Fecha de publicación: 25/02/2022 Fuente: Wipo Tobacco Agriculture The invention belongs to the technical field of tobacco leaf curing process analysis, and particularly relates to an online prediction method for chemical components in the tobacco leaf curing process based on transfer learning and a near infrared spectrum. The method comprises the steps of obtaining a tobacco spectrum in the tobacco leaf curing process; obtaining chemical component values of the tobacco leaves, wherein the chemical component values comprise moisture, starch, protein and total sugar; constructing a prediction model according to the tobacco leaf spectrum and the tobacco leaf curing chemical components; minimizing the difference between a training set tobacco leaf sample and a to-be-predicted feature data set by using a migration component analysis method, and carrying out multiple iterations on the data processed by the migration component analysis method by adopting a partial least square algorithm to train a curing process tobacco leaf chemical component prediction model; and conducting online prediction on the tobacco leaf curing process by using the updated new model, and evaluating a prediction result. The change trend of key chemical components in the tobacco leaf curing process can be predicted, and a basis is provided for accurate adjustment of the tobacco leaf curing process.