Effect of management attributes on seed potato yield and quality in
Ethiopia
Adane Hirpa12, Miranda P.M. Meuwissen1, Ivo A. Van der Lans3, Willemien J.M. Lommen2,
Alfons G.J.M. Oude Lansink1, Admasu Tsegaye4 and Paul C. Struik2
1
Business Economics, Wageningen University,
Centre for Crop Systems Analysis, Wageningen University,
3
Marketing and Consumer Behaviour, Wageningen University
4
Addis Ababa University, Ethiopia
2
Abstract
Different local situations of the farmers need different production methods to give optimum
yield and quality. A conjoint analysis was undertaken to elicit farmers’ opinions on seed
potato management attributes with respect to their effect on seed yield and quality in Jeldu
and Welmera districts interviewing 324 seed potato farmers. The results showed that
differences exist within and between districts in the degree to which the management
attributes are perceived to contribute to anticipated yield and quality; indicating possibility for
developing alternative seed potato production methods from which farmers can choose a
production method that better suit his situation.
Keywords: Seed potato, Management attributes, Conjoint analysis; Anticipated yield,
Anticipated quality
1
1. Introduction
In Ethiopia several research efforts have been made to develop new potato technologies since
the inception of potato research in 1975. Potato technologies include improved potato
varieties and new pre- and post-harvest management practices. The main objectives of potato
technology development have been to obtain high-yielding, disease tolerant varieties with
improved agronomic and postharvest management practices (Gebremedhin et al., 2008). As a
result, a number of improved varieties have been developed and released to farmers.
However, the majority of smallholder farmers are producing their own potato seeds with poor
quality (Mulatu et al., 2005; Gildemacher et al., 2009; CIP, 2011). There is scarcity of quality
seed potato in Ethiopia. The same is true for other crops in Ethiopia (Abate et al., 2011).
Potato varieties that have been released so far were released with one production method
recommended by research institution despite the possibility of producing them using several
different alternative production methods. The recommended production method can give high
yield and profit but was adopted only by few farmers due to its incompatibility to the diverse
local situations of the farmers. Local situations of farmers vary according to agro-ecology,
soil type, managerial capability, objectives of potato production, availability and access to
inputs and product markets and different local situations need different production methods to
give ‘optimum’ yield and quality of a product (Reece and Sumberg, 2003). More specifically,
majority of the farmers do not adopt new potato varieties because they do not have necessary
production conditions and resources as exactly as specified by the researchers. Therefore, to
increase the number of adopters for the released potato varieties and others in the process of
release, provision of alternative production methods that suit the local condition of the
farmers is important. To develop suitable production methods knowledge on the importance
of the seed potato management attributes with respect to seed yield and quality was essential
for which there was no information before. Therefore, this study has quantified the effects the
seed potato management attributes have on seed potato yield and quality main through
elicitation of farmers opinion.
Besides the use in the development of alternative production methods, the knowledge
generated from this research can be used by farmers to make decision on which management
attribute to invest or give more emphasis compared to the other to increase yield and quality
of seed potato production. This knowledge can be used by input supply agencies to decide the
type and amount of input to be supplied. Other researchers can also use the knowledge to
develop viable production methods. Development practitioners can also use the knowledge to
advise farmers.
2. Methodology
2.1. Study area
This study was undertaken in two major seed potato growing districts found in the central
potato growing part of Ethiopia. These districts are selected because they are the major
suppliers of seed potato of improved varieties in the country. Jeldu district is located
approximately at 128 km west of the capital, Addis Ababa. It is has altitudes ranging from
1325 to 3200 m above sea level (asl) and receives an annual average rainfall of 900 – 1350
mm. About 45% of the district is highland (2300 – 3200 m asl with an annual average rainfall
900 – 1350 mm) and predominantly growing barley, wheat, and potato in their order of
importance. Midland (1500 – 2300 m asl with an annual average rainfall 800 – 1200 mm) and
the lowland (<1500 m asl and average annual rainfall 200 – 800 mm) comprise 30% and 25%
of the district’s landmass, respectively. The main crops grown in the midland are wheat,
barley and teff and in the lowland are sorghum, maize and teff. Crop production contributes to
2
70% of the livelihood of the farmers in the district (Duncan et al., 2011). The seed potato
growing farmers considered in this study, are found at altitude range from 2900 – 3200 m asl
(Mesfin and Kebede, 2011).
The second district included in this study is Welmera. It is found approximately 40 km west
of Addis Ababa. The district is roughly divided into highland (2300 – 3380 mm asl) and
midland (2060 – 2300 m asl). The highland and lowland comprise 41% and 59% of the total
landmass of the district, respectively. The district receives annual average rainfall ranging
from 900 – 1100 mm. Wheat, barley and potato are the main crops grown in the highland part
of both districts.The seed potato growing farmers considered in this study are found at altitude
of about 2300 – 2400 m asl.
