Russian Journal of Agricultural and Socio-Economic Sciences, 2013, №1 (13) Январь


ФЕДЕРАЛЬНАЯ СЛУЖБА ПО НАДЗОРУ В СФЕРЕ СВЯЗИ, ИНФОРМАЦИОННЫХ ТЕХНОЛОГИЙ И МАССОВЫХ КОММУНИКАЦИЙ (РОСКОМНАДЗОР)

   РОССИЙСКИЙ ЖУРНАЛ СЕЛЬСКОХОЗЯЙСТВЕННЫХ И СОЦИАЛЬНО                   ЭКОНОМИЧЕСКИХ НАУК

RUSSIAN-ENGLISH JOURNAL



            Russian Journal of Agricultural and Socio-Economic Sciences



№1 (13), January 2013


ISSN 2226-1184, http://www.rjoas.com





                ciardring)

СОДЕРЖАНИЕ

     Российский журнал сельскохозяйственных и социальноэкономических наук

                            выпуск январь

М.С. Рахман
SOCIO-ECONOMIC DETERMINANTS OF OFF-FARM ACTIVITY PARTICIPATION IN BANGLADESH

Б. Цазовачии, Ц. Мутами, Д. Бовора COMMUNITY GARDENS AND FOOD SECURITY IN RURAL LIVELIHOOD DEVELOPMENT: THE CASE OF ENTREPRENEURIAL AND MARKET GARDENS IN MBERENGWA, ZIMBABWE

М. Мкпадо
SERVICE TRADE AND NON-OIL EXPORT IN NIGERIA

  К.М. Куворну, М. Сулейман, П.К. Амегаши ANALYSIS OF FOOD SECURITY STATUS
OF FARMING HOUSEHOLDS IN THE FOREST BELT OF THE CENTRAL REGION OF GHANA

Г.Д. Акквах
ASYMMETRIC PRICE TRANSMISSION MODELING: THE IMPORTANCE OF MODEL COMPLEXITY AND THE PERFORMANCE OF THE SELECTION CRITERIA

Х. Кумар, Р. Сингх
ECONOMIC ANALYSIS OF FRESHWATER AQUACULTURE PRODUCTION: A COMPARATIVE ANALYSIS OF DIFFERENT PRODUCTION SYSTEMS

Н.А. Жатто
   ASSESSING THE RETURNS TO SCALE: EVIDENCE FROM FISH FARMERS IN
ILORIN, KWARA STATE

А.М. Вакили
      ECONOMIC ANALYSIS OF COWPEA PRODUCTION IN NIGERIA

Г. Раджович, Ж. Булатович
MOVEMENT POPULATION IN THE SECOND OF XX AND BEGINNING OF XXI CENTURYN: THE CASE NORTHEASTERN
MONTENEGRO


1(13) 2013

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CONTENT

Russian Journal
of Agricultural and Socio-Economic
Sciences

issue
January

M.S. Rahman
SOCIO-ECONOMIC DETERMINANTS OF OFF-FARM ACTIVITY PARTICIPATION IN BANGLADESH

B. Chazovachii, C. Mutami, J. Bowora COMMUNITY GARDENS AND FOOD SECURITY IN RURAL LIVELIHOOD DEVELOPMENT: THE CASE
OF ENTREPRENEURIAL AND MARKET GARDENS IN MBERENGWA, ZIMBABWE

M. Mkpado
SERVICE TRADE AND NON-OIL EXPORT IN NIGERIA

K.M. Kuwornu, M. Suleyman,P.K. Amegashie ANALYSIS OF FOOD SECURITY STATUS OF FARMING HOUSEHOLDS IN THE FOREST BELT OF THE CENTRAL REGION OF GHANA

H. de-Graft Acquah
ASYMMETRIC PRICE TRANSMISSION MODELING: THE IMPORTANCE OF MODEL COMPLEXITY AND THE PERFORMANCE OF THE SELECTION CRITERIA

H. Kumar, R. Singh
ECONOMIC ANALYSIS OF FRESHWATER
AQUACULTURE PRODUCTION:
A COMPARATIVE ANALYSIS OF DIFFERENT PRODUCTION SYSTEMS

