肉牛胃肠道甲烷排放模型估算精度的评估分析

doi:10.11843/j.issn.0366-6964.2017.04.012

畜牧兽医学报 ›› 2017, Vol. 48 ›› Issue (4): 690-698.doi: 10.11843/j.issn.0366-6964.2017.04.012

肉牛胃肠道甲烷排放模型估算精度的评估分析

毛宏祥^1,3, 高凤仙^1,3*, 王敏^2,3*, 蒋载阳¹, 张秀敏², 龙栋磊¹, 王荣¹, 谭支良²

1. 湖南农业大学动物科学技术学院, 长沙 410128;
2. 中国科学院亚热带农业生态研究所, 长沙 410125;
3. 湖南畜禽安全生产协同创新中心, 长沙 410128

收稿日期:2016-09-14 出版日期:2017-04-23 发布日期:2017-04-23
通讯作者: 高凤仙，教授，硕士生导师，E-mail：gaofx1964@163.com；王敏，副研究员，E-mail：mwang@isa.ac.cn
作者简介:毛宏祥（1991-），男，湖北襄阳人，硕士生，主要从事反刍家畜营养研究，E-mail：HongXiangmao@126.com
基金资助:
国家自然科学基金项目（31561143009；31472133）；国家科技计划项目（2016YFD0500504）；湖南省科技计划项目（2015WK3043）；中国科学院青年促进会项目

Evaluating the Accuracy of Models to Predict Enteric Methane Emissions in Beef Cattle

MAO Hong-xiang^1,3, GAO Feng-xian^1,3*, WANG Min^2,3*, JIANG Zai-yang¹, ZHANG Xiu-min², LONG Dong-lei¹, WANG Rong¹, TAN Zhi-liang²

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

Received:2016-09-14 Online:2017-04-23 Published:2017-04-23

摘要/Abstract

摘要：

本研究旨在评估6个经典的肉牛胃肠道甲烷排放估算模型的预测精度，分析影响模型预测精度的原因。在湖南望城肉牛养殖场选用17头体况良好的湘中黑牛，分两阶段测定了肉牛体重、营养组分采食量及胃肠道甲烷排放量。本研究选择6个经典的肉牛胃肠道甲烷排放估算模型，包括：以干物质采食量（DMI）为核心参数的估算模型1[CH₄（MJ·d^-1）=1.246×DMI（kg·d^-1）+0.996]和模型2[CH₄（MJ·d^-1）=-2.07+2.636×DMI（kg·d^-1）-0.105×DMI²（kg·d^-1）]；以纤维摄入量为核心参数的估算模型3[CH₄（MJ·d^-1）=5.58+0.848×NDF（kg·d^-1）]和模型4[CH₄（MJ·d^-1）=3.41+0.520×DMI（kg·d^-1）-0.996×ADF（kg·d^-1）+1.15×NDF（kg·d^-1）]；以总能摄入量为核心参数的估算模型5[CH₄（MJ·d^-1）=0.065×GEI（MJ·d^-1）]和模型6[CH₄（MJ·d^-1）=0.081×GEI（MJ·d^-1）-0.024]。利用预测误差均方（Mean squared prediction error，MSPE）和一致性相关系数（Consistent correlation coefficient，CCC）两种分析方法评估6个估算模型预测肉牛胃肠道甲烷排放量的精度以及影响模型估算精度的原因。结果表明，模型5（CCC=0.86）的估测精度最高，模型1（CCC=0.74）和6（CCC=0.79）次之，模型2（CCC=0.66）、3（CCC=0.22）和4（CCC=0.54）的估算精度最低；模型1和2的估算误差主要来自于整体偏差的偏离（分别为48.8%和70.3%）；模型3的估算误差主要来自于回归斜率的偏离（47.6%）；模型4的偏差主要来自于整体偏差（29.2%）和回归斜率偏离（28.6%）。IPCC（2006）Tier2推荐的以总能GEI为单一变量的模型5是本试验中6个估算公式预测精度最高的模型。

Abstract:

