Near infrared (NIR) diffuse reflectance was used to predict the contents of taste-related compounds of tomato. Models were obtained for several varietal types including processing tomato, cherry and cocktail tomato, mid-sized tomato and tomato landraces, with a wide range of varieties. Good performance was obtained for the prediction of soluble solids, sugars and acids, considering a non-destructive methodology applied to fruits with different internal structure. Specific models averaged RMSEP (%mean) values lower than 6.1% for SSC, 13.3% for fructose, 14.1% for glucose, 12.7% for citric acid, 13.8% for malic acid and 21.9% for glutamic acid. The performance was dependent on varietal type. General models with a higher number of samples and variation did not improve the performance of specific models. The models obtained, either specific or general, couldn't be extrapolated to external assays Ginés Ibáñez a

The genetic potential of accessions from Solanum section Lycopersicon (S. lycopersicum L., S. lycopersicum var. cerasiforme, S pimpinellifolium L., and S. habrochaites Knaap & Spooner) for breeding tomato taste has been studied in three environments with clonal replicates. The environment clearly affected the accumulation and level of variation of sugars and acids and derived variables through a direct effect. It seems that photosynthetically active radiation would exert a major effect on sugar accumulation while in the case of organic acids the effect of temperature might be more important. Even more, important genotype × environment interactions can considerably modify the real value of germplasm, being considerably higher in wild species. The environment affected not only mean contents but also the levels of variation. Thus, the need to develop multienvironmental screening programs is suggested to identify solid sources of variation. An important intraaccession variability was also found in wild germplasm, emphasizing the need to analyze a high number of plants per accession in order to identify sources of variation. Accessions with a significant genotypic contribution to the accumulation of sucrose within the Lycopersicon group were identified and may be interesting to analyze the regulation of vacuolar invertase. Accessions with different genotypic contributions to citric, malic, and glutamic acid accumulation have also been identified. These accessions will be valuable for the development of breeding programs considering the acid component of taste. Additionally, these genetic resources will be interesting to study the regulation of the tricarboxylic acid cycle and the gamma-aminobutyric acid shunt.

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 R2 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. © 2019 Society of Chemical Industry

30 E-noses can be routinely used to evaluate the volatile profile of tomato samples once the sensor drift 31 and standardization issues are adequately solved. Short-term drift can be corrected using a strategy 32 based on a multiplicative drift correction procedure coupled with a PLS adaptation of the Component Correction. It must be performed specifically for each sequence, using all sequence signals data. With 34 this procedure, a drastic reduction of sensor signal %RSD can be obtained, ranging between 91.5% 35 and 99.7%for long sequences and 75.7% and 98.8% for short sequences. On the other hand, long-36 term drift can be fixed up using a synthetic reference standard mix (with a representation of main 37 aroma volatiles of the species) to be included in each sequence that would enable sequence 38 standardization. With this integral strategy, a high number of samples can be analyzed in different 39 sequences, with a 94.4% success in the aggrupation of the same materials in PLS-DA two-40 dimensional graphical representations. Using this graphical interface e-noses can be used to 41 developed expandable maps of volatile profile similitudes, which will be useful to select the materials 42 that most resemble breeding objectives or to analyze which preharvest and postharvest procedures 43 have a lower impact on the volatile profile, avoiding the costs and sample limitations of gas 44 chromatography.