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BETHEL, OYEINDOUBRA
PG/M. Sc/12/62310
EFFECTS OF AGRICUTURAL TECHNOLOGIES ON CASSAVA PRODUCTION
BY SMALLHOLDER FARMERS IN BAYELSA STATE, NIGERIA
Faculty of Agriculture
Agricultural Economics
Chukwueloka.O. Uzowulu
Digitally Signed by: Content manager’s Name
DN : CN = Webmaster’s name
O= University of Nigeria, Nsukka
OU = Innovation Centre
TITLE PAGE
EFFECTS OF AGRICUTURAL TECHNOLOGIES ON CASSAVA PRODUCTION
BY SMALLHOLDER FARMERS IN BAYELSA STATE, NIGERIA
A THESIS
SUBMITTED TO THE DEPARTMENT OF AGRICULTURAL ECONOMICS,
UNIVERSITY OF NIGERIA, NSUKKA FOR THE AWARD OF MASTER OF
SCIENCE IN AGRICULTURAL ECONOMICS
BY
BETHEL, OYEINDOUBRA
PG/M. Sc/12/62310
DECEMBER, 2015
CERTIFICATION
BETHEL OYEINDOUBRA, a post graduate student of the Department of Agricultural
Economics with registration number PG/M.Sc/12/62310 has satisfactorily completed the
requirement for the course and research work for the award of Master of Science (M.Sc) in
Agricultural Economics. The work embodied in this research is original and has not been
submitted in part or full for any other diploma or degree in this university or any university.
This research work has been approved by the Department of Agricultural Economics,
University of Nigeria, Nsukka.
___________________
Prof E.C. Okorji
(Supervisor)
___________________
Prof S.A.N.D. Chidebelu
(Head of Department)
__________________
External Examiner
DEDICATION
To God Almighty.
To my husband and parents.
;.
ACKNOWLEDGEMENT
My sincere gratitude and appreciation is to God Almighty for His strength and divine
favour upon my life. To my supervisor Prof E.C. Okorji, who despite his busy schedule,
worked tirelessly to see me through this project. Thank you sir.
I also want to express my gratitude to Prof S.A.N.D. Chidebelu (the Head of
Department), my lecturers, Dr A. Enete, Prof A.I. Achike, Dr N. Chukwuone , Prof E. Eboh,
Prof C.U. Okoye., Prof C. J. Arene, Prof R.N.Arua, Prof Nweze, Dr P. I. Opata, Dr E.
Amaechina, Dr B.C Okpukpara, Mr P.B. Njepume, Dr F.U.Agbo, Mrs Rose-Mary Arua, Mrs
Onyenekwe S.C. Mrs Chiemiela S. Mrs C.U.Ike, Mr K.P.Adeosun , Miss O.A. Eze, Miss
P.A. Nnaji, Dr. A.N Onyekuru,, Pst Ochommna, Miss Ifiorah C.M., Mr I. Ukwuaba Mr J.E.
Ihemeze , Miss T.G. Mbani and non academic staff of the department.
Also my sincere appreciation to my parents Late Elder and Mrs Bethel Amabebe for
their moral , financial and spiritual support, my dearly beloved husband Mr Imere Nwokah
for his love and support; always love you, Mr Uncle and family, Mr and Mrs Johnson
Amabebe, my Aunties and uncles for their moral and financial support. Also I want to
appreciate my siblings; George, Tarila and Oyein-ebi for their moral support. To HRH Major
and Mrs Graham P. Naingba and family for their financial and moral support, chief Abel
Ebifemowei , Mr and Mrs Emma Enukwu, also for their financial support. To Chief Douyi
Douglas Naingba for financial support. I also want to appreciate Pastor Eneyi Simeon and
family for their spiritual support.
I also want to thank my friends, Ebiere,Chidi, Yingi, Amaka(s), Marvelous, Blessing,
Rita, Preye, Samuel, Queeneth, Samson, Chioma, Uyoyo, Nike, Toro, Mercy Nimi, Robert
and to all my classmates in the 2012/2013 postgraduate class of Agricultural Economics,
University of Nigeria Nsukka.. To all those I didn’t mention, I have you in mind, God bless
you.
I also want to appreciate the families of Dr and Mrs P.E. Kainga and Prof and Mrs
F.N. Nnadi for moral support.
ABSTRACT
The study was designed to analyze the effects of agricultural technology on cassava
production by small holder farmers in Bayelsa state, Nigeria, The study area consists of three
agricultural zones. The three zones namely: Bayelsa East, Bayelsa west and Bayelsa central
were used for the study. A multistage random sampling technique was used to select 5 LGAs
(one was purposively selected from one LGA and the remaining four selected randomly from
the remaining two LGAs). Three communities were randomly selected from each the five
LGAs giving a total of 15 communities. Finally, in each community, eight respondents
(smallholder cassava farmers) were randomly selected making a sample size of 120
respondents. A structured questionnaire was administered to each of the selected respondents.
Data collected were analyzed using frequency distribution, percentages, and mean. Cassava
production was dominated by males, an active age group, more of married people, the study
area was characterized with an average level of education, a fairly large household size and
low farm income. The average farm size was low,(0.8 hectares). Farm inputs were mainly
supplied by the farmers themselves, types of technologies available were, improved cassava
stem, agro chemicals, fertilizer, extension services and irrigation. Improved cassava stem
were mostly used of all the technologies available. The level of agricultural technology use
was low. Agricultural technology had a positive effect on output for farmers that used it,
therefore the null hypothesis was rejected. The major constraints to the use of agricultural
technology were high cost of inputs, availability of inputs, lack of technical know-how, and
poverty among farmers.
TABLE OF CONTENTS
Title page i
Certification ii
Dedication iii
Acknowledgement iv
Abstract vi
Table of contents viii
List of tables x
List of figures xi
CHAPTER ONE: INTRODUCTION
1.1 Background of the study 1
1.2 Problem Statement 4
1.3 Objectives of the Study 6
1.4 Hypotheses 7
1.5 Justification of the study 7
1.6 Limitations of the study 8
CHAPTER TWO: LITERATURE REVIEW
2.1 Concept of technology and agricultural technology 9
2.2 Types of technologies used in agricultural production 12
2.2.1 Biotechnology 12
2.2.2 Water management/irrigation 13
2.2.3 Chemicals 13
2.2.4 Agricultural engineering 15
2.2.5 Agricultural extension 16
2.2.6 Farming system research 17
2.3 Effects of the use of agricultural technology 18
2.4 Constraints to the use of agricultural technologies 19
2.5 Cassava production in Nigeria 20
2.6 Application of agricultural technology for cassava production 22
2.7 Use of agricultural technologies for sustainable economic development 22
2.8 Theoretical framework 24
2.8.1 Concept of production 24
2.8.2 Production function 25
2.9 Analytical Framework 26
2.9.1 Production function analytical model 27
2.9.2 Multiple regression model 27
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 The study area 29
3.2 Sampling technique 29
3.3 Data collection 30
3.3.1 Validation of instrument 30
3.4 Data analysis 31
3.4.1 Model specification 31
3.4.2 Likert type rating scale 32
3.4.3 Test of hypothesis 32
CHAPTER FOUR: RESULTS AND DISCUSSION
4.1 Socio economic Characteristics of Respondents 33
4.1.1 Gender of Respondents 33
4.1.2 Age of Respondents 33
4.1.3 Marital Status of Respondents 34
4.1.4 Educational Level of Respondents 35
4.1.5 Household Size of Respondents 36
4.1.6 Farm Income of Respondents 37
4.1.7 Farming Experience of Respondents 38
4.1.8 Source of Labour of Respondents 39
4.1.9 Farm Size of Respondents 39
4.1.10 Acquisition of Farm Inputs by Respondents 40
4.2.0 Types of Technologies available in the study area 41
4.2.1 Types of Technology used in the study area 41
4.2.2 Means of Technology awareness 42
4.2.3 Agricultural Technology used by farmers in the study area 43
4.3.0 Level of Agric Technology usage 43
4.4 Effect of Agric Technology on Cassava Output 44
4.5 Constraints faced by Farmer on the use of Agricultural Technology 46
CHAPTER FIVE: SUMMARY CONCLUSION AND RECOMMENDATIONS
5.1 Summary 48
5.2 Conclusion 49
5.3 Recommendations 49
References 51
Appendix 58
LIST OF TABLES
Table
4.1.1 Percentage distribution of respondents according to gender 34
4.1.2 Percentage distribution of respondents according to age 34
4.1.3 Percentage distribution of respondents according to marital status 35
4.1.4 Percentage distribution of respondents according to educational level 36
4.1.5 Percentage distribution of respondents according to household size 37
4.1.6 Percentage distribution of respondents according to farm income 38
4.1.7 Percentage distribution of respondents according to farming experience 39
4.1.8 Percentage distribution of respondents according to source of labour 40
4.1.9 Percentage distribution of respondents according to farm size 40
4.1.10 Percentage distribution of respondents according to acquisition of farm inputs 41
4.2.0 Percentage distribution of respondents according to types of
technologies available in the study area 42
4.2.1 Percentage distribution of respondents according to means of
technology awareness 43
4.2.2 Percentage distribution of respondents according to agricultural
technology used by farmers in the study area 44
4.3.1 Percentage distribution of respondents according to level of agric
technology usage 45
4.4 Percentage distribution of respondents according to effect of agric
technology on cassava output 46
4.5 Percentage distribution of respondents according to constraints faced by farmers
on the use of agric technology 48
LIST OF FIGURES
Figure 2.1: Classification of agricultural technology 11
CHAPTER ONE
INTRODUCTION
1.1 Background Information
Agricultural technology is the knowledge applied by man to improve production or
marketing processes; it is seen in hybrid seeds, improved crop varieties, pesticides,
machinery, fertilizers etc. (Subba, Raghu, Neelakanta and Bhavani, 2004). Also Jeremy,
(2013) defined agricultural technology as the tools or machines that are used primarily or
entirely in order to support agricultural enterprise in modern agriculture. Agricultural
technology is thus a combination of all management practices for producing or storing crop
mixture, livestock etc. (Esther, 2004). The objective of technology is to provide more output
from a given bundle of production inputs.