N.A. Jatto
ASSESSING THE RETURNS TO SCALE: EVIDENCE FROM FISH FARMERS IN ILORIN, KWARA STATE

A.M. Wakili
ECONOMIC ANALYSIS OF COWPEA PRODUCTION IN NIGERIA

G. Rajovic, J. Bulatovic
MOVEMENT POPULATION IN THE SECOND OF XX AND BEGINNING OF XXI
CENTURYN: THE CASE NORTHEASTERN MONTENEGRO

Food and Agriculture Organization of the United Nations

The AGRIS - International Information System for the Agricultural Sciences and Technology (http://agris.fao.org) initiative was set up by the FAO - Food and Agriculture Organization of the United Nations (http://www.fao.org) in the 70s and created a worldwide cooperation for sharing access to agricultural science and technology information. Based on available technologies, AGRIS was initially collecting bibliographic references for a central database. However, since the advent of the Internet in the late 90s AGRIS has become the brand name for a network of centres, which are promoting the exchange of agricultural science and technology information through the use of common standards and methodologies.
The AGRIS open archives and bibliographical databases cover the many aspects of agriculture, including forestry, animal husbandry, aquatic sciences and fisheries, and human nutrition, extension literature from over 100 participating countries. Material includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.

AGRIS today is part of the CIARD (Coherence in Information for Agricultural Research for Development) initiative, in which the CGIAR (http://www.cgiar.org), Global Forum on Agricultural Research (http://www.egfar.org and FAO collaborate to create a community for efficient knowledge sharing in agricultural research and development.

CIARD RING - Routemap to Information Nodes and Gateways (http://ring.ciard.net) is a global registry of web-based services that give access to any kind of information pertaining to agricultural research for development (ARD). It is the principal tool created through the CIARD initiative to allow information providers to register their services in various categories and so facilitate the discovery of sources of agriculture-related information across the world. The RING aims to provide an infrastructure to improve the accessibility of the outputs of agricultural research and of information relevant to ARD management.

AIMS - Agricultural Information Management Standards (http://aims.fao.org) is a web portal managed by the FAO. It disseminates standards and good practices in information management for the support of the right to food, sustainable agriculture and rural development. AIMS underpins CIARD the international initiative which seeks to improve information access and coherence in and between organizations.

AIMS supports the implementation of structured and linked information and knowledge by fostering a community of practice centered on the themes of interoperability, reusability and cooperation. It shares vocabularies, methodologies, tools and services in order to promote coherence in agricultural information.


DOAJ - Directory of Open Access Journals (http://www.doaj.org) is a website maintained by Lund University which lists open access journals. The project defines open access journals as scientific and scholarly journals that meet high quality standards by exercising peer review or editorial quality control and use a funding model that does not charge readers or their institutions for access. As of January 2013, the database contained 8532 journals. The aim of DOAJ is to increase the visibility and ease of use of open access scientific and scholarly journals thereby promoting their increased usage and impact.


EPPO - European and Mediterranean Plant Protection Organization (http://www.eppo.int) is an intergovernmental organization responsible for European cooperation in plant health. Founded in 1951 by 15 European countries, EPPO now has 50 members, covering almost all countries of the European and Mediterranean region. Its objectives are to protect plants, to develop international strategies against the introduction and spread of dangerous pests and to promote safe and effective control methods.

As a Regional Plant Protection Organization, EPPO also participates in global discussions on plant health organized by F.A.O. and the International Plant Protection Convention Secretariat. Finally, EPPO has produced a large number of standards and publications on plant pests, phytosanitary regulations, and plant protection products.

Russian Journal of Agricultural and Socio-Economic Sciences, 1(13)

SOCIO-ECONOMIC DETERMINANTS OF OFF-FARM ACTIVITY PARTICIPATION IN BANGLADESH

M.S. Rahman, Assistant Professor
Department of Management and Finance, Faculty of Agribusiness Management Sher-e Bangla Agricultural University, Dhaka, Bangladesh
E-mail: saadrhmn@yahoo.com

ABSTRACT
The study was conducted in two districts of Bangladesh to determine the factors affecting the participation in off-farm activity. A total of 150 sample farmers were selected for interview through random sampling technique. The results showed that the average annual income was higher for service holders (Tk.1,83,696) compared to business (Tk. 1,69,215) and off-farm labour activities (Tk.1,09,373). Participations in activities like business and services were positively influenced by the farm size and education respectively. On the other hand, farm size and education were inversely related with participation in off-farm labour activities. Farmers in the study areas mentioned low income from agriculture as a reason for participating in off-farm activity.