2.2. Conjoint analysis
Conjoint analysis was conducted to elicit farmers’ opinion on seed potato management
attributes with respect to their effect on seed yield and quality. Conjoint analysis is a state
preference technique used to measure relative values of attributes that have been considered
jointly by respondents (Louviere et al., 2005; Sayadi et al., 2005; Rao, 2008; Alriksson and
Oberg, 2008). Even though conjoint analysis has its foundation and wide use in marketing
research for the evaluation of consumer behaviour and preference to product attributes (Green
and Rao, 1971), it is also used to evaluate environmental issues concerning agriculture,
ecosystem management, energy, environment evaluation, forestry, land management,
pollution, products, recreation, environmental risk analysis, waste management and
agricultural production (Alriksson and Oberg, 2008). Some research works which have a
relation to this research work have been done in agriculture in Africa using conjoint analysis.
For instance, conjoint analysis was used to design modern crop (groundnut) varieties in Niger
(Baidu-Forson et al., 1997), to valuate cow attributes in Kenya (Makokha et al., 2007), to
estimate farmer’s preferences for cattle traits in Burkina Faso (Tano et al., 2003), and to
evaluate different terms of contracts by fishermen in Kenya (Kambewa et al., 2007).
The basics of conjoint analysis is that the preference for a particular profile is built up by
separate contributions of different attributes, each with limited number of levels (Poortinga et
al., 2003). Therefore, conjoint analysis is a multi-attribute model for which individual’s utility
for a profile can be expressed as sum of utilities for its attributes. That is, the utility function
associated with profile 𝑝 (𝑝 = 1, … , 𝑃) can be expressed as
𝑈𝑝 = ∑𝐴𝑎=1 𝑢𝑎 (𝑥𝑎𝑝 )
where,𝑈𝑝 is total utility of a profile 𝑝, and 𝑢𝑎 is utility associated with attribute 𝑎 (𝑎 =
1, … , 𝐴), which is a function of 𝑥𝑎𝑝 , the level attribute 𝑎 takes in the profile 𝑝. A profile is a
specific combination of attribute levels.
In this study, traditional conjoint analysis technique was used to elicit farmers’ opinion on
seed potato management attributes because its suitability for data collected from ratings.
Factorial ANOVA is used to estimated marginal means for attribute levels and further
interpretation is based on the marginal means instead of coefficient of attribute levels.
2.3. Attributes selection
The Delphi technique was used to select seed potato management attributes because there was
dearth of empirical information on the attributes and their levels and this techniques is useful
to elicit expert judgment on issues that lack empirical evidence (Murphy et al., 1998).
Moreover, the Delphi technique is useful because it is highly flexible, good at getting beneath
3
the surface of issues, minimizes counterproductive effects often encountered using committee,
good at addressing difficult or ‘expert’ questions and more structured than conventional
interviewing (Gordon, 1994).The goal of a Delphi study is not to get any aggregated opinions
of experts that represent a population, but to identify and explore relevant issues (Angus et al.,
2003). The Delphi technique has been used to address issues in agriculture. For instance,
Angus et al. (2003) used a Delphi study to determine a package of best available techniques to
reduce nitrogen emission from a poultry unit under the Integrated Pollution Prevention and
Control Directive (IPPC) in United Kingdom; and Rikkonen (2005) developed alternative
scenarios for future agriculture in Finland.
The Delphi study was undertaken in Jeldu, Welmera and Degem districts in September 2010
by using five experts (three agronomist-breeders and two agricultural extension specialists)
and 30 farmers. The experts were selected because of their long experience in potato research
and field demonstration. The three districts were selected because they are the main producers
of seed potato of improved varieties. Jeldu district was the major supplier of seed potato
closely followed by Welmera districts. The supply seed potato from Degem district was by far
lower than the two district. The farmers, 10 from each district, were selected because of their
long experience in seed potato production. The Delphi survey was undertaken in two rounds.
In the first round, the experts and the farmers were provided with list of seed potato
management attributes and asked to make any amendment to the list and then to rate the
management attributes with respect to their importance to yield and quality, separately, on a 0
to 100 scale rating and give explanation for the scores they gave. The list of seed potato
management attributes and levels provided to the experts and the farmers was prepared using
literature review. To make the rating easy to the farmers the management variables (after the
amendment) were written on a flip chart in a language the farmer could read. From the 30
farmers involved in the amendments of seed potato management attributes and levels only 15
had made the rating. The remaining 15 farmers could not read and so were unable to divide
100 points to the list of management attributes with respect to their importance to yield and
quality even with the assistance of the interviewer. In the second round of the Delphi study,
only four experts were involved because the fifth was not available. In this round experts were
provided with the statistical feedback of the first round evaluation by the farmers (Appendix
Table 1) and the experts (Appendix Table 2, columns 1 and 3) accompanied by anonymous
farmers and experts comments about each evaluated attributes. The experts were asked 1) to
reconsider the evaluations they gave in the first round in light of the feedback they had been
provided, and 2) to give scores to the list of seed potato management attributes. The result of
the second round is shown in Appendix Table 2, columns 3 and 4.
