Animal Science

Estimated enteric methane production from cattle and small ruminants fed on diets with tropical legume forages

0000-0002-7285-4465J. M. Castro-Montoya^{1  *}  , 0000-0002-7245-236XMizeck Chagunda² 

¹Graduate School, Faculty of Agricultural Sciences, University of El Salvador, San Salvador, El Salvador.

²Institute of Agricultural Sciences in the Tropics, Animal Breeding and Husbandry in the Tropics and Subtropics, University of Hohenheim, 70593 Stuttgart, Germany.

ABSTRACT

With the aim of exploring the effects of tropical legumes on methane emissions, methane production from ruminants fed tropical legumes was estimated using predictive equations based on diet’s nutrient characteristics, dry matter intake (DMI), and digestibility from 258 in vivo studies (1355 treatments) from literature. The dataset was divided into adult and growing cattle, goat, and sheep. Additionally, subsets were created depending on the growth habit of the legume: herb, shrub and tree. Methane was expressed relative to metabolic body weight (MBW), DMI, digestible organic matter intake (DOMI), and milk yield or average daily gain (ADG). Estimated methane for each subset of data and for each unit of expression was regressed on the proportion of legume in the diet. Increasing proportion of legumes decreased methane relative to MBW, DMI and ADG -but not relative to milk yield and DOMI- in cattle. For small ruminants, increasing legume proportion decreased estimated methane relative to MBW, DMI and DOMI (by tendency), but no effects were observed on methane relative to ADG, although these effects were likely underestimated. Herb legumes consistently showed the greater decreases in estimated methane in both cattle and small ruminants, while shrubs showed the smaller effects on methane decrease. These analyses highlight the potential of tropical legumes to decrease methane emissions, with differences between types of legumes, with improved effects were found in combination with grasses and concentrate. Further evidence is needed to affirm undeniable positive effects of legumes on the decrease of emissions relative to final product.

Key words: intensity emissions; herb legumes; ruminants; methane inhibition

Incorporating legume forages in ruminants feeding has several positive impacts on the sustainability of the agricultural system including biological N fixation, control of erosion, recycling of nutrients, and maintenance of biodiversity (^{Schultze-Kraft et al. 2018}) as well as increase productivity in cattle. Enteric methane is one of the most commonly discussed environmental impacts of ruminants, and feeding legumes has been proposed as a via to inhibit methanogenesis, mainly due to their contents of phytogenic compounds with the potential to modulate rumen fermentation. Moreover, if the premise of an increased productivity when feeding legumes is achieved, the intensity of emissions (the amount of methane per unit of final product) would likely also decrease.

A great number of studies have explored the in vitro effects of legumes on methane, generally showing their ability to decrease methane. However, in vitro fermentation cannot account for dry matter intake (DMI), a main determinant of methane production, neither for the adaptation of rumen microbes to a diet. Literature on in vivo trials is scarce and less conclusive, with several studies not providing estimates of DMI or the proportion of legumes consumed. At the time of the writing, ten studies were found reporting methane production accompanied by DMI (^{Possenti et al. 2008}, ^{Kennedy and Charmley 2012}, ^{Delgado et al. 2013}, ^{Moreira et al. 2013}, ^{Archimède et al. 2016}, ^{Pineiro-Vásquez et al. 2018}, ^{Washaya et al. 2018}, ^{Lima et al. 2020}, ^{Montoya-Flores et al. 2020} and ^{Suybeng et al. 2020}). With such a small sample size it is difficult to conclude on the effects of tropical legumes on methane emissions, particularly knowing that in 6 of the 10 studies Leucaena leucocephala was the legume tested. The effects of leucaena cannot be ascribed to all tropical legumes, as tree, shrub and herb legumes differ in composition and degradability (^{Castro-Montoya and Dickhoefer 2020}).

The limited number of studies is a consequence of the complexity of the methane measurement techniques, not available for the majority of research groups in tropical regions. However, the potential of these forages can be explored using predictive equations to estimate methane based on dietary characteristics (^{Ellis et al. 2007} and ^{Ramin and Huhtanen 2013}) including some who have been developed for tropical environments (^{Patra 2017}). Even though, the accuracy and global applicability of such equations can be debated, they still allow for the screening of large number of dietary strategies with effects on DMI, organic matter digestibility (OMD) and, therefore, on methane production. Hence, the objective of this study was to estimate methane emissions from literature data in a large number of dietary treatments containing tropical legumes, attempting to assess their potential to mitigate methane emissions from ruminants accounting for their effects on DMI, digestibility and final product’s yields.

Materials and Methods

Database, parameters extracted and calculations

The data used for the current study derived from a database reported in ^{Castro-Montoya and Dickhoefer (2020)}. For the current analysis, the studies had to report legume species, their proportion in the diet, the nutritional composition of the diet [organic matter (OM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF) concentration], animal body weight (BW), DMI, and OM -or dry matter (DM)- total tract digestibility. If available, milk yield (kg/d) and average daily gain (ADG) were recorded. A total of 258 studies fulfilled these criteria, resulting in 1355 dietary treatments. Further parameters were estimated. The feeding level (FL), presented as a multiple of maintenance energy requirements, was estimated by dividing the metabolizable energy (ME) intake by the maintenance ME requirement for the animals. The ME requirement for each animal was calculated based on the BW reported using the estimates from the meta analysis of ^{Salah et al. (2014)} for tropical small ruminants and cattle (542.64 and 631.26 kJ ME/kg BW^0.75, respectively).

The majority of the studies did not provide information on the ME concentration of the diet, therefore this was estimated according to ^{Minson (1984)} [Eq. (1)] with CP and digestible OM as predictors, two parameters that account for differences between legumes and grasses.

$\text{ME}\left(\frac{\text{MJ}}{\text{kg}}\right)=0.157\text{DOM}+0.059\text{CP}-1.073$ Eq.(1)

Where

DOM =	concentration of digestible organic matter in the diet (g/100 g DM);
CP =	concentration of crude protein in the diet (g/100 g DM);

Digestible OM concentration was estimated from the concentration of OM in the diet and from the OMD (g/kg) reported in the studies. For those studies not reporting OMD but where DM digestibility was available, the former was estimated from DM digestibility (DMD (g/kg)) using regressions derived from the data used for this study [Eq. (2), (3), (4)].

$\text{OMD}\left(\frac{g}{\text{kg}}\right)=100.2+0.876\times \text{DMD};R^2=0.72;\text{for grasses only}$ Eq.(2)

$\text{OMD}\left(\frac{\text{g}}{\text{kg}}\right)=108.0+0.848\times \text{DMD};R^2=0.65;\text{for mixed legume}-\text{grasses rations}$ Eq.(3)

$\text{OMD}\left(\frac{\text{g}}{\text{kg}}\right)=44.9+0.951\times \text{DMD};R^2=0.88; \text{for legumes only}$ Eq.(4)

Equations to estimate methane

For the estimation of methane production, equations considering DMI, NDF, ADF, and ME concentrations or intakes, as well as OMD were favored, parameters that capture the characteristics of legume forages, the differences within types of legume and between legumes and grasses, while also allowing for the estimation of methane from a significant amount of observations. In this regard, the predictive equations produced by ^{Patra (2017)} and ^{Ellis et al. (2007)} were considered. From the equations produced by ^{Patra (2017)} the Binomial 12 [Eq. (5)], Binomial 13 [Eq. (6)], Linear 17 [Eq. (7)] and Linear 18 [Eq. (8)] were selected based on their performance and the availability of the predictor variables within this dataset.

