© The Authors, 2024, Published by the Universidad del Zulia*Corresponding author:fernando.molina@unach.mx
Keywords:
Energy eciency
Greenhouse gases
Livestock
Impact of agroecological technologies on energy eciency and greenhouse gas emission in a
livestock system in Chiapas, Mexico
Impacto de tecnologías agroecológicas sobre la eciencia energética y la emisión de gases de efecto
invernadero en un sistema ganadero en Chiapas, México
Impacto das tecnologias agroecológicas na eciência energética e na emissão de gases de efeito
estufa em um sistema pecuário em Chiapas, México
Luis Fernando Molina Paniagua
1
*
René Pinto Ruiz
2
Francisco Guevara Hernández
2
Manuel Alejandro La O Arias
2
Deb Raj Aryal
2
Roberto Berrones Hernández
3
Rev. Fac. Agron. (LUZ). 2024, 41(3): e244123
ISSN 2477-9407
DOI: https://doi.org/10.47280/RevFacAgron(LUZ).v41.n3.04
Crop production
Associate editor: Professor Juan Vergara-López
University of Zulia, Faculty of Agronomy
Bolivarian Republic of Venezuela
1
Doctorado en Ciencias Agropecuarias y Sustentabilidad,
Universidad Autónoma de Chiapas.
2
Universidad Autónoma de Chiapas, Facultad de Ciencias
Agronómicas, carretera Ocozocoautla - Villaores km 84.5,
Villaores, Chiapas, México, C. P. 30470.
3
Universidad Politécnica de Chiapas, carretera Tuxtla
Gutiérrez - Portillo Zaragoza Km 21+500, Las Brisas, 29150
Suchiapa, Chiapas.
Received: 29-05-2024
Accepted: 15-07-2024
Published: 02-08-2024
Abstract
To mitigate greenhouse gas (GHG) emissions in the agricultural
sector, it is necessary to propose alternatives based on a systemic
vision and agroecological principles that allow for more ecient
use of energy within the systems. The objective of this study was to
evaluate three agroecological technologies by quantifying energy
use and its relationship with GHG emissions and mitigation, to
contribute to the sustainable management of a livestock system in
Frailesca, Chiapas, Mexico. An ex-post facto study was conducted
to establish ve technological scenarios, based on combinations of
the use of the three agroecological technologies, to calculate energy
eciency (EE) and estimate GHG, for which energy equivalences
of the inputs and outputs of the production system were used. For
the livestock system with conventional management, the energy
eciency was 0.63, generating a GHG emission of 93,153.96 kg
of CO
2
eq in a period of six months; By incorporating combinations
of the three agroecological technologies (compost, bio slurry and
silvopastoral system) the energy eciency increased to 0.82 and the
GHG emission decreased to 71,523.63 kg of CO
2
eq. It is concluded
that these agroecological technologies can be implemented in
livestock systems in Chiapas, Mexico to contribute to the mitigation
of GHG.
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Rev. Fac. Agron. (LUZ). 2024, 41(3): e244123 July-September. ISSN 2477-9407.
2-7 |
Resumen
Para mitigar las emisiones de gases de efecto invernadero
(GEI) en el sector agropecuario es necesario plantear alternativas
fundamentadas con una visión sistémica y principios agroecológicos,
que permitan hacer más eciente el uso de la energía dentro de los
sistemas. El objetivo de este estudio fue evaluar tres tecnologías
agroecológicas a través de la cuanticación del uso de la energía y
su relación con la emisión y mitigación de GEI, para contribuir al
manejo sostenible de un sistema ganadero en la Frailesca, Chiapas,
México. Se realizó un estudio ex-post facto para establecer cinco
escenarios tecnológicos, basados en combinaciones del uso de las
tres tecnologías agroecológicas, para el cálculo de la eciencia
energética (EE) y la estimación de GEI, para lo cual se utilizaron
equivalencias energéticas de las entradas y salidas del sistema de
producción. Para el sistema ganadero con manejo convencional la
eciencia energética fue 0,63, generando una emisión de GEI de
93.153,96 kg de CO
2
eq en un periodo de seis meses; al incorporar
combinaciones de las tres tecnologías agroecológicas (composta,
biol y sistema silvopastoril) la eciencia energética aumentó a 0,82 y
la emisión de GEI disminuyó a 71.523,63 kg de CO
2
eq. Se concluye
que dichas tecnologías agroecológicas pueden ser implementadas
en los sistemas ganaderos de Chiapas, México para contribuir a la
mitigación de GEI.
