J. Agric. Environ. Sci. Vol. 7 No. 2 (2022) ISSN: 2616-3721 (Online); 2616-3713 (Print)
Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 9
Determinants of adoption of improved panicum forage by agro- pastorals in Dasenech
District, Southern Ethiopia
Asmera Adicha
1
*, Yidnekachew Alemayeh
1
and Dawit Darcho
1
1
Southern Agricultural Research Institute, Jinka Agricultural Research Center, Jinka, Ethiopia
*Corresponding author: asmera05@gmail.com
Received: August 24, 2022 Accepted: September 21, 2022
Abstract: Adoption of improved forage remains vital in combating feed shortages and reducing livestock deaths in
pastoral and agro-pastoral areas of Ethiopia. However, it depends on household characteristics, institutional and
socioeconomic factors, and the perception of the community. Thus, this study examined the determinants of adoption
and intensity of improved panicum forage technologies in the Dasenech district. A multistage sampling technique
was employed to select 140 forage-producing agro-pastoral households. A double hurdle model was used to analyze
the data. The results indicated that agro-pastoralists' adoption and intensity of adoption of panicum forage
production in the Dasenech district is high. However, more than 60% of agro-pastoralists who had adopted and
cultivated panicum forage claimed problems in accessing irrigation water, which was associated with high fuel for
operating irrigation water pumps. Moreover, the probability of adoption of panicum forage production in the
district is influenced by access to irrigation water, forage production experience, cooperative membership, and
distance to the training center. The intensity of adoption of panicum forage production was also influenced by the
sex of the respondent, credit access, distance to market, production experience, price of seed, and livestock
holdings. Working on issues related to the improvement of access to irrigation water, establishing cooperatives of
agro-pastoralists, and provision of credit opportunities and market information by respective stakeholders is
proposed to enhance the adoption and production of panicum forage in the study area.
Keywords: Adoption intensity, Agro-pastoral, Double hurdle, Panicum forage
This work is licensed under a Creative Commons Attribution 4.0 International License
1. Introduction
Livestock farming in Ethiopia is economically and
socially very important and generates a large amount
of export income both at the domestic and
international levels. The entire livestock industry,
which includes cattle, sheep, goats, equines, and
poultry, contributes 15–17% of the GDP, 47.7% of
the agricultural GDP, and 37–87% of household
incomes (ILRI, 2010; Behnke and Metaferie, 2011).
Despite playing a range of roles in both the domestic
and global economies of the nation, the contribution
of the livestock sub-sector is now below its potential
due to several technical and non-technical issues.
The most pressing technical problem is the lack of
cultivated and wild feed, both in terms of quantity
and quality (CSA, 2016).
In Ethiopia, cattle perform poorly because feed
quality and quantity are inconsistent, especially
during the dry seasons of the year (Ayantunde et al.,
2005). This requirement necessitates the use of
improved forage, which has various advantages over
currently available traditional feed resources. In
different parts of Ethiopia, the government of
Ethiopia has introduced various improved forages
that are utilized as animal feed and to conserve soil
and water. However, little is known about how
farmers feel about growing and using such forages.
Regarding the types of improved forages grown in
natural resource conservation areas of an agro-
ecological zone and institutional barriers preventing
individual farmers from using feed resource
management technology, farmer perceptions of
technology were one of the factors that could support
or hinder the adoption of improved forage technology
(Gecho and Punjabi, 2011).
Moreover, the main livestock feed resources
accessible in Ethiopia are natural pastures, crop
residues, and grazing (Tolera, 2008; Assefa, 2012).
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 10
However, these feed resources are very low in
quality, having high fiber, low to moderate
digestibility, and low levels of nitrogen (Habte,
2000), which might be linked with a low voluntary
intake, thus resulting in inadequate nutrient supply,
low productivity, and even weight loss. On the other
hand, the organic matter content of the soil
diminishes as a result of keeping feed supplies within
the fields, which worsens the topsoil structure and
speeds up erosion (Alemayehu et al., 2016). This
situation calls for the inclusion of improved forages,
which could provide several advantages over the
currently available traditional feed sources or
overgrazing in the field.
Adoption of those improved forages refers to a
business, a farmer, or a reflection of a farmer's
decision to employ a new technology of improved
forages, method, and practice in the farming system's
production process. Farmers will then only use the
technologies that are appropriate for their needs. This
may present a chance for smallholder farmers to
increase their income and output (Zakarias, 2016).
Forage development strategies have been used for a
long time in Ethiopia, but their uptake by the farming
community has been very low due to several factors,
including a lack of and inability to adopt forage
technologies; weak extension services; a lack of and
high cost of planting materials; resistance on the part
of most smallholder farmers; and the size of livestock
ownership and farm size (Othill, 1986; Assefa and
Kebede, 2012; Beshir, 2014). Lack of sufficient land
is one of the key obstacles to the adoption of new
technologies in the Ethiopian farming system. This is
a limitation that farmers are reluctant to plant forage
and allocate their land for food crops. As a result,
adopting specialization or intercropping forage with
other crops has little effect on land allocation and
optimizes land for both forage and food crops
(Teshome, 2014).