Agricultural Technology is quite broad and general, this study will contextualize
technology from two classifications which are; hardware technology (embodied in the green
revolution model, which promotes hybridization, use of pesticides, insecticides, herbicides
etc., the use of farm inputs and equipment), and software technology (extension and farming
system research). Some of the technologies used for cassava production were reported by
Bucyana (2006), they are; biotechnology (production of zero-to-low cyanide cassava,
production of genetically improved cassava, mass production of disease-free, pest resistant
and high yielding cassava plants, through micro propagation), agricultural engineering
(machinery, equipment and tool design for land preparation and harvesting e.g. ploughs,
ridgers, cassava lifters, tuber harvester, screw press etc.), bio-intensive integrated pest
management, herbicides, fertilizers, water management (irrigation), post harvest technology,
training, research and extension on cassava with model villages etc.
Agricultural technology has been of immense contribution to countries such as Brazil,
Thailand and Columbia. Before the use of agricultural technology (between 1986 and 1998),
the Brazilian cassava yields averaged 13 metric tonnes (MT) per hectare, the planting of
improved, higher yielding, disease resistant, pest resistant and high starch content varieties of
cassava resulted in increased yields (Kupoluyi, 2005). Low out-put small holder farmers
averaged about 15 MT per hectare, with better lands yielding about 20 MT per hectare, using
mechanized technology yields average 45 MT per hectare, with only 2.2 million hectares
under cassava, Brazil produces about 24,000,000 MT per year, (Kupoluyi, 2005). Also in
Columbia, despite its agro-ecological challenges, diversity, various systems of cultivation and
utilization and other biological problems, yield averages of 12 MT per hectare were obtained;
Thailand is often cited as a tropical country that has successfully transformed cassava into an
industrial crop, this transformation was driven by a unique export opportunity. The Thailand
cassava sector accelerated during the late sixties, increasing during the seventies and the
eighties, with high feed import duties, the EU turned to Thailand for its cassava and soybean
meal, as a ratio of 80:20 is equivalent in energy and protein to grain feeds such as maize and
barley (Bokanga, 2001). Thus, Thailand cassava meal was exported to the European Union
(EU) countries. In the late 60s, Thailand shifted its focus to cassava pellets processing, the
processing into pellets reduces its volume by about 20-25%, thereby reducing transportation
costs, there are approximately 200 pelleting factories in Thailand, with an average total
capacity of 10 million tonnes per year. These entirely were achieved through the application
of agricultural technologies, (Plucknett, 1998).
Despite Nigeria’s similarities to both Brazil and Colombia in terms of location (low land
tropical latitudes, with similar climate, vegetation and ecology), having the same soil types
and topography with similar crops cultivated including roots, cassava and cereals,
classification as developing countries using international yardsticks, with cassava farming in
Nigeria only on smallholder farms, her average yield is less than 11 MT per hectare (FAO,
2004). The latter have developed their industrial cassava sectors, proving cassava can be
transformed from a staple food to a multi-use industrial raw material, (Kupoluyi, 2005). The
improved cassava variety was better than the local at farm level, farmers have been slow to
adopt them based on factors such as; unfamiliarity; most farmers have never had opportunity
to try them and therefore do not know whether they will like them or not, unavailability of
planting materials, their high moisture content, which leads to poor yields and risk averse.The
relatively unknown processing qualities (for garri and fufu) of the improved cassava varieties
compared with the unknown qualities of the local varieties, (World Bank, 2000). It was noted
by Amao and Awoyemi (2008), that improved cassava varieties express their greater yield
potential under both low and high inputs than the local cassava varieties.
In developing countries with low income, Nigeria inclusive, two-third or more of the
people live in rural areas and their main occupation is agriculture, more than 71% of the
population is engaged in agriculture while in the United States, Canada and West Germany,
3-4 percentages; agriculture is unproductive in the low income areas despite the population
engaged in it because it is carried on in an old fashion with obsolete method of production
(Jhingan, 2011). As we enter the twenty- first century, the pace of technology use continues
to accelerate, with great potential to improve the lives and livelihoods of residents in
developing and developed countries, and with profound implications for the global economy,
(Esther, 2004).
Bayelsa State is ranked 18th in the production of cassava in Nigeria with a mean yield
of 15.3 MT (International institute of tropical agriculture, IITA, 2009), cassava is produced
largely by small-scale farmers using rudimentary implements, the average land-holding is
less than two hectares. Most farmers had land and family labour as the essential inputs,
rotation and fallow systems are the traditional systems used by the farmers to maintain soil
fertility. However, population pressure has resulted in reduced fallow, continuous cropping
and reduced soil fertility, (The Federal Ministry of Agriculture and Natural Resources
(FMANR), 2012). Presently, cassava is primarily produced for food especially in the form of
garri, fufu, starch, tapioca’ and farina with little or no use in agribusiness sector as an
industrial material, (Knipscheer, et al, 2007). It is one of the major crops which the present
government is interested in developing and encouraging investment. The major two species
of cassava produced in the state are bitter cassava and sweet cassava. However, the state
Agricultural Development Programme (ADP) is encouraging farmers to plant improved
varieties which are also made available to them (Yenagoa Chamber of Commerce, 2012).
Cassava is a major contributor to development in Nigeria, there is increasing demand for
cassava due to the rapidly growing population, the crop can also be processed into several
secondary products of industrial market value such as chips, pellets, flour, adhesives, alcohol
and starch which are vital raw materials in the alcohol, textile and soft drinks industries
(World Bank, 2000). There is need to incorporate appropriate technologies in the production
of cassava especially in Bayelsa State, which made this study a timely response. This study
sought to examine the economic effects of agricultural technology on cassava production by
smallholder farmers in Bayelsa State.
1.2 Problem Statement
Agriculture is the bedrock of all economies of the world and it is not an exception in
Bayelsa. With over 70 per cent of the population in the rural area, and most of them
dependent on agriculture, it follows that the strategy for economic transformation must
address the barriers on production and funding, (Young, 2012). There are a number of natural
barriers towards the realization of the food security goals, one of which is land availability.
Bayelsa has a riverine setting, a lot of her communities are almost (and in some cases)
completely surrounded by water, (Angela, 2011). According to the Bayelsa Development
and Investment Corporation, (2012), about three-quarters of its total area lie under water
which makes available land for cassava production inadequate as it competes with other food
crops produced in the state such as plantain, rice, oil palm, vegetables, cocoyam, etc.
Therefore appropriate technological and management innovations should be incorporated to
improve productivity.
Also efforts to increase food production as to alleviate food shortages and high cost of
food items amongst the rural dwellers of Bayelsa state cannot be achieved with the traditional
crop rotation system of agriculture. The drastic changes in agricultural practices during the
past 100 years have come about in response to social needs, and we cannot turn the clock
back and still feed the current human population (Nweke, Okorji, Njoku, King,1992). Studies
carried out by Obisesan (2013), in southwest of Nigeria showed that to boost agricultural
production and productivity, farmers have to use agricultural technologies but they lack the
finance and as a result, the use of agricultural technologies is very low. Therefore, enhanced
provision of rural credit would accelerate agricultural production and productivity (Briquette,
1999).
However, the first step in assessing the usefulness of the technology to cassava
farmers in the study area is to determine the attributes responsible for choice of technology
used among the farmers as well as the major constraints militating against the effective use of
these technologies. Earlier studies by Dorp and Rulkens (1993), Agwu, (2002), Springer,
(2002) and Kimenju, (2005), showed that farmer’s decision to use a particular technology
was influenced by a number of reasons, some of which are market-driven, level of education,
or socio-culturally biased.
These and other features endowed it with a special capacity to bridge the gap in food
security, poverty alleviation and yet little is known about available technologies used in
production of cassava by smallholder farmers in Bayelsa state as well as factors that
influence the level of usage of these technologies.
Previous studies have dealt on the agricultural technology adoption (Aliou and
Ben,2012; Chukwuone, Agwu and Ozor, 2006), the role of agricultural technology in poverty
reduction among crop farmers ( Nnadi, Chikaire, Nnadi, Utazi, Echetama and Okafor 2012;
Datt, Jollifle and Sharma, 1998; De Janvry and Sadoulet. 2002). Little or nothing has been
done to analyse the economic effects of agricultural technology on the production of cassava
by smallholder farmers in Bayelsa State. Hence this study sought to examine the economic
effects of agricultural technologies on cassava production by smallholder farmers in Bayelsa
State.
1.3 Objectives of the Study
The broad objective of the study was to examine the effects of agricultural technology
on cassava production by smallholder farmers in Bayelsa State, Nigeria. The Specific
objectives were to:
i. describe the socio-economic characteristics of smallholder cassava farmers ;
ii.. identify the types of agricultural technologies available to small holder cassava
farmers;
iii. determine the level of usage of agricultural technologies in cassava production;
iv. estimate the effects of agricultural technology on cassava production;
v. identify the constraints faced by smallholder cassava farmers on the use of
agricultural technologies.
1.4 Hypothesis
The following null hypothesis will be tested:
i. Agricultural technologies have no significant effect on cassava production.
1.5 Justification of the Study
As a progress mechanism, there are more and more changes to agricultural
technologies. The technology that is available is regularly being altered so that it can be more
precise in its functions and can perform more complex functions. In order to design
appropriate policies that will bring about an efficient production of cassava in Nigeria, there
is need to carry out a study on the use of agricultural technologies for cassava production in
Nigeria. This study brought more information about the economic effects of agricultural
technology on cassava production by smallholder farmers in Bayelsa State, which is in line
with the policy to boost food production and internally generated revenue base of the Bayelsa
state. Improve productivity for agriculture is one of the most important areas in the world,
throughout the decades technology has played a major role in improving farming conditions.
