influence of agricultural production techniques on food...

Faculty of Bioscience Engineering

Academic year 2010 – 2011

INFLUENCE OF AGRICULTURAL

PRODUCTION TECHNIQUES ON FOOD

SECURITY IN BURUNDI:

THE CASE STUDY OF NGOZI PROVINCE

JEANNINE AHISHAKIYE

Promoter: Prof. dr. ir. Luc D’ Haese

Tutor: Ir. Evy Mettepenningen

Master’s dissertation submitted in partial fulfillment of the requirements

for the degree of Master of Science in Nutrition and Rural Development,

Main subject: Human Nutrition

Copyright “All rights reserved. The author and the promoters permit the use of this Master’s Dissertation for

consulting purposes and copying of parts for personal use. However, any other use falls under the

limitations of copyright regulations, particularly the stringent obligation to explicitly mention the

source when citing parts out of this Master’s dissertation.”

Ghent University, 26th August, 2011

Promoter Tutor

Prof. dr. ir. Luc D’Haese Ir. Evy Mettepenningen

The Author

Jeannine Ahishakiye

i

ABSTRACT

The present study departed from the problematic issue of food insecurity that hits Sub-Saharan

countries and among them Burundi. One of the major components of food security is food

availability and the rest of the components take their roots in it. However, food availability is not

assured if mechanisms are not devised in order to accrue food production. This study investigates

drivers of food security with reference to agricultural development. The study’s specific objectives

are to identify different farming systems and techniques in Burundi, particularly in Ngozi, to assess

possible correlations between food security and production techniques and finally to analyze

factors influencing the uptake of agricultural production techniques. The analysis is based on

survey data gathered from 360 randomly selected households in the study area of Ngozi Province

through the use of structured questionnaires. Binary logistic regression was used not only to

identify agricultural production techniques influencing household food security but also to identify

factors influencing the uptake of fertilizer and anti-erosion hedges as agricultural production

techniques. Results indicate that among variables considered, use of fertilizer, use of manure and

farm size showed statistically significant positive effect on household food security in the study

area. As for the uptake of fertilizer, membership of cooperative and number of visits per month by

extension workers were the factors that influence the adoption of fertilizer while farm size and

membership of a cooperative were factors influencing the adoption of anti-erosion hedges. The

findings imply that improvement in food security requires strengthening and expanding extension

services in order to accelerate adoption of agricultural technology, create off-farm rural

employment, promote and strengthen farmers’ organization. These areas could provide entry

points for policy intervention in order to enhance household food security.

Key words: Food security- Burundi-Agricultural production techniques

ii

ACKNOWLEDGEMENT

This master’s dissertation would not have been realized without the help and support of many. I

would like to extend my sincere gratitude to all those who made it possible.

It is an honor for me to thank my promoter Prof.dr. ir. Luc D’ Haese. Without him this dissertation

would never have been realized. I owe my deepest gratitude to Ir. Evy Mettepenningen, my tutor,

thank you for all your assistance and support in making this master dissertation writing a success. I

thank you for your endless patience and good humor.

The financial support from the Belgian Technical Cooperation (BTC) during my entire master

studies is gratefully acknowledged.

I would like to show my gratitude to the Coordinator of the Human Nutrition and rural

development Program, Ir. Anne-Marie Remaut –De Winter, and Marian Mareen for their

understanding, encouragemet and personal guidance that have provided a good basis for the

present master’s dissertation.

I am sincerely grateful to Prof.dr.ir. Marijke D’Haese for her support in a number of ways towards

the realization and completion of this master’s dissertation.

I would also like to thank Françoise Claeys Bouuaert for her encouragement and support

throughout my stay and studies at Gent University.

Last, but not least, I would like to express my deepest gratitude to my family, my husband

Schadrack and my children, Treasure and Blessings for their love, and patience. Dear Schadrack

Dusabe, your emotional support lifted me up every day, encouraged me and gave me a reason to

always look towards my goals. For these, I cannot thank you enough.

iii

DEDICATION

To my husband Schadrack Dusabe

my son Treasure and daughter Blessings

and

my mother, brothers and sisters and my late father

iv

TABLES OF CONTENTS

Copyright.......................................................................................................................................................... ii

ABSTRACT ...................................................................................................................................................... i

ACKNOWLEDGEMENT ............................................................................................................................... ii

DEDICATION ................................................................................................................................................ iii

TABLES OF CONTENTS .............................................................................................................................. iv

LIST OF TABLES ......................................................................................................................................... vii

LIST OF FIGURES ......................................................................................................................................... ix

LIST OF ACRONYMS .................................................................................................................................... x

Chapter 1 : INTRODUCTION AND BACKGROUND INFORMATION ................................ 1

1.1. INTRODUCTION ............................................................................................................................ 1

1.2. DESCRIPTION OF THE STUDY AREA ....................................................................................... 2

1.2.1. Background information on Burundi ....................................................................................... 2

1.2.2. Main features of Ngozi province .............................................................................................. 3

1.3. PROBLEM STATEMENT .............................................................................................................. 6

1.4. STUDY OBJECTIVES AND RESEARCH QUESTIONS ............................................................. 7

1.5. STRUCTURE OF THE STUDY .................................................................................................... 8

Chapter 2 : LITERATURE REVIEW ........................................................................................... 9

2.1. AGRICULTURE IN DEVELOPING WORLD’S ECONOMY ...................................................... 9

2.2. THE CONCEPT OF FARMING SYSTEM ................................................................................... 11

2.2.1. Farming systems in Sub-Saharan Africa ................................................................................ 11

2.2.3. Adoption of new technologies by African farmers ................................................................ 13

2.2.4. Major crops under cultivation in Burundi .............................................................................. 18

2.2.5. Agricultural techniques in Burundi and institutions stimulating their uptake ........................ 19

2.3. THE CONCEPT OF FOOD SECURITY ...................................................................................... 20

2.3.1. Dimensions of food security .................................................................................................. 22

2.3.2. Determinants of Household Food Security ........................................................................... 24

2.3.3. Food security Pattern in Burundi over time ........................................................................... 25

2.3.4. Crop based contribution to food security in Burundi ............................................................. 25

v

Chapter 3 : METHODOLOGY AND DESCRIPTION OF THE SAMPLE ............................... 27

3.1. DATA COLLECTION .................................................................................................................. 27

3.2. DESIGN OF THE QUESTIONNAIRE. ....................................................................................... 27

3.3. ANALYTICAL TOOLS ................................................................................................................ 29

3.3.1. Model specification for the influence of agricultural production techniqueson food ................

security .................................................................................................................................. 31

3.3.2. Model specification for the uptake of agricultural production techniques. ............................ 32

3.4. DESCRIPTION OF THE SAMPLE .............................................................................................. 33

3.3.1. Characteristics of households in the sample ........................................................................... 33

3.3.2. Farm size and land use in Ngozi province 2007..................................................................... 34

3.3.3. Households’ source of income ............................................................................................... 35

3.3.4. Households’ yearly expenditures on food and agricultural inputs ......................................... 36

Chapter 4 : RESULTS AND DISCUSSION ............................................................................ 37

4.1. OVERVIEW OF THE ADOPTION OF FARMING TECHNIQUES IN NGOZI PROVINCE ... 37

4.1.1. The use and source of improved seeds ................................................................................... 37

4.1.2. Use of chemical products ....................................................................................................... 38

4.1.3. Source of chemical fertilizers and pesticides ......................................................................... 39

4.1.4. Soil organic matter improvement techniques ......................................................................... 39

4.1.5. Marshland improvement techniques ...................................................................................... 40

4.1.6. Sowing in line......................................................................................................................... 41

4.1.7. Anti-erosion hedges ................................................................................................................ 41

4.2. EVOLUTION OF AGRICULTURAL PRODUCTION TECHNIQUES ...................................... 42

4.3. INFLUENCE OF AGRICULTURAL PRODUCTION TECHNIQUES ON CROP YIELD ........ 43

4.3.1. Influence of chemical fertilizers ............................................................................................. 43

4.3.2. Influence of manure ............................................................................................................... 43

4.3.3. Influence of irrigation ............................................................................................................. 44

4.3.4. Influence of anti-erosion hedges ............................................................................................ 45

4.4. OVERVIEW OF FOOD SECURITY IN NGOZI PROVINCE ..................................................... 46

4.5. RELATIONSHIP BETWEEN HOUSEHOLD FOOD SECURITY AND AGRICULTURAL

PRODUCTION TECHNIQUES ....................................................................................................... 48

4.5.1. Relationship between household food security and agricultural production techniques:

bivariate analysis .................................................................................................................... 48

vi

4.5.2. Relationship between household food security and agricultural production techniques:

multivariate analysis ............................................................................................................... 49

4.6. FACTORS INFLUENCING THE ADOPTION OF AGRICULTURE PRODUCTION

TECHNIQUES .................................................................................................................................. 54

4.6.1. Factors influencing the adoption of fertilizer. ....................................................................... 55

4.6.2. Factors influencing the adoption of anti-erosion hedges. ...................................................... 58

Chapter 5 : CONCLUSION POLICY IMPLICATIONS AND RECOMMENDATIONS ...... 62

REFERENCES ................................................................................................................................ 65

ANNEX (see CD enclosed) .............................................................. Error! Bookmark not defined.

vii

LIST OF TABLES

Table 1.1: Distribution and population density per commune in 2005 .............................................. 5

Table 2.1: Data points for agriculture’s three worlds according to the 2008 World Development

Report ............................................................................................................................................... 10

Table 2.2: Typology of agricultural production systems in Burundi ............................................... 13

Table 2.3: Literature Review on factors influencing the adoption or rejection of agricultural

technologies ..................................................................................................................................... 16

Table 2.4: Literature Review on factors influencing the adoption of agriculture technologies

(Cont.) .............................................................................................................................................. 17

Table 2.5: Evolution of food crops production in Burundi between 2000 - 2007 ........................... 26

Table 3.1: Descriptive statistics of the categorical variables included in the regression model ...... 32

Table 3.2: Descriptive statistics of the continuous variables included in the regression model ...... 32

Table 3.3: Descriptive statistics of the categorical variables ........................................................... 33

Table 3.4 : Descriptive statistics of the continuous variables .......................................................... 33

Table 3.5: Characteristics of the households in the sample ............................................................. 34

Table 3.6 : Farm size and land use in Ngozi 2007 ........................................................................... 34

Table 4.1: Source of seeds for the respondents ................................................................................ 37

Table 4.2: Use of chemical products by the respondents in Ngozi (2007) ...................................... 38

Table 4.3: Sources of fertilizer and pesticide supply ....................................................................... 39

Table 4.4: Soil organic matter improvement techniques ................................................................. 40

Table 4.5: Marshland improvement techniques ............................................................................... 40

Table 4.6: Level of improvement in the use of agricultural technologies in Ngozi between 2005-

2007.................................................................................................................................................. 42

Table 4.7: Comparison of food crop yield among adopters and non adopters of fertilizer (kg over

the three seasons per farm) .............................................................................................................. 43

Table 4.8: Comparison of food crop yield among manure users and non users (kg over the three

seasons per farm) ............................................................................................................................. 44

Table 4.9: Comparison of food crop yield between adopters and non adopters of irrigation (kg over

the three seasons per farm) .............................................................................................................. 44

Table 4.10: Comparison of food crop yield among adopters and non adopters of anti-erosion

hedges (kg over the three seasons per farm) .................................................................................... 45

Table 4.11: Households food security status categories in Ngozi province in 2007 ....................... 48

Table 4.12: Bivariate analysis between food security and food production techniques .................. 49

Table 4.13: Relationship between agricultural production techniques and food security (Dependant

variable: Severely food insecure)..................................................................................................... 51

Table 4.14: Statistical tests for the model ........................................................................................ 51

Table 4.15: Factors influencing the adoption of fertilizer (Dependant variable: fertilizer use) ...... 55

Table 4.16: Statistical tests for the model ........................................................................................ 55

viii

Table 4.17: Factors influencing the adoption of anti-erosion hedges (Dependant variable: Use of

anti-erosion hedges). ........................................................................................................................ 58

Table 4.18: Statistical test for the model ......................................................................................... 59

ix

LIST OF FIGURES

Figure 1.1: Map of Burundi ............................................................................................................... 3

Figure 1.2: Analytical framework for the influence of agricultural production techniques on food

security ............................................................................................................................................... 8

Figure 2.1: Level of adoption of improved varieties of cereals ....................................................... 14

Figure 2.2: Level of adoption of fertilizer use ................................................................................. 14

Figure 2.3: Level of adoption of irrigation ...................................................................................... 15

Figure 2.4: Top production-Burundi-2007 ...................................................................................... 18

Figure 2.5: Conceptual framework of food security ........................................................................ 24

Figure 2.6: Evolution of the population and food crop production ................................................. 26

Figure 3.1: Source of income in Ngozi province (2007) ................................................................. 35

Figure 3.2: Households’ yearly expenditure on food and inputs (2007) in Ngozi province ........... 36

Figure 4.1: Agricultural production techniques in Ngozi province (2007) ..................................... 41

Figure 4.2: Frequency of respondents’ experiences for each of the nine HFIAS generic questions 46

Figure 4.3: HFIAS score for the households in Ngozi province (2007) .......................................... 47

Figure 4.4: Probability of being severely food insecure .................................................................. 54

Figure 4.5: Probability of adopting fertilizer ................................................................................... 58

Figure 4.6: Probability of adopting anti-erosion hedges .................................................................. 61

x

LIST OF ACRONYMS

ETOA Environmental Threats and Opportunities Assessment

EU European Union

FAO Food and Agriculture Organization

GDP Gross Domestic Product

GHI Global Hunger Index

HFIAS Household Food Insecurity Access Scale

HYV High Yield Variety

IFAD International Fund for Agricultural Development

IFDC International Center for Soil Fertility and Agriculture Development

IFPRI International Food Policy Research Institute

ISABU Burundi Institute of Agronomic Sciences

MDPRN Ministère de la Planification et de la Reconstruction Nationale

MINAGRI Ministry of Agriculture and Animal Husbandry

MININTER Ministry of Internal Security

NEPAD New Partnership for African’s Development

NGO Non-Governmental Organization

PRSP Poverty Reduction Strategy Papers

SPSS Statistical Package for Social Scientists

WB World Bank

WDR World Development Report

WFP World Food Program

Chapter 1 Introduction

1

Chapter 1 : INTRODUCTION AND BACKGROUND INFORMATION

1.1. INTRODUCTION

The right to food is taken for a principle in the contemporary development and human right

discourse (FAO, 2008). However, it is also said to be one of the most frequently violated human

rights in recent times. The Millennium development Goal number one, Target 1.C, set by the

World Food Summit in 1996 to reduce the number of undernourished people by half by 2015

cannot be met if present trends continue (Delgado et al.,2010) even though the global food

production has grown faster than the total population in the world (Ulukan, 2011).

