Accuracy Analysis of Prediction of Ruminal Volatile Fatty Acid Profiles in Chinese Lactating Dairy Cows by Stoichiometry Models

MAO Hongxiang, REN Ao, WANG Min, GAO Fengxian, ZHANG Xiumin, MAGN Zhiyuan, TAN Zhiliang

doi:10.3969/j.issn.1006-267x.2018.05.017

2018 , Vol. 30 >Issue 5: 1748 - 1759

DOI: https://doi.org/10.3969/j.issn.1006-267x.2018.05.017

Molecular Nutrition

Accuracy Analysis of Prediction of Ruminal Volatile Fatty Acid Profiles in Chinese Lactating Dairy Cows by Stoichiometry Models

Expand

1. Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China;
2. College of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China;
3. Hunan Collaborative Innovation Center of Animal Production Safety, Changsha 410128, China

Received date: 2017-11-01

Online published: 2018-05-06

Fold

Abstract

This study was conducted to evaluate the accuracy of models to predict ruminal volatile fatty acids (VFA) profiles in Chinese lactating dairy cows, and to analyze factors that affect the accuracy of the models. Three classical models of ruminal VFA stoichiometry were selected, which were MUR model, DIJ model and BAN model. The VFA data was selected from 18 articles of Chinese scientists, including 14 SCI articles, 3 articles from Chinese Core Journals and 1 unpublished manuscript, and data included diet, body weight, dry matter intake, feed additives, VFA proportions. Mean squared prediction error (MSPE) and consistent correlation coefficient (CCC) methods were employed to evaluate the prediction accuracy of MUR model, DIJ model and BAN model. The results showed as follow:BAN model had the highest prediction accuracy of acetate proportion (R²=0.140; P=0.007, RMSPE=6.8%), with overall bias being 47.8%. Propionate, butyrate and other acids proportions could not be predicted by the above three models. In conclusion, BAN model has highest prediction accuracy to predict acetate molar proportion among the three models, but the prediction accuracy is still low with the error mainly coming from the overall bias, and it is necessary to make use of more data to establish a VFA stoichiometry prediction model suitable for Chinese national conditions.

Key words： volatile fatty acid; model; prediction error mean square; consistency correlation coefficient; lactating dairy cow

Cite this article

MAO Hongxiang, REN Ao, WANG Min, GAO Fengxian, ZHANG Xiumin, MAGN Zhiyuan, TAN Zhiliang . Accuracy Analysis of Prediction of Ruminal Volatile Fatty Acid Profiles in Chinese Lactating Dairy Cows by Stoichiometry Models[J]. Chinese Journal of Animal Nutrition, 2018 , 30(5) : 1748 -1759 . DOI: 10.3969/j.issn.1006-267x.2018.05.017

References

[1] BERGMAN E N.Energy contributions of volatile fatty acids from the gastrointestinal tractin various species[J].Physiological Reviews,1990,70(70):567-590.

[2] MCLEOD K R,BALDWIN R L.Effects of diet forage:concentrate ratio and metabolizable energy intake on visceral organ growth and in vitro oxidative capacity of gut tissues in sheep[J].Journal of Animal Science,2000,78(3):760-770.

[3] BRUNETTE T,BAURHOO B,MUSTAFA A F,et al.Effects of replacing grass silage with forage pearl millet silage on milk yield,nutrient digestion,and ruminal fermentation of lactating dairy cows[J].Journal of Dairy Science,2016,99(1):269-279.

[4] SEYMOUR W M,CAMPBELL D R,JOHNSON Z B.Relationships between rumen volatile fatty acid concentrations and milk production in dairy cows:a literature study[J].Animal Feed Science & Technology,2005,119(1/2):155-169.

[5] FRIGGENS N C,OLDHAM J D,DEWHURST R J,et al.Proportions of volatile fatty acids in relation to the chemical composition of feeds based on grass silage[J].Journal of Dairy Science,1998,81(5):1331-1344.

[6] ARGYLE J L,BALDWIN R L.Modeling of rumen water kinetics and effects of rumen pH Changes[J].Journal of Dairy Science,1988,71(5):1178-1188.

[7] NOZIÈRE P,ORTIGUES-MARTY I,LONCKE C,et al.Carbohydrate quantitative digestion and absorption in ruminants:from feed starch and fibre to nutrients available for tissues[J].Animal,2010,4(7):1057-1174.

