Infrared thermal profiling and management of diseases affecting the biological cycle of Antheraea assamensis silkworm

The present study has been designed to establish the thermal profile of complete life cycle of the Antheraea assamensis (muga) silkworms starting from the eggs to the moth. The current study also concurrently addresses the applicability of infrared thermography (IRT) to detect muga larvae infected with pebrine. Because of its non-contact advantage, IRT imaging can be successfully manoeuvred to reduce the risk of spreading infections and ultimately lead to increased silk production. The images and data obtained by the non-invasive IRT technology can be implemented, analysed and translated into deep learning algorithm-based machine learning called ‘smart data’, which can be fine-tuned to develop an artificial intelligence (AI) and decision support system (DSS) for the management and monitoring of silkworms in their entire life progression. Hence, this will boost their productivity, which will further revolutionize their yearly production and convey attractive revenues in the global silk picturesque.