journal of Dairy Science 89, 4795–4807.
Accounting for energy and protein reserve changes in predicting diet-allowable milk production in cattle.CrossRef | 1:CAS:528:DC%2BD28XhtlWgsrjP&md5=1f7615f74f7e2902cb8c05bfc7303e2aCAS | 17106111PubMed |

Tedeschi LO, Chalupa W, Janczewski E, Fox DG, Sniffen CJ, Munson R, Kononoff PJ, Boston RC (2008) Evaluation and application of the CPM Dairy nutrition model. The Journal of Agricultural Science 146, 171–182.

Tedeschi LO, Callaway TR, Muir JP, Anderson R (2011) Potential environmental benefits of feed additives and other strategies for ruminant production. Revista Brasileira de Zootecnia 40, 291–309.

Tedeschi LO, Fox DG, Fonseca MA, Cavalcanti LFL (2013a) Models of protein and amino acid requirements for cattle. In ‘Proceedings of the 50th annual meeting of the Brazilian Society of Animal Science, Campinas, São Paulo, Brazil’. (Ed. LG Nussio) pp. 1–45. (CD-ROM) (Sociedade Brasileira de Zootecnia (SBZ): Viçosa, Brazil)

Tedeschi LO, Fox DG, Kononoff PJ (2013b) A dynamic model to predict fat and protein fluxes associated with body reserve changes in cattle. Journal of Dairy Science 96, 2448–2463.
A dynamic model to predict fat and protein fluxes associated with body reserve changes in cattle.CrossRef | 1:CAS:528:DC%2BC3sXjtVSitL0%3D&md5=76f5ff81e02fbb528588a4e3deb27c2fCAS | 23462177PubMed |

Tomkins NW, McGinn SM, Turner DA, Charmley E (2011) Comparison of open-circuit respiration chambers with a micrometeorological method for determining methane emissions from beef cattle grazing a tropical pasture. Animal Feed Science and Technology 166–167, 240–247.
Comparison of open-circuit respiration chambers with a micrometeorological method for determining methane emissions from beef cattle grazing a tropical pasture.CrossRef |

Tothi R, Lund P, Weisbjerg MR, Hvelplund T (2003) Effect of expander processing on fractional rate of maize and barley starch degradation in the rumen of dairy cows estimated using rumen evacuation and in situ techniques. Animal Feed Science and Technology 104, 71–94.
Effect of expander processing on fractional rate of maize and barley starch degradation in the rumen of dairy cows estimated using rumen evacuation and in situ techniques.CrossRef |

Tylutki TP, Fox DG, Anrique RG (1994) Predicting net energy and protein requirements for growth of implanted and nonimplanted heifers and steers and nonimplanted bulls varying in body size. Journal of Animal Science 72, 1806–1813.

Tylutki TP, Fox DG, Durbal VM, Tedeschi LO, Russell JB, Van Amburgh ME, Overton TR, Chase LE, Pell AN (2008) Cornell net carbohydrate and protein system: a model for precision feeding of dairy cattle. Animal Feed Science and Technology 143, 174–202.
Cornell net carbohydrate and protein system: a model for precision feeding of dairy cattle.CrossRef | 1:CAS:528:DC%2BD1cXms1WjsLw%3D&md5=1d04db052cb5f441b97eba22b0bd14cfCAS |

Tyrrell HF, Moe PW (1975a) Effect of intake on digestive efficiency. Journal of Dairy Science 58, 1151–1163.
Effect of intake on digestive efficiency.CrossRef |

Tyrrell HF, Moe PW (1975b) Production efficiency in the high producing cow. Journal of Dairy Science 58, 602–610.

Tyrrell HF, Moe PW, Flatt WP (1970) Influence of excess protein intake on energy metabolism of the dairy cow. In ‘Proceedings of the fifth energy metabolism of farm animals, Vitznau, Switzerland’. (Eds A Schürch, C Wenk) pp. 69–72. (European Association of Animal Production)

Vafa T, Naserian AA, Heravi Moussavi A, Valizadeh R, Danesh Mesgaran M (2012) Effect of supplementation of fish and canola oil in the diet on milk fatty acid composition in early lactating holstein cows. Asian-Australasian Journal of Animal Sciences 25, 311–319.
Effect of supplementation of fish and canola oil in the diet on milk fatty acid composition in early lactating holstein cows.CrossRef | 1:CAS:528:DC%2BC38Xltlamu7Y%3D&md5=551b4d85e08edb8a679973a5c73a2c77CAS | 25049568PubMed |

Valizadeh R, Behgar M, Mirzaee M, Naserian AA, Vakili AR, Ghovvati S (2010) The effect of physically effective fiber and soy hull on the ruminal cellulolytic bacteria population and milk production of dairy cows. Asian-Australasian Journal of Animal Sciences 23, 1325–1332.
The effect of physically effective fiber and soy hull on the ruminal cellulolytic bacteria population and milk production of dairy cows.CrossRef | 1:CAS:528:DC%2BC3cXhsFemur7L&md5=0b7a00d3230a35fcca684d4f0c914445CAS |

