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

"This is the peer reviewed version of the following article: Ibáñez, Ginés, Mercedes Valcárcel, Jaime Cebolla-Cornejo, and Salvador Roselló. 2019. FT-MIR Determination of Taste-related Compounds in Tomato: A High Throughput Phenotyping Analysis for Selection Programs. Journal of the Science of Food and Agriculture 99 (11). Wiley: 5140 48. doi:10.1002/jsfa.9760, which has been published in final form at https://doi.org/10.1002/jsfa.9760. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."
[EN] BACKGROUND: Tomato taste is defined by the accumulation of sugars and organic acids. Individual analyses of these compounds using high-performance liquid chromatography (HPLC) or capillary zone electrophoresis (CZE) are expensive, time-consuming and are not feasible for large number of samples, justifying the interest of spectroscopic methods such as Fourier-transform mid-infrared (FT-MIR). This work analyzed the performance of FT-MIR models to determine the accumulation of sugars and acids, 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) models to predict sugar and acid contents in specific sample sets representing different varietal types. A general model was also developed, obtaining R-2 values 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 contents and 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 model was 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 contents of taste-related compounds, even when the calibration has not been performed within the same assay. (c) 2019 Society of Chemical Industry