Research on the Characteristic Spectrum Selection Method of CARS on Building NIR Calibration Model to Detect Thickness of Flue-cured Tobacco

HU Weiyao; LING Jun; YANG Panpan; YANG Shihua; WANG Yu; LI Wei; YUAN Tianjun; LI Chengbin

doi:10.16211/j.issn.1004-390X(n).2017.02.014

JOURNAL OF YUNNAN AGRICULTURAL UNIVERSITY（Natural Science） > 2017 > 32(2): 288-293. > DOI: 10.16211/j.issn.1004-390X(n).2017.02.014

HU Weiyao, LING Jun, YANG Panpan, et al. Research on the Characteristic Spectrum Selection Method of CARS on Building NIR Calibration Model to Detect Thickness of Flue-cured Tobacco[J]. JOURNAL OF YUNNAN AGRICULTURAL UNIVERSITY（Natural Science）, 2017, 32(2): 288-293. DOI: 10.16211/j.issn.1004-390X(n).2017.02.014

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Research on the Characteristic Spectrum Selection Method of CARS on Building NIR Calibration Model to Detect Thickness of Flue-cured Tobacco

1.
Technology Centre of China Tobacco Yunnan Industrial Co., Kunming 650231, China
2.
Yunnan Comtestor Detection Technology Co., Ltd., Kunming 650106, China
3.
Yunnan Reascend Tobacco Technology(Group) Co., Ltd., Kunming 650106, China

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Received Date: January 27, 2016
Revised Date: March 17, 2016
Published Date: March 29, 2017

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Abstract

Abstract

The thickness of tobacco is an important factor to measure the quality and grading of flue-cured tobacco. The present study shows that it is feasibility to prediction thickness of tobacco by fourier transform near-infrared(FT-NIR)spectrometry. Two methods of screening spectrum range that calculated by competitive adaptive reweighted sampling method (CARS) and directly use the spectrum range (1 000-2 500 nm) had been combined with partial least squares (PLS) to establish the FT-NIR model. The results show that the number of variables of the thickness of tobacco FT-NIR model also had reduced to 180 from 1 543. The number of principal components also had reduced 6 from 10. The lower of standard error of calibration (SEC) and root mean square error of cross validation (RMSECV) was 0.003 4 and 0.010 3, respectively.Thirty samples had been used as external validation. The standard error of validation (SEV) and standard deviation of validation error (SDV) reduced to 0.001 1 from 0.018 2. According NIR model of paired-t tests of measured and prediction value, the results have no significant variance at level of 0.05.The CARS-NIR model have smaller variance. The stability and forecasting accuracy of FT-NIR model had been developed improved by the CARS method to select the sensitive wavelengths.

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References (26)

References

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