Constraints to agricultural intensifi cati on among rice and potato farmers in Eastern and South Western

Uganda

Lydia Nazziwa Nviiri

International Institute of Tropical Agriculture (IITA), Uganda

PASIC project

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’

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

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?

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 productionTarget 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

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

Experience in using improved seed

Ever used improved

seed

Certified Recycled by HHD Recycled by another input

provider

Certified and recycled

0

10

20

30

40

50

60

70

80

90 85

5.1

22.2

64.9

7.8

56.3

12.4

58.7

1117.9

Figure 1: % Using improved seed varieties

Potato Rice

Seed varieties commonly grown

Reasons for not using the perceived improved seed varieties

66%

14%

10%5% 5%

Figure 2: Potato farmers (n=52)

AffordabilityKnowledgeAccessProfitabilityOthers

47%

37%

13%

3%

Figure 3: Rice farmers (n=30)

AffordabilityAccessibilityKnowledgeQuality

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;

Low yields

Do not know

very low price

Insect infestation

Other attributes

0 10 20 30 40 50 60 70

Fig 4: fake potato seed

Low yields

Several varieties mixed together

Do not know

brokenness

Others

0 10 20 30 40 50 60

Fig 5: fake rice seed

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)

Affordability Knowledge Availability Others specify0

10203040506070

53

35

6 6

58

33

5 4

Fig 6: Reason for not applying fertilizer

% potato % rice

Current input use and extension services

Used Pest/

herb/fu

ngicide

Used Fe

rtiliz

er

Aware of e

xtensio

n in th

e area

Accesse

d general e

xtensio

n

Accesse

d rice

/potato exte

nsion

0

10

20

30

40

50

60

7064

32

61

38

31

15 17

49

26

12

Figure 7: % current Input use and access to extension services

Potato Rice

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

Application of recommended production practices

% practices applied as rec-ommended

% practices not applied as recommended

% practices not applied at all

0 10 20 30 40 50 60 70% 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

05

10152025303540

% 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

Comparison in level of productivity based on input use

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

me

an

of pro

d_

hh

Productivity of rice farmers based on application of recommended practices at different stages

Econometric model

Dependent variable; proportion of recommended practices applied by each householdLinear regression model was used to investigate the factors that influence the adoption of recommended farming practices

Empirical model

• Several independent variables were in the regression model namelyVariable Hypothesized relationshipSex of household head (1 male, 0 women) PositiveEducation level of household head PositiveAge of household head NegativeAccess to credit PositiveAccess to rice/potato extension and training services

Positive

Farm size NegativeLocation of the household in relation to nearest market, all weather road, extension office, water source, farm input shop

Negative

Family size PositiveAccess to hired labour PositiveTopography (dummies) Land tenancy (dummies) Land use restrictions NegativeMarket status (1 for farmers who sale and 0 for those who don’t

positive

Membership to a farming group Positive

Model results

Parameter Coef. Std. Err. t P>|t| CONSTANT .4713476 .0421667 11.18 0.000 farmsize .0005155 .0058932 0.09 0.930 sex_head_2 -.003255 .0162676 -0.20 0.841 age_head -.0000955

.0003879 -0.25 0.806

crop_extension_last_5_years .0679058 .0122572 5.54 0.000 landuse_restrictions -.0117701

.014303 -0.82 0.411

Icredit_la_2 .0221001 .0152971 1.44 0.149 Agcredit .0228281 .0130866 1.74 0.081 hired_labour .028002 .0123892 2.26 0.024 tenancy_own .0271717 .0226938 1.20 0.232 tenancy_borrowed -.0126233

.0167325 -0.75 0.451

tenancy_rented .0016046 .0134149 0.12 0.905 marketstatus .0596965 .0117614 5.08 0.000 _Ieduc_head_1 .0073648 .0187296 0.39 0.694 Ieduc_head_2 .0248069 .0212415 1.17 0.243 _Ieduc_head_3 .0268605 .0219101 1.23 0.221 educ_head_4 -.0147752

.0312741 -0.47 0.637

educ_head_5 .048979 .0345985 1.42 0.157 dependent -.0000152

.0050773 -0.00 0.998

children .0021835 .0035093 0.62 0.534 adult_men .0055757 .0051574 1.08 0.280 adult_women .0126917 .0061052 2.08 0.038 socialgroup -.0034248

.0133416 -0.26 0.797

top_gentle -.0116855

.0104647 -1.12 0.264

top_steep -.0208094

.0129672 -1.60 0.109

top_valley .0329486 .0136059 2.42 0.016 distance_extension_office -.0002303

.0008469 -0.27 0.786

distance_all_weather_roads -.0010618

.0007048 -1.51 0.132

distance_closet_farm_supply_shop .0010393 .0007159 1.45 0.147

distance_water_source -.0073635

.0032956 -2.23 0.026

crop_2 -.0343248

.0150779 -2.28 0.023

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

Thank you