Validation of enteric methane emissions by cattle estimated from mathematical models using data from <i>in vivo</i> experiments

Molina-Botero, Isabel; Díaz-Céspedes, Medardo; Mayorga-Mogollón, Olga; Ku-Vera, Juan; Arceo-Castillo, Jeyder; Montoya-Flores, María Denisse; Arango, Jacobo; Gómez-Bravo, Carlos

doi:10.4025/actascianimsci.v47i1.69328

Brazil

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ANIMAL PRODUCTION • Acta Sci., Anim. Sci. 47 • 2025 • https://doi.org/10.4025/actascianimsci.v47i1.69328 linkcopy

Validation of enteric methane emissions by cattle estimated from mathematical models using data from in vivo experiments

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT.

Several authors have developed equations to estimate methane (CH₄) emissions by cattle according to variables such as dry matter and nutrient intake, live weight, or weight gain. Mathematical models using these variables show a large variability of results, being necessary to identify those which provide more precise and accurate predictions. For this reason, the objective of this study was to validate enteric CH₄ emissions estimated from mathematical models through a comparison with a database of CH₄ emissions obtained from cattle experiments carried out in tropical regions. A database of 495 individual cattle CH₄ emissions data (g day^-1) obtained from 19 studies in three tropical Latin American countries was built for this study. Results showed that mathematical models developed for cattle in tropical production systems overestimated CH₄ emissions when they were compared with our database. The mathematical model with higher precision and accuracy was the one that included dry matter intake and organic matter digestibility in the equation (Equation 7. R²=0.34, Cb=0.94, CCC=0.55, RMSE=60.8%, r=0.58), followed by models that included neutral detergent fiber intake data (Equation 5). Our data did not show a relationship between CH₄ emissions and gross energy intake or live weight.

Keywords:
greenhouse gases; modeling; tropical livestock

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[TFN1] Abbreviations: n: number of observations; Min: minimum; Max: maximum; SD: standard deviation; DM: dry matter; DMI: dry matter intake; OMI: organic matter intake; dOM: digestibility of organic matter, dOMI: digestibility of organic matter intake; GE: gross energy; GEI: gross energy intake; CP: crude protein; CPI: crude protein intake; NDF: dietary neutral-detergent fiber content; NDFI: neutral-detergent fiber intake; dNDF: digestibility of neutral-detergent fiber; dNDFI: digestibility of neutral-detergent fiber intake; ADF: acid-detergent fiber; ADFI: acid-detergent fiber intake; EE: dietary ether extract content; Ym: Energy loss as methane, % GE intake.

Items		Descriptive statistical values
Items		n	Min	Max	Average	Median	SD
Description of the animals	Age (months)	413	10.8	30.5	20.5	19.5	4.62
Description of the animals	Body weight (kg)	468	162	521	333	313	80.5
Nutrient supply and digestibility	CP (g kg DM^-1)	469	10.8	88.3	84.4	146	183
	EE (g kg DM^-1)	134	10.0	199	19.0	20.9	15.9
	NDF (g kg DM^-1)	469	427	760	621	632	80.1
	ADF (g kg DM^-1)	469	241	508	349	357	55.9
	Ash (g kg DM^-1)	469	58.5	279	90.9	96.9	24.7
	GE (MJ kg DM^-1)	469	13.1	28.8	17.2	17.5	2.41
	dOM (g kg^-1)	260	367	776	605	594	77.1
	dNDF (g kg^-1)	187	391	853	685	665	106
Intake	DMI (kg day^-1)	495	1.93	14.0	8.53	7.78	2.34
	OMI (kg day^-1)	446	1.70	12.8	7.19	6.72	1.69
	CPI (g day^-1)	459	0.10	5.04	1.08	0.77	0.86
	NDFI (kg day^-1)	471	0.44	8.90	4.21	2.25	2.21
	ADFI (kg day^-1)	471	0.76	7.90	3.27	2.88	1.14
	GEI (MJ day^-1)	469	31.3	278	149	134	43.4
	dNDFI (kg day^-1)	192	0.69	6.68	3.58	2.49	1.74
	dOMI (kg day^-1)	211	0.87	6.42	4.01	3.66	1.09
Methane	(g day^-1)	495	74.2	453	191	169	71.6
Methane	Ym (%)	355	1.97	28.3	8.36	6.04	4.88

