FOOD SECURITY ASSESSMENT IN SYLHET HAOR AREA EMPHASIZING HOMESTEAD PRODUCTIVITY AND AGRICULTURAL RESOURCE UTILIZATION

FOOD SECURITY ASSESSMENT IN SYLHET HAOR AREA EMPHASIZING

HOMESTEAD PRODUCTIVITY AND AGRICULTURAL RESOURCE

UTILIZATION

A THESIS

Submitted to

Bangabandhu Sheikh Mujibur Rahman Agricultural University

in partial fulfillment of the requirement

for the degree of

MASTER OF SCIENCE IN

AGRONOMY

by

Md. Rukunuzzaman Talukder

Registration No. 08-05-2110

Advisory Committee

Major Professor and Chairman

Prof. Dr. Md. Rafiqul Islam

Research Supervisor

Dr. Md. Altaf Hossain

Member

Dr. M. A. Mannan

Dr. Md. Mizanur Rahman

BANGABANDHU SHEIKH MUJIBUR RAHMAN AGRICULTURAL UNIVERSITY

GAZIPUR-1706, BANGLADESH

WINTER 2014

ii

ABSTRACT

Haor area of Sylhet Basin is considered critical for its special nature, although it provides

livelihood to the local communities. In spite of making considerable socioeconomic progress for

the last two decades in Sylhet haor area, it still has the largest number of poor of which a

significant portion is chronically malnourished and suffering from silent disaster. In view of

assessing the status of food security, a study was conducted in five unions of Ajmirigonj upazila

under Habigonj district in Sylhet haor area in respect of homestead soil productivity and

agricultural resource utilization during the period from October 2013 to June 2014. A household

survey was conducted using structured questionnaire covering 60 households. Relevant primary

and secondary data were also collected during the study period. Demographic characteristics in

the study area showed that the majority of the respondents were old aged having higher level of

education, large family size having small farms, low annual income, high farming experience and

farming-based occupation. It is observed that medium to rich people are increasing and with

subsequent decrease in poor people. The most notable change of land was the increase in

settlement area, and decrease in permanent freshwater lakes or rivers. Haor water is mostly

polluted during the dry season and the people have limited access to pure drinking water. Flash

flood has been reported to be the major natural disaster. Boro rice-fallow-local Aman is the major

cropping pattern in the area. The topsoil and subsoil fertility of the homestead area varied greatly

continuing remarkably low amount of nitrogen and organic carbon in general. A significant

differences were found in organic carbon, nitrogen, phosphorus , zinc, sulfur contents between

topsoil and subsoil. Significant positive relationships were found between various nutrient

contents and fruits yield. The area is dominated by crops, followed by livestock and poultry,

fishery and homestead agro-forestry. The technology adoption indices indicate that the uses of

chemical fertilizer, low lift pump and power tiller were important adopted technologies in crop-

based farming system. The rearing of modern poultry breed in livestock and poultry farming, poly

culture of fish and cultivation of fast growing forest tree in homestead were the leading

technologies practiced by the respondents. Among twelve food items, rice consumption of the

respondents was much higher and estimated to be 32 percent higher compared to recommended

dietary need, but majority of them remained below optimum level of calorie intake. During natural

calamities, about 17 percent of the respondents failed to get available food for consumption. The

respondents fulfilled their 84 percent dietary needs from the farming enterprises. However, the

dominant contributor of farming enterprises was crops followed by fisheries and livestocks. The

major problems of the study area were loss of resources due to natural calamities, high price and

inadequate supply of agricultural inputs. From the study, it is concluded that there are enormous

scopes of utilizing land and water resources and fallow land under homestead area for ensuring

household food security in haor area of Sylhet Basin.

iii

ACKNOWLEDGEMENTS

All praises and thanks are for ALMIGHTY ALLAH, the beneficent, the merciful, whose

blessings and exaltation flourished my thoughts and thrived my ambitions to have the cherish fruit

of my modest efforts in the form of this write-up from the blooming spring of blossoming

knowledge. I offer my humblest thanks from the deepest core of my heart to the HOLY

PROPHET, the city of knowledge, HAZRAT MUHAMMAD (Peace Be upon Him) for humanity.

The author expresses the deep sense of gratitude to his honorable Major Professor and

Chairman of the Advisory Committee Dr. Md. Rafiqul Islam, Professor, Department of

Agronomy, Bangabandhu Sheikh Mujibur Rahamna Agricultural University (BSMRAU) Gazipur-

1706 under whose dynamic supervision, propitious guidance, keen interest, philanthropic attitude

and encouragement, the research work was carried out.

The author also sincerely wishes to express deep sense of respect, gratitude and high

appreciation to his honorable Research Supervisor Dr. Md. Altaf Hossain, Principal Scientific

Officer, Soil Resource Development Institute (SRDI), Krishi Khamar Sarak, Dhaka-1215 for his

valuable suggestions and comments that had provided an incentive to finish this piece of work.

Thanks are extended to the Advisory Committee Members Dr. Abdul Mannan, Associate

Professor, Department of Agronomy and Dr. Md. Mizanur Rahman, Associate Professor,

Department of Soil Science, BSMRSU for their valuable advice, encouragement and fruitful

suggestions during the research work. The author expresses heartfelt thanks to all other honorable

teachers of the Department of Agronomy, BSMRAU for their valuable teaching, generous help

and suggestions during the course of study.

The author expresses especial and earnest thanks to BAS-USDA Collaborative Research

Project personnel Md. Tariq Hassan, Former Director General, Department of Agricultural

Extension (DAE) and Dr. Md. Abdul Mannan, Chief Instructor, DAE for their valuable

suggestions, co-operation and encouragement during the research work. The author must extend

his admiration and appreciation to the BAS-USDA Collaborative Research Endeavor Program for

providing fellowship and research funding under the project of “Modeling of Year Round Fruit

Production in the Haor Homestead of Bangladesh” to conduct this research.

The author extends his special gratefulness Dr. Md. Enamul Haque, Professor, and

Mohammad Ziaul Hoque, Department of Agricultural Extension and Rural Development,

BSMRAU. The author takes this privilege to express his thanks to the staff of the Department of

Agronomy, BSMRAU and Agricultural Extension, DAE, Soil Science, SRDI and BSMRAU for

their sincere help and co-operation.

His heartiest thanks and gratefulness are also extended to my elder brothers, beloved friends,

younger brother, well-wishers specially to Mahbub Islam, Kazi Khayrul Basher, Md. Meftahul

Karim, Hanif uddin, Ranju Ahmed, Asif uddin, Mahfuz Imran, Nazmul Hasan, Saiful Islam,

Abdullah Al Mamun, Torikul Islam who inspired and helped me during the research.

Finally, the author expresses special appreciation and indebtedness to his beloved father Md.

Mominul Islam and mother Rowshanara Begum and also all other family members especially my

uncle Md. Ferdous Talukder and my aunt Selina Begum whose sacrifice and inspiration,

encouragement and continuous blessing paved the way to his higher education.

May ALLAH let this for the good of the humanity to the fulfillment of the aspiration of all

referred to here.

Winter 2014 The author

iv

CONTENTS

Page

ABSTRACT

ACKNOWLEDGEMENTS

CONTENTS

LIST OF TABLES

LIST OF FIGURES

ii

iii

iv

vi

vii

CHAPTER-I: INTRODUCTION 1

CHAPTER-II: REVIEW OF LITERATURE 3

2.1 Livelihood activities in haor area 3

2.2 Land resource availability trends in haor area 4

2.3 Farming system in haor area 4

2.4 Homestead vegetation in haor area 5

2.5 Homestead soil productivity in haor area 5

2.6 Household food security in haor area 6

CHAPTER-III: MATERIALS AND METHODS 8

3.1 Locale of the study 8

3.2 Population and sample size 8

3.3 Instrument for collection of data 9

3.4 Procedure of data collection 9

3.5 Collection and analysis of soil samples 9

3.6 Measurement of variables 9

3.7 Measurement of population characteristics 9

3.8 Land use change over time 10

3.9 Hydrological status in the Haor area 10

3.10 Cropping pattern adoption index 10

3.11 Ownership of livestock and poultry 11

3.12 Fishing system adoption index 11

3.13 Ownership of fruit, timber, and fuel wood trees 11

3.14 Extent of adoption of farming technology 11

3.15 Food consumption and calorie intake 12

3.16 Access to food 12

3.17 Contribution of farming enterprises to household food security 12

3.18 Problem confrontation 13

CHAPTER-IV: RESULTS AND DISCUSSION 14

4.1 Socio-economic and demographic profile of the respondents 14

4.1.1 Age 14

4.1.2 Education 14

4.1.3 Family size 15

4.1.4 Farm size 15

4.1.5 Farming experience 16

4.1.6 Occupation 16

4.1.7 Monthly income 16

4.2 Land use changes of Sylhet haor 17

4.2.1 Pattern of land use change 17

4.2.2 Change of hydrological status 17

4.3 Pattern of farming system 18

4.3.1 Cropping system 18

4.3.2 Livestock system 19

v

4.3.3 Fisheries system 20

4.3.4 Homestead forestry system 20

4.4 Homestead soil productivity 21

4.4.1 Homestead soil nutrient status 21

4.4.2 Comparison between topsoil and subsoil nutrients 25

4.4.3 Soil nutrient and fruit yield relationship 26

4.5 Adoption of farming technology 29

4.6 Food security status of households 31

4.6.1 Food consumption 31

4.6.2 Food security status as calorie intake 32

4.6.3 Food security status as access to food 32

4.6.4 Contribution of farm enterprises to household food security 32

4.7 Problem confrontation of the haor land farmers 34

CHAPTER-V: SUMMARY AND CONCLUSIONS 36

REFERENCES 37

vi

LIST OF TABLES

Sl. Page no.

no.

1. Properties determined and methods used for analyzing soil samples 9

2. Conversion of some cash items into energy 13

3. Distribution of the respondents according to age 14

4. Distribution of the farmers according to farm size 15

5. Distribution of the respondents according to farming experience 16

6. Changing scenario of monthly income of the respondents over time 17

7. Change in major land use/land cover pattern in the study area over time 17

8. Changing scenario of hydrological status in the study area over time 18

9. Extent of practice of cropping pattern by the farmers in haor areas 19

10. Distribution of the farmers according to ownership of livestock and poultry

on the basis of price

19

11. Extent of practice of fishing systems by the farmers in the study areas 20

12. Comparison of topsoil and subsoil nutrient contents in the homestead areas 26

13. Correction coefficient between soil nutrients contents 26

14. Correlation co-efficient between soil chemical properties and yield of major

fruit trees

28

15. Distribution of the respondents according to adoption of farming technology 29

16. Technology adoption index (TAI) in crop sector 29

17. Technology adoption index (TAI) in livestock and poultry sector 30

18. Technology adoption index (TAI) in fishery sector 31

19. Technology adoption index (TAI) in homestead agroforestry sector 31

20. Consumption of food items by the respondents 32

21. Food security status of the respondents according to calorie intake 33

22. Distribution of the respondents based on number of meals taken per day 33

23. Contribution of farming enterprises to household food security 33

24. Contribution of the major farming enterprises to the respondents’ household

food security

34

25. Problem confrontation index (PCI) of study area farmer 35

vii

LIST OF FIGURES

Sl.

no.

Page no.

1. Map showing (a) Sylhet haor area in Bangladesh (b) Azmiriganj upazila (sub-

district) of Habiganj district and (c) Five unions of Azmiriganj upazila with

homestead sites

8

2. Distribution of the respondents according to educational level 14

3. Distribution of the respondents according to family size 15

4. Distribution of the respondents according to occupation. 16

5. Distribution of the respondents according toownership of fruit trees 20

6. Distribution of the respondents according to ownership of timber trees 21

7. Distribution of the respondents according to ownership of fuel wood trees 21

8. Distribution of farmer’s homestead according to soil test value interpretation

of soil reaction (pH) based on critical limits

22

9. Distribution of farmer’s homestead according to soil test value interpretation

of organic carbon based on critical limits

22

10. Distribution of farmer’s homestead according to soil test value interpretation

of nitrogen based on critical limits

23

11. Distribution of farmer’s homestead according to soil test value of phosphorus

based on critical limits

23

12. Distribution of farmer’s homestead according to soil test value of potassium

based on critical limits

24

13 Distribution of farmer’s homestead according to soil test value interpretation

of zinc based on critical limits

24

14. Distribution of farmer’s homestead according to soil test value interpretation

of sulfur based on critical limits

25

15. Comparative contribution of farming enterprises to the respondents’

household food security

34

1

CHAPTER I

INTRODUCTION

In Bangladesh, land availability for crop production is in decreasing trend. A significant

quantity of agricultural land is being transformed to rural and urban settlements including

homestead, ponds and roads (Hasan et al., 2013). Therefore, proper utilization of homestead area

for increasing agricultural productivity is a necessity. Among many critical agro-ecological area of

Bangladesh, haor area in greater Sylhet is considered important for its special nature. About 30

percent of the population in haor area lies below the lower poverty level. The majority of

households belonging to the poor and extreme poor categories are suffering from significant

shortages of food. Data on child malnutrition shows that 55 percent children under-five in the haor

area are underweight against 41 percent in general for Bangladesh. The haor area covers about 15

percent of the total area of Bangladesh, of which 12 percent is covered by settlement. Due to

special geographical settings, the housing and settlement patterns are different from other parts of

the country. Almost all land above the maximum flood level is under human settlement. In the

area, about 52 percent of households contain agricultural land where different types of crops and

trees are grown. However, some areas in the homestead remain fallow for a considerable period

and some are not properly utilized due to lack of information on production potentials of land,

soils as well as hydrology and agro-climatic conditions.