The fact that the list of seed potato management attributes was prepared beforehand, the
Delphi technique used in this study is not any more a traditional Delphi that utilizes openended questions to collect information about a content area in the first round, instead it is a
modified Delphi (Riggs, 1983; Hsu and Sandfold, 2007). In this case, two rounds of
evaluation have been deemed to be sufficient to determine a group consensus (SnyderHalpern et al., 2000). Besides, in the second round experts were provided with farmers
amendment and rating that believed to help the experts to make optimal rating.
The attributes for the conjoint analysis were selected based on 1) the Delphi result score for
the importance, 2) relatedness of the attributes, 3) suitability of the attributes for the conjoint
study, and 4) number of attributes a traditional conjoint analysis can handle. Seed size, seed
rate and spacing are highly related and thus we represented the three attributes with seed size.
Hoeing and hilling are done simultaneously and therefore we combined them and used them
4
as one attribute. Negative selection, harvesting tools, rotation, differences in variety, haulm
killing and sorting were excluded from the conjoint study because of either low importance
from the Delphi result or not mention by the farmers of all districts and any of the experts.
Besides the Delphi study the seed potato management attributes were examined for the
possible interaction among themselves. Finally, nine attributes were selected, two attributes
with two levels and the remaining seven attributes with three levels (Table 1). Fertilizer rate
and fungicide application frequency were found to interact.
Table 1. Seed potato production and postharvest management attributes and levels
Attributes
1. Seed source
2. Seed size
3. Storage method
4. Sprouting method
5. Land ploughing
frequency
6. Planting date
7. Hoeing and hilling
8. Fertilizer rate
9. Fungicide
application
frequency
Level 1
Own
Small
Local
De-sprouting
Three times
Level 2
Market
Medium
DLS
Sprouting under
special action
Four times
Earlier than
recommended date
Once hoeing and
small hill
Below
recommended rate
Within range
recommended date
Twice hoeing and
small hill
Recommended rate
Once application
Twice application
Level 3
Institution
Mixed
Storage
Five times
Twice hoeing and
big hill
Above
recommended
rate
Thrice
application
2.4. Conjoint design
Orthogonal fractional factorial design that allows independent main effect and one interaction
effect was used to generate 27 calibration profiles (minimum number of profiles required for a
conjoint analysis with nine attributes) and six additional profiles (two warm up and four
holdout). A Profile is specific combination of seed potato management attribute levels.
Calibration profiles are those profiles used for the main analysis. Warm up profiles are used to
acquaint the respondents with the process of profiles evaluation and the holdout profiles are
not used in the main analysis of utility estimation but used to validate the model after utility
weights have been estimated.
The total number of profiles a respondent expected to evaluate was 33 (27 calibration, 2
warm-up and 4 holdout) for yield and another 33 for quality. However, number of profiles
was too large and expected to create boredom to the respondents which affected the quality of
data. To lower problem of boredom and at same time get sufficient amount of data the number
of calibration profiles were reduced systematically. That is, the calibration profiles were
randomly allotted to three blocks B1, B2 and B3, each blocking containing nine profiles and
then after the three blocks were randomly divided into three groups by allowing each group
(G) to contain two blocks. Therefore, a group contained profiles from two blocks (i.e., B1 and
B2 in G1; B2 and B3 in G2 and B3 and B1 in G3). By doing so the total number of profiles
evaluated by a respondent decreased from 66 to 48. Format of presentation of the profiles to
5
the respondent was other issue that needed attention. Given the very low literacy level of the
respondents presentation of the profiles in text format was not suitable. Therefore, the profiles
were prepared in symbols easily understood by the respondents.
2.5. Panel selection and data collection
Total of 324 farmers, 162 from Jeldu district and 162 from Welmera district, were selected
randomly from list seed potato growers. The sample size comprised roughly 50% of the total
seed growers. The survey was designed in a way the three groups (stated in selection 2.4)
were evaluated by equal numbers of respondents, i.e., each profile group evaluated by 108
respondents (54 respondents from each district).