The problem is more pertinent in developing countries which accounts for 98% of the world’s

undernourished people (FAO, 2010) and many more others experiencing deficiencies of proteins

and essential micronutrients (Smith et al., 2003). Whereas some progress has been made, the

proportion of undernourished people is still too high at 30%, in Sub-Saharan Africa for 2010

(FAO, 2010).

Sub-Saharan Africa is the most endangered region in view of food security. One of the challenges

for food security in Sub-Saharan Africa is the underdevelopment of the agricultural sector which is

the backbone of economic growth (World Bank, 2008) and the main source of income for the

majority of the rural population where poverty is more concentrated (Boussard et al., 2005). The

agricultural productivity growth is also necessary as the population continues to grow in Sub-

Saharan Africa. The current agricultural productivity in Sub-Saharan Africa is very low compared

to the population growth rate and without increasing agricultural productivity, food security

improvement and poverty alleviation goals will not be achieved.

In order to improve food security in poor farming settings in Sub-Saharan Africa, governments and

other stakeholders have suggested and or implemented a series of agricultural development

programs and interventions in order to increase people’s capabilities to meet food security needs.

An important aspect of the agricultural development programs is stimulating the adoption of

improved agricultural technologies (Doss, 2006). These technologies include the intensive use of

fertilizer, improved seeds, irrigation systems and other best agricultural practices.


2

However, the rate of adoption of these technologies has been lower in Sub-Saharan African

countries than in Asia and Latin America (World Bank, 2008) and this created opposite outcomes

to food security for these three regions where Sub-Saharan Africa is still lagging behind. The

socio-economic structures, institutional settings and the characteristics of desirable technologies

might be playing a certain role in determining levels of adoption of these disseminated agricultural

technologies for improving food security (Doss, 2006).

1.2. DESCRIPTION OF THE STUDY AREA

1.2.1. Background information on Burundi

Burundi is a landlocked country in the middle of Central Africa and covers an area of 27,834 km².

The population was estimated to be approximately 8,053,574 populations in 2010 with a an

average population density of 310 inhabitants per km2

and a population growth rate of 2.4%

(Republic of Burundi, 2010).

In general the Burundian population is young where the population below 15 years old is 46.3%,

that of 15 to 65 years is 51.2% while that of 65 and over is approximately 2.5% (Republic of

Burundi, 2006).Under five infant mortality rate was estimated at 168 deaths/1,000 live births and

the life expectancy at birth was 50 years in 2007 (FAO, 2010).

Burundi’s economy is largely dominated by agriculture accounting for about 31.6% of the total

GDP and employing more than 90% of the population. Industry and services account for 21.4%

and 47% respectively of the total GDP. Exports are mainly based on coffee and tea which

constitute 90% of total foreign exchange. The GDP per capita was estimated 110 $ in 2010.

Burundi is amongst the poorest countries in the world placed at 167 out of 177 in the 2007/2008

United Nations Development Program’s Human Development Report. The vast majority of

Burundi’s poor people are small-scale subsistence farmers living in rural areas. The percentage of

population living below the poverty line is about 67% (Republic of Burundi, 2010).


3

In rural areas, poverty is the result of high population pressure on a small size of cultivable land,

persisting drought, poor quality of agricultural technology, low cash income, inadequate basic

health services and drinking water, low productivity of labor (IFAD, 2006) and a low level of

education (Bundervoet, 2006). Figure 1.1 shows the map of Burundi. The hatched area on the map

shows the province of Ngozi which was the subject of our study.

Figure 1.1: Map of Burundi

Source: Nations Online Project, 2011

1.2.2. Main features of Ngozi province

1.2.2.1. Physical description

The province of Ngozi which was the subject of our study is located in the northern part of the

country. It has a surface area of 1473.86 km2

and is situated between 2039’19’’south latitude and


4

29037’57’’east longitude. The province of Ngozi is bordered by the province of Muyinga and

Karusi in the east, the province of Kayanza in the west, the Republic of Rwanda in the north, the

province of Kirundo in the north- east and the province of Gitega in the south.

1.2.2.2. Administrative organization

The province is made by 9 administrative communes that are Mwumba, Ngozi, Gashikanwa,

Busiga, Ruhororo, Tangara, Kiremba, Nyamurenza and Marangara. These communes are further

subdivided into 31 zones and 298 collines.

1.2.2.3. Climate

The province of Ngozi has a clement climate resulting from the presence of natural regions in that

province namely Bwiza and Buyenzi. The natural region of Bwiza has an altitude comprised

between 1,400 and 1,600 m, an annual rainfall between 1,000 and 1,100 mm per year and an

average temperature of 18.5oC.The natural region of Buyenzi has an altitude between 1,500 and

1,900 m, an annual rainfall between 1,200 and 1,500 mm and an average temperature of 18,5oC

(MPDRN, 2006). Rainfall is regular and abundant in Buyenzi and less in Bwiza.

1.2.2.4. Soils

The communes of Busiga, Mwumba, Kiremba, Kinyamurenza et Marangara, have clayey and

bulky soils. Sandy soils are observed in Gashikanwa et Tangara communes, while in Ngozi and

Ruhororo, soils are sandy but with acid tendency (Nyegayenge, 2002). Soils in general are very

fertile in Ngozi .The combination of the quality of the soils together with the climate constitutes

the favorable ecological conditions for agriculture and explain why this zone is under demographic

pressure.

1.2.2.5. Demographic characteristics of Ngozi

The population of Ngozi province was estimated to be 700,438 in 2005, in an area of 1473.86 km2

with a density of 475 people per km2 (MININTER/UPP, 2006 cited by MPDRN, 2006).


5

Nyamurenza commune was the highest in density (650 people per km2) while Tangara commune

was the lowest in density (355 people per km2).Table 1.1 gives the repartition and density of

population per commune in 2005.

Table 1.1: Distribution and population density per commune in 2005

Communes Population Surface area (km2) Density

Busiga 72,828 121.32 600

Gashikanwa 59,798 142.78 419

Kiremba 95,854 243.43 394

Marangara 73,358 182.29 402

Mwumba 77,628 128.7 603

Ngozi 107,416 184,46 582

Nyamurenza 63,078 96.89 650

Ruhororo 72,429 154.1 470

Tangara 78,049 219.8 355

Total 700,438 1473.86 475

Source: MININTER/UPP (2006) cited by MPDRN (2006)

Among the 700,438 estimated inhabitants of Ngozi in 2005, 48.5% were female while 51.5% were

male. In addition, 65 % were less than 25 years old, meaning that the population of Ngozi is very

young.

1.2.2.6. Population’s livelihood in Ngozi province

Agriculture is the primary source of livelihood in Ngozi. Farms are of subsistence agriculture,

involving intercropping of several food crops on a single small plot using rudimentary tools by

mainly family labor. The amount of land per family is generally less than one hectare and

continues to decrease making plots smaller and smaller which slowly decreases the ability of

households to produce sufficient food to meet their needs (WFP, 2008).

Both food crops and cash crops are grown in Ngozi province on both the hill side and the drained

marshes. The principal food crops grown in Ngozi are cassava, sweet potatoes, banana,beans,irish

potatoes, maize and rice while coffee is the principal cash crop grown. Livestock such as cattle,


6

goats, pigs, sheep, and poultry is also raised by the population of Ngozi. The increasing land

scarcity makes the existing pasture undersized to support extensive grazing alone and leads to the

adoption of semi-intensive and intensive production methods. In addition livestock is to some

extent incorporated into the farming system for soil nutrient cycling through the use of manure as

fertilizer. They also enhance the ability of households to deal with risk as they provide income and

food in resource-poor regions such as Ngozi (Swanepoel al., 2010). Handcraft such as tiles, bricks

and shoemaking, carpentry, sewing and soldering are also developed in Ngozi with the dominant

majority of production handcrafts.

1.3. PROBLEM STATEMENT

Food security is always at the forefront of countries’ agricultural development policies because it

gives a clear indication of the population’s living conditions especially in countries where

agriculture is the main driver of people’s livelihood. Consequently, pro poor policies would target

agricultural production processes whereby once the sector is developed the population increases

their potential for future investment on land and in other off-farm activities. It is in this perspective

that from one year to another agricultural productivity might increase as a result of introducing

best practices in agriculture for which the direct outcome would be improved food security.

Burundi is one of the countries in Sub-Saharan Africa with a significant portion of its population

basing their livelihood on agriculture. It is in the same light that the last decade has seen Burundi’s

agriculture sector changing the productivity trend through the adoption of various new farming

systems globally known as best farming practices. They promoted practices including the use of

improved seeds, fertilizers, pesticides, soil erosion control structures, marshlands planning, new

farming techniques and so forth.

An action for improving households’ food security in Burundi was timely because the food

security situation was found critical by an FAO (2007) report which revealed an average per capita

caloric intake of 1700 kcal for the period of 2002-2004 which is 400 less than the recommended

dietary caloric intake. However, it is worth analyzing if any increase in food production and

security has been a result of the introduction of best agricultural practices. Without straightly


7

pre-supposing any direct causal link we do anticipatively believe that some other institutional

factors and socio-economic factors such as households’ characteristics, farm size, land ownership

status and many others , might complement the new agricultural techniques in improving food

security. This study is aimed at analyzing the influence of new farming techniques on food security

in Burundi taking Ngozi Province as our case study.

1.4. STUDY OBJECTIVES AND RESEARCH QUESTIONS

The study has both general and specific objectives. The general objective of the study is to analyze

drivers of food security in Burundi. By analyzing drivers of food security in Burundi, the study

will attain the following specific objectives:

Identifying different farming systems and techniques used in Ngozi-Burundi;

Assessing possible correlations between food security and production techniques;

Analyzing the influence of household, institutional and farm characteristics on food

security through the uptake of agricultural production techniques.

Figure 1.2 below shows the analytical framework for the influence of agricultural production

techniques on food security.

Based on these objectives, the following research questions can be formulated:

What are the different production techniques that may significantly influence food

security in Burundi?

How do household, farm and institutional characteristics dictate the uptake of those

agricultural production techniques and hence food security?


8

SUSTAINABLE FOOD SECURITY

Figure 1.2: Analytical framework for the influence of agricultural production techniques on

food security

Source: Adapted from Oliora, 2009

1.5. STRUCTURE OF THE STUDY

After the above first chapter on general introduction, the remainder of the study is structured as

follows: second chapter is the literature review, the third chapter is the methodology describing the

sample, methods of data collection and analysis, the fourth chapter is the presentation of the

results, analysis and discussion .The fifth and last chapter gives the conclusion and policy

implications and recommendations.

Agricultural techniques

Improvement of soil

organic matters (use of

manure, compost, crop

residue and mulching)

Use of fertilizers,

pesticides and herbicides

Improved plantation

techniques (sowing in

lines)

Integrated Water

Management for

agriculture use ( drainage

and irrigation)

Use of improved seeds

Improved productivity

Improved Food

availability Socio-economic

and institutional

characteristics

Intrahousehold

equitable access to

food and its utilization

Higher income from

the surplus after food

consumption

Chapter 2 Literature review

9

Chapter 2 : LITERATURE REVIEW

This chapter focuses on the definitions of key concepts and theories related to farming systems,

agricultural production techniques, and food security. It departs from the generalities of

agricultural practices and food security in Sub- Saharan Africa to the specificities of Burundi. The

core of theories presented here were developed by research institutions and international

organizations dealing with agricultural development namely the International Food Policy

Research Institute (IFPRI), Food and Agriculture Organization (FAO), World Bank (WB) and

others.

2.1. AGRICULTURE IN DEVELOPING WORLD’S ECONOMY

According to the World Bank (2008), three types of economies can be distinguished based on both

the share of agriculture in the countries’ growth and the share of poverty in the rural sector. First,

agriculture-based economies are countries in which agriculture is not only the main source of

people’s livelihood but also the major source of economic growth. In addition, the poor people are

concentrated in rural areas.

For this latter indicator, International Fund for Agricultural development IFAD (2010) in its rural

poverty report for 2011 demonstrated that while the incidence of extreme rural poverty declined

significantly and leniently for other regions, Sub-Saharan Africa has been the only region to have

an upward curve for the last decade. In addition, Sub-Saharan Africa is the only major region

where per capita food production has stagnated and has a downward trend (Norton et al., 2010).

The second type of countries distinguished by the World Bank are transforming economies where

agriculture gives only a small contribution to the economic growth with high poverty in rural

areas. They include most of the countries of South and Eastern Asia plus North Africa and the

Middle East. Lastly, the World Bank report defines as urbanized economies countries in which

agriculture is likely to contribute very little to the economic growth and where there is more urban

poverty. These countries are found in Latin America and in Eastern Europe.


10

Burundi can be classified in the first category of agriculture based economies given the role played

by agriculture in people’s livelihood and even the incidence of extreme poverty in rural areas.

IFAD (2010) classifies Burundi alongside many other developing countries into the agriculture

dependent group. Table 2.1 provides data points for agriculture’s three worlds according to the

2008 World Development Report.

Table 2.1: Data points for agriculture’s three worlds according to the 2008 World

Development Report

Indicator Agriculture

based

economies

Transforming

economies

Urbanized

economies

Burundi

Share of agriculture in GDP

(%) with reference to year

2005

29 13 6 45.6

Rural poverty rate (2002) in

%

51 28 13 69

Source: Compiled and adapted from World Bank (2008)

In Sub-Saharan Africa, most of the countries, including Burundi, are still classified as an

agriculture based economy and agriculture is considered as an engine for growth (WDR, 2008).

This means, agriculture should gain a special attention as regard to policy making to improve on

people’s livelihood.

According to Norton et al. (2010) technical changes, institutional changes, and education are

crucial to stimulate local agricultural production and therefore contributing to overall development.

