02552naa a2200325 a 450000100080000000500110000800800410001902400390006010000170009924501880011626000090030452015320031365000250184565000120187065000110188265000160189365000150190965300320192465300130195665300320196965300250200165300310202665300340205770000220209170000220211370000200213570000170215570000180217277300360219020611082018-01-17       2017    bl uuuu     u00u1 u    #d7 a10.1016/j.talanta.2016.12.0352DOI1 aMALEGORI, C.  aComparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms.h[electronic resource]  c2017  aThe 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-NIR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-NIR 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.  aMalpighia emarginata  aAcerola  aAcidez  aMaturação  aVitamina C  aMáquinas vector de suporte  aMicroNIR  aPartial Least Squares (PLS)  aPassing-Bablok regre  aRegressão de Passo-Bablok  aSupport Vector Machines (SVM)1 aMARQUES, E. J. N.1 aFREITAS, S. T. de1 aPIMENTEL, M. F.1 aPASQUINI, C.1 aCASIRAGHI, E.  tTalantagv. 165, 112-116, 2017.