Palabras clave: eciencia energética, gases de efecto invernadero,
ganadería.
Resumo
Para mitigar as emissões de gases de efeito estufa (GEE) no setor
agrícola, é necessário propor alternativas baseadas em uma visão
sistêmica e em princípios agroecológicos, que tornem mais eciente
o uso de energia dentro dos sistemas. O objetivo deste estudo foi
avaliar três tecnologias agroecológicas através da quanticação do
uso de energia e sua relação com as emissões e mitigação de GEE,
para contribuir para a gestão sustentável de um sistema pecuário
em La Frailesca, Chiapas, México. Foi realizado um estudo ex-
post facto para estabelecer cinco cenários tecnológicos, a partir de
combinações do uso das três tecnologias agroecológicas, para o
cálculo da eciência energética (EE) e a estimativa de GEE, para os
quais as equivalências energéticas dos insumos e saídas do sistema
de produção. Para o sistema pecuário com manejo convencional,
a eciência energética foi de 0,63, gerando emissão de GEE de
93.153,96 kg de CO
2
eq no período de seis meses; Ao incorporar
combinações das três tecnologias agroecológicas (compostagem, biol
e sistema silvipastoril) a eciência energética aumentou para 0,82 e
a emissão de GEE diminuiu para 71.523,63 kg de CO
2
eq. Conclui-
se que estas tecnologias agroecológicas podem ser implementadas
nos sistemas pecuários de Chiapas, México, para contribuir para a
mitigação de GEE.
Palavras-chave: eciência energética, gases de efeito estufa,
pecuária.
Introduction
In countries where livestock farming is intensive, GHG
mitigation eorts have focused on increasing productivity by
improving feed quality and the genetic potential of animals (Gastelen
et al., 2023). However, there are practices with a systemic view of
livestock farming, applying sustainability criteria in the management
of soil, water and biodiversity, based on agroecological principles.
One alternative to reduce GHG emissions in livestock systems is to
increase energy eciency by optimising the recycling of nutrients
through carbon sequestration in the soil and biomass of production
systems, which would contribute to reducing energy losses that occur
in conventional production systems (Cevallos et al., 2019). Some
agroecological technologies allow these objectives to be achieved,
such as silvopastoral systems that store carbon in biomass (Aryal
et al., 2018) and the production of fertilisers, such as composts and
biols, as an option for recycling livestock manure (Venegas-Venegas
et al., 2023).
Despite this, these agroecological technologies are not
implemented in most livestock systems in Chiapas, where the use of
external inputs is widespread, and the amount of energy input and
output in these systems, and how it contributes to GHG emissions,
is largely unknown. In this context, the objective of this study was to
evaluate the implementation of agroecological technologies through
the quantication of energy use and its relationship with GHG
emission and mitigation, in order to contribute to the sustainable
management of a livestock system in Frailesca, Chiapas.
Materials and Methods
Description of the study area
The research was carried out in the ranch ‘Los Flamboyanes’,
which is representative of local production systems and is located
in the Frailesca region, municipality of Villaores, Chiapas, Mexico.
