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Employment Generation, Increasing Productivity and Improving Food Security Through Farming Systems Technologies in the Monga Regions of Bangladesh

Mazharul Anwar
On-Farm Research Division, Bangladesh Agricultural Research Institute, Agricultural Research Station, Alamnagar, Rangpur, Bangladesh

Zannatul Ferdous*
On-Farm Research Division, Bangladesh Agricultural Research Institute, Agricultural Research Station, Alamnagar, Rangpur, Bangladesh

Md. Asaduzzaman Sarker
Department of Agricultural Extension and Education, Bangladesh Agricultural University, Mymensingh, Bangladesh.

Ahmed Khairul Hasan
Department of Agronomy, Bangladesh Agricultural University, Mymensingh, Bangladesh.

Md. Babul Akhter
Crop Physiology Division, Bangladesh Institute of Nuclear Agriculture, Mymensingh, Bangladesh.

Md. Asad Uz Zaman
Rice Farming Systems Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh.

Zahidul Haque
IDSS Project, ACI Agribusiness, ACI Limited, Dhaka, Bangladesh.

Hayat Ullah
Department of Food, Agriculture and Bioresources, School of Environment, Resources and Development, Asian Institute of Technology, Pathumthani 12120, Thailand

Abstract/ Executive Summary:

Monga is seasonal food insecurity in ecologically vulnerable and economically weak parts of northwestern Bangladesh, primarily caused by an employment and income deficit before Transplanted aman paddy (summer rice) harvest. It mainly affects those rural poor, who have an undiversified income that is directly or indirectly based on agriculture. Rangpur and Lalmonirhat districts under greater Rangpur region are severely affected by Monga. For increasing employment and food accessibility in these regions this study was undertaken. The farm accounting data for this empirical application have been collected from two districts (Rangpur and Lalmonirhat) of greater Rangpur through a farm management survey. A sample of 90 farms from each district has been surveyed taking 30 from marginal, 30 from small and 30 from medium farm groups using random sampling technique method. Farmers get lower return due to lack of crop diversification. Linear programming model used to produce optimum farm plans for marginal, small and medium farms (i) by reorganization of existing resources (ii) by combination of improved technologies with existing technologies. For increasing food accessibility and employment, optimum farm plans by reorganization of improved technology have been conducted among six farmers in the study villages at 2010-2011. By reorganization of existing cropping patterns (using Linear Programing Model) gross output (7% to 21%), gross margin (12% to 20%) and labour employment (6% to 20%) have been increased from plan1 (existing plan) to plan 2 (by reorganization of existing lands). The cause of increase gross output, gross margin and labour employment was some cultivated land from less efficient cropping patterns has been transferred to more efficient cropping patterns. Again, by reorganization of existing and improved cropping patterns, some lands of existing patterns have been shifted to improved cropping pattern. As a result, gross out (17% to 31%), gross margin (27% to 32%) and labour employment (13% to 26%) have been raised from plan1 to plan 3 (by combination of improved technologies with existing technologies). The result of on farm demonstration showed gross output, gross margin and labour employment have been increased 24% to 53%, 32% to 51% and 12% to 47% from plan1 to plan 3, respectively. So, this study suggest, optimum farm plan with the combination of existing and improved cropping pattern will increase farm output and generate additional employment.

Keywords: Employment creation; Sustainable food security; Farming systems; Monga.

Location: (Rangpur and Lalmonirhat) of greater Rangpur

Start Date:

End Date:

Program Area: Socio-economic and Policy

Non-commodity: Employement

Objectives:

The main objective were to assess existing technology of the farmers of Monga regions, to produce optimum farm plans for marginal, small and medium farmers, reorganization of existing resources through combination of improved technologies with existing technologies in the farmers field of Monga regions.

Methodology:

A multistage stratified random sampling was employed to obtain representative sample. At later stage, out of several sub districts, one sub district (Upazila) was selected purposely from each district. The farm accounting data for this empirical application have been collected from two districts (Rangpur and Lalmonirhat) of greater Rangpur through a farm management survey. A sample of 90 farms from two villages (technologically poor villages) of one sub-district for each district have been surveyed taking 30 from marginal (farm size less than 50 decimals), 30 from small (farm size less than 150 decimals), and 30 from medium farm (farm size less than 250 decimals) groups using random sampling technique method. Input output data of all crops of the sample farmers have been included in data analysis. Linear programming (LP) model have been used to produce optimum farm plans for marginal, small and medium farms with existing technology and with improved technology for increasing employment and food accessibility of the farming of the regions.

Source of Information: Annual Research & Review in Biology 16(6): 1-15, 2017;

Article Link (Online Journal): Article no.ARRB.35645 ISSN: 2347-565X, NLM ID: 101632869

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

The solution of the linear programming model produces optimum plans by reorganization of existing resources for marginal, small and medium farms in the two study areas. Optimum plans differ in the three categories of farms due to resource and constraints. Gross output, gross margin and efficiency measures have shown an increased in these plans. Cultivated land has been shifted from existing cropping patterns to suitable cropping patterns by the solution of the model based on gross margin and resource constraints. On farm demonstration of optimum plan showed that improved cropping pattern Transplanted aman rice (BINA 7) –Maize – Mungbean, and Transplanted aman rice (Bina dhan 7) – Cauliflower- Onion-Jute were more efficient cropping pattern/technology compared to existing cropping patterns. These results can be used by policymakers, agribusiness companies, and researchers. Policymakers and agricultural planners may better focus on agricultural diversified cropping systems to promote agricultural development because it offers opportunities to reduce production and price risks, increase flexibility, increase agricultural income, and sustain productivity and growth.

Knowledge Management: Journal