Climatic and non-climatic stressors, such as temperature increases, rainfall fluctuations, population growth and migration, pollution, land-use changes and inadequate gender-specific strategies, are major challenges to coastal agricultural sustainability. In this paper, we discuss all pertinent issues related to the sustainability of coastal agriculture under climate change. It is evident that some climate-change-related impacts (e.g., temperature and rainfall) on agriculture are similarly applicable to both coastal and non-coastal settings, but there are other factors (e.g., inundation, seawater intrusion, soil salinity and tropical cyclones) that particularly impact coastal agricultural sustainability. Coastal agriculture is characterised by low-lying and saline-prone soils where spatial competition with urban growth is an ever-increasing problem. We highlight how coastal agricultural viability could be sustained through blending farmer perceptions, adaptation options, gender-specific participation and integrated coastal resource management into policy ratification. This paper provides important aspects of the coastal agricultural sustainability, and it can be an inspiration for further research and coastal agrarian planning.

The aim of the study was mainly to determine and describe the extent of the motivation on sunflower cultivation and also explore relationship between the 12 selected characteristics of the farmers with motivation on sunflower cultivation. The study was designed with mixed method approach where, both qualitative and quantitative analyses are blended in a rational way to have a deeper understanding about research problems. The study was conducted in Dumki and Patuakhali Sadar Upazilla of Patuakhali district, Bangladesh. The whole period of the study was six months from 01 January to 30 June 2016. Simple random sampling technique was used to select 110 farmers engaged in sunflower cultivation. In addition case study, focus group discussions, Key informant interviews were used to collect data. Data was collected by face to face interviews. Data was analyzed using descriptive statistical measures and computer software like SPSS. Pearson's Badhan et al.; AJAEES, 18(2): 1-11, 2017; Article no.AJAEES.33503 2 Product Moment coefficient of correlation results showed that out of 12 independent variables, the correlation coefficients of 7 variables had positive and significant relationship with their motivation on sunflower cultivation. Multiple regression analysis showed that training experience, innovativeness, and sunflower cultivation knowledge had significant contribution towards motivation on sunflower cultivation. Training, Contact with various sources of information, Organizational participation of the farmers was vital predictors. These predictors need further investigations. Original Research Article

The negative relationship between farm size and output per acre has been tested for Pakistan and it is concluded that the observed negative or positive correlations between land productivity and the farm size in the case of Pakistan are the result of over-aggregation. Land productivity curve is U-Shaped; the productivity is high on desperately small farms due to intensive labour and irrigation use and on largest farms due to capital-intensive inputs. The middle-level efficient entrepreneur farmer has so far failed to emerge.

The major aims of this study were mainly to determine and describe the extent of farmers’ crop productivity and also explore the relationship between the 12 selected characteristics of the farmers with their crop productivity level. The study was designed with a mixed-method approach where both qualitative and quantitative analyses are blended in a rational way to have a deeper understanding of research problems. The study was conducted in Dumki Upazilla under Patuakhali district, Bangladesh. Simple random sampling technique was used to select 110 farmers except landless engaged in crop production. Data were collected by face to face interview using a pre-tested interview schedule during the period from March 10 to April 15, 2016. Data were analyzed using descriptive statistical measures and computer software like SPSS. Pearson's Product Moment coefficient of correlation results showed that out of 12 independent variables, the correlation coefficients of 7 variables had a positive and significant relationship with their level of crop productivity. The stepwise multiple regression analyses stated that only 4 variables such as communication exposure, innovativeness, risk orientation and training experience had a significant contribution to the farmers' crop productivity level and also accounted for 52.8 per cent of the total variation in productivity index. This study also showed some problems which were faced by the farmers during crop production. If these problems can be solved, the farmers’ crop productivity level will be increased.