Study location: The case study was done at Jalchatra village of Madhupur upazila (sub-district) under Tangail district. Pineapple is extensively grown in this area. Madhupur is located at 24.6167° North 90.0250° East. It has 74,984 units of households having 0.297 million people in a total area of 500.67 km². It has a large forest area named 'Madhupur Sal Forest". Total cultivable land is 32900 hectares, of which the fallow land is 2000 hectares (BBS, 2018). About 65% area has irrigation facilities. Farmers of Madhupur Upazila grow a variety of crops, the major crops being rice, jute, cotton, potato, pointed gourd, ginger, cassava, vegetables, pineapple, banana, jackfruit, litchi and papaya. About 70% of the country’s pineapple cultivation is in Madhupur area. Madhupur is traditionally an agrarian sub-district like other sub-districts of Bangladesh. Farmers of Madhupur grow a variety of crops. The major crops grown in Madhupur are paddy rice, jute, wheat, cotton, potato, pointed gourd, ginger, betel leaf, cassava, vegetables, mango, jackfruit, litchi, papaya, pineapple and olive. However, Madhupur is famous for pineapple cultivation in Bangladesh. About 70% of the country’s pineapple grows in the Madhupur area of Bangladesh. Sampling, Data Collection and Analysis The sample size should be as large as possible to allow for adequate degrees of freedom in the statistical analysis. In other words, administration of field research, processing and analysis of data should be manageable within the limits imposed by physical, human and financial resources. A reasonable size of the sample to achieve the objectives of the study was taken into account. A simple random sampling technique was followed in this study. Thus, a total of 60 pineapple farmers were selected from a total of 300 pineapple farmers. For collecting primary data through the survey method, preparation of the interview schedule is, of course, a crucial need. A set of relevant questions were set in the interview schedules for having reliable information from the pineapple farmers. Then the draft schedule was pretested and attention was paid for the inclusion of new information which was not included in the draft schedule. Thus, the draft schedule was improved, rearranged and modified in the light of the actual and practical experiences gathered from pre-testing. After making the necessary adjustments, a final interview schedule was developed following logical sequences. The empirical data for the study were collected during September to October, 2017. The researcher made all possible efforts to establish desired rapport with the respondents so that they could feel free to respond to the questions contained in the schedule. During the interview, the researcher explained the purpose of collecting data to the respondent and did not face any difficulty to establish rapport in collecting data. To measure the use of agrochemicals in pineapple farming a 4-point rating scale was used. A total of 14 agrochemicals were included into the questionnaire and asked to the respondents to give their responses regarding their use following a 4-point rating scale. These selected agrochemicals were categorized into 5 categories like fertilizers, pesticides, hormones, ripening agents and shelf-life enhancers. The score was assigned to each of the responses of the farmers as 3, 2, 1 and 0 respectively. Finally, summation of the score of all of the 14 agrochemicals was treated as the score of a respondent on the use of agro-chemicals in pineapple farming. The collected data were compiled, tabulated, and analyzed in accordance with the objectives of the study. A coefficient of correlation analysis was employed for exploring relationships between the extent of use of agrochemicals by the pineapple farmers and their selected characteristics. For rejecting/accepting any null hypothesis 5% level of significance was used. The Statistical Package for Social Science (SPSS v.16) was used to perform the data analysis.