Parvej Hasan Jon

OverviewAI-generated summary

Parvej Hasan Jon's research focuses on the application of machine learning and artificial intelligence techniques to address challenges in agriculture and food science. He has investigated automated detection systems for tea leaf diseases, employing convolutional neural networks (CNNs) for image analysis. Jon's work also includes the optimization of extraction processes for bioactive compounds and pectin from agricultural byproducts, such as watermelon rinds and citrus lemon peels. These extraction methods often utilize hybrid techniques, including ultrasound and microwave assistance, with optimization guided by response surface methodology (RSM) and artificial neural networks (ANNs).

Further research extends to the development of edible coatings for extending the shelf life of fruits like strawberries. These coatings are formulated using alginate, guar gum, and pectin, with their performance optimized through machine learning approaches. Jon has also explored the creation of biodegradable packaging films derived from pectin and nanocellulose. His scholarly output includes work on statistical models for analyzing agricultural production and consumption, particularly concerning the tea industry in Bangladesh.

Metrics

• h-index: 4
• Publications: 8
• Citations: 42