Numerous researchers have been identified that lack
of knowledge as a constraint for adoption of
technology by farmers. After having forages on their
hands they do not know what is best to do with them
or how to use them efficiently. Lessening the
problem can be possible with the help of good
extension services. It is well recognized that
extension service is an important pillar in the
transformation of subsistence agriculture to market-
oriented agriculture (Gebremedhin et al., 2006). Lack
of funds for covering the costs of creating specific
forage technologies is the other significant reason
preventing many Ethiopian farmers from adopting
new forage technologies. Primary variables that
influenced farmers' adoption of forage technology
were their physical and social capital holdings,
educational accomplishments, household parameters,
and income level (Cramb, 2000; Shelton et al., 2005;
Mapiye et al., 2006; Gillah et al., 2012).
Many previous studies conducted on the adoption
of improved forage technologies and its intensity of
usage as well as the impact on livestock productivity
suggested that adoption did not result in higher
income for beneficiaries of the technology as a
result of different socioeconomic and institutional
factors of production among others (Njarui et al.,
2017; Beshir, 2014; Gebremedhin et al., 2003;
Mwangi and Wambugu, 2003; Kumwenda and
Ngwira, 2003). These studies evaluated the intensity
and rate of adoption of better fodder technologies.
However, they were unable to evaluate the specific
panicum forage technologies that have recently been
made available to farmers and agro-pastoralists.
Therefore, this study is aimed at identifying
determinants of adoption decisions and the intensity
of adoption of improved panicum forage technologies
in pastoral/agro-pastoral areas of Southern Ethiopia.
Furthermore, South Omo is one of the zones in
southern Ethiopia with total area coverage of 108ha
for panicum forage production (SOZLFO, 2020).
However, the information regarding how many
pastoralists or agro-pastoralists grow panicum
forages on their farm, the knowhow about what is
best to do with panicum forages or how to use them
efficiently, and what associated social, economic,
household, and institutional constraints of production
or determinants of adoption decision and adoption
intensity of panicum forage production has not yet
been seen in the study site.
2. Research Methodology
2.1. Description of the study area
Dasenech district is one of the ten districts in the
South Omo zone of Southern Ethiopia. The economic
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 11
activity in the district is mainly based on livestock,
crop, and fishing production. Crop production is
mainly dependent on irrigation from the Omo River
and Omo overflow. In the district, rainfall is both low
and irregular, making the pastoralists and agro-
pastoralists vulnerable to famine and drought. Flood-
recession agriculture along the banks of the Omo
River is considered more reliable than rain-fed
shifting cultivation. However, this system of
production is limited in extent and contributes little to
the overall subsistence needs of the local agro-
pastoral groups. Major crops grown are sorghum,
maize, and bananas. Major livestock types kept in the
district are cattle, sheep, and goats. In terms of
livelihood patterns of households, the district is under
the South Omo Pastoral Livelihood, distinguished by
its semi-arid climate, with low and erratic rainfall,
low altitudes, and warm temperatures. According to
the Central Statistical Agency projection, the
estimated population in the district is about 66,000.
The district is administratively divided into 39
kebeles, of which 28 kebeles are along the Omo
River practicing flood-recession agriculture in
addition to cattle rearing and recently practicing
forage production, particularly panicum, Rhodes, and
elephant grass.
Figure 1: Map of the study area
2.2. Research design, data types and sources
The study employed a cross-sectional survey research
design. Primary data was collected from the study
population at a single point in time to examine the
relationship between variables of interest. Both
qualitative and quantitative data types were collected
from primary and secondary data sources. The
primary data collected from households includes
information on household households,
socioeconomic, land characteristics, institutional
factors, and other factors that are supposed to explain
smallholder improved panicum forage producers.
Secondary data sources used for this study were
journals, relevant textbooks, government and non-
government reports, and South Omo zone agricultural
office and district agricultural office reports.
2.3. Sampling procedure, sample size
determination, and method of collection
The study site was purposefully selected based on
improved panicum forage production and
availability. Multistage stage sampling techniques
were employed to draw sample household heads. In
the first stage, potential kebeles in panicum forage
production were identified based on district
information and consequently, five kebeles were
randomly selected. In the second stage, the number of
J. Agric. Environ. Sci. Vol. 7 No. 2 (2022) ISSN: 2616-3721 (Online); 2616-3713 (Print)
Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 12
sample households from each sample kebele was
determined from the recent lists of households using
a proportional size. In the third stage, given the
relative homogeneity of households in terms of their
socioeconomic characteristics and livelihood styles,
samples of households were drawn using a simple
random sampling method from each kebele. To
determine sample size the formula described by
Yemane (1967) was used [1]. Accordingly, the
sample size was 154, which was adjusted to 140
pastoral households during data cleaning to be
consistent and reliable for the analysis.
