Method for matching cured tobacco leaves by using tobacco leaf beating and re-drying module

A technology of threshing and re-baking and module grouping, which is applied in the field of tobacco, can solve the problems of not considering the impact of existing cognition and discrimination results, and achieve the effect of accurate classification and combination, saving time and manpower

Active Publication Date: 2015-04-29
CHINA TOBACCO SICHUAN IND CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This new technology allows for quicker and more efficient analysis by analyzing infrared spectrometry (IR) data from cured toast or bread crumbs samples before they can be further processed into specific categories such as tobaccos that meet certain standards set forth in various regulations.

Problems solved by technology

This patented technical solution described in the previous describes a new way of producing high grade tobaccos (Tobacco Leaf) from plants grown indoors or outdoors. However, due to poorly understood factors such as weather conditions during growth, it can be difficult to achieve uniform productivity rates across all garnery units. Current solutions involve manual assessments and repeated experimentings, leading to slow downed timely delivery times. Therefore, the objective of this patents is to provide a more efficient and precise system for making Tobsilene safer cigarettage products while ensuring they perform well within specified standards.

Method used

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  • Method for matching cured tobacco leaves by using tobacco leaf beating and re-drying module
  • Method for matching cured tobacco leaves by using tobacco leaf beating and re-drying module
  • Method for matching cured tobacco leaves by using tobacco leaf beating and re-drying module

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] Huili area module leaf-threshing assembly method:

[0044] Through sensory evaluation, according to the modeling requirements of the aroma module, smoke module and taste module, 62 tobacco leaf modeling samples of the aroma module, 70 tobacco leaf modeling samples of the smoke module, and 54 tobacco leaf modeling samples of the taste module were collected. Each sample is 500g. The modeling samples were dried in an oven at 40°C for 2 hours, crushed and passed through a 60-mesh sieve. After scanning the modeling sample on the near-infrared spectrometer, the near-infrared spectrum of the modeling sample is obtained, and the spectrum acquisition range is 12000-4000cm –1 , resolution 8cm –1 , the number of scans is 64 times. The method of combining WT and SNV is used to preprocess the spectrum, and the method of singular value decomposition is used to analyze the –1 And 6200~9300cm –1 The spectral data matrix in the two regions is subjected to principal component calculati

Embodiment 2

[0050] The combination method of module leaf threshing in Panzhihua area:

[0051] Through sensory evaluation, according to the modeling requirements of aroma module, smoke module and taste module, 52 tobacco leaf modeling samples of aroma module, 95 tobacco leaf modeling samples of smoke module, and 74 tobacco leaf modeling samples of taste module were collected respectively. Each sample is 500g. The modeling samples were dried in an oven at 40°C for 2 hours, crushed and passed through a 60-mesh sieve. After scanning the modeling sample on the near-infrared spectrometer, the near-infrared spectrum of the modeling sample is obtained, and the spectrum acquisition range is 12000-4000cm –1 , resolution 8cm –1 , the number of scans is 64 times. The method of combining WT and SNV is used to preprocess the spectrum, and the method of singular value decomposition is used to analyze the –1 And 6200~9300cm –1 The spectral data matrix in the two regions is subjected to principal compo

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Abstract

The invention discloses a method for matching cured tobacco leaves by using a tobacco leaf beating and re-drying module. The method comprises the following steps: performing classified collection on tobacco leaf samples of an aroma module, a smoke module and a mouthfeel module to serve as modeling samples by adopting a sensory evaluation method; then preparing the modeling samples into powder, scanning and acquiring a near infrared spectrogram, preprocessing the spectrogram, then performing calculation on principal components, and creating a Naive Bayes classification model by using principle component scores; and then preparing to-be-matched tobacco leaf samples into powder, acquiring a near infrared spectrum, preprocessing the spectrum, then performing principle component decomposition operation on the spectrum of the to-be-matched tobacco leaf samples by using spectrum data loads of the modeling samples to obtain principle component scores of the to-be-matched tobacco leaf samples, classifying the to-be-matched tobacco leaves by using the principle component scores and the Naive Bayes classification model, and performing module matching according to a classification result. By adopting the method disclosed by the invention, the sensory evaluation is only needed at a modeling stage, manpower and time are saved, and the to-be-matched tobacco leaves can be classified and matched quickly and accurately.

Description

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Claims

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Application Information

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Owner CHINA TOBACCO SICHUAN IND CO LTD
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