Wetland ecosystems are of great importance to Bangladesh because of their extent and critical

economic and ecological role that they play in sustaining life and livelihoods in the country (Khan

et al., 1994). Bangladesh possesses vast area of wetlands including rivers and streams, freshwater

lakes and marshes, haors, baors, beels, water storage reservoirs, fish ponds, flooded cultivated

fields and estuarine systems with extensive mangrove swamps. The haors, baors, beels and jheels

are of fluvial origin and are commonly identified as freshwater wetlands. These freshwater

wetlands occupy four landscape units-floodplains, freshwater marshes, lakes and swamp forests.

Bangladesh is estimated to possess seven to eight million hectares of wetlands in the form of

permanent rivers and streams, estuarine and mangrove swamps, shallow lakes and marshes, large

reservoirs, small ponds and tanks, shrimp ponds and seasonally flooded flood plains (Nishat,

1993).

Haors are bowl-shaped depressions between the natural levees of a river subject to recurrent

monsoon flooding and are mostly located in the north-eastern region of the country, covering an

area of approximately 24,500 km2. It consists of about 47 major haors and 6300 beels of varying

size of which about 3500 are permanent and 2800 are seasonal (Hussain and Salam, 2007). The

haor dwellers are some of the poorest and most vulnerable people, particularly those who live on

the marooned island/adjacent to river banks.

The overall scenario of food security in Bangladesh indicates inadequate calorie intake,

malnutrition and hidden hunger. Many households fail to meet the basic food requirements. The

rural areas where head of households’ income is less than one dollar per day experience acute food

shortages. In haor area farmers face food shortages especially during pre-harvesting/lean periods.

Rice is the staple food which provides 68 percent of the calorie and 54 percent of the protein

needs. Approximately 32 million of the total population in Bangladesh cannot afford an average

daily intake of more than 1800 kilocalories (USAID, 2007). USAID recommended that the

average daily calorie intake should be 2828 Kcal for the countries like Bangladesh. It indicates that

most of the households in Bangladesh particularly in haor rural areas suffer from malnutrition.

Mostly children and the women in the rural households face this acute malnutrition.

There are little employment opportunities in haor areas where most of the people make their

living from cropping, raising cattle and catching fish. Land is the most important resource in the

haors, but poor households lack the support they need to utilize it fully, including poor access to

technical advice and training, agricultural inputs and marketing facilities (Mahmud, 2008).

Promoting sustainable development in haor areas of Bangladesh poses important challenges.

Poverty caused by traditional agriculture and environmental degradation in the haor areas of

Bangladesh needs to be addressed by appropriate policies and programs to develop an

2

environmentally compatible and economically viable agricultural systems. During 1990s, the

international NGOs, such as CARE and Oxfam developed sustainable livelihood models

considering the need to broaden the scope of development project. However, policies and

programs aimed at promoting alternative land use systems in Bangladesh failed to achieve

expected goals because of inadequate understanding of the changing trends in existing land use

systems and forces driving the changes.

Farmers in the haor area are engaged in increasing agricultural production and income by

utilizing their available resources around the homestead. For maximizing and diversifying as well

as sustaining the production potentials in homestead areas, acquiring data and information on soil

and land resources is imperative. However, such information is scanty, which is considered as an

impediment for up scaling new technologies and practicing modern production packages in the

area. The suitability assessment of various plant species especially fruits trees to be grown in

homestead area based on land and soil characteristics, and their quality has not been done hitherto.

Moreover, there are lack of information on knowledge gaps between farmers practice and

recommended management practice for fruit trees and other plant species in the homestead area. In

this regards, appropriate management packages needs to be disseminated for increasing fruit

production in homesteads.

Furthermore, there is still very little quantitative information on health, nutrition, and food

security of haor dwellers. There are dearth of study reports addressing the management of farming

systems and the food security aspects in haor areas. In this context, it is indispensable to

understand the characteristics and potentiality of homestead land and soils, and agricultural

resources towards household food security in selected areas in haor region of Bangladesh. Taking

the above facts into consideration, a specific area of Azmiriganj Upazila was selected for the study

aiming at:

i. inventorizing agricultural resources at farm level;

ii. evaluating homestead productivity emphasizing soil fertility and fruit productivity;

iii. assessing technology adoption in enhancing productivity of farm enterprises; and

iv. assessing food security in terms of resource utilization, and food availability,

consumption and demand in the farming community.

3

CHAPTER II

REVIEW OF LITERATURE

2.1 Livelihood activities in haor area

The haor areas in Sylhet basin is located in the north-eastern region of Bangladesh. It is

considered as a wetland ecosystem having international importance. There are 423 small and large

haors in Bangladesh comprising an area of about 8000 km2 dispersed in the districts of

Sunamgonj, Sylhet, Moulvibazar, Hobigonj, Netrokona and Kishoreganj (Alam et al., 2010;

BHWDB, 2011). Haor is a highly productive natural source of livelihoods that supports millions

of poor people and plays a vital role in supplying protein to human diets. It is also one of the major

sources of livelihoods particularly for fishing, cultivating food crops, vegetables, and pasture lands

(BCAS, 2005). The wetlands are generally used for cultivation, while it also works as a back-water

reservoir during the monsoon (IUCN, 2010). Cultivation of rice during dry season is the major

livelihood activity in and around the wetlands of haor area (IUCN, 2011). In Bangladesh, about 76

percent of the population live in rural area and major parts of it is under various types of wetlands

including floodplains, haors, baors, and lakes (Kabir, 2006). The rural people are directly or

indirectly dependent on agriculture for their livelihoods. During winter, the haor basin is planted

with modern Boro paddy. In recent years, almost all seasonal wetlands came under modern rice

cultivation in winter. Poor people and the landless groups work in crop fields as daily labor or

cultivate rich people’s land as sharecropper for earning livelihood (Ahmed, 2008).

In haor area, fishing is the largest livelihood activity (Amin et al., 2007). Two million people

are fully engaged in fishing, handling, packaging, transporting, distribution and marketing of fish.

Moreover, about 10 million are part-time fishermen to supplement their income or live on fishing

for some part of the year. About 62 percent head of households are engaged in farming, 18 percent

as day labor, 8 percent in fishing and 2 percent in business (Nuruzzaman, 2004). Few families are

engaged in fuel wood and sand collection, bird trapping, duck rearing also. Kabir and Amin (2006)

reported that agriculture, collection of sand, stone and coal, small business, rowing passenger boats

and goods transportation are common activities in the haor area.

Floodplain fishing and fish related activities play a vital role to employ rural people (Amin et

al., 2007). When the people become unemployed due to less demand of labor in agriculture field,

the agriculture labors are engaged in floodplain fishing to earn livelihood expenditure. Some of the

fishermen are involved in making fishing gears and bamboo traps to protect their livelihoods

(Ahmed, 2008). The socio-economic census showed that 19 percent families are involved in

fishing as their primary occupation, while 54 percent as a secondary occupation. The average

annual per capita income from this sector is about BDT 5400 (Khan, 1993). Moreover, lack of

cultivable area due to prolonged flooding in the haor areas restricts livelihoods of local

communities (Sarma, 2010).

Sarma (2010) tried to explore the socioeconomic status and their dependency on its natural

resources of the people residing near deeply flooded haor areas. The local residents having an

annual average per capita income of BDT 3175 essentially depend on the wetlands for their

survival. Studies revealed that 32 percent households prefer fishing during the monsoon, while 37

percent prefer small business, 17 percent prefer beef fattening, 23 percent prefer handicraft. Many

people in haor areas are also involved in dairy and poultry farming also. There is a huge potential

for dairy and poultry farming especially the duck rearing in haor areas. Collection of fodder grass

for cattle from the haor is also an important livelihood activity of both poor and rich. The poor

people usually sell a portion of the collected grass to supplement their family income (Hossian and

Khan, 2006). About 5 percent households are engaged in rowing passenger boats. Boats are also

used in stone and coal collection and transportation (Ahmed, 2008; Hossian and Khan, 2006).

Women are also engaged in sewing and embroidery as alternative livelihood activities. All these

multifarious activities are important to the haor people for a reliable income throughout the year.

4

2.2. Land resource availability trends in haor area

Land use change has been a very important phenomenon on the ecosystems of many areas

(Metzger et al., 2006; Turner et al., 1997). Land use change directly influences the provisional

ecosystem services (food and timber), climate regulation, nutrient cycling and cultural identity

(Reid et al., 2005; Daily, 1997). Land use and land cover change has number of consequences such

as change in the atmospheric composition, biotic diversity, biological systems and its ability to

support human needs and environmental risk (Daniel, 2008). Foley et al. (2005) reported that

between 30-40 percent of the natural vegetation on the earth’s surface has been converted to

pastures and croplands, which are currently expanding by around 13 million hectares per year

(FAO, 2002). The effects of the land conversion on climate could be very important at regional

and global scales (Foley et al., 2003).

The haor ecosystem is changing and it makes the livelihood more vulnerable. Particularly the

agriculture sector is expected to be heavily influenced by land cover changes. Salauddin and Islam

(2011) estimated that water bodies of the haor area has been reduced by around 6.88 percent,

whereas, land area has been increased by 8.35 percent during the period of 2000 to 2008. It is

obvious that loss of biodiversity due to such conversion is a great threat for nature (Hoekstra et al.,

2005; Dirzo and Raven 2003; Sanderson et al., 2002; UNEP, 1995). Many of these changes are

driven by land use practices that feed a growing population, but affect other ecosystem services.

(Foley et al., 2005; MA, 2005; DeFries et al., 2004).

Besides anthropogenic activities, land cover of haor area can also be altered by other forces

such as weather, flooding, climate fluctuations, and ecosystem dynamics. Both human-induced and

natural land cover changes can influence the global change because of its interaction with

terrestrial ecosystem (Houghton, 1994), biodiversity (Sala et al., 2000) and landscape ecology

(Reid et al., 2000). Land cover changes may increase the risk of flash floods which is historically

very common in haor area where Boro rice is the major crop grown during winter season.

Occurrence of flash flood at the later stages of Boro rice affects the farmers who are mostly

dependent on Boro rice production (Mas et al., 2004; Zhao et al., 2004).

2.3 Farming system in haor area

Farming is an activity carried out by the members of households that represent managerial units

organized for the economic production of crops, livestock, and fishes (Ruthenberg, 1980).

According to CGIAR (1986), a farming system is a complicated interwoven mesh of soils, plants,

animals, implements, workers, other inputs, environmental influences with the strands held. Shaner

et al. (1982) defined farming systems in relation to Bangladesh situation as physical, biological

and socio-economic setting. Hossain (1988) found that the farmers in subsistent farming systems

generally maintain different enterprises in their farms for sustenance and they are very dynamic in

selecting enterprises and adopting technology.

In terms of farming system, crop production practices, and economic activities of haor areas

are quite different from those of the other parts of the country. The total cultivated area of haor

districts is about 1.26 million hectares of which about 66 percent is under haor. The farming

system of haor area is rice-based. Huda (2004) reported that almost 80 percent of this area is

covered by Boro rice, while only about 10 percent area is under transplanted Aman. Hybrid rice is

also grown in haor area and the area is increasing in different locations. (Das, 2004; Husain et al.,

2001). Agriculture is the main source of livelihood in haor area. Directly or indirectly, all other

sources of income in this ecologically disadvantaged area are subject to harvesting of crops. But

early flash floods often cause extensive damage to the crops. Cultivation of early maturing short-

duration rice variety would enable farmers to escape crop damage due to early flash flood. Lack of

water control dam also appeared to be an important problem in the haor areas.