[1]
Where
n is sample size for the study
N is the population of interest (14895)
e is the precision level, which was 0.08
Formal and informal methods of data collection were
implemented to acquire primary data. A key
informant interview and focus group discussion with
pre-defined social groups (3 elderly, 3 agro-
pastoralists, 2 youth, 2 women, and 2 development
agents) were conducted before the formal survey to
collect general information about the study site and
improve panicum forage production. A checklist was
used to guide the informal discussion conducted to
generate data that could not be collected from
individual interviews. Formal data collection was
employed with the help of a pre-tested structured
questionnaire. With the help of local enumerators,
researchers collected data during the 2021 production
season.
2.4. Descriptive analysis and Double hurdle
model
The descriptive statistics employed were mean,
standard deviation, frequency distribution,
percentages, chi-square tests (for categorical
variables), and t-tests (continuous variables) and were
used to describe and examine adopters and non-
adopters of panicum forage technology.
2.4.1. The adoption decision of smallholder agro-
pastoralists and the intensity of improved
panicum forage production
The intensity of increased panicum forage production
and the decision to adopt it were examined using the
Double Hurdle Model. This concept presupposes that
farmers must overcome two obstacles when making
agricultural decisions (Cragg, 1971; Sanchez, 2006;
Humphreys, 2013). According to Cragg (1971), there
are two stages of adoption challenges. The first stage
involves deciding whether or not to embrace the
technology, while the second stage has to do with the
adoption level. It is believed that there is a
connection between the two layers (Berhanu and
Swinton, 2003). Therefore, this proposed association
has been examined in a number of recent studies
(Gebremichael and Gebremedhin, 2014; Katengeza et
al., 2012; Akpan et al., 2012; Mal et al., 2013).
Therefore, a double hurdle model was chosen
because it allows for the distinction between the
determinants of adoption and the level of adoption of
improved panicum forage production through two
separate stages. This model estimation procedure
involves running a probit regression to identify
determinants of adoption decisions in the activity
using all of the sample population in the first stage,
and a truncated regression model on the adopting
households to analyze the adoption intensity in the
second stage. In our case, the first stage of the double
hurdle model examined the determinants of the
adoption decision to panicum forage and was
analyzed by means of the probit.
Burke (2009) claims that the double hurdle model
(DHM) is helpful because it enables a subset of the
data to accumulate at a certain value without
introducing bias in the second stage's estimation of
the determinants of the continuous dependent
variable, allowing you to collect all the data from the
participant's remaining sample. Therefore, there are
no limitations on the components of explanatory
variables in each decision stage in the double hurdle
model. Therefore, the factors influencing the decision
to use improved panicum forage and the degree of
adoption can be studied individually.
As a result of this, estimates for adoption decisions
can be generated using probit regression, and
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 13
truncated regression can be used to investigate the
number of adoption decisions. Burke (2009) asserts
that the separable in estimates should not be confused
with the possibility of separability. We start in the
first stage (adoption decision), where households are
classified according to whether they are adopters or
not by using probit analysis, and from there we
calculate the likelihood function. To do so, let Pi
denote a binary indicator function, taking the value
"1" if agro-pastoralists adopted panicum forage in the
2021 production year and "0" otherwise. Further, let
Qi denote the proportion of area covered by panicum
forage of the total land owned in the specified
production year. We can then derive the likelihood
function for the standard double hurdle model as
follows:
[2]
[3]
Where
Ф denotes the standard normal CDF, is the
univariate standard normal PDF
σ is the variance of error terms
logLprobit is the log-likelihood for a probit
Log truncate is log-likelihood for a truncated
regression with truncation at zero value of the
continuous dependent variable in the second
stage (proportion of area covered by panicum
forage from the total land owned).
The log-likelihood from the Cragg-type double
hurdle model is therefore the sum of the log-
likelihood from probit and a truncated regression.
The fact that these two component parts can be
completely separated and used individually to
estimate, reduced regression is more beneficial
(Ground and Koch, 2008; Aristei and Pieroni, 2008;
Burke, 2009). Then the log-likelihood function for
the double hurdle model was:
[4]
Where
Φ and ϕ were the standard normal cumulative
distribution function and density function,
respectively.
The maximum likelihood estimation (MLE) method
was used to estimate the log-likelihood function. The
test statistics double hurdle model was used as
described by Greene (2000).
[5]
Where:
LT, LP and LTP are the log-likelihoods of the
Tobit, probit and truncated regression models,
respectively.
Rejecting the null hypothesis indicates that the
choices regarding adoption and level adoptions are
made at two different phases and support the double-
hurdle model's superiority over the Tobit model.
