© The Authors, 2025, Published by the Universidad del Zulia*Corresponding author: ciro.ortiz@unillanos.edu.co
Keywords:
Livestock
Typologies
Multivariate analysis
Agroecosystem
Characterization of bovine production system typologies on indigenous reservations
(Etnia-Pijao) at Natagaima-Tolima, Colombia
Caracterización de tipologías del sistema de producción bovina en los resguardos indígenas
(Etnia-Pijao) de Natagaima-Tolima, Colombia
Caracterização de tipologias de sistemas de produção bovina em reservas indígenas (Etnia-Pijao) no
Natagaima-Tolima, Colômbia
Ciro Ortiz-Valdes
1*
José Guillermo Velázquez-Penagos
2
Gloria Estefanía Pastrana-Aguirre
1
Jorge Humberto Arguelles-Cárdenas
3
Hernando Flórez-Díaz
3
Yohaira Andrea Pérez-Guerrero
4
Rev. Fac. Agron. (LUZ). 2025, 42(3): e254233
ISSN 2477-9407
DOI: https://doi.org/10.47280/RevFacAgron(LUZ).v42.n3.IV
Socioeconomics
Associate editor: Dra. Fátima Urdaneta
University of Zulia, Faculty of Agronomy
Bolivarian Republic of Venezuela
1
Investigador Independiente, Yopal, Colombia.
2
Investigador Independiente, Villavicencio, Colombia.
3
Corporación Colombiana de Investigación Agropecuaria
(AGROSAVIA), Centro de Investigación La Libertad,
Villavicencio, Colombia.
4
Universidad Internacional del Trópico Americano, Yopal,
Colombia.
Received: 13-03-2025
Accepted: 06-06-2025
Published: 07-07-2025
Abstract
In southern Tolima, Colombia, the Indigenous Reservations
(IR) of the Pijao ethnic group depend on cattle ranching, but their
productive dynamics are poorly understood, making it dicult
to design sustainable models. The objective of this study was to
characterize the emerging typologies of the bovine production
system of these IR by considering the sociocultural, techno-
economic, and environmental processes. In 2023, a semi-structured
interview was conducted in fteen production units (PU) of the
twenty-nine existing in the area. Indicators from each dimension
(techno-economic, sociocultural, and environmental) were analyzed
through multivariate analysis, identifying three typologies: G1
(46.6 %), composed by small IRs whith technology low level,
showing a small-scale production; G2 (26.7 %), also grouped small
IRs with small-scale production but moderately technied; and G3
(26.7 %) was integrated by large IRs, moderately technied and
with a medium scale production. G3 stood out for some indicators
of the techno-economic dimension. Although, all groups showed
a low level of technological adoption, which resulted in poor
productive and reproductive performance. The dierences in G3’s
better economic outcomes are due to its larger scale of production.
In the social sphere, female leadership stood out, especially in
groups with the highest proportion of trained people (G2 and G3).
Overall, the PUs showed soils with poor organic matter content,
low fertility level, little forest coverage and a moderate degree of
erosion, indicating some alterations of the agroecosystem.
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). 2025, 42(3): e254233 July-September. ISSN 2477-9409.
2-6 |
Resumen
En el sur del Tolima, Colombia, los Resguardos Indígenas (RI)
de la etnia Pijao dependen de la ganadería, pero sus dinámicas
productivas son poco conocidas, lo que diculta el diseño de
modelos sostenibles. El objetivo de este estudio fue caracterizar las
tipologías emergentes del sistema de producción bovina de estos
RI considerando los procesos socioculturales, tecnoeconómicos y
ambientales. En 2023, se realizó una entrevista semiestructurada en
quince unidades de producción (UP) de las veintinueve existentes
en la zona. Los indicadores de cada dimensión (tecnoeconómica,
sociocultural y ambiental) fueron analizados mediante análisis
multivariado, identicando tres tipologías: El G1 (46,6 %),
compuesto por RI pequeños, con bajo nivel tecnológico y producción
a pequeña escala; el G2 (26,7 %), agrupó también a RI pequeños
con producción a pequeña escala, pero moderadamente tecnicados;
y el G3 (26,7 %) estaba integrado por RI grandes, moderadamente
tecnicados y con una producción a mediana escala. El G3 se
destacó en algunos indicadores de la dimensión tecnoeconómica.