Technical aspects include expanding suitable land for agriculture or a more intensive use of land

currently being used which necessitates improved technologies.

The performance of the agricultural sector reflects the emerging farming system. The section

below clarifies the concept.


11

2.2. THE CONCEPT OF FARMING SYSTEM

A farming system is defined as a population of individual farm systems that have similar resource

bases, enterprises patterns, household livelihoods and constraints and for which similar

development strategies and interventions would be appropriate (Dixon et al., 2001).

Defoer et al. (1998) state that a farm system comprises not only resources such as fields, crops

animals, feeds and manure ,etc., which are managed and transformed through human activity, but

also it includes the farming family, housing facilities and food stores. The same authors recognize

3 sub-systems within the farm system: the crop production system, the animal production system,

and the household system.

The type of farming system prevailing in a region depends on technical, institutional and human

determinants which interact at each location and point in time to provide a unique environment for

agricultural production (Norton et al., 2010). The above determinants will dictate the most suitable

farming systems with a maximum productivity and any change in these determinants will have an

effect on agricultural productivity. In this study, the focus is on the influence of technical aspects.

2.2.1. Farming systems in Sub-Saharan Africa

The large variety of agro ecological conditions of Sub-Saharan Africa dictates a wide range of

farming systems as well. Dixon et al. distinguishes 15 different farming systems based on criteria

like dominant crops, agro ecological and livelihood features (Dixon et al., 2001). Despite a

diversity of extensive farming systems in Sub Saharan Africa, the continent still faces a number of

challenges namely declining soil fertility, inadequate use of improved germplasm, limited

irrigation that severely limits the production potential, poor extension services to farmers and poor

access to markets (Jama and Pizarro, 2008).


12

2.2.2. Prevalent farming systems in Burundi

As mentioned in the previous paragraph, the prevalent farming system found in Burundi is the

highland perennial farming system. This farming system is based not only on perennial crops such

as banana, plantain and coffee complemented by cassava, sweet potatoes, beans and cereals but

also cattle is kept for milk, manure, and social security (Dixon et al.,2001).

According to Wodon et al. (2008), food production systems in Burundi have been changed in

response to the high population density associated with acute scarcity of agricultural land and

intensive work on land yet with very low returns. The same author gives a simplified typology of

agricultural production systems in Burundi based on soil fertility management practices, cropping

and livestock systems, linked to the level of population density. This typology is presented in

Table 2.2. With regard our case study, farms in Ngozi province are located in area with very high

population density.

Both food crop and livestock subsectors are affected by a number of key constraints contributing to

limited growth. For the food crop subsector, there is limited use of improved farm management

practices such as irrigation, limited use of purchased inputs, uncertain water supply, high input

prices, and post harvest constraints. In all the constraints as noted above, population density comes

in as another determining factor (Wodon et al., 2008).


13

Table 2.2: Typology of agricultural production systems in Burundi

Parameter Farms located in areas of

medium population

density

Farms located in areas of

high population density

Farms located in areas of

very high population

density

Cropping

systems

Extensive cropping of:

cereals, legumes, roots and

tubers

Intensive cropping using

complex associations:

banana, cereals, roots, and

tubers, legumes,

development of marshland

Multilevel permanent

cropping: fruit trees, banana,

roots and tubers, legumes,

cereals

Development of marsh land

Livestock

systems

Pasture readily available Pasture increasingly scarce Pasture no longer available

Animals allowed to graze

free during the day and

return to the farm at night

Limited free grazing

Most animals are kept in

stalls

Animals kept in stalls Forage

and water brought to animals

Fertility

management

practices

Lateral fertility transfers

from pastures to cropland

via livestock

Decreasing lateral fertility,

transfer from pastures to

crops via livestock

Major importance of banana

and other tree species in

fertility improvement

No use of mineral

fertilizer

Limited use of fallowing

Some use of mineral

fertilizer

Increasing role of banana

and other trees in soil

protection and fertility

management

Use of mineral fertilizer

Management

of tree and

agro forestry

Land cleared

Trees minimally integrated

into the farming system

Use of live hedges planting

of fruits

Three level cropping: forest

trees, fruits trees, associated

crops

Source: Wodon et al. (2008)

2.2.3. Adoption of new technologies by African farmers

Sub-Saharan Africa is the only region in the world where livelihood and food security continue to

deteriorate and where the number of people living in poverty has increased in the last decade

(Norton et al., 2010). One of the reasons for that is the low agricultural productivity ((Norton et

al., 2010). These concerns led the African governments to pursue different kinds of agricultural

policies and strategies, among others stimulating the adoption of new technologies, to boost

agricultural production, and therefore reduce poverty (Jayna et al., 2003). However, these


14

technologies such as intensive use of fertilizers, improved varieties of seeds, pesticides, irrigation

have not been adopted by a significant number of farmers especially in Sub-Saharan Africa yet

their potential to increase agricultural productivity exists if we compare the actual farm yields with

those of demonstration plots (Beddington, 2010). The figures 2.1, 2.2 and 2.3 below show

respectively the level of adoption of improved varieties of cereals, fertilizers and irrigation in Sub-

Saharan Africa and other regions.

Figure 2.1: Level of adoption of improved varieties of cereals

Source: FAO2006a in World Bank, 2008

Figure 2.2: Level of adoption of fertilizer use

Source: FAO 2006a in World Bank, 2008


15

Figure 2.3: Level of adoption of irrigation

Source: FOA 2006a in World Bank, 2008

Feder et al. (1985) denote that these technologies are introduced in packages that include several

components, for example High Yielding Varieties (HYV), fertilizers and corresponding land

preparation practices.

According to Rogers (1995) the adoption of an innovation is a complex process consisting of five

stages: The first step is the knowledge step in which potential adopters discover an innovation and

gain a basic understanding of what it is and how it works. The second step is persuasion in which

potential adopters form a positive or negative impression of the innovation. The third is the

decision stage in which the innovation is adopted or rejected .The fourth is the implementation

stage which occurs when the innovation is used. The fifth stage is the confirmation stage in which

the adopter seeks information about the innovation and either continues or discontinues using the

innovation.

Several variables influence farmers in the adoption of new technologies. The following table 2.3

summarizes various ranges of literature based on theories and empirical studies on the adoption of

various agricultural innovation techniques in order to improve on productivity.

For the specific context of Burundi, joint efforts from the Government of Burundi and its

development partners are underway to transfer technologies and best practices to farmers in order

to ensure food security. In that framework, different agricultural production techniques are being

promoted.


16

Table 2.3: Literature Review on factors influencing the adoption or rejection of agricultural technologies

Source: Author’s own compilation from extensive literature review

Type of agricultural

technique

Influencing farmer's

characteristics

Influencing socio-

economic

characteristics

Influencing

institutional

characteristics

Influencing farm

characteristics

Author

Soil and water

management

Age, education, farming

experience, family labor

Social

acceptability and

cost of the

technology

Access to credit,

government policies,

extension services,

farmers' groups and

research

Farm size Bett (2001)

General Awareness towards the

technology

Applicability of

the technology

Technical support Abiasaka et al. (2001)

General Education ,age, family

size

Income Farm size Okaya et al. (1998)

General Utility Credit Land availability Just and Zilberman

(1985),

Matata et al.(2010)

Improved seedlings Technology

attributes

Wale and Yalew

(2007)

Land management

techniques

Agricultural labour

force

Extension services Yila and Thapa

(2008)

Improved cereal crop

production

technologies

Meetings and

frequency of

extension agents

visits

Odoemenem and

Obinne (2010)


17

Table 2.4: Literature Review on factors influencing the adoption of agriculture technologies (Cont.)

Source: Author’s own compilation from extensive literature review

Type of

agricultural

technique

Influencing farmer's

characteristics

Influencing

socio-economic

characteristics

Influencing

institutional

characteristics

Influencing

farm

characteristics

Author

Inorganic fertilizer

use

Farm experiences Income Ezeh et al. ( 2008)

Improved maize

varities and

chemical fertilizers

Knowledge of

advantages

Local agro

ecological

conditions

Cavane (2009)

Fertilizer use Knowledge of

efficient use of

fertilizer

Prices of

fertilizer

Extension services Morris et

al.(2007)

Use of improved

seeds and other

inputs

Access to credit Kudi et al.(2010)

and Doss (2003)

General Level of education

and awareness of the

household head

Agwu (2004)

Soil and water

conservation

Age Beleke and Drake

(2003); Tabi et al.

(2010)


18

2.2.4. Major crops under cultivation in Burundi

The economy of Burundi is mainly based on subsistence agriculture. A total of 94% of the

Burundi working population depend on agriculture (Republic of Burundi, 2006). Maize, cassava,

bananas, sorghum, beans and sweet potatoes are the principal food crops, while coffee is the

main agricultural export product.

Burundi has three main agricultural seasons referred to as A, B and C. Season A occurs during

the short rainy season (October to January). Maize, cassava, rice, beans, potato, sweet potatoes

and sorghum are the main crops cultivated during this season. Season B occurs during the long

rainy season (February to May) with beans, potato and sweet potatoes as the main crops of that

season. Season C occurs during the dry season (June to September) with maize, beans, potatoes

and sweet potatoes as the main crops. Coffee and banana are perennial crops (World vision

Burundi, 2003). However, according to FAO (2007), bananas and sweet potatoes are the two top

ranked crops both in terms of production and related returns, as figure 2.1 reveals.

Figure 2.4: Top production-Burundi-2007

Source: FAO (2007)


19

2.2.5. Agricultural techniques in Burundi and institutions stimulating their uptake

Population growth is a major problem in Burundi (Cochet, 2004). As the population growth

keeps on rising where for example the 2008 population growth rate is estimated at 2.4 (World

Bank, 2010), it will be necessary to increase the agricultural productivity of existing farms (Beck

et al., 2003). Therefore, in order to overcome diminishing returns to labor as fertile soil is

limited, new technologies are necessary (Norton et al., 2010).

The Burundian government has been pursuing different kinds of agricultural policies and

strategies to boost agricultural production. Improving food security through increased food

production capacities is one of the major flagships of the country’s Poverty Reduction Strategies

framework (Republic of Burundi, 2006). Key government institutions involved are The Institute

of Agricultural Sciences of Burundi (ISABU) and the Ministry of Agriculture (MINAGRI)

together with other stakeholders such as World Vision international, the European Union (EU)

and FAO. These NGOs and international organizations are supporting the Government of

Burundi in its efforts to revitalize the agricultural sector through the introduction of best farming

techniques in order to increase productivity. In 2006, the FAO alone supported 400,000

households with seeds and farm tools together with the restoration of agricultural services at

community level. (FAO, 2006). These services at community level help in the dissemination and

supervision of best farming practices and techniques as transferred by agricultural research

institutions and other stakeholders. The most commonly disseminated techniques include the use

improved farm inputs such as seeds, fertilizers and pesticides, soil fertility management through

erosion control techniques and others.

However, the country is facing constraints limiting the uptake of recommended agricultural

production techniques and among them are the low purchasing power of most of the rural

population, the high cost and restricted availability of fertilizers in countryside, and the little

fertilizer available is used mostly to cash crops in particular cotton and tea (Wodon et al., 2007).

In addition, the withdrawal of the Government of Burundi from the fertilizer sector has led to a

fall in the use of fertilizers on all crops including food crops (Baghdadli et al., 2008).


20

Less than 1% of farmers use improved seeds (IFDC, 2007). Commercial seed for most crops

remains out of reach by many farmers due to a severe scarcity of ability to multiply foundation

seed (Wodon et al., 2008).

The adoption of new sowing techniques, planting in lines, depends on the availability of

chemical fertilizer. If fertilizer is available, in this case sowing techniques are used and fertilizer

is applied along the lines. As for water management for irrigation purposes, less than 10% or less

than 5,000 ha of the country’s potentially irrigable area is under irrigation (Wodon et al., 2008)

while the country is not running short of water. Yet it would be a rational choice to maintain the

potential of crop production even during off-rain season.

The desired outcome of the intensive use of the best farming practices and techniques as

described above is to improve on people’s food security. The section below discusses the

concept of food security in general and Burundi in particular.

2.3. THE CONCEPT OF FOOD SECURITY

The concept of food security has gone through several renovations over the past few decades.

The current focal of attention is not only the food security at global, national, and regional levels

but also the individual and household food security. This came as a result of Amartya Sen’s

entitlement approach to poverty and hence to food security whereby he has been credited with

initiating a paradigm shift in the early 1980s that brought the issue of access and entitlement to

food.

Maxwell and Smith (1992) admit that the food security concept has been widely defined. The

authors illustrate for example that by the end of the 80s around 200 definitions of food security

had appeared in various writings (Faridi and Wadood, 2010). With this view it is essential to

analyze drivers of food security first at household level and any national wide generalization

should come later.


21

According to the World Food Summit (1996) food security exists when all people, at all times,

have physical, social and economic access to sufficient, safe and nutritious food that meets their

dietary needs and food preferences for an active and healthy life.

Despite the increased attention to reducing hunger since the adoption of the Millennium

Development Goals, the World still faces large problems of widespread hunger and malnutrition.

On the world level, the number of hungry has declined, but remains unacceptably high. FAO

estimates that a total number of 925 million people are undernourished in 2010 compared to

1023 billion in 2009 (FAO, 2010). Developing countries account for 98 percent of the world’s

undernourished people (FAO, 2010). If this situation does not change, the Millennium

Development Goal number one (reduce the number of hungry people with 50% by 2015) will not

be reached.

The International Food Policy Research Institute (IFPRI) and other cooperating organizations in

the ‘2020 vision for food, agriculture and environment’ maintained that this vision entails a

world where every person has economic and physical access to sufficient food to sustain a

healthy and productive life, where malnutrition is absent, and where food originates from

efficient, effective, and low cost food and agriculture systems that are compatible with

sustainable use and management of natural resources (Pinstrup-Andersen and Pandya-Lorch,

1998). The authors highlighted major challenges that brought IFPRI to design the vision to

address them. The challenges include inadequate capacity to grow or purchase the needed food,

large increases of population in developing countries, gross under-investment in agriculture

research, and inadequacies in availability of and access to agriculture inputs, degradation of

natural resources, inefficient functioning of markets and inadequate infrastructures and lastly

insufficient domestic resource mobilization.

The same views are shared with FAO Regional Office for Africa (2006) which asserts that

productivity has remained low because of underutilization of water resources, limited fertilizer

use, limited use of improved soil fertility management practices and weak support services.