2.4.2. Constraints on the production of improved
panicum forage
Kendall's coefficient of concordance was used to rank
constraints associated with the use of improved
panicum forage production. The respondents
mentioned and ranked constraints they faced on the
production of improved panicum forage using the
five-point Likert scale, where +1 = most important
constraints, 1 = more important constraints, 0 =
important constraints, -0.5 = less important and -1 =
least important. The values of Kendall's coefficient of
concordance were calculated using the formula below
[6].
[6]
Where
W stands for Kendall's coefficient of
concordance
m stands for the number of respondents
n stands for the number of constraints
T stands for the sum of rankings for the
constraints being ranked
2.5. Variable definition and measurement as well
as prior expectations
This section illustrates the variable description,
measurement of variables, and prior expectations as
indicated in Table 1.
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 14
Table 1: Variables, their measurements and expectations in the Double Hurdle Model
Variables
Measurement
Expected sign
Dependent variables
Adoption
1 if agro pastoralist has adopted panicum forage,
0 if agro pastoralist has not adopted
Intensity of adoption
Proportion of area covered by improved
panicum forage from the total land owned
Explanatory variables
Sex
1 if male, 0 if female agro pastoralist
-/+
Age
Years
-/+
Education level (formal)
Years of schooling
+
Farm size
The total area of land managed by a household
head
-/+
Family size
Number of family members in a household
living for more than 6 months
+
Livestock holding
Number of livestock owned by a household
head(TLU)
+
Price of forage seed
Market price of a forage seed (ETB)
+
Extension contact
1 if agro pastoralist contact with extension
agents in a month, 0 otherwise
+
Credit access
1 if agro pastoral get credit services, 0 otherwise
+
Feed shortage
1 if feed shortage is a problem for agro pastoral,
0 otherwise
-
Irrigation to access
1 if access to irrigation, 0 otherwise
+
Member of cooperative
1 if member of panicum forage production
cooperative, 0 otherwise
+
Experience in forage production
Number of years, agro pastorals cultivated
panicum forage
+
Distance to market center
Distance to nearest market center in
hours/minute
-
Distance to training center
Distance to nearest agro pastoral training center
in hours/minute
-
3. Results and Discussion
3.1. Socioeconomic, institutional, and household
characteristics of respondents
3.1.1. Sex, age, education level, and family size of
the respondent
Male household heads made up 75% of adopters and
more than 74% of panicum growers in the pooled
sample. The average age of panicum forage growers
was 37 years, showing that panicum forage growers
in the research area are in their productive age
category. On average, both adopters and non-
adopters have less than one year of formal education.
As a result, neither adopters nor non-adopters of
panicum forage producers have completed primary
school, suggesting that both groups had limited
access to formal education and a low level of
education overall in the research area. The average
family size is nearly seven in pooled data, indicating
family size for both adopters and non-adopters of
panicum forage.
3.1.2. Experience of forage production, feed
shortage and extension visit
Panicum forage growers at the study site had an
average of 4 years and a maximum of 8 years of
experience in growing forage, indicating that some of
them had good knowledge of forage production. On
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 15
average, an adopter of panicum forage has been
working in forage production for two more years than
a non-adopter. Major feed resources for livestock in
the study site are free grazing, crop residue, panicum
forage, and elephant grass. However, about 51% of
the agro-pastoralists in the pooled sample faced feed
shortages and did not produce improved forages due
to lack of irrigation water access and limited supply
of improved seed; and more than half (51%) of the
adopters have faced feed shortages for livestock.
Thus, the lack of improved feed and forage limits the
productivity of livestock production in the study site,
and the study by Galmessa et al. (2013) reported that
an inadequate supply of quality feed is the major
factor limiting dairy productivity. In 2021, 88% of
adopters had visits by extension agents regarding
forage cultivation, including panicum forage,
whereas 54% of non-adopters did not. The aggregate
data suggests that around 81% of the respondents had
extension contacts. This demonstrates that extension
work regarding forage cultivation is relatively good
in the area.
3.1.3. Access to irrigation water and credit services,
and cooperative membership
About 91% of adopters had access to irrigation water
for panicum forage production, compared with 67%
of non-adopters at survey time. The aggregate data
reveals that about 77% of the respondents had access
to irrigation water. Only 9% of adopters and 3% of
non-adopters had access to credit services. In the
pooled sample, 8% of the panicum growers had used
credit services. This demonstrates that the agro-
pastoralists in the study area are less experienced in
obtaining financial services. Additionally, the
absence of financing has frequently been mentioned
as a productivity problem, particularly for small-scale
farmers and pastoral herders (O'Lakes, 2010). About
37% of the panicum producers in the pooled sample
were involved in panicum forage production
cooperatives. This shows that agro-pastoralists in the
study site are less involved in panicum forage
production cooperatives. About 47% of adopters
were involved in cooperatives for panicum forage
production, compared with 3% of non-adopters at
survey time.
