Understanding the information landscape in agricultural communities in rural Bangladesh

Mazumdar, Suvodeep; Ehdeed, Sukaina; Jiménez, Andrea; Ahmed, S Faisal; Momen, Sifat; Rasheduzzaman, Mirza

doi:10.1002/isd2.12245

Cited by 3 publications

(1 citation statement)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Positioned as the largest delta globally, Bangladesh is bestowed with rivers cascading from the Himalayas. Despite having fertile soil and advantageous seasons, the country has been unable to fully harness its agricultural potential due to limited access to cutting-edge technology [3] as well as the hesitancy to adopt new technologies due to wide number of factors including misconception, confusion and uncertainty [4]. Currently, it produces approximately 35 million metric tons of rice annually, falling short of meeting the demands of its growing population [5].…”

Section: Introductionmentioning

confidence: 99%

Towards Sustainable Agriculture: A Novel Approach for Rice Leaf Disease Detection Using dCNN and Enhanced Dataset

Bijoy,

Hasan,

Biswas

et al. 2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

Rice is one of the foremost food grains that dispenses sustenance to about half of the world's population. It is cultivated all over the world. The leaf disease detection of this crop is one of the chronic agricultural obstacles that farmers and planting experts have been struggling with for a long time. As a result of the leaf diseases, producing the amount of rice required to feed the world's rising population has become very challenging. Hence, automatically detecting rice leaf diseases is an inevitable task to increase productivity. Numerous deep learning based methods have been proposed for rice leaf disease detection, which we found rather inefficient considering the size of the models. In this article, we introduce a lightweight deep Convolutional Neural Network (dCNN) based method for rice leaf disease detection, that outperforms contemporary state-of-the-art methods and showcases competitive performance against 21 established benchmark architectures, including AlexNet, MobileNet, ResNet50, DenseNet121, ResNeXt50, ShuffleNet, ConvNext, EfficientNet, GogoleNet, SwinTransformer, VisionTransformer, and MaxVit, to name a few, with significantly lower trainable parameters. Notably, our method achieves an accuracy score of 99.81%, a precision score of 0.99828, a recall score of 0.99826, and an f1-score of 0.99827. Moreover, we enhance the rice leaf disease dataset by merging two existing datasets and supplemented them with an additional 95 manually annotated images gathered from publicly available sources on the internet. We also develop a comprehensive crop health monitoring system for farmers, and develop an open API for the automatic annotation of new instances, benefiting the research community at large. INDEX TERMS deep learning; deep convolutional neural network; rice leaf disease detection; leaf disease classification

show abstract

Section: Introductionmentioning

confidence: 99%

Towards Sustainable Agriculture: A Novel Approach for Rice Leaf Disease Detection Using dCNN and Enhanced Dataset

Bijoy,

Hasan,

Biswas

et al. 2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

Does joining online groups increase farmers' incomes in the mountainous areas of northern Vietnam? The role of information

Doanh

2024

JADEE

View full text Add to dashboard Cite

PurposeThis study analyzes whether farmers' incomes increase as they participate in online groups.Design/methodology/approachThe study analyzed interview data from 673 farming households in three mountainous provinces of northern Vietnam, utilizing the propensity score matching (PSM) method.FindingsThe empirical results reveal that farmers participating in online groups, particularly those engaged in 1–3 groups, experience an increase in their income attributed to the three advantages of sharing-accessing-saving (SAS) information. Farming households engaged in online groups earn higher incomes, ranging from equivalent to 25.78 to 26.96 USD, in comparison to those who do not participate. Notably, farmers participating in 1–3 online groups outpace their counterparts in 4–5 groups in terms of income.Research limitations/implicationsThis study exclusively focuses on examining farmers' total income derived from all their agricultural activities and does not quantify the specific impact of online group participation on the income generated by each product. Furthermore, it is important to note that the PSM method has the potential to introduce bias due to unobserved factors, such as social networks and local culture. Consequently, future research should prioritize the segmentation of income from individual agricultural products, distinct from the overall income, to gain a more nuanced understanding of each product’s sensitivity to information exchanged in online groups. Simultaneously, accounting for unobserved factors is crucial to obtain unbiased estimates.Originality/valueThis study represents the inaugural exploration into the comparison of farmers' incomes within a novel context – participation in digital-based groups. Furthermore, it extends the inquiry by delving into the correlation between the number of online groups joined and farmers' income. The empirical findings indicate that farmers may benefit the most by limiting their participation to a select few groups that align with their information needs and analytical abilities.

show abstract

Barriers, Challenges, and Requirements for ICT Usage among Sub-Assistant Agricultural Officers in Bangladesh: Toward Sustainability in Agriculture

et al. 2022

View full text Add to dashboard Cite

The present work is the first detailed study of sub-assistant agricultural officers (SAAOs), who are key players in delivering agriculture extension services in Bangladesh. We determined the status of information and communication technology (ICT) usage, knowledge gaps, approaches and tools for information delivery, barriers and obstacles to ICT usage, requirements for adoption, and possible solutions for efficient agriculture extension advisory services. We surveyed key respondents (SAAOs, n = 117) from nine sub-districts under the six administrative districts of Bangladesh with a semi-structured questionnaire. We found that 73.2% of all extension officers had basic knowledge of ICT. We observed that the most effective tool for information dissemination was field visits (90.90%, Moulvibazar district) and the most frequent extension approach was training and workshops (77.31%, Dhaka district). The best sources for information collection were broadcast media and social media. While delivering information, difficulty was found due to technical obstacles in Gazipur district, Rajshahi district, Sylhet district, and Dhaka district among 60% to 70% of SAAOs. However, farmers’ ignorance was reported in both Feni district and Moulvibazar district (36.36%). A shortage of computers in Gazipur district (56.25%) was an essential barrier to ICT usage for extension services. A major challenge in using ICT applications in Dhaka district was inadequate training support (64.51%). Mobile devices, internet connectivity, updated ICT applications, and a farmers’ database were the most important supports needed for the SAAO’s skilled advisory activities. In conclusion, our results and recommendations will help to redesign policies to improve infrastructure and allocate funding for capacity and skill development and ICT-based innovations in this sector to achieve sustainable extension and advisory services and attain food security in Bangladesh.

show abstract

Understanding the information landscape in agricultural communities in rural Bangladesh

Cited by 3 publications

References 59 publications

Towards Sustainable Agriculture: A Novel Approach for Rice Leaf Disease Detection Using dCNN and Enhanced Dataset

Towards Sustainable Agriculture: A Novel Approach for Rice Leaf Disease Detection Using dCNN and Enhanced Dataset

Does joining online groups increase farmers' incomes in the mountainous areas of northern Vietnam? The role of information

Barriers, Challenges, and Requirements for ICT Usage among Sub-Assistant Agricultural Officers in Bangladesh: Toward Sustainability in Agriculture

Contact Info

Product

Resources

About