Early flood and drought are the main constraints in growing modern Boro rice (Alam et al.,

2010). Though flood is the common phenomenon in the haor areas, the people have had an

experience about the seasonal and flash flood with its frequency and magnitude. Now-a-days they

are unable to predict the flood due to construction of different structures and embankments in the

upstream, and siltation of river beds as well as change in river flow. As Boro is damaged by early

5

flash flood, flood-controlling dams need to be constructed to prevent huge loss of Boro rice (Khan

et el., 2012)

3.4 Homestead vegetation in haor area

There are 25.53 million homesteads in Bangladesh (BBS, 2011). Homesteads provide some basic

household needs like fruit, food, shelter and cash. In Bangladesh, a large area of every homestead

remain fallow year after year, where plantation of diversified fruit trees is possible and farmers can

easily get year round fruits from their homestead gardens and consequently improve their

livelihood. Akinnifesi et al. (2004) emphasized the nutritive economic values of fruits, being rich

in minerals and vitamins, sold for cash income and supplement foods during famines and or in

emergencies.

The importance of homestead garden is also well recognized worldwide. In western Africa,

Irvingia gabonensi is a popular tree-fruit for home consumption and the other species are grown

for cash sale in local markets (Ayuk et al., 1999). The presence of fruit trees appeared to be most

closely related to subsistence in Soqotra Island. The number of large fruit trees declined as the

importance of crops destined for the market increased (Ceccolini, 2002). Farmers prefer to produce

fruit trees rather than multipurpose- or timber trees on their farms in Costa Rica (Marmillod, 1987)

and Honduras (Hellin et al., 1999). Low labor requirement was seen as an advantage and the

relatively free availability of forest-based timber- and fuel wood products as a limitation. In

Nicaragua, 37 percent space of homesteads have been found to be allocated for producing fruit

species and about 85 percent of the fruits so produced were used for home consumption and the

remainder for marketing (Mendez et al., 2001). In Jamaica, fruit was regarded as the second most

important product following timber based on importance of tree species that farmers usually

practiced in their homesteads (McDonald et al., 2003).

The above reviews clearly ascertain the importance of growing fruit trees on homestead areas

both for consumption and income generation. Many studies reveal that the biophysical interactions

between trees and crops in agroforestry systems have been relatively well studied (Rao et al.,

1998). However, such interactions between annual crops and fruit trees have seldom been studied.

On the other hand, economic performance and relative yields of mixed annual-fruit tree systems

have not been better studied and reported in Bangladesh. Akinnifesi et al. (2004) emphasized on

the conservation of genetic resources of homestead fruit trees and approached four basic steps: (i))

identification of priority species by communities and other users, (ii) participatory selection of

superior trees and naming them in situ, (iii) propagation and cultivation of trees as fruit orchards,

and (iv) dissemination and adoption.

The diversity of fruit species, species richness and relative prevalence of species were

investigated in the haor area of Bangladesh (Islam et al., 2011). They ranked the fruit species

according to their relative prevalence in five different unions viz Azmiriganj, Kakailcheo,

Bodolpur, Jolshukha and Sibpasha. Banana was found in abundance in all the unions except

Azmiriganj where betel nut was the most prevalent one followed by coconut, mango and date.

Mannan (2000) reported that mango was the most prevalent followed by guava, jackfruit and

coconut. Islam et al. (2011) emphasized that such study would provide the foundation for the

policy makers to understand the species richness, fruit species conservation, and socio-economic

importance of homestead as well as to formulate biodiversity conservation planning.

3.5 Homestead soil productivity in haor area

The homestead garden system is common in many countries of Asia including Bangladesh. These

gardens provide family nutrition, increase household income, act as buffer to food insecurity

during lean season and more importantly protect habitat and conserve soil (Landauer and Brazil

1990). It is reported that more than 60 varieties of fruits and vegetables are commonly cultivated in

homestead areas of Bangladesh. The choosing of types and mixing of species depend on household

food preferences, soil and climatic conditions, and availability of local planting materials and

seeds.

In India, Pandey and Singh (2009) studied soil fertility in three depths (0 -10, 10-20 and 20-30

cm) at two canopy positions under home garden trees: coconut palm (Cocos nucifera L.), clove

6

(Eugenia cariophyllata Thunb), and nutmeg (Myristica fragrans Houtt. Nees) spice and native

moist evergreen forest, where they described the variations in organic carbon (C), total nitrogen

(N) and phosphorus (P), mineral N and P, and exchangeable potassium (K), calcium (Ca), and

Magnesium (Mg) and microbial biomass C in soils in relation to leaf litter and root biomass of

three 20-year-old home garden. Zingore et al. (2007) measured the variability of soil fertility with

distance from homesteads on smallholder farms of different socio-economic groups on two soil

types in Zimbabwe. They observed that soil organic matter, available P and cation exchange

capacity (CEC) decreased with increasing distance from homestead on most farms. Soil available

P was particularly responsive to management, irrespective of soil type, as it was more concentrated

on the plots closest to homesteads on wealthy farms, compared with distant plots and all plots on

poor farms. There was a large gap in the amounts of mineral fertilizers used by the wealthiest

farmers and the poorest farmers. The wealthy farmers who owned cattle also used large amounts of

manure, which provide at least 90 kg N and 25 kg P (36 kg N ha−1

and 10 kg P ha−1

) per farm per

year. The poor farmers used little or no organic sources of nutrients.

Variability of soil fertility within, and across farms, poses a major challenge for increasing

crop productivity in smallholder systems in Africa. Impact of different soil fertility management

strategies on spatial soil fertility gradients was studied by Masvaya et al. (2010). They observed

that soil available P was higher in homestead (8-13 mg kg−1

) of resource-endowed farmers than on

crop field and all fields on resource constrained farms (2-6 mg kg−1

). Heterogeneity in soil fertility

in smallholder systems is caused by both inherent soil-landscape and human-induced variability

across farms differing in resources and practices. Soil fertility indicators in respect of C, N, P, K,

Ca, Mg content and pH decreased significantly with increasing distance from the homesteads

(Tittonell et al., 2012).

3.6 Household food security in haor area

Food security includes the ready availability of nutritionally adequate and safe foods as well as an

assurance of the ability to acquire suitable foods in socially acceptable ways. Webb et al. (2002)

stated that physical availability of food underscores the significance of production in order to

supply enough food for all people at all times. Maxwell (1995) stated that the concept of food

security is based on three distinct yet inter-related fundamental concepts: food availability, food

access and food utilization. These concepts together determine the food security status at any

level of analysis. A very few literature are available on food security, of which some are relevant

to the strategies adopted by the people suffering from food insecurity more frequently. The

literature on food security aspects of the people living in the haor areas is limited.

A number of studies focusing on the different aspects of food insecurity have been conducted

by Rahman and Khan, 2005; Halder and Mosley, 2004; Radhakrishna and Ravi, 2003; Talukder

and Quilkey, 1991. They have identified that lack of economic and social access to safe and

nutritious food items to meet daily dietary need are the major reason for food insecurity. Sarma

(2010) conducted detail studies on vulnerability issues and sustainable livelihood development in

haor area. He reported that 71 percent households were found effectively landless of which about

55 percent were absolutely landless and 17 percent households were migrated and 78.9 percent

haor households suffered from food insecurity mainly because of landlessness, mono-crop

culture, seasonal unemployment and natural calamities. The haor basin is poverty stricken where

more than 28 percent of the population lives below the poverty line (FSHB, 2012). The major

drivers of poverty in the haors are the prolonged deep flooding associated with settlement on

cramped islands, lack of easy communicating roads and predominantly growing a single rice crop

(Prance, 1997). Crop agriculture is the principal livelihood of the farmers who practice mono-

culture (FSHB, 2012). This single crop remains under constant threat of partial to complete

damage from early flash flood. The haor inhabitants face economic, social and technical

constraints in earning their livelihood. Optimum food security in haor areas can be ensured if

acclimatized species are introduced in the haor region with appropriate management alternatives

including seasonal floating vegetable garden. .

Fishing is observed to be the best optional source of income for the haor people. Besides

fishing, there is little work during non-crop season in the haor area (Gardener and Ahmed, 2006).

7

The haor area supports rich fisheries after flood water have receded. Apart from actually

professional fishermen, there are seasonal participants in fishing (Craig et al., 2004). Since they

are landless and marginal farmers, fishing has been conceived as a critical component of their

livelihood. Nobody is allowed to fish during monsoon in the disadvantaged area of haors to secure

a livelihood. As a result, the incidence of poverty is very high which is about 50 percent (Kam et

al., 2005). In some haor area, poverty varies from 61 to 81 percent (Rahman and Razzaque, 2000).

Although number of studies on food security is available in different ecologically critical areas

of Bangladesh, there is little information for haor areas of the country. The haor area of Sylhet

region is most vulnerable due to its geographical settings and food security aspects are most vital

that needs to be addressed based on available resources and their appropriate utilization.

Unfortunately, appraisal of various resources on spatial and temporal basis and holistic approach

of utilization of resources for improving livelihood of the rural community are still lacking.

Thus the present study was undertaken to evaluate the situation of food security of the people

living in selected areas of Azmiriganj Upazila through productivity assessment of homestead land

resources along with agricultural resource utilization.

8

CHAPTER III

MATERIALS AND METHODS

3.1 Locale of the study

The study was conducted at Azmiriganj upazila of Habiganj district in Bangladesh taking into

consideration of homesteads of thirty three villages from five unions. The study area was selected

as a part of haor in Sylhet basin area having better accessibility. A map showing the study area is

presented in Figure 3a-c.

3.2 Population and sample size

All the household farmers of the selected thirty three villages of Azmiriganj upazila under

Habiganj district constituted the population of this study. The sampling size were determined

considering time and budget provisions allocated for the study. In this study, 60 farmers homestead

were selected randomly as the respondents (Figure 3c).

'

Figure 1. Map showing (a) Sylhet haor area in Bangladesh (b) Azmiriganj upazila (sub-district) of

Habiganj district and (c) Five unions of Azmiriganj upazila with homestead sites.

(a)

(c)

(b)

Selected homestead

Union map and sampling sites Azmiriganj upazila

9

3.3 Instrument for collection of data

In order to collect information from the respondents, an interview schedule was prepared keeping

in mind the objectives of the study. The interview schedule contained both open and closed

questions. The questions were made easily understandable by the respondents. Besides, secondary

data including official records, reports, journals, proceedings and other related printed materials

were also used as base materials for the study. The interview schedule was pre-tested involving 20

respondents and modified through incorporating necessary amendments. Then the researcher

discussed with the Members of the Advisory Committee and the questionnaire was finalized. An

English version of the Interview Schedule has been presented in Appendix I.

3.4 Procedure of data collection

Data were collected through face to face interview of farmers during October 2013 to June 2014

by the researcher himself. To get valid and relevant information, the researcher made all possible

efforts to explain the purpose of the study to the respondents. Appointments with the interviewees

were made in advance. In case of failure to collect information from the respondents due to their

other business, re-visits were made with prior appointments. While interviewing any respondent,

the researcher took all possible care for establishing rapport with him so that the respondents feel

free to furnish with appropriate response to the questions and statements as included in the

schedule. Questions were asked in multiple ways so that the respondents could easily understand

the content of the questions. If any respondent was not clear about what was wanted from him,

supplementary questions were asked for further clarification. Data were also collected through

focus group discussion (FGD) and from available published and unpublished secondary sources.

3.5 Collection and analysis of soil samples

Soil samples were collected form 60 homesteads following standard methods. Collected samples

were air dried ground and sieved through a 2 mm (10 mesh) sieve. The composite samples were

stored in clean plastic bag for physical and chemical analyses following standard methods

provided by BARC (2012). Soil samples were analyzed for determining different properties

following standard protocols (Table 1).

Table 1: Properties determined and methods used for analyzing soil samples

Properties Methods of analysis References

Soil Texture Hydrometer Method Black, 1965

Soil reaction (pH) Glass electrode pH meter Jackson,1962

Organic carbon Wet oxidation method Page et al.,1982

Total Nitrogen micro-Kjeldahl method Jackson,1973

Available Phosphorus Colorimetrically Olsen et al ,. 1954

Exchangeable potassium Flame-photometer Jackson,1973

Available Sulfur Turbidimetrically Page et al.,1982

Available Zinc Atomic absorption

spectrophotometer.

Lindsay and Norvell,1978

3.6 Measurement of variables

In the present study, the researcher gathered and reviewed related literature to widen his

understanding about the nature and scope of the relevant variables.

