11 research outputs found

    Potencies of Justicia adhatoda L. for its possible phytotoxic activity

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    The phytotoxic effects of Justicia adhatoda L. were investigated on cauliflower, broccoli, tomato, foxtail millet and barnyard grass. The experiments were carried out under laboratory and in pot experiments. Six different aqueous methanol extract concentrations (control, 0.001, 0.003, 0.01, 0.03 and 0.1 g DW equivalent mL-1 extract) were tested in the laboratory and six aqueous extract concentrations (control, 1.0, 2.0, 3.0, 4.0 and 5.0 g DW mL-1 extract equivalent) were evaluated in the pot experiment. Results showed a reduction in germination and growth (shoot length, root length and biomass weight) at higher extract concentration compared to control. The leaf extracts from J. adhatoda showed that the foxtail millet and barnyard grass are germinating below 50 % both in the laboratory condition and in the pot experiment at their maximum concentration. When maximum extracts have been applied, we have found less than 0.5 cm of shoot and root of foxtail millet and barnyard grass. Maximum dry weight reduction was observed in foxtail millet and barnyard grass at the same concentration. The findings show that J. adhatoda may have phytotoxic potential and thus contains phytotoxins. Therefore, J. adhatoda can be used in sustainable crop production as a mulch or soil additive to suppress weeds

    Adoption Determinants of Exotic Rice Cultivars in Bangladesh

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    Agrarian Bangladesh relies heavily on rice. Since independence, many varieties have been released and targeted to increase productivity, farmers' income, and food security. However, few gained widespread adoption. Moreover, farmers in the border regions are adopting exotic cultivars, and it's gradually spreading throughout the country. But, the reasons for adopting exotic rice cultivars are still unexplored. Using field data from 1,260 farm households and 42 focus group discussions, this study analyzes farmers' preferences for domestic and exotic rice varieties and identifies the factors of adoption linked to design national breeding programs and farmers' welfare. Findings show, exotic varieties (69%) monopolized the area coverage in the dry season, whereas in the wet season, domestic varieties (58%) dominated. Farmers select exotic varieties for their better yield and price, low production costs, high grain quality, resistance to pests and diseases, and ability to withstand stresses. Risk analysis shows domestic varieties adoption is riskier with lower returns. The empirical findings indicate that household characteristics, access to institutions and infrastructure, varietal characteristics, and weather condition, all play a significant role in adoption decisions. National breeding should focus on developing rice varieties in response to market demands and farmer preferences toward sustainable food security in Bangladesh

    Legumes in conservation agriculture: A sustainable approach in rice-based ecology of the Eastern Indo-Gangetic Plain of South Asia − an overview

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    Legumes in Conservation Agriculture (CA) have the potential to increase crop productivity and sustainability of the rice-based system. However, there is limited information available on the importance of legume crops in CA in the rice-based system of the Eastern Indo-Gangetic Plain (EIGP). Rice-based cropping is the mainstay of the people in Bangladesh, on the EIGP. These systems are the major food supplier to the region. In addition, they provide income and employment opportunities to the majority of people in the region. However, the system is facing unprecedented challenges and increased risk due to water, energy, labour and capital scarcity, which are exaggerated due to the effects of climate change. This could be further aggravated by deteriorating soil health, depleting underground water, and reduced land and water productivity which ultimately threaten sustainable food production and food security of the EIGP. Hence, sustainable crop intensification is essential, but increasing cropping intensity has reduced the yield of single crops by degrading soil properties. To address these constraints, Conservation Agriculture (CA), with a minimum tillage system, residue retention and crop diversification with legumes, could be an effective approach for improving crop productivity while sustaining the natural resources in intensive rice-based systems of EIGP. The addition of legumes in crop rotation is a suitable technique for crop diversification due to its multiple benefits related to soil health and natural resources. Diverse legume crops involving rice-based cropping exist at different agro-ecological zones in Bangladesh, and their rotation definitely could act a major role in promoting the CA in rice-based systems. Legume-based rotation offers multiple benefits, such as biological nitrogen fixation, improves soil pores through the deep root system, P-availability, soil fertility and enhanced nutrient cycling, and reducing the use of external input and thereby minimizing greenhouse gas emission and groundwater pollution, improving water productivity, and minimizes diseases and pest incidence. As a result, crop rotation with legumes has a high potential for CA and sustainable rice-based cropping systems in Bangladesh. The gaps between legume and non-legume crops in CA for each parameter suggest a noteworthy possibility for the improvement of rice-based systems in EIGP. This review suggests further sustainability improvements can be achieved through future field research focused on the inclusion of legume crops in the diverse rice-based systems under CA