$C{H}_4\left(\frac{\text{MJ}}{\text{d}}\right)=-{1.012}_{\pm 0.709}+{0.308}_{\pm 0.249}\times \text{DMI}+{0.0404}_{\pm 0.0119}\times {\text{DMI}}^2+{2.424}_{\pm 0.415}\times \text{NDFI}-{0.290}_{\pm 0.0409}\times {\text{NDFI}}^2$ Eq.(5)

${\text{CH}}_4\left(\frac{\text{MJ}}{\text{d}}\right)=-{1.490}_{\pm 0.745}+{0.418}_{\pm 0.232}\times \text{DMI}+{0.0415}_{\pm 0.0118}\times {\text{DMI}}^2+{4.311}_{\pm 0.718}\times \text{ADFI}-{0.977}_{\pm 0.138}\times {\text{ADFI}}^2$ Eq.(6)

${\text{CH}}_4\left(\frac{\text{MJ}}{\text{d}}\right)={0.910}_{\pm 0.746}+{1.472}_{\pm 0.154}\times \text{DMI}-{1.388}_{\pm 0.451}\times \text{FL}-{0.669}_{\pm 0.338}\times \text{ADFI}$ Eq.(7)

${\text{CH}}_4\left(\frac{\text{MJ}}{\text{d}}\right)=-{1.559}_{\pm 2.010}+{1.217}_{\pm 0.164}\times \text{DMI}-{2.418}_{\pm 0.724}\times \text{FL}+{0.00714}_{\pm 0.00316}\times \text{OMDm}$ Eq.(8)

Where

DMI =	dry matter intake in kg/d;
NDFI =	NDF intake in kg/d;
ADFI =	ADF intake (kg/d);
FL =	feeding level as multiple of the maintenance requirements.
OMDm =	organic matter digestibility (g/kg) at a maintenance level of feeding (estimated based on OMD following the procedure outlined by ^Ramin and Huhtanen (2013).

Where DMI = dry matter intake in kg/d; NDFI = NDF intake in kg/d; ADFI = ADF intake (kg/d); FL = feeding level as multiple of the maintenance requirements; OMDm = organic matter digestibility (g/kg) at a maintenance level of feeding (estimated based on OMD following the procedure outlined by ^{Ramin and Huhtanen (2013)}.

From the work of ^{Ellis et al. (2007)} predictive equations 6c [Eq. (9)], 7c [Eq. (10)], 8c [Eq. (11)], and 10c [Eq. (12)] were used to estimate methane in this dataset:

${\text{CH}}_4\left(\frac{\text{MJ}}{\text{d}}\right)={3.44}_{\pm 0.937}+{0.502}_{\pm 0.115}\times \text{DMI}+{0.506}_{\pm 0.211}\times \text{NDFI}$ Eq.(9)

${\text{CH}}_4\left(\frac{\text{MJ}}{\text{d}}\right)={3.63}_{\pm 0.921}+{0.0549}_{\pm 0.00939}\times \text{MEI}+{0.606}_{\pm 0.306}\times \text{ADFI}$ Eq.(10)

${\text{CH}}_4\left(\frac{\text{MJ}}{\text{d}}\right)={4.41}_{\pm 1.13}+{0.0224}_{\pm 0.0106}\times \text{MEI}+{0.980}_{\pm 0.241}\times \text{NDFI}$ Eq.(11)

${\text{CH}}_4\left(\frac{\text{MJ}}{\text{d}}\right)={3.41}_{\pm 0.973}+{0.520}_{\pm 0.120}\times \text{DMI}-{0.996}_{\pm 0.447}\times \text{ADFI}+{1.15}_{\pm 0.321}\times \text{NDFI}$ Eq.(12)

Where

DMI =	dry matter intake in kg/d;
NDFI =	NDF intake in kg/d;
MEI =	ME intake in MJ/d;
ADFI =	ADF intake in kg/d.

Subsetting of data

The dataset was divided into cattle and small ruminants, and subsets were created according to physiological stage (adult or growing), species (goat and sheep). and legume’s growth habit (herb, shrub and tree legumes). The latter classification was based on the PLANTS database (https://plants.usda.gov) of the Natural Conservation service of the United Sates as described by ^{Castro-Montoya and Dickhoefer (2018)}. Descriptive statistics of the variables used in the study are presented in table 1. Another subset of data was created including only diets with grass forage with and without concentrate supplementation from small ruminants (table 1). This was not done for cattle because of the reduced number of observations available.

Table 1 Descriptive statistics of parameters used for the prediction of methane emissions for the different datasets used. 