KEY WORDS
Household income; Off-farm income; Service; Off-farm labour; Determinants.

     Due to economic pressure, many households often search for alternative means like off-farm activities to cope with the problem of income variability. Off-farm activities have become an important component of livelihood strategies among rural households in our country. Several studies have reported a substantial and increasing share of off-farm income in total household income (Haggblade et al, 2007). The role of off-farm activities in promoting growth of rural economy and reducing poverty is well documented (Child and Kaneda, 1975; Islam, 1984; Ranis and Stewart, 1993; Reardon, 1997; Weijland, 1999; Lanjouw, 2001). Rural off-farm sector encompasses generally all non crop activities that are not directly related to crop and non crop production operations but are carried out as backward-forward linkages to the various enterprises with in the rural areas proper and also in the small urban and peri urban areas of large metropolitan (Mandal, 2002).
     Diversifying one’s sources of income has become a major challenge in Bangladesh in recent years. Compared to the agricultural sector, employment opportunities in the off-farm sector have been increasing rapidly since the early nineties (The Financial Express, 2012). The Government of Bangladesh in its national poverty reduction strategy paper identified the off-farm sector as a “leading sector” in the rural economy (GOB, 2005). There are several studies (Islam, 1984; Hossain et al, 1994; Bhattacharya, 1996; Khandker, 1996; Hossain, 2005) reviewed the off-farm sector in Bangladesh. The purpose of this paper is to provide additional information on off-farm activity in rural areas of Bangladesh for assessing the recent status of off-farm activity. Keeping these factors in consideration the present study was undertaken with the following specific objectives.
     Specific Objectives:
   1. To examine the structure of rural household incomes in the study areas;
   2. To find out factors affecting household participation in off-farm activities; and
   3. To find out the reasons for participating in off-farm activities.

METHODOLOGY

     The study was conducted in two districts namely Jessore and Rangpur due to high concentration of off-farm activities. Rural off-farm activities in the study areas were classified into three categories; i) Business enterprises such as shop keeping, petty trading, contractor services etc; ii) Services such as salaried service in public and private sector institutions, teachers, lawyer, village doctors etc and iii) Off-farm labour such as mechanics, wage employment in rural business, transport operations, construction labour etc. A total of 150

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Russian Journal of Agricultural and Socio-Economic Sciences, 1(13)

samples taking 25 from each group and 75 from each district were selected randomly for this study. The study was mainly based on primary data collected through face to face interview during the month of March to May, 2011. The collected data were then edited and processed to fulfill the objectives of the study.
      Analytical technique. Descriptive statistics were used to analyze the annual household income of the sample farmers. The probit model was used to identify the factors influencing the participation in off-farm activities; a binary choice model based on the method of maximum likelihood is specified. The dependent variable of these models was participation in off-farm activities. Since the dependent variable was dichotomous, OLS cannot be used. Therefore, the following type of probit model was used for this study.

Yi* = в Xi + ui, where ui~ N(0, 1), i = 1,.n

                                 Y = 1{Y*>0} = 1 if Y* > 0 0 Otherwise

Where, Yi = Farmers participating in the off-farm activities (if participate = 1; other wise = 0), Xi = Independent variables. Three separate models for this purpose were run for three categories of off-farm activity like (i) Business activities (ii) Services, and (iii) Off-farm labour.
      Variable used in the probit model and their measurement:
      Age (X1): Respondent’s age in year was directly inserted in the model. This variable could have a positive or negative effect on the respondent’s decision to participate in the off-farm activities.
      Farm size (X2): Farm size is an indicator of social status of the respondents. It was calculated on per hectare basis for each respondent.
      Household workers (X3): It was measured on the basis of number of earning members in the family.
      Dependency ratio (X4): It is the ratio of total number of family members and earning members of the family.
      Organizational participation (X5): It was measured on basis of participation in the different organization. A respondent was given a score of one if he is a member of any organization, otherwise 0.
      Infrastructure development (X6): In this study development of road and highways was considered as a proxy of infrastructure development. A score of 1 is given if the respondents have the facilities to use the roads and highways, otherwise 0.
      Education (X7): Education of the respondent was measured on the basis of total schooling years.