The data was collected in the period from May to July 2011 through face-to-face interviews of
a structured questionnaire. The questionnaire had two parts. The first part contained general
questions on demographic characteristics and agricultural activities undertaken by the
respondent with more emphasis to seed potato production and marketing activities. At the end
of the introduction questionnaire the respondents were asked to give the maximum anticipated
seed potato yield they could produce if they had all necessary inputs. The anticipated
maximum yield was used as a reference point to evaluate the profiles for yield. To evaluation
the profiles for quality, three seed potato quality variables defined by respondents themselves
were used. The quality variables are 1) proportion of tuber size in total produce (the higher the
proportion of medium sized tubers the higher the quality of the produce), 2) disease burden
(the higher the infestation of the potato plant by late blight, bacterial wilt and other diseases
the lower the quality of the produce), and 3) physical damage (the higher the proportion of
bruised and cracked tubers the lower the quality of the produce).We collected the data using
0-10 Juster scale. The data is mean centred to minimize individual differences in the use of
the scale. The data was analyzed using factorial analysis of variance.
2.6. Description of seed potato farmers
In both districts, seed potato farmers allotted substantial area of total operated land for potato
production, i.e., 25% (0.74 ha) in Jeldu and 21% (0.58 ha) in Welmera (Table 2). Of the total
land area allotted for potato production more than 94% was allotted for seed potato
production indicating that seed potato production was among the most important agricultural
activities in the districts. It was also the main source of cash income to seed potato farmers in
both districts (Table 3). The area of rented in land and the area of land allotted for seed potato
production were equivalent indicating farmers rented in land mostly to seed potato (Table 2).
Land is scarce and fragmented. The problem of land fragmentation is more severe in Welmera
district (more than 7 plots) than in Jeldu district (about 4 plots) and average area per plot of
own land was also smaller in Welmera (0.21 ha) than in Jeldu (0.39 ha).
Table 2. Demographics, agricultural land, production activities of seed potato farmer
Jeldu
Walmera
Items
Mean±Std. dev.
Range
Mean±Std. dev. Range
Age
40±11.9
20-79
38±10.9
20-73
Household size
7.0±2.74
1-15
5.9±2.59
1-14
Total operated land (ha)
2.80±1.79
0.5-16.5
2.62±1.55
0.5-10
Landholding (ha)
1.69±1.23
0-8
1.58±1.17
0-6.5
Rented in land (ha)
0.71±1.45
0-14.5
0.73±1.30
0-9.5
Sharecropped land (ha)
0.35±0.62
0-4
0.27±0.51
0-3
Land cultivated under potato (ha)
0.74±0.74
0.13-5.5
0.58±0.62
0.10-6
Number of plots
4.36±2.55
1-15
7.53±4.54
1-20
6
Land poughing frequency
3.91±0.58
1-5
3.93±0.58
Spacing (cm) between potato plants
29±5.2
15-50
31±6.7
Spacing (cm) between rows
62±13.7
30-100
69±11.7
Hoeing frequency
2.14±0.468
1-3
2.03±0.294
DAP (Mg/ha)
15.5±6.88
0-42.5
13.5±7.15
Urea rate (Mg/ha)
9.0±5.9
0-30
10.2±5.6
Fungicide application frequency
Gudene a
2.4±0.58
1-5
2.2±0.63
a
Jalene
2.6±0.72
1-5
2.2±0.55
Experience in seed potato
4.56±2.13
2-12
4.78±2.33
production (years)
Number of years the farmers had been growing the seed potato once they obtained
Jalene
4.06±1.6
1-7
4.39±1.34
Gudene
3.42±0.95
1-5
3.56±1.02
Number of seasons between seed
1.56±0.71
0-4
1.73±0.64
production on the same plot
Actual seed potato yield (Mg/ha)
15±11
1-50
10.3±6.8
Anticipated maximum yield (Mg/ha)
Gudene
33.3±9.3
6-50
25.3±9.6
Jalene
35.7±11.5
6-60
27.4±10.4
Ox holding (number)
2.3±1.68
0-18
2.7±1.72
a Jalene and Gudene are potato varieties.
3-5
15-60
40-100
1-4
1.6-40
0-26.7
0-5
1-4
1-12
1-7
1-5
0-3
0.6-37.7
8-50
8-50
0-14
There was difference in seed potato production activities between the farmers in the two
districts. For instance, farmers in Jeldu district used higher fertilizer rate, narrower inter- and
intra-spacing, and more frequent fungicide application than the farmers in Welmera district.
There was considerable gap in the actual reported yield and anticipated maximum yield
between the districts. Farmer in Jeldu reported higher actual and anticipated yields than
farmers in Welmera district. According to the 2010 harvest, farmers produced only 45% and
40.71% of the anticipated yield in Jeldu and Welmera districts respectively indicating seed
potato yield can be increased by 122% in Jeldu district and 145.63% in Welmera district.
