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Robust PLS models for soluble solids content and firmness determination in low chilling peach using near-infrared spectroscopy (NIR)

dc.contributor.authorNascimento, Paloma Andrade Martins [UNESP]
dc.contributor.authorCarvalho, Lívia Cirino de [UNESP]
dc.contributor.authorJúnior, Luis Carlos Cunha
dc.contributor.authorPereira, Fabíola Manhas Verbi [UNESP]
dc.contributor.authorTeixeira, Gustavo Henrique de Almeida [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal de Goiás (UFG)
dc.date.accessioned2018-12-11T16:39:26Z
dc.date.available2018-12-11T16:39:26Z
dc.date.issued2016-01-01
dc.description.abstractThe objectives of this study was to develop partial least square (PLS) models using NIR spectroscopy for the determination of SSC and firmness in intact low chilling 'Aurora-1' peach fruit, and verify the influence of maturity stage and harvest season on the models to be developed (robustness). FT-NIR spectra were obtained as log 1/R with fruit harvested in 2013 at 3 maturity stages and in 2014. The spectra were collected on the background and blush colour skin areas of the each fruit. Model performance was evaluated based on the values of root mean square error for prediction (RMSEP) and coefficient of determination (RP 2) obtained from validation fruit set (Kennard-Stone), and prediction fruit set (2014). PCA could not group the fruit based on blush and background skin colour, maturity stages, and harvest season. The model constructed using the external validation method obtained a RMSEVE of 1.08 % with 11 latent variables (LVS) and a RVE 2 of 0.59. The prediction set, independent data, resulting in a less accurate model (RMSEP 1.04 %, Rp 2 0.45 and 11 LVS). The same trend happened for determining firmness with the external validation resulting in better model with RMSEVE 9.51N and RVE 2 of 0.40 and the prediction set with RMSEP of 13.2N, RP 2 0.40 with 7 LVS. The NIR spectroscopy showed to be a potential analytical method to determine SSC and firmness of intact low chilling 'Aurora 1' cultivar. However, it is necessary to optimize the models in other to reduce the prediction errors.en
dc.description.affiliationUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Farmacêuticas (FCFAR), Campus de Araraquara. Rod. Araraquara- Jau, km.1 s/n
dc.description.affiliationUniversidade Federal de Goiás (UFG), Escola de Agronomia (EA), Setor de Horticultura, Avenida Esperança s/n - Campus Universitario
dc.description.affiliationUniversidade Estadual Paulista (UNESP), Instituto de Química (IQ), Campus de Araraquara, Rua Prof. Francisco Degni, 55
dc.description.affiliationUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Agrárias e Veterinárias (FCAV), Via de acesso Prof. Paulo Donato Castellane s/n
dc.description.affiliationUnespUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Farmacêuticas (FCFAR), Campus de Araraquara. Rod. Araraquara- Jau, km.1 s/n
dc.description.affiliationUnespUniversidade Estadual Paulista (UNESP), Instituto de Química (IQ), Campus de Araraquara, Rua Prof. Francisco Degni, 55
dc.description.affiliationUnespUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Agrárias e Veterinárias (FCAV), Via de acesso Prof. Paulo Donato Castellane s/n
dc.format.extent345-351
dc.identifierhttp://dx.doi.org/10.1016/j.postharvbio.2015.08.006
dc.identifier.citationPostharvest Biology and Technology, v. 111, p. 345-351.
dc.identifier.doi10.1016/j.postharvbio.2015.08.006
dc.identifier.file2-s2.0-84943385060.pdf
dc.identifier.issn0925-5214
dc.identifier.lattes5704445473654024
dc.identifier.orcid0000-0002-8117-2108
dc.identifier.scopus2-s2.0-84943385060
dc.identifier.urihttp://hdl.handle.net/11449/168061
dc.language.isoeng
dc.relation.ispartofPostharvest Biology and Technology
dc.relation.ispartofsjr1,480
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectAurora 1
dc.subjectChemometrics
dc.subjectMaturity stages
dc.subjectPLS
dc.subjectPrunus persica L
dc.titleRobust PLS models for soluble solids content and firmness determination in low chilling peach using near-infrared spectroscopy (NIR)en
dc.typeArtigo
unesp.author.lattes5704445473654024(4)
unesp.author.orcid0000-0002-8117-2108(4)

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