Municipality between the parallels 16° 14′ 1″ N, 93° 16′ 0″ W, at
an altitude of 840 m above sea level and with an annual rainfall
of 1200 mm. The rainy period is ve months and the dry period is
seven months, where cattle are stabled. During the dry period, the
diet consists of providing the cattle with maize silage (Zea mays),
sorghum sudan forage (Sorghum x drummondii) and ground dried
grass (Andropogon gayanus). During milking, 1 kg of concentrated
feed is oered for every 4 kg of milk produced and mineral salts are
freely available. Other activities carried out are milking, cleaning
of the milking parlour and pens, loading the biodigester with cattle
manure and insemination of the cows. Inputs such as electricity,
diesel, chemical fertilisers, agrochemicals and others are used for
these activities.
Conceptualisation of the production system
Using the production systems approach, boundaries, components,
interactions, inputs and outputs related to EE and GHG emissions
of the livestock system were identied (Guevara-Hernández et al.,
2018). Subsequently, a delimitation of the primary production area
within the livestock system, which is the dairy herd, was carried out,
specifying the interactions between the components of the system
with respect to energy use and GHG emission. With this information,
the livestock system and the dairy herd subsystem were schematized.
Data collection
Data collection was performed daily during the drought period
(November to April), by means of registers and tours of the ranch,
which allowed descriptions of the work, quantication of inputs and
labour.
Calculation of energy eciency
Energy equivalences were compiled for each input used in
each component, as well as for the outputs of the livestock system
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Molina et al. Rev. Fac. Agron. (LUZ). 2024 41(3): e244123
3-7 |
(Martínez-Aguilar et al., 2021). Subsequently, a database was
created in a Microsoft Excel
®
spreadsheet, Version 16.77.1 (2019),
where the measured variables were multiplied with their respective
energy equivalence. Specic information on inputs, outputs and
energy values were processed using the methodology and parameters
proposed by Guevara-Hernández et al. (2018).
Greenhouse gas emission and mitigation of the livestock
system. The GHG emission estimation was performed by segments,
i.e. based on the components identied in the conceptualisation of the
livestock system, in particular, those that are part of the dairy herd
subsystem. The components assessed for GHG emissions were the
agricultural components (maize, sudan sorghum and grain sorghum
plots) and the livestock component (enteric fermentation and
manure produced and stored). For GHG mitigation, the components
silvopastoral system, biodigester (biol and biogas) and composting
were considered.
Estimation of GHG emissions from agricultural components
With the previously obtained data, GHG emissions associated
with agricultural production, transport and inputs were estimated. For
these estimates, equivalences provided by Olesen et al. (2004) were
used, which provides approximations of the implications of energy
use in agriculture for GHG emissions.
Estimation of enteric methane production
Methane production was estimated based on dry matter intake of
the dairy herd, with the regression equation proposed by Niu et al.
(2021), CH
4
= (107 + 14.5 × DMI) × 0.05565, where; DMI is dry
matter intake.
Estimation of GHG emission from stored manure
The daily manure production of the dairy herd was weighed in
15 random samples. This information was used to estimate the daily
manure production per cow for 6 months. Based on the equivalences
proposed by Hao and Laney (2017) on GHG emissions during cattle
manure storage, the daily emissions from manure stored in the dairy
herd subsystem were estimated.
Estimation of carbon storage in the silvopastoral system
For above-ground biomass, a forest inventory was carried out
directly to quantify the number of trees, diameter at breast height
(DBH) and height. For juvenile trees between 2.5 cm and 9.5 cm
DBH, the methodology proposed by Gómez-Castro et al. (2010)
was used. For trees with DBH less than 2.5 cm, destructive sampling
was performed with 40 trees, generating the following regression
equation:
Y = 81.91e
1.0231DBH
Where Y = biomass (kg.tree
-1
) and DBH = diameter at breast
height.
To determine the carbon stored, the biomass of juvenile trees and
trees with DBH less than 2.5 cm were summed and multiplied by 0.47
(López-Hernández et al., 2023).
Estimation of methane and carbon dioxide generation in the
biodigester
The daily biogas production was estimated by means of a
gas ow meter, subsequently, by means of gas chromatography,
the composition of the biogas (methane and carbon dioxide) was
determined, which allowed the GHG to be calculated.