Table 3. Education level, farm income and seed potato production activities of seed potato
farmers (in %)
Items
Jeldu
Welmera
Education level
Illiterate; primary (1-6); secondary (716; 47; 37; 0
30.2; 41.4; 27.8;
12);college (>12)
0.6
Total cash income per farmer – ETB 33137 for Jeldu and ETB 20722 Welmera
Seed potato; other crops; livestock
75.4; 19.6; 5.0
78.0; 12.8; 9.2
Occupation
Sole farming; farming and other
82.1; 17.9
91.4; 8.6
activities
Seed source
Own; market; institution
90.7; 1.9; 7.4
96.3; 1.9; 1.8
Seed size
Small; medium; mixed
0.6; 81.5; 17.9
1.2; 77.2; 21.6
Storage methods
Local; DLS
18.5; 81.5
28.4; 71.6
Planting date
7
Recommended; earlier than
recommended
Seed size for seed rate adjustment
No; yes
Negative selection
No; yes
Reason for negative selection
Bacterial wilt; other
18.5; 81.5
60.5; 39.5
26.3; 73.7
11.8; 88.2
100; 0
34; 66
-
99.1; 0.9
NB: ETB=Ethiopian Birr (1 USD equivalent to ETB 17)
3. Results and discussion
3.1. Effects of management attributes
Before running a main analysis, Leveve’s test was made on yield and quality scores, to check
for homogeneity of variance between groups. The Levene’s test was significant at p < 0.001
for both yield and quality scores indicating assumption of homogeneity of variance is
violated. However, for large sample size like the one used in this study, significant difference
between groups is expected and a double check for homogeneity of variance by using
variance ratio is recommended (Andy, 2005). If the quotient of the largest variance divided by
the smallest variance is less than two it is safe to assume homogeneity of variance. For data
used in this study the variance ratios were 1.24 for the yield scores and 1.27 for quality scores
indicating that it is safe to assume homogeneity of variance between the groups indicating
possible for undertaking parametric analysis. Besides, equal sample size per group are used.
In this case ANOVA gives fairly robust result even when assumption of homogeneity of
variance is broken.
Table 4 shows the main effects and effect sizes of seed potato management attributes
(conjoint attributes) on anticipated seed potato yield (from now on referred as yield unless
specified) and anticipated seed potato quality (from now on referred as quality unless
specified) scores. The main effects of the conjoint attributes on yield and quality were
significant for all attributes except the effect of land ploughing frequency on yield. That is,
farmers gave significantly different scores to the levels of all attributes with respect to their
effect on yield and quality except for the levels of land ploughing frequency with respect to
their effect on yield. This indicates, keeping other attributes levels constant, a shift from one
level to other level of an attribute significantly affected yield and quality.
The interaction effect between fertilizer rate and fungicide application frequency on yield and
quality was significant indicating that for a given level of fertilizer rate farmers gave lower
scores for anticipated yield and quality as the fungicide application frequency increased
and/or vice versa. For instance, for twice fungicide application the estimated marginal mean
was -0.283 when combined with below recommended fertilizer rate, 1.584 when combined
with recommended fertilizer rate and 0.174 (Table 7). The interaction effect between seed
source and district, planting date and district, and fertilizer rate and fungicide application
frequency and district on yield were significant at p < 0.001 and same held true for interaction
between seed source and district, planting date and district, fertilizer rate and district,
fungicide application frequency and district on quality. These significant interaction effects
between the attributes and the district indicates that farmers in the two districts perceived the
effects of the levels on yield and quality differently and thus gave different scores to the
levels. For instance, the highest estimated marginal means for seed source was highest for
institution seed farmers in Jeldu and the same was highest for own seed in Welmera (Table 6).
8
The values of Eta squared shows the effect sizes. The model explained 27.20% of the total
variation in yield due to conjoint attributes and their interactions. The same was 30.10% for
quality. The values of ‘per cent Eta Squared explained by the model’ show effects sizes of the
conjoint attributes and their interactions relative to the values of Eta Squared explained by the
model. Of the total variation in yield explained by the model 26.73, 17.98, 17.93, and 13.71%
were due to fertilizer rate, storage method, combined hoeing frequency and hill size, and
fungicide application frequency, respectively. Storage method, fertilizer rate, combined
hoeing frequency and hill size, fungicide application frequency had shares of 21.65, 18.19,
15.57 and 10.40% of the total variation of quality explained by the model in their respective
orders. The interaction between conjoint attributes and district contributed below 1% to the
total variation explained by the model for anticipated seed yield and quality even the
significant interactions.
The results of the effects and the importance score of the Delphi results (Appendix 2) are
more or less similar.