Technologies have also provided new opportunities for farmers, without technologies,
farmers will still need to pick every cassava plant by hand and plough the ground without
machinery. If farmers in Bayelsa State would embrace technology, food production can be
more efficient and cost less labour.
As part of the International Fund for Agricultural Development (IFAD) global
strategy for cassava development, Nigeria has been selected to conduct a country case study
among other nations. The selection of Nigeria is largely based on the considerable level of
experience in the development, multiplication and processing of cassava into various food,
feed and raw material forms. These gains would need to be sustained, especially through a
diversification of usage of cassava for industrial purposes; hence this study would help in
formulating a future strategy for the realization of this important goal and also may be useful
for future project interventions and development strategy in the cassava subsector.
Also information provided by this study to the student and research bodies has made
this study not only a timely response, but a right step in a right direction. It will also be useful
to individuals and firms who may wish to engage in cassava production in Bayelsa State. In
addition, this study will enable government bodies identify problems faced by smallholder
cassava farmers on the use of agricultural technologies. More so, apart from providing useful
information on the effects of Agricultural technology on cassava production in the area, it
will also serve as a benchmark for further studies in this area.
1.6 Limitations of the Study
Data were not kept by farmers because they were not highly educated which made it
difficult to get information but efforts were made to get reliable data through interviews on
one- on-one administration of questionnaires to the respondents. Also accessibility of the
study area was another limitation experienced while collecting data; the study area is riverine
which made it accessible by water means of transportation but efforts were made by using
enumerators conversant with the area to get data and the responses were cross checked with
the production trend in the state.
CHAPTER TWO
REVIEW OF RELATED LITERATURE
Literature for this study will be reviewed under the following subheadings;
Concept of technology and Agricultural technology;
Types of technologies used in agricultural production;
Effects of the use of agricultural technology;
Constraints to the use of agricultural technologies;
Concept of production;
Cassava production in Nigeria;
Application of agricultural technology for cassava production;
Use of agricultural technologies for sustainable economic development;
Theoretical framework; and
Analytical framework;
2.1 Concept of Technology and Agricultural Technology
In general, technology means material artifacts — machines and other physical
devices and products. In a broader sense, it means a particular kind of knowledge about how
to produce desired and intended outcomes, not only “knowing about” but also “knowing how
to do” (Layton, 1974). In this view, technology is not only material artifacts, but also social
wisdom (Law and Bijiker, 1992). According to Mackenzie and Wacman (1985) in Esther,
(2004), technology is composed of material objects, and scientific knowledge and
methodological processes utilized to transform them for individual and social needs.
In agriculture, technology is the knowledge applied by man to improve production or
marketing processes. It is seen in hybrid seeds, improved crop varieties, pesticides,
machinery, fertilizers etc. The objective of technology is to provide more output from a given
bundle of production inputs. It is vital in the economizing process and is related to a specific
activity, it connotes a way of completing a particular task, (Subba et al, 2004). Also Esther
(2004), defined it as the way agriculture is done, it includes methods by which land is
cultivated and crops are harvested and also the way livestock is cared for. It includes the
seeds, fertilizers, pesticides, medicines and the fodder for livestock, tools and implements the
farmers use, and their source of power are also included. Moreso, Field and John (2007),
stated that agricultural technology is among the most revolutionary and impactful areas of
modern technology, driven by the fundamental need for food and for feeding an ever growing
population. It has opened an era in which powered machinery does the work formerly
performed by people and animals (such as oxen and horses), these machines have massively
increased farm output and dramatically changed the way people are employed and produce
food worldwide.
Agricultural Technology is quite broad and general. This study will contextualize
technology from two classifications:
i. Hardware technology (embodied in the green revolution model, which promotes
hybridization, use of pesticides, insecticides herbicides etc., the use of farm inputs
and equipments), and
ii. Software technology (extension and farming system research).
A similar classification was done by The Zimbabwe National situation analysis report
(ZNSAR), (2007), where they classified technology as hardware (tangible) and
software.(intangible)
AGRICULTURAL TECHNOLOGY
Tangible (Hardware) Intangible (Software)
Chemical mechanical Bio technology Extension Farming Systems Research
Herbicides Tractors Hybrid seeds
Pesticides Plows Gene manipulation
Fungicides Irrigators Micro propagation
Insecticides etc Threshers etc.
Figure 2.1: Classification of Agricultural Technology
Source: Adapted from ZNSAR, (2007)
Tangible (hardware) technology is something physical and can be felt with the hand,
like a treadle pump used for delivering water from source to the irrigated land. The tangible
technologies are chemicals (herbicides, pesticides, insecticides etc), mechanic (threshers
plows, tractors irrigators etc) and biotechnology (hybrid seeds, micro propagation, gene
manipulation etc) while intangible (software) technology on the other hand refers to the
approach or extension model used to impart the technology and skills to the farmer on the
use of the hardware technology (ZNSAR, 2007). The software technology is grouped into
extension and farming system research. Software technology refers to the approach or
extension model used to impart the knowledge and skills to the farmer on the use of hardware
technology. Both hardware and software technologies play a significant role in the food
production cycle among rural communities who are dependent on managing the environment
for their livelihood. The technologies are applied in production, harvesting, processing and
marketing of crop and livestock produce etc.(ZNSAR, 2007).
2.2 Types of Technologies used in Agriculture
According to Hurst (1991), agricultural machines have been designed for practically
every stage of the agricultural process. They include machines for tilling the soil, planting
seeds, irrigating the land, cultivating crops, protecting them from pests and weeds,
harvesting, threshing grain, livestock feeding, and sorting and packaging the products.
2.2.1. Biotechnology:
According to Ania (2000), biotechnology is the application of scientific techniques to
modify and improve plants, animals, and microorganisms to enhance their value. Agricultural
biotechnology is the area of biotechnology involving applications to agriculture. Agricultural
biotechnology has been practiced for a long time, as people have sought to improve
agriculturally important organisms by selection and breeding. An example of traditional
agricultural biotechnology is the development of disease-resistant wheat varieties by cross-
breeding different cassava types until the desired disease resistance was present in a resulting
new variety. The following varieties are recommended for their high yield and processing
quality: TMS 30572, NR 8082, NR8083, TMS 4(2) 1425, TMS 81/00110, TMS 92/0326. An
additional 10 varieties are in the process of being released (IITA 2009).
2.2.2 Water Management/Irrigation
Water management/irrigation is an important area in agricultural production; various
techniques have been developed for increasing water use efficiency. In scarcity region, the
practice that is gaining momentum is protective/supplemental irrigation (Subba et al, 2004).
Irrigation is an artificial application of water to the soil, usually to assist with the growth of
crops. In cassava production, it is mainly used in dry areas and in periods of rainfall
shortfalls, but also to protect plants against frost. By contrast, agriculture that relies only on
direct rainfall is referred to as rain-fed farming. Irrigation is often studied together with
drainage, which is the natural or artificial removal of surface and sub-surface water from a
given area. There are several types of irrigation and they include; surface irrigation, drip
irrigation, sprinkler irrigation, localized irrigation, irrigation sub-irrigation etc. (Frenken,
2005). The objective of irrigation is to optimize water use, thereby covering large are with
available water discharge for plant growth and increased productivity.
2.2.3. Chemicals
Agricultural production relies heavily on man-made chemicals used as fertilizers and
pesticides, and to regulate plant growth. The benefits of their use in terms of economic
returns and of improved human health and well-being have led to the rapid world-wide
adoption of this chemical technology. However, their use in advanced countries is often
regulated and monitored because of potential problems associated with their injudicious use.
Chemicals include;
Fertilizers: Plimmer (2007), defined fertilizers as compounds given to plants to promote
growth; they are usually applied either via the soil, for uptake by plant roots, or by foliar
feeding, for uptake through leaves. Fertilizers can be organic (composed of organic matter),
or inorganic (made of simple, inorganic chemicals or minerals). They can be naturally
occurring compounds such as peat or mineral deposits, or manufactured through natural
processes (such as composting) or chemical processes (such as the Haber process). Havlin, et
al (2004), stated that fertilizers typically provide in varying proportions the three major plant
nutrients (nitrogen, phosphorus and potassium) the secondary plant nutrients (calcium,
sulphur, magnesium), and sometimes trace elements (or micronutrients) with a role in plant
nutrition: iron, zinc, boron etc. The growth of the world's population to its current figure has
only been possible through intensification of agriculture associated with the use of fertilizers.
IITA (2009), recommended the following fertilizers and their rate/ha;
•NPK 15:15:15 – 12bags (50kg per/bag)
•NPK 20:10:10 – 9bags (50kg per/bag)
• NPK 12:12:17 – 15 bags (50 kg per/bag)
Apply fertilizer at 8 weeks after planting. Apply fertilizer in a ring, 6 cm wide and 10
cm from the plant or broadcast with care around the plant, making sure the fertilizer does not
touch the stem or leaves.
Pesticides: United States. Environmental Protection Agency (EPA), (2007), defines a
pesticide as "any substance or mixture of substances intended for preventing, destroying,
repelling, or lessening the damage of any pest". A pesticide may be a chemical substance,
biological agent (such as a virus or bacteria), antimicrobial, disinfectant or device used
against pests including insects, plant pathogens, weeds, mollusks, birds, mammals, fish,
nematodes (roundworms) and microbes that compete with humans for food, destroy property,
spread or are a vector for disease or are a nuisance. Many pesticides are poisonous to humans.