RESULTS AND DISCUSSION

      Average annual income of the respondents. Average annual income was found higher for service holders (Tk. 183696) than that of business (Tk. 169215) and off-farm labour (Tk. 109373). Among the service holders higher income was found for the respondents of Rangpur compared to Jessore. Out of the total income, highest portion of the income comes from off-farm income activities compared to agricultural income for all categories of respondents. Service holders of Jessore received highest 68% of their total income from off-farm activities compared to the service holders of Rangpur (see Table 1).
      Factors affecting participation in off-farm activities. The parameters of the Probit model estimated to identify the factor influencing participation in off-farm activities are presented in Table 2, 3 and 4.
      The intensity of participation in business activities is positively related with farm size, organization participation and infrastructure development. If the farm size increases by 1%, keeping other factors constant, the probability of participating in business activities would increase by 0.60%. This may be for the fact that if farm size increases respondents may earn more money by producing more crops in the field. As a result they can invest this extra money in their business activities. Similarly, if the respondents can avail developed


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Russian Journal of Agricultural and Socio-Economic Sciences, 1(13)

infrastructure like road and highways they can easily communicate with other areas and increase their volume of business (see Table 2).


Table 1. Average annual income of different categories of respondents

  Sources        Business             Service              Off-farm        
              J      R     All     J      R     All     J      R     All  
                        A. Ag    ricultural income (Tk)                    
Crop sector 54162  77943  66052  40997  76962  58980  36132  41213  38672 
Livestock    9605   9988   9796   4620  11596   8108  10795   8991   9893 
Poultry      665    428    547    596    304    450    852   490     671  
Fisheries    1260   3140   2200   1060   1280   1170   800   600     700  
  Others     3880    ^B    1940   8780   980    4880   1600    28    814  
Sub Total   69572  91499  80535  56053  91122  73588  50179  51322  50750 
             (50)   (46)   (48)   (32)   (47)   (40)   (45)   (47)   (46) 
                     B. Off-farm income (Tk)                               
Business    68880  108480 88680    ^B     ^B     ^B     ^B     ^B     ^B  
  Service     ^B     ^B     ^B   118248 101969 110108   ^B     ^B     ^B  
 Off-farm     ^B     ^B     ^B     ^B     ^B     ^B   60222  57024  58623 
  labour                                                                  
Sub Total   68880  108480 88680  118248 101969 110108 60222  57024  58623 
             (50)   (54)   (52)   (68)   (53)   (60)   (55)   (53)   (54) 
Grand total 138452 199979 169215 174301 193091 183696 110401 108346 109373
   (A+B)    (100)  (100)  (100)  (100)  (100)  (100)  (100)  (100)  (100) 

Note: J= Jessore, R= Rangpur, Figures in the parentheses indicates percentage of grand total

Table 2. Factors affecting participation in business activities: estimates of a probit model

          Factors            Coefficients Standard error z-value Marginal effect
Education                       0.004          0.03       0.17       0.0016     
Age                             0.004          0.01       0.37       0.0014     
Farm size                      0.601**         0.23       2.50      0.2027**    
Household workers               0.004          0.11       0.03       0.0013     
Dependency ratio                 0.19          0.14       1.53       0.0652     
Organizational participation    0.75**         0.27       2.92      0.2401***   
Infrastructure development     1.27***         0.35       3.71      0.3392***   
Constant                       -1.93**         0.85       -2.39        ^B       
Log likelihood function                           -75.16                         
LR chi2                                           40.62                          
Prod>chi2                                         0.000                          
Pseudo Rz                                          0.21                          
Observations (n)                                   150                           

       In the case of service, education plays a positive and significant role. The respondents having higher education are encouraged to participate in services. If the education is increased by 1%, keeping other factors constant, the probability of participation in services would increase by 0.20%. Dependency ratio also positively associated with the participation in services. On the other hand, organizational participation is negatively related with services due to the fact that organizational participation requires additional time which restricts the service holders to take part in this kind of activity (see Table 3).
       Most of the factors included in the model are negatively associated with the participation in off-farm labour activities. The negative association with age indicates the preference of the younger generation for off-farm jobs over agricultural wage labour. Negative association with farm size indicates that if the respondents have more land they can produce more crop and earn money from selling this crops. Organizational participation and infrastructure development were also negatively associated with off-farm labour activities. Negative association of education indicates educated persons are more comfortable with service sector compared to off-farm labour activities (see Table 4).