Sin embargo, todos los grupos mostraron un bajo nivel de adopción
tecnológica, lo que resultó en un pobre desempeño productivo y
reproductivo. Las diferencias en los mejores resultados económicos
del G3 se deben a su mayor escala de producción. En el ámbito social,
se destacó el liderazgo femenino, especialmente en los grupos con
mayor proporción de personas formadas (G2 y G3). En general, las
UPs mostraron suelos con pobre contenido de materia orgánica, bajo
nivel de fertilidad, escasa cobertura forestal y un moderado grado de
erosión, indicando algunas alteraciones del agroecosistema.
Palabras clave: ganadería, tipologías, análisis multivariado,
agroecosistema.
Resumo
No sul de Tolima, Colômbia, as Reservas Indígenas (RI) da
etnia Pijao dependem da criação de gado, mas suas dinâmicas
produtivas são pouco conhecidas, dicultando o desenho de modelos
sustentáveis. O objetivo deste estudo foi caraterizar as tipologias
emergentes do sistema de produção bovina dessas RI, considerando
os processos socioculturais, tecnoeconômicos e ambientais. Em 2023,
foi realizada uma entrevista semi-estruturada em quinze unidades de
produção (UP) das vinte e nove existentes na área. Os indicadores
de cada dimensão (tecnoeconômica, sociocultural e ambiental)
foram analisados por meio de análise multivariada, identicando três
tipologias: O G1 (46,6 %), composto por pequenas RI, com baixos
níveis de tecnologia e produção em pequena escala; o G2 (26,7 %),
também agrupava pequenas EIs com produção em pequena escala,
mas moderadamente tecnicadas; e o G3 (26,7 %) era integrado por
grandes RI, moderadamente tecnicadas e com produção em média
escala. O G3 destacou-se em alguns indicadores da dimensão tecno-
económica. No entanto, todos os grupos apresentaram um baixo
nível de adoção tecnológica, o que resultou num fraco desempenho
produtivo e reprodutivo. As diferenças nos melhores resultados
económicos do G3 devem-se à sua maior escala de produção. Na
esfera social, a liderança feminina destacou-se, sobretudo nos grupos
com maior proporção de pessoas formadas (G2 e G3). No geral, as
UPs apresentaram solos com baixo teor de matéria orgânica, baixo
nível de fertilidade, pouca cobertura orestal e um grau moderado de
erosão, indicando algumas alterações do agroecossistema.
Palavras-chave: pecuária, tipologias, análise multivariada,
agroecossistema.
Introducción
There are about 476 million indigenous peoples worldwide,
representing 6.2 % of the world’s population. Their territories cover
28 % of the planet’s surface and account for 11 % of the world’s
forests (Food and Agriculture Organization of the United Nations
[FAO], 2024). The ways of life and subsistence of these ethnic groups
integrate elements that allow food production in harmony with nature.
This is related to local ecological knowledge, forest conservation,
native crops and agricultural practices that are resilient to climate
change (FAO, 2024). These production models are considered to have
the potential to feed the world based on the structuring of sustainable
agrifood systems in the world.
There are 1.9 million indigenous people in Colombia, of whom
62,836 live in the department of Tolima and 6,845 in the Natagaima-
Tolima municipality. (Departamento Administrativo de Estadística
de Colombia [DANE], 2018). Most of this population belongs
to the Pijao ethnic group, native peoples of Tolima, who live and
develop their activities in rural areas, based on the interrelationship
of spirits, gods and mother earth; they are mostly organized as
Indigenous Reservations (IR) and use a large part of their territory
for cattle ranching, becoming one of their main economic activities
(Organización Nacional Indígena de Colombia [ONIC], 2024).
However, there is very scarce information that allows a more precise
understanding of the dynamics and interrelationship of the socio-
cultural, technical-economic and environmental processes of these
productive units (UP), which is of utmost importance for planning
the care of these communities.
Some published references on the socioeconomic dynamics of
these livestock systems showed its realtionship to a low technological
adoption, production backwardness, limited development of the
value chain and low competitiveness (Arrieta-González et al., 2022).
