Abstract
The objective of this study was to evaluate the performance of a handheld NIR spectrometer for non-destructive quality analysis of apples and pears produced in the Brazilian Semi-arid region. NIR spectra were acquired with a portable spectrometer in the wavelength range of 750–1065 nm and reference analyses of dry matter content (DMC) and soluble solids content (SSC) were measured weekly during 10 weeks of storage at 0.5 °C. Spectra were pre-processed with standard normal variate and used to develop DMC and SSC models using partial least squares regression with full cross-validation. The models were validated using data not included in the calibration. Satisfactory prediction results were obtained for SSC in apples (R² = 0.58) and pears (R² = 0.55), and for DMC in apples (R² = 0.55) and pears (R² = 0.65). All prediction models showed a relative root mean square error of prediction lower than 8%. These findings indicate that the NIR spectrometer is a promising tool to be used for a rapid and non-destructive determination of internal quality traits in apples and pears.
Index terms
partial least squares regression; multivariate regression; fruit quality; soluble solids; dry matter
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