    Effect of nutrient and weed management strategies on the yield performance of boro rice cv. BRRI dhan63

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    An experiment was conducted to study the yield components and yield of Boro rice (cv. BRRI dhan63) under different nutrient and weed management strategies. The experiment was laid out in a two factor randomized complete block design with three replications consisting of four nutrient management strategies viz. cowdung 10 t ha-1, recommended dose of chemical fertilizer (urea, triple super phosphate, muriate of potash, gypsum and zinc sulphate @ 258, 101, 120, 113 and 11.5 kg ha-1, respectively), 75% recommended dose of chemical fertilizer + cowdung 5 t ha-1 and 50% recommended dose of chemical fertilizer + cowdung 10 t ha-1; and five weed management strategies viz. weedy check, hand weeding twice at 15 and 30 days after transplanting (DAT), pre-emergence herbicide Panida at 3 DAT, post-emergence herbicide Granite at 10 DAT and Panida at 3 DAT + Granite at 10 DAT. Yield components and yield of Boro rice cv. BRRI dhan63 were significantly influenced by nutrient and weed management strategies. Application of 75% recommended dose of chemical fertilizer + cowdung 5 t ha-1 showed the highest values for all yield components and produced the highest grain yield (6.24 t ha-1) while among the weed management strategies, Panida at 3 DAT + Granite at 10 DAT produced the highest grain yield (6.39 t ha-1) and the interaction of this two treatments also produced the highest grain yield (6.97 t ha-1). Among the different nutrient management strategies, cowdung 10 t ha-1 produced the lowest values of most of the yield contributing characters and grain yield (4.92 t ha-1) while in case of weed management strategies weedy check produced the lowest grain yield (4.55 t ha-1) and the interaction of this two treatments also produced the lowest grain yield (4.05 t ha-1). Therefore, it can be concluded that 75% recommended dose of chemical fertilizer + cowdung 5 t ha-1 combined with Panida at 3 DAT + Granite at 10 DAT can be practiced for the cultivation of Boro rice cv. BRRI dhan63 to obtain the highest grain yield. [Fundam Appl Agric 2018; 3(2.000): 491-497

    Foreign direct investment and agricultural output nexus in Bangladesh: An autoregressive distributed lag approach

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    Foreign Direct Investment’s (FDI) contribution to the agricultural share of GDP is a questionable topic in Bangladesh’s current economy. Therefore, this study aims to inspect the effect of FDI inflow in agriculture on the agriculture sector’s contribution to Bangladesh’s economic development. The study used advanced econometric tools to the time series data obtained from the Bangladesh Bank and the Bangladesh Economic Review from 1996 to 2021. For the empirical analysis, the authors employ the Autoregressive Distributed Lag (ARDL) co-integration approach to measure short-run dynamics and long-run relationship between FDI inflow in agriculture (AFDI) and agricultural share to GDP (AGDP) in Bangladesh. The findings from the estimation confirm that AFDI has a statistically significant effect on AGDP in the short run; in the long run, it is insignificant. Bangladesh will have to improve its policy for creating the environment to attract FDI in the agricultural sector to draw more promising investments to boost agricultural productivity. In this regard, the country can reform its taxation and agricultural investment policies to create an ‘investment-friendly climate’ for attracting long-term foreign capital in agriculture

    Cultivation of Local Rice Varieties in Bangladesh: Assessing the Farm Level Determinants