22

2.3.1. Dimensions of food security

Food security has four main dimensions (FAO, 2008): physical availability, food access, food

utilization and stability of the availability and access to food. All these dimensions will be further

explained in the next sections.

2.3.1.1. Physical availability of food

Food availability refers to the physical availability of food which is a function of both home

production and imports, that is, through national food stocks and commercial food import,

farming, community gardens and harvesting (own production and reserves), purchasing (the

market), hunting wild food and fishing and food handouts (Renzaho and Mellor, 2010).

However, this study concentrates more on domestically produced food.

Increased food production will have to come from more efficient use of land already under

cultivation as opposed to significant expansion of cultivated land which is not an economically

or environmentally feasible option in most of the world (Pinstrup-Andersen and Pandya-Lorch,

1998).

For this, food security on its food supply or availability component implies adoption of best

agricultural practices that have potential to increase productivity as a result of efficient and

environmentally friendly agricultural practices. Therefore from a food availability perspective,

increased food security occurs when the producer price of food rises, conventional factor input

prices fall, improved agriculture technology prices fall, user costs of infrastructural services fall,

weather conditions improved in food–producing areas, the world market price of food falls,

national domestic income rises, international interest rates fall, the volume of food aids increases,

and the domestic interest rates fall (Fosu and Nico, 2011).

2.3.1.2. Food access

Food access is seen at the household and individual levels. Food access refers to the capability to

obtain the needed food, either from own production or purchasing from the market (Bahiigwa,


23

2002). Access to food depends on the purchasing power of the households but also on what

portion of income they spend on food. Within the households, full income is used not only for

achieving food security but also for accessing other basic needs such as basic education, health

care and housing .This means that in the household, food access is influenced by intrahousehold

food distribution decisions.

2.3.1.3. Food utilization

There are two forms of food utilization: physical utilization and biological utilization. The

physical utilization is the ability of a household to have all the physical means to use food

available. This may include cooking utensils, culturally regulated feeding hierarchies, cuisine

patterns, adequate housing, caretaker behavior, knowledge, family structure, and workload while

the biological utilization is concerned with the ability of the body to effectively use the nutrients

once the food is consumed (Renzaho and Mellor, 2010). To this point, food security has been

correlated accordingly with the status of malnutrition prevalence, dietary energy balance or

supply and prevalence of absolute poverty (Smith et al., 2000).

2.3.1.4. Stability of the availability and access to food

In order to be food secure, adequate supply and access to food on individual, household or

population levels must be met at all times. If there is inadequate access to food due to sudden

political, economic or climatic chocks like conflict, high food prices or droughts then there is

food insecurity. Some temporal man made or natural disasters may affect food security and

hence cause transitory food insecurity (Hartwig and Gunter, 2006). Figure 2.5 shows the

conceptual framework of food security as a multisectorial and multi-dimensional phenomenon.


24

Figure 2.5: Conceptual framework of food security

Source: NEPAD, 2009

2.3.2. Determinants of Household Food Security

Household’s potential towards food availability, access and utilization is a function of different

variables. In a study conducted in Bangladesh, it was found that household’s food security is

significantly correlated with some household’s characteristics like the level of education of the

household’s head, electricity connection and land ownership (Faridi and Wadood, 2010).

On their side, Feleke and his co-authors (2005) concluded from a study applied to Southern

Ethiopia that the determinants of food security can be found at both supply and demand side.

Determinants such as agricultural technology adoption, farming systems, farm size, land quality,

per capita aggregate production and access to market were seen as having a deterministic

relationship with household’s food security ( Feleke et al., 2005).


25

However, despite the above factors among others set as determinants of food security, it is worth

recognizing that they don’t act in isolation. They instead interact with other institutional and

natural factors that are at some point uncontrolled at household level. Consequently, we argue

that food security improvement at household level is in the hands of not only individual

households’ efforts but also other actors like the Government, Private sector and Civil Society.

2.3.3. Food security Pattern in Burundi over time

Food security in Burundi has not improved for the greater part of the population in recent years

(WFP, 2011). The percentage of population suffering from undernourishment rose from 44% in

1991 to 63% in 2006 (WFP&FAO, 2009). This alarming hunger situation is also illustrated by

the Global Hunger Index (GHI) of the country which was 42.7 percent in 2003 (IFPRI, 2006)

and decreased to 38.3 in 2010(Wodon, 2008) which is still too high as well. This high percentage

of GHI in Burundi was primarily due to an increase in the proportion of the undernourished

population as a consequence of inadequate food supply. The average caloric intake at the

national level was 2,086 kcal per adult equivalent per day with specific categories in which more

than half (56%) of the population had a caloric intake less than 1,900 kcal (Wodon, 2008).

2.3.4. Crop based contribution to food security in Burundi

Food crops production occupies on estimate 85% of the total cultivated area in Burundi

(D’Haese et al., 2010). Food crops in Burundi include cereals (maize, sorghum, rice, wheat,

grasses), legumes (beans, green peas), oilseed crops (soybeans, groundnuts, oil palm, and

sunflowers), tuber crops (sweet potatoes, cassava, potatoes, and yams), bananas, fruits, and

vegetables (Banderembako, 2006). Table 2.4 shows the evolution of food crops production in

Burundi between 1990 -2007, where banana and plantains category was the first one in term of

production followed by tubers and roots.


26

Table 2.5: Evolution of food crops production in Burundi between 2000 - 2007

Period 2000 2001 2002 2003 2004 2005 2006 2007 Total %

Cereals

(MT)

251 274 282 246 280 290 287 290 2200 8

leguminous

(MT)

224 282 282 246 280 250 247 241 2052 7

Tubers and

roots (MT)

1481 1613 1707 1545 1641 1575 1508 1527 12597 42

Banana and

plantains (MT)

1516 1549 1603 1569 1587 1636 1654 1721 12835 43

Total 3472 3718 3874 3606 3788 3751 3696 3779 29684 100

Source: Compiled and adapted from MINAGRI Burundi, 2008

The volume of food production showed little change between the 2000 and 2007. This pitiable

performance of Burundi’s agricultural sector is deteriorating food security as the population

keeps on growing while the per capita food production goes down. The consequence is an

inadequate caloric intake and a nutrient poor diet. Figure 2.6 illustrates the gap between food

crops production and the population growth between 1998 - 2007.

Figure 2.6: Evolution of the population and food crop production

Source: MINAGRI Burundi, 2008

This situation shows that the country is far from reaching food security for everybody as food

supply is insufficient unless measures to increase agricultural productivity, agricultural

production and thus food security are enhanced.

Chapter 3 Methodology

27

Chapter 3 : METHODOLOGY AND DESCRIPTION OF THE SAMPLE

This chapter is presented in 4 sections. Section 3.1 is about data collection; section 3.2 is the

design of the questionnaire, section 3.3 gives the analytical tools while section 3.4 gives

description of the sample.

3.1. DATA COLLECTION

The study on the influence of agricultural production techniques on food security in Burundi was

informed by quantitative data collected from a randomly selected sample of 360 households in

Ngozi Province in 2007 by a team from the University of Burundi. The questionnaire included

variables such as household, farm and farming systems characteristics together with income and

expenditures (D’Haese at al., 2010) but also food security related questions are incorporated in

the questionnaire. (See annex enclosed on CD).

3.2. DESIGN OF THE QUESTIONNAIRE

The questionnaire has the following sections:

Section A have information related to the localization of the household;

Section B shows the demographic characteristics of the respondents;

Section C is about farm identification;

Section D is more specifically about farming techniques;

Section E have questions related to livestock;

Section F contains information related to expenditures on agricultural inputs;

Section G is about expenditures on food;

Section H is about the level and source of income;

Section I is more specifically related to food security and lastly factors of production and

social related questions is in section J.


28

The complete questionnaire is presented in annex on an enclosed CD. In this study; livestock was

not included in our study objective. The focus of the study is about crops production farming

techniques and their influence on food security.

The section related to food security is based on the conventional questionnaire format for the

Household Food Insecurity Access Scale (HFIAS).

The HFIAS is a tool to assess whether households have experienced problems in food access in

the preceding 30 days (Coates, 2006). HFIAS is composed of nine questions that ask about

modifications made by households in their diet due to limited resources to acquire food. It

measures the severity of food insecurity in the past 30 days, as reported by the households

themselves (Coates, 2006). Reactions and responses caused by household’s experience of food

insecurity are captured, quantified and summarized in a scale.

The HFIAS questions are based on three different aspects of food insecurity that are anxiety and

uncertainty about the household food supply, insufficient quality including variety and

preferences of the types of food and insufficient food intake and its physical consequences

(Coates, 2006). For each question four response options ranging from 0 to 3 represent

frequencies of occurrence of the condition (never, rarely, sometimes, and often ) in the past 30

days. The following are the HFIAS questions related to household food security:

Did you worry that your household would not have enough food?

Were you or any household member not able to eat the kinds of food you preferred

because of a lack of resources?

Did you or any household member eat just a few kinds of food day after day?

Did you or any household member eat food that you preferred not to eat because of a

lack of resources to obtain other types of food?

Did you or any household member eat a smaller meal than felt you need because there

was not enough food?

Did you or any other household member eat fewer meals in a day because there was not

enough food?

Was there ever no food at all in your household there were not resources to get more?


29

Did you or any household member go to sleep at night because there was not enough

food?

Did you or any household member go a whole day without eating anything because there

was not enough food?

3.3. ANALYTICAL TOOLS

In this study, Statistical Package for Social Scientists (SPSS) 16.0 was used to obtain descriptive

statistics, run chi- square tests of association, independent samples T-test, correlation analysis,

and binary logistic regression analysis.

Descriptive analysis offers statistics that are used to describe the results obtained by providing a

summary of what has been gathered such as measures of dispersion and central tendency.

Information provided by descriptive analysis can be used for further advanced analysis.

To test for the significance of relationship between categorical variables, cross-classified in a

bivariate table, contingency table associated with a chi-square test is used. The null hypothesis of

this test is that variables in a bivariate table are independent of each other.

Independent samples T-test is applied for the examination of the significant differences on one

factor (dependant variable) among means of two independent groups. Here the null hypothesis is

that the two means are equal.

Correlation analysis is a statistical analysis that defines whether an association exists between

continuous variables. The strength of association is provided by the Pearson r coefficient which

takes a value between -1 and +1.The sign of the Pearson r coefficient indicates the direction of

association where a -1 stands for the perfect negative linear association while +1 stands for a

perfect positive linear association and 0 indicates zero linear association.

To predict a dependant variable using one or more independent variables, regression analysis is

most often used. When the dependant variable is categorical with only two categories and


30

independent variables are either continuous or categorical variables, binary logistic regression

can be used.

Binary logistic regression provides a method for modeling a binary response variable, which

takes values 1 and 0 (Bewick et al., 2005). It is a generalized linear model that utilizes the logit

as its link function (Agresti, 2002).

When the outcome variable is dichotomous, the equation below represents the probability that Y

= 1, in other words the probability of an event to occur ( ) given X independent variables:

equation (1)

The probability that represents the probability of the event to not occur given X

independent variables:

) equation (2)

The natural logarithm of the probability of an event to occur divided by the probability of the

event to do not occur has a linear relationship with the explanatory variables.

equation (3)

Where p is the conditional probability of an event to occur, βi’s are parameters to be estimated,

Bo the intercept and X is a set of explanatory variables. This probability can be written as

follow:

equation (4)

To test the goodness of fit of the model, the following statistical tests are used: The chi-square

for the model, Cox & Snell R square and the Nagelkerke R Square, and the chi-square for

Hosmer Lemeshow.

The chi-square statistic for the model tests whether the null hypotheses which states that the

explanatory variables in the model make no difference to predict the dependant variable

compared to the model containing only the intercept may or may not be rejected. When the


31

probability is lower than 0.05, in that case the null hypothesis can be rejected and at that time the

explanatory variables make a difference in predicting the dependant variable.

Cox & Snell R square and the Nagelkerke R Square statistics do not measure the goodness of -fit

of the model but they indicate how useful the explanatory variables are in predicting the response

variable.

Hosmer and Lemeshow goodness of fit test is used to detect whether there is a difference

between the observed values of the dependent variable and the predicted values by the model.

Once the value of Hosmer and Lemeshow the goodness of fit is higher than 0.05, the null

hypothesis that the predicted values are not significantly different from the observed values is

accepted.

3.3.1. Model specification for the influence of agricultural production techniques

on food security

The above binary logistic regression present in equation (3) was chosen to be used in the analysis

because the dependant variable can only take the value 1 or 0. The dependent variable is severely

food insecure, one of the four categories of the household food security status. This dependant

variable is 1, when the household is severely food insecure or 0 if otherwise, when the household

is not severely food insecure.

The p in this case represents the conditional probability of a household to be severely food

insecure given a set of explanatory variables X. Table 3.2 and table 3.3 show variables that have

been used as independent variables. These variables are various production techniques that have

been reported to be used by the respondents in the study area, but also famers’ characteristics,

socio-economic and institutional characteristics possibly influencing household food security.


32

Table 3.1: Descriptive statistics of the categorical variables included in the regression

model

Categorical variables Yes (%) No (%)

Use of chemical fertilizer (1=yes,0 =no) 46 54

Use of manure (1= yes, 0 = no) 62 38

Composting (1= yes, 0= no) 80 20

Muchling (1= yes, 0= no) 75 25

Use of anti erosion hedges (1= yes,0=no) 39 61

Marshland irrigation (1=yes, 0=no) 9 91

Access to credit (1=yes, 0= no) 12 88

Table 3.2: Descriptive statistics of the continuous variables included in the regression

model

Continuous variables Minimum Maximum Mean

Farm size (hectares) 0.05 13.99 0.99

Household size (number ) 1 14 5.7

Trainings attended per season (number ) 0 6 0.19

3.3.2. Model specification for the uptake of agricultural production techniques.

In this study it was also interesting for us to look at the factors influencing farmers in the

adoption of agricultural production techniques such as use of fertilizer, and anti erosion hedges.

The above binary logistic regression in equation (3) has been used where in this case the

outcome variables was respectively the use of fertilizer and anti-erosive hedges which can be

equal to 1 if yes (household adopted the technique) or 0 if otherwise. Separate binary logistic

regression models with different outcome variables (use of fertilizer, use of anti-erosive hedges),

were made.


