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Monitoring, Evaluation and Learning (MEL): Regional TrendSri Lmb
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Karnataka has largest proportion (79%) of drought prone area in India. Over 56% of population depends on agriculture for its livelihood. Reduction in per capita land availability from 1.95 to 1.74 ha during 1976-77 to 2005-06. Largest producer of coarse cereals (15.35%). Shift towards horticultural crops.
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IFPRI is engaged in Policy Reform Initiative in Nepal with overall goal to reform agriculture sector for accelerating agricultural growth and enhancing farm incomes. In view of large number of smallholdings in Nepal, contract farming is envisaged as one of the strategies to increase their incomes by linking them with remunerative domestic and global markets. At present, contract farming in Nepal is at its infancy and needs to be popularized. This would require enabling polices and appropriate institutional arrangements. The main aim of the workshop is to learn lessons from the best practices in neighboring countries to address the multi-faceted challenges and opportunities in promoting and up scaling pro-smallholder contract farming in Nepal.
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Constraints to agricultural intensification among rice and potato farmers in Eastern and South Western Uganda
1. Constraints to agricultural intensification among rice
and potato farmers in Eastern and South Western
Uganda
Lydia Nazziwa Nviiri
International Institute of Tropical Agriculture (IITA), Uganda
PASIC project
2. Rationale
• Uganda’s population growth rate currently stands at of 3.2% per annum
• The agricultural sector is growing at a much slower rate (1.5% in 2013/14)
• To feed this rapidly growing population, yields will have to increase
significantly
• Actual yields for nearly all crops are far below (<30%) potential
• Agricultural intensification is a must to achieve significant yield increments
• Need to produce more on the same land resources
• Options to put new land into production is rather limited
For farmers to change:
• -> Need for technologies
• -> Need for ‘enabling environment’
3. Over view of the PASIC project
The Policy Action for Intensification of Cropping Systems (PASIC) is a project in
Uganda which aims to contribute to improved household incomes, livelihoods,
and food and nutrition security in Uganda through sustainable intensification of
cropping systems.
The project will stimulate action in selected policies and programs relevant for
agricultural intensification of smallholder production systems, through
evidence-based research and strengthening of capacities of relevant
institutions.
The PASIC project is being managed by International Institute of Tropical
Agriculture (IITA) in partnership with;
- Ministry of Agriculture, Animal Industries and Fisheries (MAAIF)
- Economic Policy Research Centre (EPRC)
- International Food Policy Research Institute (IFPRI)
Target policies; Seed, fertilizer and extension
Target crops; Lowland rice and Irish potatoes
4. Household socio economic survey
• The aim of the study was to generate an evidence base surrounding crop
intensification; provide an understanding of the current status of agricultural
production, productivity and marketing at household level given the current
enabling environment surrounding crop intensification.
• Research questions
1. What are the drivers of intensification?
2. Does intensification improve production and productivity?
3. Does intensification affect well-being?
5. Methodology of Household socio economic survey
Purposive random sampling in two regions
South Western Highlands (Kabale, Kisoro and Kanungu) for potato production
Kioga plains (Tororo, Bugiri and Butaleja) for rice production
Target farmers
Grew potato or rice in the 2nd season of 2013 and 1st season of 2014
Individual face to face interviews with a structured questionnaire
A total of 902 farmers were interviewed
6. Constraints to Agricultural Intensification among Rice and Potato Farmers in
Eastern and South Western Uganda
Specific Objective
The objective of the paper is to explore the
knowledge gaps that are influencing the
adoption of agricultural intensification
technologies among rice and potato
farming households in Uganda
7. Experience in using improved seed
85
5.1
22.2
64.9
7.8
56.3
12.4
58.7
11
17.9
0
10
20
30
40
50
60
70
80
90
Ever used
improved seed
Certified Recycled by HHD Recycled by
another input
provider
Certified and
recycled
Figure 1: % Using improved seed varieties
Potato Rice
9. Reasons for not using the perceived improved seed varieties
66%
14%
10%
5% 5%
Figure 2: Potato farmers (n=52)
