Prediction of raspberries puree quality traits by Fourier transform infrared spectroscopy

- Models of some quality traits of raspberries were developed with FTIR spectroscopy.
- pH, TA and SSC were accurately predicted by FTIR and PLS regression.
- Glucose, fructose and sucrose models fitted perfectly.
- Prediction of vitamin C, phenolics and anthocyanins have to be improved.

FTIR applications combined with chemometric methods can provide alternative techniques to conventional methods to determine quality traits of fruits or vegetables. In the present study, these techniques were used to predict the main traits involved in sensory quality of raspberry fruits (such as soluble solids content, total acid, pH, fructose, glucose and sucrose) and the main bioactive compounds implied in antioxidant capacities (vitamin C, phenolics and anthocyanins). Partial Least Squares regressions (PLS) were used to develop the prediction models. A leave-one-out procedure has been performed to determine the optimal number of latent variables and the wavenumber selection; and k-one-out procedure (2/3, 1/3) to calibrate and to cross-validate the models. Excellent predictions were achieved for quality traits (pH, TA, SSC) with R2-greater than 0.90, except for TA prediction in the second validation steps where R2-value decreased to 0.61. Predictions of reducing sugars and sucrose were also excellent with R2-values above 0.95 in both validation steps. Models aiming at to predict bioactive compounds presented lower performances than sugar models. They remain acceptable and promising for vitamin C and phenolics (R2 ≥ 0.65; RMSECV ≤ 12%). Finally, the validation of anthocyanins prediction model did not give satisfactory results.