Table 4. Main and interaction effects of seed potato management attributes on anticipated
seed yield and quality (0 - 10 scale)
Source
Yield a
df
F
Corrected model
f1 (seed source)
f2 (seed size)
f3 (storage method)
f4 (sprouting method)
f5 (ploughing
frequency)
f6 (planting date)
f7 (hoeing frequency
and hill size)
f8 (fertilizer rate)
f9 (fungicide
application frequency)
f8 * f9
district * f1
district * f2
district * f3
district * f4
district * f5
district * f6
district * f7
district * f8
district * f9
district * f8 * f9
Error
Total
Corrected Total
Quality b
Eta
% Eta
F
Squared explained
by the
model
0.272
100
57.33***
0.011
4.18
99.87***
0.005
1.68
36.67***
0.049
17.98
509.50***
0.013
4.73
81.03***
0.000
0.00
26.70***
Eta
% Eta
Squared explained
by the
model
0.301
100
0.026
8.49
0.009
3.13
0.065
21.65
0.021
6.89
0.007
2.37
42
2
2
1
2
2
49.72***
42.65***
17.13***
367.12***
48.31***
0.42ns
1
2
102.94*** 0.014
183.08*** 0.049
5.04
17.93
93.90*** 0.012
183.19*** 0.047
3.99
15.57
2
2
272.90*** 0.073
139.96*** 0.037
26.73
13.71
213.97*** 0.055
122.31*** 0.031
18.19
10.40
4
2
2
1
2
2
1
2
2
2
4
5467
5832
5831
19.87***
7.11***
4.74**
2.15ns
0.33ns
5.96**
14.17***
0.66ns
2.13ns
1.09ns
4.93***
0.011
0.002
0.001
0.000
0.000
0.002
0.002
0.000
0.001
0.000
0.003
3.89
0.70
0.46
0.00
0.00
0.58
0.69
0.00
0.21
0.00
1.00
29.94***
7.61***
5.15**
6.48**
0.45ns
2.76ns
23.29***
0.003ns
7.22***
6.53***
2.62**
0.015
0.002
0.001
0.001
0.000
0.001
0.003
0.000
0.002
0.002
0.001
5.09
0.65
0.44
0.28
0.00
0.23
0.99
0.00
0.61
0.55
0.44
a = R Squared = 0.272 (Adjusted R Squared = 0.266); b = R Squared = 0.301 (Adjusted R Squared = 0.296)
*** = significant at p < 0.001; ** = significant at p < 0.01; * = significant at p < 0.05; ns = non-significant
9
3.2. Effect of attribute levels
The F-ratios in table 4 show only whether the conjoint attributes have significant effects on
yield and quality or not but do not show where the differences lie. For the significant effects it
is important to know where the difference between the attributes’ levels lie. Pairwise
comparisons of attribute levels were made using Ryan-Einot-Gabriel-Welch (REGWQ) Post
hoc procedures to know where the differences lie. REGWQ post hoc procedure was used
because it has good statistical power and tight control of the Type I error rate. Besides,
Games-Howell procedure was also used to compare the means for there is a little doubt in the
homogeneity of variance and Games-Howell test gives best performance when there is a
doubt of unequal variance. Table 6 shows estimated marginal means of levels and pairwise
comparisons. The estimated marginal means are the means predicted based on original values
for mean centred data of the dependent variables (yield and quality). The estimated marginal
means for yield and quality were below observed mean (for yield 3.526 in Jeldu and 4.270 in
Welmera; and for quality 3.522 in Jeldu and 4.243 in Welmera) for local storage method,
below recommended fertilizer rate and one time fungicide application, in both districts.
Besides, estimated marginal means for earlier than planting date in Jeldu and market seed and
once hoeing combined with small hill size in Welmera were below observed means for both
yield and quality. The highest estimated marginal means were scored by medium seed size,
DLS storage method, in store sprouting method, recommended planting date, twice hoeing
combined with big hill size and recommended fertilizer rate for yield and quality in both
districts.
The estimated marginal means for planting dates are not in line with the prevailing farmers
practice in Jeldu because 81.5% of the seed growers in Jeldu district plant seed potato in
earlier than recommended planting date which is contrary to the values of estimated marginal
means given in Table 7. According to some well experienced and well benefited seed potato
producing farmers in the two districts earlier than recommended planting date is preferred to
recommended planting date because when seed potato are planted in recommended planting
date 1) the yield becomes lower because of high incidence of diseases and lower intensity of
field management (e.g. not convenient for hoeing for the field gets muddy due high rainfall),
2) the cost of production becomes higher (e.g. farmers estimated the cost of hired labour and
fungicide to double because a) one day hoeing roughly takes two days due to inconvenience
to work and discontinuity of work when rain comes b) wage rate is higher because higher
demand for labour from other agricultural activities; and because of high incidence of diseases
due to high intensity of rainfall fungicide application frequency increase).
