Tobacco Origin

Research on tobacco origin focuses on identifying and quantifying tobacco products and their sources, primarily to combat illicit trade and understand market dynamics. Current methods leverage machine learning, including deep learning architectures for image and text analysis, and broad learning systems with fuzzy subsystems for analyzing near-infrared spectroscopy data to rapidly and accurately classify tobacco origins. These advancements improve the speed and accuracy of tobacco origin identification, aiding in regulatory efforts and providing valuable insights into the tobacco industry.