3.1.4. Distance to agro-pastoral training and
nearest market center, and market price of
panicum forage
Both adopters and non-adopters have nearly the same
walking distance to a knowledge and experience
sharing center or agro-pastoral training center. This
might be due to agro-pastorals being settled in certain
common places in a group manner as a government
strategy to settle them rather than their previous
experience of mobile nature in the area. The distance
between adopters and non-adopters to the nearest
market is only one to two minutes-walking distance.
The aggregate data indicates that agro-pastorals have
an average of a 15-minute walking distance to the
nearest market to sell or buy either panicum seed or
other agricultural inputs or products. Awareness
about the current market price of panicum forage
stimulates the adoption decision to grow panicum
forage. Adopters reported that the current market
price of panicum forage seed is 240 ETB per
kilogram, whereas non-adopters reported 119 ETB
per kilogram. But during survey time, the market
price of panicum forage in the district market was
350 ETB per kilogram. This implies that adopters
have slightly better information regarding panicum
forage seed than non-adopters in knowing the real
market prices
3.1.5. Livestock holding and farm size
The mean tropical livestock unit (TLU) for adopters
is about one unit higher than that of non-adopters.
This means the adopters have more livestock
holdings than non-adopters. The mean TLU for
adopters and non-adopters was 9 and 8, respectively.
The mean landholding for adopters is about 0.81
hectares, which is higher than that of non-adopters
(0.77 hectares). This suggests that adaptors with
higher land holdings could allocate land for panicum
forage compared to non-adopters with lower land
holdings. The average proportional area covered by
panicum forage for adopters was 0.22 hectares.
As per the key informant discussion, panicum forage
production has been started in 2018 by PCDP and the
district livestock and fishery office. Following a slow
initial rate of uptake in the first few years, the
adoption rate accelerated and almost 150 households
had adopted and planted panicum forages at the
individual farm level by 2021. Planted forages had
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 16
also spread in the area and were incorporated into
development plans by local governments, NGOs, and
development projects. Planting panicum forage is
now becoming the ‘normal practice’ in the district
and currently, about 28 kebeles are producing
panicum forage. Various stakeholders such as the
office of livestock and fishery resource, Jinka
Agricultural Research center, RPLRP, FAO, PCDP,
and others were engaged in the promotion of
different forages mainly grass types such as panicum,
Buffelgrass, Rhodes, elephant grass; legumes type
lablab, cowpea and tree type like Pigeon pea,
Sesbania sesban, and Leucaena. The different
varieties of forage have varying levels of adoption
rates. As revealed in key informant discussions with
experts and focus groups discussions with agro-
pastoralists the two major forages that have relatively
been expanded and grown in the study sites included
panicum and elephant grass. The others forage types
mentioned were less adopted forage by agro-
pastoralists. The reasons behind the less adoption
rates of forage are associated with the interest of the
agro-pastoralists to give priority to cash forage like
panicum and less managed forage like elephant grass.
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Table 2: Descriptive statistics of socioeconomic, institutional and household characteristics
Variables
Adopters (n=109)
Non-adopters (n=31)
All (n=140)
N
Mean
Std.
dev.
Min
Max
N
Mean
Std.
dev.
Min
Max
t-test
N
Mean
Std.
dev.
Min
Max
Sex (1=male)
109
0.75
0.43
0
1
31
0.68
0.48
0
1
-0.83
140
0.74
0.44
0
1
Age (years)
109
37.97
9.11
19
65
31
34.58
7.89
22
55
-1.88*
140
37.22
8.95
19
65
Education (years)
109
0.19
0.09
0
8
31
0.48
1.39
0
6
1.32
140
0.26
1.09
0
8
Family size (number)
109
6.73
2.44
1
15
31
6.94
3.13
2
14
0.38
140
6.78
2.59
1
15
Feed shortage (1=yes)
109
0.51
0.50
0
1
31
0.48
0.51
0
1
-0.29
140
0.51
0.50
0
1
Experience of forage production
(years)
109
4.18
1.81
0
8
31
1.58
2.20
0
6
-6.72***
140
3.61
2.18
0
8
Panicum forage production
cooperative membership (1=yes)
109
0.47
0.50
0
1
31
0.03
0.18
0
1
-4.74***
140
0.37
0.48
0
1
Market price of panicum forage
(ETB)
109
240.3
91.2
0
350
31
119.4
145.3
0
350
-5.64***
140
213.5
116.4
0
350
Access to credit service (1=yes)
109
0.09
0.29
0
1
31
0.03
0.18
0
1
-1.08
140
0.08
0.27
0
1
Distance market center(minute)
109
15.32
12.02
0
45
31
14.19
13.86
0
40
-0.44
140
15.07
12.41
0
45
Extension visit (1=yes)
109
0.88
0.33
0
1
31
0.54
0.51
0
1
-4.38***
140
0.81
0.39
0
1
Access to irrigation water (1=yes)
109
0.91
0.42
0
1
31
0.67
0.52
0
1
-2.58**
140
0.77
0.41
0
1
Livestock holding (TLU)
109
8.67
15.9
0
159
31
7.79
5.58
1.25
20.53
-0.29
140
8.45
14.28
0
159
Distance to agro pastoral training
center (minute)
109
20.01
10.40
0
70
31
20.23
10.45
0
50
0.72
140
20.06
14.1
0
70
Farm size (ha)
109
0.81
0.33
0.5
2
31
0.77
0.36
0.25
2
0.43
140
0.78
0.35
0.25
2
Adoption (1=yes)
-
-
-
-
-
-
-
-
-
-
-
140
0.78
0.42
0
1
Proportion of area covered by
panicum forage
109
0.22
0.20
0
1.25
-
-
-
-
-
-
-
-
-
-
-
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 18
3.2. Constraints of panicum forage production
Table 3 shows the major constraints prioritized by the
respondents on panicum forage production including
problems in irrigation water pump or breaking down
of primary canals, informal seed suppliers/sellers
harvesting of immature seeds due to awareness
problems, insufficient seed provision by the
government and weak extension support and training.