33

The p represents the conditional probability of a household to adopt fertilizer or anti-erosion

hedges given a set of explanatory variables X. The following variables in table 3.4 and 3.5 have

been considered as independent variables.

Table 3.3: Descriptive statistics of the categorical variables

Categorical variables Yes (%) No (%)

Access to credits 12 88

Member of cooperative 49 51

Table 3.4 : Descriptive statistics of the continuous variables

Continuous variables Minimum Maximum Mean

Farm size (hectares) 0.05 13.99 0.99

Household size (number ) 1 14 5.7

Number of visits per month by extension works 0 9 0.42

Total number of plots 1 26 7

Trainings attended per season (number ) 0 6 0.19

3.4. DESCRIPTION OF THE SAMPLE

The sample presents diverse farm and household characteristics which could dictate some

specific production behaviors and outcomes.

3.3.1. Characteristics of households in the sample

The sample has been drawn from nine communes of Ngozi province in 2007. A total sample of

360 households were randomly selected in which 21 households (6%) had a female head of the

household while 339 (94%) were male headed. The average age for the household head was 41.

The average household’s size was 5.8 while the number of household members working on farm

was on average 2.7. Table 3.6 gives an overview of the household characteristics of the sample.


34

Data concerning the household characteristics of the total population of Ngozi was not available

to allow comparison and check representativeness of the sample.

Table 3.5: Characteristics of the households in the sample

3.3.2. Farm size and land use in Ngozi province 2007

Land is the most important resource for agricultural production .As Ngozi is one of the most

densely populated areas in Burundi; there is a limited access to land and overuse of the little

fertile soil that exists. The overuse of land resources may generate food insecurity induced by

poor yield as a result of land related resource depletion. Table 3.4 gives an overview of farm size

and land use in Ngozi 2007.

Table 3.6 : Farm size and land use in Ngozi 2007

The Sample (n=360)

Variables Mean SD

Farm size (ha) 0.99 1.41

Total number of plots on hills 5.64 2.77

Total number of plots in swamps 1.41 1.42

Share of surface for food crops (%) 75.94 20.07

Share of surface for cash crops (%) 11.87 12.71

Share of surface under fallow (%) 7.12 12.34

The sample (n=360)

Variables Mean S.D

Mean age of the household head(year) 41.5 12.5

Gender of the household head (%)

Male 94.2 -

Female 5.8 -

Household size (number) 5.8 2.3

Average number of the household members

working on farm (number)

2.7 1.3


35

The quantity of farmland available for a household was on average 0.99 ha of which 75.94% was

for food crops while 11.87% was for cash crops. This indicates the priority given to food

production at the expense of cash crops which could lead us to assume the importance of food

production in the area. The number of plots on hills per household is on average 5.64 while the

number of plots in swamps is on average 1.41. This indicates how farm land in the study area is

highly fragmented. As the province of Ngozi is densely populated, almost all available farmland

was in use where on average only 7.12% of farmland was under fallow. This limited fallowing

reflects the consequence of overuse of land resources as a result of demographic explosion yet

fallowing would help increase soil fertility. However, fallowing should not be confused with

uncultivated spaces because of laziness or other impeding factors.

3.3.3. Households’ source of income

As presented on the figure 3.1 below, households in Ngozi province have different sources of

income. Agriculture is the main source of income for the respondents. As revealed on the figure

3.1, food crops and cash crops sale are the most important sources of income followed by

livestock and salary. Commerce, artisans and forestry were also a source of income for some of

the respondents. It is important to note that income diversification is also one of the practiced

strategies by households in the study area as a way of risks management. These are calculated

based on the share of the total of all households in the sample.

Figure 3.1: Source of income in Ngozi province (2007)

11%

11%

25%

3%

22%

11%

4%0%

5%8% Salary

Commerce

Food crops

Land lease

Cash crops

Livestock

Forestry


36

3.3.4. Households’ yearly expenditures on food and agricultural inputs

Looking at the average household expenditure for the sample, 68% of expenditure goes to food

purchase and 32% to agricultural inputs. Among agricultural inputs labor occupies 18% while

7% goes to improved seed and a remaining 4% and 3% go respectively to land rental and

fertilizer inputs. The share of expenditure on pesticides is very small.

Figure 3.2: Households’ yearly expenditure on food and inputs (2007) in Ngozi province

The high proportion of food purchase expenditure shows that farmers are not able to satisfy their

food needs through their own production. They still need to purchase food. Even though we

recognize that farmers cannot only eat the food produced on their farms, 69% of the total

household expenditure is high and reveals limited food production for intrahousehold

consumption.

69%

18%

7%

4% 2%

Food

Labor

Improved seeds

Fertilizer

Pesticide

Chapter 4 Results and Discussion

37

Chapter 4 : RESULTS AND DISCUSSION

This chapter is presented in six sections. Section 4.1 gives an overview of the use of farming

techniques in Ngozi province; 4.2 is about the evolution of agricultural production techniques.

Section 4.3 is about the influence of agricultural production techniques on production. Section

4.4 gives an overview of food security in Ngozi province. Section 4.5 and 4.6 gives the empirical

results for conceptual models described in chapter 3 respectively about the relationship between

household food security and agricultural production techniques in one part and about factors

influencing the uptake of agricultural production techniques on the other part.

4.1. OVERVIEW OF THE ADOPTION OF FARMING TECHNIQUES IN NGOZI

PROVINCE

This section describes the frequency of the uptake of different farming techniques that present

potential to improve food security through an increase of production. The techniques analyzed

here include the use of improved seeds, chemical products (fertilizer, herbicides and pesticide),

organic soil improvements and other soil management practices.

4.1.1. The use and source of improved seeds

Farmers in Ngozi province obtained seeds from different sources. As illustrated in table 4.1 a

total of 46% of the respondents got their seeds from their own stocks of the previous harvest.

Cooperatives constitute a source of seeds for 3% of the respondents .The market supplied seeds

for 86% of the respondents while extension services provided seeds for 4% of the respondents.

Table 4.1: Source of seeds for the respondents

Sources of seeds % of respondents

Farmers’ own production 46

Cooperatives 3

Market 86

Extension 4


38

Table 4.1 above, shows that the most common source of seeds for the respondents was the

market followed by the farmer’s own production of the previous harvest. Cooperatives and

extension services was used as source of seeds for a very small proportion of the respondents

which reveals weakness in extension services while promoting food security in Ngozi.

Cooperatives would ideally be seen as conducive channels for passing on extension services

message to farmers or any other incentive to them. This is because if farmers are scattered, it is

not easy for whoever is engaged in it to reach a desired bigger outreach.

4.1.2. Use of chemical products

Chemical fertilizers, herbicides and pesticides play important roles in protecting crops from

insects, diseases and other pests, and decreasing soil fertility. Table 4.2 shows the level of use of

each of the chemical products.

Table 4.2: Use of chemical products by the respondents in Ngozi (2007)

Chemical products Adopters (%)

Chemical fertilizer 46

Herbicide 4

Pesticide 73

As indicated in table 4.2 above, pesticide was the most important chemical product reported to

be used by a large proportion of the respondents, 73%, while chemical fertilizer followed with a

proportion of 46% of the respondents and finally herbicide was used by a proportion of 4% of

the respondents. This high pesticide use by the respondents can be an indication that pest attack

on crops is widespread in Ngozi and hence extension workers or farmers animators stimulate to

tackle the problem.


39

4.1.3. Source of chemical fertilizers and pesticides

In this study, the private sector, cooperatives, markets, farmer’s associations, extension services

were all considered as possible sources of chemical fertilizers and pesticides for the respondents.

Table 4.3 below shows the percentages of respondents buying chemical fertilizer and pesticide

from above sources.

Table 4.3: Sources of fertilizer and pesticide supply

Source of chemical products Fertilizer (%) Pesticide (%)

Private sector 1 1

Market 35 4

cooperatives 1 4

Farmer's association 1 1

Extension services 11 75

Furthermore, table 4.3 above, indicates that the market was the major source of fertilizer for the

respondents, with a proportion of 35% of the respondents buying the fertilizer at the market. A

proportion of 11% of the respondents confirmed to get chemical fertilizer from extension

services. Cooperatives and farmer‘s associations rank the last according to the respondents.

However, a proportion of 51% of the respondents did not use any of the given sources of

fertilizers. Concerning the source of pesticides, extension services were the most important

source as confirmed by 75% of the respondents. The market, cooperatives and farmers

associations were sources of pesticides for a smaller proportion of the respondents.

4.1.4. Soil organic matter improvement techniques

Manure, composting, landfill and mulching were the farming techniques considered in the survey

for soil organic matter amelioration. Table 4.4 below shows the fraction of respondents using

each of the different soil organic matter amelioration techniques.


40

Table 4.4: Soil organic matter improvement techniques

Soil organic matter improvement techniques Adopters (%)

Manure 62

Composting 80

Mulching 75

Landfill 92

As indicated from table 4.4 above, a large proportion of respondents, 92%, affirmed the use of

landfill techniques, followed by composting with a proportion of 80% of respondents. Mulching

and manure also have been used by the respondents in the survey area of Ngozi province. If we

compare the use of organic soil fertility management practices with the chemical fertilizer (46%)

we realize that the uptake is much higher for the organic ones than the uptake of chemical

fertilizer use. A possible reason for preferring manure over chemical fertilizers is the higher price

of the latter.

4.1.5. Marshland improvement techniques

Drainage and irrigation are the most important marshland improvement techniques considered in

our study area. Table 4.5 below shows the level of adoption by the respondents for each of the

techniques.

Table 4.5: Marshland improvement techniques

Marshland improvement techniques Adopters (%)

Drainage 68

Irrigation 9

From the above table 4.5 we realize that there were a large percentage of respondents, 69%, who

confirmed the use of drainage techniques. However, irrigation techniques were not well adopted

by the respondents in the study area. Drainage is a simple practice of regulating the water flow

on a farmland and may be done by the active household members only without necessitating an


41

external laborer. Irrigation, on the other hand, is a costly practice and requires enormous human

and financial resources to be implemented.

4.1.6. Sowing in line

The survey indicates that there were a high proportion of respondents, 79%, using sowing in line

as an improved plantation technique. The high take up may be explained by the fact that it is not

so demanding in the process except being labour intensive at the beginning. Unlike other

techniques which accrue the production costs, sowing in line is less demanding in terms of costs

as it facilitates efficiency in agricultural inputs use.

4.1.7. Anti-erosion hedges

Anti-erosive hedges are also adopted in the study area where 39% of the respondents confirmed

that they use anti erosive hedges.

To summarize, figure 4.1 below gives an overview of the agricultural production techniques

which have been confirmed to be used by the respondents in the study area of Ngozi province.

Figure 4.1: Agricultural production techniques in Ngozi province (2007)

46%

4%

73%62%

80% 75%

92%

68%

9%

79%

39%

0%10%20%30%40%50%60%70%80%90%

100%


42

We can conclude the section by saying that the level of uptake of various farming and production

techniques in Ngozi largely depends on the financial capability to afford the production cost.

This is evidenced by the fact that the findings reveal that the adoption rate is higher for the

techniques and practices that do not require much external resources to be adopted and precisely

those that can easily be technically implemented by family labor

4.2. EVOLUTION OF AGRICULTURAL PRODUCTION TECHNIQUES

In the study area, only 17% of the respondents confirmed that there was an increase in the use of

agricultural techniques during the previous 2 years, while 16% of the respondents affirmed that

there was a decline in the use of agricultural technologies. A proportion of 45% of the

respondents confirmed that the use of agricultural technologies remained constant; another 14%

experienced a high decrease in the use of agricultural technologies. A proportion of 7% of the

respondents did not use the agricultural technologies. This is an indication of the low progress of

the adoption of agricultural technologies in Ngozi Province. Table 4.6 below shows the level of

improvement in the use of agricultural technologies.

Table 4.6: Level of improvement in the use of agricultural technologies in Ngozi between

2005-2007

Level of improvement in the use of

agricultural technologies

Percentage

Do not use 7

Highly decreased 14

Decreased 16

Stable 45

Improved 17

Highly increased 1

Total 100


43

4.3. INFLUENCE OF AGRICULTURAL PRODUCTION TECHNIQUES ON CROP

YIELD

In this section, influence of production techniques (fertilizer, manure, irrigation and anti-erosion

hedges) on crop yield is shown by comparison of average crop yield of some of the main food

crops among adopters and non adopters of the techniques

4.3.1. Influence of chemical fertilizers

Increasing food production requires intensive agriculture based on modern technologies,

fertilizer included (Mwangi, 1997; FAO, 2006), as land is no longer plentiful. Table 4.7 shows

the importance of fertilizer use by comparing mean crop yield of some crops between adopters

and non adopters of fertilizer in the study area of Ngozi.

Table 4.7: Comparison of food crop yield among adopters and non adopters of fertilizer

(kg over the three seasons per farm)

Mean crop yield per

Crop

Users (n=166) Non users (n = 194)

Mean SD Mean SD T-test P- value

Rice 92.8 188.5 68.6 196.2 -1.2 0.236

Maize 92.8 197.6 32.2 71.6 -3.7 0.000

Beans 195.3 200.1 115 155.8 -4.1 0.000

Potatoes 175.1 364 61.3 187.2 -3.6 0.000

The results of T-test provide evidence that there is no statistically significant difference in mean

production of rice between fertilizer users and non users. However, there is a statistically

significant difference between fertilizer users and non users in mean production of Maize, beans

and potatoes. This is an indication that fertilizer use lead to increased production.

4.3.2. Influence of manure

Organic matter improves the soil structure, diminishes soil erosion, and helps to accumulate

moisture (FAO, 2006). Manure use contributes to releasing nutrients to the soil slowly and helps

to make organic matter with long –term benefits (Place et al., 2003).


44

In this study the importance of manure use is shown by comparing selected crops production

among users and non-users of manure (Table 4.8).

Table 4.8: Comparison of food crop yield among manure users and non users (kg over the

three seasons per farm)

Mean crop yield per

crop

Users (n= 223) Non users (n=137)

Mean SD Mean SD T-test P-value

Rice 111.6 229.2 27.9 89.2 -4.8 0.000

Maize 76.6 173.3 33.3 82.6 -3.1 0.002

Beans 181 185.5 106.2 165.8 -3.9 0.000

Potatoes 160 338.9 38.5 149.5 -4.6 0.000

Results show that there is a statistically significant difference in mean production of rice, maize,

beans, and potatoes between users and non users of manure. For all crops considered the mean

production was higher for manure users compare to non users.