Estimation of energy eciency and GHG mitigation with
dierent agroecological scenarios
An ex-post facto study was carried out where ve possible
GHG mitigation technology scenarios were considered (table 1).
Conventional management was considered as the one where practices
requiring high use of external inputs and no agroecological practices
are used.
Results and discussion
Conceptualisation of the livestock system and primary
production subsystem
The study area was delimited to the dairy herd as a subsystem
(gure 1). The ranch has an area of 62.5 ha, of which 39.5 % is
forest area of oak (Quercus peduncularis) and holm oak (Quercus
acutifolia), 36.3 % is pasture, 17.9 % is agricultural plots of maize,
grain sorghum and forage, 3.6 % is intensive silvopastoral system,
2.2 % is facilities area and, nally, 0.5 % represents a small orchard.
For feeding the dairy cattle, 79.1 t of maize silage, 44.35 t of sorghum
sudan fodder, 21.76 t of sorghum fortuna fodder, 3.7 t of grain
sorghum and 1.6 t of sorghum stubble were harvested within the
system; 14.3 t of concentrate feed were purchased as external feed
inputs. Nine hundred litres of diesel were used to operate the tractor
and 6,585 kW of electric power for the irrigation system and the
mechanical milking machine. The main output of the dairy herd was
the production of 39.87 t of milk in six months and, as by-products
of the cattle manure, compost, biol and biogas were generated. The
analysis of the livestock system in the conceptualisation allowed
it to be considered an agroecological ranch in transition, as it has
characteristics of agroecological systems such as nutrient recycling
and decreased soil degradation by producing manure, as well as the
presence of forested areas and live fences (Cevallos et al., 2019).
Table 1. Scenarios proposed with agroecological technologies in the livestock system and dairy herd subsystem.
Conventional (kg)
Scenario 1
biol (kg)
Scenario 2
compost (kg)
Scenario 3 SSP
(kg)
Scenario 4
biol and compost
(kg)
Scenario 5
biol, compost and
SSP (kg)
Chemical fertilizer 3,300 943 200 3,300 335 335
Biol 0 434,713 0 0 178,670 178,670
Compost 0 0 62,939 0 39,519 39,519
Sudan sorghum fodder 44,350 44,350 44,350 14,969 44,350 14,969
SSP forage 0 0 0 29,361 0 29,361
SSP: Silvopastoral system.
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Rev. Fac. Agron. (LUZ). 2024, 41(3): e244123 July-September. ISSN 2477-9407.
4-7 |
Figure 1. Conceptualization of the components and relationships of the dairy herd subsystem.
Energy eciency of the maize plot component and the dairy
herd subsystem with dierent agro-ecological scenarios
The results are presented in table 2. For the maize plot component,
the rst scenario involved the incorporation of biol, where the EE
increased from 3.17 (conventional) to 4.58. For the second scenario
using compost, the best EE was obtained, reaching 6.62, and in
scenarios four and ve the EE also improved reaching a value of 5.86.
The results in table 2, for the maize plot, are higher than those
found by Guevara-Hernández et al. (2015), who obtained ES between
0.99 and 1.12 in maize production systems in the buer zone of the
‘La Sepultura’ Biosphere Reserve in Chiapas, Mexico. Martínez-
Aguilar et al. (2021), calculated EE between 9.87 and 17.37, in
several types of maize production systems in the Frailesca, Chiapas,
Mexico, characterised by the low use of external inputs, which prove
to be highly ecient.
For the dairy herd subsystem, the EE increased by 30.15 %
when incorporating agroecological technologies. The best result
was obtained in scenario 5, with the use of biol, compost and SSP,
reaching a value of 0.82, while with conventional management it
was 0.63. These results are in agreement with Llanos et al. (2013),
where they obtained energy eciencies of 0.69, 0.94 and 1.53, in
three dierent livestock strata in dairy farms in Uruguay. Moreover,
they are higher than those reported by Gimenez et al. (2022), with
EE between 0.26 and 0.64 in Argentinean dairies. The increase of EE
in the maize plot, altered the eciency in the dairy herd subsystem,
since the maize silage was used for feeding the dairy herd, in addition
to this, the SSP also makes an additional contribution to the increase
in eciency, because it is a forage produced with high EE (15.54),
being the component with the highest eciency within the livestock
system.
