Correction of the moisture variation in wood NIR spectra for species identification using EPO and soft PLS2-DA

Kunze, Daniele Cristina Gomes da Cunha; Pastore, Tereza Cristina Monteiro; Rocha, Hugo S.; Lopes, Priscila Veras dos Anjos; Vieira, Rafaela Dornelas; Coradin, Vera Teresinha Rauber; Braga, Jez Willian Batista

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Campo DC	Valor	Idioma
dc.contributor.author	Kunze, Daniele Cristina Gomes da Cunha	-
dc.contributor.author	Pastore, Tereza Cristina Monteiro	-
dc.contributor.author	Rocha, Hugo S.	-
dc.contributor.author	Lopes, Priscila Veras dos Anjos	-
dc.contributor.author	Vieira, Rafaela Dornelas	-
dc.contributor.author	Coradin, Vera Teresinha Rauber	-
dc.contributor.author	Braga, Jez Willian Batista	-
dc.date.accessioned	2022-12-05T18:59:26Z	-
dc.date.available	2022-12-05T18:59:26Z	-
dc.date.issued	2021-09-17	-
dc.identifier.citation	KUNZE, Daniele C.G.C. et. al. Correction of the moisture variation in wood NIR spectra for species identification using EPO and soft PLS2-DA. Microchemical Journal, v. 171, art. 106839, dez. 2021. DOI 10.1016/j.microc.2021.106839. Disponível em: https://www.sciencedirect.com/science/article/pii/S0026265X21009255?via%3Dihub. Acesso em: 05 dez. 2022.	pt_BR
dc.identifier.uri	https://repositorio.unb.br/handle/10482/45253	-
dc.language.iso	Inglês	pt_BR
dc.publisher	Elsevier	pt_BR
dc.rights	Acesso Restrito	pt_BR
dc.title	Correction of the moisture variation in wood NIR spectra for species identification using EPO and soft PLS2-DA	pt_BR
dc.type	Artigo	pt_BR
dc.subject.keyword	Madeira - discriminação	pt_BR
dc.subject.keyword	Ortogonalização dos parâmetros externos	pt_BR
dc.subject.keyword	Madeira - umidade	pt_BR
dc.identifier.doi	https://doi.org/10.1016/j.microc.2021.106839	pt_BR
dc.description.abstract1	The NIRS technology, together with multivariate methods, has already proved to be capable of discriminating wood from different forest species that are visually similar and determining the provenance within the same species. However, models developed with dry wood under controlled conditions of humidity and temperature present prediction errors or high outlier exclusion rates when applied to the analysis of samples under different moisture conditions. This work proposes applying external parameter orthogonalization (EPO) to minimize the effect of moisture in the spectra of wood from native Brazilian species under different moisture conditions and enable its analysis by PLS-DA discrimination models. After correction, the models showed high-efficiency rates and a significant reduction in the number of outliers. For the model trained with oven-dried samples and validated with spectra measured on samples under environment conditions, it was observed that the rate of samples with inconclusive results (RIR) was reduced from 87.8% to 18.4% by using EPO. Under these conditions, efficiency rates of 93.5% were obtained for the identification of Carapa guianensis Aubl. (Andiroba), 98.6% for Swietenia macrophylla King (Mogno) and 100.0% for Cedrela odorata L. (Cedro), Erisma uncinatum Warm. (Cedrinho) and Micropholis melinoniana Pierre (Curupixa). ´ For the second validation set, with samples in more extreme moisture conditions, the same model without EPO correction had a RIR of 100.0%. In comparison the model with EPO had a RIR of 43.8%, demonstrating the feasibility of EPO in the correction of moisture interference in samples under moisture conditions different from those used in the model development. Applying more flexible criteria in the identification of samples by PLS-DA also favored the reduction of errors. Thus, EPO and soft-PLS-DA proved to be an effective strategy to enable the application of NIR technology in field conditions, such as in the inspection of illegal timber trade.	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0001-9417-8114	pt_BR
dc.contributor.email	mailto:jez@unb.br	pt_BR
dc.description.unidade	Instituto de Química (IQ)	pt_BR
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