3.7 Measurement of population characteristics

Age, education, family size, farming experience, farm size, annual income, and contact with the

sources of information were the population characteristics of the study. The meaning of these

characteristics along with their measurement procedures are stated below:

10

Age: Age of a respondent referred to the period from his birth to the time of data collection. Age

of a respondent was measured in terms of actual years on the basis of his statement. A score of one

(1) was assigned for each year of age.

Education: Education means a process of learning, especially in school or college. Education was

measured on the basis of completed years of schooling by a respondent in the formal educational

institutions. Score of one (1) was given to a respondent for each year of schooling.

Family size: The family size of a respondent was measured in terms of the number of family

member who used to eat and live together permanently. Respondents were classified into three

categories on the basis of their family size according to Alam (2007).

Farm size: The farm sizes of the respondents were measured in hectares using the following

formula (Alam, 2007):

Total farm size= a+b/2+c/2+d

Where,

a = Own cultivated land

b = Cultivated land under others on borga

c = Cultivated land taken from others on borga

d = Non cultivated land

Farming experience: The farming experience of the respondent means the experience he gained

directly by performing various farming activities and it was expressed in years i.e. score of one

was given for each year of experience.

Occupation: For determining the occupation of the respondents in the study area, every

respondent was asked about their daily activities in which they were involved for maintaining their

livelihood.

Estimation of income: Incomes of each respondent from haor activities (fishing, farming, farm

labor, livestock rearing, driving boat etc.), non-haor activities (service, business etc.) and other

cash income (social benefits scheme, relief and interest) were recorded in taka for estimating total

monthly income.

Annual income: Family income of a respondent was measured by taking sum of income earned by

a respondent and other member of the family in a year from crop sector, livestock, fisheries,

homestead forestry sector and non-agricultural sector. It was expressed in taka being considered as

the income of a respondent‟s family.

3.8 Land use change over time

For measurement of the change in land use pattern over time the respondents‟ opinions in 2014

were compared with that of 2002-2004.

3.9 Hydrological status in the haor area

For determining the hydrological status in the haor area, some criteria such as sources of irrigation

water, quality of haor water, quality of drinking water, depth of inundation, duration of inundation,

flooding and condition of haor were considered and respondents opinions in 2014 were compared

with that of 2002-2004.

3.10 Cropping pattern adoption index

Farmers follow different types of cropping patterns based on their resources and demand.

Therefore, the adoption of cropping pattern might appear as an important indicator for food

security. A measuring scale containing 7-item was used to determine the extent of technology

adoption of cropping pattern by an individual. Each respondent was asked about the extent of his

adoption against each of the cropping patterns practiced. The extent of adoption was rated as

„much‟, „little‟ and „not at all‟ and the weight for the corresponding rating scale was assigned as 2,

11

1, and 0, respectively. From the responses, the total score of each adoption was calculated by

adding up the weights. The score of adoption of each respondent could range from 0 to 20, 0

indicating no adoption, and 20 very high adoption.

3.11 Ownership of livestock and poultry

It was measured by quantity with current values and then transformed into 4 point ordinal scale for

making livestock and poultry index such as:

(a) No ownership

(owned none of the livestock or poultry)

0

(b) Small ownership

(owned livestock and poultry valued up to BDT: 15,000)

1

(c) Medium ownership

(owned livestock and poultry valued between BDT: 15,001-30,000)

2

(d) Large ownership

(owned livestock and poultry having value above BDT: 30,000)

3

3.12 Fishing system adoption index

Farmers adopt different types of fishing technology. Therefore, the adoption of fishing technology

appears to be an important factor for food security. A 4-item measuring scale was used to

determine the extent of adoption of fishing system by an individual. Each respondent was asked

about the extent of his adoption against each of the fishing system. The extent of adoption was

rated as „much‟, „little‟ and „not at all‟ and the weight for these rating scales was assigned as 2, 1,

and 0, respectively. From the responses, the total score of each adoption was calculated by adding

up the weights. The score of adoption of each respondent could range from 0 to 8, 0 indicating no

adoption and 8 indicating much adoption.

3.13 Ownership of fruit, timber, and fuel wood trees

It was measured by actual number of the components possessed by an individual respondent and

then transformed into ordinal scale as:

(a) No ownership (owned none of the trees) 0

(b) Small ownership (owned up to 10 trees) 1

(c) Medium ownership (owned 11-20 trees) 2

(d) Large ownership (owned more than 20 trees 3

3.14 Extent of adoption of farming technology

A four point type scale was used for computing the extent of adoption of farming technology

score. Weightage of the responses against each technology were assigned in the following way.

Scores of 0, 1, 2 and 3 were assigned for “no use”, „low use‟, „medium use‟ and „high use‟,

respectively. The weightage of responses of all the farming technologies adopted by an individual

respondent were added together to obtain the extent of adoption of farming technology.

For a better understanding of particular farming technologies adopted by the respondents, a

technology adoption index (TAI) was computed. The TAI was calculated by multiplying the

frequency counts of each of the technologies with its corresponding weights such as 3 for „high‟, 2

for „medium‟, 1 for „low‟ and 0 for „not at all‟. By adding all the values of each cell together, the

score of TAI was calculated. The TAI for each technology could range from 0 to 180 where zero

indicating „not at all‟, while 180 indicating „high adoption‟ of such farming technologies.

12

3.15 Food consumption and calorie intake

The food consumption of the respondents was estimated on the basis of their food needed for a

month. The respondents were directly asked to mention the amount of food consumed by the

members of the household per month. Food consumption was measured based on average monthly

calorie intake of the family members. The household food consumption was converted into calorie

intake per person per day. The selected food items were rice, wheat, tuber, pulse, vegetables, fruit,

fish, meat, milk, sugar, and edible oil. Calorie uptake was measured by using the formula

developed by Imai (2003) (Appendix IV).

3.16 Access to food

Access to food was measured on the basis of ability to have meals/day by each member of the

family. The respondents were directly asked to mention whether they were able to have three

meals/day, two meals/day and one meal/day over a period as per described by Hossain (2009).

Scores assigned were: For taking 1 meal daily=1, for taking 2 meals per day=2 and for taking 3

meals per day=3.

3.17 Contribution of farming enterprises to household food security

Farming enterprises functionally indicated the crops, livestock, fisheries and homestead

agroforestry enterprises. Household food security expressed the economic, physical and social

availability, accessibility and sustainability of the dietary needs of the individual in farm families

(FAO, 1996). In this study, contribution of farming enterprises to the household food security was

determined by using the following formula:

Contribution of farming enterprises to household food security (%) =

Total calorie obtained from farm produces per year was determined with the help of a list of

energy (Kcal) content in 100g of different food items (Meyer, 2004). All the farming enterprises

could not be converted into energy (Kcal) by using this list. Problem arose when it was found that

some part of the farm produces were sold by the respondents and some item like jute and tree

could not be directly converted into energy (Kcal). These are obviously cash item i.e. directly

related to monetary return rather than having calorie value. It was, therefore, inevitable to find out

a conversion factor to be used to convert cash items into energy (Kcal).

Hence, information were sought from focus group discussion (FGD) involving direct

participation of selected respondents regarding prices of the products and food items needed to be

bought by the farmers. The price of some products which were sold was determined giving a value

in BDT. This monetary value was converted into energy following the procedure as stated in Table

2. The cash energy conversion factor was computed according to the following formula.

Cash energy conversion factor

= 41250/1533 =26.91

This means that the calorie value of the items sold was calculated by multiplying the monetary

value (BDT) with cash energy conversion factor. It was then added to the calorie value of the

consumed food items to get the total calorie obtained from farm produces per year. On the other

hand, total calorie needed by the family members was known from the average Recommended

Desired Intake (RDI) (Kcal/capita/day) of food item which employed the rate of dietary needs as

2187 Kcal/person/day (Anon, 2008). Finally, contribution of farming enterprises to household food

security was determined by dividing the total calorie obtained from farm produces per year by the

Total calorie obtained from farm produces per year ----------------------------------------------------------------× 100 Total calorie needed by family members per year

Total calorific value of the produces = Total monetary value of the produces

13

total calorie needed by family members per year. It was then multiplied by 100 to have the

contribution in percentage following Kabir (2007).

Table 2.Conversion of some cash items into energy

Food item needed

to be bought

Monetary value (MV)

(BDT: Per kg of food item)

Calorific value (CV)

(Kcal per kg of food item )

Rice 38 3650

Wheat 30 3410

Fishes 115 1360

Broiler 130 1200

Beef 250 3450

Mutton 360 1160

Soybean oil 100 9000

Fruits 110 800

Chili 90 1030

Ginger 130 4320

Turmeric 105 3490

Potato 13 970

Vegetable 20 430

Coriander 150 2880

Milk 32 670

Lentil 110 3430

Total MV=1533 CV = 41250

3.18 Problem confrontation

Respondents confront different types of difficulties and when they cannot solve their problems,

they usually discuss with others, and seek help from different sources. Therefore, the problem

confrontation could appear as an important factor in respondent's perception. A 16-item measuring

scale was used to determine the problem confrontation of the respondents. Each respondent was

asked about the extent of his problem confrontation against each of the statements. The score of

problem confrontation of the each respondent could range from 0 to 32. The problem

confrontation index (PCI) was calculated by multiplying the frequency count of each of the cell of

a scale of extent of problem with its corresponding weights such as 2 for much, 1 for little and 0

for no problem. By adding all the values of each cell together, the score of PCI was calculated.

PCI= (Pm × 2 + P1 × 1 + Pn × 0)

Where, PCI=Problem confrontation index

Pm=Much problem,

Pl =Less problem and

Pn= No problem.

14

CHAPTER IV

RESULTS AND DISCUSSION

4.1 Socio-economic and demographic profile of the respondents

The socio-economic and demographic profile of the respondents under the study is discussed in

this section to get an idea about population characteristics of selected area of Azmiriganj Upazila.

The socio-economic and demographic characteristics include age, education, family size, farm

size, farming experience, annual income of the respondents.

4.1.1 Age

The age of an individual is an important social factor pertaining to one’s personality make up. The

elders are important in having long experience in many spheres of life. The age of the respondents

of the study site ranged from 23 to 80 years with an average of 49.38 years. Based on their age,

the respondents were classified into three categories like young (< 35 years), middle aged (35-50

years) and old aged (>50 years) as suggested by Haider (2010). Data displayed in Table 3 also

indicates that the highest portion of respondents (42 percent) was in the old aged group followed

by middle (34 percent) and young aged groups (24 percent).

4.1.2 Education

The literacy of the respondents is an important factor which determines their communication

behavior. The level of education of the respondents were categorized into four groups i.e. illiterate

(no schooling), primary level (1-5 years schooling), secondary level (6-10 years schooling) and

above secondary level. About 15 percent of the respondents had primary level education, whereas,

23 percent and 38 percent of the respondents had secondary and above secondary level education,

respectively. About 24 percent of the respondents were illiterate (Figure 3). The overall literacy

rate was 76.0 percent which is higher than the general literacy rate of 53.7% for population aged

11 to 44 years in Bangladesh (BBS, 2013).

Table 3. Distribution of the respondents according to age

Age group Respondents Range Mean±SE*

Number Percent

Young aged (<35) 12 24

Middle aged (35-50) 17 34 23-80 49.38±0.06

Old aged (>50) 31 42

Total 50 100

*SE-standard error

Figure 2. Distribution of the respondents according to educational level.

24

15

23

38

0

5

10

15

20

25

30

35

40

Illiterate Primary Secondary Higher

Per

cen

t re

spo

nd

ents

Level of education

15

4.1.3 Family size

Family size of the respondents refers to the total members of the family including the respondent

himself, spouse, children and other dependents those use to live, eat and act together in a family

unit. Family size was assessed on the basis of the total number of members in a family. The

number of family members of the respondents ranged from 3-20 with an average of 7.68, which is

much higher than national average family size of 4.35 (BBS, 2011). The family size was

categorized into three groups, i.e. small (below five members), medium (5-8 members) and large

(above 8 members) (Figure 4). About 37 percent of the respondents had the largest family size, and

33 and 30 percent of the respondents had small and medium family size, respectively. The larger

family size in haor area is observed from a study conducted by Parvin and Akteruzzaman (2012).

They also showed that increase in family size would lead to increase in the farming status of the

household and one percent increase in family size will increase the household’s farm and non-farm

income by 0.46 and 3.68 percent respectively.

Figure 3. Distribution of the respondents according to family size.