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Russian Journal of Agricultural and Socio-Economic Sciences, 1(13)

Table 3. Factors affecting participation in different services: estimates of a probit model

          Factors            Coefficients Standard error z-value Marginal effect
Education                      0.207***        0.04       5.72      0.0704***   
Age                             0.005          0.01       0.50       0.0020     
Farm size                       -0.150         0.23       -0.68      -0.0513    
Household workers               0.148          0.15       1.13       0.0504     
Dependency ratio               0.288**         0.14       2.32      0.0981**    
Organizational participation   -0.419*         0.27       -1.63      -0.145*    
Infrastructure development      -0.386         0.29       -1.38      -0.136     
Constant                       -2.90***        0.77       -3.55        ^B       
Log likelihood function                           -69.40                         
LR chi2                                           52.15                          
Prod>chi2                                         0.000                          
Pseudo Rz                                          0.27                          
Observations (n)                                   150                           

Table 4. Factors affecting participation in off-farm labour activities: estimates of a probit model

          Factors            Coefficients Standard error z-value Marginal effect
Education                      -0.23***        0.04       -5.49     -0.060***   
Age                             -0.22*         0.01       -1.60      -0.005*    
Farm size                      -1.43**         0.61       -2.34     -0.374**    
Household workers                0.18          0.15       1.14        0.047     
Dependency ratio                 0.21          0.15       1.41        0.055     
Organizational participation    -0.33          0.29       -1.12      -0.088     
Infrastructure development     -0.93**         0.35       -2.64     -0.284**    
Constant                       4.40***         1.10       4.05         ^B       
Log likelihood function                           -52.61                         
LR chi2                                           88.03                          
Prod>chi2                                         0.000                          
Pseudo Rz                                          0.46                          
Observations (n)                                   150                           

       Reasons of participation. According to the Table 5 the majority of the respondents (79%) mentioned that low income from agriculture is the major reason for participating in off-farm activity in the study areas. Burden of maintaining large family was ranked second most important reason for participating in off-farm activity followed by availability of off-farm work opportunity.


Table 5. Reasons for participating in off-farm activities

          Reasons                % of farmers         
                            Jessore Rangpur All areas
Burden of large family        80      77       77    
Low income from agriculture   76      83       79    
Available opportunities       67      53       60    

CONCLUSION

        The findings of the study reveal that on an average service holders received higher annual income compared to other categories of respondents. Farm size, infrastructure development and education had significant contribution in promoting off-farm activities like business and service whereas these factors are inversely related with off-farm labour activities. Low income and large family were the reasons for participating in off-farm activities in the study areas. Government and concerned authority should provide efficient support services to the farmers and build roads and highway to ensure participation in off-farm activities. By promoting this sector, farmers will be able to get sufficient amount of income which in turn may be used for investment in the farm practices. Off-farm activities may be used as a means of income diversification which will help to reduce poverty and boost the rural economy as a whole.


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Russian Journal of Agricultural and Socio-Economic Sciences, 1(13)

REFERENCES

[1]    Bhattacharya, D. 1996. The emerging pattern of rural non-farm sector in Bangladesh: A Review of Micro Evidence. The Bangladesh Development Studies, 24 (3-4), 143180.
[2]    Child, F.C., and H. Kaneda. 1975. Links to the green revolution: A study of smallscale agriculturally related industry in the Pakistan Punjab. Economic Development and Cultural Change, 23 (2): 249-275.
[3]    Haggblade, S., Hazell, P.B., Reardon, T. 2007. Transforming the Rural Off-farm Economy, Johns Hopkins University Press, Baltimore, MD.
[4]    Hossain, M., 2005. Growth of the rural non-farm economy in Bangladesh: determinants and impact on poverty reduction. In: Proceedings of International conference 'Rice is life: scientific perspectives for the 21st century', 436-439.
[5]    Hossain, M. Rahman, M. Bayes A. 1994. Rural off-farm Economy in Bangladesh: a Dynamic Sector or a Sponge of Absorbing Surplus Labor? SAAT Working Paper, International Labor Organization, New Delhi.
[6]    Islam, R. 1984. Off-farm Employment in Rural Asia: Dynamic Growth or Proletarization? Journal of Contemporary Asia. Vol. 14: 306-324.
[7]    Khandker, Shahidur R.1996. Role of targeted credit in rural non-farm growth. The Development Studies, 24(3-4), 181-193.
[8]    Lanjouw, P. 2001. Rural non-agricultural sector and poverty in El Salvador. World Development, 29(3): 529-527.
[9]    Mandal, M. A. Sattar and M. Assaduzzaman. 2002. Rural Off-farm Economy in Bangladesh: Characteristics, Issues and Livelihood Strategies for the Poor, Farm Economy, Vol. 12: 43-61.
[10]   Ranis, G., and F. Stewart. 1993. Rural non-agricultural activities in development: Theory and application. Journal of Development Economics 40: 75-201.
[11]   Reardon T. 1997. Using evidence of household income diversification to inform study of the rural nonfarm labor market in Africa. World Development, 25 (5) 735-748.
[12]   The Financial Express. 2012. Non farm Employment in Rural Bangladesh, March 31, Bangladesh.
[13]   Weijland H. 1999. Microenterprise clusters in rural Indonesia: Industrial seedbed and policy target. World Development, 27 (9): 1515-1530.