These conditions are closely related to the conventional dual-purpose
bovine system (SDPBC) in Colombia, where more than 60 % of
the UPs develop forms of production focused on an animal feeding
model based on grazing, stocking rate of 0.5 AU.ha
-1
, in pastures with
predominantly gramineae cover, mostly overgrazed (Parodi et al.,
2022; González-Quintero et al., 2020). This management, leads to a
soil degradation and water contamination, and also favors indirectly
deforestation processes (Parodi et al., 2022). Finally, these conditions
are expressed in a poor agribusiness technical-economic performance
since they can barely produce 44.5 kg of meat.cow
-1
.year
-1
, 483.3 L
of milk.cow
-1
.year
-1
and the protability is below 14 % (Ortiz-Valdes
et al. 2023). In the same way, it is likely that IRs are immersed
in a production model far removed from their cultural identity,
contributing to the progressive degradation of their agroecosystems
and the deterioration of the quality of life of these ethnic groups.
Characterization and typication processes are important as
mechanisms to identify limitations and opportunities in order to
promote changes in the socio-cultural, technical-economic and
environmental components of UPs (Cuevas-Reyes and Rosales-Nieto,
2018). This favors the approach of viable production alternatives to
improve technical-economic performance, considering a reduction
in environmental impact and a better linkage with local ecological
knowledge (Arrieta-González et al., 2022). The objective of this paper
was to characterize the typologies of productive units considering the
socio-cultural, technical-economic and environmental processes of
the RI cattle production system (Pijao ethnic group) at Natagaima-
Tolima municipality, Colombia.
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Ortiz-Valdes et al. Rev. Fac. Agron. (LUZ). 2025, 42(3): e254231
3-6 |
Materials y methods
Study area
This study was carried out in the bovine productive units of
the indigenous reservations (Pijao ethnic group), Municipality of
Natagaima-Tolima, Colombia, located at coordinates 3°37’18.0 “N
75°05’36.2 ”W. This region corresponds to the tropical dry forest
life zone, between 0-1000 masl, with an average temperature of 32
°C. It is also characterized by precipitation between 1,000 and 1,500
mm per year, with a bimodal climatic regime, with two dry seasons
(December-March and July-September) and two rainy seasons
between April-June and October-December (Instituto de Hidrología,
Meteorología y Estudios Ambientales (IDEAM, 2024).
Sampling thecnique and sample size
A non-probabilistic convenience sampling was used (Otzen and
Manterola, 2017), given the need to have the voluntary participation
of the communities, the legally constituted indigenous reserves were
selected and they expressed their voluntary willingness to participate
in the research. The study included fteen IRs out of the twenty-nine
existing in the area (Ministerio de Tecnologías de la Información y las
Comunicaciones de Colombia, 2024).
Data collection and related variables.
The eldwork was carried out in the rst half of 2023. Previously,
an informed consent form was signed explaining the objectives and
scope of the study. Data were obtained through semi-structured
interviews with the indigenous leaders (governors) of each community,
using a guide designed by three expert researchers, which addressed
socio-cultural, technical-economic and environmental aspects (Table
1). In addition, data were veried through eld visits and a review of
production records.
Table 1. Description of the dimensions and indicators studied in the cattle production systems of Pijao indigenous communities of
Natagaima-Tolima, Colombia.
Sub dimension Indicators by dimension
Socio-cultural dimension
1) Social and cultural
Number of families (NF), persons (NP) and persons per family (NPF) that make up the community, time of
experience in community cattle production (TE), sex of the indigenous leader (male, female), personnel trained
in cattle management (yes, no).
Técnico-económico dimension
2) Production unit management
Livestock management area (GA), number of paddocks (NP), stocking rate (CA), number of total cows (NVT)
and milking cows (NVO), milk production (PL), technology adoption index (IAT), infrastructure index (IINFRA
and machinery (IMAQ).
3) Productive performance
Milk production per day (PLD), milk production per cow (PLV), calf weight (PD) and age at weaning (ETD),
calf weight gain/day (GPD), milk production per lactation (PLL), and eective milk (PEL) and meat (PEC)
production.
4) Reproductive performance Age at rst calving (EPP), cow days open (DA), calving interval (IEP) and birth rate (TN).
5) Economic performance
Total gross income per year (IB), production cows per year (CPA), net income per year (BN) and per family
(BNF), return on cost.
Ambiental dimension
6) Environmental
Land cover and land use (dense forest, fragmented forest, gallery forest, crops and pastures). Soil characteristics;
depth (deep or shallow), pH (alkaline, acid and neutral), organic matter (high, medium and low) and fertility
(high, medium and low), soil erosion (light, moderate and severe).
The Animal Unit measure was considered as established by
González-Quintero et al (2020). The index of machinery (IMAQ)
and infrastructure (INFRA) was calculated using an adjustment of the
methodology proposed by Cuevas-Reyes and Rosales-Nieto (2018).