4.1.4 Farm size

Based on farm size, the respondents were classified into marginal, small, medium and large as

suggested by with Rahman (2007) (Table 4). In the study area, the average farm size was 2.22 ha

which is higher than the national average of 0.62 ha (Krishi Diary, 2011). A study conducted by

Parvin and Akteruzzaman (2012) showed that one percent increase in farm size would lead to an

increase in the household’s farm income by 0.28 percent. However, present study indicates that

most of the respondents (41.7 percent) had small farm size followed by medium (31.7 percent),

large (21.6 percent) and marginal (5 percent) farm size. The majority of the families had marginal

to small farm size plausibly because of land fragmentation due to inheritance. The study area is

surrounded by rivers and haor and subjected to river erosion every year, which drastically reduces

the cultivable land as well as homestead area.

Table 4. Distribution of the respondents according to farm size

Character Categories Respondents Range Mean±SE*

Number Percent

Farm size Marginal (<0.04 ha) 3 5.0

0.08-14.31

2.22±0.02

Small (>0.04 to 0.99 ha) 25 41.7

Medium(1 to 2.99 ha) 19 31.7

Large (3 ha and above) 13 21.6

Total 60 100

*SE-standard error

33%

30%

37%

Small (upto 5 members)

Medium (6-8 members)

Large (>8 members)

16

4.1.5 Farming experience

Farming experience refers to number of years of involvement of respondents in farming activities.

It helps an individual to take correct decision. There was a wide range of farming experience

between 0 and 60 years with an average 26.1 years (Table 5). Among the sample population, 71.7

percent had high farming experience. Only 20 and 8.3 percent had poor and moderate farming

experience, respectively.

Table 5. Distribution of the respondents according to farming experience

Farming experience Respondents Mean±SE

Number Percent

Poor (<15 years) 12 20.0 26.1±0.06

Moderate (16-20 years) 5 8.3

High (>20 years) 43 71.7

Total 60 100

*SE-standard error

4.1.6 Occupation

The villages study area are mostly farmers depending on agriculture for their livelihood. The

occupations of the respondents were broadly categorized into nine groups (Figure 5). Generally an

individual respondent is engaged in one or more than one occupation. Farming followed by

fishing were the major occupations of the respondents. However, a significant number is involved

in day labor, livestock rearing, small business, and rowing boats. Few peoples are engaged in

grocers and handicrafts. A recent study also showed similar results where 70 percent of the

household were involved in fishing for their livelihood in haor area (IUCN, 2011).

Figure 4. Distribution of the respondents according to occupation.

4.1.7 Monthly income

Monthly income of the respondents ranged from less than BDT 1999 to more than BDT 8000 in

2014 and was compared with that of 2002-2004. The respondents’ income was classified into four

categories such as extreme poor, poor, medium and rich (Table 6).

82

70

26

18 1611 9

6 4

0

10

20

30

40

50

60

70

80

90

Farming Fishing Day labor Livestock

rearing

Business Boatman Grocer Service Handicrafts

Per

cent re

spon

den

ts

Occupation

17

Table 6. Changing scenario of monthly income of the respondents over time

Income group

Income level

(BDT)

Respondents (percent)

Year:

2002-2004

Year:

2014

Change

(percent)

Extreme poor <1999 18 10 -44.4

Poor 2000 - 4999 50 45 -10.0

Medium 5000 - 7999 24 33 +37.5

Rich >8000 8 12 +50.0

Information presented in Table 6 also indicates that in 2014 the monthly income of majority of

the respondents (45 percent) ranged between BDT 2000-4999 and were grouped in poor category

followed by medium category (33 percent) having income level of BDT 5000-7999 and rich

category (12 percent) having income level of more than BDT 8000. The extreme poor category

was 18percent having income level of less than BDT 1999. It was observed that the medium and

rich people increased by 37.5 and 50.0 percent, respectively while poor and extreme poor people

decreased by 10 and 44.4 percent, respectively, compared to 2002-2004.

4.2 Land use changes in Sylhet haor

Changes in land use patterns, adoption of rice varieties and cultivation practices over time were

used to assess the land use changes of study area over time.

4.2.1 Pattern of land use change

Land cover or land use was implicit during 2002-2004 and 2014 from respondent’s opinion (Table

7). The permanent fresh water lakes/rivers and cropland (seasonally flooded in monsoon and rice

in winter) are two major land uses existing in the study area. Permanent fresh water lakes/rivers

occupied 49 percent of the total area during 2002-2004 that reduced to 35 percent in 2014 with an

overall reduction of 28.5 percent and at the same period, cropland occupied 18 percent that

increased to 29 percent of the total area with an overall increase of 61.1 percent. Swamp forest and

settlement were 8 and 7 percent, respectively and both the land uses increased to some extent. The

most notable changes of land use pattern in the study area showed that area under cropland,

settlement and swamp forest increased remarkably, while permanent fresh water lakes/rivers and

fallow land decreased.

Table 7. Changes in major land use pattern in the study area over time

Major land use/land

cover

Land use pattern (percent) over time

2002-2004 2014 Change (percent)

Cropland 18 29 +61.1

Swamp forest 8 10 +25.0

Settlement 7 11 +57.1

Lakes and rivers 49 35 -28.6

Fallow land 7 4 -42.9

4.2.2 Change of hydrological status

The present (2014) hydrological situations have been compared with that prevailed in 2002-2004

(Table 8). It is observed that all the respondents used haor water for irrigation during 2002-2004.

Over the years, haor water has been polluted and majority of the respondents (77 percent) reported

that illegal transportation of coal, misuse or use of pesticides, imbalanced dose and frequent use of

chemical fertilizers and throwing domestic wastes were the reasons behind increased water

pollution. Rivers have been carrying heavy loads of silts and other debris from upstream. Quality

18

of drinking water was reported to deteriorate over time. During 2002-2004, majority of the

respondents (71 percent) were satisfied with the quality of drinking water, but in 2014 the

satisfaction level decreased to 50.7 percent which was supported by more than half (65 percent) of

the respondent (Table 8).

Table 8. Changing scenario of hydrological status in the study area over time

Hydrological

status

Changes Respondent’s opinion (percent)

2002-2004 2014 Change (percent)

Sources of

irrigation water

Haor 100 100 0.00

Irrigation scheme 0 0 0.00

Quality of haor

Water

Polluted 13 77 +492

Non polluted 87 23 -73.56

Quality of

drinking water

Satisfied 71 35 -50.70

Not satisfied 29 65 +124.13

Duration of

inundation

April–November (8 months) 31 15 -51.61

May –Mid December (7.5 months) 35 23 -34.28

May– November (7 months) 25 49 +96

Mid May– November (6.5 months) 9 13 +44.4

Flooding

Early flood 5 2 -60

Late flood 2 2 0.00

Flash flood 93 96 +3.22

In the study area, duration of inundation was to decrease over time. About 31 percent

respondents reported that haor area had been inundated for 8 months (April- November) in 2002-

2004, while this statement was currently supported by only 15 percent respondents. In 2014, 49

and 13 percent respondents opined that haor areas are inundated for 7 months (May- November)

and 6.5 months (Mid May- November), respectively, while for 2002-2004 this statement was

supported by 25 and 9 percent respondents, respectively. The reason behind decreasing inundation

period may be due to decrease of water flow from upstream, particularly from different tributaries

originated from Meghalaya hills of India. In case of flooding situation, almost all of the

respondents reported that flash flood is the major natural disaster in the study area and increased

by 3.22 percent over the last 10-12 years. Flash flood is generally caused by heavy and excessive

rainfall and onrush of water from adjacent Assam and Meghalaya hills in India during early

monsoon. Such floods cause immense damage to the standing boro rice, lives and properties every

year and the situation has been aggravating in the haor region due to siltation in downstream over

time.

4.3 Pattern of farming system

Farming system of Bangladesh indicates the homestead as a common feature of all farming

systems from where other enterprises are managed by the farmers. The cropping systems were

divided into field and horticultural crops, while both were again sub-divided into irrigated and

rainfed. The livestock systems were divided into cattle, buffalo, poultry, goat, and sheep, while

poultry was subdivided into chicken, duck, and pigeon. The fisheries systems were mainly of two

types - fish culture and fish catching. Fish cultures were of three types - pond, backyard pond and

rice shrimp culture. Fish catching was divided into catching from river, canal, and haor and from

rice field. The agro-forestry systems were mainly observed in the homestead and field (Hossain et

al.,1991).

4.3.1 Cropping system

Haor farmers practice different types of cropping pattern. In order to find out the extent of

practicing different cropping pattern, adoption index was determined through seven cropping

19

patterns which are being practiced by the haor farmers and were ranked accordingly. Ranking

order of the cropping pattern was identified by adding the specific score given to each pattern. The

adoption score ranged from 2 to 120. Ranking order of the cropping pattern followed by the

respondents is presented in Table 9. Among all the cropping patterns, Boro rice-fallow-

transplanted Aman ranked first position scoring 120 followed by Boro rice-fallow-broadcasting

Aman. Huda (2004) reported that almost 80% of haor area (i.e. 0.68 million ha) is covered by Boro

rice, while only about 10% area is covered by transplanted Aman production. The study area is

mostly dominated by medium high land and transplanted Aman cultivation is very common. Rabi

crop-fallow-fallow score 65 and 16 and they were ranked second and third, respectively. Potato-

fallow- transplanted Aman got lowest score (2) and placed in the last position.

From Table 9, it is evident that the cropping pattern of the haor area is predominantly rice

based followed by rabi crops like tuber, potato and wheat. This might be due to the fact that the

study area was attached with mainland and annual flooding increase the soil fertility and creates

favorable condition for production of these major crops.

Table 9. Extent of practice of cropping pattern by the farmers in the study area

Type of cropping pattern

Extent of practice (N=60) CPAI

Rank

order Much (2) Little (1) Not at all (0)

Boro rice - fallow – T. aman 60 0 0 120 I

Boro rice - fallow – B. aman 5 55 0 65 II

Rabi crops - fallow – fallow 2 12 46 16 III

Rabi frops - jute – fallow 0 5 55 5 IV

Wheat - fallow – T. aman 1 3 56 4 V

Tuber – fallow - T. aman 0 3 57 3 VI

Potato - fallow- T. aman 0 2 58 2 VII

4.3.2 Livestock system

Livestock and poultry are the essential resources of the haor farmers. The peoples of the haor area

are much aware of their livestock and poultry resources as the sector contributes greatly to their

daily diets and draft energy required for land preparation. The respondents along with their

livestock and poultry ownership on the basis of price are categorized following Mahmud (2008)

and presented in Table 10. It is evident that only 25 percent of the respondents did not own any

livestock and poultry resource (Table 10). Data reveals that 35 percent of the respondents had low

ownership of livestocks and poultry resources and about one-seventh of the respondents owned

livestock and poultry resources indicating medium ownership. About one-fourth of the respondents

had high ownership of livestock and poultry resources. These patterns of ownership indicate that

the livestock and poultry resources play an important role to livelihood development and there is

scope of further development of the sector for ensuring food security in future.

Table 10. Distribution of the farmers according to ownership of livestock and poultry on the basis

of price

Category of ownership No. of respondents Percent Mean±SE

No livestock 15 25 22250±3.16

Low (up to BDT.15000) 21 35

Medium ( BDT. 15001-30000) 8 13

High (above BDT. 30000) 16 27

Total: 60 100

20

4.3.3 Fisheries system

Fisheries sector is a source of animal protein and contributes to rural employment and alleviation

of poverty to a great extent. Farmers adopted various system of fishing according to their dietary

needs and income generation. Fishing systems of haor farmers are illustrated in Table 11. It

reveals that fish catching in backyard pond ranked first position, and this is probably because of

the fact that haor area is flood-prone and low-lying, and water remains in their backyard pond for

8-10 months in most of the areas and even throughout the year in some places. Round the year fish

culture in pond ranked second position, fish catching in canal and fish catching in river were

ranked third and fourth, respectively. As haor lands are low-laying areas, every household had

backyard pond which was dug during building homesteads. There is greater scope to bring the

backyard pond under commercial fish culture for income generation for ensuring food security.

There are ample scopes to develop the fishery sector, but it requires timely availability of inputs

like fish fries, feed and credit.