According to Greene and Richard (2005), there are several types of pesticides and they
include; Bactericides for the control of bacteria, fungicides for the control of fungi and
oomycetes, herbicides for the control of weeds, insecticides for the control of insects- these
can be Ovicides, Larvicides or Adulticides, Miticides for the control of mites, Molluscicides
for the control of slugs and snail nematicides for the control of nematodes, rodenticides for
the control of rodents, virucides for the control of viruses. Cassava is affected by the cassava
mosaic and cassava leave blight, the use of pesticides have shown to control these diseases
that affect it.
2.2.4 Agricultural Engineering
According to Subba et al (2004), agricultural engineering deals with mechanization
through efficient use of inputs to increase farm productivity, conserving natural resources,
reduce crop losses; improve quality of agro produce, etc. Mechanization is one of the
measures of modernization in agriculture. Yeoshua, (2005), stated that agricultural machines
have been designed for practically every stage of the agricultural process, they include
machines for tilling the soil, planting seeds, irrigating the land, cultivating crops, protecting
them from pests and weeds, harvesting, threshing grain, livestock feeding, and sorting and
packaging the products. People who are trained to design agricultural machinery, equipment,
and structures are known as agricultural engineers. Some of the areas agricultural engineering
can be applied and examples of such machines used according to Field and John (2007)
include,
Traction and Power: they include tractors which may be either crawler tractors or
caterpillar tractors etc.
Soil Cultivation: they are plows, harrows, cultivators, spading machines, tillers,
walking tractors subsoilers etc.
Planting: they include broadcast seeder (broadcast spreader or fertilizer spreader),
plastic mulch layer, seed drill, transplanter,etc.
Fertilizing and pest control: fertilizer spreader, manure spreader, sprayers.
Irrigation: center pivot Irrigation
Harvesting /post- harvest: harvesters ( bean harvester, combine harvester, corn
harvester, forage harvester, etc ). Conveyor belt, digger, sickle, swather etc
2.2.5 Agricultural Extension
Strengthening of national agricultural support system has been advocated as a strategy
for increasing agricultural production in Sub-Saharan Africa by governments in the region
and by international development agencies (World Bank, 1983, Bindlish and Robert, 1997).
The T &V system (training and visit) of agricultural extension has been central to this
strategy. The World Bank-supported agricultural extension programs, based on the T&V
system have been implemented in some thirty Sub-Saharan countries or in about three-fifths
of African countries. A substantial amount of resources have been committed to this system,
both by national governments and international development agencies (Bindlish and Robert,
1993). Studies carried out by Robert and Germano (1998), shows that productivity gains from
agricultural extension are highest at the top end of the distribution of yield residuals,
suggesting that agricultural extension may be enhancing unobserved productive attributes of
farmers such as managerial abilities. Extension workers focus on imparting key messages to
farmers on each visit, with the complexity of these messages being increased in subsequent
visits. Initial messages aim at improving basic production techniques, with attention being
focused on land preparation, the timeliness of operations, crop spacing, plant population
sizes, the use of better seed varieties and on weeding. After the simple messages, attention
shifts to more complex messages such as those relating to fertilizer use and pest control
measures. The primary duties of the frontline extension agents under the T & V system is to
transfer agricultural information to farmers and to report farmers’ problems to higher levels
of the system, especially to supervisors and the subject matter specialists. Access to extension
services afford the farmers the opportunity to be better informed about production techniques
as well acquire basic training and skills on how best to allocate resources to achieve higher
productivity.
2.2.6 Farming Systems Research (FSR)
Before one can thoroughly explain farming system research, we ought to know what a
farming system is. Farmers typically view their farms, whether small subsistence units or
large corporations, as systems in their own right. Their resources normally include different
types of land, various water sources and access to common property resources – including
ponds, grazing areas and forest. To these basic natural resources may be added climate and
biodiversity, as well as human, social and financial capital. Each individual farm has its own
specific characteristics arising from variations in resource endowments and family
circumstances. The household, its resources, and the resource flows and interactions at this
individual farm level are together referred to as a farm system (Dillon, Plucknett, and
Vallaeys, (1978), Shaner, Philipp, and Schmehl, (1982).) Farming system research is
therefore a system approach that can incorporate all types of inquiry, as considered
appropriate by participants. It is participatory and involves cycles of observation, diagnosis,
planning action and evaluation (Petheram and Clark, 1998). The goal of FSR is to improve
the benefits of farm families and/or communities, through improving the performance of their
farming system.( McCowen, 1991).
2.3 Effects of the use of agricultural technology
Agricultural technology has been seen to have both negative and positive effects on
agricultural production. According to Anikpo, Mohammed, Ezegbe, Salau, Okunamiri,
(2008), technology has improved food production and preservative methods, also it enables
farmers to cultivate surplus food and preserve enough against times of scarcity. It has also
improved agricultural production through the provision of farm equipment such as tractors,
harvesters and chemicals like herbicides ad insecticides which help to increase crop yield and
make mass production possible.
However as technology advances, it is important that scientists and regulatory agencies
assess the impacts of both new and existing technologies for farmers and consumer safety and
for any environmental effects on plants, animals and water systems. Research carried out by
Land grant college and University in the Unites States of America between the years 2000-
2003 stated that some areas of risk-assessment considered with our present biotechnology
crops include the potential for genes moving from genetically engineered crops into wild
plants; pests eventually developing resistance to pest-resistant crops; introducing allergy-
causing compounds or changing the nutritional composition in foods. These are the same
types of concerns that should be evaluated with traditional methods of producing our food
and fiber.
Also the availability of nutrient responsive high yielding varieties of crops led to
intensive nutrient application and improved farm management to derive full benefits from
such varieties. The practices of integrated plant nutrient system and also integrated pest
management system are an outcome of the apprehension that the application of large doses of
fertilizers, pesticides, fungicides etc would lead to deterioration of soil health and pollution
hazards. The consumption of nutrients which is about 16.5 million tones realized from
40million tones of nitrogenous, phosphatic and potassic fertilizer is also causing a serious
strain on foreign exchange in the Indian foreign exchange reserves. Hence it calls for
exploration of supplementary and indigenous renewable form of nutrient sources. ( Subba et
al, 2004).
2.4 Constraints to the use of agricultural technologies
Several factors have been shown as constraints to the use of agricultural technology
for production by small scale farmers. Studies carried out by Chukwuone, Agwu and Ozor
(2006) noted that some of the constraints to the use of agricultural technologies for efficient
production were;
1. high cost of agricultural inputs and services.
2. high risk of uncertainty in agriculture.
3. non existence/inadequate farmers co-operative organization.
4. lack of political consensus to commitment and policies by government.
5. poor government commitment to implementation of policies in agriculture.
6. general reluctance on part of the farmers to pay for services.
7. poor economic status of farmers (poverty).
8. lack of ready market to sell increased output as a result of improved extension
services.
9. high level of illiteracy among farmers etc.
A similar result was ascertained by Akinnagbe (2010), where he noted that some of the
constraints to the use of technology for agricultural production were Lack of finance, scarcity
of planting materials, difficulty in obtaining credit facilities, lack of technical knowledge in
the use of improved technology, high cost of improved varieties, high interest rate on loan,
unavailability of agro-chemicals and other equipment, high cost of agro-chemicals.
Farm size is another constraint to the use of agricultural technology. According to
Anyaegbunam, Nto, Okoye and Madu (2011), positive polices aimed at land reforms towards
redistribution of land to make more land are available to peasant and landless farmers in
order to increase productivity and efficiency. Also the use of chemicals has been shown to
cause health and environmental hazards , such as, soil population, water pollution,
radioactive contamination soil contamination etc. (Hond and Frank, 2003).
2.5 Cassava Production in Nigeria
Cassava (Manihot esculenta) is a perennial root crop that grows in non-ideal
conditions and represents a major stable crop in Africa, especially in Nigeria. In the early
years of Nigeria’s independence, agriculture accounted for nearly 60 percent of Gross
Domestic Product (GDP) and 80 percent of export earnings (Shaib, Aliyu, and Bakshi, 1997).
Today agriculture accounts for a third of GDP and less than one percent of export earnings,
oil accounting for the rest (Federal Office of Statistics, 2001).
Nigeria is the largest producer of cassava in the world. Its production is currently put
at about 34 million metric tonnes a year (FAO, 2004). Total area harvested of the crop in
2001 was 3.125 million ha with an average yield of 10.83 tonnes per ha. According to Ezike,
Nwibo and Odoh, (2011), cassava production in Nigeria accounts for 19% of world output
and 34% of African output. Improved cassava varieties became available in Nigeria from
mid- 1970’s and started in 1986 (IITA, 1994; NRCRI, 2006). ). It performed so well in the
country that the nation became the largest producer having overtaken Brazil and Thailand
(FAO, 2004). Presently, cassava is primarily produced for food especially in the form of gari,
lafun fufu,tapioca, abacha with little or no use in the agribusiness sector as an industrial raw
material. Also, cassava is gradually being transformed from a famine-reserve commodity and
rural food staple to a cash crop for urban consumption these products include chips, pellets,
flour, adhesives, alcohol, and starch, which are vital raw materials in the livestock, feed,
alcohol/ethanol, textile, confectionery, wood, food and soft drinks industries. They are also
tradable in the international market.
In 2002, the President of Nigeria announced an initiative to use cassava as a foreign
revenue earner of five billion naira annually three years hence. To achieve this, there is need
to develop the domestic market, diversify the use of cassava in industries, curtail the threat of
the virulent form of the cassava mosaic virus and entrench national policies that will leverage
cassava development in the country (Bamikole, 2002). Unfortunately, no supply chain
structures exist for the commercialization of secondary cassava products as primary source of
raw materials for agro industries (Ezedinma, Nkang and Simon, 2006). The production of
cassava is concentrated in the hands of numerous smallholder farmers located primarily in the
south and central regions of Nigeria. At the farm level, production costs for cassava are high
relative to other countries. Production is not oriented towards commercialization but instead
farmers produce and process cassava as a subsistence crop (Dixon et al, (2002). A significant
population of cassava growers in Nigeria has made the transition from traditional production
systems to the use of high yielding varieties and mechanization of processing activities
(Nweke, Dunstan and Lynam (2002). For the cassava transformation to advance to the next
stage of livestock feed and industrial raw material, labour-saving production, harvesting and
processing technologies are needed to reduce costs, improve productivity and make cassava
more competitive.