4.3.3. Influence of irrigation

Irrigated agriculture has been attributed a greater importance in increasing food production

(Dabour, 2002). In our case study irrigation is mainly done in the marshes therefore it mostly

applies for farmers with access to land in marshes. Table 4.9 shows the importance of irrigation

by comparing mean production of selected crops between adopters and non adopters.

Table 4.9: Comparison of food crop yield between adopters and non adopters of irrigation

(kg over the three seasons per farm)

Mean crop yield per

crop

Adopters(n=32) No adopters (n=328 )


Rice 147.3 251.3 73.2 185.3 -2.0 0.038

Maize 137.6 304.5 52.5 119.5 -1.5 0.127

Beans 181.2 182.1 149.7 181.7 -0.9 0.351

Potatoes 181.4 314.8 107.1 285 -1.3 0.164


45

There is no statistically significant difference in mean production of maize, beans and potatoes

between adopters and non adopters of irrigation. Nevertheless there was a statistically significant

difference in mean production of rice between adopters and non adopters of irrigation. The lack

of significance for other crops other than rice can be explained by the fact that irrigation is done

in marshland and in most cases rice is the only food production produced in marshland

4.3.4. Influence of anti-erosion hedges

Anti–erosion hedges contribute to the protection of soil against erosion especially in the areas

where the topography is made by hills. The importance of anti-erosion hedges is shown by

comparing the mean production of selected crops between adopters and non adopters as

presented in table 4.10 below.

Table 4.10: Comparison of food crop yield among adopters and non adopters of anti-

erosion hedges (kg over the three seasons per farm)

Adopters (n=141) Non adopters (n=219)

Mean crop yield per

crop


Rice 108.9 247.3 61 145 -2.1 0.038

Maize 80.5 175.7 47 123.7 -1.9 0.05

Beans 189.9 194.5 128 169.1 -3.1 0.002

Potatoes 124.8 236.1 106.6 317.3 -0.5 0.561

The results of T-test prove that there is no statistically significant difference between adopters

and non adopters of anti-erosion hedges in mean production of potatoes. On the other hand, there

was a statistically significant difference in mean production of rice, maize, and beans between

adopters and non adopters of anti-erosion hedges. This indicates that this practice has a positive

influence on production in the study area.


46

Concerning productivity, it is difficult to compare productivity among adopters and no adopters

of the above techniques, because with a mixed cropping system, it is difficult to know how much

hectares of each crop are planted per season

4.4. OVERVIEW OF FOOD SECURITY IN NGOZI PROVINCE

In the following paragraphs, an overview of the household’s food security in the survey area of

Ngozi province is given. HFIAS was used to measure the degree of food insecurity (access) in

the households in the past 30 days. Figure 4.2 indicates the frequency of the respondents who

answered affirmatively or negatively to each of the nine HFIAS questions.

Figure 4.2: Frequency of respondents’ experiences for each of the nine HFIAS generic

questions

From the figure 4.1 above, we could realize that in our sample a big proportion of respondents,

74.4%, confirmed that they have been worried about not having enough food in their households

over the past 30 days. This is a sign of food insecurity in the sampled region and households of

Ngozi Province. Furthermore, it indicates that a large percentage of respondents, 86%, ate few

kinds of food and was not able to eat the kinds of food they preferred over the past 30 days

because of a lack of resources. Moreover, a considerable proportion of respondents, 78% and

75%, revealed respectively eating smaller meals than needed and fewer meals in a day by any

household member because there was not enough food. More to these points, 59% and 29% of

the respondents stated respectively that any household member went a whole day without eating

74

86

86

87

78

75

43

29

59

26

14

14

13

22

25

57

71

41

0 20 40 60 80 100

Worry about food

Not able to eat food they preferred

Eating just a few kind of food

Eating food not preferred

Eating smaller meals

Eating fewer meals in a day

No food at all in the household

Went to sleep hungry

Whole day without eating

no yes


47

anything and went to sleep at night hungry because there was not enough food. Even 43% of the

respondents stated not having food at all (rarely, sometimes, or often) in the household because

there were no resources to get more.

By summing up the household response of experience during the past 30 days for the 9 food

insecurity related questions, the HFIAS score (0-27) was calculated for each household. Figure

4.3 gives the HFIAS score frequency for the households in the study area.

Figure 4.3: HFIAS score for the households in Ngozi province (2007)

Based on the results of the above figure 4.3, knowing that the maximum score of HFIAS is 27

(where the household response to all 9 questions was often) and the minimum score is 0 (where

the household response to the 9 generic questions was never), food security groups were

identified. The higher the score, the more food insecurity (access) the household experienced.

The lower the score the less food insecurity the household experienced and the more food secure

the household was. Table 4.11 gives the household food security status categories in Ngozi

province.

0

5

10

15

20

25

30

35

0 2 4 6 8 10 12 14 16 18 20 22 24 26

Fre

qu

ency

HFIAS score

HFIAS score frequency


48

Table 4.11: Households food security status categories in Ngozi province in 2007

Categories of food insecurity with respect

to HFIAS

Frequency Percentage (%)

Food secure 31 9

Mild food insecure 33 9

Moderate food insecure 68 19

Severely food insecure 228 63

TOTAL 360 100

From the above table 4.11, we notice that only 9% of the households in the study area were food

secure, other 9% were mild food insecure while 19% of the households were moderately food

insecure. A significant proportion of the households, 63%, were classified among the severely

food insecure group indicating how severe the food insecurity situation was in Ngozi in 2007.

4.5. RELATIONSHIP BETWEEN HOUSEHOLD FOOD SECURITYAND

AGRICULTURAL PRODUCTION TECHNIQUES

In this section it was interesting for us to determine whether the agricultural production

techniques that have been confirmed to be used by the respondents are associated with food

security in the study area. This was done in two ways: first of all through bivariate analysis using

crosstabs and chi-square tests, and secondly through a more advanced multivariate analysis using

binary logistic regression.

4.5.1. Relationship between household food security and agricultural production

techniques: bivariate analysis

In this section, a bivariate analysis was conducted to see the relationship between food security

and different techniques in use by farmers in Ngozi Province (2007) such as fertilizer use,

manure application, anti erosion structures and marshland irrigation.

A positive relationship was found between food secure households and production techniques

like fertilizer use, manure application, and marshland irrigation. At the 5% significance level,


49

there is a strong correlation between food security and use of manure. This suggests that the use

of manure for improving on soil fertility and productivity is very important. The findings come

to reinforce the calling for farmers not to rely exclusively on chemical fertilizers because manure

has the same potential of improving soil fertility and most importantly while sustainably

preserving the soil’s minerals. The application of manure contributes to the supply of plant

nutrient and contributes to soil organic matter improvement (FAO, 2006). The same significance

was found with marshland irrigation even though not adopted by many farmers because of the

high cost factor it has a great potential to improve food security because of the less dependency

on rainfall. With irrigation, the drought is not a problem and hence food is available throughout

the whole yearly cycle. Table 4.12 below shows the relationship between food security and

selected production techniques where in each case the first row is the number of respondents and

the second row are percentages.

Table 4.12: Bivariate analysis between food security and food production techniques

Food secure Use of chemical

fertilizer

Manure

application

Anti erosive

hedges

Marshland

Irrigation

No Yes Total No Yes Total No Yes Total No Yes Total

No 184 145 329 135 194 329 202 127 329 303 26 329

56 44 100 41 59 100 61 39 100 92 8 100

Yes 10 21 31 2 29 31 17 14 31 25 6 31

32 68 100 6 94 100 55 45 100 81 19 100

Total 194 166 360 137 223 360 219 141 360 328 32 360

54 46 100 38 62 100 61 39 100 91 9 100

Pearson

Chi-

square& p-

value

Pearson chi-

square= 6.387,

P-value=0.011

Pearson chi-

square = 14.372,

P value = 0.000

Pearson chi-

square= 0.512,

P value=0.474

Pearson

Chi-square=4.588,

P value = 0.032

4.5.2. Relationship between household food security and agricultural production

techniques: multivariate analysis

The dependent variable for this subsequent analysis is severely food insecure as we previously

documented that majority of households in Ngozi is classified in this category. To examine the


50

relationship between this dependant variable and several independent variables simultaneously

multivariate analysis is used.

According to the literature, Faridi and Wadood (2010); Feleke et al.(2005), the following

variables could influence food security:

Socio-demographic characteristics of the households such as the household size, age of the

household head, and sex of the household head could influence the household food security status;

The endowment of resources to produce own food such as land size also could influences

household food security;

The level of income to purchase food from the market could influence household food

security;

Finally agricultural production techniques such as the use of chemical fertilizer, manure,

composting, irrigation, mulching also could affect household food security.

Not all the above variables could be included in the model because of the problem of

multicollinearity. The best model obtained, which can explain most of the variance in the

dependent variable, is represented in table 4.13. The model is verified on correctness and

strength by means of statistical tests presented in table 4.14.


51

Table 4.13: Relationship between agricultural production techniques and food security

(Dependant variable: Severely food insecure)

95% C.I. for EXP

Determinants B SD Sig EXP(B) Lower Upper

Constant 1.592 0.444 0 4.912

Household size 0.018 0.056 0.747 1.018 0.913 1.136

Use of chemical fertilizer (1) -0.484 0.243 0.047** 0.616 0.383 0.993

Use of manure (1) -0.788 0.274 0.004** 0.455 0.266 0.778

Composting (1) -0.217 0.327 0.507 0.805 0.425 1.527

Mulching (1) 0.311 0.284 0.274 1.364 0.782 2.378

Marshland irrigation (1) -0.472 0.4 0.238 0.624 0.285 1.366

Anti-erosion hedges (1) 0.075 0.25 0.763 1.078 0.661 1.759

Number of trainings per season -0.271 0.201 0.178 0.762 0.514 1.131

Farm size (ha) -0.347 0.117 0.003** 0.707 0.562 0.889

Access to credit (1) 0.347 0.366 0.343 0.707 0.345 1.448

Significance level: **= 0.05

Table 4.14: Statistical tests for the model

Test statistics Value P-value

Chi- square 47.769 0

Cox & snell R Square 0.125 -

Nagelkerke R Square 0.171 -

Hosmer and Lemeshow test 6.399 0.603

Analysis with binary logistic regression reveals that there is no statistically significant effect of

individual technologies such as mulching, composting, irrigation of marshland, and anti-erosion

hedges on severely food insecurity in Ngozi province, at 5% significance level. The frequency of

agricultural trainings from an extension service attended by a farmer per season and household

size also have no statistically significant effect on severely food insecure. Checking for


52

multicollinearity already revealed only a weak correlation between the number of trainings and

the different agricultural production techniques, indicating only a small effect of this type of

education on the quality of agricultural production and thus on food security. This may be a sign

that the existing delivery system of trainings is too weak to contribute to improved food security.

On the other hand, the results from analysis using a binary logistic regression as presented in

table 4.13 above show a significant negative effect of fertilizer and manure use on the likelihood

of being severely food insecure at the 5% significance level. The log of the odds of being

severely food insecure decreases by a factor of 0.484 when households use fertilizer compared to

those that do not use fertilizer, ceteris paribus. The same situation is observed in the case of

manure application where the log of the odds of being severely food insecure decreases by a

factor of 0.788 when households use manure compared to households not using manure, ceteris

paribus. This means that households that use manure are less likely to be severely food insecure

than households that do not utilize manure, ceteris paribus.

The results show also that households with a smaller farm size are more likely to be severely

food insecure compared to households with larger farm size. This is confirmed by statistically

significant negative coefficient of the variable which shows that for a one unit (ha) increases in

farm size, the log of the odds of being severely food insecure decreases by a factor of 0.347,

ceteris paribus. In our case study the average farm size is shrinking and the land: man ratio is

reducing as population growth continues to increase and this may result in reduced farm yield,

income and expenditure levels which in turn are able to worsen the standard of living of the

population and thus lead to food insecurity for many households in rural areas of Ngozi province.

The results from table 4.14 show that the model chi-square is 47.769 with a p-value of 0.000.

This indicates that the model is significant, that variables in the model other than the intercept

are useful in explaining severe food insecurity. The Cox & Snell R² for the model is 0.125 and the

Nagelkerke R² is 0.171 which leads us to believe that there is at least some association between the

dependant and independent variables .The goodness-of-fit measure (Hosmer and Lemeshow) has a

value of 6.399 and a p- value of 0.603 which means that the predicted values are not significantly

different than the observed values.


53

From the results of table 4.13 following model is estimated for the log odds of being severely

food insecure

Where X1= household size, X2 = use of chemical fertilizer (1), X3 = use of manure (1), X4

=composting (1), X5 = mulching (1), X6 = marshland irrigation (1), X7 = anti-erosion hedges

(1), X8 = number of trainings per season, X9 = farm size (ha), X10 = access to credit (1).

The following equation estimates the odds:

Finally, the probability of being severely food insecure (p) is obtained by applying the logistic

transformation:

Figure 4.4 below shows that the probability of being severely food insecure when fertilizer is

used drops by 0.09 compared to the reference value while this probability drops by 0.16 when

manure is used compared to the reference. In addition, a one unit (ha) increase in farm size

decreases the probability of being severely food insecure by 0.07 compared to the reference

value. The reference represents a farmer which uses no fertilizer but also doesn’t use manure and

has an average farm size.


54

Figure 4.4: Probability of being severely food insecure

To summarize, the results from this analysis show that the use of fertilizer, manure and farm size

are major determinants of food security in the study area, where the likelihood of being severely

food insecure decreases with the use of fertilizer, manure and an increase in farm size. Similar

findings were found by Feleke et al. (2005), Bogale and Shimelis (2009), Faridi and Woodod

(2010), Omotesho et al. (2010) to name a few.

The next step consists of exploring factors influencing farmers to adopt agricultural production

techniques namely for fertilizer and anti-erosion hedges.

4.6. FACTORS INFLUENCING THE ADOPTION OF AGRICULTURE

PRODUCTIONTECHNIQUES

According to the literature, Bett (2001); Cavane (2009), Yila and Thapa (2008); Kudi et al

(2010)), the following variables could influence households to adopt agricultural production

techniques.

