Fast inline tobacco classification by near-infrared hyperspectral imaging and support vector machine-discriminant analysis

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Near-infrared hyperspectral imaging combined with support vector machine-discriminant analysis provides an effective method for the fast inline classification of tobacco leaves. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Marcelo C.A. Marcelo; Frederico Luis Felipe Soares; Jorge Armando Ardila; Jailson C. Dias; Ricardo Pedó; Samuel Kaiser; Oscar F.S. Pontes; Carlos E. Pulcinelli; Guilherme Post Sabin

doi:10.1039/c9ay00413k

January 1, 2019Analytical Methods

Fast inline tobacco classification by near-infrared hyperspectral imaging and support vector machine-discriminant analysis

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Abstract

Classification systems are frequently used in tobacco Green Leaf Threshing (GLT) facilities to assess the chemical characteristics and quality of tobacco leaves.

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Marcelo et al. (2019) studied this question.

synapsesocial.com/papers/6a060396f66c1d959e9f428a https://doi.org/10.1039/c9ay00413k

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Fast inline tobacco classification by near-infrared hyperspectral imaging and support vector machine-discriminant analysis

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Fast inline tobacco classification by near-infrared hyperspectral imaging and support vector machine-discriminant analysis

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