The current status and potential demand for cassava and its secondary products as
industrial raw material in Nigeria is neither unknown nor documented.
2.6 Application of Agricultural Technology for Cassava Production
According to Project Coordinator of Support for Agricultural Research and Development of
Strategic Crops ( SARD-SC) Chrysantus Akem from the International Institute of Tropical
Agriculture (IITA),” narrowing the yield gap in cassava production is key for African
farmers, and it will help them to compete globally and to feed themselves,” IITA scientists
have played a leading role in developing improved cassava varieties which are disease- and
pest-resistant, low in cyanide content, drought-resistant, early maturing, and high yielding.
Disease-resistant varieties give sustainable yields of about 50% more than local varieties.
Distribution of CMD-resistant varieties in response to the CMD outbreak resulted in
production levels recovering to pre-epidemic levels in less than five years. Improved cassava
varieties are now used in most cassava-growing Nigeria. (IITA, 2009)
2.7 Use of Technology for Sustainable Development
The 1990 Farm Bill in the United States of America (Title XVI, Subtitle A, Sec.
1603) defined Sustainable Agriculture as "an integrated system of plant and animal
production practices having a site-specific application that will, over the long term: satisfy
human food and fiber needs; enhance environmental quality and the natural resource base
upon which the agriculture economy depends; make the most use of nonrenewable resources
and on-farm resources, and integrate, where appropriate, natural biological cycles and
controls; sustain the economic viability of farm operations; and enhance the quality of life for
farmers and ranchers, and society as a whole “
Sustainable Agriculture is a way of farming that can be carried out for generations to
come. This long-term approach to agriculture combines efficient production with the wise
stewardship of the earth's resources. Chet (1998) stated, that it is hoped that, over time,
sustainable agriculture would; meet human needs with a safe, high-quality, and affordable
supply of food and fiber, protect the natural resource base and prevent the degradation of air,
soil and water quality, use nonrenewable resources efficiently, use natural biological cycles
and controls, assure the economic survival of farming and the well-being of farmers, their
families and communities. Also technology in all areas has improved agricultural production,
thus its sustainability. Today’s Agriculture is using best management practices (BMP’s), by
targeting many of its applications, not broadcasting as was done in the past. New disease
resistant hybrids, biological pest control, reduced pesticide use, cultural practices that reduce
the incidence of pests and diseases, and better placement and reduced amounts of fertilizers
are all being employed. Insect specific chemicals and biological insect controls are now being
utilized, instead of broad-spectrum a pesticide, that actually reduces the number of sprays
needed along with costs. Micro-sprinkler water is now being applied directly to the roots, not
overhead or flooding of the entire block as was done in the past. Agriculture manages land
for both agriculture and wildlife.
By using the best hybrids, specialized applications of chemical pesticides and
fertilizers, maximum economical production per acre can be realized. Without these inputs,
more acreage would need to be cleared and farmed in the future to be able to provide the
world’s growing population with safe, high-quality, and affordable supply of food and fiber.
The most environmentally friendly solution is to upgrade all of the existing acreage, not clear
more land to simply accommodate a shift due to economic reasons. If regulations and other
inputs keep increasing agriculture’s costs that can’t be passed on to the consumer in a market
driven economy, Nigerian Agriculture won’t survive. Nigerian Agriculture needs
sustainability so that she can rely on a safe domestic supply of food rather than relying on
foreign imports which could affect our security if cut off and not be able to guarantee its
safety.
2.8 Theoretical Framework
This section reviews the theories that are relevant to this study. The theoretical
framework of this study hinges on the theory of production.
2.8.1 Concept of Production
Production theory refers to the principles in making production decision (Oji, 2002).
Production decisions include the decision to acquire resources, organize production and
distribute the products of the production activity and in general to manage the reserves of
production resources (Kamajou, (1991). According to Adewusi (2006) production is the ratio
of outputs to inputs used to produce goods and services.The use of resources to make goods
or services which have value is known as production, the production process is one whereby
some goods and services called inputs are transformed into other goods and services called
output. (Olayide and Heady, 1982)
The term input and output only have meaning in connection with a particular
production process. In agriculture, the physical inputs with which we deal with are usually
Land, Labour, Capital and Management. These resources can be organized into a farm-firm
or a producing unit, whose ultimate objective may be profit maximization, output
maximization, cost minimization or a combination of all these motives of enterprises.
(Olayide and Heady, 1982).
2.8.2 Production Function
Production function is the technical relationship between resources (factors) inputs
and production commodity (output) (Arene and Okpukpara, 2006). The relationship shows
that output depends on the quality and quantity of the inputs used in the production. Choosing
any particular production process among the technically efficient process at any time is a
decision which also depend on the prices and not a technical decision alone (Nweze, 2002).
It is a technical and mathematical relationship describing the manner and extent to
which a particular product depends upon the quantities of inputs or service inputs, used at a
given level of technology and at a given period of time, it portrays an input-output
relationship. Mathematically, production function is continuous and differentiates and this
property of differentiability enables the user to estimate the rate of returns (Olayide and
Heady, 1982). The purpose of the production function is to identify and measure which
variable inputs explains variation in output. For any production function, the correct
functional form can be determined by fitting various feasible functional forms to obtain the
best fitting various feasible functional forms to obtain the best fit which is normally selected
on the basic of economic, statistical and econometric soundness (Nwosu, 2005). The simplest
mathematical form of the production function can be stated as Q=f(x),
where ;
Q=output,
x=input and
f=function of indication of casual relationship between Q and X . Dillon, (1977). Nwosu
(2005), explained that in practice, the most commonly used form include linear, quadratic and
Cob Douglas forms, but various functional forms can be used to describe production
relationships.
Over the years, farmers have through the application of technology evolved methods
of increasing agricultural productivity. Some of these methods include use of improved crops
and livestock varieties, fertilizers, better cultural practices, provision of land and more
efficient use of water, (Onoja, 2004).The productive resources which are grouped into
human, material and natural resources are land, labour capital and management. These
resources are combined in various ways to produce outputs, therefore increase or decrease in
an output results from the level and/ method in which they are combined (Olayide and Heady,
1982).
Production can be enhanced by increase in quality of inputs, changes in techniques,
substitution of capital for labour, skilled labour, better organization of production and new
ideas even when there are no change in the quality, or proportion of factors (Lipsey, 1983).
2.9. Analytical Frame work
2.9.1 Production Function Analytical Model
This model is used for analyzing the technological or physical relationship between
input and output in any production processes. Adegeye and Dittoh (1985) explain production
function as the relationship between inputs and output. They further opined that production
function could be studied under the following main headings such as input-output
relationship, input-input relationship and output-output relationship. The production function
shows the rate at which the production inputs or resources are transformed into output(s) or
product(s) assuming that the mode under which the production process is organized is known.
In other words, production represents the technical relationship connecting factor inputs with
output and can be represented arithmetically by means of tables, graphically by means of
two-dimensional graphs, or algebraically by means of equation (Arene, 2008; Oji, 2002).
Essentially, therefore, the production function indicates a quantitative terms the
production possibilities available to the producer given factor inputs at his disposal. By
estimating the marginal products and production elasticities, the production model also
provides information on the effects of varying levels of inputs on total output (Olagoke,
1990).
2.9.2 Multiple Regression Model
Multiple regressions are used to measure the relationship between variable and their
factors that affects it. Okeke, (1988) used multiple regression models to establish the
relationship between transport cost as dependent variable, distance travelled and quantity
transported as explanatory variables. He also used quantity stored, period of storage, cost of
labour and chemicals to predict storage cost. Oguoma, (2002) used multiple regression
analysis to establish and test whether there is a significant relationship between farmers
output and amount of loan granted. Used along with the volume of loan obtained by farmers
as explanatory variables are farming experiences, household size, sex of farmers and farm
size. Baba and Adeleke (2006) used multiple regression analysis to determine the factors
affecting snail farming profitability. The model used was specific as:
Y = ƒ(X1,X2,X3,X4,X5,…………..ei) …(2.1)
Where: Y = Quantity of snails produced (kg); X1 = Labour (in days); X2 = fixed capital; X3 =
Land size (ha); X4 = input cost/expenditure (N); X5 = years of experience (years); ei = error
term
The relationship between the endogenous and each of the exogenous variables were
examined using double logarithmic production function. Also, Adewuyi, Phillip, Ayinde and
Akerele (2010) used multiple regression in their work “Analysis of Profitability of Fish
Farming in Ogun State, Nigeria”, stating the following models:
Y= ƒ(X1, X2, X3, X4, X5, X6, X7, e) …(2.2)
Where Y is the value of fish output in naira (N), X1 represents the pond size measured in
square metres (m2), X2 is the quantity of labour used in fish production in man/days, X3 is the
cost of feeds measured in naira (N), X4 represents the cost of fertilizer in naira (N), X5 stands
for the cost of lime in naira (N), X6 represents the cost of fixed inputs in naira (N), X7 is the
cost of fingerlings measured in naira (N), e= Error term.
Although the explicit specification of the production function can take several
mathematical forms including the linear, semi-log, double log, inverse, quadratic and cubic
functional forms, Mbanasor and Obioha (2003) noted that the three most commonly used
production functional forms include the linear functional form, the Cobb-Douglas (or double
log) form and the quadratic functional form. To choose the appropriate functional form for
use in social and economic research, the various forms are the form of ‘best fit’ is selected
based on economic, statistical and econometric criteria (Nkereuwem, Daniel and Idiong,
2000).