N	Equation	Unit	Comments	Source
1	-66+39.2 x DMI-0.64 x DMI²	g day^-1	Beef cattle, non-lactating	Charmley et al., 2016
2	20.7 x DMI	g day^-1	Beef cattle, non-lactating	Charmley et al., 2016
3	((35.1 x DMI) +14.7) x 0.714	g day^-1	Beef cattle	Yan, Porter, & Mayne, 2009
4	(1.959 x GEI+ 8.8) x 0.714	gday^-1	Beef cattle	Yan et al., 2009
5	(5.58+0.848 x NFDI)	MJ day^-1	Beef cattle	Ellis et al., 2007
6	(20+35.8 x DMI-0.5 x DMI²) x 0.714	g day^-1	Beef, dairy, and sheep	Ramin and Huhtanen, 2013
7	(7.14+0.22 x dOM) x DMI	g day^-1	Beef, dairy, and sheep	Sauvant and Noziere, 2016
8	0.44 x BW	g day^-1		Benaouda et al., 2020
9	19.4+16.7 x DMI	g day^-1		Benaouda et al., 2020
10	63.8+0.57 x GEI	g day^-1	Growing cattle	Benaouda et al., 2020
11	17.0 x DMI+0.03x NDF (g kg^-1 DM)	g day^-1		Benaouda et al., 2020
12	23.3 x DMI	g day^-1	Forage diet ≥75%	Intergovernmental Panel on Climate Change -IPCC, 2019
13	-1.47+1.28 x DMI	MJ day^-1	Beef cattle, non-lactating	Storlien et al., 2014
14	-1.012+0.308 x DMI+0.0404 x DMI²+2.424 x NDFI-0.29 x NDFI	MJ day^-1	Beef cattle, non-lactating	Ribeiro et al., 2020 (Equation 9)
15	1.006+0.97² x DMI	MJ day^-1	Beef cattle, non-lactating	Ribeiro et al., 2020 (Equation 1)
16	1.1010+0.906 x DMI	MJ day^-1	Beef, dairy, and sheep	Ribeiro et al., 2020 (Equation 1)
17	0.065 x GEI	MJ/day^-1	Beef, dairy, and sheep	Intergovernmental Panel on Climate Change -IPCC, 2006
18	1.289+0.051 x GEI	MJ day^-1	Beef cattle, non-lactating	Moraes, Strathe, Fadel, Casper, & Kebreab, 2014
19	-0.221+0.048 x GEI+0.005 x BW	MJ day^-1	Beef, dairy, and sheep	Ribeiro et al., 2020 (Equation 6)
20	-0.163+0.051 X GEI+0.038 X NDF(%)	MJ day^-1	Beef cattle, non-lactating	Moraes et al., 2014
21	1.067+0.051 x GEI	MJ day^-1	Beef, dairy, and sheep	Ribeiro et al., 2020 (Equation 49)
22	-0.3+0.753 x DMI+0.007 x BW	MJ day^-1	Beef, dairy, and sheep	Ribeiro et al., 2020 (Equation 17)