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Russian Journal of Agricultural and Socio-Economic Sciences, 1(13)

COMMUNITY GARDENS AND FOOD SECURITY IN RURAL LIVELIHOOD DEVELOPMENT: THE CASE OF ENTREPRENEURIAL AND MARKET GARDENS IN MBERENGWA, ZIMBABWE

Bernard Chazovachii, Cephas Mutami, Lecturers
Department of Rural and Urban Development, Great Zimbabwe University, Zimbabwe E-mail: bchazovachii@gmail.com, cmutami@gmail.com

John Bowora, Lecturer
Department of Rural and Urban Planning, University of Zimbabwe, Zimbabwe E-mail: johnbowora@gmail.com

ABSTRACT
This paper seeks to assess the contribution of community gardens on food security in rural livelihoods development in Mberengwa ward 27. Despite the introduction of community gardens in ward 27, poverty persisted amongst the vulnerable groups in the district. Both qualitative and quantitative methods were used in collection of data through questionnaires, interviews and focused group discussions (FGDs). Analysis was done using descriptive statistics and content analysis. This study revealed that the vulnerable people of Mberengwa derived income, basic horticultural skills, enriching their garden soils and food commodities from the Imbahuru community garden. Factors like all year-round production of crops, intensiveness of the activity, monitoring and evaluation by extension workers, field days in all seasons and demand of the crop varieties grown influence food security in the district. However challenges persisted due to their seclusion of these gardeners from credit facilicities, lack of irrigation equipment, unstable power relations among leaders and the project was associated with the weak in society. The research concludes that the gardening project should be done not in isolation with the Zimbabwe’s agrarian reform programme which would provide all forms of capital which capacitated the vulnerable rural dwellers.

KEY WORDS
Community gardens; Vulnerability; Livelihoods; Food security; Sustainable rural development.

     Community gardens were initiated back from the eighteenth and nineteenth centuries where tropical veg culture survived in remote areas and mixed gardens in south East Asia (Grigg, 1974). According to Taylor and Francis (2009) community gardens in Africa involved irrigation in home gardens since prehistoric time with the provision of vegetables for household consumption. The goal of community gardens was to increase household and intra household food security throughout the year. Community gardens provide marketing opportunities to rural people and built a base for food production for the vulnerable. Recently mass establishment of community gardens was done by non-governmental organisations namely Action Faim and CARE Zimbabwe in a bid to maintain sustainable rural livelihoods among the rural households.
     Communities have been upgrading communal gardens by selling the surplus production to obtain household income. Auret (1990) revealed that NGOs assist in establishing small irrigated vegetable gardens as they are a major component for the daily food consumption. In 2006, CARE Zimbabwe assisted in establishing community garden projects in Mberengwa ward 27, Imbahuru Community Garden to accommodate the vulnerable groups to alleviate rural poverty. Community gardens promoted food security as children and elderly participate in this field agriculture,(World Bank, 2007).Since the inception of community garden projects in Mberengwa ward 27 there is persistent food insecurity derailing sustainability of other livelihood activities. The problem this study seeks to address is the increasing in poverty among the vulnerable groups despite, the introduction of community gardens in Mberengwa ward 27 by CARE to reduce poverty. The garden projects were supposed to offer food security among the households but the real poor are still in

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