Variable	n	Average	Median	Standard deviation	Minimum	Maximum
Adult cattle
Body weight (kg)	70	378.00	367.00	140.40	180.00	820.00
Dry matter intake (kg/d)	76	9.27	8.70	3.55	2.50	19.60
Organic matter digestibility (g/kg)	47	624.00	630.00	72.00	420.00	751.00
Digestible organic matter intake (kg/d)	38	5.45	4.84	2.97	1.51	12.60
Metabolizable energy (MJ/kg DM)	38	8.24	8.49	1.33	4.69	10.60
Metabolizable energy intake (MJ/d)	38	81.8	72.3	46.2	22.30	196.00
Feeding level	35	1.50	1.47	0.63	0.51	2.77
Neutral detergent fiber intake (kg/d)	69	5.21	5.31	1.71	1.34	8.64
Acid detergent fiber intake (kg/d)	57	3.27	3.00	1.15	0.85	5.96
Milk yield (kg/d)	23	7.68	6.30	4.50	3.75	22.00
Growing cattle
Body weight (kg)	79	195.00	181.00	94.80	36.00	411.00
Dry matter intake (kg/d)	79	4.62	4.30	2.01	0.34	9.40
Organic matter digestibility (g/kg)	44	573.00	584.00	92.9	129.00	724.00
Digestible organic matter intake (kg/d)	44	2.17	2.23	0.75	0.51	3.60
Metabolizable energy (MJ/kg DM)	44	7.78	7.86	1.27	1.66	9.38
Metabolizable energy intake (MJ/d)	44	32.30	33.20	11.00	7.21	53.00
Feeding level	44	1.08	1.03	0.37	0.23	2.20
Neutral detergent fiber intake (kg/d)	76	2.79	2.74	1.31	0.08	6.57
Acid detergent fiber intake (kg/d)	57	1.85	1.81	0.87	0.32	4.08
Average daily gain (g/d)	43	429.3	434.00	237.10	0.00	920.00
Adult goat
Body weight (kg)	98	31.10	29.00	11.90	14.20	67.00
Dry matter intake (kg/d)	100	0.88	0.68	0.51	0.11	2.61
Organic matter digestibility (g/kg)	84	594.00	622.00	120.4	293.00	759.00
Digestible organic matter intake (kg/d)	82	0.45	0.36	0.28	0.06	1.17
Metabolizable energy (MJ/kg DM)	82	8.17	8.63	1.84	3.59	11.3
Metabolizable energy intake (MJ/d)	82	6.80	5.44	4.25	0.86	18.0
Feeding level	82	0.94	0.91	0.40	0.21	1.84
Neutral detergent fiber intake (kg/d)	87	0.49	0.43	0.28	0.07	1.67
Acid detergent fiber intake (kg/d)	74	0.32	0.31	0.16	0.04	1.02
Growing goat
Body weight (kg)	232	15.10	14.90	4.06	5.43	25.80
Dry matter intake (kg/d)	235	0.51	0.50	0.15	0.11	0.96
Organic matter digestibility (g/kg)	145	631.00	632.00	84.00	455.00	819.00
Digestible organic matter intake (kg/d)	138	0.30	0.27	0.11	0.13	0.65
Metabolizable energy (MJ/kg DM)	138	8.76	8.84	1.33	5.60	11.80
Metabolizable energy intake (MJ/d)	138	4.54	4.11	1.62	1.94	9.90
Feeding level	135	1.09	1.07	0.34	0.48	2.36
Neutral detergent fiber intake (kg/d)	217	0.28	0.27	0.09	0.04	0.53
Acid detergent fiber intake (kg/d)	193	0.18	0.17	0.07	0.02	0.38
Average daily gain (g/d)	82	44.9	38.7	25.90	1.60	143.00
Adult sheep
Body weight (kg)	253	31.90	29.50	11.50	12.50	70.00
Dry matter intake (kg/d)	266	0.80	0.74	0.31	0.16	1.87
Organic matter digestibility (g/kg)	233	558	570	85.00	270.00	769.00
Digestible organic matter intake (kg/d)	211	0.40	0.38	0.19	0.05	1.04
Metabolizable energy (MJ/kg DM)	211	7.50	7.66	1.30	3.79	10.70
Metabolizable energy intake (MJ/d)	211	5.94	5.55	2.84	0.74	15.90
Feeding level	205	0.83	0.82	0.32	0.09	1.97
Neutral detergent fiber intake (kg/d)	242	0.48	0.48	0.19	0.06	1.01
Acid detergent fiber intake (kg/d)	205	0.31	0.30	0.13	0.04	0.61
Growing sheep
Body weight (kg)	357	21.60	19.50	15.00	4.10	209.00
Dry matter intake (kg/d)	357	0.70	0.68	0.20	0.21	1.28
Organic matter digestibility (g/kg)	207	592.00	578.00	83.70	408.00	840.00
Digestible organic matter intake (kg/d)	190	0.40	0.36	0.30	0.19	4.27
Metabolizable energy (MJ/kg DM)	190	8.53	7.95	6.82	5.22	101.00
Metabolizable energy intake (MJ/d)	190	5.92	5.35	4.80	2.72	66.9
Feeding level	190	1.12	0.96	1.32	0.23	18.7
Neutral detergent fiber intake (kg/d)	353	0.41	0.39	0.13	0.10	0.82
Acid detergent fiber intake (kg/d)	298	0.25	0.24	0.09	0.09	0.61
Average daily gain (g/d)	75	57.6	48.00	34.90	2.00	170.00
No legumes small ruminants
Body weight (kg)	264	24.10	21.20	11.40	5.43	70.00
Dry matter intake (kg/d)	271	0.65	0.59	0.32	0.17	2.89
Organic matter digestibility (g/kg)	200	586.00	592.00	106.90	227.00	840.00
Digestible organic matter intake (kg/d)	184	0.34	0.31	0.19	0.09	1.28
Metabolizable energy (MJ/kg DM)	184	7.79	7.90	1.67	2.56	11.7
Metabolizable energy intake (MJ/d)	184	5.08	4.55	2.88	1.14	19.7
Feeding level	179	0.85	0.78	0.38	0.17	2.21
Neutral detergent fiber intake (kg/d)	195	618.00	620.00	116.70	242.00	899.00
Acid detergent fiber intake (kg/d)	253	0.42	0.40	0.19	0.10	1.41
Average daily gain (g/d)	33	42.90	36.20	28.4	1.60	120

Using an energy density of 55.5 MJ/kg (^{Elert 2006}), the estimated methane in MJ/d from Eq. (5 - 12) were converted into g/d. Methane estimated from Eq. (5) for cattle and from Eq. (8) for small ruminants was further expressed as g/kg metabolic body weight (MBW), g/kg DMI, g/kg digestible organic matter intake (DOMI), g/kg milk, and g/kg ADG.

With the objective of comparing different forages without influence of other ingredients, a subset of data was created where small ruminants were fed exclusively on grasses, straw/stover, herb legumes, shrub legumes, or tree legumes. Boxplots were created with the forages categories for methane in g/kg DMI and in g/kg DOMI. Also, a subset was created to compare different forages when supplemented with concentrate feed in small ruminants. First, observations were selected where grasses or straw/stover were fed in proportions between 60 and 90 g/100 g DM, with the remainder of the DM coming from concentrate feeds. Second, observations were selected where legumes were fed mixed with grasses, where the legume inclusion ranged between 20 and 50 g/100 g DM, and where the total forage proportion (grass + legume) ranged between 60 and 90 g/100 g DM, with the remainder of the DM coming from concentrate feeds. Legumes were then divided into herbs, shrubs and trees. Boxplots were created with the forage categories for methane in g/kg DMI, in g/kg DOMI, and in g/kg ADG.

Statistical analysis

Outliers in the predicted methane from each equation were identified and removed based on the interquartile range. Pearson correlation was estimated within the methane predictions from all equations using the cor ( ) function of R program. The estimated methane production from Eq. (5) for cattle and from Eq. (8) for small ruminants was regressed on the legume proportion in the diet using the lm ( ) function of R. Regression analyses were conducted independently for the cattle and the small ruminant datasets. Within each of these datasets, further regression analyses were conducted for subsets based on the physiological stage (adult or growing), species (goat or sheep), and growth habit of legumes (herb, shrub, tree). For the dataset including only control treatments in small ruminants, predicted methane emissions were regressed on the proportion of concentrate in the diet following the procedure described above. Significances of the slopes were declared at P < 0.05, whereas tendencies were declared at 0.05 < P < 0.10.

Results

For the cattle dataset there was a high correlation between methane estimates from all equations, with those of Eq. (5) having the highest correlations with all other estimates (data not shown). Average methane estimated (g/d) for cattle was consistently higher when derived from the equations of ^{Ellis et al. (2007)}[Eq. (9 - 12)] than when estimated from the equations of ^{Patra (2017)} [Eq. (5 - 8)] (Table 2). For the dataset on small ruminants Eq. (5), (6) and (7) (^{Patra 2017}) produced a high number of negative estimations, and were not considered for further analyses (data not shown). Similarly, the estimates from the equations of ^{Ellis et al. (2007)} ranged between 71.6 and 313 g/d (data not shown) and were deemed unrealistic, thus were also disregarded for further analysis. Only the estimates of Eq. (8) (^{Patra 2017}) appeared to be within realistic ranges of methane production for small ruminants (Table 2).