The analysis of fteen implements (plow, tractor, cooling tank,
harrow, mill, chopper machine, water pump, scale, straw thermo-
storage, mechanical milking machine, rennet vats, back pump, pickup
truck, trailer and scythe) and fteen facilities (animal handling pen,
milking parlor, administrative area, maternity paddock, feeding
troughs, drinking area, salting area, electric fences, input storage, calf
grazing paddocks, pharmacy, house, calf grazing paddock, manure
management area). The indexes were calculated by dividing the
amount of equipment or facilities found in the UPs by 15 x 100.
The technological adoption index (TAI) was estimated by
adjusting the methodology proposed by Valdovinos et al. (2015),
integrating twenty-one technological components (technical and
economic records, water harvesting, deworming and vaccination,
genetic selection and improvement, integrated management of
ectoparasites, disease diagnosis, good milking practices, animal load
adjustment, pasture rotation, electric fences, forage conservation,
supplementation with balanced diets, silvopastoral systems,
fertilization of grazing areas, irrigation systems, forage banks,
mineral supplementation, articial insemination, gestation diagnosis
and reproductive evaluation of the breeding male. In the calculation
of this index, a value of 0 was considered if the producer does not
apply the technology, 0.5 if it applies it deciently and 1 if it applies
it adequately, the total value of the index being the arithmetic sum of
what was found.
The birth rate was valued considering the number of calves born
per year. The PEC and PEL and the economic performance indicators
were determined by means of the methodology used by Ortiz-
Valdes et al. (2023). The environmental variables were evaluated by
analyzing geospatial information in ArcGIS Desktop version 10.8
(Environmental Systems Research Institute (Esri, 2020). For this
purpose, the Shape type le corresponding to the Map of marine and
coastal continental ecosystems of Colombia-2017 (Ministerio de
Ambiente y Desarrollo Sostenible de Colombia (Minambiente, 2024)
was used.
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). 2025, 42(3): e254233 July-September. ISSN 2477-9409.
4-6 |
Statistical analysis
To group the IRs, a principal component analysis (PCA) was
performed, considering only quantitative variables, which represented
more than 75 % of the variables linked to the study. The PCA was
applied by blocks of subdimensions, to reduce the dimensionality of
the information and multicollinearity between variables, maintain
the conceptual coherence of the indicators, and thus improve the
robustness of the analyses in view of the available sample size (n=15).
A hierarchical cluster analysis (Ward’s algorithm) was then
performed, integrating the components of each subdimension that
explained the greatest variance in the model (cut-o point greater
than 70 %). Basic statistics (means and frequency tables) were used
to characterize the groups. In addition, the eect of the groups found
on the quantitative variables was evaluated by analysis of variance
(ANOVA), considering the typologies as a xed eect, within a
general linear model. The analysis was complemented with Tukey’s
multiple comparison tests (α=0.10). All analyses were performed by
SAS Enterprise Guide 8.3 software (SAS Institute Inc., 2020).
Results and discussion
Principal Component Analysis
The principal component analysis made it possible to select the
following components: in subdimension 1 (social and cultural), the
rst 3 PCs were selected, which explained 99.9 % of the variability;
in subdimension 2 (management of the productive unit), the rst
3 PCs were chosen which explained 74.7 % of the variability; in
subdimension 3 (productive performance), were selected the rst 2
PCs, with 80.0 %; and for dimensions 4 (reproductive performance)
and 5 (economic performance), the rst 2 PCs were selected, with
88.4 % and 98.0 %, respectively (Table 2).
Table 2. Principal components retained by thematic subdimension,
variance explained and higher factor weights variables.
Sub dimension CP
Explained
variance
(%)
Variable
Factorial
weight
Social and
cultural
1 43.85
Number of persons
0.73
Number of persons per family
0.61
2 31.93
Number of families
0.84
3 24.07
Time of experience
0.97
Production unit
management
1 38.26
Number of paddocks
0.41
Number of milking cows
0.39
Number of animals
0.33
Infrastructure index
0.40
2 23.06
Area dedicated to livestock
0.59
Animal load
-0.44
3 13.35
Technology adoption index
0.68
Machinery index
0.54
Productive
performance
1 51.14
Milk production per day
0.42
Milk production cow day
0.45
Milk production per lactation
0.51
Eective milk production
0.51
2 28.78
Final calf weight
0.66
Eective meat production
0.66
Reproductive
performance
1 56.69 Age at rts birth 0.69
2 31.78 Interval between births -0.44
Economic
performance
1 81,53
Net income per family 0,45
Gross income 0,46
Net income 0,49
2 16,51
Production cost -0,52
Return on cost 0,67
PC: principal components
PCA did not imply a large reduction in the number of variables.