[8] MURPHY M R,BALDWIN R L,KOONG L J.Estimation of stoichiometric parameters for rumen fermentation of roughage and concentrate diets[J].Journal of Animal Science,1982,55(2):411-421.

[9] DIJKSTRA J,NEAL H D,BEEVER D E,et al.Simulation of nutrient digestion,absorption and outflow in the rumen:model description[J].The Journal of Nutrition,1992,122(11):2239-2256.

[10] BANNINK A,KOGUT J,DIJKSTRA J,et al.Estimation of the stoichiometry of volatile fatty acid production in the rumen of lactating cows[J].Journal of Theoretical Biology,2006,238(1):36-51.

[11] WANG M,WANG R,XIE T Y,et al.Shifts in rumen fermentation and Microbiota are associated with dissolved ruminal hydrogen concentrations in lactating dairy cows fed different types of carbohydrates[J].The Journal of Nutrition,2016,146(9):1714-1721.

[12] 王吉峰,王加启,李树聪,等.不同日粮对奶牛瘤胃发酵模式及泌乳性能的影响[J].畜牧兽医学报,2005,36(6):569-573.

[13] SUN P,WANG J Q,DENG L F.Effects of Bacillus subtilis natto on milk production,rumen fermentation and ruminal microbiome of dairy cows[J].Animal,2013,7(2):216-222.

[14] YANG S L,BU D P,WANG J Q,et al.Soybean oil and linseed oil supplementation affect profiles of ruminal microorganisms in dairy cows[J].Animal,2009,3(11):1562-1569.

[15] PENG H,WANG J Q,KANG H Y,et al.Effect of feeding Bacillus subtilis natto fermentation product on milk production and composition,blood metabolites and rumen fermentation in early lactation dairy cows[J].Journal of Animal Physiology and Animal Nutrition,2012,96(10):506-512.

[16] GUO T J,WANG J Q,BU D P,et al.Evaluation of the microbial population in ruminal fluid using real time PCR in steers treated with virginiamycin[J].Czech Journal of Animal Science,2010,55(7):276-285.

[17] PAN L,BU D P,WANG J Q,et al.Effects of Radix Bupleuri extract supplementation on lactation performance and rumen fermentation in heat-stressed lactating Holstein cows[J].Animal Feed Science and Technology,2014,187:1-8.

[18] ZHAO M,BU D P,WANG J Q,et al.Milk production and composition responds to dietary neutral detergent fiber and starch ratio in dairy cows[J].Animal Science Journal,2015,87(6):756-766.

[19] WANG B,MAO S Y,YANG H J,et al.Effects of alfalfa and cereal straw as a forage source on nutrient digestibility and lactation performance in lactating dairy cows[J].Journal of Dairy Science,2014,98(1):7706-7715.

[20] ZHANG R Y,ZHU W Y,ZHU W,et al.Effect of dietary forage sources on rumen microbiota,rumen fermentation and biogenic amines in dairy cows[J].Journal of the Science of Food and Agriculture,2014,94(9):1886-1895.

[21] 张倩,夏建民,李胜利,等不同比例压块秸秆与羊草组成粗饲料对奶牛瘤胃发酵和生产性能的影响[J].动物营养学报,2010,22(2):474-480.

[22] 曾银,贺鸣,曹志军,等.全混合日粮中粗饲料长度对奶牛咀嚼行为和瘤胃发酵的影响[J].动物营养学报,2010,22(6):1571-1578.

[23] GUO Y Q,ZOU Y,CAO Z J,et al.Evaluation of coarsely ground wheat as a replacement for ground corn in the diets of lactating dairy cows[J].Asian-Australasian Journal of Animal Sciences,2014,26(7):961-970.

[24] SUN T,YU X,LI S L,et al.Responses of dairy cows to supplemental highly digestible rumen undegradable protein and rumen-protected forms of methionine[J].Asian-Australasian Journal of Animal Sciences,2009,22(5):659-666.

[25] CHEN P,JI P,LI S L.Effects of feeding extruded soybean,ground canola seed and whole cottonseed on ruminal fermentation,performance and milk fatty acid profile in early lactation dairy cows[J].Asian-Australasian Journal of Animal Sciences,2008,21(2):204-213.