Table 2 Summary statistics of estimated methane for cattle and small ruminants 

		Average	Median	Standard deviation	Minimum	Maximum
Cattle
Patra (2017) (g/d)	Eq. (5)	128.0	131.2	50.6	7.4	249.1
	Eq. (6)	128.2	137.4	49.6	5.3	261.2
	Eq. (7)	135.8	128.2	74.8	32.4	313.6
	Eq. (8)	122.1	118.8	52.8	48.7	254.0
Ellis et al. (2007) (g/d)	Eq. (9)	158.4	154.5	48.1	65.7	301.8
	Eq. (10)	149.2	134.8	49.7	84.8	273.4
	Eq. (11)	169.8	154.9	49.6	96.8	287.6
	Eq. (12)	165.2	163.2	49.2	74.9	296.6
Small ruminants
Patra (2017) (g/d)	Eq. (8)	25.9	26.2	22.4	2.12	62.7

The regressions presented in table 3 as well as scatterplots in figure 1and figure 2 correspond to Eq. (5) (^{Patra 2017}). Overall for cattle, when expressed relative to MBW, DMI and ADG, increasing proportions of legume in the diet decreased methane emissions (P ≤ 0.04) (figure 1) (table 3, Reg. 1, Reg. 7, Reg. 23). When expressed relative to DOMI or milk yield, the proportion of legume in the diet did not affect methane production (P ≥ 0.48) even though negative slopes for legume proportion were observed in both cases (figure 1) (table 3, Reg. 13 and Reg. 19). For adult cattle, methane in any unit was not affected by legume proportion in the diet (table 3; P ≥ 0.27), even though a negative slope was observed for all regressions with the exception of methane in g/kg DOMI (table 3, Reg. 14). For growing cattle methane in all units of expression decreased with increasing legume proportion (P < 0.01) (Table 3, Reg. 3, Reg. 9, Reg. 15, Reg. 23). Methane in g/kg MBW was greater in adult compared with growing cattle (figure 1) but the opposite appeared when expressed in g/kg DMI (figure 1).

Table 3 Regression equations of legume proportion in the diet on methane emissions for cattle ruminants. 

Variable (n^1)		Intercept	SE	Slope	SE	P slope
Methane relative to metabolic body weight (g/kg MBW)
Reg. 1 (134)	All	2.23	0.085	-7.17 × 10^-3	2.24 × 10^-3	<0.01
Reg. 2 (61)	Adult	2.24	0.157	-5.80 × 10^-3	5.61 × 10^-3	0.30
Reg. 3 (73)	Growing	2.17	0.113	-6.73 × 10^-3	2.56 × 10^-3	0.01
Reg. 4 (65)	Herb	2.49	0.150	-10.0 × 10^-3	4.33 × 10^-3	0.02
Reg. 5 (19)	Shrub	2.07	0.148	-6.31 × 10^-3	4.33 × 10^-3	0.16
Reg. 6 (50)	Tree	1.98	0.123	-5.36 × 10^-3	2.90 × 10^-3	0.07
Methane relative to dry matter intake (g/kg DMI)
Reg. 7 (137)	All	21.2	0.359	-1.98 × 10^-2	0.99 × 10^-2	0.04
Reg. 8 (66)	Adult	19.8	0.527	-1.13 × 10^-2	1.90 × 10^-2	0.55
Reg. 9 (71)	Growing	23.2	0.411	-4.54 × 10^-2	0.97 × 10^-2	<0.01
Reg. 10 (70)	Herb	19.9	0.585	2.01 × 10^-2	1.76 × 10^-2	0.26
Reg. 11 (19)	Shrub	21.3	0.543	-0.37 × 10^-2	1.59 × 10^-2	0.82
Reg. 12 (48)	Tree	22.1	0.625	-4.89 × 10^-2	1.54 × 10^-2	<0.01
Methane relative to digestible organic matter intake (g/kg DOMI)
Reg. 13 (75)	All	38.9	1.41	-0.925 × 10^-2	3.46 × 10^-2	0.79
Reg. 14 (35)	Adult	32.5	2.72	13.0 × 10^-2	11.7 × 10^-2	0.27
Reg. 15 (40)	Growing	45.7	1.71	-9.81 × 10^-2	3.32 × 10^-2	0.01
Reg. 16 (24)	Herb	35.2	2.77	13.6 × 10^-2	8.30 × 10^-2	0.12
Reg. 17 (13)	Shrub	34.3	1.84	9.02 × 10^-2	4.65 × 10^-2	0.08
Reg. 18 (38)	Tree	42.1	2.11	-8.77 × 10^-2	4.67 × 10^-2	0.07
Methane relative to milk yield (g/kg MY)
Reg. 19 (45)	All	30.7	4.45	-1.27 × 10^-1	1.81 × 10^-1	0.48
Reg. 20 (30)	Herb	28.7	5.62	-1.47 × 10^-1	2.17 × 10^-1	0.50
Reg. 21 (5)	Shrub	28.4	15.03	1.15 × 10^-1	7.64 × 10^-1	0.89
Reg. 22 (10)	Tree	31.6	5.82	1.31 × 10^-1	2.52 × 10^-1	0.62
Methane relative to average daily gain (g/kg ADG)
Reg. 23 (38)	All	0.275	0.027	-1.73 × 10^-3	0.621 × 10^-3	0.01
Reg. 24 (16)	Herb	0.322	0.054	-2.66 × 10^-3	1.21 × 10^-3	0.04
Reg. 25 (5)	Shrub	0.304	0.101	-1.83 × 10^-3	2.79 × 10^-3	0.56
Reg. 26 (17)	Tree	0.242	0.032	-1.24 × 10^-3	0.719 × 10^-3	0.11

¹number of observations used in the regression

Figure 1 Scatter plot of the regression of legume proportion in the diet on methane emissions expressed in different units for the complete cattle data (solid black line) and for data separated into growing and adult animals. 

Figure 2 Scatter plot of the regression of legume proportion in the diet on methane emissions of cattle expressed in different units for data separated into herb, shrub and tree legumes. 

Regarding legume’s growth habit, when expressed as g/kg MBW herbs decreased methane production (P = 0.02), trees tended to decrease it (P = 0.07) and shrubs did not have an effect (P = 0.16) (table 3, Reg. 4-6) ). Herbs showed a greater methane production (g/kg MBW) than both trees and shrubs (figure 2). Relative to DMI, methane decreased with increasing proportions of tree legumes (P < 0.01), while no effects were observed for herbs and shrubs (P ≥ 0.26) (table 3, Reg. 10-12). Methane relative to DOMI (figure 2) tended to increase with increasing proportion of shrubs in the diet (P = 0.08) and tended to decrease with tree legumes (P = 0.07), while no effects of herbs was detected even though a positive slope was obvious (figure 2) and greater than that of shrubs (table 3, Reg. 16-18). Relative to milk no effects of legume type was significant (P ≥ 0.50), and only herbs had a negative slope (table 3, Reg. 20-23). Relative to ADG herbs showed a decrease in methane with increasing proportion of legume (P = 0.04), with no effects found for shrubs and trees (P ≥ 0.11) (table 3, Reg. 24-26).

