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The article examines the relationship between poverty and food insecurity using a primary sample ( n = 319) collected from the enclave areas of Bangladesh. The study reveals that among the poor respondents, 80% are food insecure and among the non-poor respondents 30.8% are food insecure. Uni-variate probit regressions find that per capita income, household size, number of earners, household’s head education, improved communication, suffering from disease, livestock rearing, fishing, improved crop variety, micro-credit, social safety net programme and income shock cause differential influence on poverty and food insecurity simultaneously. Marginal probability of bi-variate probit model illustrates that per capita income, household size and suffering from disease are the three most prominent factors of poverty and food insecurity concurrently that varies at individual factor level from composite factor level. The average predicted probability indicates that majority of the households are more likely to stay poor and food insecure. There is a strong and complex link between poverty and food insecurity, while some poor are food insecure and some are not. Hence, policies devised based on only one indicator may not achieve the development targets fully and resource allocation may be inefficient. The study recommends that there should be synergies between policies which should address both the social indicators jointly.

The present study aims at examining the effectiveness of the training on “Application of Improved technology of postharvest handling of Mango”. The research was conducted in three upazilas of Chapainawabganj district- a leading mango growing region of Bangladesh. A total of 50 respondents were selected randomly from the list of the trainees taking 25 from each of the trader‟s and farmer‟s group. The data were collected from the selected respondents employing direct interview method using pre-designed, pre-tested interview schedule. Both descriptive and statistical analysis was used in analyzing the data. The findings of the study revealed that majority of the respondents (94%) were educated and belonged to young aged group of 23-40 years. The study showed that before receiving the training, the postharvest losses at farm and traders‟ level accounted for 28.12% and 21.80%, respectively and after receiving training, the postharvest losses reduced to 12.68% at farm and 8.52% at traders‟ level which was significant at 95% level of confidence. The findings also revealed that after obtaining training, income of respondents had increased significantly by 25.47% at farm and 16.48% at traders‟ level. The study identified important problems faced by the respondents such as lack of capital, costly and unavailability of BARI (Bangladesh Agricultural Research Institute) mango harvester and hot water treatment plant in the market and limited access to institutional credit. If these constraints were removed, postharvest losses of mango could be reduced substantially thus ensuring increased sustainable income for both mango cultivators and traders. A pool of master trainers should be developed to train a large number of mango cultivators and stakeholders on this important issue, government should provide institutional credit to the mango farmers and traders at an ease terms and condition, BARI mango harvester and hot water treatment plant should be made available at an affordable price to the farming community and traders in mango growing regions of Bangladesh Res. Agric., Livest. Fish.7(3): 351-361, December 2020

Sustainable rice production in the coastal region of Bangladesh is threatened due to various climatic impacts. The study investigated the current scenario of rice production and identified the linkage among different input variables related to rice production such as seed, urea, pesticide, etc. in three districts of Patuakhali, Khulna, and Cox’s Bazar, using a log–log model and panel data analysis. The Stochastic Model of multiple regression analysis helped to identify the most important input variables. The input factors found common in all three study areas were seed. The log–log model was used to identify how climatic factors influenced these input variables. Identifying such factors would help to ensure sustainable agriculture production in the future. Seed cost showed a negative elasticity in Patuakhali, while urea cost showed a negative elasticity in Khulna region. Time series forecasting of rice production up to 2030 in the study areas was examined using the best fitted ARIMA model. While rice production showed an increasing trend in two regions, it did not show a satisfactory upward trend in Kutubdia, which is mostly related to their mismanagement of fertilizer use and irrigation water scarcity. The analysis from the research indicated that an area-specific adaptation plan is required to sustain the agricultural production, as the input variables for rice production were not found similar for three different study districts where a specific attention needs to be given. Moreover, to address the nonexistence of quality panel data for rice production, measures have been introduced which includes an online data collection system using a mobile application.