Farmers’ characteristics such as age of the household head, family labour, sex of the

household head, and household size;

Socio-economic characteristics such as access to credit, farm size,

0.79

0.70.63

0.72

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Reference Use of fertilizer Use of manure Average farm size

(increases by one

hectare)

Pro

ba

bil

ity

Independant variables


55

Institutional characteristics such as extension services including trainings, visits and

farmer’s groups.

The above factors cannot be all included in the model because of the problem of

multicollineallity. The best models obtained are presented in table 4.15 and 4.17. While table

4.16 and table 4.18 show the statistical tests of the accuracy and strength of the models.

4.6.1. Factors influencing the adoption of fertilizer.

Table 4.15: Factors influencing the adoption of fertilizer (Dependant variable: fertilizer

use)

Determinants B S.E. Sig. Exp (B)

95.0% C.I. for EXP(B)

Lower Upper

Constant -1.687 0.313 0.000 0.185

Total number of plots 0.154 0.040 0.000** 1.166 1.078 1.262

Number of visits per month

by extension workers

0.245 0.133 0.066* 1.277 0.984 1.659

Number of trainings per

season

0.253 0.230 0.271 1.287 0.821 2.019

Access to credit (1) 0.114 0.380 0.765 1.120 0.532 2.359

Member of cooperative (1) 0.533 0.231 0.021** 1.704 1.084 2.680

Farm size (ha) 0.060 0.093 0.517 1.062 0.885 1.274

Significance level: *= 0.1, **= 0.

Table 4.16: Statistical tests for the model







56

The results of the binary logistic regression from the above table 4.15 show that the number of

trainings attended by a farmer per season, access to credit, and the farm size have no statistically

significant influence on the adoption of fertilizer at 10% significance level. Although it is evident

that the use of fertilizer necessitates capital such as money in order to purchase fertilizer, access

to credit has no significant influence on the uptake of fertilizer in Ngozi province. Only small

number of farmers in Ngozi has access to credit and therefore access to credit is not so

determining. This may be explained by the fact that most of the households in Ngozi are small

farmers and most of them lack the land titles or other acceptable security for collateral. Another

reason may be that the procedures for obtaining credit are too complicated and time consuming

for farmers who need credit in advance.

On the other hand, the total number of plots, the number of visits per month by extension

workers and membership of farmer’s cooperatives influence positively the use of fertilizer. A

one unit increase in the number of visits per month by extension workers increases the log of the

odds of fertilizer use by a factor of 0.245, ceteris paribus. This is logical in the sense that

knowledge exchange between extension workers and farmers on the one hand and sensitization

about the benefit of using fertilizer for productivity growth on the other hand can help farmers to

improve their way of combining assets to improve their methods of production including

fertilizer use. Furthermore with extension workers’ visits, farmers are exposed to information

which reduces their subjective uncertainty and in that way increases the chance of improved

level of uptake of technologies, fertilizers included.

In addition, the results from the analysis illustrate that farmers who are members of cooperatives,

are more likely to use fertilizer than non-members of cooperatives. This is probably due to the

fact that farmers’ cooperatives have more access to agricultural information, credit and therefore

their members have a better ability to adopt innovations, fertilizer included, than non-members

of cooperatives. Also, when it comes to agricultural support provision farmers’ cooperatives

reduce the transaction costs and have high potential to remediate on the issue of imperfect

information and uncertainty of agricultural inputs. In addition the total number of plots has a

significant positive influence on the use of fertilizer. Households having more number of plots

are more likely to use fertilizer than households with less number of plots.


57

The results from table 4.16 show that the model chi-square is 40.003.with a p-value of 0.000.

This indicates that the model is significant, that there is a significant relationship between

fertilizer use and the set of independent variables other than the intercept. The Cox & Snell R² for

the model is 0.108 and the Nagelkerke R² is 0.144 which leads us to believe that there is at least some

association between the dependent and independent variables. The goodness-of-fit measure (Hosmer

and Lemeshow) has a value of 7.138 and p-value of 0.522 which means that the predicted values

are not significantly different than the observed values

From the above table 4.15, the fitted model is:

Where X1 = total number of plots, X2 = number of visits per month by extension workers, X3 =

number of trainings attended per season, X4 = Access to credit, X5 = member of cooperative, X6

= farm size (ha)


Finally, the probability of fertilizer adoption (p) is obtained by applying the logistic

transformation:

Figure 4.5 below shows that the probability of fertilizer use increases by a factor of 0.14 when

the household head is a member of cooperative compare to the reference. While this probability

increases by a factor of 0.04 when the number of plots increases with one unit and by a factor of

0.03 when the number of visits increases with one unit.


58

Figure 4.5: Probability of adopting fertilizer

To summarize the results of this analysis we conclude that being a member of cooperative, and

the number of visits per month by extension workers and the total number of plots per farming

household are major factors determining the adoption of fertilizer in the study area. Similar

results were found by Wanyama al. (2010), Cavane (2009), Waithaka et al. (2007), and Morris et

al. (2007).

4.6.2. Factors influencing the adoption of anti-erosion hedges

Table 4.17: Factors influencing the adoption of anti-erosion hedges (Dependant variable:

Use of anti-erosion hedges).

95%C.I. for EXP

Determinants B SD Sig EXP(B) Lower Upper

Constant -1.568 0.335 0 0.208

Number of visits per month by

extension workers

0.24 0.127 0.059* 1.272 0.991 1.631

Number of trainings per season 0.248 0.215 0.248 1.281 0.842 1.951

Member of cooperative (1) 0.52 0.231 0.025** 1.682 1.069 2.646

Household size 0.095 0.053 0.072* 1.099 0.999 1.219

Farm size 1.188 0.091 0.038** 1.206 1.01 1.441

Significance level: *= 0.1, **= 0.05**

0.42

0.56

0.46 0.45

0

0.1

0.2

0.3

0.4

0.5

0.6

Reference Member of

cooperative (1)

Total number of

plots (increase by

one)

Number of visits

per month by

extension workers

Pro

ba

bil

ity



59

Table 4.18: Statistical test for the model






The results of the analysis by binary logistic regression presented in table 4.17 above, show that

there is no significant influence of the number of trainings attended by farmers per season on the

adoption of anti erosion hedges. Nevertheless, the numbers of visits per month by extension

workers, being a member of a cooperative, household size and farm size have a significant

positive influence on the adoption of anti-erosion hedges.

The results show that a one unit increase in the number of visits per month by extension workers

increases the log of the odds of the uptake of anti-erosion hedges by a factor 0.24, keeping other

variables constant. This is possibly due the fact that uptake of anti-erosion hedges requires

technical information and with more visits by extension, farmers may have reduced hesitation

and consequently may have enhanced probability to adopt anti-erosion hedges.

Moreover the results show that households who are member of cooperatives are more likely to

adopt anti-erosion hedges compare to households who are not members of cooperatives. This

implies that farmers who belong in cooperatives may have more necessary technical information

and benefits of anti-erosion hedges and this may result in increased chance of adoption.

Furthermore, the results from table 4.17 indicate that bigger households are more likely to adopt

anti-erosion hedges. In addition, a one unit (ha) increase in the farm size increases the log of the

odds of adopting anti-erosion by a factor of 1.188, keeping other variables constant. This makes

sense as once more land is available farmers are likely to adopt anti-erosion hedges because in

that case farmers do not fear that there is rivalry of land between crops and anti erosion hedges.

Also, a large farm size ownership is likely to go with tenure security which might bring the

owner to investing on his/her farmland through various ways including anti- erosive hedgerows.


60

The results from table 4.18 show that the model chi-square is 28.761 with a p-value of 0.000.

This indicates that the model is significant, that variables in the model other than the intercept

are useful in explaining anti-erosion adoption. The Cox & Snell R² for the model is 0.079 and the

Nagelkerke R² is 0.107 which leads us to believe that there is at least some association between the

dependent and independent variables .The goodness-of-fit measure (Hosmer and Lemeshow) has a

value of 11.046 and p-value of 0.199 which means that the predicted values are not significantly

different than the observed values.

As a result, the estimated model in the equation is as below:

Where X1 = number of visits per month by extension workers, X2 = number of trainings per

season, X3 = member of cooperative, X4 = household size, X5 = farm size (ha)


Finally, the probability of anti-erosion adoption ( ) is obtained by applying the logistic

transformation:

Figure 4.6 below show that the probability of adopting anti-erosion hedges increases by a factor

of 0.12 when the household head is a member of cooperative compared to no member of

cooperative. When the number of visits per month by extension workers increases by one unit,

the probability of adopting anti-erosion increases by a factor of 0.02. Also a one unit increase in

farm size increases the probability of adopting anti-erosion hedges by a factor of 0.24.


61

Figure 4.6: Probability of adopting anti-erosion hedges

0.57

0.69

0.59

0.81

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Reference Member of cooperative (1)

Number of visits per month by

extension workers

Farm size (increases by one

hectare)

Pro

bab

ility


Chapter 5 Conclusion, policy implications and recommendations

62

Chapter 5 : CONCLUSION POLICY IMPLICATIONS AND

RECOMMENDATIONS

The present study departed from the problematic issue of food insecurity that hits Sub- Saharan

countries and among them Burundi. The general objective of the study was to analyze drivers of

food security with special reference to agriculture development. One of the major components of

food security is food availability and the rest of the components take their roots in it. However,

food availability is not assured if mechanisms are not devised in order to accrue food production.

Moreover, given the high population pressure, increasing agricultural productivity of the

available land is needed in order to provide food for every more people.

Consequently, this study’s specific objectives were to identify different farming systems and

techniques used in Burundi particularly in Ngozi, to assess possible correlations between food

security and production techniques. More specifically the study assessed the influence of the

agricultural production techniques such as fertilizer, manure, composting, mulching, anti-erosion

hedges, and marshland irrigation on food security in Ngozi province.

The compiled literature for this study showed that Burundi is part of highland perennial farming

system but with limited uptake of production techniques, like irrigation, adopted by only 9% of

our sampled households, and limited access to loans (only 12% of the households). Yet, these are

the facilities that would best help settle the problem of limited food production that causes food

insecurity.

Using a bivariate and multivariate analysis of correlation, the study revealed that two majors

agricultural production techniques that are the use of fertilizer and manure, both aimed at

increasing soil fertility, have significant positive effects on household food security. Fertilizer

and manure use improves household food security through the increased food production and

thus food availability and household income.


63

We also note that farm size revealed to have a significant positive effect on household food

security which means that the higher the farm size the higher the probability of being food

secure. But of course as the results suggested, farm size alone cannot be a significant determinant

of food security. It has to be coupled by a rational management of the land through adoption of

integrated soil fertility management practices especially since most of the related techniques

were significantly related to food security.

From the above results, we can conclude that in order to improve food security in Ngozi

province, people should be stimulated to use these techniques. For that we analyzed the

determinants of uptake of these techniques. More specifically we analyzed the determinants of

fertilizer uptake and anti-erosion hedges. This showed the following results:

The fertilizer use itself is significantly dependent on the total number of plots, the number or

frequency of visits by agricultural extension workers to the farmers and the latter’s membership

to cooperatives. Both factors show the importance of extension services and access to

information for farmers in order to increase their farm productivity and consequently food

availability. This is logical due to the fact that knowledge exchange between extension workers

and farmers helps the latter to improve their methods of production including the uptake of

fertilizer. Additionally, farmers in cooperatives are more exposed to market information. On the

side of adoption of anti-erosion hedges, the number of visits by extension workers, farm size, household

size and membership to a cooperative revealed to be positively and significantly correlated with the

uptake of that technique as well.

From all the above, we can conclude the study of factors influencing food security in Burundi by

confirming that production techniques are part of the determining factors of food security in

Burundi and mainly the techniques that improve soil fertility like the use of fertilizer and other

techniques like manure use, composting and soil erosion control mechanisms through hedging

for example.

However, for whatever technique introduced or to be introduced, there is a strict need to take

care of environmental conservation for sustainable development. For example, the statistical


64

significance of fertilizer use and food security should not mislead by thinking that using

excessive quantity or dose of fertilizer would help improve food security. It may give a sign of

increased production but in the long run generate more severe food insecurity because of soil

depletion. This problem is described very well by Tirado and Bedoya (2008) who concluded that

excessive use of fertilizer may lead to a declining crop yields and have negative effects on

human health and the environment.

Consequently, the findings suggest a series of policy implications that should guide policy

makers as regard to improving sustainable food security in Ngozi Province:

Increase the capacity and strengthen extension services: extension services are important

elements that influence the adoption of new agricultural technologies, among them

fertilizer. Therefore providing training and improving incentives to extensions workers

may lead to improved food security.

The promotion and strengthening of cooperatives and farmers’ organizations: This would

be a good prerequisite for aspiring to a high and informed uptake of new agriculture

practices that would play a significant role towards food security improvement. These

cooperatives and/or farmers’ organizations are good drivers of key messages carried or to

be carried by the extension service officers. Cooperatives would in that sense favor the

economies of scale induced by the intensive use of fertilizer and the culture of

cooperative farming.

Promote and create labor-intensive off-farm rural employment opportunities: Off-farm

rural employments can lead to direct increase in household income but also can have an

indirect effect when off-farm income is invested in agriculture may lead to an increase in

farm production and income.

To complement this study, a study to assess food security based on energy requirement per capita

of households is recommended.

References

65

REFERENCES

Agresti, A. 2002. An Introduction to Categorical Data Analysis, 2nd ed. NewYork: John Wiley

and Sons, Inc.

Agwu, A.E. 2004. Factors Influencing Adoption of Improved Cowpea Production Technologies in

Nigeria. Journal of International Agricultural and Extension Education, Volume 11, number1

Asiabaka, C.C., Morse, S., and Kenyon, L., 2001.The Development, Dissemination and Adoption of

Technologies Directed at Improving the Availability of Clean Yam Planting Material in Nigeria and

Ghana. Report of a study mission commissioned UK Government Department for International

Development (DFID) Crop Protection Program (CPP)

Baghdadli, I., Harborne, B., 2008. Breaking the Cycle. A strategy for Conflict Sensitive Rural Growth in

Burundi. World Bank Working Paper No. 147

Bahiigwa, B.A.G. 2002. Rural Household Food Security in Uganda: An Empirical Analysis. Eastern

Africa Journal of Rural Development 18(1): 8-22

Banderembako, D., 2006. The Link Between Land, Environment, Employment, and Conflict in Burundi.