27	0.983+0.0368 x GEI+0.0098 x BW	MJ day^-1	Beef cattle, non-lactating	Ribeiro et al., 2020 (Equation 65)
28	1.002+0.0497 x GEI	MJ day^-1	Beef cattle, non-lactating	Ribeiro et al., 2020 (Equation 49)
29	-1.02+0.681 x DMI+4.81 x Forrage	MJ day^-1	Beef cattle	Ellis et al., 2007
30	0.060 x GEI	MJ day^-1	Beef, dairy, and sheep	Intergovernmental Panel on Climate Change -IPCC, 1997
31	117+36.1 x ADG	g day^-1		Benaouda et al., 2020
32	1.289+0.051 x GEI	MJ day^-1	Heifers	Moraes et al., 2014
33	0.163+0.051 x GEI+0.038 x NDF (%)	MJ day^-1	Heifers	Moraes et al., 2014
34	-1.487+0.046 x GEI+0.032 x NDF (%) + 0.006 x BW	MJ day^-1	Heifers	Moraes et al., 2014
35	0.743+0.054 x GEI	MJ day^-1	Steers	Moraes et al., 2014
36	-0.221+0.048 x GEI+0.005 x BW	MJ day^-1	Steers	Moraes et al., 2014
37	0.2433 x DMI	Mcal day^-1	Beef cattle, non-lactating	Hales et al., 2022
38	22.71 x DMI+8.91	g day^-1	Beef cattle, non-lactating	Suzuki et al., 2018
39	22.67 x DMI-3.73 x EE+23.32	g day^-1	Beef cattle, non-lactating	Suzuki et al., 2018
40	52.8+13.8 x DMI	g day^-1	High forage diets	Van Lingen et al., 2019
41	23.8+13.5 x DMI+0.844 x NDF (%)	g day^-1	High forage diets	Van Lingen et al., 2019
42	66.4+13.3 x DMI-3.69 x EE	g day^-1	High forage diets	Van Lingen et al., 2019
43	23.4+13.2 x DMI+0.571 x Forraje	g day^-1	High forage diets	Van Lingen et al., 2019
44	-6.41+11.3 x DMI+0.557 x Forraje+0.0996 x BW	g day^-1	High forage diets	Van Lingen et al., 2019
45	17.9+0.732 x Forraje+0.226 x BW	g day^-1	High forage diets	Van Lingen et al., 2019
46	1.29+0.878 x DMI	MJ day^-1		Patra, 2017
47	4.41+0.50 x DMI	MJ day^-1		Pires Sobrinho et al., 2019
48	5.26+2.53 x DMI-59.7 x EEI	MJ day^-1		Pires Sobrinho et al., 2019
49	4.32+1.85 x ADFI	MJ day^-1		Pires Sobrinho et al., 2019
50	4.35+0.543 x OMI	MJ day^-1		Pires Sobrinho et al., 2019
51	4.50+3.40 x CPI	MJ day^-1		Pires Sobrinho et al., 2019
53	7.4-3.28 x Fl	g kg^-1 DMI	High forage diets	Congio et al., 2023

