In this study, we attempt to anticipate annual rice production in Bangladesh (1961–2020) using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme Gradient Boosting (XGBoost) methods and compare their respective performances. On the basis of the lowest Corrected Akaike Information Criteria (AICc) values, a significant ARIMA (0, 1, 1) model with drift was chosen based on the findings. The drift parameter value shows that the production of rice positively trends upward. Thus, the ARIMA (0, 1, 1) model with drift was found to be significant. On the other hand, the XGBoost model for time series data was developed by changing the tunning parameters frequently with the greatest result. The four prominent error measures, such as mean absolute error (MAE), mean percentage error (MPE), root mean square error (RMSE), and mean absolute percentage error (MAPE), were used to assess the predictive performance of each model. We found that the error measures of the XGBoost model in the test set were comparatively lower than those of the ARIMA model. Comparatively, the MAPE value of the test set of the XGBoost model (5.38%) was lower than that of the ARIMA model (7.23%), indicating that XGBoost performs better than ARIMA at predicting the annual rice production in Bangladesh. Hence, the XGBoost model performs better than the ARIMA model in predicting the annual rice production in Bangladesh. Therefore, based on the better performance, the study forecasted the annual rice production for the next 10 years using the XGBoost model. According to our predictions, the annual rice production in Bangladesh will vary from 57,850,318 tons in 2021 to 82,256,944 tons in 2030. The forecast indicated that the amount of rice produced annually in Bangladesh will increase in the years to come.

This study aims to determine trends in the long-term monthly total data series using non-parametric methods like Mann-Kendall and Sen's T test. The change per unit time in a time series having a linear trend is estimated by applying a simple non-parametric procedure, namely Sen's estimator of slope. Serial correlation structure in the data is accounted for determining the significance level of the results of the Mann-Kendall test. The data used in this study, consists of seven divisional meteorological stations across Bangladesh. Station basis trend analysis has been performed for temperature data. For temperature data most of the stations show significant trend. There are rising rates of temperature in some months and decreasing trend in some other months obtained by these statistical tests suggesting overall significant changes in the area.

The poultry selling and processing practices followed in the poultry wet markets of Bangladesh are always being overlooked unknowingly. The research was conducted to observe the existing scenario of poultry selling and processing practices at the selected wet markets located in the Gazipur City Corporation of Bangladesh. A total of 43 poultry selling shops were randomly selected and interviewed using a semi-structured questionnaire. It was surprising to observe the absence of female personnel and involvement of few (6.9%) people over the age of 50 years in the wet markets. All the persons engaged in poultry selling and processing had no institutional training. The shops found to be abstained from following some important practices such as feed withdrawal period, isolation of diseased birds, ante and post mortem inspection. The proper bleeding time (1-2) min was recorded in 58.2% cases. The killing cone was recognized as the best device in terms bleeding time. The 72.1% of the outlets never cleaned the carcass prior to deliver the customers. The absence of ante- and post-mortem inspections may cause a great threat of disease outbreak. Taken together, the poultry selling and processing practices followed in the wet market needs to be assessed carefully to deliver safe and quality meat to the customers. In addition, organizing basic training on pre-slaughter management and processing for both seller and processor and also ensuring the regular ante- and post- mortem inspection could improve the present situation in order to produce quality poultry meat. Progressive Agriculture 31 (3): 205-217, 2020

The major objective of this investigation was to assess the costs and benefits for farmers of the BINA advanced draught-tolerant cultivar Binamasur-10 in Nachole and Sadar upazilas of Chapainawabganj district, Bangladesh. All of the original data used in this investigation was acquired from 50 farmers who grew the Binamasur-10 variety, through a pre-planned interview schedule and data collected from April to May 2021. To estimate profitability in this study, costs and return evaluation were done using variable value and total price principles. A total of Tk. 51370.47 was spent on production costs per ha, of which 35% were fixed costs and 65% were variable costs. The cost in Nachole was Tk. 51799.24 per ha, while the cost in Chapainawabganj Sadar was Tk. 50941.70 per ha. In the studied locations, the average net return was Tk. 61909.25 per ha, greater in Chapainwabganj Sadar (Tk. 74050.57 ha-1) than in Nachole (Tk. 49767.92 ha-1). The BCR was assessed to be 2.20 based on overall cost, which was similarly higher in Sadar (2.45) than in Nachole (1.96), both of which are located in the Chapainawabganj district. The 88% of respondents mentioned that shortage of Binamasur-10 seeds was the top constraint. Other restrictions include the lack of information (51%), lack of technical understanding (40%), increased insect infestation (38%), untimely rainfall (36%), and high insecticide costs (19%). Farmers in these regions ought to have access to superior lentil seeds at reasonable market rates as a result. Therefore, the current study is a modest attempt to investigate if the availability of pulse seeds of higher quality at a lower cost could increase production in the chosen areas.

Bangladesh is facing unpredictable weather patterns, as well as a consistent rise in temperature and precipitation. Climate change has had a negative impact on physical and mental health, leading to an increase mostly in the prevalence and variation of infectious diseases, as well as psychological issues such as depression and anxiety disorders. Given the country's inherent sensitivity to climatic influences, the climate-health nexus is a relatively unexplored subject of research. The purpose of this article is to investigate the severity of climate change in Bangladesh and how it impacts the health of the public. Morbidity and mortality due to heat stress, cyclones, floods, droughts, and other weather extremes at various spatiotemporal scales have been observed as direct effects of climate change in Bangladesh. The indirect effects involve more complicated paths, such as affecting food and water security due to salinity intrusion and the development of infectious diseases because of shifts in vector and pathogen ecology. To mitigate the effects of climate change on various infectious diseases, healthcare and response systems must be strengthened. By implementing proactive adaptation methods, we may significantly and actively contribute to preventing and regulating the negative consequences of climate change on human health. There is little evidence to make sound health policy decisions in the context of climate change, and there is a lack of multidisciplinary research activities. Despite these constraints, gathering and reporting scientific information is essential for developing a resilient health system in climate-vulnerable countries like Bangladesh and other low-income regions.