For small ruminants overall, increasing proportions of legumes decreased methane emissions relative to MBW, DMI and DOMI (by tendency; P = 0.06) (table 4, Reg. 27, 35, 43), but did not have an effect on methane in g/kg ADG (P = 0.97; table 4, Reg. 51). When analyzing the data by species (goats and sheep) and physiological stage (i.e. adult and growing) no effect was observed for adult goats or growing sheep in any unit of methane expression (P > 0.10) (table 4, Reg. 28, 31, 36, 39, 44, 47, 53). Feeding increasing proportions of legumes decreased methane in growing goats when expressed as g/kg MBW, g/kg DMI, and g/kg DOMI (by tendency; P = 0.08) (table 4, Reg. 29, 37, 45). For adult sheep methane decreased when expressed relative to DMI (by tendency; P = 0.06) or DOMI (table 4, Reg. 38, 46). Moreover, growing goats appeared to produce more methane than growing sheep when expressed relative to MBW, DMI and DOMI, but differences between adult and growing animals for other units of expression of methane appeared less clear (figure 3).

Table 4 Regression equations of legume proportion in the diet on methane emissions for small ruminants. 

Variable (n^1)		Intercept	SE	Slope	SE	P slope
Methane relative to metabolic body weight (g/kg MBW)
Reg. 27 (572)	All	2.46	0.051	-2.62 × 10^-3	1.14 × 10^-3	0.02
Reg. 28 (75)	Goat - Adult	2.03	0.149	3.92 × 10^-3	3.11 × 10^-3	0.21
Reg. 29 (124)	Goat - Growing	3.10	0.116	-7.54 × 10^-3	2.74 × 10^-3	0.01
Reg. 30 (190)	Sheep - Adult	2.19	0.065	-1.34 × 10^-3	1.31 × 10^-3	0.31
Reg. 31 (183)	Sheep - Growing	2.37	0.090	-0.986 × 10^-3	2.24 × 10^-3	0.66
Reg. 32 (160)	Herb	2.66	0.102	-5.12 × 10^-3	2.03 × 10^-3	0.01
Reg. 33 (58)	Shrub	1.95	0.174	3.07 × 10^-3	3.19 × 10^-3	0.34
Reg. 34 (354)	Tree	2.45	0.064	-2.65 × 10^-3	1.57 × 10^-3	0.09
Methane relative to dry matter intake (g/kg DMI)
Reg. 35 (576)	All	40.4	1.15	-5.15 × 10^-2	2.56 × 10^-2	0.04
Reg. 36 (72)	Goat - Adult	32.2	3.20	7.93 × 10^-2	6.76 × 10^-2	0.24
Reg. 37 (125)	Goat - Growing	48.8	2.57	-13.0 × 10^-2	6.14 × 10^-2	0.04
Reg. 38 (192)	Sheep - Adult	40.0	1.77	-6.71 × 10^-2	3.52 × 10^-2	0.06
Reg. 39 (187)	Sheep - Growing	37.2	2.19	-0.51 × 10^-2	5.50 × 10^-2	0.93
Reg. 40 (160)	Herb	45.0	2.41	-11.9 × 10^-2	4.80 × 10^-2	0.01
Reg. 41 (58)	Shrub	34.1	4.53	5.65 × 10^-2	8.42 × 10^-2	0.50
Reg. 42 (358)	Tree	39.9	1.37	-5.21 × 10^-2	3.36 × 10^-2	0.12
Methane relative to digestible organic matter intake (g/kg DOMI)
Reg. 43 (578)	All	77.1	2.24	-0.953 × 10^-1	4.98 × 10^-2	0.06
Reg. 44 (75)	Goat - Adult	62.3	6.72	2.27 × 10^-1	13.9 × 10^-2	0.11
Reg. 45 (125)	Goat - Growing	87.3	5.21	-2.19 × 10^-1	12.4 × 10^-2	0.08
Reg. 46 (189)	Sheep - Adult	82.2	3.58	-1.99 × 10^-1	7.14 × 10^-2	0.01
Reg. 47 (189)	Sheep - Growing	70.8	3.94	-0.263 × 10^-1	9.96 × 10^-2	0.79
Reg. 48 (160)	Herb	86.2	4.62	-2.58 × 10^-1	9.22 × 10^-2	0.01
Reg. 49 (59)	Shrub	58.2	8.89	2.65 × 10^-1	16.2 × 10^-2	0.11
Reg. 50 (359)	Tree	77.2	2.65	-1.16 × 10^-1	6.54 × 10^-2	0.08
Methane relative to average daily gain (g/kg ADG)
Reg. 51 (135)	All	0.526	0.055	-0.071 × 10^-3	1.63 × 10^-3	0.97
Reg. 52 (64)	Goat - Growing	0.665	0.075	-3.40 × 10^-3	2.39 × 10^-3	0.16
Reg. 53 (71)	Sheep - Growing	0.413	0.079	2.23 × 10^-3	2.20 × 10^-3	0.32
Reg. 54 (43)	Herb	0.644	0.110	-1.79 × 10^-3	2.79 × 10^-3	0.53
Reg. 55 (7)	Shrub	0.817	0.437	0.143 × 10^-3	0.10 × 10^-3	0.99
Reg. 56 (85)	Tree	0.515	0.061	-1.72 × 10^-3	2.06 × 10^-3	0.41

¹number of observations used in the regression

Figure 3 Scatter plot of the regression of legume proportion in the diet on methane emissions for small ruminants expressed in different units for the complete dataset (solid black line) and for data separated into adult and growing goat and sheep 

Moreover, in small ruminants, herbs decreased methane relative to MBW, DMI and DOMI (P = 0.01; Table 4, Reg. 32, 40, 48) (figure 4). Tree legumes only tended to decrease methane relative to MBW and DOMI (table 4, Reg. 34, 50). Feeding increasing proportions of shrub legumes did not have any effect on methane (P ≥ 0.11), but it is important to note that it showed a positive slope in all cases (table 4, Reg. 33, 41, 49, 55) (figure 4).

Figure 4 Scatter plot of the regression of legume proportion in the diet on methane emissions for small ruminants expressed in different units for data separated into herb, shrub and tree legumes. 

The regression of methane emissions on the concentrate proportion in diets with grasses but no legumes showed that higher concentrate proportion in the diet decreased methane emissions relative to DMI, DOMI and ADG (P ≤ 0.03), but not when expressed in g/kg MBW (P = 0.41) (table 5, Reg. 57, 60, 63, 66) (figure 5). However, when the analysis was conducted separately for grasses and for crop residues (straw or stover) supplementing grasses with concentrates always decreased methane emissions (P ≤ 0.02; table 5, Reg. 58, 61, 64, 67), but when concentrates supplemented straw/stover methane tended to decrease only in g/kg DOMI (P = 0.05), while it tended to increase when expressed in g/kg MBW (P = 0.05), with no effects over methane in g/kg DMI or g/kg ADG (P ≥ 0.56) (table 5, Reg. 59, 62, 65, 68).

Table 5 Regression of estimated methane on concentrate proportion in diets of small ruminants having grass or straw/stover as sole forage source in the diet. 

