Predicting apple (cv. Elshof) postharvest dry matter and soluble solids content with near infrared spectroscopy

Fruit dry matter (DM) and soluble solids content (SSC) are primarily composed of carbohydrate and are standard parameters for assessing quality. Near infrared spectroscopy provides potential for non-destructive fruit quality analysis but the collinearity between DM and SSC is an issue for prediction. Shorter wavelength spectra have been used for the prediction of fruit DM and SSC, but radiation between 1000 and 2500 nm may be suitable for distinguishing between the two forms of carbohydrate.

Spectra and DM and SSC samples were taken for a total of 450 'Elshof' apples 30, 58 and 93 days after harvest. Regression models were built using the interval partial least squares method. Prediction models for DM and SSC for each day yielded R² values between 0.63 and 0.86 and residual predictive deviations (RPDs) between 1.7 and 2.7 for DM, and R² = 0.76-0.85 and RPDs = 2.2-2.6 for SSC.

Model RPD values were not high enough for general quantitative predictions, although they compare well to previous work. Certain factors affected model success, including changes in fruit physiology over time and the range of reference data. The complexity of absorbance spectra for DM and SSC plus their strong correlation suggests that prediction models cannot easily distinguish between soluble and non-soluble forms of carbohydrate.