Betel leaf is one of the important cash crops that gaining popularity in recent time in Bangladesh. This study was conducted to identify the present and future production pattern of betel leaf in Bangladesh as well as its prospects and challenges. Secondary data of 29 years from 1991 to 2019 have been used to specify the production pattern and forecasting of betel leaf at national level by using deterministic, stochastic and dynamic time series model. While the primary data were collected from three sub-districts of the Rajshahi district namely Bagmara, Durgapur and Mohanpur to identify the prospects and challenges through SWOT analysis. This study found significant relationship among betel leaf production, price and annual average temperature of Bangladesh. A total of six growth models of different types were used for forecasting production, cultivation area, and price of betel leaf. Based on the model selection criteria cubic model, quadratic model, and growth model were chosen for initial forecasting of betel leaves production, cultivation area, and price respectively. Among the stochastic model auto regressive integrated moving average ARIMA (0, 1, 0) was fitted well to forecast the production. Finally, a dynamic regression model of ARIMA (1, 1, 0) with dynamic regressors has been used to forecast the production of betel leaf from 2020 to 2023. Forecast values range minimum 202770.41 tons to 296217.14 tons with 95% confidence interval. All the best-fitted models revealed that the production of betel leaf has an upward trend in the future. At the end SWOT analysis was implemented to identify the strengths, weakness, opportunities and threats involved in betel leaf farming which will be helpful for making future national level policy options. Diseases control at the betel leaf garden and access to credit for initial investments were identified as the major challenges for this enterprise. Res. Agric., Livest. Fish.7(2): 209-223, August 2020

Asthma, a global public health problem, is affecting both developing and developed countries. Bangladesh is one of the asthma prone countries with high concentration of the disease in Mymensingh zone. This study has been conducted to identify the determinants and impact of asthma disease in Mymensingh zone of Bangladesh. Cluster sampling technique is used for sampling 100 asthmatic patients from Mymensingh zone. Different socio-economic and biological information of the asthmatic patients have been collected. Multinomial logistic regression and multivariate logistic regression have been used to find out the determinants and impact of asthma.The result suggests that the likelihood of being in severe asthma is 5.182 times higher if the public rule of smoking is not maintained in work place. Positive impact of access to sunlight and presence of cockroaches, mice or rats in household on reducing asthmatic condition was also revealed in the analyses. The multivariate logistic regression suggests that hypertension and weight change both are significantly influenced by disease status of asthma.This research identifies that along with other determinants smoking in the working places is an important determinant of asthma in Mymensingh zone of Bangladesh. Furthermore, asthma is found to have significant influence on hypertension and weight change which will guide the policy planners and health professionals to address the issues together in systematic fashion. Mymensingh zone being an asthmatic region needs special attention in the national health program. J. Bangladesh Agril. Univ. 16(3): 478–481, December 2018

The agricultural arena in the coastal regions of South-East Asian countries is experiencing the mounting pressures of the adverse effects of climate change. Controlling and predicting climatic factors are difficult and require expensive solutions. The study focuses on identifying issues other than climatic factors using the Livelihood Vulnerability Index (LVI) to measure agricultural vulnerability. Factors such as monthly savings of the farmers, income opportunities, damage to cultivable lands, and water availability had significant impacts on increasing community vulnerability with regards to agricultural practice. The study also identified the need for assessing vulnerability after certain intervals, specifically owing to the dynamic nature of the coastal region where the factors were found to vary among the different study areas. The development of a climate-resilient livelihood vulnerability assessment tool to detect the most significant factors to assess agricultural vulnerability was done using machine learning (ML) techniques. The ML techniques identified nine significant factors out of 21 based on the minimum level of standard deviation (0.03). A practical application of the outcome of the study was the development of a mobile application. Custom REST APIs (application programming interface) were developed on the backend to seamlessly sync the app to a server, thus ensuring the acquisition of future data without much effort and resources. The paper provides a methodology for a unique vulnerability assessment technique using a mobile application, which can be used for the planning and management of resources by different stakeholders in a sustainable way., Graphical abstract Unlabelled Image, Highlights • The coastal areas are dynamic in nature and vulnerable to the changing climate. • Agricultural practice is one of the main livelihood sources for coastal communities, which is highly dependent on nature. • Use of machine learning techniques and mobile application can play an important role in assessing livelihood vulnerability.

This study examined the Gross margin and factor productivity of watermelon production in Patuakhali district, Bangladesh. A multi-stage stratified sampling design had been used for the selection of the watermelon growing farmers. Data were obtained with the aid of a pre-tested structured questionnaire. The socio-economic characteristics of the respondents was described and categorized by Descriptive statistics, Gross margin analysis was used to analyze the cost and returns to watermelon production and Cobb Douglas production function was used to evaluate the input factor productivity. Results showed that the farmers are relatively middle-aged with an average age of 41 years with a sizable number of the respondents (1.7%) having passed through tertiary education. It was also observed that the farmers are typically smallholders with an average farm size of 50-249 decimal. The result of the gross margin analysis showed that watermelon production is profitable with a gross margin of Tk 756 per decimal. The result of the Cobb Douglas production function shows that the coefficients of cost of seed (0.137), cost of tillage (0.227), cost of irrigation (0.304), cost of labour (0.156), and cost of pesticide (0.305) were positively significant at 5% and 1%. The overall factor productivity index is 1.19 implying an increasing return to scale in water melon production in the study area. However, lack of irrigation facility and pesticide were identified as major production constraints.

