Logotipo do repositório
 

Publicação:
Sex type determination in papaya seeds and leaves using near infrared spectroscopy combined with multivariate techniques and machine learning

dc.contributor.authorFernandes, Thiago Feliph Silva [UNESP]
dc.contributor.authorSilva, Raíssa Vanessa de Oliveira
dc.contributor.authorFreitas, Daniel Lucas Dantas de
dc.contributor.authorSanches, Alex Guimarães [UNESP]
dc.contributor.authorSilva, Maryelle Barros da [UNESP]
dc.contributor.authorCunha Júnior, Luis Carlos
dc.contributor.authorLima, Kássio Gomes de
dc.contributor.authorTeixeira, Gustavo Henrique de Almeida [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionQuímica Biológica e Quimiometria
dc.contributor.institutionUniversidade Federal de Goiás (UFG)
dc.date.accessioned2022-04-28T19:49:04Z
dc.date.available2022-04-28T19:49:04Z
dc.date.issued2022-02-01
dc.description.abstractPapaya trees (Carica papaya L.) can bear female, hermaphrodite, and male flowers. However, only the hermaphrodite type produces elongate fruit required and appreciated by the consumer market. Sex type determination is carried out based on the plant phenotype after planting the seedlings, increasing the production costs. In this regard, the objective of this study was to verify the feasibility of using near infrared spectroscopy (NIR) as a non-destructive method for sexing papaya trees. The NIR spectra were collected using seeds and leaves of the respective seedlings of the cultivars ‘T2′, ‘Formosa’, and ‘Calimosa’ (Formosa group), and ‘THB’ and ‘Ouro’ (Solo group). By using the seeds, it was possible to obtain a F-score value of 0.81 for the external validation set applying the principal component analysis and quadratic discriminant analysis (PCA-QDA). By using the leaves, the F-score values was slightly lower (0.79) applying PCA and linear discriminant analysis (PCA-LDA). It was possible to use NIR spectroscopy associated with multivariate techniques as a non-destructive method to determine the sex types in papaya trees using both seeds and leaves of the seedlings.en
dc.description.affiliationUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Agrárias e Veterinárias (FCAV) Campus de Jaboticabal Departamento de Ciências da Produção Agrícola Via de Acesso Prof. Paulo Donato Castellane s/n
dc.description.affiliationUniversidade Federal do Rio Grande do Norte Instituto de Química Química Biológica e Quimiometria Departamento de Química, Lagoa Nova
dc.description.affiliationUniversidade Federal de Goiás (UFG) Escola de Agronomia Campus Samambaia. Departamento de horticultura. Av. Esperança s/n
dc.description.affiliationUnespUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Agrárias e Veterinárias (FCAV) Campus de Jaboticabal Departamento de Ciências da Produção Agrícola Via de Acesso Prof. Paulo Donato Castellane s/n
dc.identifierhttp://dx.doi.org/10.1016/j.compag.2021.106674
dc.identifier.citationComputers and Electronics in Agriculture, v. 193.
dc.identifier.doi10.1016/j.compag.2021.106674
dc.identifier.issn0168-1699
dc.identifier.scopus2-s2.0-85122320370
dc.identifier.urihttp://hdl.handle.net/11449/223178
dc.language.isoeng
dc.relation.ispartofComputers and Electronics in Agriculture
dc.sourceScopus
dc.subjectCarica papaya L
dc.subjectChemometrics
dc.subjectPCA-LDA
dc.subjectPCA-QDA
dc.subjectSexing
dc.titleSex type determination in papaya seeds and leaves using near infrared spectroscopy combined with multivariate techniques and machine learningen
dc.typeArtigopt
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Agrárias e Veterinárias, Jaboticabalpt

Arquivos