FT-MIR determination of taste-related compounds in tomato: a high throughput phenotyping analysis for selection programs

Abstract

BACKGROUND:Tomatotasteisdefinedbytheaccumulationofsugarsandorganicacids.Individualanalysesofthesecompoundsusing high-performance liquid chromatography (HPLC) or capillary zone electrophoresis (CZE) are expensive, time-consumingand are not feasible for large number of samples, justifying the interest of spectroscopic methods such as Fourier-transformmid-infrared(FT-MIR).ThisworkanalyzedtheperformanceofFT-MIRmodelstodeterminetheaccumulationofsugarsandacids,considering the efficiency of models obtained with different ranges of variation.RESULTS: FT-MIR spectra (five-bounce attenuated total reflectance, ATR) were used to obtain partial least squares (PLS) modelsto predict sugar and acid contents in specific sample sets representing different varietal types. A general model was alsodeveloped, obtainingR2values for prediction higher than 0.84 for main components (soluble solids content, fructose, glucose,and citric acid). Root mean squared error of prediction (RMSEP) for these components were lower than 15% of the mean contentsand lower than 6% of the highest contents. Even more, the model sensitivity and specificity for those variables with a 10%selection pressure was 100%. That means that all samples with the 10% highest content were correctly identified. The modelwas applied to an external assay and it exhibited, for main components, high sensitivities (>70%) and specificities (>96%).RMSEP values for main compounds were lower than 21% and 13% of the mean and maximum content respectively.CONCLUSION: The models obtained confirm the effectiveness of FT-MIR models to select samples with high contentsof taste-related compounds, even when the calibration has not been performed within the same assay.