Affordability
Knowledge
Access
Profitability
Others
47%
37%
13%
3%
Figure 3: Rice farmers (n=30)
Affordability
Accessibility
Knowledge
Quality
10. Experience in using “fake” rice and potato seeds
• 48% of the potato farmers and 34% of rice farmers had experience
in using fake seeds
• The common traits of fake seeds are;
0 20 40 60 80
Low yields
Do not know
very low price
Insect infestation
Other attributes
Fig 4: fake potato seed
0 20 40 60
Low yields
Several varieties mixed…
Do not know
brokenness
Others
Fig 5: fake rice seed
11. Experience in fertilizer use on rice and potato
• 41% of potato farmers and 18% of the rice farmers have ever applied fertilizer on
potato and rice
• The reasons for not applying fertilizer are;
• 16 % of potato and 11% of rice farmers abandoned the use of fertilizers because;
Not affordable (29% of potato and 36.4% of rice farmers)
Not profitable (27.3% of rice and 7% of potato farmers)
53
35
6 6
58
33
5 4
0
20
40
60
80
Affordability Knowledge Availability Others specify
Fig 6: Reason for not applying fertilizer
% potato % rice
12. Current input use and extension services
64
32
61
38
31
15
17
49
26
12
0
10
20
30
40
50
60
70
Used Pest/herb/fungicide Used Fertilizer Aware of extension in the
area
Accessed general
extension
Accessed rice/potato
extension
Figure 7: % current Input use and access to extension services
Potato Rice
13. Experience in accessing extension and training services
The major reasons for not accessing extension services are;
Programmes not available in the area (54% pot and 71% rice)
Target only farmers group (20% pot and 9% rice)
Other reasons are lack of interest, mistrust the information provided, lack
information about the training
Major areas of focus for the extension/training service
Training on agronomic practices (34.6 % pot, 46.4% rice)
fertilizer use (14.4% pot, 17.4% rice)
pesticide/herbicide use (17.7% pot, 7.3% rice)
Improved seed varieties (9.1% pot, 11.6% rice)
Only 9% of potato (n=172)and 12% (n=60)of rice farmers paid for the
extension services
84% of potato (n=171) and 64% (n=58) of rice farmers were willing to pay for
extension services
14. Application of recommended production practices
0 20 40 60 80
% practices applied as
recommended
% practices not applied as
recommended
% practices not applied at all
% Rice % Potato
Practices not applied as recommended are
considered as “not practicing”
59% of the potato and 65% of the rice
practices not being applied was because
the farmers were not aware of the
recommendations
0
5
10
15
20
25
30
35
40
Expensive Not
necessary
Labor
intensive
Lack
technical
knowledge
Not
beneficial
dangerous
to health
or plant
Other
specify
% Potato % Rice
53% of potato and 47% of rice for not
applying recommended practices is
due to knowledge gaps.
This is illustrated in farmers’ perception
that some practices are not necessary,
not beneficial, dangerous and limited
technical knowledge
16. Comparison in level of productivity based on application of recommended practices
0
500
1,000
1,500
2,000
Never Rarely Often Never Rarely Often
Pre_planting production_phase
Productivity of rice farmers based on application of recommended practices at different stages
17. Econometric model
Dependent variable; proportion of recommended practices applied by each
household
Linear regression model was used to investigate the factors that influence the
adoption of recommended farming practices
18. Empirical model
• Several independent variables were in the regression model namely
Variable Hypothesized relationship
Sex of household head (1 male, 0 women) Positive
Education level of household head Positive
Age of household head Negative
Access to credit Positive
Access to rice/potato extension and training
services
Positive
Farm size Negative
Location of the household in relation to nearest
market, all weather road, extension office, water
source, farm input shop
Negative
Family size Positive
Access to hired labour Positive
Topography (dummies)
Land tenancy (dummies)
Land use restrictions Negative
Market status (1 for farmers who sale and 0 for
those who don’t
positive
Membership to a farming group Positive
20. Conclusion
The econometric modelling using farmer and area
characteristics, socioeconomic and institutional variables
can lead to more effective targeting to farmers and areas
where higher adoption rates of agricultural intensification
technologies may occur.
Achieving increased productivity requires availing the
farmers with adequate information and knowledge about
the recommended farming practices.
Farmers will only realize the increased productivity from
modern technologies like improved seeds, fertilizers, and
pesticides/herbicides if these are applied correctly along
with all the other farming practices