Abstract: A USB2000+ micro spectrometer was used to acquire the transmittance spectra of Red Globe table grapes in the range of 400–1 000 nm. Moreover, the sugar content and acidity value were measured chemically. The original spectra were pretreated by SavitZky-Golay smoothing (SG) and then the singularity was eliminated by Monte-Carlo cross validation method (MCCV) followed by dimension reduction by competitive adaptive reweighted sampling for development of a random forest (RF) prediction model. The correlation coefficient and root mean square error of the sugar prediction model were 0.955 8 and 0.315 8 for the calibration set, and 0.956 8 and 0.318 5 for the validation set, respectively. The correlation coefficient and root mean square error of the acidity prediction model were 0.945 6 and 0.300 1 for the calibration set, and 0.940 5 and 0.311 2 for the validation set, respectively. The results showed that this method could be suitable for rapid, nondestructive and accurate detection of sugar content and acidity in Red Globe table grapes.

Key words: visible near infrared spectroscopy, Monte-Carlo cross validation, competitive adaptive weighting sampling, Red Globe table grape, sugar content, acidity