The livelihood of the people in the dynamic coastal regions of Bangladesh is highly dependent on nature and thus is vulnerable to climatic events. The research study developed the Fishermen Livelihood Vulnerability Index (LVI) to measure the vulnerability of the fishing communities living in the coastal regions of Bangladesh. The weighted average method was used to measure the FLVI and the binary logistic regression was used to find out the determinants of vulnerability. The variables to measure vulnerability such as exposure, sensitivity, and adaptive capacity were taken from the IPCC climate vulnerability framework. The results, based on the findings of a survey of 164 households from 3 coastal districts (Patuakhali, Khulna & Cox's Bazar) indicated that the coastal fishing communities are more vulnerable (FLVI = 0.48) compare to the people living in other parts of Bangladesh. The study also revealed that the livelihood activities of the coastal fishermen are mainly affected by the impacts of natural disasters. Spatial maps were prepared to show the distribution of the vulnerable areas with indicating the houses according to their level of vulnerability. The study also identified the most significant factors of vulnerability. As part of the analysis, it was found that the variables that had the most significant impact on fishermen livelihood vulnerability were natural disasters, diseases due to climate change, NGO and microcredit, income, and piracy problem. The study also identified that vulnerability factors are highly influenced by spatial characteristics and thereby identification of location specific factors is crucial in assessing and calculating vulnerability score. The study concluded that if location specific fishermen vulnerability factors are identified after certain interval with the active engagement of local communities can generate valuable information for developing appropriate strategy to secure their livelihood in a sustainable way.

Objective: This research work was conducted for the molecular characterization of the circulating foot-and-mouth disease (FMD) virus in Bangladesh and revealed out their serotype. Materials and methods: The VP1 gene of six field isolates of FMD virus (FMDV) serotypes (two serotypes O, two serotypes A, and two serotypes Asia 1) was subjected for sequencing and phy­logenetic analysis. Neighbor-joining trees were constructed by using the Molecular Evolutionary Genetics Analysis 6, having the field nucleotide sequences of FMDV and related sequences avail­able in the GenBank. Results: The nucleotide sequences of the VP1 genes of serotypes O, A, and Asia-1 of the isolates revealed that overall isolates were 91%–100% similar to the isolates reported from Bangladesh and other neighboring countries. Among the isolates reported from Bangladesh, serotype O had 98%–100% identity, serotype A had 91%–100% identity, and serotype Asia-1 had 94%–100% iden­tity. A phylogenetic analysis revealed that the FMDV serotype O PanAsia-02 sub-lineage was con­firmed in Bangladesh under the Middle East–South Asian (ME-SA) topotype. On the other hand, we identified genotype VII (18) of Asia topotype (serotype A) and lineage C (serotype Asia-1). Conclusion: The FMDV serotype O PanAsia-02 sub-lineage was confirmed in Bangladesh under the ME-SA topotype for the first time. The extensive cross-border animal movement from neigh­boring countries may act as the source of diversified FMDV serotypes in Bangladesh. Adv. Vet. Anim. Res., 7(2): 360-366, June 2020

Objective: The study was aimed to analyze the microbiological quality of mixed vegetable salads and to understand the risk related with its consumption from different restaurants around Bangladesh Agricultural University campus in Mymensingh. Materials and Methods: Sixty (60) samples of mixed vegetable salads were taken from twelve (12) different restaurants in five different time points from each restaurant. In parallel, restaurant workers were asked for handling practices while the consumers were interviewed about their salad consumption pattern and whether they had experienced any health-related problems. Microbial risk assessment of Staphylococcus spp., Salmonella spp., and Escherichia coli was esti¬mated by Monte Carlo simulation (10,000 iterations), an exponential model. Results: Aerobic plate count was ranged from 7.73 ± 0.61 to 9.04 ± 0.26 log cfu/gm, Staphylococcus spp. from 4.64 ± 0.61 to 6.42 ± 0.53 log cfu/gm, Salmonella spp. from 4.75 ± 0.08 to 5.27 ± 0.53 log cfu/gm, and E. coli from 4.98 ± 0.20 to 6.66 ± 0.80 log cfu/gm. From the survey, it was found that total consumers had 18% chances where the male had 13% and the female had 30% chances of being infected with salads. Again frequent, average, and occasional consumers had 31%, 13%, and 0% chances, respectively, of being infected with those salads. From the Monte Carlo simulation, the calculated mean annual risks of Staphylococcus spp., Salmonella spp., and E. coli infection for the three exposure scenarios were found to be about 100%. Conclusion: The study actually revealed the potential microbial contamination in mixed vegetable salads which may impact on food safety and human health. So, the findings suggest that following hygienic measures during processing and handling the microbiological quality of mixed vegetables salads can be improved. [J Adv Vet Anim Res 2020; 7(1.000): 34-41]