Insufficient irrigation water pump and or break down
of primary canals harvesting immature seeds were the
1
st
and 2
nd
main constraints in panicum forage
production. On the other hand, the involvement of
informal seed suppliers/sellers and fluctuations in
seed supply by governments and NGOs to agro-
pastoralists were mentioned as the third and fourth
main constraints in panicum forage production. The
absence of sufficient planting material as well as
limited extension provision on forage management
and harvesting has been indicated as a hindering
factor to the adoption of improved forage (Ndah et
al., 2022). These constraints could lead to less
adoption of panicum forage, reduced economic
benefits and incomes from the production of
improved forages. Kendall’s coefficient of
concordance shows that there was a low (31.7%)
level of agreement among smallholder agro-
pastoralists in ranking of constraints.
Table 3: Major constraints of agro-pastoralists in panicum production
Level of agreements (frequency/percent)
Constraints
Strongly
agree
Agree
Neutral
Disagree
Strongly
disagree
Mean
rank
Ranking
Informal seed suppliers/sellers
38(27.1)
29(20.7)
51(36.4)
10(7.1)
12(8.6)
3.88
3
rd
Fluctuation of seed provision
by government and support
8(5.7)
10(7.1)
54(38.6)
50(35.7)
18(12.9)
2.92
4
th
Market access problem
8(5.7)
8(5.7)
63(45)
18(12.9)
43(30.7)
2.47
6
th
Awareness problem of
harvesting un matured seed
53(37.9)
28(20)
35(25)
11(7.9)
13(9.3)
4.18
2
nd
Irrigation water pump
problems or breaking of
primary cannels
71(50.7)
49(35)
15(10.7)
3(2.1)
2(1.4)
4.88
1
st
Weak extension support
14(10)
36(25.7)
21(15)
33(23.6)
36(25.7)
2.58
5
h
Test statistics
Number of observations
140
Kendall’s coefficient of
concordance
0.317
Chi-square
221.595
Degree of freedom
5
Asymptotic significance
0.000
Source: own result, 2021
3.3. Determinants of adoption decision and
intensity of adoption of improved Panicum
forage
3.3.1. Sex of the respondents
The sex of the respondents is negatively related to the
adoption intensity of improved panicum forage
production (Table 4). This means that male agro-
pastorals allocate a lower proportion of area to
improved panicum forage production as compared to
their female counterparts. The reason for this is that
male agro-pastorals might compare many alternatives
to growing either forage or crops while allocating
land because of their access to more agricultural
information than their female counterparts. Female
agro-pastorals in the study site cut and carry panicum
forage to feed cattle and shoat, sell fresher biomass
than their male counterparts, and want to allocate
more land for panicum forage production. The
marginal effect indicates that the proportion of area
allocated to improved panicum forage production by
J. Agric. Environ. Sci. Vol. 7 No. 2 (2022) ISSN: 2616-3721 (Online); 2616-3713 (Print)
Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 19
male forage producers decreases by 5.6% compared
to their female counterparts. However, the study by
Gebremedhin et al. (2003) disclosed that the gender
of the household head had no impact on forage
adoption.
3.3.2. Experience in panicum forage production
It is positively related to agro-pastoral adoption
decisions (Table 4). The likelihood that agro-
pastoralists will adopt improved panicum forage
likewise rises as years of forage planting and gaining
advantages grow. When all other conditions are
maintained constant, the marginal effect shows that
one additional year of growing panicum forage
improves the likelihood of adoption and intensity by
3.1%. This might be due to agro-pastoralists getting
more benefits from panicum production and being
willing to expand the production. Because they can
access information from a variety of sources, more
experienced agro-pastoralists are more likely to have
access to forage value and seed price information
than less experienced ones. This is because
households have already been exposed to
technologies and realized their importance. An
analogous result was stated by Van Den Berg (2013)
on the adoption of improved farming practices.
