期刊
TALANTA
卷 165, 期 -, 页码 112-116出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2016.12.035
关键词
Acerola; Malpighia emarginata DC.; MicroNIR; Partial Least Squares (PLS); Support Vector Machines (SVM); Passing-Bablok regression
资金
- CNPq
- INCTAA
- FAPESP [573894/2008, 2008/57808-1]
- CAPES
- FACEPE
- NUQAAPE [APQ-0346-1.06/14]
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.
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