.
CHAPTER THREE
RESEARCH METHODOLOGY
3.1 The Study Area
The Study Area is Bayelsa State. Bayelsa State is a state in southern Nigeria in the
heart of the Niger Delta. Bayelsa State lies between latitude 040 15’N and 05o 23’S of the
equator, along longitude 06o 45’E and 05o 22’W of the equator. The state has a total land area
of 9,415.8km2. About three-quarters of its total area lie under water. (Bayelsa Development
and Investment Corporation, 2012). .
Bayelsa State is on the coast and bounded by Delta state on the North and Rivers state
on the east and the Atlantic Ocean on the west and southern part. The state has a population
of 1,704,515 (NPC, 2006). Bayelsa is a riverine area, a lot of her communities are almost
(and in some cases) completely surrounded by water, hence making these communities
inaccessible by road. The mean monthly temperature ranges from 260C to 310C. (Bayelsa
Development and Investment Corporation, 2012). .
The primary occupation of the people is farming, fishing, petty trading as well as
forestry activities such as hunting and timbering (lumbering) gathering of wilds and raffia
palm tapping. The languages spoken are Izon, Nembe, Ogbia and Epie-Atisa. However, like
the rest of Nigeria, English is the official language, Bayelsa State has eight (8) local
Government Areas (Alagoa, 1999). The state also has an Agricultural Development
Programme (ADP).
3.2 Sampling Technique
A multistage sampling technique was used to select the respondents for the study.
The respondents were cassava farmers with small holdings. Bayelsa state consists of three
agricultural zones. These are the, Bayelsa East (with 3 LGAs: Ogbia, Brass and Nembe),
Bayelsa west (with two LGAs: Ekeremor and Sagbama) and the Bayelsa central (with three
LGAs: Southern Ijaw, Kolokuma/Opokuma and Yenagoa). The three zones were used for the
study.
Firstly from Bayelsa East one LGA (Ogbia) was purposively selected because the
other two LGAs (Nembe and Brass) do not produce cassava. Two LGAs were selected
randomly from Bayelsa central and the two LGAs in the Bayelsa west zone making a total of
five LGAs. Secondly three communities were randomly selected from each LGA to give a
total of fifteen communities. Finally, in each community eight respondents (smallholder
cassava farmers) were randomly selected from each of the fifteen communities with the help
of extension agents in the area and the farmers union in each of the communities, making a
total of 120 respondents. This was the sample size for this study.
3.3 Data Collection
Data for this study were obtained from primary source. Data were collected using a
set of structured questionnaire. The questionnaire were administered to respondents eliciting
information on their socio-economic characteristics, types of agricultural technologies
available, level of usage, constraints to the use of agricultural technology.
3.3.1 Validation of Instrument
To ascertain the validity of the instruments, the initial drafts were given to three
experts in the department. The experts requested to review and criticize the various items on
the instruments, in terms of relevance, clarity, appropriateness of language and response
patterns as they relate to the study. Their criticisms, suggestions and modifications were
incorporated into the relevant items to give the instruments their present structure and
content.
3.4 Data Analysis
Objectives (i), (ii) and (v) were realized using descriptive statistics such as mean and
percentages,. The descriptive statistical tool (iv) was realized using multiple regression
models.
3.4.1 Model Specification
Production function Analytical Model
The production function analytical model was used to realize objective (v), which is
to examine the influence of socio-economic characteristics on cassava production and the
effect of agricultural technology on cassava production utilizing a multiple regression model
to achieve this; which has been elaborately explained (section 2.9.2)
Multiple Regression Model
The implicit form of the regression model used is specified as follows:
Y = f(X1, X2, X3, X4, X5, X6, X7, X8, X9, e) ............ (3.1)
The model is specified in its explicit form as thus;
Y = b0 + b1X1 + b2X2 + b3X3 + b4X4 + b5X5 + b6X6 + b7X7 + b8X8 + U ….(3.2)
This was used to achieve objective (iv).
Yi = quantity of cassava (tonnes/hectare)
X1 = improved cassava stem (Naira)
X2 = hired labour (Naira)
X3 = family labour (mandays)
X4 = fertilizer cost (Naira)
X5= Chemical cost (Naira)
X6== Irrigation (Naira)
X7 = Extension awareness/application of services; awareness=1, otherwise=0
U = Error term
3.4.2 Hypothesis Testing
Hypothesis was tested using t-test embedded in the multiple regression model for
objective (iv). The model is specified below;
t = 𝑋 ̅- µ
S.D/√𝑛 …………..(3.3)
Where ,
t= t-test
x = sample mean
µ= population mean
S.D = Standard Deviation
√𝑛 = root of the sample size
CHAPTER FOUR
RESULTS AND DISCUSSION
4.1 Socio-economic Characteristics of Respondents
The socioeconomic characteristics considered included; gender, age, marital status,
educational level, household size, annual farm income, farming experience, source of labour
and farm size.
4.1.1 Gender of Respondents
The Percentage distribution of respondents according to gender is shown in Table 4.1.
Table 4.1: Percentage distribution of respondents according to gender (n=120)
Gender Frequency Percentage (%)
Male 74 61.7
Female 46 38.3
Total 120 100
Source: Field Survey, 2014.
Table 4.1 shows that 61.7% of the respondents were males while the remaining 38.3%
were females. This goes to show that the domination of the male gender in cassava farming
was due to the nature of the job which is mostly strenuous for their female counterpart.
4.1.2 Age of Respondents
The Percentage distribution of respondents according to age is shown in table 4.2.
Table 4.2: Percentage distribution of respondents according to age (n=120)
Age Frequency Percentage(%) Mean
20- 30
12
10.00
31-40 29 24.20
41-50 60 50.00
50-60 12 10.00
60-70
Total
7
120
5.80
100.00 47
Source: Field Survey, 2014.
Table 4.2 shows that 10% of the respondents indicated their age between 20-30 years,
another 24.2% and 50% indicated their ages between 31-40 years and 41-50 years
respectively. Only 10.0% and 5.8% indicated their ages between 50-60 years and 60-70
years respectively. An average of 47 years approximately was recorded. This is an indication
that cassava farming is dominated by young people who are active and within the productive
age group. This finding is similar to that of Nweke et al, (2002) who reported that this age
group constitutes the major productive work force since they are young.
4.1.3 Marital Status of Respondents
The Percentage distribution of respondents according to marital status is shown in
table 4.3.
Table 4.3: Percentage distribution of respondents according to marital status (n=120)
Gender Frequency Percentage (%)
Married 84 70
Single 36 30
Total 120 100
Source: Field Survey, 2014.
Table 4.3 shows that 70% of cassava farmers were married while 30% were single.
This could be attributed to the western culture and tradition, where people are encouraged to
marry at an early stage in life.
4.1.4 Educational Level of Respondents
The Percentage distribution of respondents according to educational level is shown in
table 4.4.
Table 4.4: Percentage distribution of respondents according to educational level (n=120)
Educational level Frequency Percentage (%)
No formal education 8 6.7
Adult education 10 8.3
Primary education 33 35.8
Secondary education 66 55
Tertiary institution 3 2.5
Total 120 100
Source: Field Survey, 2014.
Table 4.4 shows that 6.7% of the respondents had no formal education, 8.3% passed
through adult education, another 35.8% and 55% had primary and secondary education
respectively and 2.5% tertiary education. This trend is in line with an earlier study by Kainga
and Kingdom (2012) and could be attributed to poor access to schools due to proximity and
transportation problems coupled with the high rate of poverty to meet basic requirements of
schooling such as school fees and learning materials. However, a relative literate class could
be seen for their easy adoption and use of improved farming methods which is in line with
Alabi and Aruna, (2006) who found Education to be a vital component in technology
adoption in agriculture. The present internet age calls for a step-up in the educational
background of the people.
4.1.5 Household Size of Respondents
The percentage distribution of respondents according to household sizer is shown in
table 4.5.
Table 4.5: Percentage distribution of respondents according to household size (n=120)
Household size Frequency Percentage (%) Mean ( x )
1- 3 8 6.7
4-6 24 20
7-9 67 55.8
10-12 21 17.5
Total 120 100 9
Source: Field Survey, 2014.
About 6.7% of respondents had a household size of 1- 3 persons, 20% had a
household size of 4-6 persons while 55.8% and 17.5% had a household size of 7-9 and 10-12
persons respectively, an average of nine persons was recorded. This implies a large
household. The large household is believed to constitute an important labour source for them
but there is still need to advocate for family planning in the area because this may have
serious implication on the standard of living of the people in the study area in the face of
economic meltdown. Also on the contrary, large household size may mean an additional
responsibility on the household heads (Adebayo and Onu, 1999).
4.1.6 Annual Farm income of Respondents
The Percentage distribution of respondents according to annual income is shown in
table 4.6.
Table 4.6: Percentage distribution of respondents according to annual farm income (n=120)
Annual farm income (N) Frequency Percentage (%) Mean ( x )
1000-50,000 46 38.8
50,001-100,000 43 35.8
100,001-150,000 21 17.5
150,001 –200,000 9 7.5
Total 120 100 71,650.30
Source: Field Survey, 2014.
Table 4.6 shows that a greater percentage (46%) of the respondents had an annual
farm income 1000 - N50,000, 43% and 21% had an annual farm income of N50,001-
N100,000 and N100,001- N150,000 respectively. An average of N71,650.30 was recorded as
annual income, thus income per capita of household given the 9 persons recorded is far too
poor and indeed an ugly situation when compared to the world standard of living. This is as a
result of low usage of agricultural technologies.
4.1.7 Farming Experience of Respondents
The Percentage distribution of respondents according to farming experience is shown
in table 4.7.