However, it allowed grouping redundant information into latent
components by subdimension block, improving the robustness of the
cluster analysis, compared to the sample size (n=15) available.
Ethnic agroecosystems Typology
Based on the CPs selected in the ve thematic areas, the IRs
were classied into three groups or types of UPs, according to the
following characteristics:
Group 1 (G1): small reservations, with reduced availability of
infrastructure and small production scale (n=7; 46.6 %); group (G2):
small reservations, with moderate availability of infrastructure and
small scale of production (n: 4; 26.7 %) and group 3 (G3): Large
reservations, with moderate availability of infrastructure and medium
scale of production (n=4; 26.7 %).
Characteristics of the production unit groups
The mean comparison test between groups showed statistically
signicant dierences =0.10) to the variables: number of families,
number of people, number of animals, number of milking cows,
infrastructure index, milk production per day, calving interval, birth
rate, eective milk production, gross income, production costs, net
income, income per family, and protability (Table 3).
Groups 1 (G1) y 2 (G2)
These two groups of UP have similarities in most of the studied
characteristics. However, G2 has 15.83 more families per community,
8.67 more infrastructure index and 69.61 more days of cows calving
interval than G1 (α=0.10). In these groups, women participate in
community leadership. G1 carries out productive activities in an
empirical way, while G2 has trained personnel.
Cattle raising activity is carried out in areas with a medium sized
surface area, also with medium sized herds with scarce availability
of milking cows (Table 3). These groups reect a small technological
adoption rate (<5.85 rated from 1 to 21). Animal feeding is mainly
based on grazing, with Bothriochloa pertusa forages, using a
rotational system with low stocking rate (<0.87 AU.ha
-1
). Nutritional
supplementation is based on the supply of mineralized salt and
little amounts of corn silage that were used during the dry season
(mainly for milking cows) in some UPs. G1 and G2 showed basic
infrastructure for the management of the production system. However,
the G2 infrastructure index is higher compared to G1 (α=0.10), since
there are approximately 20 and 25 % more UP that have a pharmacy
area and maternity paddocks in G2.
These groups are characterized by an average milk production
less than 51.37 L.day
-1
and an individual production per cow lower
than 3.21 L. day
-1
, reaching a lactation anual volume less than 730.95
L. At the same time, they showed an annual birth rate less than 0.57
calves.cow
-1
and an eective annual production that did not exceed
98 kg.cow
-1
of meat and 414.64 L.cow
-1
of milk. These groups are
statistically similar in most of the economic indicators, except for net
income per family, which is $32.4 USD higher in G1 compared to G2.
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Ortiz-Valdes et al. Rev. Fac. Agron. (LUZ). 2025, 42(3): e254231
5-6 |
Table 4. Socio-cultural characteristics by typology in the cattle
production system of indigenous reserves.
Variables Categoría
G1
(n=7, %)
G2
(n=4, %)
G3
(n=4, %)
Indigenous leader
sex
Man 5 (71,4) 1 (25,0) 2 (50,0)
Female 2 (28,6) 3 (75,0) 2 (50,0)
Trained
personnel
Yes 0 (0,0) 3 (75,0) 3 (75,0)
No 7 (100,0) 1 (25,0) 1 (25,0)
Table 3. Socio-economic characteristics by typology of bovine
agrosystems on indigenous reservations.