Table 11. Extent of practice of fishing systems by the farmers in the study area

Type of fishing system Extent of practice (N=60) FSAI Rank

order Much (2) Little (1) Not at

all (0)

Fish catching in backyard pond 33 12 15 78 I

Round the year fish culture in pond 24 21 15 69 II

Fish catching in canal 6 39 15 51 III

Fish catching in river 10 28 22 48 IV

4.3.4 Homestead forestry system

Homestead is considered as a lifeboat for the survival of the landless, marginal and small farmers

who don’t have any resources other than the homestead products. On the other hand, forestry

system ensures sound environment through plantation of fruit, timber and fuel wood trees in and

around the homestead as well as in the marginal and fallow land. It also helps the respondents in

raising their income and for improving livelihood pattern. Figures 5-7 showed the distribution of

the respondents according to fruit, timber and fuel wood trees ownerships, respectively following

Mahmud (2008). Finding reveals that every respondent has fruit trees either in the homestead or in

the marginal/fallow or crop field. About three-fourth of respondents owned more than 20 trees.

Small and medium ownership of fruit trees were found 5 percent and 20 percent respondents,

respectively. This pattern of ownership reflects medium to high ownership of fruit trees by the

respondents.

Figure 5. Distribution of the respondents according to ownership of fruit trees.

0%

5%

20%

75%

Ownership having no fruit tree

Small ownership (up to 10 fruit trees)

Medium ownership (11-20 fruit trees)

Large ownership (>20 fruit trees)

21

In case of ownership of timber trees, highest portion (43 percent) of the respondents had large

ownership followed by small ownership (37 percent) and medium ownership (10), while 10

percent have no ownership (Figure 6). This pattern indicates that more than half of the respondents

had medium to high ownership of timber trees. As every farmer has homestead, so there is enough

scope of utilizing some fallow area for homestead agro-forestry. With regard to the ownership of

fuel wood trees, it was observed that about fourth-fifth (81 percent) of the respondents had no

ownership as compared to large ownership (15 percent) and equal portion (2 percent) have small

and medium ownership (Figure 7). This pattern of ownership reflects that the extent of ownership

of fuel wood trees was very low among the respondents.

Figure 6. Distribution of the respondents according to their ownership of timber trees.

Figure 7. Distribution of the respondents according to their ownership of fuel wood trees.

4.4 Homestead soil productivity

4.4.1 Homestead soil nutrient status

Soil fertility means ability of soil to supply nutrients to the plants, whereas soil productivity refers

to ability of soil to produce crops. Effort has been made to measure soil productivity of homestead

areas of the respondents by analyzing topsoil and subsoil chemical properties. The respondents

were classified into six categories viz. very low, low, medium, optimum, high and very high based

on the interpretation of soil test values of pH, organic carbon, nitrogen, phosphorus, potassium,

10%

37%

10%

43%

Ownership having no timber tree

Small ownership (up to 10 timber trees)

Medium ownership (11-20 timber trees)

Large ownership (>20 timber trees)

81%

2%

2% 15%

Ownership having nofuel wood tree

Small ownership (up to 10

fuel wood trees)

Medium ownership (11-20 fuel wood trees)

Large ownership (>20 fuel wood trees)

22

zinc, sulfur as indicated in the Fertilizer Recommendation Guide 2012. Distribution of respondents

according to their soil test value interpretation is shown in figures 8-14.

Irrespective of soil layers, most of the homestead soils are slightly acidic (Figure 8). A

significant number of homestead soils are strongly acidic in nature. Very few were neutral in

reaction. However, there is no homestead topsoil having very strong acidity, while five homestead

soils showed strong acidity. In general, topsoil and subsoil pH differences in the homestead soils

were not remarkable.

Figure 8. Distribution of farmer’s homestead according to soil test value interpretation of soil

reaction (pH) based on critical limits.

In case of topsoil, the highest portion of the farmer’s homestead contained low organic matter

followed by medium organic matter (Figure 9). Although some of the homesteads soil were having

very low organic carbon, there was none having high or very high organic carbon containing

homestead. In case of subsoil, the highest portion of the farmers' homestead contained low organic

carbon followed by very low organic carbon. However, some homesteads soil were having

medium organic carbon content. In general, the homestead soils were deficit in organic carbon

content in both topsoil and subsoil. However, topsoil contained comparatively higher organic

carbon than subsoil. This might be due to addition of organic matter in the topsoil from plant

debris and household waste products.

Note: OM (percent)=Very low>1;Low;1-1.7; Medium;.1.8-3.4; High;3.5-5.5;Very high;>5.5

Figure 9. Distribution of farmer’s homestead according to soil test value interpretation of organic

carbon based on critical limits.

6

2826

0 0

17

28

15

0 00

5

10

15

20

25

30

Very low low Medium High Very high

Nu

mb

er o

f re

spo

nd

ents

Ogranic matter content

Topsoil Subsoil

5

19

32

4

0

25

33

2

0

5

10

15

20

25

30

35

Very strongly acidic (<4.5)

Strongly acidic (4.6-5.5)

Slightly acidic (5.6-6.5)

Neutral (6.6-7.3)

Nu

mb

er o

f re

spo

nd

ents

Soil reaction (pH)

Topsoil

Subsoil

23

In case of topsoil, most of the homesteads contained low nitrogen content followed by medium

amount of nitrogen (Figure 10). Some of the homesteads had very low as well as optimum content

of nitrogen. Like organic carbon, there was none having high or very high nitrogen containing

homestead soil. In case of subsoil, majority of the soils contained low amount of nitrogen, but

followed by very low amount of nitrogen. However, some homestead soils contained medium

amount of nitrogen. Both topsoil and subsoil of the homesteads were deficit in nitrogen contents.

However, nitrogen content remarkably decreased in subsoil compared to topsoil indicating

accumulation of nitrogen in topsoil probably due to addition of organic matter from plant debris

and waste form household sources.

Note: N (percent)=Very low: ≤0.09; Low: 0.091-0.18; Medium: 0.181-0.27; Optimum: 0.271-0.36; High:

0.361-0.45; Very high: >0.45

Figure 10. Distribution of farmer’s homestead according to soil test value interpretation of nitrogen

based on critical limits.

Figure 11 reveals that about 50 percent of the homestead topsoil contained very high amount

of phosphorus (P), although P content varied from very low to very high. However, P content of

topsoil was optimum to very high in 62 percent of the homestead indicating that only 38 percent

homestead soils were deficit in P content. In most cases, subsoil P content remarkably decreased in

each category from low to very high. In contrast, P content at very low category increased from 4

homesteads to 25 homesteads indicating a decreasing trend in P content in subsoil.

Note: P (µg/g Soil): Very low=≤7.5; Low=7.51-15.00; Medium=5.1-22.5; Optimum=22.51-30.0;

High=30.1-37.5; Very high=>37.5

Figure11. Distribution of farmer’s homestead according to soil test value of phosphorus based on

critical limits.

6

29

19

6

0 0

17

30

12

1 0 00

5

10

15

20

25

30

35

Very low low Medium Optimum high Very high

Num

ber

of

resp

ond

ents

Nitrogen contents

Topsoil Subsoil

4

12

7 7

1

29

25

8

3 2 2

20

0

5

10

15

20

25

30

35

Very low low Medium Optimum high Very high

Num

ber

of

resp

ond

ents

Phosphorus content

Topsoil Subsoil

24

In general, potassium (K) content of topsoil in 67 percent homestead was optimum to very

high, while 33 percent of the homestead was deficit in K content (Figure 12). About 48 percent of

the homesteads contained a very high amount of K. In contrast, 23 percent homestead soil

contained very low to low amount of K. Potassium content of subsoil in optimum to high

categories decreased much in 52 percent homestead when compared with topsoil. On the other

hand, the number of homestead containing very low to medium amount of K in subsoil increased

indicating that subsoil is more deficit in K content than topsoil.

Note: K (meq/100g)= Very low=≤0.09; Low=0.091-0.18; Medium=0.181 0.27; Optimum= 0.271-0.36;

High=0.361-0.45; Very high=>0.45

Figure12. Distribution of farmer’s homestead according to soil test value of potassium based on

critical limits.

Irrespective of layers, the homestead soil contained a very high amount of Zinc (Zn) (Figure

13). About 87 percent homestead soils contained optimum to very high amount of Zn, while only

13 percent of the homesteads was deficit in Zn contents. Even no soils contained very low amount

Note: Zn(µg/g soil)=Very low=≤0.45; Low=0.451-0.9; Medium=0.91-1.35; Optimum=1.351-1.8;

High=1.81-2.25.5;Very high=>2.25

Figure 13. Distribution of farmer’s homestead according to soil test value interpretation of zinc

based on critical limits.

2

12

6 6 5

29

4

17

8

5 4

22

0

5

10

15

20

25

30

35

Very low low Medium Optimum high Very high

Nu

mb

er o

f re

spo

nd

ents

Potassium content

Topsoil Subsoil

02

6 5 5

42

0

5

96

3

37

0

5

10

15

20

25

30

35

40

45

Very low low Medium Optimum high Very high

Num

ber

of

resp

ond

ents

Zinc content

Topsoil Subsoil

25

of Zn. Zn content of subsoil under high to very high categories decreased much when compared

with topsoil. On the other hand, the number of homestead containing low to optimum amount of

Zn in subsoil increased compared to topsoil indicating subsoil is more deficit in Zn content relative

to topsoil.

Generally, most of the topsoil contained high to very high amount of sulfur (S) (Figure 14).

Only 10 percent of the homestead topsoil contained very low to low amount of S. However,

subsoil contained comparatively less amount of S. For instance, where 67 percent topsoil was

having with very high amount of S, there only 13 percent subsoil contained this amount. However,

S content of subsoil for 51 homesteads increased in low to high categories indicating a decreasing

trend in subsoil S contents compared to topsoil.

Note: S (µg/g soil)=Very low≤7.5; Low: 7.51-15.00; Medium: 15.1-22.5; Optimum: 22.51-30; High: 30.1-

37.5; Very high: >37.5.

Figure 14. Distribution of farmer’s homestead according to soil test value interpretation of sulfur

based on critical limits.

4.4.2 Comparison between topsoil and subsoil nutrients

The comparison profile of topsoil and subsoil nutrient contents in the homestead soil is presented

in Table 12. In general, topsoil nutrient status is much higher than subsoil. Organic matter and N

content of topsoil were medium and low respectively, whereas, P, K. Zn and S contents were very

high. Except K, all the nutrients of subsoil were significantly lower than the topsoil. Among the

nutrients, S and P contents were much less corresponding to 50.3 and 37.2 percent less compared

to other nutrients. The results suggest that there is depletion of organic matter and nitrogen was

well as other nutrients. The reasons might be due to the higher rate of organic matter

decomposition under the prevailing hot and humid climate, use of lesser quantities of organic

manure, little or no use of green manures.

Pearson correlation (r) was computed in order to measure the relationship between soil nutrient

variables. The coefficient of correlation (r) was used to test the null hypothesis regarding the

relationship among concerned variables. The null hypothesis was formulated as Ho: There is no

relationship among soil nutrient variables. The correlation values indicate there is no relation

between S and other soil nutrients. However, there were significant relationships between other

nutrients, The relationships were strong and significant between P and K (r=0.65) and Zn and other

nutrient elements.

Coefficient of correlation was computed in order to explore the relationships between the soil

chemical properties and fruit yield of seven plant species namely Banana (Musa acuminate),

Coconut (Cocos nucifera), Guava (Psidium guajava), Jackfruit (Artocarpus heterophyllus), Mango

(Mangifera indica) Papaya (Carica papaya), Lemon (Citrus limon) (Table 14). The relationships

42 2

57

40

1

5

16

20

108

0

5

10

15

20

25

30

35

40

45

Very low low Medium Optimum high Very high

Nu

mb

er o

f re

spo

nd

ents

Sulfur content

Topsoil Subsoil

26

between soil nutrients and fruit yields indicate that P, K and Zn contents are the most important

elements contributing to increased fruit production.

Table 12 Comparison of topsoil and subsoil nutrient contents in the homestead areas

** Significant at 0.01 level of probability

Table13. Correction coefficient between soil nutrients contents

Variables N P K OC Zn S

N 1.00

P 0.30* 1.00

K 0.44** 0.65** 1.00

OC 1.00** 0.30* 0.44** 1.00

Zn 0.55** 0.67** 0.65** 0.55** 1.00

S 0.12 0.15 0.10 0.12 0.18 1.00

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level

(2-tailed).

4.4.3 Soil nutrient and fruit yield relationship

Soil reaction: In general, there was no significant relationship between soil reaction (pH) and

yield of fruit species except the topsoil pH in case of banana. The correlation coefficient values

indicate that there were very weak negative relationships between pH and fruit yield indicating pH

had no remarkable contribution to increase fruit yield. Only in banana, relationship was positive

for topsoil that indicates higher pH might have favorable effect on the growth and yield of banana.

The study also reveals that there is no remarkable difference in the relationship for topsoil and

subsoil pH with the fruit yield.