3.3.3. Access to irrigation water
Access to irrigation water had a direct relationship
with the adoption of improved panicum forage
production. Agro-pastoralists who had access to
irrigation water in the 2021 production season had
about 0.59% more probability of adopting panicum
forage than those with no access to irrigation water.
Access to irrigation water enables agro-pastoralists to
plant panicum seeds, irrigate them and get more
benefits from them than those who have no access to
irrigation water. The result is consistent with the
study by Asmera and Yidnekachew (2021), which
indicated that agro-pastoralists who are nearby the
water source may have more access to water for their
household consumption, livestock, and crop watering
than those who are distant from water sources.
Irrigation access offers the chance for forage
production to the farmers, and those farmers who
have good access to irrigation grow forage three
times a year (Shiferaw et al., 2018).
3.3.4. Cooperatives in panicum forage production
The forage production cooperative was positively
related to the adoption decision of the improved
panicum forage production (Table 4). When all other
factors are held constant, being a member of a
panicum-growing cooperative enhances the adoption
of panicum forage by 6.1% as compared to non-
members of cooperatives. This is because agro-
pastoralists in groups have easier access to financing,
agricultural inputs, capacity-building programs,
success stories from other agro-pastoralists, and
extension services since a group can access these
resources more easily than individuals. Amfo and Ali
(2020) assert that farmers in cooperatives are more
likely to exchange ideas and learn from one another
over time, increasing the adoption of agricultural
technologies. Cooperative membership of
beneficiaries to introduced technologies could
enhance individual farmers' bargaining power and
reduce transaction costs, hence creating an
opportunity for extremes that could be used to
announce improved forages for dairy cows (Kassie et
al., 2013).
3.3.5. Distance to training center
Distance to the training center was negatively related
to the adoption decision of improved panicum forage
production. The marginal effect indicates that as the
distance from the agro-pastoral home to the agro-
pastoral training center increases by one more
minute, the adoption of panicum forage decreases by
2.1%. This is because the adoption process may be
aided by being close to the training facility and
receiving knowledge about various agricultural
inputs. Growers of panicum forage who were closer
to the training center and those who received
information were more likely to adopt the panicum
forage than those who were farther away. According
to Zekarias (2016), farmers who live a long distance
away from a farmer's training center have less access
and utilization opportunities for forage technology,
which lowers the adoption probability of improved
forages. Similarly, findings by Mwakaje (2012) and
Kassie et al. (2013) reported that access to training
centers and information plays a key role in the
adoption of introduced forage technologies.
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 20
3.3.6. Market price of panicum forage
Market price was positively related to the intensity of
the adoption of panicum forage. Agro-pastoralists
who sell panicum biomass and seed and get a high
price advantage have a higher probability of
allocating more areas for panicum forage than those
who do not get income or sell panicum seed or
biomass. From the marginal effect, a unit increase in
a panicum seed price increases the area allocated to
panicum forage by 0.03%, other factors being held
constant. The positive result of the market price of
panicum forage, either to sell or to buy to grow, is an
essential factor in deciding the allocation of land.
Previous findings by Wandji et al. (2012) noted that
the positive perception and knowledge of the price of
characteristics of new technology have a significant
effect on their adoption. The high price of forage
seeds and farm inputs is one of the reasons for the
non-adoption of some improved forages in Africa
(Gebremedhin et al., 2003; Mwangi and Wambugu,
2003; Kumwenda and Ngwira, 2003; Morris et al.,
2015).
3.3.7. Distance to marketing center
It had a negative relationship to the intensity of
adoption of improved panicum forage. The marginal
effect suggests that a one-minute increase in walking
distance from the agro-pastoral home to the market
center decreases the tendency of the area allocated to
panicum forage production by 11.4%, all other things
being constant. This implies that the panicum forage
growers who were further away from the market
center were less likely to allocate an area to panicum
forage than those who were closer to the market
center. This might be due to less access to market
information like the price of panicum seed and its
importance. Similar findings by Beshir (2014)
reported that distance from farmers’ homes to the
market center has a negative effect on the adoption of
improved forages as farmers get different inputs from
nearby markets. Proximity to markets usually
encourages market participation by reducing
transaction costs, thereby enhancing the adoption of
improved forages (Gebremedhin et al., 2003).
3.3.8. Access to credit service
Credit access was positively related to the adoption
intensity of panicum forage production (Table 4).