Variable (n^1)		Intercept	SE	Slope	SE	P slope
Methane relative to metabolic body weight (g/kg MBW)
Reg. 57 (151)	All	2.45	0.06	-2.28 × 10^-3	2.75 × 10^-3	0.41
Reg. 58 (949)	Grass	2.52	0.08	-7.96 × 10^-3	3.33 × 10^-3	0.02
Reg. 59 (57)	Straw/Stover	2.33	0.10	9.09 × 10^-3	4.54 × 10^-3	0.05
Methane relative to dry matter intake (g/kg DMI)
Reg. 60 (152)	All	46.5	1.53	-15.9 × 10^-2	5.82 × 10^-2	<0.01
Reg. 61 (93)	Grass	45.0	1.94	-30.3 × 10^-2	7.56 × 10^-2	<0.01
Reg. 62 (59)	Straw/Stover	49.6	2.05	2.72 × 10^-2	7.51 × 10^-2	0.72
Methane relative to digestible organic matter intake (g/kg DOMI)
Reg. 63 (152)	All	95.3	2.96	-56.9 × 10^-2	11.3 × 10^-2	<0.01
Reg. 64 (97)	Grass	89.9	3.59	-82.4 × 10^-2	14.3 × 10^-2	<0.01
Reg. 65 (55)	Straw/Stover	106.0	3.75	-26.6 × 10^-2	13.3 × 10^-2	0.05
Methane relative to average daily gain (g/kg ADG)
Reg. 66 (27)	All	0.861	0.139	-7.35 × 10^-3	3.24 × 10^-3	0.03
Reg. 67 (16)	Grass	0.956	0.141	-15.2 × 10^-3	4.21 × 10^-3	<0.01
Reg. 68 (11)	Straw/Stover	0.826	0.314	-3.54 × 10^-3	5.84 × 10^-3	0.56

¹ number of observations used in the regression

Figure 5 Scatter plot of the regression of concentrate proportion in the diet on methane emissions for small ruminants expressed in different units. Solid line represents the general regression line. 

Discussion

For this discussion the reader must keep in mind that methane was estimated from predictive equations and not directly measured, which carries an uncertainty in the results obtained from these analyses. However, similar exercises have been made before (^{Chagunda et al. 2010}) with results in line with in vivo observations. Moreover, the trends observed in this study across the subsets of data are consistent throughout the study and in accordance with physiological principles. Another important aspect to consider is that legumes contain a number of bioactive compounds with the capability to alter rumen fermentation, including methane production (^{Archimède et al. 2011}). Secondary compounds may have effects on DMI and OMD, both parameters strongly linked with methane production, thus indirectly, the equations used to estimate methane have accounted for some of the possible effects of secondary compounds. Even with these caveats, the robustness of this study lays in the volume of information that could be analyzed, where even small tendencies might be indicative of important and biologically relevant effects. Therefore, the results of the current analysis certainly contribute to the discussion on the ability of tropical legumes to decrease methanogenesis.

Predictive equations used

Equations to predict methane were selected based on the available parameters in our dataset. Therefore, equations including e.g. fat, non-structural carbohydrates, or gross energy concentration were not considered. Equations based exclusively on DMI were also disregarded, as these do not consider the differences in the nutritional composition of legumes and grasses. Hence, predictive equations considering DMI, OMD, NDF and ADF concentration or intake were purposely targeted. Recent studies have shown that, when accounting for the nutritional composition and at high inclusion levels, diets with increasing legume level tend to decrease DMI and OMD (^{da Silva et al. 2017} and ^{Montoya-Flores et al. 2020}) with clear differences between herb, shrub and tree legumes (^{Castro-Montoya and Dickhoefer 2018}). Along this line, tropical legumes have a fairly high concentration of NDF and ADF, which reflects on a lower in vitro OMD than grasses, particularly for shrub legumes (^{Castro-Montoya and Dickhoefer 2020}), hence, this study aimed at capturing this variation into the estimation of methane.

For the cattle dataset, including both adult and growing animals, all the equations used yielded estimates of methane within expected values for large ruminants (table 3). For example, estimates of Eq. (5) to (7) ranged between 0.76 and 1.58 MJ/kg DMI, while ^{Ellis et al. (2007)} and ^{Yan et al. (2009)}, reported methane emissions ranging from 1.12 to 1.49 MJ/kg DMI. For the cattle dataset, there was a high correlation between all predictive equations (r ≥ 0.71; data not shown). The equations of ^{Ellis et al. (2007)} had consistently higher estimated methane than that of ^{Patra (2017)} (table 2) likely due to the higher overall methane production of the temperate cattle used by ^{Ellis et al. (2007)}. Not only because Eq. (5) was developed from tropical cattle, but also because it was the equation that allowed for the maximum number of observations predicted, the estimates of Eq. (5) were used for the calculation of methane relative to MBW, DMI, DOMI, milk yield, and ADG, and the subsequent regression analyses.

For small ruminants Eq. (5), (6) and (7) produced a high number of negative estimations, likely due to the quadratic nature of NDFI and ADFI in Eq. (5) and (6) and due to the high ADF concentrations in diets in the tropics. Equation (8), based on the OMD, FL and DMI, yielded methane estimates with mean, min and max (g/d) of 25.9, 2.12 and 62.7 (table 2). The estimates of Eq. (8) still appeared to be on the higher end of daily methane emissions for small ruminants (^{Pelchen and Peters 1998}), but despite the possible overestimation, these estimates were used to calculate methane relative to MBW, DMI, DOMI, and ADG, and the subsequent regression analyses. The estimates from the equations of ^{Ellis et al. (2007)} averaged methane emissions between 71.4 and 88.9 g/d and were deemed not plausible for tropical small ruminants (data not shown).

In vivo methane production when feeding tropical legumes

Methane synthesis is a function of intake, therefore, robust conclusions can only be obtained when DMI has been reported in a study, thus manuscripts with grazing animals are not included in the following discussion. Under those considerations, ten studies were found reporting methane emissions and DMI from ruminants fed on tropical legumes comparing them with a control diet. Six of those in vivo studies tested the effects of leucaena, with four of them finding decreases in methane emissions (^{Archimède et al. 2016}, ^{Montoya-Flores et al. 2020}, ^{Pineiro-Vásquez et al. 2018} and ^{Possenti et al. 2008}) while two other finding no effects (^{Delgado et al. 2013} and ^{Moreira et al. 2013}). Importantly, three of the studies reporting a decrease in methane when feeding leucaena also found a decrease in OMD (^{Archimède et al. 2016}, ^{Pineiro-Vásquez et al. 2018} and ^{Montoya-Flores et al. 2020}). When testing other legume species, ^{Suybeng et al. (2020)} found decreases in methane (g/kg DMI) with increasing levels of Descanthus spp. but ADG decreased at the highest inclusion level (31 g/100 g DM). Three additional studies did not find any effect of feeding Lablab purpureus, Vigna unguiculata, Styzolobium aterrimum, Mimosa caesalpiniaefolia and Macrotyloma axiliare on methane emissions in g/kg DMI (^{Moreira et al., 2013}; ^{Washaya et al., 2018} and ^{Lima et al., 2020}).