Livestock enteric methane and GHG production from stored
manure
The dairy herd consisted of 43 Jersey cows, the total enteric
methane production during the six months of study was 2,572,402.86
L (1,546.91 kg CH
4
), the daily production of enteric methane per
animal was 330 L.day
-1
(198 g.cow
-1
) with a consumption of 10.23
kg DM, slightly higher than that reported by Abarca-Monge et al.
(2018), with Jersey and crossbred cows, where they mention that
methane production in dairy cows was 265.7 g.cow
-1
.day
-1
, with an
average consumption of 16 kg DM per day.
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Molina et al. Rev. Fac. Agron. (LUZ). 2024 41(3): e244123
5-7 |
Table 2. Energy parameters with conventional management and incorporating agroecological technologies in the maize plot and dairy
herd components.
Component Scenario* Energy eciency Input energy (MJ.ha
-1
)
Energy cost of
protein (MJ.kg
-1
)
Labour energy
productivity (h.MJ
-1
)
Protein labour
productivity (h.kg
-1
)
Maize plot
Conventional 3.17 16,226.27 44.62 0.00265 0.37473
Scenario 1 4.58 11,232.81 30.89 0.00354 0.50082
Scenario 2 6.62 7,778.30 21.39 0.00286 0.40459
Scenario 3** 3.17 16,226.27 44.62 0.00265 0.37473
Scenario 4 5.86 8,780.93 24.14 0.00315 0.44544
Scenario 5** 5.86 8,780.93 24.14 0.00315 0.44544
Dairy herd
Conventional 0.63 32,112.64 138.03 0.00918 0.80322
Scenario 1 0.71 28,684.55 123.29 0.00918 0.80322
Scenario 2 0.77 26,323.23 113.14 0.00918 0.80322
Scenario 3 0.68 29,806.35 128.11 0.00918 0.80322
Scenario 4 0.75 27,007.19 116.08 0.00918 0.80322
Scenario 5 0.82 24,700.90 106.17 0.00918 0.80322
*The characteristics of each scenario can be found in table 1.
**Scenarios that include the SSP do not aect the maize plot component, as there is no interaction between the two components.
The dairy herd produced 144,904.25 kg of manure during six
months, for scenario 2 (table 3), this amount of manure generated an
emission of 4,644 kg of CO
2
, 396.52 kg of CH
4
and 6.92 kg of N
2
O,
being 15,118 kg CO
2
eq. Scenarios 4 and 5 (table 3) consider the use
of compost and biol, the amount of manure used for composting was
90,984 kg, which produced 2,916.51 kg of CO
2
, 248.97 kg of CH
4
and 4.35 kg of N
2
O, which is expressed as 9,492.5 kg of CO
2
eq. In
relation to these data, Gastelen et al. (2023), mention that emissions
from enteric fermentation and cattle manure corresponded to 46.5 %
of the total carbon footprint associated with milk production, in the
present work in the dairy herd subsystem this proportion was 51.1 %
with conventional management.
Methane and carbon dioxide generation in the biodigester
In scenario 1 (table 3), the use of 144,904.25 kg of manure for
biodigestion was considered, estimating a production of 6.377 m
3
of
biogas in six months, the composition of the biogas was 60.3 % CH
4
and 38.6 % CO
2
, generating 2,350.76 kg of CH
4
and 4,071.39 kg of
CO
2
, which is equivalent to 53,437 kg of CO
2
eq, when the biogas is
combusted it is transformed into 10,535.98 kg of CO
2
.
Table 3. GHG emissions in manure treated by composting and biodigestion.