As a very common feature of fish marketing, small-scale fisheries in tropical countries suffers from huge post-harvest loss every year. A method was proposed to quantify the post-harvest quality loss of wet fish using sensory based assessment tool. The assessments were conducted on four fish species (rohu Labeo rohita; Ilish Tenualosa ilisha, catfish Pangasius sutchi and tilapia Oreochromis niloticus) in different steps of major distribution channels in Bangladesh for a year. Sensory quality defect point data were standardized with corresponding biochemical and microbiological quality parameters through interval estimate based on regression analysis, where a “near to actual” sensory quality breaking point was found to be DP 3.3. High value of goodness of fit 2 R indicated a highly fitted regression model for all the fishes tested, with highly significant (p

This article attempts to develop the model and to forecast the wholesale price of coarse rice in Bangladesh. Seasonal Autoregressive Integrated Moving Average (SARIMA) models have been developed on the monthly data collected from July 1975 to December 2011and validated using the data from December 2010 to December 2011. The results showed that the predicted values were consistent with the upturns and downturns of the observed series. The model with non seasonal autoregressive 1, difference 1 and moving average 1 and seasonal difference 1 and moving average 1 that is SARIMA (1,1,1)(0,1,1)12 model has been found as the most suitable model with least Root Mean Square Error (RMSE) of 61.657, Normalised Bayesian Information Criteria (BIC) of 8.300 and Mean Absolute Percent Error (MAPE) of 3.906. The model was further validated by Ljung-Box test (Q18=17.394 and p>.20) with no significant autocorrelation between residuals at different lag times. Finally, a forecast for the period January 2012 to December 2013 was made. DOI: http://dx.doi.org/10.3329/jbau.v11i2.19925 J. Bangladesh Agril. Univ. 11(2): 271-276, 2013

The study was conducted to develop a cytology based diagnostic tool for the diagnosis of avian Mycoplasma and E. coli infections at post mortem in the field condition. A total of 38 culture and PCR confirmed Mycoplasma , E. coli or mixed infected samples were used for this study. Lung impression smears were prepared on glass slide from the samples at post mortem examination. Inflammatory cells were counted on microscope after Giemsa staining. Cell counts were analyzed with Bonferroni joint confidence interval and Mann-Whitney U test. The average cell percentages in healthy cases were 73.54- 81.66%, 9.63-13.37% and 7.42-14.38% for lymphocyte, heterophil, and macrophage, respectively. In case of Mycoplasma infection, average percentages of lymphocyte, heterophil and macrophages were 82.01-88.10%, 5.6 to 8.16% and 4.52 – 9.68%, respectively. In E. coli infection, average percentage of lymphocyte, heterophil and macrophages were found as 64.44-70.76%, 19.73-23.47% and 8.9- 12.7%, respectively. In mixed infection, lymphocyte, heterophil and macrophage were found as 76.08-80.50%, 13.47 –17.63% and 4.56 –7.66%, respectively. Statistical analyses revealed that in Mycoplasma infection number of lymphocyte and in E. coli infection number of heterophil increased significantly (p< 0.01). In MC complex, number of heterophil increased and macrophages decreased significantly (p < 0.01). These findings could help identification of Mycoplasma , E. coli or Mycoplasma - E. coli complex at post mortem examination in the field condition . DOI: http://dx.doi.org/10.3329/sja.v10i2.18331 SAARC J. Agri., 10(2): 95-105 (2012)

Bangladesh being a developing country, always tries to control the market prices of coarse rice for stable political and social condition. The main aim of this paper is to find out appropriate deterministic time series model using the latest selection criteria that could best describe the coarse rice price pattern in Bangladesh during the time period July 1975 to December 2011. A total of 438 secondary data on monthly wholesale prices of coarse rice from July 1975 to December 2011 have been used for time series analysis. In this study growth models of different types are fitted using the software package SPSS 20 for the selected time series. The study reveals that cubic model is the best fitted model for wholesale price of coarse rice on the basis of model selection criterion (R2, R2 , RMSE, AIC, BIC, MAE and MAPE). Cubic growth rates varied from 0.68% to 4.03%. After choosing the best growth model by the model selection criteria the coarse rice prices are forecasted for the time period January 2012 to December 2013. DOI: http://dx.doi.org/10.3329/pa.v22i1-2.16480 Progress. Agric. 22(1 & 2): 193-201, 2011