Table 4.7: Percentage distribution of respondents according to farming
experience (n=120)
Farming experience Frequency Percentage (%) Mean ( x )
10- 20 36 30.00
21-30 50 41.7
31-40 21 17.54
41- 50 13 10.80
Total 120 100.00 26
Source: Field Survey, 2014.
Respondents who had 10-20 years of experience in cassava production were 30%,
those with 21-30 years and 31-40 years were represented by 41.7% and 17.5% respectively
while 10.80% 40-50 years. The result is in line with Tashikalma, (1998) who reported that
farmers with more years of experience in terms of farm operations, are better compared to
farmers with few years of experience The result shows that farmers in the study area have
acquired enough experience in cassava production; therefore, adoption of new agricultural
technologies will pose no problem. Kwaghe, (2006) reported that farmers with many years of
experience are more willing to change towards adopting current recommended technologies.
4.1.8 Source of Labour of respondents
The percentage distribution of respondents according to source of labour is shown in table
4.8.
Table 4.8: Percentage distribution of respondents according to source of labour (n=120)
Source of labour Frequency Percentage (%)
Family 87 72.7
Hired 7 5.8
Both 26 21.7
Total 120 100
Source: Field Survey, 2014.
A greater percentage (72.7%) of the respondents engaged family labour for
production while 5.8% engaged hired labour and 21.7 % engaged both ( family and hired
labour).. The study showed that family labour is a naturally characteristics of the peasant
nature of Nigerian farmers. This is in line with Adegeye and Dittoh, (1985) who noted that
family labour is the most important component of labour in smallholder farmer’s production
in Nigeria and indeed African countries.
4.1.9 Farm Size of Respondents
The Percentage distribution of respondents according to farm size is shown in table
4.9.
Table 4.9: Percentage distribution of respondents according to farm size (n=120)
Farm size (hectares) Frequency Percentage (%) Mean( x )
0.1-1 84 70
1.1-1.5 29 24.2
1.6- 2 7 5.8
Total 120 100 0.8
Source: Field Survey, 2014.
From the table above a greater percentage (84%) of the respondents have a farm size
of 0.1- 1 hectare while 29% had a farm size of about 1.1-1.5 hectares and only 7% had a
farm size of 1.5- 2hectares. This shows that more of the respondents are involved in small
scale farming due to the extent of the land.
4.1.10 Acquisition of Farm Inputs of Respondents
The Percentage distribution of respondents according to acquisition of farm inputs is
shown in table 4.10.
Table 4.10: Percentage distribution of respondents according to acquisition of farm inputs
(n=120)
Farm size Frequency* Percentage (%)
Self 75 62.5
Government 35 29.2
Agro dealers 42 35
Total 150*
* Multiple responses were obtained
Source: Field Survey, 2014..
Table 4.10 shows that 62.5% of respondents acquired their inputs from stored
products of previous farming seasons (self), while 29.2% acquired theirs from input made
available by the state government and 35% acquired from agro dealers. The inputs acquired
were improved cassava stem, fertilizer, irrigation, chemicals and extension services.
4.2.0 TECHNOLOGIES AVAILABLE IN THE STUDY AREA
4.2.1 TYPE OF TECHNOLOGIES USED IN THE STUDY AREA
The frequency distribution of respondents according to type of technologies available
in the study area is shown in table 4.11.
Table 4.11: Distribution of respondents according to type of technologies available in the
study area (n=120)
Technology type Frequency Percentage (%)
Improved cassava stem 48 40
Irrigation 10 8.3
Pesticides 20 16.7
Fertilizer 30 25
Extension services 40 33.3
Farming system research 0 0
Herbicides 20 16.7
Total 168* 140*
* Multiple responses were obtained
Source: field survey, 2014.
From table 4.11, 40% of the respondents indicated the use of improved cassava stems
in the study area, 8.3% indicated the use of irrigation in the study area, another 16.7%, 25%
and 33.3% indicated the use of pesticides, fertilizers and extension services respectively,
none indicated the use of farming system research and 16.7% indicated the use of herbicides
in the study area. This trend is quite poor as could be seen as one of the reasons for the low
output in the study area (15.3MT), (International institute of tropical agriculture, IITA, 2004).
4.2.2 Means Of Agricultural Technology Awareness
The percentage distribution of respondents according to means of agricultural
technology awareness is shown in table 4.12.
Table 4.12: Percentage distribution of respondents according to means of agricultural
technology awareness (n=120)
Means Frequency Percentage (%)
Extension Services 50 41.6
Cooperatives 34 28.3
Not aware 36 30
Total 120 100
Source: Field Survey, 2014.
From Table 4.12 41.6% of the respondents were aware of agricultural technology
through agricultural extension services, 28.3% were aware through cooperatives and 30%
were not aware. This finding shows the need for improvement of extension services in the
study area because this could have a significant effect on output, if agricultural technologies
are not efficiently utilized. Adeyunmi and Okunmadewa (2001) reported that the efficiency
level of farmers is significantly affected by extension services. Access to extension services
afford the farmers better opportunities to be better informed about production techniques as
well as acquire basic training and skills on how best to allocate resources to achieve higher
productivity and making cassava production a profitable venture, (Robert and Germano,
1998)
4.3.0 LEVEL OF AGRICULTURAL TECHNOLOGY USAGE
The frequency distribution of respondents according to level of agricultural
technology usage is shown in table 4.14.
Table 4.13: Distribution of respondents according to level of agric technology usage (n=120)
Level of usage Frequency Percentage (%) mean
Great (4-5) 11 9.2
Moderate (3-4 18 15
Little(1-2) 32 26.7
Non(0-1) 59 49.2
Total 120 100 2
Source: Field Survey, 2014.
From Table 4.14, it was observed that the level of usage of agricultural technology by
the respondents was low. An average of 2 technologies was recorded as been used by the
farmers. With a greater number of cassava farmers not using agricultural technologies
(49.2%), and a lower number of cassava farmers using agricultural technologies (11%). Also
with a great number of farmers having a primary and secondary school level of education, it
could affect their adoption level. Also it could be observed that there is not much extension
visits to farmers in the study area, hence the farmers are either not aware of the technologies
or they are not readily available to the farmers. Some of the major reasons for the low level of
usage were availability, affordability illiteracy level of the respondents. This was also noted
by Agwu, and Anyaeche,(2007) that non-availability of inorganic fertilizers in the area was
rated the most important factor limiting the level of usage of improved cassava cultivars in
the area with a mean score of 4.72. This is in line with FMANR (1998) report which noted
that the need for fertilizer is unmatched by availability due to the combined effects of
insufficient supply, costs and an inefficient distribution system.
4.4 Effect of Agric Technology on Cassava Output
The multiple regression result on the effect of agric technology on cassava output is
shown in table 4.15.
Table 4.15: Multiple regression result on the effect of agric technology on cassava output
S/N0 Variables Coefficient Std Error t-value Probability
1 agro chemicals 0.000252 0.000222 4.136324** 0.0003
2. extension awareness 0.207560 0.354238 6.585934** 0.0001
3. fertilizer -0.000127 4.62E-05 -2.745466 -0.0071
4. family labour 0.395019 0.408979 5.965869** 0.0005
5. hired labour -0.096721 0.274741 -0.352046 0.7255
6. improved stems 0.000702 2.79E-05 25.16254** 0.0000
7. irrigation 0.000973 0.000121 8.069847** 0.0000
R2 =0.934737; Adjusted R2=0.930033; F-statistics= 198.7267;
Prob (F.statistic)=0.00000; Durban Watson= 1.899442
Note;** indicates at 5% and 1% level of significance.
The results showed that agrochemicals had a positive effect on cassava output
(coefficient of agrochemicals= 0.000252) but very low, extension awareness also had a
positive effect on output (coefficient of extension awareness= 0.0207560); family labour had
a positive effect on output (coefficient of family labour = 0.395019), it also had a significant
t-value of 5.965869 at 5% level of significance and improved stems and irrigation had a
positive effect on output (coefficient of irrigation = 0.000973 ). Improved stems (coefficient
of improved cassava stem = 0.000702). Also, hired labour and fertilizer had a negative effect
on output (coefficient of hired labour= -0.096721 and coefficient of fertilizer= -0.000127
respectively). This fact might be as a result of under utilization of the inputs, it could also be
linked to the educational level of the farmers and the number of extension contacts they had.
This finding is in line with Ibekwe et al (2012), who noted that when resources are not
optimally allocated; it leads to a negative effect on output. For increase in cassava production,
there is need to either decrease or increase the quantity of inputs used by the amount of their
deviations.
Based on the properties of the model specified for this study such as; linearity in
parameters, homoskedascity and no serial correlation, the fitness of the model is analyzed
using the F-statistics, coefficient of multiple determination R2 and the Durban Watson
statistics. The coefficient of multiple determinations R2 of 0.93 approximately shows that
93% of the variation in output was explained by the explanatory variables in the model;
which is an evidence of goodness of fit. Also an F-statistics of 198.7, implying that more of
the agricultural technology has a positive and significant effect on cassava output, and that
the model was well specified. With the Durban Watson statistic of 1.968, being greater than
the R2 in the study, and a reasonable number of significant factors, the model is said to be
free from multicolinearity, positive first order autocorrelation and estimation bias.
The null hypothesis stated for the study was that “agricultural technology has no
significant effect on cassava production”. This was evaluated using the F-statistic result in
Table 4.15. The F-statistic shows how significant the overall parameters are, in explaining the
variations in the dependent variable. Hence from the F-statistic value (198.7267) with a
probability of 0.00000, implying that more of the agricultural technology has a positive and
significant effect on cassava output; therefore the null hypothesis was rejected at 5%
significant level.