This study was conducted to evaluate the accuracy of 6 classic models to predict the enteric methane emissions in beef cattle and analyze the factors affecting predictive accuracy of models. Seventeen Xiangzhong Black cattle were selected in the Hunan Wangcheng beef farm, to measure body weight, dry matter and nutrients intake, enteric methane emissions in two stages. The selected 6 classic models included: equations developed by dry matter intake (DMI), such as Model 1 [CH₄(MJ·d^-1)=1.246×DMI(kg·d^-1)+0.996] and Model 2 [CH₄(MJ·d^-1)=-2.07+2.636×DMI(kg·d^-1)-0.105×DMI²(kg·d^-1)]; equations developed by fiber intake, such as Model 3 [CH₄(MJ·d^-1)=5.58+0.848×NDF(kg·d^-1)] and Model 4 [CH₄(MJ·d^-1)=3.41+0.520×DMI(kg·d^-1)-0.996×ADF(kg·d^-1)+1.15×NDF(kg·d^-1)]; equations developed by gross energy intake (GEI), such as Model 5 [CH₄(MJ·d^-1)=0.065×GEI(MJ·d^-1)] and Model 6 [CH₄(MJ·d^-1)=0.081×GEI(MJ·d^-1)-0.024]. Mean Squared Prediction Error (MSPE) and Consistent Correlation Coefficient (CCC) methods were employed to evaluate the prediction accuracy, and factors influencing the accuracy were also discussed. The result showed that: Model 5 (CCC=0.86) had the highest prediction accuracy among 6 models, next for Model 1 (CCC=0.74) and 6 (CCC=0.79), the lowest for Model 2 (CCC=0.66), 3 (CCC=0.22) and 4 (CCC=0.54). Model 1 and 2 had overall bias of 48.8% and 70.3%, respectively. Model 3 had greatest deviation of regression slope from unity (47.6%), while Model 4 had 28.6% deviation of regression slope from unity and 29.2% overall bias. The current results indicate that Model 5 developed by GEI based on world-wide data by IPCC (2006) Tier 2 is the most accurate model to predict the enteric methane emissions in beef cattle.

中图分类号:

毛宏祥, 高凤仙, 王敏, 蒋载阳, 张秀敏, 龙栋磊, 王荣, 谭支良. 肉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, 2017, 48(4): 690-698.

MAO Hong-xiang, GAO Feng-xian, WANG Min, JIANG Zai-yang, ZHANG Xiu-min, LONG Dong-lei, WANG Rong, TAN Zhi-liang. Evaluating the Accuracy of Models to Predict Enteric Methane Emissions in Beef Cattle[J]. ACTA VETERINARIA ET ZOOTECHNICA SINICA, 2017, 48(4): 690-698.