The estimated marginal mean for market seed was the lowest among the seed sources for the
anticipated yield and quality in both districts. Farmers had no trust on market seed for they
think the seed has problem of disease and impurity. Furthermore in Welmera the estimated
means were below observed means for both yield and quality because of incidence of
diseases, especially bacterial wilt, in the district. Farmers gave significantly different and high
score for medium seed size compared to small and mixed seed sizes for yield and quality in
both district except for anticipated yield in Welmera. Farmers in Welmera had attached less
importance to seed size compared to farmers in Jeldu which is evidenced by the not
significant difference between the seed sizes for yield in the district. There was interaction
effect of between ploughing frequency and district, but the interaction was not significant for
yield and significant for quality in both districts. Four and five ploughings had no significant
difference on yield and quality in both districts. For hoeing frequency combined with hill
size, estimated marginal mean for big hill size was significantly different from for small hill
sizes for yield and quality in both districts. Moreover, the three levels of hoeing frequency
10
combined with hill size were significantly different for anticipated quality in both districts.
Similar situation was true for fungicide application frequency.
The three fertilizer rate levels were significantly different for anticipated yield and quality in
both the districts. Majority of the farmers did not believe that use of above recommended
fertilizer rate increase their yield. The estimated marginal means were highest for interaction
between recommended fertilizer rate and twice fungicide application followed by the
interaction between recommended fertilizer rate and thrice fungicide application (Table 7).
1.
2.
3.
4.
5.
6.
7.
8.
Table 6. Estimated marginal means for main effects seed potato management attributes on
yield and quality in Jeldu and Welmera districts
Estimated marginal means for
Estimated marginal means for
yield
quality
Attributes
Jeldu
Welmera
Jeldu
Welmera
Seed source
Own
0.251a
0.390a
0.306a
0.323a
b
b
a
Market
0.061
-0.169
0.005
-0.306b
Institution
0.453c
0.313a
0.494a
0.488c
Seed size
Small
0.145a
0.171a
0.081a
0.102a
a
a
a
Mixed
0.105
0.105
0.140
0.088a
Medium
0.516b
0.257a
0.584b
0.316b
Storage method
Local
-0.202a
-0.214a
-0.242a
-0.238a
b
b
b
DSL
0.713
0.570
0.778
0.575b
Sprouting method
De-sprouted
0.053a
-0.014a
0.080a
0.017a
Special action
0.151a
0.109a
0.087a
0.000a
b
b
b
In store
0.561
0.439
0.638
0.488b
Ploughing frequency
Three
0.312a
0.079ac
0.034a
0.008a
Four
0.154a
0.269b
0.440b
0.214b
a
bc
b
Five
0.299
0.185
0.331
0.284b
Planting date
Earlier
-0.053a
0.036a
-0.026a
0.070a
Recommended
0.564b
0.319b
0.563b
0.267b
Hoeing frequency and hill size
Once and small
0.046a
-0.087a
-0.097a
-0.194a
a
a
b
Twice and small
-0.068
-0.151
0.132
0.029b
Twice and big
0.788b
0.772b
0.769c
0.671c
Fertilizer rate
Below
-0.302a
-0.452a
-0.151a
-0.448a
Recommended
Recommended
0.881b
0.756b
0.689c
0.635b
Above
0.186c
0.230c
0.267c
0.319c
Recommended
Fungicide application frequency
Once
-0.202a
-0.354a
-0.048a
-0.343a
Twice
0.492b
0.412b
0.344b
0.349b
b
b
c
Thrice
0.476
0.476
0.508
0.500c
11
Std. error is 0.052 for yield and 0.047 for quality except for local storage and earlier than planting date 0.037 for yield and 0.034 for quality
and DLS storage and recommended planting date 0.51 for yield.
Table 7. Estimated marginal means for fertilizer rate and fungicide application frequency
interaction effects on yield and quality in Jeldu and Welmera districts
Interaction of fertilizer rate (FR) and
fungicide application (FA) frequency
Below recommended FR and once FA
Below recommended FR and twice FA
below recommended FR and thrice FA
Recommended FR and once FA
Recommended FR and twice FA
Recommended FR and thrice FA
Above recommended FR and once FA
Above recommended FR and twice FA
Above recommended FR and thrice FA
Estimated marginal
means for yield
Jeldu
Welmera
-0.527
-0.969
-0.283
-0.336
-0.095
-0.052
0.087
-0.040
1.584
1.201
0.973
1.108
-0.166
-0.052
0.174
0.371
0.550
0.371
Estimated marginal
means for quality
Jeldu
Welmera
-0.040
-0.719
-0.398
-0.550
-0.016
-0.074
0.055
-0.062
1.163
1.065
0.849
0.901
-0.158
-0.247
0.268
0.531
0.691
0.673
Std. error equals 0.087 for yield and 0.080 for quality
4. Conclusions and further research
This study elicited farmer’s opinion on seed potato management attributes with respect to
their effect on yield and quality. The results show that differences existed within and between
districts in the degree to which management attributes and their levels were perceived to
contribute to yield and quality which indicate that there exists possibility to develop
alternative seed potato production methods from which farmers can choose a method that
suits their local circumstances. However, further research is needed to examine cost
effectiveness of the production methods.