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    One of the main objectives of the green revolution is to replace the local (traditional) cultivars with high-yielding varieties (HYVs). Replacing HYVs in the local cultivars-intensive areas would increase rice production and strengthen national food security. To do this, it is necessary to identify the determinants of cultivating local rice varieties by farmers. Therefore, this study used fractional logistic regression and a cognitive approach in the popular Aman and Boro season local rice variety-intensive areas to find out the causes of cultivating local rice varieties. The findings reveal that the main cause is the adverse ecology, where HYVs are not suitable, but local cultivars have physiological attributes to be well suited. The local cultivars are growing mainly in the Haor and flood-prone ecosystems, where modern varieties can not be sustained. The profitability of local rice cultivars is better than the HYVs as well. Moreover, farmers' socioeconomic conditions such as age, education, occupation, income, and farm size influence the cultivation of local rice varieties. The yield, land topography, and market price also have an impact on the adoption intensity of local cultivars. The farmers also opined that the special grain quality of the local rice cultivars attracts the farmers, consumers, and market price that lubricate the intensity of local rice varieties adoption in the specific areas of Bangladesh. The findings of this study would be helpful for the rice breeders, scientists, and policymakers to develop suitable modern rice cultivars and management packages for boosting rice production in the targeted local rice cultivars intensive areas of Bangladesh. [J Bangladesh Agril Univ 2023; 21(1.000): 46-56

    A Comprehensive Exploration of Outlier Detection in Unstructured Data for Enhanced Business Intelligence Using Machine Learning

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    Due to the rapid growth of online data, it is evident that social informatics faces a significant obstacle. The task of effectively utilizing this abundance of information for business intelligence purposes and extracting valuable insights from it across diverse and heterogeneous platforms presents a daunting challenge. Coordinating AI with business knowledge stands apart as an essential worry in the ongoing scene. Customarily, exceptions were many times excused as boisterous information, bringing about the deficiency of relevant data. This paper highlights the need to rethink how outliers are handled and shed light on the primary research challenges in this mining subfield. It presents a thorough scientific categorization of different Business Knowledge strategies and diagrams their ongoing application areas. Also, the paper talks about future exploration bearings and proposals to overcome any barrier concerning oddities in information examination, consequently empowering more successful business methodologies. This work plans to improve the usage of tremendous web-based information hotspots for better business insight results

    Revolutionizing Banking Decision-Making: A Deep Learning Approach to Predicting Customer Behavior

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    This article explores a machine learning approach focused on predicting bank customer behavior, emphasizing deep learning methods. Various architectures, including CNNs like VGG16, ResNet50, and InceptionV3, are compared with traditional algorithms such as Random Forest and SVM. Results show deep learning models, particularly ResNet50, outperform traditional ones, with an accuracy of 86.66%. A structured methodology ensures ethical data use. Investing in infrastructure and expertise is crucial for successful deep learning integration, offering a competitive edge in banking decision-making

    Epidemiological Profile of a Human Hepatitis E Virus Outbreak in 2018, Chattogram, Bangladesh

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    Hepatitis E virus (HEV) is a waterborne zoonotic disease that can result in a high fatality rate in pregnant women and infants. In 2018, a large HEV outbreak emerged in Chattogram, Bangladesh, resulting in 2800 cases and a significant public health response to mitigate the transmission. While the source of the outbreak remained poorly understood, authorities suggested that possible risk factors for HEV infection included contamination of water supply, exacerbated by concurrent severe flooding events in the community. A cross-sectional study was conducted to investigate the distribution and risk factors for HEV seroprevalence between January and December 2018 in the Chattogram city area. A total of 505 blood samples were collected from symptomatic patients of 10 hospitals who met the case definition for an HEV infection. Standard ELISA tests were performed in all patients to identify anti-HEV antibodies. The size and location of HEV seroprevalence clusters within Chattogram were investigated using SaTScan. We investigated the association between risk of HEV infection and individual and environmentally lagged risk factors using Bernoulli generalised linear regression models. Our results indicate an overall HEV seroprevalence of 35% with significant variation according to sex, source of drinking water, and boiling of drinking water. A positive cross-correlation was found between HEV exposure and precipitation, modified normalised difference water index (MNDWI), and normalised difference vegetation index (NDVI). Our model indicated that risk of infection was associated with sex, age, source of drinking water, boiling of water, increased precipitation, and increased MNDWI. The results from this study indicate that source and boiling of drinking water and increased precipitation were critical drivers of the 2018 HEV outbreak. The communities at highest risk identified in our analyses should be targeted for investments in safe water infrastructure to reduce the likelihood of future HEV outbreaks in Chattogram
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