4.5 Constraints Faced on the Use of Agricultural Technology
The percentage distribution of respondents according to constraints faced by
respondents on the use of agricultural technology is shown in table 4.16.
Table 4.15: Percentage distribution of respondents according to constraints faced by
respondents on the use of agricultural technology (n=120)
Constraints Frequency* Percentage (%)
Rank
high cost of agricultural inputs and services 71 59.2 3
high risk and uncertainty in agriculture 55 45.8 5
non existence/inadequate farmers
co-operative organization. 43 35.8 6
lack of political consensus to commitment 59 49.1 4
and policies by government.
high rate of poverty of the farmers 71 59.2 3
high level of illiteracy among farmers 83 69.2 1
Others specify: non availability of inputs 75 62.5 2
Total 407*
*Multiple Responses
Source: Field Survey, 2014.
From Table 4.16 the major constraints to the use of agricultural technologies in the study
area were high cost of agricultural inputs and services, high risk and uncertainty in
agriculture, non existence/inadequate farmers co-operative organization, lack of political
consensus to commitment and policies by government, high rate of poverty of the farmer and
high level of illiteracy among farmers. Others were non-availability of inputs, inadequate
extension worker/visits. A similar result was ascertained by Akinnagbe (2010), where he
noted that some of the constraints to the use of technology for agricultural production were
lack of finance, scarcity of planting materials, difficulty in obtaining credit facilities, lack of
technical knowledge in the use of improved technology, high cost of improved varieties, high
interest rate on loan, unavailability of agro-chemicals and other equipment as well as high
cost of agro-chemicals. According to Anyaegbunam, Nto, Okoye and Madu (2011), positive
polices aimed at land reforms towards redistribution of land to make more land available to
peasant and landless farmers in order to increase productivity and efficiency. Also the use of
chemicals has been shown to cause health and environmental hazards , such as, soil, water
pollution, radioactive contamination soil contamination etc. (Hond and Frank, 2003).
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Summary
This study was designed to examine the effects of agricultural technology on
cassava production by smallholder farmers in Bayelsa state, Nigeria. The specific objectives
were to; describe the socio-economic characteristics of smallholder cassava farmers,
identify the types of agricultural technology available to small holder cassava farmers,
determine the level of usage of agricultural technologies in cassava production, estimate the
effects of agricultural technology on cassava production and identify the constraints faced
by smallholder cassava farmers on the use of agricultural technologies. The study was
guided by a null hypothesis; agricultural technology has no significant effect on cassava
production (output).
Data were collected from 120 cassava farmers (primary source) through a structured
questionnaire. Data were analyzed with frequency distribution, percentages and mean, other
statistical tools such as multiple regression model and t-test was used to analyze and
estimate the effects of agricultural technology on cassava production and the significance of
the effect respectively.
The results of the study showed that cassava farming was dominated by males, middle
aged, had a medium level of education, several years of farming experience; these are
plausible as they are qualities that could help move the people forward. It was obvious that
agriculture (cassava production) received a low patronage, a situation that must be
addressed. The level of usage of agricultural technologies by the farmers in the study area
was low because of factors such as availability, illiteracy, high cost of inputs, extension
awareness, etc. However, there was a positive effect on cassava output for the few farmers
that used agricultural technologies; therefore the null hypothesis stated was rejected.
5.2 Conclusion
Based on the analysis on the effects of agricultural technology on cassava production
by smallholder farmers in Bayelsa state, Nigeria, its shows that there is a positive effect on
the use of agricultural technologies in the study area, except for fertilizer and hired labour
because of inadequate utilization of the inputs.
Agricultural technologies should be made readily available and affordable for the
farmers in the study area as it is the major constraint to the use of these technologies. Also
agricultural extension services should be encouraged to educate the people on the technical
know-how.
5.3 Recommendations
Based on the analysis the following recommendations are made;
i. Grass-root mobilization and education of farmers in Bayelsa state on intensive
cassava production to improve output should be encouraged. Government agricultural
initiative should be extended to Bayelsa state to make cassava production attractive to the
people, in other for them to engage in cassava production not just at the subsistence level but
at a commercial level.
ii. Also, policy measures to support micro-credit institutions especially through linkage
with commercial banks would enhance credit delivery to farmers. Other intervention
measures include providing effective information dissemination to farmers, improvement in
technology delivery mechanisms and increasing outreach such as making technology
component farmer specific, decentralization of agricultural technology delivery institutions,
enhancing farmer’s managerial ability especially through cooperative organizations and
education and reforming agricultural markets to stabilize income of farmers.
iii. Government should make available agricultural technologies for the farmers since it is
one of the major constraints against the use of it. Awareness about the existence of
agricultural technologies should be created, the study reveals that a great number of farmers
are not aware of the availability of these technologies and the few that are aware do not have
the technical know-how.
iv. Cost of the agricultural technologies should be subsidized, so that the farmers can buy
them, the improved cassava stem when compared to the improved in terms of price is about
6 times higher.
v. There is need for government support also in terms of revitalization and prioritizing
funding of extension delivery system in the state’s ADPs. This will help to motivate the
extension agents to reach the farmers with relevant information of the availability and use of
agricultural technologies.
vi. Access roads should be provided by government because it discourages the extension
workers from going to the interior villages to do their jobs. Also further studies on this
research should be encouraged as there is a literature gap in this field.
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Appendix 1
UNIVERSITY OF NIGERIA NSUKKA
DEPT OF AGRICULTURAL ECONOMICS
RESEARCH QUESTIONNAIRE FOR SMALL HOLDER CASSAVA FARMER
Dear respondent,
I am a post-graduate student of the above named institution currently conducting a
research work on “Economic effects of Agricultural technology on cassava production by
small holder farmers in Bayelsa state, Nigeria”.
This questionnaire is a part of the research procedure that will enable me to gather
adequate information to give my work authenticity. I therefore, urge you to kindly r respond
to the following questions as objectively as possible. Every information supplied will be
treated strictly confidential. Thank you.
Yours faithfully,
Bethel Oyeindoubra
Researcher
QUESTIONNAIRE SCHEDULE
Please tick the correct option [ ]
A. SOCIO- ECONOMIC CHARACTERISTICS OF THE FARMERS
1. Gender: Male [ ] Female [ ]
2. Age: (a) ≤ 30yrs [ ] (b) 31 – 40yrs [ ] (c) 41 – 50yrs [ ] (d) above 50 [ ]
3. Marital status: married [ ] single [ ]
4. Educational Level:
a) No formal education [ ]
b) Adult Education [ ]
c) Primary education [ ]
d) Secondary education [ ]
e) Tertiary education [ ]
5. Household size: (a) ≤ 3 [ ] (b) 4 - 6 [ ] (c) 7-9 [ ] (d) >9 [ ]
6. Farming experience: (a) ≤ 5yrs [ ] (b) 6-10 yrs [ ] (c) 11-15 yrs [ ]
(d) 15 - 20 yrs [ ] (e) above 20 yrs [ ]
7. Source of Labour: (a) family labour [ ] (b) hired labour [ ] (c) both [ ]
8. Annual Income: (a) ≤ N 5,000 [ ] (b) N50, 001- 100,000 [ ] (c) N100, 001 –
150,000 [ ] (d) above N 150,000 [ ]
9. Cost of hired labour (a) ≤ N3000 [ ] (b) N 3001 – N5000 [ ] (c) N5001 - N 7000
[ ] (d) N 7001 - N 10,000 [ ] (e) above N 10,000 [ ]
10. what is your annual output _______________?
B. TYPES OF AGRIC TECHNOLOGY AVAILABLE
11. What types of technology are available?
(a) Improved cassava stem [ ] (b) Irrigation [ ]
(c) Pesticides [ ] (d) Fertilizer [ ]
(e) Extension Services [ ] (f) Farming system research(FSR)[
]
(g) Herbicides [ ] (h) Others Specify __________
12. How did you know about the technology?
(a) Extension Services [ ] ( c) Cooperative [ ] (c) others
Specify_______________
C. LEVEL OF USAGE OF AGRICULTURAL TECHNOLOGIES
13. Which of the technology do you adopt?
(a) Improved cassava stem [ ] (b) Irrigation [ ]
(c) Pesticides [ ] (d) Fertilizer [ ]
(e) Extension Services [ ] (f) Farming system research (FSR) [
]
(g) Herbicides [ ] (h) Others Specify __________
14. What is your level of usage of agricultural technology?
(a) Great extent (>4) [ ]
(b) Moderate extent ( 3-4 ) [ ]
(c) Little extent ( 1-2 ) [ ]
(d) Non ( 0 ) [ ]
15. What are the reasons for your choice of technology you adopt?
Technology type Availability Affordability Simplicity Effectiveness
Improved cassava stem
Irrigation
Pesticides
Fertilizer
Herbicides
Extension Services
FSR
Others Specify
__________
D. FARM RESOURCES
16. What is the size of your farm (in hectares) (a) < 1 [ ] (b) 1– 1.5 [ ] (c) >1.5 [
]
17. How do you acquire your farm inputs ?
(a) self [ ]
(b) government [ ]
(c) Agro dealers [ ]
E. COST OF INPUT
18. How much do you spend on these technologies?
Technology Units cost Quantity Total cost
Improved stems
Pesticides
Herbicides
Extension service
Farming system research
Fertilizer
Others Specify
F. CONSTRAINTS FACED BY FARMERS ON THE USE OF TECHNOLOGY
Y
19. Which of these constraints do you face while using agricultural technology?
SA= STRONGLY AGREE, A= AGREE, D=DISAGREE, SD= STRONGLY
DISAGREE
S/NO Constraints SA A D SD
1 high cost of agricultural inputs and services.
2 high risk of uncertainty in agriculture
3 non existence/inadequate farmers co-operative organization.
4 lack of political consensus to commitment and policies by
government.
5 Poverty
6 high level of illiteracy among farmers
7 Others specify