Moreover, ^{Kennedy and Charmley (2012)} quantified the methane emission from several diets containing Lablab purpureus, Leucaena leucocephala, Stylosantes hamata, and Macroptilium bracteatum, but the study was not designed to compare those emissions to those of other diets. The authors found that when increasing the legume proportion in the diet from 20 to 40 g/100 g DM, the changes in methane production where not consistent and depended on the basal grass, the legume species, and the unit in which methane was expressed (^{Kennedy and Charmley 2012}). The meta-analysis of ^{Archimède et al. (2011)} concluded that legumes from warm environments produced less methane than their grasses counterparts, but the analysis was based on only 12 observations comparing legumes versus grasses. All of these studies point towards reductions in methane production when tropical legumes are fed, but the heterogeneity in legume species, animal characteristics, and diet’s nutritional composition make it venturous to draw a conclusion on the potential of these forages to reduce methane emissions.

Overall effects of legume forages on estimated methane production

Methane decreased with increasing legume proportion in the diet when expressed relative to MBW, however, emissions could decrease simply because of a lower DMI or degradability of the feed. Indeed, recent studies showed that high proportions of tropical legumes decrease intake, as well as OM and NDF degradability of the diet (^{Castro-Montoya and Dickhoefer 2018} and ^{da Silva et al. 2017}). In this regard, when expressed relative to DMI, methane still decreased with increasing legume proportion in the diet. However, when expressed relative to DOMI tropical legumes caused a less obvious response in methane, with no effects when fed to cattle and only a tendency to decrease in small ruminants.

Several mechanisms by which legumes may exert this decrease in methane production are discussed. First, microbial degradation of cellulose and hemicellulose yields H₂ that must be later removed from the rumen environment (^{Carroll and Hungate 1955}). A lower fiber degradability compared with grasses has been observed in tropical legumes, resulting in less substrate for methane formation. Second, diets conducive of higher propionate production sequester H₂ away from methane (^{Marty and Demeyer 1973}), however, studies have shown that tropical legumes have higher acetate to propionate ratios (e.g. ^{Castro-Montoya et al. 2020} and ^{Montoya-Flores et al. 2020}), thus, a higher sequestration of methane from propionate seems unlikely.

Also, it has been argued that the presence of secondary compounds in legumes may play a role on activity and number of methanogens (^{Makkar et al. 2007}). The in vivo studies reporting microbial activity and methane are inconclusive. The study of ^{Montoya-Flores et al. (2020)} with leucaena did not find any effect of the legume on methanogens number, despite the high concentration of total and condensed tannins and a decreased methane production. Conversely, ^{Lima et al. (2020)} found no decrease in methane production when macrotyloma was fed to lambs but found a decrease in the abundance of methanogens (also an increase in Ruminococcus flavefaciesn and Fibrobacter succionogens). In this study it was not possible to prove the direct effects of secondary compounds on methane, nevertheless, the indirect effects of those compounds, if any, could reflect on OMD and DMI, variables considered in these estimations. Importantly, not all tropical legumes are rich in secondary compounds neither it is proven that their activity is biologically significant to exert an effect on methanogenesis, therefore, not all the effects of legumes on methane production can be ascribed to secondary compounds.

Decreased degradability and intake can have negative consequences if their extent affects the supply of nutrients to the animal, ultimately decreasing its performance. Therefore, the best indicator of the effectiveness of a strategy to reduce methane is the reduction of intensity of emissions. In this regard, methane relative to milk yield was not affected by legume proportion (even though a negative slope was observed), whereas methane relative to ADG declined in cattle fed legumes. For methane relative to milk yield, it is important to notice that in the current dataset 95 % of the yields recorded was below 16.7 kg/d (average + 2 standard deviations), therefore the current results represent methane emissions of cattle with low to medium production level. Much higher milk yields are commonly found across the tropics. Not only are diets of high yielding cows usually well balanced in terms of nutrients, but also marginal improvements tend to decrease with higher yields. It is therefore uncertain and worth researching how tropical legumes would influence the intensity of emissions at high milk yield levels. The scenario presented for growing cattle appears to cover a larger range of growth for tropical cattle, where the majority of the ADG’s recorded were below 903 g/d.

Contrary to the cattle dataset, no effect of legumes was observed on methane in g/kg ADG for small ruminants. For goats, decreases in methane relative to MBW, DMI and DOMI were observed, hence a decrease in methane in g/kg ADG would be expected provided that ADG is maintained or increased when feeding legumes. Indeed, median ADG for sheep and goats was 48.0 and 38.7 g/d, respectively, higher than median ADG of small ruminants fed no legumes (36.2 g/d) (table 1). A previous study suggested a quadratic relationship between legume level and ADG, with ADG being maximized around 400 g legume/kg DM (^{Castro-Montoya and Dickhoefer 2018}). High levels of legume inclusion were more common in small ruminants than in cattle (figure 1, Figure 3), therefore, a quadratic effect of legume proportion in the diet on methane in g/kg ADG was tested, but was found not significant (data not shown). Maybe more relevant, for small ruminants, but not for cattle, a number of observations reported a negative ADG, that is when animals lost weight throughout the experimental period. These data were not used for this analysis, as such calculation would produce a negative methane emission which is biologically impossible. Therefore, 12, 9 and 2 observations were removed from the calculations of methane in g/kg ADG of small ruminants without legume, growing sheep, and growing goat, respectively. When considering those negative observations, the median ADG of diets without legumes (25.0 g/d) was much lower than the median observed for growing sheep and goats, (48.0 and 38.1 g/d, respectively; data not shown). This means that the effect of feeding legumes to small ruminants on methane relative to ADG are indeed underestimated in this study, and that a greater reduction in methane emissions, for example over the lifespan of an animal, is likely when improving their feeding via legumes.

Effects of legumes forages according to their growth habit on estimated methane emissions

Recent literature reviews on tropical legumes have shown strong differences in the nutritional characteristics between herb, shrub and tree legumes (^{Castro-Montoya and Dickhoefer 2018} and ^{Castro-Montoya and Dickhoefer 2020}) with shrubs having the highest NDF concentrations, and herbs having the greatest in vivo and in vitro OMD. Herb, shrub and tree legumes also differ in terms of ME, secondary compounds, and CP, to mention some (^{Castro-Montoya and Dickhoefer 2020}). All of these parameters will influence intake level, fermentation patterns, total tract digestibility, and performance. It is therefore expectable that different types of legumes will elicit different responses on methane production. Remarkably, the differential effects of herb, shrub and tree legumes were consistent across cattle and small ruminants and reflected previously outlined differences in their nutritional composition. A greater degradability would lead to higher methane emissions, and indeed, higher methane production was observed for herbs when expressed relative to MBW. When expressed relative to DMI and DOMI, herb legumes have higher methane emissions at levels of inclusion below 500 g/kg DM, but because of the steeper slope, with greater inclusion levels herbs produce less methane than shrubs and trees. Shrubs clearly show the lesser potential to decrease methane emissions, even having a tendency for higher emissions when expressed relative to DOMI, likely related to their higher NDF content directly linked to methane production.