Manure treatment Scenario Manure (kg) CO
2
(kg)
CH
4
(kg)
N
2
O
(kg)
CO
2
eq SCB
(kg)
CO
2
eq
CB (kg)
Biodigestion
Scenario 1 144,904.25 4,071.39 2,350.76 0 53,437 10,535.98
Scenario 4 and 5 53,920 1,514 874.73 0 19,884.46 3,920.52
Compost
Scenario 2 144,904.25 4,644 396.52 6.92 15,118 NC
Scenario 4 and 5 90,984 2,916.51 248.97 4.35 9,492.5 NC
NC = No combustion. SBC = No biogas combustion. BC = Combustion of biogas.
The composition of the biogas is in agreement with Suarez-
Chernov et al. (2019), who present results of methane between 50-70 %
and carbon dioxide between 25-50 % for biogas produced from cattle
manure. In scenarios 4 and 5 (table 3), the amount of manure used for
the biodigester was 53,920 kg, the estimate of biogas produced was
2,372.95 m
3
, therefore, the GHG generation was 874.73 kg CH
4
and
1. 514 kg of CO
2
, which is equivalent to 19,884.46 kg CO
2
eq, with the
combustion of the biogas being transformed into 3,920.52 kg CO
2
,
generating a mitigation of 15,963.93 kg CO
2
. Venegas-Venegas et al.
(2023) reported that biogas, with a composition of 60 % CH
4
and 40
% CO
2
, contains 22.81 MJ of energy per m
3
, so the biodigester used
in this livestock system has the potential to substitute 54,128.13 MJ
of energy, which is equivalent to mitigating 11,438.63 kg of CO
2
eq.
Carbon storage in the silvopastoral system
In the intensive SSP with Leucaena leucocephala, a population
of 860 juvenile trees with DBH greater than 2.5 cm and 37,460
juvenile trees with DBH less than 2.5 cm per hectare was estimated.
The amount of carbon stored in two years since its establishment
was 3,205 kg, equivalent to 11,764 kg of CO
2
; for GHG mitigation,
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Rev. Fac. Agron. (LUZ). 2024, 41(3): e244123 July-September. ISSN 2477-9407.
6-7 |
the amount stored in six months, 2,941 kg of CO
2
, was considered.
López-Hernández et al. (2023) reported carbon storage values in
livestock systems in Chiapas, Mexico, between 0.5 and 15.5 Mg C.ha
-1
,
depending on the age of the SSP.
GHG generation and mitigation in the maize plot, livestock
system and dairy herd subsystem with agroecological technologies
Greenhouse gas generation decreased in the livestock system with
the incorporation of agroecological technologies, specically in the
maize plot and dairy herd subsystem components, as shown in table 4.
On the maize plot, with the incorporation of the biol in scenario 1,
GHGs were reduced from 27,756.64 kg CO
2
eq to 10,933.32 kg CO
2
eq
and using compost in scenario 2 gave the best result with 4,141.62 kg
CO
2
eq. Scenarios 4 and 5 emitted 5,629.52 kg CO
2
eq. As the SSP
(scenario 3) has no interaction with the maize plot component, it does
not aect the GHG emission.
Scenario 5 of the dairy herd subsystem generated the lowest GHG
emissions, where the components corn silage, sorghum sudan, and
sorghum fortuna contributed 3,395, 2,025.27 and 4,426 kg CO
2
eq,
respectively. The green fodder cutting activity produced 379 kg
CO
2
eq, stubble grinding generated 1,629 kg CO
2
eq, balanced feed
contributed 14,240 kg CO
2
eq and hauling silage and green fodder to the
feed bunkers generated 677 and 178 kg CO
2
eq, respectively. Electric
power for milking emitted 1,144 kg CO
2
eq, enteric fermentation
contributed more GHGs with 35,653 kg CO
2
eq, which is equivalent
to 1,546.9 kg CH
4
, manure produced and stored generated 9,492
kg CO
2
eq; and the biodigester with the combustion gas generated
3,921 kg CO
2
eq. These results show that the use of agroecological
technologies decreases GHG emissions in this livestock system. The
use of compost and biol in the maize plot decreased GHG emissions
by 79.71 % for this agricultural component by substituting industrial
energy with ecological energy by recycling nutrients (Cevallos et al.,
2019). By combining the use of these fertilisers in the agricultural
plots with the intensive silvopastoral system, 21,630.33 kg CO
2
eq of
the dairy herd subsystem were mitigated, representing 23.22 % of the
total GHG emissions.
