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ZENODO
Dataset . 2019
License: CC BY SA
Data sources: ZENODO
ZENODO
Dataset . 2019
License: CC BY SA
Data sources: Datacite
ZENODO
Dataset . 2019
License: CC BY SA
Data sources: Datacite
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FT-MIR determination of taste-related compounds in tomato: a high throughput phenotyping analysis for selection programs

Authors: Ibañez, Ginés; Valcárcel, Mercedes; Cebolla-Cornejo, Jaime; Roselló, Salvador;

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

Abstract

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 (SSC, 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. Ibáñez, G., Valcárcel, M., Cebolla‐Cornejo, J., & Roselló, S. (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), 5140-5148. environments. Food chemistry, 239, pp.148-156. Link to publication: https://doi.org/10.1002/jsfa.9760 Link to repository: http://hdl.handle.net/10234/183409 For more detailed data contact the authors ACKNOWLEDGEMENTS This research was performed despite the lack of direct public funding for its development and thanks to the enthusiasm of the authors. The authors thank Dr Lahoz and Dr Campillo for providing samples of processing tomato. G. Ibañez thanks Universitat Jaume I for funding his pre-doctoral grant (PREDOC/2015/45).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average