According to the current analysis, tree legumes appear to be intermediate in their potential to decrease methane. Tree legumes have a higher lignin concentration and a lower OMD than herbs (^{Castro-Montoya and Dickhoefer 2020}), as well as a decreased DMI and NDF digestibility (^{Castro-Montoya and Dickhoefer 2018}). The lower digestibility an intake of tree legumes may reflect on a lower animal performance, and ultimately in their potential to decrease methane. Only the foliage of tree legumes is fed to ruminants, resulting in that, compared to herbs, tree legumes have a higher CP content, but also higher secondary compounds content. The presence of secondary compounds in trees may further influence their effects on methane, but the extent and direction of such effects are uncertain, as outlined before. For example, ^{Tiemann et al. (2008)} found no correlation between the concentration of condensed tannins and NDF degradability of tropical legumes in vitro. The unclear effects of secondary compounds on ruminants’ nutrition and methane are likely related to their diversity, and must not be neglected from research, this, however, escapes the scope of this study.

The higher degradability and Metabolizable energy of herbs (^{Castro-Montoya and Dickhoefer 2020}) is likely conducive of a greater positive effect on animal performance, whereas shrubs would have the lowest. Indeed, when expressed relative to ADG and milk yield, the slopes of the regression of legume herbs on methane were consistently negative and showed a greater potential to decrease intensity of emissions than trees and shrubs (figure 2).

Estimated methane emissions from diets of small ruminants without legumes

In general, the results of the current study evidence that legumes have potential to decrease methane emissions, particularly when expressed relative to DMI and DOMI. The decreases, however, where not comparable to those achieved when concentrate is supplemented to grasses or crop residues from cereals, as reflected in the greater negative slopes in table 5 compared with those of Table 4. Interestingly, the effects of feeding concentrate were contrasting when the basal forage was a grass or a crop residue. Concentrate feeding is regarded as a strategy to decrease methane emissions as less substrate for H₂ producing is available, while steering the fermentation towards more propionate production (^{Carroll and Hungate, 1955}), while increasing animal productivity, thereby decreasing the intensity of emissions. In the current analysis, higher concentrate supplementation in the diet of small ruminants fed on grass constantly decreased methane emissions, including when expressed relative to ADG, an effect not always observed with the legumes. However, when concentrate was supplemented to straw, methane tended to increase when expressed relative to MBW and had no effect on methane relative to DMI. The supplementation of straw with concentrate feed certainly caused an increase in the overall diet digestibility, thereby producing more methane. Indeed, when methane was expressed relative to DOMI the supplementation of concentrate tended to decrease methane emissions. The effects of supplementing concentrate feeds to crop residues were not obvious when expressed relative to ADG. The reduction of methane when feeding a concentrate feed is remarkable considering that in most cases the portion referred as concentrate consisted of only a cereal meal, brans, cakes or byproducts from other industry, or mixtures of cereal and protein meals. This highlights, on the one hand, the low quality of basal forages found across the tropics, but on the other hand, the great potential that adding even a small proportion of readily digestible energy or protein sources may have in the utilization of that basal forage, performance, and emissions.

Importantly, the authors do not want to suggest that concentrates should be used in detriment of legume forages. Utilizing legume forages has several advantages for the agricultural production system. Moreover, enteric methane is not the only measurement of environmental impact of a given strategy, and other factors like carbon footprint, water footprint, or biodiversity should be considered for the legume forages vs. concentrates comparison.

^{Archimède et al. (2011)} found that sole legumes decrease methane emissions compared with sole grasses. In an attempt to do a similar evaluation boxplots were created comparing estimated methane for diets containing only grasses, only straw/stover, or only legumes (figure 6A-B). The boxplots clearly show higher methane emissions from both grasses and straw compared with only legumes for both methane in g/kg DMI and in g/kg DOMI, with herbs consistently having less methane than that of shrubs and trees. Unfortunately, not enough observations were available to compare sole forages on the basis of methane relative to ADG. Furthermore, when the grasses supplemented with concentrates were compared with mixed legume-grass rations supplemented with concentrates (figure 6C-D-E), relative to DMI and DOMI, median methane produced by grasses was lower than that of herbs and shrubs, and appeared similar to that of trees. However, when expressed relative to ADG the lowest median methane was found for diets where herbs were combined with grasses and supplemented with concentrate, slightly lower than those of only grass supplemented with concentrate. The synergism between legumes and grasses has been previously reported (^{Minson 1990}), albeit not specific for methane emissions, but it could be related to a greater partitioning of energy away from metabolic losses.

Figure 6 Boxplots of the comparison in methane emissions (g/kg DMI, g/kg DOMI) between diets were small ruminants were fed solely on forages (grasses, stover/straw or legumes forages (Herb, Shrub, Tree)) (A, B); and where small ruminants were supplemented with concentrate to basal diets of grasses, straw/stover or legumes (Herb, Shrub, Tree) mixed with grasses (g/kg DMI, g/kg DOMI, g/kg ADG) (C, D, E). 

Worth noticing is that the median estimates of methane (g/kg ADG) from shrubs seem to be higher even than those where straws as sole forage were supplemented with concentrates. It is also important to see the variation in the effects of diets with tree legumes on methane relative to ADG. This further highlights the need to evaluate the effects of legumes depending on their growth habit or other classifications that account for their different nutritional quality. It becomes obvious that not all tropical legumes share the same nutritional attributes.

The results of the current analysis must be still validated with further studies in vivo, where the main varying effect should be the inclusion of the legume. If possible, factors like the forage to concentrate ratio or the NDF, CP, and ME concentration across dietary treatments should remain constant or at least similar. For forage based diets the comparison of diets with and without legumes is still valuable, but adjusting for the nutrients composition is not possible. In this case, the use of relevant nutrients concentration as covariates in the statistical analysis might be an option to account for the changes in the nutritional value of the diet. Expressing methane relative to DMI and digestible OM or DM intake, can also help to draw stronger conclusions. More importantly, aiming at obtaining a measure of intensity of emissions should be a priority of any study. Knowing the ability of rumen microbes to adapt to different conditions, mid to long-term trials would be ideal to assess the potential of tropical legumes to decrease methane emissions when routinely included in the rations of ruminants.

The results of the current analysis clearly show the potential of legumes to decrease methane emissions in ruminants in tropical environments, even though the evidence on the reduction of intensity of methane emissions is still inconclusive. Strong differences appeared in the effects of tropical legumes on estimated methane between herb, shrub, and tree legumes, where herbs showed a clear advantage in reducing methane. While methane estimates from only grasses versus only legumes appeared to favor the latter, the reduction of methane estimates when feeding tropical legumes is less than that of supplementing concentrate feeds to grasses. In terms of intensity of methane emissions, a good potential was observed when herb legumes were fed mixed with a grass and supplemented with a concentrate, highlighting the complementarity and the potential that exists in diets containing all these feed resources.

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Received: November 22, 2022; Accepted: June 15, 2023

^*Email: [e-mail]

Data availability, Funding & Conflict of Interest: The database used for this study is available upon request to the authors. No funding was utilized for the execution of this study. The authors declare no conflict of interest.

Author´s contribution: J.M. Castro-Montoya: Conceptualization, Methodology, Formal analysis, Data curation, Writing - original draft, Visualization. Mizeck Chagunda: Conceptualization, Writing - Review & Editing