Van Amburgh ME, Overton TR, Chase LE, Ross DA, Rechtenwald RJ (2009) The Cornell Net Carbohydrate and Protein System: current and future approaches for balancing of amino acids. In ‘Proceedings of Cornell nutrition conference for feed manufacturers, Syracuse, NY’. pp. 28–37. (New York State College of Agriculture & Life Sciences, Cornell University: New York)

Van Amburgh ME, Chase LE, Overton TR, Ross DA, Rechtenwald RJ, Higgs RJ, Tylutki TP (2010) Updates to the Cornell Net Carbohydrate and Protein System v6.1 and implications for ration formulation. In ‘Proceedings of Cornell nutrition conference for feed manufacturers, Syracuse, NY’. pp. 144–159. (New York State College of Agriculture & Life Sciences, Cornell University: New York)

Van Amburgh ME, Foskolos A, Collao-Saenz EA, Higgs RJ, Ross DA (2013) Updating the CNCPS feed library with new feed amino acid profiles and efficiencies of use: evaluation of model predictions – version 6.5. In ‘Proceedings of Cornell nutrition conference for feed manufacturers, Syracuse, NY’. pp. 59–76. (New York State College of Agriculture & Life Sciences, Cornell University: New York)

Van Es AJH (1975) Feed evaluation for dairy cows. Livestock Production Science 2, 95–107.
Feed evaluation for dairy cows.CrossRef |

Van Es AJH (1978) Feed evaluation for ruminants. I. The systems in use from May 1977– onwards in The Netherlands. Livestock Production Science 5, 331–345.
Feed evaluation for ruminants. I. The systems in use from May 1977– onwards in The Netherlands.CrossRef |

Van Soest PJ (1963a) Use of detergents in analysis of fibrous feeds. I. Preparation of fiber residues of low nitrogen content. Journal of the Association of Official Analytical Chemists International 46, 825–829.

Van Soest PJ (1963b) Use of detergents in analysis of fibrous feeds. II. A rapid method for the determination of fiber and lignin. Journal of the Association of Official Analytical Chemists International 46, 829–835.

Vermorel M (1978) Feed evaluation for ruminants. II. The new energy systems proposed in France. Livestock Production Science 5, 347–365.
Feed evaluation for ruminants. II. The new energy systems proposed in France.CrossRef |

Volden H (2011) ‘NorFor – the Nordic feed evaluation system.’ (Wageningen Academic Publishers: Wageningen, The Netherlands)

Waldo DR, Smith LW, Cox EL (1972) Model of cellulose disappearance from the rumen. Journal of Dairy Science 55, 125–129.
Model of cellulose disappearance from the rumen.CrossRef | 1:STN:280:DyaE38%2Fps12jsQ%3D%3D&md5=50a4d8bbaa6c300af1f77f0aa2b1e8f9CAS | 5009526PubMed |

Walker GP, Dunshea FR, Heard JW, Stockdale CR, Doyle PT (2010) Output of selenium in milk, urine, and feces is proportional to selenium intake in dairy cows fed a total mixed ration supplemented with selenium yeast. Journal of Dairy Science 93, 4644–4650.
Output of selenium in milk, urine, and feces is proportional to selenium intake in dairy cows fed a total mixed ration supplemented with selenium yeast.CrossRef | 1:CAS:528:DC%2BC3cXhsFKmsLnL&md5=c25f05201c1a3bad3c07c98d13c190b8CAS | 20854998PubMed |

Wickham H (2009) ‘ggplot2 elegant graphics for data analysis.’ (Springer: New York)

Wilkerson VA, Casper DP, Mertens DR (1995) The prediction of methane production of Holstein cows by several equations. Journal of Dairy Science 78, 2402–2414.
The prediction of methane production of Holstein cows by several equations.CrossRef | 1:CAS:528:DyaK28XhtFOrtA%3D%3D&md5=90ea6d49ac4f81777cafe177c7d6ee3cCAS | 8747332PubMed |

Wylie MJ, Ellis WC, Matis JH, Bailey EM, James WD, Beever DE (2000) The flow of forage particles and solubles through segments of the digestive tracts of cattle. The British Journal of Nutrition 83, 295–306.

Yalçın S, Yalçın S, Can P, Gürdal AO, Bağcı C, Eltan Ö (2011) The nutritive value of live yeast culture (Saccharomyces cerevisiae) and its effect on milk yield, milk composition and some blood parameters of dairy cows. Asian-Australasian Journal of Animal Sciences 24, 1377–1385.
The nutritive value of live yeast culture (Saccharomyces cerevisiae) and its effect on milk yield, milk composition and some blood parameters of dairy cows.CrossRef |

Yan T, Porter MG, Mayne CS (2009) Prediction of methane emission from beef cattle using data measured in indirect open-circuit respiration calorimeters. Animal 3, 1455–1462.
Prediction of methane emission from beef cattle using data measured in indirect open-circuit respiration calorimeters.CrossRef | 1:CAS:528:DC%2BD1MXhtlGnsb7N&md5=2b62d016f5260b3236e05a709ae7b44bCAS | 22444941PubMed |



Rent Article (via Deepdyve) Export Citation

View Altmetrics