Organic matter and nitrogen: Organic matter (OM) or nitrogen content of topsoil had

positive effects on yield of fruits species. Except banana, there were significant relationships

Soil properties Mean±SE %

Change

Significance

(2-tailed) Topsoil Subsoil

Organic matter (%) 1.71±0.01

(Medium)

1.37±0.01

(Low)

-19.9 0.001**

Nitrogen (%) 0.17±0.004

(Low)

0.14±0.004

(Low)

-17.6 0.001**

Phosphorus (µg/g soil) 41.21±0.09

(Very high)

25.87±0.09

(Optimum)

-37.2 0.000**

Potassium (meq/100g

soil)

0.56±0.01

(Very high)

0.49±0.01

(Very high)

-12.5 NS

Zinc (µg/g soil) 5.81±0.039

(Very high)

4.46±0.04

(Very high)

-23.2 0.015**

Sulfur (µg/g soil) 56.47±0.01

(Very high)

28.08±0.06

(Optimum)

-50.3 0.000**

27

between soils OM or N and fruit yield and the relationships were stronger for topsoil OM or N

status. The exception was for Jackfruit, where the relationship between subsoil OM or N content

and fruit yield was significant. The OM or N and S contents of topsoil contribute more to fruit

yield. This might be due to the fact that organic matter has direct and indirect effect on the

availability of other nutrients and improving soil physical and biological properties that may

subsequently enhance growth and yield of fruit trees. Generally, N helps rapid growth of fruit

trees, increases yield and improving the quality of fruits.

Phosphorus: Irrespective of topsoil and subsoil, phosphorus (P) content showed significant

correlation with fruit yield of all the species. Such relationships were much strong for banana,

coconut, jackfruit and guava. In case of lemon and papaya, P content for topsoil had strong

significant relationship with fruit yield, but for subsoil the relationships were weak. Only

exception was mango where there was no significant relationship between P content of topsoil and

fruit yield, although there existed a weak relationship for subsoil P content. Phosphorus helped

fruit trees with the transformation of solar energy into chemical energy, proper plant maturation

withstanding stress. It also encouraged blooming and root growth of fruit trees.

Potassium: Potassium (K) contents of both topsoil and subsoil showed strong significant

correlations with fruit yield of all the species. Only exception was for subsoil of mango, where the

relationship was weak. Interestingly, the other fruit species were having much stronger correlations

between K contents and fruit yield for subsoil compared to topsoil indicating subsoil K content

contributes much in maintaining higher fruit yield. Potassium helped in the building of protein,

photosynthesis, fruit trees quality and reduction of diseases. Potassium is supplied to fruit trees by

organic materials. It also improves root growth and seed production of fruit trees.

Zinc: In general, zinc (Zn) contents of both topsoil and subsoil showed significant correlations

with fruit yield in all the plant species. Only the subsoil Zn content had no significant relationship

with the yield of coconut and papaya. The fruit yield relationship with the soil Zn contents were

comparatively stronger in topsoil compared to subsoil, This indicates that the maintenance of

topsoil Zn content is much important for sustainable fruit yield in the homestead area. Zinc helped

with the transformation of carbohydrates and regulated consumption of sugars and fruit trees

growth.

Sulfur: The relationships between soil sulfur (S) and yield of fruit species were mostly

insignificant. However, there existed significant relationships between topsoil S and fruit yield of

lemon, papaya and jackfruit. In most cases, the correlation coefficient values between S and fruit

yield showed very weak relationships indicating S content had very little effects on fruit yield. The

study also reveals that there were some weak and negative relationships for subsoil S compared to

topsoil S content with the fruit yield. Sulfur helped fruit trees in chlorophyll formation, with

vigorous plant growth and resistance to cold. It also improves root growth and seed production of

fruit trees. Sulfur helped fruit trees in chlorophyll formation, with vigorous plant growth and

resistance to cold.

Table 14. Correlation co-efficient between soil chemical properties and yield of major fruit trees

Variables

Correlation co-efficient (r) with fruit yield

Banana Coconut Lemon Papaya Mango Jackfruit Guava

Topsoil Subsoil Topsoil Subsoil Topsoil Subsoil Topsoil Subsoil Topsoil Subsoil Topsoil Subsoil Topsoil Subsoil

pH 0.30* -0.18 -0.15 -0.12 -0.31* -0.1 -0.23 0.01 -0.18 -0.13 -0.21 -0.16 0.07 -0.06

OC 0.21 -0.11 0.29* -0.01 0.29* 0.33** 0.38* 0.17 0.83** -0.19 0.21 0.38** 0.26* -0.22

N 0.21 -0.11 0.29* -0.01 0.29* 0.33** 0.38* 0.17 0.83** -0.19 0.21 0.38** 0.26* -0.22

P 0.51** 0.66** 0.44** 0.42** 0.55** 0.32* 0.44** 0.31* 0.18 0.27* 0.57** 0.41** 0.40** 0.74**

K 0.44** 0.49** 0.54** 0.85** 0.51** 0.66** 0.48** 0.75** 0.34** 0.30* 0.48** 0.55** 0.40** 0.40**

Zn 0.41** 0.33* 0.38** -0.14 0.49** 0.34** 0.42** 0.20 0.38** 0.36** 0.51** 0.43** 0.43** 0.36**

S -0.09 -0.14 0.20 -0.17 0.44** -0.07 0.31* 0.10 0.08 -0.17 0.38** -0.05 -0.05 -0.01

*Correlation is significant at the 0.05 level (2-tailed), **Correlation is significant at the 0.01 level (2-tailed).

28

29

4.5 Adoption of farming technology

The respondents were grouped into three categories based on scores of farming technology

adoption. Various farming technologies adopted in crops, livestock, fisheries and homestead

agroforestry sectors have been included. The adoption scores of farming technologies ranged from

28.7 to 61.1 with an average of 47.4 (Table 15). A medium level of farming technologies was

adopted by 78.4 percent respondents, whereas 18.3 percent respondents had low and only 3.3

percent had high level of adoption.

Table 15. Distribution of the respondents according to adoption of farming technology

Category

No. of respondents (N=60) Mean and range

SD

Number Percent

Low use (up to 40) 11 18.3 Mean: 47.4±0.04

Range: 28.7-61.1

6.58

Medium use (41-60) 47 78.4

High use (60 & above) 2 3.3

Total 60 100.0

For better understanding the adaptation of a particular farming technology, a technology

adoption index (TAI) was computed and provided in Tables 16-19. The computed TAI for crop

management sector is shown in Table 16. Among nine important crop management technologies,

the uses of chemical fertilizers, low lift pumps (LPP), power tillers, and power threshers are most

important technologies ranking one to four, respectively. The respondents are much aware of using

chemical fertilizers assuming their soils having low fertility. The low prices and the availability of

chemical fertilizers are encouraging the farmers to use chemical fertilizers for higher crop yield.

LLP is the major irrigation equipment frequently being used in cultivating boro rice, a major crop

in rice-based cropping system. Wheat, vegetables and other rabi crops are also grown in the area.

LLP is promoted satisfactorily in the area because it is suitable and cost effective. For land

preparation use of power tiller is also widespread in the area. Now, the farmers are also using

power thresher for post-harvest operation to save time, money and labor. The use of hand sprayer

for controlling pest and diseases followed by integrated pest management (IMP) methods has also

been popularized in the area. The cultivation of modern variety of crops using quality seeds have

also been practiced by the farmers. However, the use of organic fertilizer is not satisfactory at the

farm level, though the soil organic matter content is mostly very low to low.

Table 16. Technology adoption index (TAI) in crop sector

Name of technology

Level of adoption behavior (N=60) TAI Rank

order

Freque-

ntly (3)

Occasion-

ally (2)

Rarely

(1)

Not at

all (0)

Chemical fertilizers 32 24 4 0 148 I

Low lift pump 36 14 10 0 146 II

Power tiller (diesel) 27 29 4 0 143 III

Power thresher 34 10 16 0 138 IV

Hand sprayer 21 28 8 3 127 V

Modern/improved variety 20 24 12 4 120 VI

Use of quality seed 6 15 35 4 83 VII

IPM method for pest control 3 12 36 9 69 VIII

Use of organic fertilizer 0 4 1 55 9 IX

30

The TAI in livestock and poultry is shown in Table 17. The rearing of improved breed of

poultry is the most adopted technology in the homestead level. This might be due to easy

involvement of female members and children of the family in poultry rearing as well as the

availability of poultry feed in haor areas. The use of balanced diet, beef fattening, vaccination of

poultry bird, improved housing, use of modern breed ranking from second to sixth, respectively

are also important technologies reasonably adopted in the area. Besides, rearing of goat and pigeon

is practiced although the use of urea molasses block for beef fattening and artificial insemination

in livestock are rarely practiced.

Table 17. Technology adoption index (TAI) in livestock and poultry sector

Name of technology

Level of adoption behavior (N=60) TAI Rank

order Freque-

ntly (3)

Occasion-

ally (2)

Rarely

(1)

Not at

all (0)

Rearing poultry variety 10 22 6 22 80 I

Using balanced diet 2 13 21 24 53 II

Beef fattening 6 12 9 33 51 III

Vaccination of poultry bird 0 13 23 24 49 IV

Improved housing 0 12 21 27 45 V

Use of modern breed 4 7 15 34 41 VI

Goat rearing 0 5 17 38 27 VII

Pigeon rearing 3 6 3 48 24 VIII

Beef fattening urea molasses 0 0 16 44 16 IX

Artificial insemination 0 1 5 54 7 X

The computed TAI of fisheries management technologies on individual aspects of different

technologies is shown in Table 18. It reveals that poly culture of fish is the widely used

management technology followed by cultivation of quick growing fruit trees on the pond banks,

and applying supplementary feed for fish. The use of balanced diet and modern breed are also two

important technology usually practiced by the respondents. The production of fodder on the bank

of the ponds, the proper water management for fish culture and urea molasses apply in the pond

were not widely practiced fishery management technology. From the ranking order of different

technologies, it reveals that adoption of technology for fisheries management is not satisfactory in

haor areas because out of eight important technologies only three have been frequently used. The

reasons behind such low adoption might be due to unavailability of modern breed of fishes in haor

areas. The majority of the respondents catch fish from backyard pond, river and canals. Lack of

transport facilities, lack of commercial fish cultivation technique, lack of knowledge on

commercial fish culture, and lack of information sources were also assumed for low adoption of

fish management technology.

The computed TAI regarding the adoption of homestead agro-forestry management

technologies is shown Table 19. The cultivation of fast growing forest tree followed by cultivation

of vegetables and fruit trees in homestead areas have been widely practiced in the area. Farmers

are much aware of utilizing homestead fallow land where family labor can easily be utilized.

Forest tree and vegetable cultivation became popular to the farmers for their easy cultivation and

management, and higher profitability. The pruning practice of fruit trees were adopted as a

technology in the area for getting higher yield from the fruit trees. The cultivation of spices and

condiments in shady place are also practiced in the area. Other technologies according to

descending ranking adopted in the area are production of vegetable seeds, employing modern

method of harvesting, food processing for sell and raise seedling in the nursery.

31

Table 18.Technology adoption index (TAI) in fishery sector

Name of technology

Level of adoption behavior (N=60) TAI

Rank

order Freque-

ntly (3)

Occasio-

nally (2)

Rarely

(1)

Not at

all (0)

Poly culture of fish 29 15 0 16 117 I

Growing fruit trees on pond bank 14 22 9 15 95 II

Apply supplementary feed 3 20 22 15 71 III

Using balanced diet 0 16 29 15 61 IV

Use of modern breed 0 17 23 20 57 V

Fodder production on pond bank 0 10 28 22 48 VI

Proper water management 0 4 26 30 34 VII

Urea molasses apply in pond 0 0 12 48 12 VIII

Table 19. Technology adoption index (TAI) in homestead agroforestry sector

Name of technology

Level of adoption behavior TAI Rank

order Freque-

ntly (3)

Occasio-

nally (2)

Rarely

(1)

Not at

all (0)

Cultivating fast growing forest tree 24 30 6 0 138 I

Cultivating homestead vegetables 19 36 3 2 132 II

Cultivation of improved fruit trees 24 24 5 7 125 III

Pruning of fruit trees 8 39 13 0 115 IV

Cultivating spices and condiments 12 36 3 9 111 V

Production of vegetable seed 0 21 28 11 70 VI

Modern method of harvesting 0 10 26 24 46 VII

Food processing for sell 0 2 23 35 27 VIII

Raise seedling in the nursery 0 3 13 44 19 IX

4.6 Food security status of households

Food security status was measured on the basis of consumption of different food items, calorie

intake, the number of meals taken per day by the family members of the respondent’s household.

