Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/36943
Title: Espectroscopia no infravermelho próximo para classificação de frutos de morango quanto ao sistema de cultivo e tempo de armazenamento
Other Titles: Near infrared spectroscopy for strawberry fruit classification regarding the cultivation system and the storage period
Authors: Resende, Luciane Vilela
Santos, Heloisa Oliveira dos
Nassur, Rita de Cássia Mirela Resende
Keywords: Espectros
Fragaria x ananassa Duch
Near infrared spectroscopy (NIR)
Quimiometria
Spectra
Chemometrics
Issue Date: 26-Sep-2019
Publisher: Universidade Federal de Lavras
Citation: FERREIRA, T. C. R. Espectroscopia no infravermelho próximo para classificação de frutos de morango quanto ao sistema de cultivo e tempo de armazenamento. 2019. 78 p. Dissertação (Mestrado em Agronomia/Fitotecnia) - Universidade Federal de Lavras, Lavras, 2019.
Abstract: Near infrared spectroscopy (NIR) is a fast, accurate and non-destructive technique that can be used to determine the quality of harvested and marketed strawberry fruits. Therefore, this study aimed to verify the potential of NIR spectroscopy (Tensor 27 Bruker® equipment, with Fourier- transform near-infrared detector) to identify fruits from conventional cultivation and semi- hydroponic systemss, as well as to determine fruit quality parameters and storage period. Fruits of the cultivar San Andreas were harvested in two cultivation areas (conventional and semi- hydroponic) located in Bom Repouso, state of Minas Gerais. The randomized complete design (CRD) was adopted, using a 2 x 5 factorial, with three replications. Two cultivation systems (conventional and semi-hydroponic) associated with five storage periods (D0: harvest day, D2: second day, D4: fourth day, D6: sixth day and D8: eighth day) were studied, totaling 30 experimental plots with 10 fruits each. Fruits were harvested and stored in BOD at a constant temperature of 5 °C. Spectra were obtained by NIR analysis using whole fruits. The data were processed and analyzed by principal component analysis (PCA), partial least squares regression (PLS-R) and partial least discriminant analysis (PLS-DA), using Chemoface® statistical softaware. By using NIR associated with chemometric analysis, it was not possible to differentiate strawberry fruits from conventional and semi-hydroponic production systems. PCA showed spectral similarity and it was not possible to separate the treatments. By PLS-R the models obtained by NIR were inefficient. Nevertheless, it was possible to classify the fruits in relation to the storage period in each cultivation system using PLS-DA.
URI: http://repositorio.ufla.br/jspui/handle/1/36943
Appears in Collections:Agronomia/Fitotecnia - Mestrado (Dissertações)



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