Socio-economic indicators are significant for determining the overall lifestyle of the Pineapple Growers. The study examines the different socio-economic variables of the pineapple farmers. The researchers selected the Sreemangal upazila of Moulvibazar district purposively and primary data was collected through a structured questionnaire during 2017-2018 cropping season from one hundred pineapple growers (small, medium and large) following simple random sampling technique. Descriptive statistics include frequency, sum, average, percentage and ratios were used to analyze the data. The study revealed that majority of the farmers were in small (44 percent) and medium (30 percent) categories and average farm size was 2.130 ha. Most of the pineapple growers were middle aged (31-40 years old) while a little portion of them were older aged (greater than 60 years).  It was found that 81 percent of the respondents were married in the study area.  In addition, almost all farmers (95 percent) were literate and more than sixty percent of them had primary education. Averagely, a family consists five members and above three members are dependent to their family in the study areas.  Majority of the respondents had 11-20 years of farming experience and the primary occupation of them (91 percent) was agriculture including pineapple cultivation. Moreover, a significant portion of farmers received training from government agricultural extension office whereas around one sixth of pineapple farmers received credit from both public and private banks as well as from NGOs. However, Extension office need to provide more and effective training facilities to the pineapple farmers for profitable production, simplification of buying, selling, renting and leasing of land to reduce production cost as well as different incentive packages can be introduced by the government for encouraging unemployed youth people to engage in pineapple production.

The present study aims to examine the contribution of fishing in total income and extent ofhaor livelihood diversification; and identify the factors affecting haorlivelihood diversification of the fishing community. This study was conducted in Dekhar Haor of Sunamganj district. The data were collected from primary sources by using Simple random sampling from 100 respondents. Tobit model was used to determine the factors affecting the livelihood diversification. Fishing contributed highest to the household income. The estimated Simpson Index showed that fishermen have diversified their livelihood activities at medium level. The results showed that age of the respondents, years of schooling, access to credit and savings had positive effect, while, mode of land ownership, distance from the nearest market and value of household’s assets had negative effects on livelihood diversification. Non-farm employment opportunities should be expanded to increasehaor livelihood diversification.

According to Nutritional Intake Survey Series, conducted by the National Sample Survey Organisation (NSSO), there has been slow, but steady decline in consumption of calories and proteins, but the consumption of fat has been increasing both in rural and urban India. Unlike calorie and protein, the difference in fat intake between rural and urban areas is pronounced. In the country,the States belonging to north eastern region seem to be lagging in terms of nutritional intake when compared to the national average. Among calorie, protein and fat, it is the protein where relatively lesser number of States in the country have exhibited positive trend during 2004-05 and 2011-12. In terms of calorie intake, about 39 per cent of country's population remains undernourished. However, there has been a decrease of about 33 million people who registered to have deficient intake of calories during 2004-05 and 2011-12. With rise in food expenditure among rural and urban masses, there has been less than proportionate increase in calorie, protein and fat intake. Yet, relatively higher propensity has been witnessed to consume more of fat with the rise in food expenditure.

No abstract

No abstract