Articles

The reeling machines and technologies commonly utilized in Bangladesh are inadequate for producing quality and quantity raw silk. Therefore, there was an urgent need to replace the current reeling machines and technologies to enhance the quality and volume of raw silk production. Considering these factors, this experiment was carried out, leading to the development of an improved modern reeling machine at BSRTI. The raw silk generated by this machine outperformed the silk produced by conventional multi-end reeling machines in both quality and quantity. This experiment was conducted to enhance the quality of raw silk while reducing reeling costs by developing a modern reeling machine. This experiment was undertaken to improve the quality of raw silk and to minimize the reeling cost by fabricating a modern reeling machine. The result of this study revealed that the fabricated modern reeling machine showed the highest reelability% 69.72 with the lowest renditta 9.83 compared to the multi-end reeling machine with reelability% 65.94 and renditta 11.24. A significant difference was also recorded for that the average size (d), size deviation, maximum size deviation, wending breaks, tenacity (g/d), elongation %, and cohesion between fabricated modern reeling machine and multi-end reeling machine. Considering the reeling performances and raw silk quality, the fabricated modern reeling machine showed better performance compared to the multi-end reeling machine.

Silk production in Bangladesh's rural economy, which is the practice of raising silkworms, has long been an essential part of the country’s rural economy and this has contributed a lot to the national economy as well as improved people’s lives. Traditional sericulture however faces problems such as pest infestations, inconsistent yields of mulberry leaves, wasteful use of resources and effects of climatic change despite the country having favorable climate that supports silk farming and availability of a skilled labor force. These challenges can be addressed through recent technological innovations including artificial intelligence technology and drone surveillance for instance. Drones fitted with cameras combined with GPS have ability to control fully grown mulberry farms whereas artificial intelligence system analyze data on optimal resource management in terms of pests’ control among others. The objective is to establish how drones and AI can affect Bangladeshi sericulture farming field primarily in Jessore and Rajshahi – two most important sericulture areas in the country. For two crop cycles namely July-October 2022 and March-June 2023, research used drones along with TensorFlow for AI integration where it recorded aspects such as leaf yield, pest loads, input application rates among others. Technologies integrations had resulted to increased mulberry leaf yield by approximately 18% from 2500Kg/ha to 2950Kg/ha.