Equation	n	Minimum	Maximum	Mean	SD	r	R²	CB	CCC	MSPE, %	ECT, %, MSPE	ER, %, MSPE	ED, %, MSPE	RMSPE, %
1	493	62.0	358	195	65.2	0.25	0.06	1.22	0.31	76.6	8.36	28.7	63.0	87.5
2	495	40.0	291	161	48.4	0.28	0.08	0.87	0.24	56.1	1.31	14.1	84.6	74.9
3	495	58.9	362	207	58.6	0.28	0.08	1.36	0.38	75.9	18.2	19.3	62.5	87.1
4	471	6.3	395	173	62.0	0.11	0.01	1.02	0.11	80.2	0.13	36.5	63.4	89.5
5	471	107	236	157	33.7	0.49	0.24	0.70	0.34	41.0	3.96	0.09	95.9	64.0
6	495	87.8	452	279	69.5	0.27	0.07	4.33	1.17	191	62.2	12.9	24.9	138
7	260	84.9	306	164	58.8	0.58	0.34	0.94	0.55	36.9	0.91	7.01	92.1	60.8
8	495	71.3	229	137	35.0	0.24	0.06	0.63	0.15	62.4	17.15	5.03	77.8	79.0
9	495	51.6	254	151	39.1	0.28	0.08	0.73	0.20	54.3	6.16	6.47	87.4	73.7
10	471	63.8	222	144	25.3	0.11	0.01	0.52	0.06	60.5	11.1	4.97	83.9	77.8
11	495	54.1	256	152	39.5	0.29	0.08	0.74	0.22	53.3	5.56	6.18	88.3	73.0
12	495	45.0	327	181	54.5	0.28	0.08	1.06	0.29	60.5	2.25	19.3	78.4	77.8
13	495	18.0	297	148	53.8	0.28	0.08	0.82	0.23	63.5	7.61	17.6	74.7	79.7
14	471	44.5	247	140	34.8	0.31	0.10	0.64	0.20	56.5	15.4	2.50	82.1	75.2
15	495	49.5	247	147	38.1	0.28	0.08	0.70	0.19	55.9	9.34	5.68	85.0	74.7
16	495	51.2	248	149	38.1	0.28	0.08	0.71	0.20	55.1	8.12	5.73	86.1	74.2
17	469	36.5	325	157	50.7	0.11	0.01	0.86	0.09	70.9	2.36	26.0	71.7	84.2
18	469	51.8	278	149	39.7	0.11	0.01	0.73	0.08	65.4	6.65	15.7	77.7	80.9
19	469	38.8	272	142	41.4	0.14	0.02	0.71	0.10	67.6	11.2	14.3	74.5	82.2
20	469	69.4	290	168	37.8	0.15	0.02	0.81	0.13	57.2	0.04	12.3	87.7	75.6
21	469	47.8	274	144	39.7	0.11	0.01	0.71	0.07	67.4	9.43	15.2	75.4	82.1
22	495	42.9	238	141	36.8	0.30	0.09	0.66	0.20	56.8	14.0	3.80	82.2	75.4
23	471	45.8	316	125	70.6	0.49	0.24	0.77	0.37	71.6	28.1	17.0	54.8	84.6
24	471	74.3	512	208	69.7	-0.02	0.00	1.38	-0.03	117	12.5	43.6	43.9	108
25	495	95.4	314	206	42.3	0.28	0.08	1.22	0.34	65.3	20.0	7.37	72.7	80.8
26	446	88.1	300	187	32.0	0.22	0.05	0.85	0.19	54.3	5.24	4.65	90.1	73.7
27	469	69.3	277	167	37.5	0.18	0.03	0.80	0.14	55.9	0.15	10.8	89.1	74.8
28	469	45.9	266	140	38.7	0.11	0.01	0.68	0.07	69.2	12.7	13.9	73.4	83.2
29	495	13.5	162	83	28.6	0.28	0.08	0.42	0.11	122	60.7	0.56	38.8	111
30	469	33.7	300	145	46.8	0.11	0.01	0.76	0.08	72.3	8.63	21.1	70.3	85.0
32	306	66.4	329	159	51.0	0.14	0.02	0.87	0.13	67.8	1.59	24.2	74.3	82.3
33	306	88.7	290	166	36.1	0.18	0.03	0.78	0.14	55.3	0.20	9.77	90.0	74.4
34	306	87.2	279	158	38.8	0.21	0.04	0.76	0.16	56.1	2.47	9.87	87.7	74.9
35	343	43.7	283	158	40.5	-0.09	0.01	0.78	-0.07	74.5	1.95	29.7	68.4	86.3
36	343	38.8	272	155	39.6	-0.04	0.00	0.75	-0.03	72.0	3.19	25.6	71.2	84.8
38	495	52.7	328	187	53.1	0.28	0.08	1.10	0.30	61.1	4.76	17.6	77.6	78.2
41	469	107	269	187	31.5	0.34	0.11	0.84	0.28	48.9	5.90	0.92	93.2	69.9
42	495	106	266	188	30.9	0.28	0.08	0.84	0.23	51.9	6.46	2.15	91.4	72.1
45	495	128	209	164	18.0	0.24	0.06	0.45	0.11	48.9	0.67	0.01	99.3	69.9
46	495	53.6	245	148	36.9	0.28	0.08	0.69	0.19	54.8	8.37	5.02	86.6	74.0
47	495	96.6	205	153	21.0	0.28	0.08	0.48	0.13	50.2	5.53	0.01	94.5	70.9
49	471	103	340	179	37.8	-0.02	0.00	0.89	-0.02	67.8	1.33	22.9	75.8	82.3
50	420	94.8	204	147	16.7	0.23	0.05	0.38	0.09	53.8	9.58	0.00	90.4	73.3
53	495	45.9	240	146	36.2	0.25	0.06	0.68	0.17	56.8	9.51	5.63	84.9	75.4