This study examines the dynamics of rice commercialization in Tanzania through a panel study approach. The objectives are to identify drivers of commercialization such as technology adoption, rural electrification, and migration. The study also analyzes the effects of different commercialization options on livelihood outcomes like poverty, food security, and women's empowerment. A stratified random sample of 559 households in eight villages is used. The results show that labor-saving technologies like tractors, herbicide/insecticide, and animal drawn tillage are widely adopted. Commercialization is occurring in response to demand, with area expansion driven by these technologies. Migration is also influencing commercialization patterns. Overall, commercialization options are improving livelihoods, though

1. Dynamics of Rice Commercialisation
in Tanzania
Aida Isinika – Sokoine University of Agriculture, Tanzania
Christopher Magomba – Sokoine University of Agriculture, Tanzania
APRA Work Stream 1 Panel Study Review and Planning Workshop
Afrint-APRA Seminar, IDS, Brighton - 3 October 2018
Funded by UK aid from the UK Government
www.future-agricultures.org/apra

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Introduction

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Study Objectives & Design
Drivers;
• Technology adoption
• Rural electrification
• Migration (people &
Livestock)
• Market linkage
Stratification
• Electrification
• Farm holding
SSF
MSF
SRI
Identify and analyse the effect of different forms of
rice commercialisation options on livelihoods in
terms of Poverty, Food Security and Women’s
Empowerment
Specific objective
What Drivers?
What Options?
What Outcomes &
Impacts?

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Stratum Village SSF MSF SRI Total
With electricity
by 2016/17
Mchombe 41 0 27 68
Mngeta 40 1 22 63
Chita 40 2 14 56
Itongowa 40 1 9 50
Has electricity
by 2017/2018
Njage 40 2 10 52
Mkusi 40 4 0 44
Makutano 43 4 4 51
Nakaguru 40 10 8 58
No electricity
by 2019
Ijia 41 19 4 64
Luvilikila 43 7 3 53
Total 408 50 101 559
Percent 73% 9% 18% 100%
Final sample size of households per village

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Adoption of intensification options
Technology
% Adopters
With Electricity Without Electricity Whole
Sample
SSF MSF SRI All SSF MSF SRI All
Purchased rice seed 21.9 2.4 16.6 19.6 17.2 11.3 17.1 16.3 17.56
Inorganic fertilizer 7.6 5.9 26.7 14.4 10.0 3.6 23.6 10.4 12.0
Organic fertilizer 1 0 8.5 3.6 0.8 0 5.5 1.2 2.2
Tillage services 90.9 94.1 89.2 90.4 84.1 92.8 94.5 86.6 88.1
Tractor 68.2 43.8 82.2 71.9 29.3 10.4 38.5 27 45.3
ADT 41.9 56.3 26.2 37.1 75.6 94.8 65.4 77.7 61.2
Herbicide/
Insecticide
59.9 70.6 71.7 64.7 50 66.3 74.5 55.3 59.0
• Labor↓ technologies widely adopted
• Followed Herbicides
• Organic fertilizer least adopted
• SRI leading on productivity technologies
• Followed by SSF
• MSF lead in adopting ADT related to
immigration
• Electricity villages doing better except
ADT

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Main alternative income
10.2
44
57.2
25.9
4.85.5
60.7
36.8
17.9
3.5
7.6
53.1
46.1
21.5
4.1
0
10
20
30
40
50
60
70
Regulary
employment
Casual labour Household
Enterpise
Gift&Remittance Social transfer
%
Main alternative income source
With electricity Without electricity Total

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Highlights
• Commercialisation is happening – driven by
technology responding to demand
• Labour-saving technologies (ADT, Tractor,
herbicide/insecticide) → Area expansion
• MSF driving ADT adoption, Spillover to SSF & SRI
• Proportion of farmers who are intensifying using
new inputs (improved seed; fertiliser; SRI) is still
small
• Area expansion → Land markets; giving
immigrants relative advantage for land rental

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The Team
Team Member Organisational
Affiliation
Area of Responsibility
Aida Isinika Sokoine University of
Agriculture(SUA)
Research leader/ Qualitative
Gilead Mlay SUA Quantitative (sampling & data
analysis)
Christopher Magomba SUA Quantitative/ Data analysis
Kizito Mwajombe SUA Extension/ Sociology
Jeckonia John SUA Political Scientist
Devotha Kilave SUA Gender/ nutrition
Ntengua Mdoe SUA Advisor
Isack Minde SUA Advisor
Colin Poulton SOAS Advisor