4.6.1 Food consumption

Food consumption is one of the important factors for measuring the social development of a

person. Usually a person’s income and health consciousness improve his/her food consumption

behavior in terms of consuming nutritious food. Food intake was measured as consumption of food

items by respondents’ households. The survey included twelve most essential food items like rice,

wheat, tuber, pulses, vegetables, fruit, fish, meat, milk, sugar, spices and edible oil (Table 20).

The respondents were asked to give information about the quantity of twelve food items they

used to consume in a month by all of his/her family members. It reveals that the respondents'

dietary habit is cereal-based and rice is the principal food item. The average rice intake was 32

percent higher than the requirement, although there were huge variations in rice consumption

among the respondents. Of all the essential elements in food items, 42.91 percent is carbohydrate.

Persuading the people to reduce rice consumption from the current level of 463.20 gm to 350 gm

would not be very easy and would require rapid, broad-based economic growth and reduction of

inequalities. The vegetable consumption is more than 20 percent which is assumed to be

32

satisfactory. However, there were much variations in consumption of food items among the

respondents. Even some of the respondents did not consume any wheat, tuber or meat. A shift in

dietary habit is required to eradicate micronutrient deficiency of the people.

Table 20. Consumption of food items by the respondents

Food items Food consumption

(kg/month/

household)

Food

consumption

(g/day/person)

Percent Range

(g/day/person)

Rice 105.97 463.20 37.72 250-714

Wheat 7.48 37.63 3.06 0-238

Tuber 5.15 26.11 2.13 0-275

Pulses 3.75 18.36 1.50 3.846-55.55

Vegetables 50.03 250.39 20.39 7-750

Fruit 19.09 98.71 8.04 12.8-333.33

Sugar 3.77 16.52 1.35 6.67-25

Fish 23.01 108.67 8.85 23.81-266.66

Meat 10.84 55.06 4.48 0-133.33

Milk 17.04 95.41 7.77 5.5-500

Spices 7.28 34.27 2.79 15.68-76.19

Edible Oil 5.06 23.49 1.91 13.33-60

Total 258.47 1227.85 100

4.6.2 Food security status as calorie intake

Food security status was measured by calorie intake per person per day. There are various

dimension of livelihood status change as well as poverty alleviation. Food consumption is one of

them. Effort has been made to measure Kcal intake by the respondents’ family members. Based on

the calorie intake the respondents were classified into four categories viz. much below optimum,

below optimum, optimum and above optimum according to Hossain (2009). Distributions of

respondents according to their calorie intake (per capita/day) are shown in Table 21. The daily

calorie intake ranged from 1510 to 3840 Kcal/capita with an average of 2073 Kcal/capita

indicating much below the optimum level. It reveals that about 65 percent of the respondents were

found to take calorie below the optimum level; even one-third of the respondents' calorie intake

was much below of optimum. The calorie intake level indicates that the respondents have

possibility of suffering from malnutrition.

4.6.3 Food security status as access to food

The food security status was measured by another dimension i.e. the number of full meal taken

per day over the month of a year. The study area is prone to early, late flooding and other natural

hazards and there is possibility of decreasing the number of full meals taken per day specially for

landless, marginal or small farmers. Number of full meals taken by the family members/day is

shown in Table 22. Under normal situation, cent percent of the family members used to take three

meals per day. However, during adverse situation, 83.33 percent of the family members of the

respondents could take three meals and about 16.67 percent took two meals per day. This might be

due to damage of crops and livestock, lack of employment and income generation activities for

both male and female members of the households.

4.6.4 Contribution of farm enterprises towards household food security

Farmers in haor area operate various farming enterprises i.e. rice, wheat, chili, potato, fisheries,

livestock, poultry, fruits, trees, and spices in their land holdings. Contribution of farming

enterprises has been seen as the part of the dietary needs being satisfied with their farm produces

and finally expressed as percentage. The contribution of farming enterprises of the respondent to

33

their household food security is illustrated in Table 23. The observed range of contribution varied

from 0.45 to 1659 percent with an average of 84.2 percent. Among the respondents, 48.3 percent

received high level of contribution, while 10 percent and 41.67 percent of them received medium

and low level of contribution, respectively from their farming enterprises towards household food

security.

Table 21. Food security status of the respondents according to calorie intake

Categories

Number Percent Mean SD

Range (Kcal/

capita/day

Much below optimum

(upto1800 kcal/capita/day)

14 23.33 2073

340

1510-3840

Below optimum

(>1800-2122 kcal/capita/day)

25 41.67

Optimum

(>2122-2444 kcal/capita/day)

17 28.33

Above optimum

(>2444 kcal/capita/day)

4 6.67

Total 60 100

Table 22. Distribution of the respondents based on the number of meal taken per day

Status of access to food Normal situation Adverse situation

No. of

respondents

Percent No. of

respondents

Percent

Three meals/day 60 100 50 83.33

Two meals/day 00 00 10 16.67

One meal/day 00 00 00 00

Table 23. Contribution of farming enterprises to household food security

Categories Number Percent Mean SD

Low (below 33) 25 41.7 84.2±94.3

Observed Range

(percent)=0.45-1659

Medium ( 33 to 67) 6 10.0

High (above 67) 29 48.3

Total 60 100

The main reason behind high range and standard deviation of the respondents might be due to

land ownership and ownership structure of different farming enterprises. Most of the respondents

had land area of 0.2 to 1.00 ha. This land was not completely owned by the respective respondents

rather cultivated as sharecropping, lease and mortgaged. In case of sharecropper small farmers,

decision making capacity retained to the land owners. Consequently, crop diversification and

intensification could not be adopted by the respondents which lead to lower household food

security.

Overall contribution of the farming enterprises to the respondent farmers’ household food

security has been further partitioned into major farming enterprises which is presented in Table 24.

Among the five major sectors of farming enterprises, crop sector alone contributed 63.5 percent to

34

the household food security followed by fisheries that contributed 23 percent. The other enterprises

i.e. livestock, fruits and homestead forestry contributed 18.3, 13.6 and 12.4 percent respectively.

Table 24. Contribution of the major farming enterprises to the respondents’ household food

security

Farming enterprises Range (percent) Mean

Possible Observed

Crops Unknown 0.34-867.0 63.5±0.19

Livestock Unknown 0-242.2 18.3±0.11

Fisheries Unknown 0-342.0 23.0±0.15

Homestead forestry Unknown 0-92.5 12.4±0.08

Fruits Unknown 4.2-330.9 13.6±0.13

For further clarity of the contributions of major farming enterprises to the household food

security, a pie-graph has been made (Figure 15). Findings in Figure 15 show that crop enterprise

alone contributed 59 percent out of five major sectors of farming enterprises to the respondents’

household food security. Above15 percent contribution was obtained from fish culture, 12 percent

from livestock rearing, and 9 percent from fruit trees, 8 percent from homestead forestry.

These findings conclude that farmers in the study area usually given more emphasis on crop

cultivation as the prime means for their household food security. Contribution of different farming

enterprises to the household food security do not fulfill totally. This meant that the rest percent of

the annual dietary needs of the respondents’ families remain unsatisfied. It means that the haor

land farmers could not achieve the expected contribution from their farming enterprises even one-

fourth of households remained far from food security as their calorie intake was much below than

the required amount.

Figure 15. Comparative contribution of farming enterprises to the respondents’ household food

security.

4.7 Problem confrontation of the haor land farmers

Haor land farmers used to face many problems socially and individually. In order to find out the

problem confrontation of the haor land farmers, problem confrontation was determined through 16

problems which might be faced by the respondents of the haor homestead farmers through focus

group discussion (FGD). Rank order of the problems was done by adding the specific score given

to each problem. The problem score ranged from 20 to 114. Rank order of the problems faced by

the respondents is presented in Table 24. Data indicates that losses due to natural calamity got the

highest score and ranked first among the problems. Generally haor areas are highly prone to early,

Crops

59%Fisheries

13%

Llivestock

11%

Homestead

forestry

9% Fruits

8%

35

late and flash flood, As a result, the crops as well as human, livestock and other biological

organisms are subjected to be victim of natural calamity. It was also reported that lack of flood

control measures associated with lack of short-duration crop varieties is the major hindrance to the

adoption of potential cropping patterns in haor area (Alam et al., 2010).

Table 25. Problem confrontation index (PCI) of study area farmers

Problems

Extent of problem (N=60) PCI

Rank

order Much

((2)

Little

(1)

Not at

all (0)

Losses due to natural calamity 55 4 1 114 I

High price of inputs 41 18 1 100 II

Inadequate supply inputs 46 7 7 99 III

Lack of storage facilities 43 12 5 98 IV

Lack of marketing facilities 39 16 5 94 V

Problems in getting bank credit 32 25 3 89 VI

Lack of transport facilities 33 23 4 89 VII

Low price of product 36 15 9 87 VIII

River bank erosion 24 27 9 75 IX

Lack of change agent contact 24 25 11 73 X

Malnutrition 22 28 10 72 XI

Infertility of soil 21 26 13 68 XII

Absentee land lord system 19 28 13 66 XIII

Lack of land management technology 13 15 32 41 XIV

Lack of electricity 12 15 33 39 XV

Irregular relief supply 4 12 44 20 XVI

High input cost and inadequate supply of inputs were identified as other important problems.

Farmers need to purchase required inputs for their agricultural and other production sector.

Sometime input dealers and agencies cheat the farmers by demanding high price for inputs. Lack

of storage facility was also a problem. Sometimes respondents produce excess vegetable and other

perishables, which they could not sell and consume. So, large amount of produces were in wastage

loss. The respondents had no technical knowledge of preservation and value addition of their

products.

Lack of marketing facility was another vital problem. Respondents are bound to sell their

produces in the local market due to lack of transport facilities. So they do not get fair price.

Unavailability of bank loan is another important problem of the study area and respondents

initially need financial support to start farming activities for which they need to borrow from bank.

Lack of proper contact with the change agents involved in facilitating development activities was

another important problem. Because of inadequate number of extension workers in the study area,

important modern technologies cannot spread easily to the haor farmers. During flooding season,

about one-third of the households usually used to face food insecurity and they are dependent on

relief both from GO and NGOs sectors.

36

CHAPTER V

SUMMARY AND CONCLUSIONS

The study reveals that majority of the farmers in the study area of Sylhet haor were aged having

higher level of education, large family size but small farm size, and high farming experience. The

economic condition of the farmers greatly changed during the year from 2002-2004 to 2014. This

time many of the farmers have been found to switch over from low income group to high income

group. Land use and land cover also changed a lot for this period. A vast area of lakes and rivers,

and fallow land have been transformed to cropland, swamp forest and settlement. Land inundation

period decreased to one and half months, but incidence of flash flood increased. Water pollution

increased and drinking water quality decreased. There exists an acute shortage of fuel wood at

household level.

There were huge variations in nutrient content of homestead soil. In general, soil is very low

to low in N contents, very rich in P content, particularly in subsoil. Soil is also rich in K, very rich

in S content particularly in topsoil and much rich in Zn content. Except K, topsoil and subsoil

nutrient contents have significant relationships. Fruit yield had strong significant relationship with

organic carbon, N, P, K and Zn contents of both topsoil and subsoil. Technology adoption index

(TAI) was much higher for cultivation of vegetables, plantation of fruit and tree species in the

homestead area. Rice is the dominant crop in the area and found to be the principal food item

followed by vegetables, fish, fruit and milk. Rice intake rate was found higher than recommended

amount, although the total calorie intake was below optimum level. Three-fourth of the annual

dietary requirement of the farm family is fulfilled from farming enterprises. The major problems of

the study area were losses of farming enterprises due to natural calamities, high price and

inadequate supply of agricultural inputs. Based on the above findings, the following conclusions

may be drawn:

(i) For getting accurate picture of the household-based food security in the entire haor area,

more spatial and temporal data on the availability of resources and their utilization pattern

needs to be generated;

(ii) There are ample scopes of utilizing fringed land resulting from siltation and fallow land

under homestead area for increasing food production;

(iii) Detailed appraisal of homestead resources including land availability, plant species

diversity and other resource-based is also important. The homestead resources

management applying appropriate technologies and increasing farmers' managerial

capability may contribute to increase food production for attaining food security at

household level;

(iv) The participation of the community people to local, regional and national level planning

and sustainable utilization of resources are vitally important for the development of haor

area; and

(v) Various awareness building programs should be undertaken for the local community to

utilize homestead resources with a view to increase their contribution to household level

food security.

37

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