Online prediction method for chemical components in tobacco leaf curing process based on transfer learning and near infrared spectrum

Abstract

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.

Description

technical field [0001] The invention belongs to the technical field of tobacco leaf curing process analysis, in particular to an online prediction method for chemical components in the tobacco leaf curing process based on transfer learning and near-infrared spectroscopy. Background technique [0002] Baking is an important link in determining the final quality of tobacco leaves. The three-stage baking method currently used mainly coordinates the transformation of moisture and substances by controlling the temperature and humidity at different times, so as to achieve the baking goals of yellowing, drying, and aroma. . As a green, non-destructive and rapid process analysis technique, near-infrared spectroscopy can reflect the characteristics of the internal chemical components of tobacco leaves, and has been widely used in the analysis of tobacco leaf curing process. [0003] Due to the influence of environment, climate and other factors, the composition information of tobacc...

AI Technical Summary

Problems solved by technology

[0003] Due to the influence of environment, climate and other factors, the composition information of tobacco leaves in different years will be different, and the corresponding spectral information will also change accordingly, making the composition detection model based on near-infrared spectroscopy technology in the tobacco leaf curing process no longer applicable. For new samples, if the built model is directly used for the prediction of new tobacco leaf samples, very poor prediction results may be obtained or the model may fail

However, to rebuild an accurate and stable model every year, it is necessary to re-collect samples and measure data. The workload is heavy, the cycle is long, the cost is high, and it does not meet the requirements of actual use.

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