02242naa a2200277 a 450000100080000000500110000800800410001902200140006002400520007410000170012624501460014326000090028930000120029852014190031065300250172965300080175465300080176265300290177065300080179970000200180770000170182770000200184470000190186470000200188377300610190321245892022-08-16       2021    bl uuuu     u00u1 u    #d  a0022-11557 ahttps://doi.org/10.1007/s13197-020-04589-x2DOI1 aBORBA, K. R.  aNon-invasive quantification of vitamin C, citric acid, and sugar in "Valência" oranges using infrared spectroscopies.h[electronic resource]  c2021  a731-738  aNear (NIR) and mid (MIR) infrared spectroscopies have been studied as potential methods for non-destructive analyses of the fresh fruits quality. In this study, vitamin C, citric acid, total and reducing sugar content in ‘Valência’ oranges were evaluated using NIR and MIR spectroscopy with multivariate analysis. The spectral data were used to build up prediction models based on PLS (Partial Least Squares) regression. For vitamin C and citric acid, both NIR (r = 0.72 and 0.77, respectively) and MIR (0.81 and 0.91, respectively) resulted in feasible models. For sugars determination the two techniques presented a strong correlation between the reference values and analytical signals, with low RMSEP and r &gt 0.70 (NIR: sucrose RMSEP = 12.2 and r = 0.75; glucose RMSEP = 6.77 and r = 0.82; fructose RMSEP = 5.07 and r = 0.81; total sugar RMSEP = 12.1 and r = 0.80; reducing sugar RMSEP = 20.32 and r = 0.82; MIR: sucrose RMSEP = 9.47 and r = 0.80; glucose RMSEP = 6.70 and r = 0.82; fructose RMSEP = 5.20 and r = 0.81; total sugar RMSEP = 11.72 and r = 0.81; reducing sugar RMSEP = 20.42 and r = 0.81). The models developed with MIR presented lower prediction error rates than those made with NIR. Therefore, infrared techniques show applicability to determine of orange quality parameters in a non-destructive way.  aIntact fruit quality  aMIR  aNIR  aNon-destructive analyses  aPLS1 aSPRICIGO, P. C.1 aAYKAS, D. P.1 aFOSCHINI, M. M.1 aCOLNAGO, L. A.1 aFERREIRA, M. D.  tJournal of Food Science and Technology,v. 58gn. 2 2021.