Produced by Nathan Associates, Inc. for the USAID

Beck, J., Citegetse, G., Ko, J., Sieber, S. 2010. Burundi environmental threats and opportunities

assessment (ETOA). USAID

Beddington J., 2010. Food security: contributions from science to a new and greener revolution. In

Philosophical Transaction of The Royal Society B 365, 61-71. Royal Society Publishing, UK

Bekele, W., Drake, L., 2003. ANALYSIS. Soil and water conservation decision behavior of subsistence

farmers in the Eastern Highlands of Ethiopia: a case study of the Hunde- Lafto area. Ecological

Economics, volume 46, pp. 437- 451

Bogale, A., and Shimelis, A., 2009. Household Level Determinants of Food Insecurity In Rural Areas Of

Dire Dawa, Eastern Ethiopia. African Journal of Food Agriculture Nutrition and Development, Volume

9, pp. 1914-1926

Cavane, E., 2009. Farmers’attitudes and adoption of improved maize varieties and chemical fertilizers in

Mozambique. African Crop Science Conference Proceedings, Volume 9. pp. 163 - 167

Clover, J. 2003. Food Security in Sub-Saharan Africa .African security review 12(1)

Coates, J., Swindale, A., and Bilinsky, P. 2006. Household Food Insecurity Access Scale (HFIAS) for

Measurement of Food Access: Indicator Guide. Washington, D.C.: Food and Nutrition Technical

Assistance Project, Academy for Educational Development

Cochet, H. 2004. Agrarian dynamics, population growth and resource management: The case of Burundi.

GeoJournal 60: 111–122

Dabour, Md. 2002. The role of irrigation in food production and agricultural development in the Near

East region. Journal of economic cooperation 23, 3 p 31-70

References

66

Defoer, T., Budelman, A., Toulmin, C., Carter, S., and Ticheler, J. 1998. Soil fertility management in

Africa: A resource guide for participatory learning and action research

Dei, J., 2008. Vulnerability and Food Insecurity in Three Urban Areas of Burundi. An Assessment of the

Impact of High Prices on Households in Bujumbura Mairie, Ngozi and Gitega Cities, UN World Food

Programme

Delgado, C., Townsend, R., Ceccacci, I., Hoberg, Y.T., Bora, S., Martin, W., Mitchell, D., Larson, D.,

Anderson, K., and Zaman, H. 2010. Food security: The Need for multilateral actions. Postcrisis Growth

and Development, pp 383-438

D’Haese, L., Ndimubandi, J., D’Haese, M., Speelman, S., Vandamme, E., Nkunzimana, T. Recovering

from conflict: an analysis of food production in Burundi. Poster presented at the Joint 3rd African

Association of Agricultural Economists (AAAE) and 48th Agricultural Economists Association of South

Africa (AEASA) Conference

Dixon, J., and Gulliver, A., and Gibbon, D. 2001. Farming systems and poverty: Improving farmers’

livelihoods in a changing world. Rome and Washington, DC: Food and Agriculture Organization of the

United Nations (FAO) and World Bank

Doss, C.R. 2006. Analyzing technology adoption using microstudies: limitations, challenges, and

opportunities for improvement. Agricultural Economics 34, pp 207–219

Doss, C.R., 2003. Understanding Farm Level Technology Adoption: Lessons Learned from CIMMYT’s

Micro Surveys in Eastern Africa. CIMMYT Economics Working Paper 03-07

Food and Agriculture Organization of the United Nations, 2008. Methods to Monitor the Human Right to

Adequate Food, The Right to Food Publication, Volume 1

Food and Agriculture Organization of the United Nations, 2007. Statistical databases

Food and Agriculture Organization of the United Nations, 2009. Food insecurity in the world, economic

crises impacts and lessons learned. Rome

Food and Agriculture Organization of the United Nations, 2009. The State of Food Insecurity in the

World. Rome

Food and Agriculture Organization of the United Nations, 2010. The State of Food Insecurity in the

World. Addressing food insecurity in protracted crises. Rome

Food and Agriculture Organization, 2010. Burundi country profile. Available from

http://www.fao.org/fileadmin/templates/ess/documents/food_security_statistics/country_profiles/eng/Bur

undi_E.pdf. Accessed at 8/8/2011

Faridi, R., and Wadood, S.N. 2010. An Econometric Analysis of Household Food Security in Bangladesh.

In The Bangladesh Development Studies, N0 3

Feder, G., Just, R.E., Zilberman, D. 1985. Adoption of Agricultural Innovations in Developing Countries:

A Survey. Economic Development and Cultural Change, Volume 33, No. 2, pp 255-298

http://www.fao.org/fileadmin/templates/ess/documents/food_security_statistics/country_profiles/eng/Burundi_E.pdf.%20Accessed%20at7/8/2011

http://www.fao.org/fileadmin/templates/ess/documents/food_security_statistics/country_profiles/eng/Burundi_E.pdf.%20Accessed%20at7/8/2011

References

67

Feleke, T., Kilmer, R.L., and Gladwin, C.H. 2005. Determinants of food security in Southern Ethiopia at

the Household level. Agriculture Economics, issue 33, 351-363

Fosu, K.Y., and Nico, H. 2011. Food Security and Nutrition: Implication of policy reforms with a case

study of Ghana. Available from http://www.uclouvain.be/cps/ucl/doc/ecru/documents/TF5M4D08.pdf

Accessed at 9/8/2011

Hartwig, H., and Gunter, H. 2006. The Economics of Natural Disasters. Implications and Challenges for

Food Security International Association of Agricultural Economists. Annual Meeting, August 12-18,

2006, Queensland, Australia

Human Development Report 2007/2008. United Nations Development Program

Idrisa, Y.L., Ogunbameru, B.O., Amaza, P.S. 2010. Influence of farmers’ socio-economic and technology

characteristics on soybean seeds technology adoption in Southern Borno State, Nigeria. African Journal

of Agricultural Research Volume 5(12), pp 1394-1398

International Center for Soil Fertility and Agricultural Development, 2007. An Action Plan for

Developing Agricultural Input Markets in Burundi

International Fund for Agricultural Development, 2006. Enabling the rural poor to overcome poverty in

Burundi. Available from http://www.ruralpovertyportal.org/web/guest/country/home/tags/burundi

International Fund for Agricultural Development, 2011. Rural Poverty Report Rome, Italy. Also

downloadable at www.ifad.org/rpr2011/report/

Jama, B., and Pizarro, G. 2008. Agriculture in Africa: Strategies to Improve and Sustain Smallholder

Production Systems United Nations Development Programme, New York, USA

Jayne, T. S., Yamano, T.,Weber, M.T.,Tschirley, D., Benfica, R.,Chapoto, A., and Zulu, B. 2003.

Smallholder income and land distribution in africa: implications for poverty reduction strategies. Food

Policy 28, 253-275

Kudi, T. M., Bolaji, M., Akinola M. O. and Nasa’I D. H. 2010. Analysis of adoption of improved maize

varieties among farmers in Kwara State, Nigeria. International Journal of Peace and Development

Studies Vol. 1(3), pp 8-12

Matata, P.Z., Ajay, O.C., Oduol, P.A. and Agumya, A. 2008. Socio-economic factors influencing

adoption of improved fallow practices among smallholder farmers in western Tanzania. African Journal

of Agricultural Research Vol. 5 (8), pp. 818-823

Maxwell, S. and Smith, M. 1992. Household Food Security: A Conceptual Review, in Household Food

Security: Concepts, Indicators and Measurements: A technical review, S. Maxwell and T.R

Frankenberger. New York and Rome: UNICEF and IFAD

Ministère de l’Agriculture et de l’élevage, République du Burundi, 2008. Stratégie Agricole Nationale

2008-2015

Ministry of Urban Planning, Tourism and Environment, Republique of Burundi, 2006. National biosafety

framework in Burundi

http://www.uclouvain.be/cps/ucl/doc/ecru/documents/TF5M4D08.pdf

http://www.ruralpovertyportal.org/web/guest/country/home/tags/burundi

References

68

Morris, M., Kelly, V.A., Kopicki, R.J., and Byerlee, D. 2007. Fertilizer Use in African Agriculture.

Lessons Learned and Good Practice Guidelines. The International Bank for Reconstruction and

Development / The World Bank

Mwangi, W.M. 1997. Low use of fertilizers and low productivity in sub-Saharan Africa. Nutrient cycling

in agroecosystems. Volume 47, 135-147

New Partnership for Africa’s Development, 2009. Comprehensive African Agriculture Development

Programme (CAADP) PillarIII. Framework for African Food Security (FAFS).Available from

http://www.caadp.net/pdf/CAADP%20FAFS%20BROCHURE%20indd.pdf. Accessed at 2/8/2011

Norton, G.W., Alwang, J., Masters, W. A. 2010 .World food systems and resource use. Economics of

Agricultural Development, 2nd

Edition, USA

Odoemenem, I.U., and Obinne, C.P.O. 2010. Assessing the factors influencing the utilization of improved

cereal crop production technologies by small scale farmers in Nigeria. Indian Journal of Science and

Technology Vol. 3 No. 1

Okoye, C.U. 1998. Comparative analysis of factors in the adoption of traditional and recommended soil

erosion control practices in Nigeria. Soil and Tillage Research 45: 251-263

Omotesho, O.A., Adewumi, M.O and Fadimula, K.S. 2010. Food Security and Poverty of the Rural

Households in Kwara State, Nigeria. Libyan Agriculture Research Center Journal International 1 (1) pp

56-59

Nations Online Project, 2011. Administrative Map of Burundi. Available at http://www.nationsonline.org

/ one world/map /burundi_map2.htm

Oriola, E.O. 2009. A Framework for Food Security and Poverty Reduction in Nigeria, European Journal

of Social Sciences. Volume 8, Number 1, pp 132-139

Pinstrup-Andersen, P., and Pandya-Lorch, R. 1997. Food security and sustainable use of natural

resources: a 2020 Vision, International Food Policy Research Institute, Washington

Place, F., Barret, C.B, Freeman, H.A, Ramisch, J.J, and Vanlauwe, B. 2003. Prospects for integrated soil

fertility management using organic and inorganic inputs: evidence from smallholder African agricultural

systems. Food Policy 28, pp 365–378

Rapport Burundi, 2010. Objectifs du Millénaire pour le Dévelopement

Renzaho, A.M.N., and Mellor, D. 2009. Food security measurement in cultural pluralism: Missing the

point or conceptual misunderstanding? Nutrition 26, pp 1–9

Republic of Burundi, 2006. Poverty Reduction Strategy Paper-PRSP

Rogers, E.M. 1995. Diffusion of Innovations (4th edition) New York: The Free University Press

Rome

Rome Declaration on World Food Security and World Food Summit Plan of Action 1996. Rome; World

Food Summit

http://www.caadp.net/pdf/CAADP%20FAFS%20BROCHURE%20indd.pdf.

References

69

Rushikanywa, T., and Roose, E. 1998. The Contribution of Banana Farming Systems to Sustainable Land

Use in Burundi, Advances in GeoEcology 31, 1197-1 204

Smith, L.C., Obeid, A.E., and Jensen, H.H. 2000. The geography and causes of food insecurity in

developing countries. Agricultural Economics 22, pp 199-215

Swanepoel, F., Stroebel, A., and Moyo, S. 2010. The Role of Livestock in Developing Communities:

Enhancing Multifunctionality. The Technical Centre for Agricultural and Rural Cooperation (CTA)

Tabi A.J., Vabi, M.B., Malaa, D.K. 2010 .Adoption of maize and cassava production technologies in the

forest savanna zone of Cameroun: implications for poverty reduction. World Applied Science Journal 11

(2):196-209

The Food and Agriculture organization Component of the 2007 Inter-agency Consolidated Appeals:

Protecting and rebuilding livelihoods in crisis –affected countries. Rome

Tirado, R., and Bedoya, D.2008. Agrochemicals use in Philippines and its consequences to the

environment. Greenpeace Organization

Ulukan, H. 2011. Plant genetic resources and breeding: current scenario and future prospects.

International Journal of Agriculture and Biology, 13: 447–454

Waithaka, M.M., Thornnton, P.K., Shepherd, K.D., and Ndiwa, N.N. 2007. Factors affecting the use of

fertilizers and manure by smallholders: the case of Vihiga, western Kenya. Nutrient Cycling in

Agroecosystms, 78:211–224

Wale, E., and Yalew, A. 2007. Farmers’ Variety Attribute Preferences: Implications for Breeding Priority

Setting and Agricultural Extension Policy in Ethiopia. African Development Bank, pp. 378-396

Wanyama, J.V., Mose, L.O., Rono, S.C., Masinde, A.A.O., and Kariuki, N. 2010. Determinants of

Fertilizer Use and Soil Erosion Control Measures in Maize Based Production System in Greater Trans

Nzoia District, Kenya. Middle-East Journal of Science Research 5(5): pp 425-434

Wodon, Q., Morris, M., Glaesener, V., Zoyem, J. P., Larbouret, P., Moens, M., Dianga, E., Mdaye, B.,

and Kavalec, A. 2008. Agricultural Recovery: Food Security and Beyond .World Bank Working Paper

World Bank, World Development Report, 2008. New York: Oxyford University Press

World Bank, 2010. Burundi: Country Brief. Available from http://go.worldbank.org/X3R55Z5AU0.


World Food Program, 2011. Burundi Overview. Available from http://www.wfp.org/countries/burundi.


World Vision International Burundi, 2003. Karuzi province food security Program. Final Report

Yila, O.M., and Thapa, G.B., 2008. Adoption of Agricultural Land Management Technologies by

Smallholder Farmers in the Jos plateau, Nigeria. International journal of agricultural sustainability 6 (4)

pp 277-288

http://go.worldbank.org/X3R55Z5AU0

http://www.wfp.org/countries/burundi

Annex

70

Annex

71

Annex

72

Annex

73

Annex

74

Annex

75

Annex

76

Annex

77

Annex

78

Annex

79

Annex

80

Annex

81

Annex

82

Annex

83

Annex

84

Annex

85

Annex

86

Annex

87

Annex

88

Annex

89

Annex

90

Annex

91

influence of agricultural production techniques on food...

Documents