Table 4. GHG emissions of the maize plot component and the dairy herd subsystem with agroecological scenarios.
Component Scenario*
CO
2
(kg)
CH
4
(kg)
N
2
O
(kg)
CO
2
eq
(kg)
CO
2
eq (kg.ha
-1
) CO
2
eq (kg.kg
-1
MS)
Maize plot
Conventional 11,656.68 27.24 50.09 27,756.64 3,965.23 0.6896
Scenario 1 6,169.82 11.15 14.61 10,933.32 1,561.90 0.2716
Scenario 2 3,029.83 4.32 3.29 4,141.62 591.66 0.1029
Scenario 3** 11,656.68 27.24 50.09 27,756.64 3,965.23 0.6896
Scenario 4 3,840.90 5.86 5.37 5,629.52 804.22 0.1399
Scenario 5** 3,840.90 5.86 5.37 5,629.52 804.22 0.1399
Dairy herd
Conventional 27,893.89 1,993.37 75.48 93,153.96 15,097.89 17.55
Scenario 1 30,476.41 1,587.15 47.16 78,427.54 12,711.11 14.78
Scenario 2 22,691.94 1,979.55 47.26 78,914.21 12,789.99 14.87
Scenario 3 22,675.65 1,988.62 71.40 86,571.20 14,030.99 16.31
Scenario 4 25,373.12 1,832.93 45.94 78,106.39 12,659.06 14.72
Scenario 5 20,154.88 1,828.17 41.86 71,523.63 11,592.16 13.48
*The characteristics of each scenario can be found in table 1.
**Scenarios that include the SSP do not aect the maize plot component, as there is no interaction between the two components.
Taking the following indicators as a reference, with the use of
three agroecological technologies, dairy herd emissions decreased
from 2.01 kg CO
2
eq.kg
-1
milk equivalent to 1.83 kg CO
2
eq.kg
-1
energy-corrected milk (ECM) to 1.51 kg CO
2
eq.kg
-1
milk equivalent
to 1.40 kg CO
2
eq.kg
-1
ECM. These results are higher than those
reported by Ridha (2013), where he estimated GHG emissions from
several dairy herds in three regions of Spain, with the lowest value
being 0.59 kg CO
2
eq.kg
-1
ECM and the highest value being 1.09 kg
CO
2
eq.kg
-1
ECM.
Despite the improvement in GHG emissions from the dairy herd
subsystem, in order to contribute signicantly to GHG mitigation,
it is recommended to: 1) Increase the productive eciency of the
animals; 2) Increase the area of the intensive silvopastoral system; 3)
Decrease diesel consumption; 4) Incorporate tropical forage varieties
that decrease the production of enteric methane; and 5) Estimate the
carbon sequestration of the forest area.
Conclusions
The use of agroecological technologies in the livestock system
increased energy eciency and decreased greenhouse gas emissions
as a result of the substitution of fossil inputs and carbon sequestration.
The results of this research suggest the use of agroecological
technologies such as composting, silvopastoral system and
biodigesters in livestock units in Chiapas, to contribute to ecient
energy management and, therefore, mitigate GHG.
Acknowledgements
The authors dedicate this work to Dr. Heriberto Gómez Castro,
who was a fundamental pillar of the Academic Body of Livestock
Agroforestry at the Universidad Autónoma de Chiapas, Facultad de
Ciencias Agronómicas. Part of his work and ideas over the years are
immersed in this research.
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Molina et al. Rev. Fac. Agron. (LUZ). 2024 41(3): e244123
7-7 |
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