Indicator G1 (n=7) G2 (n=4) G3 (n=4)
Social and cultural
Number of families
30.42 a 46.25 b 47.25 b
Number of persons
255.43 a 284.75 a 536.50 b
Number of persons per family
9.00 ab 6.06 a 11.5 b
Time of experience (years)
21 .71 a 23.50 a 20.75 a
Productive unit management
Livestock management area (ha)
136.3 a 73.25 a 12 .5 a
Stocking rate (AU.ha
-1
) 0.63 a 0.87 a 0.88 a
Number of total cows 66.85 a 85.25 a 153.75 b
Number of cows in milking 14.57 a 16.50 a 33.50 b
Technology adoption index (0-21) 5.85 a 4.25 a 7.25 a
Infrastructure index (0-100)
52.04 a 60.71 b 62.50 b
Machinery index (0-100) 21.9 a 28.33 a 30.00 a
Productive performance
Milk production per lactation (L) 730.95 a 709.48 a 1,108.03 b
Milk production (L.day
-1
) 39.1 a 51.37 a 133.12 a
Milk production per cow (L.day
-1
) 2.70 a 3.21 a 3.91 a
Weaning weight (kg)
172.8 a 163.75 a 176.5 a
Weight gain (kg.day
-1
)
0.54 a 0.63 a 0.52 a
Eective milk production ***
414.64 ab 362.73 a 607.17 b
Eective meat production ****
98.27 a 84.03 a 95.9 a
Reproductive performance
Age at rst birth (months) 36.80 a 37. 5 a 35.70 a
Birth interval (days)
643.19 a 712.80 b 674.41 ab
Birth rate
0.57 b 0.51 a 0.54 ab
Economic performance
Gross income (USD*) 11,973.55
a
11,241.90
a
25,364.46 b
Production costs (USD*) 10,263.70
a
10,139
.87 a
20,217.72 b
Net income (USD*)
1.709.85 a
1,102.03
a
5,146.74 b
Net income per family (USD*)
56.20 b 23.80 a 109.04 c
Return on cost (%)
16.0 ab 10.00 a 25.00 b
*
1 USD equals to $ 4,129.5 COP (exchange rate of October 29, 2023). ** (Calves. cow
-1
by year); *** (L.cow
-1
.year
-1
); **** (kg.cow
-1
.year
-1
). Dierent letters between rows indicate
signicant dierences (p<0.10), according to Tukey test.
The analysis of gross income and production costs of the two groups
showed a prot and a return on cost less than $ 1,709.85 USD and 16
%, respectively.
In these UPs, the predominant land use cover is pasture and crop
areas, with supercial soils in most of the farmlands. There was also a
predominance of soils with poor organic matter content, low fertility,
slightly acidic and acidic pH, with a predominantly moderate level of
erosion (Table 5). These physicochemical characteristics of the soil are
indicative of a degradation process. This condition can be attributed
mainly to the low forest cover, which limits water inltration capacity
and causes the soil to be more exposed to the sun. As a result, the soil’s
internal humidity is decient and its biological activity is altered. In
turn, the scarce forest cover restricts nutrient cycling and favors the
minerals washing from the soil by runo (Parodi et al., 2022).
Table 5. Environmental characteristics by typology on indigenous
reserves cattle production system.
Variables Categoría
G1
(n=7, %)
G2
(n=4, %)
G3
(n=4,
%)
Land Use
Coverage
Pasture and crops 7 (100.0) 4 (100.0) 4 (100.0)
Gallery forest 1 (14.4) 2 (50.0) 0 (0.00)
Dense forest 3 (42.8) 2 (50.0) 0 (0.00)
Fragmented forest 1 (14.4) 0 (0.00) 0 (0.00)
Soil depth
Deep 1 (14.3) 1 (25.0) 2 (50.0)
Supercial 6 (85.7) 3 (75.0) 2 (50.0)
Soil pH
Alkaline 0 (0.00) 0 (0.00) 2 (50.0)
Acid 1 (14.4) 2 (50.0) 0 (0.00)
Neutral 3 (42.8) 0 (0.00) 1 (25.0)
Slightly acidic 3 (42.8) 2 (50.0) 1 (25.0)
Soil organic
matter level
High 0 (0.00) 0 (0.00) 0 (0.00)
Medium 0 (0.00) 0 (0.00) 0 (0.00)
Low 7 (100.0) 4 (100) 4 (100.0)
Soil fertility
level
High 0 (0.00) 0 (0.00) 0 (0.00)
Moderate 3 (42.9) 1 (25.0) 4 (100.0)
Low 4 (57.1) 3 (75.0) 0 (0.00)
Soil erosion
level
Slight 0 (0.00) 0 (0.00) 1 (25.0)
Moderate 2 (28.5) 1 (25.0) 2 (50.0)
Severe 0 (0.00) 0 (0.00) 0 (0.00)
Slight to moderate 1 (14.4) 1 (25.0) 1 (25.0)
Moderate to severe 4 (57.1) 2 (50.0) 0 (0.00)
Grupo 3 (G3)
In this group, women also play a very important role in
community leadership processes, since half of the UPs are being
guided by women. These UPs are made up of a large population
size, with 281.07 and 251.75 more people per community than the
G1 and G2 groups (p<0.10), respectively. In addition, the size of
the family nuclei of G3 are larger compared to the previous groups.