参考文献

[1] Intergovernmental Panel on Climate change. Climate change 2007:The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[M]. Cambridge:Cambridge University Press,2007.
[2] Intergovernmental Panel on Climate change. Climate change 2001:The scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change[M]. Cambridge:Cambridge University Press,2001.
[3] KNAPP J R, LAUR G L, VADAS P A, et al. Invited review:Enteric methane in dairy cattle production:Quantifying the opportunities and impact of reducing emissions[J]. J Dairy Sci, 2014, 97(6):3231-3261.
[4] 王荣,邓近平,王敏,等. 基于IPCC Tier 1层级的中国反刍家畜胃肠道甲烷排放格局变化分析[J]. 生态学报, 2015, 35(21):7244-7254.
WANG R, DENG J P, WANG M, et al. Using intergovernmental panel on climate change Tier 1 to analyze the trends anddistribution patterns of enteric methane emissions from ruminants in China during 1990-2010[J].Acta Ecologica Sinica,2015,35(21):7244-7254.(in Chinese)
[5] JOHNSON K A, JOHNSON D E. Methane emissions from cattle[J].J Anim Sci, 1995, 73(8):2483-2492.
[6] RAMIN M, HUHTANEN P. Development of equations for predicting methane emissions from ruminants[J]. J Dairy Sci, 2013, 96(4):2476-2493.
[7] CASTELÁ N-ORTEGA O A, KU-VERA J C, ESTRADA-FLORES J G. Modeling methane emissions and methane inventories for cattle production systems in Mexico[J]. Atmósfera, 2014, 27(27):185-191.
[8] PATRA A K. Prediction of enteric methane emission from buffaloes using statistical models[J]. Agric Ecosyst Environ, 2014, 195:139-148.
[9] ALEMU A, OMINSKI K H, KEBREAB E. Estimation of enteric methane emissions trends (1990-2008) from Manitoba beef cattle using empirical and mechanistic models[J]. Can J Anim Sci, 2011, 91(2):305-321.
[10] 张丽英. 饲料分析及饲料质量检测技术(第3版)[M]. 北京:中国农大出版社, 2007.
ZHANG L Y. The technology of feed analysis and quality inspection[M]. 3rd edition. Beijing:China Agricultural University Press,2007.(in Chinese)
[11] WANG M, WANG R, SUN X Z, et al. A mathematical model to describe the diurnal pattern of enteric methane emissions from non-lactating dairy cows post-feeding[J]. Anim Nutr, 2015, 1(4):329-338.
[12] KRISS M. 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[J]. J Agric Res, 1930, 40(3):283-295.
[13] AXELSSON J. The amount of produced methane energy in the European metabolic experiments with adult cattle[J].Ann R Agric Coll Sweden,1949,16:404-419.
[14] ELLIS J L, KEBREAB E, ODONGO N E, et al. Prediction of methane production from dairy and beef cattle[J]. J Dairy Sci, 2007, 90(7):3456-3466.
[15] Intergovernmental Panel on Climate change.IPCC Guidelines for National Greenhouse Gas Inventories Volume 4:Agriculture,Forestry and other Land Use[M].Geneva,Switzevland:Intergovernmental Panel on Climate Change,2006.
[16] YAN T, PORTER M G, MAYNE C S. Prediction of methane emission from beef cattle using data measured in indirect open-circuit respiration calorimeters[J]. Animal, 2009, 3(10):1455-1462.
[17] 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]. Anim Feed Sci Tech, 2011, 165(3-4):137-150.
[18] LIN L I. A concordance correlation coefficient to evaluate reproducibility[J]. Biometrics, 1989, 45(1):255-268.
[19] 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.
XIE T Y, WANG M, WANG R, et al. Evaluation of accuracy of models to predict enteric methane emissions in dairy cows[J]. Acta Veterinaria et Zootechnica Sinica, 2015, 46(9):1574-1583. (in Chinese)
[20] LEE S M, JEONG J S, LEE S C, et al. Prediction of ruminal methane production from cattle[J]. J Anim Vet Adv, 2012, 11(17):3228-3233.
[21] HIPPENSTIEL F, PRIES M, BÜSCHER W, et al. Comparative evaluation of equations predicting methane production of dairy cattle from feed characteristics[J]. Arch Anim Nutr, 2013, 67(4):279-288.
[22] ELLIS J L, KEBREAB E, ODONGO N E, et al. Modeling methane production from beef cattle using linear and nonlinear approaches[J]. J Anim Sci, 2009, 87(4):1334-1345.
[23] HEGARTY R S, GOOPY J P, HERD R M, et al. Cattle selected for lower residual feed intake have reduced daily methane production[J]. J Anim Sci, 2007, 85(6):1479-1486.
[24] 赵一广,刁其玉,邓凯东,等. 反刍动物甲烷排放的测定及调控技术研究进展[J]. 动物营养学报, 2011, 23(5):726-734.
ZHAO Y G, DIAO Q Y, DENG K D, et al. Measurements and modulation of methane emission from ruminants[J]. Journal of Animal Nutrition, 2011, 23(5):726-734. (in Chinese)
[25] 桑断疾,董红敏, 郭同军,等. 日粮类型对细毛羊甲烷排放及代谢物碳残留的影响[J]. 农业工程学报, 2013, 29(17):176-181.
SANG D J, DONG H M, GUO T J, et al. Effects of diet types on methane production and carbon resiue of metabolites of Xinjiang fine wool sheep[J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(17):176-181. (in Chinese)
[26] 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]. J Nutr, 2016, 146(9):1714-1721.
[27] MILLS J A N, KEBREAB E, YATES C M, et al. Alternative approaches to predicting methane emissions from dairy cows[J]. J Anim Sci, 2003, 81(12):3141-3150.
[28] WILKERSON V A, CASPER D P, MERTENS D R. The prediction of methane production of Holstein cows by several equations[J]. J Dairy Sci, 1995, 78(11):2402-2414.
[29] MILLS J A, DIJKSTRA J, BANNINK A, et al. A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow:model development, evaluation, and application[J]. J Anim Sci, 2001, 79(6):1584-1597.
[30] VAN GASTELEN S, ANTUNES-FERNANDES E C, HETTINGA K A, et al. Enteric methane production, rumen volatile fatty acid concentrations, and milk fatty acid composition in lactating Holstein-Friesian cows fed grass silage-or corn silage-based diets[J]. J Dairy Sci, 2015, 98(3):1915-1927.
[31] YAN T, AGNEW R E, GORDON F J, et al. Prediction of methane energy output in dairy and beef cattle offered grass silage-based diets[J]. Livest Prod Sci, 2000, 64(2-3):253-263.

肉牛胃肠道甲烷排放模型估算精度的评估分析

Evaluating the Accuracy of Models to Predict Enteric Methane Emissions in Beef Cattle

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