Prediction of Soluble Solids and Lycopene Content of Processing Tomato Cultivars by Vis-NIR Spectroscopy - Égei, Márton; Takács, Sándor; Palotás, Gábor; Palotás, Gabriella; Szuvandzsiev, Péter; Daood, Hussein Gehad; Helyes, Lajos; Pék, Zoltán (Frontiers in Nutrition, 2022)
Tomato-based products are significant components of vegetable consumption. The processing tomato industry is unquestionably in need of a rapid definition of soluble solids content (SSC) and the lycopene content. The objective was to find the best chemometric method for the estimation of SSC and lycopene content from visible and near infrared (Vis-NIR) absorbance and reflectance data so that they could be determined with the elimination of chemicals from the process. A total of 326 Vis-NIR absorbance and reflectance spectra and reference measurements were available to calibrate and validate prediction models. The obtained spectra can be manipulated using different pre-processing methods and multivariate data analysis techniques to develop prediction models for these two main quality attributes of tomato fruits. Eight different method combinations were compared in puree and intact fruit samples. For SSC prediction, the results showed that the best root mean squared error of cross validation (RMSECV) originated from raw absorbance (0.58) data and with MSC (0.59) of intact fruit in Vis-NIR, and 1st derivatives of reflectance (R²=0.41) for puree in the short-wave infrared (SWIR) region. The best predictive ability for lycopene content of puree in the SWIR range (R2=0.47; RMSECV=17.95 mg kg-1) was slightly lower than that of Vis-NIR (R2=0.68; 15.07 mg kg-1). The present study reports the suitability of two Vis-NIR spectrometers, absorbance/reflectance spectra, pre-processing methods and partial least square (PLS) regression to predict SSC and lycopene content of intact tomato fruit and puree.