The marginal effect indicates that agro-pastoralists
who have access to credit services have a higher
adoption intensity of panicum forage production
compared to their counterparts by about 9.9%, other
factors held constant. This means that agro-
pastoralists who have access to credit services
allocate more land for panicum forage production
than those who have no access. This is because it
enhances the opportunity to get additional income,
and its accessibility reduces the transport cost, and
farmers may learn more about the technology by
observing; this furthers its adoption (Dehinenet et al.,
2014). The study by Adicha and Mada (2020)
revealed that the accessibility of credit facilities is a
prerequisite for a technology to be adopted and
promoted properly. According to earlier research,
having access to financial services gives farmers a
strong chance to build up assets and buy various
agricultural technologies, such as panicum forage
technologies (Yehuala et al., 2013; Muzari et al.,
2012; Akudugu et al., 2012; AE et al., 2017; and
Quddus, 2012).
3.3.9. Livestock holding
It had positively related to the allocation of the area
to grow panicum forage. Other factors held constant,
a one-unit increase in total tropical units increases the
area allocated to panicum forage by 0.3%. This
indicates that agro-pastoralists with a great number
of livestock were more likely to allocate land and
grow panicum forage for their livestock feed as well
as have a chance to sell biomass and seed. Similar
findings by Beshir (2014) suggest that livestock
holding in tropical livestock units has a positive
effect on the probability of adoption of improved
forages due to the availability of cash to buy the
technology, as livestock in agro-pastoral areas is
considered an asset that could be used either in the
production process or in exchange. Njarui et al.
(2017) reported that a large herd of cattle requires a
large amount of feed and an area allocation to grow
forage.
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 21
Table 4: Determinants of adoption decision and intensity of adoption of improved panicum forage
Coefficients (standard error)
Explanatory variables
Adoption
Intensity of adoption
Average marginal
effects
Sex (1=male)
0.630(0.404)
-0.180(0.069)***
-0.056(0.030)*
Age (years)
0.009(0.024)
-0.002(0.004)
-0.0005(0.002)
Education (years)
-0.196(0.109)*
0.018(0.023)
0.001(0.010)
Family size (number)
-0.038(0.065)
0.014(0.012)
.0049(0.0052)
Feed shortage (1=yes)
-0.413(0.336)
0.109(0.058)*
0.033(0.031)
Panicum forage production experience (years)
0.372(0.101)***
0.041(0.018)**
0.031(0.008)***
Panicum forage production cooperative
membership (1=yes)
1.913(0.452)***
-0.016(0.061)
0.061(0.018) ***
Market price of panicum forage (ETB)
0.0016(0.0015)
0.0006(0.0003)**
0.0003(0.0001)**
Access to credit service (1=yes)
-
0.229(0.136)*
0.099(0.046)**
Distance to market center(minute)
-
-0.264(0.120)**
-0.114(0.032)***
Extension visit (1=yes)
0.008(0.013)
0.002(0.002)
0.001(0.001)
Access to irrigation water (1=yes)
0.054(0.017)***
0.003(0.002)
0.003(0.001)**
Livestock holding (TLU)
0.010(0.011)
0.005(0.0006)***
0.003(0.0006)***
Distance agro pastoral training center (minute)
-0.335(0.108)***
-0.021(0.017)
-0.021(0.008)***
Farm size (ha)
-0.529 (0.364)
0.111(0.089)
0.029(0.031)
Constant
-.677(0.961)
-0.017(0.187)
-
Number of observations
140
Wald chi-squared (15)
163.55
Probability chi-squared
0.0000
Log pseudo likelihood
23.158
Lnsigma
Constant
-1.534(0.165)*
/sigma
0.216(0.036)
Model variance-covariance matrix of the estimators (VCE)
Robust
Note: Selection and intensity models must differ at least in one explanatory variable in order to use Cragg hurdle
regression. Thus, selection model did not include access to credit services or the distant market center. Significant
levels at 1%, 5%, and 10% are indicated by ***, **, and *, respectively.
4. Conclusions and Recommendations
Improved panicum forage production is becoming an
important vendor in livestock feed production
systems and a source for income generation of agro-
pastorals. Understanding how household
characteristics and institutional and socioeconomic
factors affect the adoption and intensity of improved
panicum forage production in the area was very
important. Access to irrigation water, market
distance, and membership in cooperative were major
factors for the production of the feed in the study site.
According to the study results adoption decision for
panicum forage production is influenced by access to
irrigation water, the education level of household
heads, experiences in panicum forage production,
cooperative membership and distance to the training
center. The intensity of adoption is influenced by
feed shortage, sex of the respondents, credit access,
distance to market or market information, experience
in panicum forage production, prices of biomass and
seed, and the number of livestock holdings. Working
towards the improved accessibility of irrigation
water, the establishment of cooperatives of agro-
pastoralists, provision of credit opportunities and
market information by responsible stakeholders are
recommended to enhance the adoption and
production of panicum forage in the study area.
Competing interests
Authors declare that there is no conflict of interest.
J. Agric. Environ. Sci. Vol. 7 No. 2 (2022) ISSN: 2616-3721 (Online); 2616-3713 (Print)
Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 22
Acknowledgment
The authors would like to acknowledge Southern
Agricultural Research Institute and Jinka Agricultural
Research Center for financial support.
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