Adoption Trend of Climate-Resilient Rice Varieties in Bangladesh

Climate-adaptive strategies for enhancing agricultural resilience in southeastern coastal Bangladesh: Insights from farmers and stakeholders

Climate change impacts crop production worldwide, and coastal regions are particularly vulnerable to its adverse effects. Given the projected rise in temperature and shifting precipitation patterns, it is crucial to examine the current challenges faced by farmers in coastal Bangladesh. Using Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs), we assessed the perceptions and experiences of farmers and stakeholders regarding the existing agricultural practices, the challenges they face in crop cultivation, and the adoption of climate-adaptive practices in 2 sub-districts in the southeastern coastal region of Bangladesh. Moreover, using the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Terrestrial Water Storage Index (STI), we assessed the frequency and intensity of different climatic conditions in these two sub-districts. Results show that 100% of the respondents reported an increase in dry climatic conditions, the occurrence of untimely precipitation, and a decline in irrigation water during the cropping season. All the respondents in the FGDs expressed a loss of crop production because of these climate-induced disturbances. Despite these challenges, farmers have been implementing several climate-adaptive practices. Among the 9 mentioned climate-adaptive practices, 50% of FGD respondents utilize organic fertilizers, 42% cultivate heat- and drought-resilient crop varieties, use improved irrigation and harvest rainwater, and 25% cultivate integrated crops. The results of quantitative analysis of 3- and 6-month SPEI and STI values show that this region experienced frequent and intense dry climatic conditions during the growing-season, which supports the farmers' and stakeholders' concern about the increasing occurrence of droughts during crop growing periods. The results suggest that despite adopting climate-resilient practices under increasing growing-season droughts, farmers require support from the government and NGOs in capacity-building training and input support (e.g., stress-resilient seeds). This study holds practical implications for government, NGOs, and policymakers for ensuring sustainable agricultural productivity in the coastal region of Bangladesh.

Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh

High-resolution mapping of rice fields is crucial for understanding and managing rice cultivation in countries like Bangladesh, particularly in the face of climate change. Rice is a vital crop, cultivated in small scale farms that contributes significantly to the economy and food security in Bangladesh. Accurate mapping can facilitate improved rice production, the development of sustainable agricultural management policies, and formulation of strategies for adapting to climatic risks. To address the need for timely and accurate rice mapping, we developed a framework specifically designed for the diverse environmental conditions in Bangladesh. We utilized Sentinel-1 and Sentinel-2 time-series data to identify transplantation and peak seasons and employed the multi-Otsu automatic thresholding approach to map rice during the peak season (April-May). We also compared the performance of a random forest (RF) classifier with the multi-Otsu approach using two different data combinations: D1, which utilizes data from the transplantation and peak seasons (D1 RF) and D2, which utilizes data from the transplantation to the harvest seasons (D2 RF). Our results demonstrated that the multi-Otsu approach achieved an overall classification accuracy (OCA) ranging from 61.18% to 94.43% across all crop zones. The D2 RF showed the highest mean OCA (92.15%) among the fourteen crop zones, followed by D1 RF (89.47%) and multi-Otsu (85.27%). Although the multi-Otsu approach had relatively lower OCA, it proved effective in accurately mapping rice areas prior to harvest, eliminating the need for training samples that can be challenging to obtain during the growing season. In-season rice area maps generated through this framework are crucial for timely decision-making regarding adaptive management in response to climatic stresses and forecasting area-wide productivity. The scalability of our framework across space and time makes it particularly suitable for addressing field data scarcity challenges in countries like Bangladesh and offers the potential for future operationalization.

Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm

Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981-2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). Out of 24 ML algorithms, the four best ML methods, ranger, bagEarth, support vector machine, and random forest (RF) have been identified for the prediction of multi-scale drought indices. The RF classifier and the Boruta algorithms shows that water balance, precipitation, maximum and minimum temperature have a higher influence on drought intensity and occurrence across Bangladesh. The trend of spatio-temporal analysis indicates, drought intensity has decreased over time, but return time has increased. There was significant variation in changing the spatial nature of drought intensity. Spatially, the drought intensity shifted from the northern to central and southern zones of Bangladesh, which had an adverse impact on crop production and the livelihood of rural and urban households. So, this precise study has important implications for the understanding of drought prediction and how to best mitigate its impacts. Additionally, the study emphasizes the need for better collaboration between relevant stakeholders, such as policymakers, researchers, communities, and local actors, to develop effective adaptation strategies and increase monitoring of weather conditions for the meticulous management of droughts in Bangladesh.

Dealer-customer partnership in rice production demonstration: Assessment of private extension system in Bangladesh

Traditional public extension worker-farmer cooperation in rice production demonstration is not working efficiently, therefore, private partnership-based demonstration has been attempted to introduce as its alternative very recently involving dealer-customer farmer. The study evaluated the private extension services rendered through dealer-customer farmer cooperation in Bangladesh. Thirty-three rice seed dealers and ninety-two customer farmers formed the samples for the study. Face-to-face interviews were employed as a quantitative method while focus group discussion was used as a qualitative method in the present study. Involving in the private rice production demonstration approach, customer farmers indicated high profit, greater involvement in decision-making, and improved marketing skills as the major advantages; while the dealers stressed the benefit received by the small farmers, improvement in their decision-making capacity and increased local rice production. However, the slow distribution of inputs during the production period was a weakness in the arrangement, which was mostly because of the dealers' lack of understanding of the customer farmers' needs. The private extension system being a new concept in the country may be observed over a period and gradually extended to the nooks and crannies of the country.

Variations in the Major Nutrient Composition of Dominant High-Yield Varieties (HYVs) in Parboiled and Polished Rice of Bangladesh

Rice (Oryza sativa L.) is the principal staple food, a fundamental component of food security, a significant source of energy and major nutrients, and a key player in the overall nutritional status in Bangladesh. Parboiling is a common rice-processing treatment in Bangladesh. Recently, polishing has also become a common practice among millers seeking to attract consumers. Polishing may influence the nutrient composition of rice. The present study aimed to investigate the impact of parboiling and polishing on the nutritional content of the five High Yield Varieties (HYVs) of rice (BR11, BRRI dhan28, BRRI dhan29, BRRI dhan49, and BRRI dhan84) and their percent contributions to the Recommended Dietary Allowances (RDA) of vitamins and minerals. All of the rice samples were analyzed for proximate parameters, vitamins (B1, B2, B3, B6, and folate), and minerals (Ca, Mg, Fe, Zn, Na, K, P). Moisture, ash, fat, and total dietary fiber (TDF) were determined gravimetrically, according to the AOAC Official Methods; protein was measured by the Kjeldahl method; B-group vitamins were measured using Ultra Pressure Liquid Chromatography; and mineral content was determined by ICP-OES. The energy, protein, fat, and total dietary fiber (TDF) content of the samples ranged between 342-357 kcal/100 g, 6.79-10.74 g/100 g, 0.31-1.69 g/100 g, and 2.59-3.92 g/100 g respectively. Thiamin, riboflavin, niacin, pyridoxin, and folate content ranged from 0.11-0.25 mg/100 g, 0.01-0.05 mg/100 g, 2.82-6.42 mg/100 g, 0.12-0.30 g/100 g, and 5.40-23.95 g/100 g respectively. In a comparison of parboiling and polishing, macronutrients and vitamin retention were higher in parboiled unpolished rice than in polished unparboiled rice. The minerals (mg/100 g) Ca, Mg, Fe, Zn, Na, K, and P were in the ranges 32.82-44.72, 30.69-58.34, 0.51-0.70,1.83-2.79, 5.00-5.36, 106.49-112.73, and 162.23-298.03. Minerals of BRRI dhan84 were unaffected by polishing and parboiling. BRRI dhan84 contributed a higher percentage of RDA of all B vitamins and minerals. Therefore, to reduce nutrient loss in rice, industries and consumers should be encouraged to avoid polishing or limit polishing to 10% DOM and to consume unpolished rice, either parboiled or unparboiled.