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13
Appendix. Delphi result
Table 1. Weight (%) of management attributes regarding their importance to yield and quality
of seed potato production given by farmers
Yield
Quality
Attributes
Mean±Std.dev
Degem
Jeldu
Welmera
Degem
Jeldu
Welmera
(n=3)
(n=4)
(n=8)
(n=3)
(n=4)
(n=8)
Seed source
6.0±1.7
25.0±10.0
7.6±2.9
9.7±5.5 22.0±8.0
7.5±1.8
Seed size
4.0±1.0
5.5±1.7
5.0±1.9
6.7±4.7
4.3±3.0
5.1±2.7
Storage method
3.0±1.0
4.0±1.4
7.8±2.5
4.7±3.1
8.7±4.5
6.6±1.8
Sprouting method
6.7±3.2
5.0±3.8
6.0±1.9
5.3±0.6
2.7±1.7
5.8±1.0
Land ploughing
frequency
5.3±1.2
6.5±1.7
8.0±3.7
9.3±6.0
4.7±1.7
8.1±3.4
Spacing
5.0±3.5
4.7±2.1
6.6±1.7
4.3±2.1
4.0±1.8
5.9±2.7
Seed rate
5.7±3.5
3.7±1.5
4.9±1.5
4.7±2.9
5.1±1.3
5.4±2.3
Planting date
6.3±2.1
4.3±1.0
6.5±1.5
8.3±2.9
4.0±0.8
6.4±1.6
Hoeing frequency
7.0±2.6
4.5±1.7
7.4±1.6
6.3±3.2
5.0±1.4
6.3±2.0
Hilling
6.0±2.6
3.3±1.5
7.1±1.4
5.3±4.0
5.8±2.5
6.8±2.1
Fertilizer rate
8.0±1.5
6.0±1.7
5.8±2.5
9.3±0.6
7.5±2.4
6.6±3.1
Fungicide
application
frequency
11.0±5.3
5.0±0
8.0±2.2
8.0±3.5
4.5±2.4
7.5±1.3
Negative selection
na
Na
6.4±1.6
na
na
6.7±1.6
Harvesting tools
3.7±1.5
3.0±1.4
0.9±2.1
3.0±1.7
5.0±3.6
4.7±2.3
Rotation
4.7±4.0
4.5±1.0
6.2±0.9
6.0±2.6
6.5±3.1
4.9±2.1
Difference in
variety
6.7±2.3
6.5±4.0
2.6±1.8
5.4±2.5
3.7±2.1
3.1±1.2
Haul killing
na
na
1.0±2.5
na
na
1.6±1.2
Sorting
5.3±1.5
3.0±1.4
na
5.3±5.1
4.5±1.3
1.0±2.8
Type of
transportation
4.3±1.2
2.0±1.4
na
1.7±0.6
3.7±2.5
na
Total
100
100
100
100
100
100
Note: na means not applicable
Table 2. Weight (%) of management attributes regarding their importance to yield and quality
of seed potato production as given by experts
Yield
Quality
Attributes
Mean±Std. dev.
Round 1 (n=5) Round 2 (n=4) Round 1 (n=5) Round 2 (n=4)
Seed source
7.9±2.4
8.3±1.2
6.6±3.8
6.8±0.5
Seed size
6.4±2.0
6.4±1.0
5.8±1.8
5.8±0.9
Storage method
7.5±2.9
6.8±2.9
7.2±1.9
6.8±1.3
Sprouting method
7.2±2.3
6.5±1.7
6.7±2.6
5.9±2.2
Land ploughing
frequency
6.0±1.5
6.6±0.4
5.2±1.3
5.5±1.0
Spacing
6.5±1.2
6.1±0.9
5.9±0.7
5.9±0.3
Seed rate
6.1±1.9
5.5±1.7
5.3±2.7
4.4±2.3
Planting date
5.2±0.8
5.4±1.1
5.4±0.9
5.2±0.5
14
Hoeing frequency
Hill size
Fertilizer rate
Fungicide frequency
Negative selection
Harvesting tools
Rotation
Difference in variety
Haul killing
Sorting
Total
Note: na means not applicable
5.6±2.2
6.9±1.6
11.0±4.0
8.6±2.0
7.9±3.5
1.0±2.2
2.4±1.4
2.8±1.4
1.0±2.2
na
100
5.6±1.4
6.8±0.9
9.0±4.0
8.8±2.2
6.0±0.9
na
5.6±1.3
6.6±0.9
na
na
100
4.4±0.9
5.4±0.9
9.0±3.8
6.0±1.2
8.2±1.3
8.2±3.1
na
na
5.8±3.3
na
100
4.2±1.0
5.7±0.5
7.0±3.4
6.8±1.5
6.5±1.3
6.9±1.4
4.5±2.1
5.6±0.9
4.5±2.4
2.0±2.4
100
15