[26] CAO Z J,LI S L,XING J J,et al.Effects of maize grain and lucerne particle size on ruminal fermentation,digestibility and performance of cows in midlactation[J].Journal of Animal Physiology and Animal Nutrition,2008,92(2):157-167.

[27] WANG D S,ZHANG R Y,ZHU W Y,et al.Effects of subacute ruminal acidosis challenges on fermentation and biogenic amines in the rumen of dairy cows[J].Livestock Science,2013,155(2/3):262-272.

[28] 张丽英.饲料分析及饲料质量检测技术[M].3版.北京:中国农大出版社,2007.

[29] AOAC.Official methods of analysis[S].15th ed.Arlington,V.A.:Association of Official Analytical Chemists,1990.

[30] AOAC.Official methods of analysis[S].16th ed.Gaithersburg,M.D.:Association of Official Analytical Chemists,1997.

[31] VAN SOEST P J,ROBERTSON J B,LEWIS B A.Methods for dietary fiber,neutral detergent fiber,and nonstarch polysaccharides in relation to animal nutrition[J].Journal of Dairy Science,1991,74(10):3583-3597.

[32] 熊本海.国际反刍动物饲料成分及营养价值表[M].北京:中国农业科学技术出版社,2013.

[33] 熊本海,蒋林树.CNCPS体系演变模型及饲料成分表[M].北京:中国农业科学技术出版社,2015.

[34] BENCHAAR C,RIVEST J,POMAR C,et al.Prediction of methane production from dairy cows using existing mechanistic models and regression equations[J].Journal of Animal Science,1998,76(2):617-627.

[35] ØRSKOV E R,MCDONALD I.The estimation of protein degradability in the rumen from incubation measurements weighted according to rate of passage[J].Journal of Agricultural Science,1979,92(2):499-503.

[36] FOX D G,TEDESCHI L O,TYLUTKI T P,et al.The Cornell net carbohydrate and protein system model for evaluating herd nutrition and nutrient excretion[J].Animal Feed Science and Technology,2004,112(1/2/3/4):29-78.

[37] WANG M,TANG S X,TAN Z L.Modeling in vitro gas production kinetics:Derivation of Logistic-Exponential (LE) equations and comparison of models[J].Animal Feed Science and Technology,2011,165(3/4):137-150.

[38] LIN L I K.A concordance correlation coefficient to evaluate reproducibility[J].Biometrics,1989,45(1):255-268.

[39] 谢天宇,王敏,王荣,等.奶牛胃肠道甲烷排放模型估算精度的评估分析[J].畜牧兽医学报,2015,46(9):1574-1583.

[40] ALEMU A W,DIJKSTRA J,BANNINK A,et al.Rumen stoichiometric models and their contribution and challenges in predicting enteric methane production[J].Animal Feed Science and Technology,2011,166-167:761-778.

[41] BANNINK A,FRANCE J,LOPEZ S,et al.Modelling the implications of feeding strategy on rumen fermentation and functioning of the rumen wall[J].Animal Feed Science & Technology,2008,143(1/2/3/4):3-26.

[42] CHAMBERLAIN D G,THOMAS P C,ANDERSON F J.Volatile fatty acid proportions and lactic acid metabolism in the rumen in sheep and cattle receiving silage diets[J].The Journal of Agricultural Science,1983,101(1):47-58.

[43] LONCKE C,ORTIGUES-MARTY I,VERNET J,et al.Empirical prediction of net portal appearance of volatile fatty acids,glucose,and their secondary metabolites (beta-hydroxybutyrate,lactate) from dietary characteristics in ruminants:a meta-analysis approach[J].Journal of Animal Science,2009,87(1):253-268.

[44] MORVAY Y,BANNINK A,FRANCE J,et al.Evaluation of models to predict the stoichiometry of volatile fatty acid profiles in rumen fluid of lactating Holstein cows[J].Journal of Dairy Science,2011,94(6):3063-3080.

[45] HOGAN J P.The absorption of ammonia through the rumen of the sheep[J].Australian Journal of Biological Sciences,1961,14(3):448-460.

[46] DANIELLI J F,HITCHCOCK M W.The mechanism of absorption from the ru

Options

Outlines

模态框（Modal）标题

Abstract

Cite this article

References