These dierences could be due to historical, socio-political, economic
factors or settlement strategies, which have inuenced the dierential
growth of the communities (Ortiz-Gordillo et al., 2023; Velásquez,
2021).
The G3 UPs are slightly larger in area, but without statistically
signicant dierences compared to G1 and G2 (p>0.10). The
zootechnical characteristics of the G3 herd are similar to those of
the G1 and G2 groups. The technological adoption index of the G3
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). 2025, 42(3): e254233 July-September. ISSN 2477-9409.
6-6 |
UPs is low (7.5 from 1 to 21), while, the index of infrastructure and
machinery are slightly higher than the previous groups. However, the
forms of production in these models are related to the characteristics
of the SDPBC (González-Quintero et al., 2020), where meat and milk
are produced in grazing systems, with predominantly Bos Taurus x
Bos Indicus animals and technological indexes that do not exceed
10.8 points as reported by Chuquirima et al. (2023).
Among the overall herd characteristics, G3 exceeds the number
of total animals by 86.9 and 68.5 compared to G1 and G2 UPs
respectively (α=0.10). Similarly, G3 UPs have 19 and 17 more
milking cows compared to G1 and G2 groups. In this sense, milk
availability per day was higher by 94.02 and 81.75 L in contrast to G1
and G2. These characteristics demonstrate a superior production scale
of G3 compared to G1 and G2. This condition may be associated
with a better availability of technology, machinery, infrastructure and
a more organized productive development in G3 (Arrieta-González
et al., 2022).
The individual productive performance of G3 analyzed by
milk production per day (3.91 L), calf weight gain (0.52 kg.day
-1
),
age at rst calving (35.7 months), annual calving rate (0.54 calves.
cow
-1
) and eective annual meat production (95.9 kg.cow
-1
) did not
dier statistically from those found in G1 and G2 UPs =0.10). In
contrast, eective annual milk production in G3 (607.17 L.cow
-1
)
was higher by 192.53 and 105.7 L. cow
-1
compared to indicators
found in G1 and G2, which were statistically dierent from G2, but
equal to G1. The economic performance analysis showed superiority
in all G3 indicators compared to G1 and G2, with the exception of
return on cost, which was similar to G1 (p>0.10). Thus, this group
expresses better economic performance and monetary benet per
family compared to the other two groups (Table 3). The superiority in
economic performance of G3 compared to G1 and G3 arises mainly
from technological superiority and larger scale of production. These
factors are associated as important contributors to the advantage in
individual and group milk yield, and consequently in gross income.
100 % of the UPs in G3 have only pasture and cropland areas
for land use. Fifty percent of the UPs develop their agricultural
activities on supercial soils and the rest on deeper soils. The soil pH
varies from farm to farm, ranging from alkaline, neutral and slightly
acidic (Table 5). The organic matter content is poor in all the UPs.
Fertility levels are moderate. The soil has a level of erosion that varies
between light, light to moderate, moderate and moderate to severe,
with variation between UP. These environmental characteristics, as
in G1 and G2, contrast with the worldview of the Pijao people, who
conceive of human beings as guardians of the balance between the
spiritual and the physical, which represent the resources of Mother
Earth (ONIC, 2024). Thus, it can be interpreted that these indigenous
communities have not congured their territory according to their
cultural principles.
Conclusions
The principal component and cluster analyses identied
three types of production units dierentiated by population size,
infrastructure index and scale of production. G3 stood out due to
some of its technical-economic performance indicators. However, all
groups present a small degree of technological adoption, a low index
of machinery and a reduced stocking rates management in similar
áreas size (α≥0.10), obtaining a weak productive and reproductive
performance; thus, the dierences in the best economic results of G3
are mainly related to a larger scale of production (greater number of
milking cows).
In the social sphere, female leadership stood out, particularly in
groups G2 and G3, that were also characterized by a higher proportion
of trained people, which may favor the adoption of practices oriented
towards the care and improvement of the productive process.
The environmental characteristics of the studied Ups, showed
predominant pasture and crop cover, with poor organic matter soil
content, low fertility, scarce forest coverage and a predominant
moderate level of erosion, indicating alterations in the agro-ecosystem.
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