Comparing the analytical performances of Micro-NIR and Ft-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms

Autor(es)

Malegori, Cristina ; Nascimento Marques, Emanuel Jose ; de Freitas, Sergio Tonetto ; Pimentel, Maria Fernanda ; Pasquini, Celio ; Casiraghi, Ernestina

• Tipo de documento: Artigo Científico
• Fonte: Talanta; v. 165, p. 112-116, APR 1 2017.
• Citações Web of Science: 33

Resumo

The main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer in the evaluation of the prediction accuracy. In particular, the aim of this study was to estimate in a non-destructive manner, titratable acidity and ascorbic acid content in acerola fruit during ripening, in a view of direct applicability in field of this new miniaturised handheld device. Acerola (Malpighia emarginata DC.) is a super-fruit characterised by a considerable amount of ascorbic acid, ranging from 1.0% to 4.5%. However, during ripening, acerola colour changes and the fruit may lose as much as half of its ascorbic acid content. Because the variability of chemical parameters followed a non-strictly linear profile, two different regression algorithms were compared: PLS and SVM. Regression models obtained with Micro-MR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-MR data give comparable results using both SVM and PLS algorithms, with lower errors for SVM regression. The prediction ability of the two instruments was statistically compared using the Passing-Bablok regression algorithm; the outcomes are critically discussed together with the regression models, showing the suitability of the portable Micro-NIR for in field monitoring of chemical parameters of interest in acerola fruits. (AU)

• Processo FAPESP: 08/57808-1 - Instituto Nacional de Ciências e Tecnologias Analíticas Avançadas - INCTAA
• Beneficiário: Celio Pasquini
• Modalidade de apoio: Auxílio à Pesquisa - Temático